U.S. patent application number 14/466741 was filed with the patent office on 2016-02-25 for methods for quantitative genetic analysis of cell free dna.
The applicant listed for this patent is Clearfork Bioscience, Inc.. Invention is credited to CHRISTOPHER D. ARMOUR, LEE P. LIM, CHRISTOPHER K. RAYMOND.
Application Number | 20160053301 14/466741 |
Document ID | / |
Family ID | 55347787 |
Filed Date | 2016-02-25 |
United States Patent
Application |
20160053301 |
Kind Code |
A1 |
RAYMOND; CHRISTOPHER K. ; et
al. |
February 25, 2016 |
METHODS FOR QUANTITATIVE GENETIC ANALYSIS OF CELL FREE DNA
Abstract
The invention provides a method for genetic analysis in
individuals that reveals both the genetic sequences and chromosomal
copy number of targeted and specific genomic loci in a single
assay. The present invention further provides methods for the
sensitive and specific detection of target gene sequences and gene
expression profiles.
Inventors: |
RAYMOND; CHRISTOPHER K.;
(SEATTLE, WA) ; LIM; LEE P.; (KIRKLAND, WA)
; ARMOUR; CHRISTOPHER D.; (KIRKLAND, WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Clearfork Bioscience, Inc. |
Kirkland |
WA |
US |
|
|
Family ID: |
55347787 |
Appl. No.: |
14/466741 |
Filed: |
August 22, 2014 |
Current U.S.
Class: |
506/9 ;
702/20 |
Current CPC
Class: |
C12Q 1/6869 20130101;
G16B 30/00 20190201; C12Q 1/6869 20130101; C12Q 2525/191 20130101;
C12Q 2545/114 20130101; C12Q 2563/159 20130101; G16B 20/00
20190201; G16B 25/00 20190201; C12Q 1/6806 20130101 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68; G06F 19/00 20060101 G06F019/00; G06F 19/28 20060101
G06F019/28; G06F 19/20 20060101 G06F019/20; G06F 19/22 20060101
G06F019/22 |
Claims
1. A method for genetic analysis of cell-free DNA (cfDNA)
comprising: (a) treating cfDNA with one or more end-repair enzymes
to generate end-repaired cfDNA; (b) ligating one or more adaptors
to each end of the end-repaired cfDNA to generate a cfDNA library;
(c) amplifying the cfDNA library to generate cfDNA library clones;
(d) determining the number of genome equivalents in the cfDNA clone
library; and (e) performing a quantitative genetic analysis of one
or more target genetic loci in the cfDNA library clones.
2. The method of claim 1, further comprising isolating cfDNA from a
biological sample of a subject.
3. The method of claim 1, wherein the cfDNA is isolated from a
biological sample selected from the group consisting of: amniotic
fluid, blood, plasma, serum, semen, lymphatic fluid, cerebral
spinal fluid, ocular fluid, urine, saliva, stool, mucous, and
sweat.
4. The method of claim 1, wherein (a) the one or more adaptors
comprise a plurality of adaptor species; (b) the one or more
adaptors each comprise a primer binding site for amplification of
the cfDNA library; (c) the one or more adaptors each comprise one
or more unique read codes; (d) the one or more adaptors each
comprise one or more sample codes for sample multiplexing; or (e)
the one or more adaptors each comprise one or more sequences for
DNA sequencing.
5.-8. (canceled)
9. The method of claim 1, wherein qPCR is performed on the cfDNA
clone library and a qPCR measurement is compared to standards of
known genome equivalents to determine the genome equivalents of the
cfDNA clone library.
10. The method of claim 9, wherein the qPCR is performed with a
primer that binds to an Alu sequence and a primer that binds to a
sequence in an adaptor.
11. The method of claim 1, wherein: (a) the quantitative genetic
analysis is performed on a plurality of genetic loci in the cfDNA
library clones; (b) the quantitative genetic analysis is performed
on a plurality of genetic loci in a plurality of cfDNA clone
libraries; (c) the quantitative genetic analysis comprises
hybridizing one or more capture probes to a target genetic locus to
form capture probe-cfDNA clone complexes; (d) the quantitative
genetic analysis comprises isolating the capture probe-cfDNA clone
complexes; (e) the quantitative genetic analysis comprises
amplification of the cfDNA clone sequence in the isolated
hybridized capture probe-cfDNA clone complexes; or (f) the
quantitative genetic analysis comprises DNA sequencing to generate
a plurality of sequencing reads.
12.-16. (canceled)
17. The method of 11, further comprising bioinformatic analysis of
the plurality of sequencing reads.
18. The method of claim 1, wherein bioinformatics analysis is used:
(a) to quantify the number of genome equivalents analyzed in the
cfDNA clone library; (b) to detect genetic variants in a target
genetic locus; (c) to detect mutations within a target genetic
locus; (d) to detect genetic fusions within a target genetic locus;
and (e) to measure copy number fluctuations within a target genetic
locus.
19. The method of claim 2, wherein: (a) the subject does not have a
genetic disease; (b) the subject has not been diagnosed with a
genetic disease; or (c) the subject has been diagnosed with a
genetic disease.
20.-21. (canceled)
22. The method of claim 19, wherein the quantitative genetic
analysis is used to identify or detect one or more genetic lesions
that cause or associated with the genetic disease.
23. The method of claim 22, wherein the genetic lesion comprises a
nucleotide transition or transversion, a nucleotide insertion or
deletion, a genomic rearrangement, a change in copy number, or a
gene fusion.
24. The method of claim 22, wherein the genetic lesion comprises a
genomic rearrangement that fuses the 3' coding region of the ALK
gene to another gene.
25. The method of claim 24, wherein the 3' coding region of the ALK
gene is fused to the EML4 gene.
26. The method of claim 22, wherein the genetic disease is
cancer.
27. The method of claim 2, wherein the subject is pregnant.
28. The method of claim 27, wherein the quantitative genetic
analysis is used to identify or detect one or more genetic variants
or genetic lesions of one or more target genetic loci in fetal
cfDNA.
29. The method of claim 2, wherein the subject is a transplant
recipient.
30. The method of claim 27, wherein the quantitative genetic
analysis is used to identify or detect donor cfDNA in the
subject.
31. A method of predicting, diagnosing, or monitoring a genetic
disease in a subject comprising: (a) isolating or obtaining cfDNA
from a biological sample of a subject; (b) treating the cfDNA with
one or more end-repair enzymes to generate end-repaired cfDNA; (c)
ligating one or more adaptors to each end of the end-repaired cfDNA
to generate a cfDNA library; (d) amplifying the cfDNA library to
generate a cfDNA clone library; (e) determining the number of
genome equivalents in the cfDNA clone library; and (f) performing a
quantitative genetic analysis of one or more target genetic loci
associated with the genetic disease in the cfDNA clone library,
wherein the identification or detection of one or more genetic
lesions in the one or more target genetic loci is prognostic for,
diagnostic of, or monitors the progression of the genetic
disease.
32. The method of claim 31, wherein the cfDNA is isolated from a
biological sample selected from the group consisting of: amniotic
fluid, blood, plasma, serum, semen, lymphatic fluid, cerebral
spinal fluid, ocular fluid, urine, saliva, stool, mucous, and
sweat.
33. The method of claim 31, wherein the genetic lesion comprises a
nucleotide transition or transversion, a nucleotide insertion or
deletion, a genomic rearrangement, a change in copy number, or a
gene fusion.
34. The method of claim 31, wherein the genetic lesion comprises a
genomic rearrangement that fuses the 3' coding region of the ALK
gene to another gene.
35. The method of claim 32, wherein the 3' coding region of the ALK
gene is fused to the EML4 gene.
36. The method of claim 31, wherein the genetic disease is
cancer.
37. A companion diagnostic for a genetic disease comprising: (a)
isolating or obtaining cfDNA from a biological sample of a subject;
(b) treating the cfDNA with one or more end-repair enzymes to
generate end-repaired cfDNA; (c) ligating one or more adaptors to
each end of the end-repaired cfDNA to generate a cfDNA library; (d)
amplifying the cfDNA library to generate a cfDNA clone library; (e)
determining the number of genome equivalents in the cfDNA clone
library; and (f) performing a quantitative genetic analysis of one
or more biomarkers associated with the genetic disease in the cfDNA
clone library, wherein detection of, or failure to detect, at least
one of the one or more biomarkers indicates whether the subject
should be treated for the genetic disease.
38. The method of claim 37, wherein the cfDNA is isolated from a
biological sample selected from the group consisting of: amniotic
fluid, blood, plasma, serum, semen, lymphatic fluid, cerebral
spinal fluid, ocular fluid, urine, saliva, stool, mucous, and
sweat.
39. The method of claim 37, wherein the biomarker is a genetic
lesion.
40. The method of claim 39, wherein the genetic lesion comprises a
nucleotide transition or transversion, a nucleotide insertion or
deletion, a genomic rearrangement, a change in copy number, or a
gene fusion.
41. The method of claim 39, wherein the genetic lesion comprises a
genomic rearrangement that fuses the 3' coding region of the ALK
gene to another gene.
42. The method of claim 41, wherein the 3' coding region of the ALK
gene is fused to the EML4 gene.
43. The method of claim 37, wherein the genetic disease is cancer.
Description
STATEMENT REGARDING SEQUENCE LISTING
[0001] The Sequence Listing associated with this application is
provided in text format in lieu of a paper copy, and is hereby
incorporated by reference into the specification. The name of the
text file containing the Sequence Listing is
CLFK.sub.--002.sub.--00US_ST25.txt. The text file is 117 KB, was
created on Aug. 22, 2014, and is being submitted electronically via
EFS-Web.
BACKGROUND
[0002] 1. Technical Field
[0003] The invention relates generally to compositions and methods
for the quantitative genetic analysis of cell free DNA (cfDNA). In
particular, the present invention relates to improved targeted
sequence capture compositions and methods for the genetic
characterization and analysis of cfDNA.
[0004] 2. Description of the Related Art
[0005] It is becoming increasing clear that most, if not all, of
the most common human cancers are diseases of the human genome. The
emerging picture is that somatic mutations accumulate during an
individual's lifetime, some of which increase the probability that
the cell in which they are harbored can develop into a tumor
(Vogelstein et al., Science 339(6127): 1546-1558 (2013)). With just
the wrong combination of accumulated mutational events, a
precancerous growth loses constraints that keep uncontrolled
proliferation in check and the resulting cell mass becomes a
cancer. The constellations of mutations that are necessary and
sufficient to cause cancer are often collectively referred to as
"driver mutations." One of the themes that have emerged from recent
and intensive molecular analysis is that cancer, once thought of as
a single, tissue-specific disease, is in fact a group of related
diseases, each with a unique molecular pathology. The human genome
project laid the groundwork for genome-wide analysis of
cancers.
[0006] For example, the introduction of next-generation sequencing
technologies (2004-present) has accelerated the discovery pace of
causal genomic factors that underlie the diagnosis of NSCLC, making
it clear that NSCLC is really a family of related diseases, each of
which may be responsive to a different targeted therapy.
[0007] The art lacks reliable and robust molecular analysis methods
for the analysis of genetic diseases. Traditionally, molecular
diagnostics have consisted of antibody-based tests
(immunohistochemistry), in-situ hybridization with DNA probes
(fluorescence in situ hybridization), and hybridization or
PCR-based tests that query specific nucleotide sequences. Until
recently, DNA sequencing as a molecular diagnostic tool has been
generally limited to the coding exons of one or two genes. While
DNA sequencing has been used in the diagnosis and treatment of
solid cancers, one of the most significant drawbacks of these
methods is that they require direct access to tumor tissues. Such
material is often difficult to obtain from the initial biopsy used
to diagnose the disease and virtually impossible to obtain in
multiple repetitions over time. Similarly, biopsies are not
possible in patients with inaccessible tumors and not practical in
individuals suffering from metastatic disease.
[0008] Thus, the vast potential of molecular diagnostics for
genetic diseases; fetal testing; paternity testing; predicting
response to drug treatment; diagnosing or monitoring a medical
condition; mendelian disorders; genetic mosaicism; pathogen
screening; microbiome profiling; and organ transplant monitoring;
has yet to be realized. To date, existing molecular diagnostics
approaches lack efficient solutions to clone and amplify individual
DNA molecules, as well as solutions to efficiently target
sequencing to specific genomic loci, with sensitivity sufficient to
discriminate true positive test results from false positive signals
that arise during sample processing.
BRIEF SUMMARY
[0009] The invention relates generally to compositions and methods
for improved compositions and methods for the genetic analysis of
cfDNA.
[0010] In various embodiments, a method for genetic analysis of
cell-free DNA (cfDNA) is provided, comprising: treating cfDNA with
one or more end-repair enzymes to generate end-repaired cfDNA;
ligating one or more adaptors to each end of the end-repaired cfDNA
to generate a cfDNA library; amplifying the cfDNA library to
generate cfDNA library clones; determining the number of genome
equivalents in the cfDNA clone library; and performing a
quantitative genetic analysis of one or more target genetic loci in
the cfDNA library clones.
[0011] In a particular embodiment, the method further comprises
isolating cfDNA from a biological sample of a subject.
[0012] In an additional embodiment, the cfDNA is isolated from a
biological sample selected from the group consisting of: amniotic
fluid, blood, plasma, serum, semen, lymphatic fluid, cerebral
spinal fluid, ocular fluid, urine, saliva, stool, mucous, and
sweat.
[0013] In a certain embodiment, the one or more adaptors comprise a
plurality of adaptor species.
[0014] In a particular embodiment, the one or more adaptors each
comprise a primer binding site for amplification of the cfDNA
library.
[0015] In a further embodiment, the one or more adaptors each
comprise one or more unique read codes.
[0016] In an additional embodiment, the one or more adaptors each
comprise one or more sample codes for sample multiplexing.
[0017] In another embodiment, the one or more adaptors each
comprise one or more sequences for DNA sequencing.
[0018] In a particular embodiment, qPCR is performed on the cfDNA
clone library and a qPCR measurement is compared to standards of
known genome equivalents to determine the genome equivalents of the
cfDNA clone library.
[0019] In another particular embodiment, qPCR is performed with a
primer that binds to an Alu sequence and a primer that binds to a
sequence in an adaptor.
[0020] In a certain embodiment, the quantitative genetic analysis
is performed on a plurality of genetic loci in the cfDNA library
clones.
[0021] In a further embodiment, the quantitative genetic analysis
is performed on a plurality of genetic loci in a plurality of cfDNA
clone libraries.
[0022] In an additional embodiment, the quantitative genetic
analysis comprises hybridizing one or more capture probes to a
target genetic locus to form capture probe-cfDNA clone
complexes.
[0023] In a particular embodiment, the quantitative genetic
analysis comprises isolating the capture probe-cfDNA clone
complexes.
[0024] In a certain embodiment, the quantitative genetic analysis
comprises amplification of the cfDNA clone sequence in the isolated
hybridized capture probe-cfDNA clone complexes.
[0025] In a further embodiment, the quantitative genetic analysis
comprises DNA sequencing to generate a plurality of sequencing
reads.
[0026] In another embodiment, the quantitative genetic analysis
comprises bioinformatic analysis of the plurality of sequencing
reads.
[0027] In a particular embodiment, bioinformatics analysis is used:
to quantify the number of genome equivalents analyzed in the cfDNA
clone library; to detect genetic variants in a target genetic
locus; to detect mutations within a target genetic locus; to detect
genetic fusions within a target genetic locus; and to measure copy
number fluctuations within a target genetic locus.
[0028] In an additional embodiment, the subject does not have a
genetic disease.
[0029] In a certain embodiment, the subject has not been diagnosed
with a genetic disease.
[0030] In another certain embodiment, the subject has been
diagnosed with a genetic disease.
[0031] In another embodiment, the quantitative genetic analysis is
used to identify or detect one or more genetic lesions that cause
or associated with the genetic disease.
[0032] In a certain embodiment, the genetic lesion comprises a
nucleotide transition or transversion, a nucleotide insertion or
deletion, a genomic rearrangement, a change in copy number, or a
gene fusion.
[0033] In a particular embodiment, the genetic lesion comprises a
genomic rearrangement that fuses the 3' coding region of the ALK
gene to another gene.
[0034] In a particular embodiment, the 3' coding region of the ALK
gene is fused to the EML4 gene.
[0035] In another embodiment, the genetic disease is cancer.
[0036] In a further embodiment, the subject is pregnant.
[0037] In an additional embodiment, the quantitative genetic
analysis is used to identify or detect one or more genetic variants
or genetic lesions of one or more target genetic loci in fetal
cfDNA.
[0038] In a particular embodiment, the subject is a transplant
recipient.
[0039] In an additional embodiment, the quantitative genetic
analysis is used to identify or detect donor cfDNA in the
subject.
[0040] In various embodiments, a method of predicting, diagnosing,
or monitoring a genetic disease in a subject is provided,
comprising: isolating or obtaining cfDNA from a biological sample
of a subject; treating the cfDNA with one or more end-repair
enzymes to generate end-repaired cfDNA; ligating one or more
adaptors to each end of the end-repaired cfDNA to generate a cfDNA
library; amplifying the cfDNA library to generate a cfDNA clone
library; determining the number of genome equivalents in the cfDNA
clone library; and performing a quantitative genetic analysis of
one or more target genetic loci associated with the genetic disease
in the cfDNA clone library, wherein the identification or detection
of one or more genetic lesions in the one or more target genetic
loci is prognostic for, diagnostic of, or monitors the progression
of the genetic disease.
[0041] In an additional embodiment, the cfDNA is isolated from a
biological sample selected from the group consisting of: amniotic
fluid, blood, plasma, serum, semen, lymphatic fluid, cerebral
spinal fluid, ocular fluid, urine, saliva, stool, mucous, and
sweat.
[0042] In a certain embodiment, the genetic lesion comprises a
nucleotide transition or transversion, a nucleotide insertion or
deletion, a genomic rearrangement, a change in copy number, or a
gene fusion.
[0043] In a particular embodiment, the genetic lesion comprises a
genomic rearrangement that fuses the 3' coding region of the ALK
gene to another gene.
[0044] In a further embodiment, the 3' coding region of the ALK
gene is fused to the EML4 gene.
[0045] In a particular embodiment, the genetic disease is
cancer.
[0046] In various embodiments, a companion diagnostic for a genetic
disease is provided comprising: isolating or obtaining cfDNA from a
biological sample of a subject; treating the cfDNA with one or more
end-repair enzymes to generate end-repaired cfDNA; ligating one or
more adaptors to each end of the end-repaired cfDNA to generate a
cfDNA library; amplifying the cfDNA library to generate a cfDNA
clone library; determining the number of genome equivalents in the
cfDNA clone library; and performing a quantitative genetic analysis
of one or more biomarkers associated with the genetic disease in
the cfDNA clone library, wherein detection of, or failure to
detect, at least one of the one or more biomarkers indicates
whether the subject should be treated for the genetic disease.
[0047] In a particular embodiment, the cfDNA is isolated from a
biological sample selected from the group consisting of: amniotic
fluid, blood, plasma, serum, semen, lymphatic fluid, cerebral
spinal fluid, ocular fluid, urine, saliva, stool, mucous, and
sweat.
[0048] In an additional embodiment, the biomarker is a genetic
lesion.
[0049] In a particular embodiment, the genetic lesion comprises a
nucleotide transition or transversion, a nucleotide insertion or
deletion, a genomic rearrangement, a change in copy number, or a
gene fusion.
[0050] In an additional embodiment, the genetic lesion comprises a
genomic rearrangement that fuses the 3' coding region of the ALK
gene to another gene.
[0051] In a further embodiment, the 3' coding region of the ALK
gene is fused to the EML4 gene.
[0052] In a certain embodiment, the genetic disease is cancer.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0053] FIG. 1 shows the expected versus observed variant
frequencies as a function of admix dilution in the absence of
unique read filtering. In the absence of unique read filtering,
random base changes at these four selected positions occurred with
measurable, non-zero frequencies; thus, demonstrating a lack of
sensitivity to detect the particular single nucleotide variants
(SNV).
[0054] FIG. 2 shows that unique read filtering performed on the
data generated in FIG. 1. The left hand panel shows the data from
FIG. 1 on the BRAF I326T SNV without unique read filtering. The
right hand panel shows that using unique read filtering of the same
data increased the assay sensitivity and allowed the discrimination
of true signal from error-prone noise.
[0055] FIG. 3 shows capture probe performance as a function of
length and wash temperature. The y-axis shows the total number of
reads associated with each capture probe. The bars in the bar chart
are broken into two categories, where open bars correspond to
on-target reads that align to the intended capture probe targets
and solid bars show off-target reads that are associated with a
capture probe but that map to unintended regions of the genome.
Overall, the 40-mer and 60-mer capture probes perform substantially
the same with 44.degree. C. and 47.degree. C. washes. With the
50.degree. C. wash, the 40-mer capture probes perform erratically.
These data validate the use of 40-mer capture probes at wash
temperatures in the range of about 44.degree. C. to about
47.degree. C.
[0056] FIG. 4 shows a schematic for the targeted and oriented
sequencing of intron 19 of the ALK gene. A) In the "wild-type"
reference sequence, antisense-oriented ALK capture probes identify
sequences from intron 19. B) In the case of pathogenic fusion
genes, some ALK capture probes will identify junction sequences
associated with the gene fusion event.
[0057] FIG. 5 shows a schematic for high density capture probe
placement for complete sequencing of target regions. Each capture
probe captures a collection of sequences that provide cumulative
coverage at each base position. Here, coverage is represented by a
line, and the amplitude of the line denotes depth of coverage
derived from a particular capture probe. Overlapping coverage from
adjacent capture probes provides complete sequencing of target
regions in both possible directions. In addition, the head-to-head
placement of opposite strand capture probes ensures that all
capture probe binding sites are sequenced.
[0058] FIG. 6 shows a representative example of the size
distribution of fragmented DNA used in library construction.
[0059] FIG. 7 shows the performance of high-density 40-mer capture
probes in a representative experiment. The y-axis shows the total
number of reads, which are broken out as on-target reads,
off-target reads, and unmappable reads. The x-axis enumerates each
of the 105 capture probes used in this experiment for sequence
capture.
[0060] FIG. 8 shows a representative example of the cumulative
coverage of a target region using high density 40-mer capture
probes. Shown here is the cumulative coverage of TP53 coding
exons.
[0061] FIG. 9A shows a representative example of the size
distribution of cell-free DNA (cfDNA) libraries. The dominant band
is consistent with a collection of 170.+-.10 bp fragments ligated
to 90 bp of adaptors. FIG. 9B shows a published gel image of cfDNA
and a representative cfDNA library generated using the methods
disclosed and/or contemplated herein. The qualitative "ladder"
appearance is conserved in the library, but the library is shifted
to higher mass by the addition of 90 bp of adaptor sequences. FIG.
9C shows a representative example of genomic, plasma-derived cfDNA
libraries from Ovarian cancer patients (OvC) and "healthy donors"
(HD).
[0062] FIG. 10 shows the unique read counts across eight cfDNA
libraries derived from four plasma samples. Fragmentation (frag)
prior to library construction with this sample 23407 increased the
library yield by more than two-fold.
[0063] FIG. 11 shows the representative read coverage of cfDNA
across a region of the TP53 gene. Twenty four 131 bp reads captured
by the
"TP53_NM.sub.--000546_chr17:7579351:region.sub.--3:280nt:41:80:r"
capture probe (SEQ ID NO:201) were chosen at random and aligned
using the BLAT algorithm within the UCSC genome browser. Twenty one
reads map to the target region, and they do so in a pattern of
overlapping coverage. The probe used to capture these reads is
marked with an arrow.
[0064] FIG. 12 shows an overview of targeted DNA sequencing of the
coding regions of the TP53 gene from a cfDNA genomic library. The
coverage (horizontal axis) extends across all 10 coding regions and
includes intronic regions involved in mRNA splicing. The sequencing
depth (vertical axis) reaches a maximum of 4851 and is uniform
across all coding exons.
[0065] FIG. 13 shows a plot of unique read counts versus qPCR
estimated genome equivalents in an ACA2-based assay. qPCR
measurements are shown on the X-axis versus read counts on the
Y-axis. Perfect agreement between these measurements is shown as
the diagonal. There is very poor, if any, correlation between
measurements, especially at lower genomic inputs. These data show
that the ACA2-based qPCR assay chronically underestimates library
complexity and is inadequate for measuring genome equivalents.
[0066] FIG. 14 shows a schematic of the core elements of a qPCR
genome equivalent measurement assay that couples an genomic repeat
specific primer (e.g., Alu) and a long adaptor-specific primer. (A)
Standard library amplification using a single, 25 nt primer named
ACA2 (primer 1). (B) Longer, 58 nt versions of the ACA2 primer
(primer 2) do not amplify genomic libraries because of stem-loop
suppression. (C) Forward and reverse primers directed to a
consensus human Alu repeat element (primers 3 and 4) recognize
1000's of loci and readily amplify genomic DNA. (D) A single Alu
primer alone, either forward or reverse (primer 3 or primer 4),
coupled with the long ACA2 primer (primer 2) do not amplify genomic
DNA. (E) The same primer pair as in (D) readily amplifies genomic
cfDNA library clones that contain Alu sequences.
[0067] FIG. 15 shows proof-of-concept data for an Alu plus
adaptor-based qPCR assay of genome equivalents. (A) Amplification
of 10 pg of a standard genomic library with various PCR primers.
The x-axis specifies PCR primers used for amplification and the
Y-axis (log scale) indicates the PCR signal measured in units of
fg/.mu.L. The standard ACA2 primer produced a strong signal, as
expected. The ACA2 long primer failed to produce signal owing to
PCR suppression. The two Alu primer pairs both produced signal at
1% the amount of ACA2, suggesting that 1% of clones possess an
amplifiable Alu sequence. The combination of any Alu primer with
the long ACA2 primer also produced signal in .about.1% of clones.
(B) Validation against 10 pg of genomic DNA (left four samples) or
10 pg of library DNA (right four clones). Alu primer pairs amplify
comparable signal from genomic DNA or a genomic library. In
contrast, primer pairs consisting of an Alu primer and a long ACA2
primer amplify genomic DNA poorly (L+A1F) or not at all (L+A1R).
These same pairs exhibit amplification of library that slightly
exceeds the signal from Alu primer pairs.
[0068] FIG. 16 shows a direct comparison of ACA2 primer qPCR assay
with the Alu-ACA2 long-primer qPCR assay. The Alu ACA2 long-primer
qPCR assay shows an 8-fold increase in detectable genome
equivalents, which is more consistent with unique read counts
derived from sequencing data.
[0069] FIG. 17 shows a representative example of adaptor structure
and function for high sensitivity, quantitative genetic assays that
provide accurate determinations of genome equivalents analyzed. (A)
Fine structure of the adaptor ligation strand. Details relating to
each numbered element are provided in Example 4. (B) The duplex
formed between 45 nt ligation strands and 12 nt partner oligo
strand creates a blunt-end ligation substrate compatible with
end-repaired cfDNA fragments (solid bars). (C) Following ligation,
the complement to the ligation strand is created by a DNA
polymerase-mediated fill-in reaction.
[0070] FIG. 18 shows a representative example of the size
distribution of two DNA samples (NA06994 & NCI-H2228) processed
to mimic cfDNA.
[0071] FIG. 19 shows a representative example of the sensitivity of
detection of the TP53 point mutation Q331* in tumor sample DNA
(H2228) admixed with normal genomic DNA (N). The most sensitive
detection corresponds to .about.1 mutant copy of TP53 among 1000
normal copies of the gene.
[0072] FIG. 20 shows the precise determination of the junction
sequence for the EML4-ALK fusion gene harbored in cell line
NCI-H2228 using the compositions and methods contemplated
herein.
[0073] FIG. 21 shows the detection of the EML4-ALK fusion gene
tumor sample DNA (H2228) admixed with normal genomic DNA (N).
Because the fusion is present as a heterozygote in the NCI-H2228
cell line, the most sensitive detection corresponds to one gene
fusion among .about.100 normal chromosomal copies of the ALK gene
(50 genome equivalents).
[0074] FIG. 22 shows the detection of the MYCN gene amplification
in admixtures of cell line NCI-H69 (H69) diluted into normal human
DNA (N). The threshold value of two normal diploid copies is shown
as a dashed red line.
[0075] FIG. 23 shows the DNA mutations detected in the TP53 gene of
three different cancer patients. The canonical gene model is shown
at the top of the figure. The peaks represent DNA sequence coverage
(X-axis) and depth (Y-axis). Sequencing depth was >4000 genome
equivalents for all sample analyzed. An expanded view of exon 7
below the gene model shows where all detected mutations were
localized. The frequency of mutant detection in cfDNA (plasma),
tumor tissue, and normal adjacent tissue is shown, where available
(NA--not available). OVA1 and OVA2 are ovarian cancer patients;
CRC406 and CRC407 are colorectal cancer patients. No mutations in
TP53 were found in any of the OVA1 samples.
[0076] FIG. 24 shows the DNA sequencing of a larger, thirteen gene
panel (boxed). The sequencing identified a KRAS mutation in cfDNA
and tumor from ovarian cancer patient OVA1.
[0077] FIG. 25 shows the DNA sequencing of a larger, twelve gene
panel. The sequencing identified an ERBB2 gene amplification in the
plasma of colorectal cancer patient CRC407.
DETAILED DESCRIPTION
A. Overview
[0078] The present invention contemplates, in part, compositions
and methods for the quantitative genetic analysis of the genetic
state of an individual using cell-free DNA (cfDNA). As used herein,
the term "genetic state" refers to the sequence of one or more
target genome sequences in the genome in relation to a non-causal
normal sequence or in relation to a sequence that is causal for a
genetic condition or disease. In one embodiment, analyzing the
genetic state refers to identifying, quantifying, or monitoring a
genetic variant in a target genetic locus, wherein the variant
varies with respect to a reference sequence (e.g., a normal or
mutated sequence). The present inventors have provided solutions to
the molecular diagnostic problems of genetic conditions or diseases
associated with lack of sensitivity to discriminate true positives
from false positives, inefficient cloning and amplification of
individual DNA molecules, and inefficient targeted sequencing to
specific genomic loci. The solutions contemplated herein comprise
compositions and methods for reliable and robust quantitative
genetic analysis with sensitivity sufficient to discriminate true
positive test results from false positive signals that arise during
sample processing.
[0079] Next-generation sequencing technology has afforded the
opportunity to add broad genomic surveys to molecular diagnosis in
a variety of scenarios including cancers, fetal diagnostics,
paternity testing, pathogen screening and organ transplant
monitoring. In the context of genetic diseases, next-generation
sequencing information is being used in a clinical setting to
identify mutations within genes that are likely to alter gene
function, to identify the gain or loss of genetic material within
cells, and to identify genomic rearrangements that are not found in
normal, healthy cells. The results of these broad diagnostic
surveys are often used to guide patient treatment.
[0080] However, the potential benefits of DNA sequencing in
diagnosis and treatment of the genetic state of an individual or
genetic conditions or diseases is outweighed by the need to
directly access affected tissues to obtain samples. Such material
is often difficult to obtain from the initial biopsy used to
diagnose the disease and virtually impossible to obtain in multiple
repetitions over time. Similarly, in cancer patients, biopsies are
not possible in patients with inaccessible tumors and not practical
in individuals suffering from metastatic disease. In contrast, the
present inventors' approach derives from the fact that all tissues
require access to the vasculature to survive and as a consequence
these masses deposit DNA into bodily fluids. One major depot of
bodily fluid in which the DNA of diseased cells is found is the
plasma of human blood.
[0081] In contrast to testing methods that rely on shallow,
genome-wide sequence coverage, molecular diagnostics contemplated
herein for the genetic state of an individual; genetic diseases;
mendelian disorders; genetic mosaicism; fetal testing; paternity
testing; predicting response to drug treatment; diagnosing or
monitoring a medical condition; pathogen screening; microbiome
profiling; and organ transplant monitoring leverage the
availability of cfDNA to provide deep sequence coverage of select
target genes. In addition, the cfDNA-based cancer diagnostics
contemplated herein possess the ability to detect a variety of
genetic changes including somatic sequence variations that alter
protein function, large-scale chromosomal rearrangements that
create chimeric gene fusions, and copy number variation that
includes loss or gain of gene copies. Using the contemplated
compositions and methods, these changes are detectable and
quantifiable in the face of significant dilution, or admixture, of
normal sequences within cfDNA that are contributed by the normal
turnover processes that happen within healthy tissues. The
compositions and methods contemplated herein also successfully
address the major challenges associated with detecting rare genetic
changes causal of disease; namely, that cfDNA is highly fragmented,
that cfDNA levels vary substantially between different individuals,
and that the degree of admixture of diseased versus normal
sequences is highly variable among patients, even within
individuals suffering from the same molecular disease and
stage.
[0082] In various embodiments, compositions and methods for genetic
analysis of comprise interrogating the DNA fraction within
biological fluid samples and stool samples. The methods
contemplated herein provide a novel comprehensive framework address
molecular genetic analysis using cfDNA available from a variety of
biological sources. Cloning of purified cfDNA introduces tagged
cfDNA sequences that inform downstream analysis and enable
amplification of the resulting clone libraries. Hybrid capture with
target specific oligonucleotides is used to retrieve specific
sequences for subsequent analysis. Independent measurements of the
number of genomes present in the library are applied to each
sample, and these assays provide a means to estimate the assay's
sensitivity. The assays contemplated herein provide reliable,
reproducible, and robust methods for the analysis, detection,
diagnosis, or monitoring of genetic states, conditions, or
disease.
[0083] The practice of particular embodiments of the invention will
employ, unless indicated specifically to the contrary, conventional
methods of chemistry, biochemistry, organic chemistry, molecular
biology, microbiology, recombinant DNA techniques, genetics,
immunology, and cell biology that are within the skill of the art,
many of which are described below for the purpose of illustration.
Such techniques are explained fully in the literature. See, e.g.,
Sambrook, et al., Molecular Cloning: A Laboratory Manual (3rd
Edition, 2001); Sambrook, et al., Molecular Cloning: A Laboratory
Manual (2nd Edition, 1989); Maniatis et al., Molecular Cloning: A
Laboratory Manual (1982); Ausubel et al., Current Protocols in
Molecular Biology (John Wiley and Sons, updated July 2008); Short
Protocols in Molecular Biology: A Compendium of Methods from
Current Protocols in Molecular Biology, Greene Pub. Associates and
Wiley-Interscience; Glover, DNA Cloning: A Practical Approach, vol.
I & II (IRL Press, Oxford, 1985); Anand, Techniques for the
Analysis of Complex Genomes, (Academic Press, New York, 1992);
Transcription and Translation (B. Hames & S. Higgins, Eds.,
1984); Perbal, A Practical Guide to Molecular Cloning (1984); and
Harlow and Lane, Antibodies, (Cold Spring Harbor Laboratory Press,
Cold Spring Harbor, N.Y., 1998).
B. Definitions
[0084] Unless defined otherwise, all technical and scientific terms
used herein have the same meaning as commonly understood by those
of ordinary skill in the art to which the invention belongs.
Although any methods and materials similar or equivalent to those
described herein can be used in the practice or testing of the
present invention, preferred embodiments of compositions, methods
and materials are described herein. For the purposes of the present
invention, the following terms are defined below.
[0085] The articles "a," "an," and "the" are used herein to refer
to one or to more than one (i.e. to at least one) of the
grammatical object of the article. By way of example, "an element"
means one element or more than one element.
[0086] The use of the alternative (e.g., "or") should be understood
to mean either one, both, or any combination thereof of the
alternatives.
[0087] The term "and/or" should be understood to mean either one,
or both of the alternatives.
[0088] As used herein, the term "about" or "approximately" refers
to a quantity, level, value, number, frequency, percentage,
dimension, size, amount, weight or length that varies by as much as
15%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2% or 1% to a reference
quantity, level, value, number, frequency, percentage, dimension,
size, amount, weight or length. In one embodiment, the term "about"
or "approximately" refers a range of quantity, level, value,
number, frequency, percentage, dimension, size, amount, weight or
length.+-.15%, .+-.10%, .+-.9%, .+-.8%, .+-.7%, .+-.6%, .+-.5%,
.+-.4%, .+-.3%, .+-.2%, or .+-.1% about a reference quantity,
level, value, number, frequency, percentage, dimension, size,
amount, weight or length.
[0089] Throughout this specification, unless the context requires
otherwise, the words "comprise", "comprises" and "comprising" will
be understood to imply the inclusion of a stated step or element or
group of steps or elements but not the exclusion of any other step
or element or group of steps or elements. In particular
embodiments, the terms "include," "has," "contains," and "comprise"
are used synonymously.
[0090] By "consisting of" is meant including, and limited to,
whatever follows the phrase "consisting of." Thus, the phrase
"consisting of" indicates that the listed elements are required or
mandatory, and that no other elements may be present.
[0091] By "consisting essentially of" is meant including any
elements listed after the phrase, and limited to other elements
that do not interfere with or contribute to the activity or action
specified in the disclosure for the listed elements. Thus, the
phrase "consisting essentially of" indicates that the listed
elements are required or mandatory, but that no other elements are
optional and may or may not be present depending upon whether or
not they affect the activity or action of the listed elements.
[0092] Reference throughout this specification to "one embodiment,"
"an embodiment," "a particular embodiment," "a related embodiment,"
"a certain embodiment," "an additional embodiment," or "a further
embodiment" or combinations thereof means that a particular
feature, structure or characteristic described in connection with
the embodiment is included in at least one embodiment of the
present invention. Thus, the appearances of the foregoing phrases
in various places throughout this specification are not necessarily
all referring to the same embodiment. Furthermore, the particular
features, structures, or characteristics may be combined in any
suitable manner in one or more embodiments.
[0093] As used herein, the term "isolated" means material that is
substantially or essentially free from components that normally
accompany it in its native state. In particular embodiments, the
term "obtained" or "derived" is used synonymously with
isolated.
[0094] As used herein, the term "DNA" refers to deoxyribonucleic
acid. In various embodiments, the term DNA refers to genomic DNA,
recombinant DNA, synthetic DNA, or cDNA. In one embodiment, DNA
refers to genomic DNA or cDNA. In particular embodiments, the DNA
comprises a "target region." DNA libraries contemplated herein
include genomic DNA libraries and cDNA libraries constructed from
RNA, e.g., an RNA expression library. In various embodiments, the
DNA libraries comprise one or more additional DNA sequences and/or
tags.
[0095] A "target genetic locus" or "DNA target region" refers to a
region of interest within a DNA sequence. In various embodiments,
targeted genetic analyses are performed on the target genetic
locus. In particular embodiments, the DNA target region is a region
of a gene that is associated with a particular genetic state,
genetic condition, genetic diseases; fetal testing; genetic
mosaicism, paternity testing; predicting response to drug
treatment; diagnosing or monitoring a medical condition; microbiome
profiling; pathogen screening; or organ transplant monitoring.
[0096] As used herein, the terms "circulating DNA," "circulating
cell-free DNA" and "cell-free DNA" are often used interchangeably
and refer to DNA that is extracellular DNA, DNA that has been
extruded from cells, or DNA that has been released from necrotic or
apoptotic cells.
[0097] A "subject," "individual," or "patient" as used herein,
includes any animal that exhibits a symptom of a condition that can
be detected or identified with compositions contemplated herein.
Suitable subjects include laboratory animals (such as mouse, rat,
rabbit, or guinea pig), farm animals (such as horses, cows, sheep,
pigs), and domestic animals or pets (such as a cat or dog). In
particular embodiments, the subject is a mammal. In certain
embodiments, the subject is a non-human primate and, in preferred
embodiments, the subject is a human.
C. Methods of Genetic Analysis of Cell Free DNA
[0098] In various embodiments, a method for genetic analysis of
cfDNA is provided.
[0099] In particular embodiments, a method for genetic analysis of
cfDNA comprises: generating and amplifying a cfDNA library,
determining the number of genome equivalents in the cfDNA library;
and performing a quantitative genetic analysis of one or more
genomic target loci.
[0100] A method for genetic analysis of cfDNA comprises treating
cfDNA with one or more end-repair enzymes to generate end-repaired
cfDNA and ligating one or more adaptors to each end of the
end-repaired cfDNA to generate a cfDNA library; amplifying the
cfDNA library to generate cfDNA library clones; determining the
number of genome equivalents of cfDNA library clones; and
performing a quantitative genetic analysis of one or more target
genetic loci in the cfDNA library clones.
[0101] 1. Generating a cfDNA Library
[0102] In particular embodiments, methods of genetic analysis
contemplated herein comprise generating a cfDNA library comprising
treating cfDNA with one or more end-repair enzymes to generate
end-repaired cfDNA and ligating one or more adaptors to each end of
the end-repaired cfDNA to generate the cfDNA library.
[0103] (a) Cell-Free DNA (cfDNA)
[0104] The methods and compositions contemplated herein are
designed to efficiently analyze, detect, diagnose, and/or monitor
genetic states, genetic conditions, genetic diseases, genetic
mosaicism, fetal diagnostics, paternity testing, microbiome
profiling, pathogen screening, and organ transplant monitoring
using cell-free DNA (cfDNA) as an analyte. The size distribution of
cfDNA ranges from about 150 bp to about 180 bp fragments.
Fragmentation may be the result of endonucleolytic and/or
exonucleolytic activity and presents a formidable challenge to the
accurate, reliable, and robust analysis of cfDNA. Another challenge
for analyzing cfDNA is its short half-life in the blood stream, on
the order of about 15 minutes. Without wishing to be bound to any
particular theory, the present invention contemplates, in part,
that analysis of cfDNA is like a "liquid biopsy" and is a real-time
snapshot of current biological processes.
[0105] Moreover, because cfDNA is not found within cells and may be
obtained from a number of suitable sources including, but not
limited to, biological fluids and stool samples, it is not subject
to the existing limitations that plague next generation sequencing
analysis, such as direct access to the tissues being analyzed.
[0106] Illustrative examples of biological fluids that are suitable
sources from which to isolate cfDNA in particular embodiments
include, but are not limited to amniotic fluid, blood, plasma,
serum, semen, lymphatic fluid, cerebral spinal fluid, ocular fluid,
urine, saliva, mucous, and sweat.
[0107] In particular embodiments, the biological fluid is blood or
blood plasma.
[0108] In certain embodiments, commercially available kits and
other methods known to the skilled artisan can used to isolate
cfDNA directly from the biological fluids of a patient or from a
previously obtained and optionally stabilized biological sample,
e.g., by freezing and/or addition of enzyme chelating agents
including, but not limited to EDTA, EGTA, or other chelating agents
specific for divalent cations.
[0109] (b) Generating End-Repaired cfDNA
[0110] In particular embodiments, generating a cfDNA library
comprises the end-repair of isolated cfDNA. The fragmented cfDNA is
processed by end-repair enzymes to generate end-repaired cfDNA with
blunt ends, 5'-overhangs, or 3'-overhangs. In some embodiments, the
end-repair enzymes can yield for example. In some embodiments, the
end-repaired cfDNA contains blunt ends. In some embodiments, the
end-repaired cfDNA is processed to contain blunt ends. In some
embodiments, the blunt ends of the end-repaired cfDNA are further
modified to contain a single base pair overhang. In some
embodiments, end-repaired cfDNA containing blunt ends can be
further processed to contain adenine (A)/thymine (T) overhang. In
some embodiments, end-repaired cfDNA containing blunt ends can be
further processed to contain adenine (A)/thymine (T) overhang as
the single base pair overhang. In some embodiments, the
end-repaired cfDNA has non-templated 3' overhangs. In some
embodiments, the end-repaired cfDNA is processed to contain 3'
overhangs. In some embodiments, the end-repaired cfDNA is processed
with terminal transferase (TdT) to contain 3' overhangs. In some
embodiments, a G-tail can be added by TdT. In some embodiments, the
end-repaired cfDNA is processed to contain overhang ends using
partial digestion with any known restriction enzymes (e.g., with
the enzyme Sau3A, and the like.
[0111] (c) Ligating Adaptor Molecules to End-Repaired cfDNA
[0112] In particular embodiments, generating a cfDNA library
comprises ligating one or more adaptors to each end of the
end-repaired cfDNA. The present invention contemplates, in part, an
adaptor module designed to accommodate large numbers of genome
equivalents in cfDNA libraries. Adaptor modules are configured to
measure the number of genome equivalents present in cfDNA
libraries, and, by extension, the sensitivity of sequencing assays
used to identify sequence mutations.
[0113] As used herein, the term "adaptor module" refers to a
polynucleotide comprising at least five elements: (i) a first
element comprising a PCR primer binding site for the single-primer
library amplification; (ii) a second element comprising a 5
nucleotide read code that acts to uniquely identified each
sequencing read; (iii) a third element comprising a 3 nucleotide
sample code to identify different samples and enable sample
multiplexing within a sequencing run; (iv) a fourth element
comprising a 12 nucleotide anchor sequence that enables calibration
of proper base calls in sequencing reads and acts as an anchor for
hybridization to a partner oligonucleotide; and (v) a fifth element
comprising the two 3' terminal nucleotides of Element 4 (FIG. 17
and Tables 12-16). The adaptor module is hybridized to a partner
oligonucleotide that is complementary to Element 4 to form an
adaptor suitable for ligating to the ends of cfDNA, optionally
end-repaired blunt-ended cfDNA.
[0114] In particular embodiments, an adaptor module comprises one
or more PCR primer sequences, one or more read codes, one or more
sample codes, one or more anchor sequences, and two or more 3'
nucleotides that are efficient ligation substrates. In additional
embodiments, the adaptor module further comprises one or more
sequencing primer binding sites.
[0115] In particular embodiments, an adaptor module comprises a
first element that comprises one or more PCR primer binding
sequences for single-primer amplification of a cfDNA library. In
one embodiment, the PCR primer binding sequence is about 12 to
about 40 nucleotides, about 18 to about 40 nucleotides, about 20 to
about 35 nucleotides, or about 20 to about 30 nucleotides. In
another embodiment, the PCR primer binding sequence is about 12
nucleotides, about 13 nucleotides, about 14 nucleotides, about 15
nucleotides, about 16 nucleotides, about 17 nucleotides, about 18
nucleotides, about 19 nucleotides, about 20 nucleotides, about 21
nucleotides, about 22 nucleotides, about 23 nucleotides, about 24
nucleotides, about 25 nucleotides, about 26 nucleotides, about 27
nucleotides, about 28 nucleotides, about 29 nucleotides, about 30
nucleotides, about 31 nucleotides, about 32 nucleotides, about 33
nucleotides, about 34 nucleotides, about 35 nucleotides, about 36
nucleotides, about 37 nucleotides, about 38 nucleotides, about 39
nucleotides, or about 40 nucleotides or more.
[0116] In one embodiment, the PCR primer binding sequence is about
25 nucleotides.
[0117] In particular embodiments, an adaptor module comprises a
second element that comprises one or more read code sequences. As
used herein, the term "read code" refers to a polynucleotide that
is used to identify unique sequencing reads. In one embodiment, the
read code is a random sequence of nucleotides. In one embodiment,
the read code is about 1 nucleotide, about 2 nucleotides, about 3
nucleotides, about 4 nucleotides, about 5 nucleotides, about 6
nucleotides, about 7 nucleotides, about 8 nucleotides, about 9
nucleotides, about 10 nucleotides, or more.
[0118] By way of a non-limiting example, a 5 nucleotide codes
consists of 256 possible unique sequences where each code chosen is
2 nucleotides different from every other code in the set. This
feature enables unique and distinct reads to be differentiated from
reads that appear to be unique owing to a sequencing error in the
code region. In particular embodiments, codes that have been
empirically determined to interfere with adaptor function, owing to
particular sequence combinations, may be excluded from use, e.g.,
seven codes of the 256 had an overrepresentation of G nucleotides
and were excluded.
[0119] In other embodiments, each read code of 5, 6, 7, 8, 9, 10 or
more nucleotides may differ by 2, 3, 4, or 5 nucleotides from every
other read code.
[0120] In one embodiment, the read code is about 5 nucleotides and
differs from every other read code by 2 nucleotides.
[0121] In particular embodiments, an adaptor module comprises a
third element that comprises one or more sample code sequences. As
used herein, the term "sample code" refers to a polynucleotide that
is used to identify the sample. The sample code is also useful in
establishing multiplex sequencing reactions because each sample
code is unique to the sample and thus, can be used to identify a
read from a particular sample within a multiplexed sequencing
reaction.
[0122] In one embodiment, the sample code comprises sequence that
is about 1, about 2 nucleotides, about 3 nucleotides, about 4
nucleotides, or about 5 nucleotides, or more. In another
embodiment, each sample code of 2, 3, 4, 5 or more nucleotides may
differ from every other sample code by 2, 3, 4, or 5
nucleotides.
[0123] In one embodiment, the sample code is about three
nucleotides and differs from every other sample code used in other
samples by two nucleotides.
[0124] In particular embodiments, an adaptor module comprises a
fourth element that comprises one or more anchor sequences. As used
herein, an "anchor sequence" refers to a nucleotide sequence of at
least 8 nucleotides, at least 10 nucleotides, at least 12
nucleotides, at least 14 nucleotides, or at least 16 nucleotides
that hybridizes to a partner oligonucleotide and that comprises the
following three properties: (1) each anchor sequence is part of a
family of four anchor sequences that collectively represent each of
the four possible DNA bases at each site within extension; this
feature, balanced base representation, is useful to calibrate
proper base calling in sequencing reads in particular embodiments;
(2) each anchor sequence is composed of only two of four possible
bases, and these are specifically chosen to be either and equal
number of A+C or an equal number of G+T; an anchor sequence formed
from only two bases reduces the possibility that the anchor
sequence will participate in secondary structure formation that
would preclude proper adaptor function; and (3) because each anchor
sequence is composed of equal numbers of A+C or G+T, each anchor
sequence shares roughly the same melting temperature and duplex
stability as every other anchor sequence in a set of four.
[0125] In particular embodiments, an adaptor module comprises a
fifth element that is comprised of the two 3' terminal nucleotides
of Element 4. These two bases at the 3' end of each anchor are
chosen based on an empirical determination that shows that these
two nucleotides are efficient substrates for ligation to the cfDNA.
In particular embodiments, Element 5 comprises the sequences
selected from the group consisting of: AA, CC, TT and GG. In
particular embodiments, Element 5 does not comprise the
dinucleotide combination CG or TG as the inventors have determined
that these combinations are not efficient ligation substrates.
[0126] In particular embodiments, a ligation step comprises
ligating an adaptor module to the end-repaired cfDNA to generate a
"tagged" cfDNA library. In some embodiments, a single adaptor
module is employed. In some embodiments, two, three, four or five
adaptor modules are employed. In some embodiments, an adaptor
module of identical sequence is ligated to each end of the
fragmented end-repaired DNA.
[0127] In one embodiment, a plurality of adaptor species is ligated
to an end-repaired cfDNA library. Each of the plurality of adaptors
may comprise one or more primer binding site for amplification of
the cfDNA library, one or more read code sequences, one or more
sequences for sample multiplexing, and one or more sequences for
DNA sequencing.
[0128] Ligation of one or more adaptors contemplated herein may be
carried out by methods known to those of ordinary skill in the art.
In particular embodiments, one or more adaptors contemplated herein
are ligated to end-repaired cfDNA that comprises blunt ends. In
certain embodiments, one or more adaptors contemplated herein are
ligated to end-repaired cfDNA that comprises complementary ends
appropriate for the ligation method employed. In certain
embodiments, one or more adaptors contemplated herein are ligated
to end-repaired cfDNA that comprises a 3' overhang.
[0129] 2. cfDNA Library Amplification
[0130] In particular embodiments, methods of genetic analysis
contemplated herein comprise amplification of a cfDNA library to
generate a cfDNA clone library or a library of cfDNA clones. Each
molecule of the cfDNA library comprises an adaptor ligated to each
end of an end-repaired cfDNA, and each adaptor comprises one or
more PCR primer binding sites. In one embodiment, different
adaptors are ligated to different ends of the end-repaired
cfDNA.
[0131] In a preferred embodiment, the same adaptor is ligated to
both ends of the cfDNA. Ligation of the same adaptor to both ends
of end-repaired cfDNA allows for PCR amplification with a single
primer sequence. In particular embodiments, a portion of the
adaptor ligated-cfDNA library will be amplified using standard PCR
techniques with a single primer sequence driving amplification. In
one embodiment, the single primer sequence is about 25 nucleotides,
optionally with a projected Tm of .gtoreq.55.degree. C. under
standard ionic strength conditions.
[0132] In particular embodiments, picograms of the initial cfDNA
library are amplified into micrograms of cfDNA clones, implying a
10,000-fold amplification. The amount of amplified product can be
measured using methods known in the art, e.g., quantification on a
Qubit 2.0 or Nanodrop instrument.
[0133] 3. Determining the Number of Genome Equivalents
[0134] In various embodiments, a method for genetic analysis of
cfDNA comprises determining the number of genome equivalents in the
cfDNA clone library. As used herein, the term "genome equivalent"
refers to the number of genome copies in each library. An important
challenge met by the compositions and methods contemplated herein
is achieving sufficient assay sensitivity to detect and analysis
rare genetic mutations or differences in genetic sequence. To
determine assay sensitivity value on a sample-by-sample basis, the
numbers of different and distinct sequences that are present in
each sample are measured, by measuring the number of genome
equivalents that are present in a sequencing library. To establish
sensitivity, the number of genome equivalents must be measured for
each sample library.
[0135] The number of genome equivalents can be determined by qPCR
assay or by using bioinformatics-based counting after sequencing is
performed. In the process flow of clinical samples, qPCR
measurement of genome equivalents is used as a QC step for cfDNA
libraries. It establishes an expectation for assay sensitivity
prior to sequence analysis and allows a sample to be excluded from
analysis if its corresponding cfDNA clone library lacks the
required depth of genome equivalents. Ultimately, the
bioinformatics-based counting of genome equivalents is also used to
identify the genome equivalents--and hence the assay sensitivity
and false negative estimates--for each given cfDNA clone
library.
[0136] The empirical qPCR assay and statistical counting assays
should be well correlated. In cases where sequencing fails to
reveal the sequence depth in a cfDNA clone library, reprocessing of
the cfDNA clone library and/or additional sequencing may be
required.
[0137] In one embodiment, the genome equivalents in a cfDNA clone
library are determined using a quantitative PCR (qPCR) assay. In a
particular embodiment, a standard library of known concentration is
used to construct a standard curve and the measurements from the
qPCR assay are fit to the resulting standard curve and a value for
genome equivalents is derived from the fit. Surprisingly, the
present inventors have discovered that a qPCR "repeat-based" assay
comprising one primer that specifically hybridizes to a common
sequence in the genome, e.g., a repeat sequence, and another primer
that binds to the primer binding site in the adaptor, measured an
8-fold increase in genome equivalents compared to methods using
just the adaptor specific primer (present on both ends of the cfDNA
clone). The number of genome equivalents measured by the
repeat-based assays provides a more consistent library-to-library
performance and a better alignment between qPCR estimates of genome
equivalents and bioinformatically counted tag equivalents in
sequencing runs.
[0138] Illustrative examples of repeats suitable for use in the
repeat-based genome equivalent assays contemplated herein include,
but not limited to: short interspersed nuclear elements (SINEs),
e.g., Alu repeats; long interspersed nuclear elements (LINEs),
e.g., LINE1, LINE2, LINE3; microsatellite repeat elements, e.g.,
short tandem repeats (STRs), simple sequence repeats (SSRs); and
mammalian-wide interspersed repeats (MIRs).
[0139] In one embodiment, the repeat is an Alu repeat.
[0140] 4. Quantitative Genetic Analysis
[0141] In various embodiments, a method for genetic analysis of
cfDNA comprises quantitative genetic analysis of one or more target
genetic loci of the cfDNA library clones. Quantitative genetic
analysis comprises one or more of, or all of, the following steps:
capturing cfDNA clones comprising a target genetic locus;
amplification of the captured targeted genetic locus; sequencing of
the amplified captured targeted genetic locus; and bioinformatic
analysis of the resulting sequence reads.
[0142] (a) Capture of Target Genetic Locus
[0143] The present invention contemplates, in part, a capture probe
module designed to retain the efficiency and reliability of larger
probes but that minimizes uninformative sequence generation in a
cfDNA clone library. A "capture probe module" refers to a
polynucleotide that comprises a capture probe sequence and a tail
sequence. In particular embodiments, the capture probe module
sequence or a portion thereof serves as a primer binding site for
one or more sequencing primers.
[0144] In particular embodiments, a capture probe module comprises
a capture probe. As used herein a "capture probe" refers to a
region capable of hybridizing to a specific DNA target region.
Because the average size of cfDNA is about 150 to about 170 bp and
is highly fragmented the compositions and methods contemplated
herein comprise the use of high density and relatively short
capture probes to interrogate DNA target regions of interest.
[0145] One particular concern with using high density capture
probes is that generally capture probes are designed using specific
"sequence rules." For example, regions of redundant sequence or
that exhibit extreme base composition biases are generally excluded
in designing capture probes. However, the present inventors have
discovered that the lack of flexibility in capture probe design
rules does not substantially impact probe performance. In contrast,
capture probes chosen strictly by positional constraint provided
on-target sequence information; exhibit very little off-target and
unmappable read capture; and yield uniform, useful, on-target reads
with only few exceptions. Moreover, the high redundancy at close
probe spacing more than compensates for occasional poor-performing
capture probes.
[0146] In particular embodiments, a target region is targeted by a
plurality of capture probes, wherein any two or more capture probes
are designed to bind to the target region within 10 nucleotides of
each other, within 15 nucleotides of each other, within 20
nucleotides of each other, within 25 nucleotides of each other,
within 30 nucleotides of each other, within 35 nucleotides of each
other, within 40 nucleotides of each other, within 45 nucleotides
of each other, or within 50 nucleotides or more of each other, as
well as all intervening nucleotide lengths.
[0147] In one embodiment, the capture probe is about 25
nucleotides, about 26 nucleotides, about 27 nucleotides, about 28
nucleotides, about 29 nucleotides, about 30 nucleotides, about 31
nucleotides, about 32 nucleotides, about 33 nucleotides, about 34
nucleotides, about 35 nucleotides, about 36 nucleotides, about 37
nucleotides, about 38 nucleotides, about 39 nucleotides, about 40
nucleotides, about 41 nucleotides, about 42 nucleotides, about 43
nucleotides, about 44 nucleotides, or about 45 nucleotides.
[0148] In one embodiment, the capture probe is about 100
nucleotides, about 200 nucleotides, about 300 nucleotides, about
400 nucleotides, or about 100 nucleotides. In another embodiment,
the capture probe is from about 100 nucleotides to about 500
nucleotides, about 200 nucleotides to about 500 nucleotides, about
300 nucleotides to about 500 nucleotides, or about 400 nucleotides
to about 500 nucleotides, or any intervening range thereof.
[0149] In a particular embodiment, the capture probe is not 60
nucleotides.
[0150] In another embodiment, the capture probe is substantially
smaller than 60 nucleotides but hybridizes comparably, as well as,
or better than a 60 nucleotide capture probe targeting the same DNA
target region.
[0151] In a certain embodiment, the capture probe is 40
nucleotides.
[0152] In certain embodiments, a capture probe module comprises a
tail sequence. As used herein, the term "tail sequence" refers to a
polynucleotide at the 5' end of the capture probe module, which in
particular embodiments can serve as a primer binding site. In
particular embodiments, a sequencing primer binds to the primer
binding site in the tail region.
[0153] In particular embodiments, the tail sequence is about 5 to
about 100 nucleotides, about 10 to about 100 nucleotides, about 5
to about 75 nucleotides, about 5 to about 50 nucleotides, about 5
to about 25 nucleotides, or about 5 to about 20 nucleotides. In
certain embodiments, the third region is from about 10 to about 50
nucleotides, about 15 to about 40 nucleotides, about 20 to about 30
nucleotides or about 20 nucleotides, or any intervening number of
nucleotides.
[0154] In particular embodiments, the tail sequence is about 30
nucleotides, about 31 nucleotides, about 32 nucleotides, about 33
nucleotides, about 34 nucleotides, about 35 nucleotides, about 36
nucleotides, about 37 nucleotides, about 38 nucleotides, about 39
nucleotides, or about 40 nucleotides.
[0155] In various embodiments, the capture probe module comprises a
specific member of a binding pair to enable isolation and/or
purification of one or more captured fragments of a tagged and or
amplified cfDNA library that hybridizes to the capture probe. In
particular embodiments, the capture probe module is conjugate to
biotin or another suitable hapten, e.g., dinitrophenol,
digoxigenin.
[0156] In various embodiments, the capture probe module is
hybridized to a tagged and optionally amplified cfDNA library to
form a complex. In some embodiments, the multifunctional capture
probe module substantially hybridizes to a specific genomic target
region in the cfDNA library.
[0157] Hybridization or hybridizing conditions can include any
reaction conditions where two nucleotide sequences form a stable
complex; for example, the tagged cfDNA library and capture probe
module forming a stable tagged cfDNA library-capture probe module
complex. Such reaction conditions are well known in the art and
those of skill in the art will appreciated that such conditions can
be modified as appropriate, e.g., decreased annealing temperatures
with shorter length capture probes, and within the scope of the
present invention. Substantial hybridization can occur when the
second region of the capture probe complex exhibits 100%, 99%, 98%,
97%, 96%, 95%, 94%, 93%, 92% 91%, 90%, 89%, 88%, 85%, 80%, 75%, or
70% sequence identity, homology or complementarity to a region of
the tagged cfDNA library.
[0158] In particular embodiments, the capture probe is about 40
nucleotides and has an optimal annealing temperature of about
44.degree. C. o about 47.degree. C.
[0159] In certain embodiments, the methods contemplated herein
comprise isolating a tagged cfDNA library-capture probe module
complex. In particular embodiments, methods for isolating DNA
complexes are well known to those skilled in the art and any
methods deemed appropriate by one of skill in the art can be
employed with the methods of the present invention (Ausubel et al.,
Current Protocols in Molecular Biology, 2007-2012). In particular
embodiments, the complexes are isolated using biotin-streptavidin
isolation techniques.
[0160] In particular embodiments, removal of the single stranded
3'-ends from the isolated tagged cfDNA library-capture probe module
complex is contemplated. In certain embodiments, the methods
comprise 3'-5' exonuclease enzymatic processing of the isolated
tagged DNA library-multifunctional capture probe module complex to
remove the single stranded 3' ends.
[0161] In certain other embodiments, the methods comprise
performing 5'-3' DNA polymerase extension of multifunctional
capture probe utilizing the isolated tagged DNA library fragments
as template.
[0162] In certain other embodiments, the methods comprise creating
a hybrid capture probe-isolated tagged cfDNA target molecule
through the concerted action of a 5' FLAP endonuclease, DNA
polymerization and nick closure by a DNA ligase.
[0163] A variety of enzymes can be employed for the 3'-5'
exonuclease enzymatic processing of the isolated tagged cfDNA
library-multifunctional capture probe module complex. Illustrative
examples of suitable enzymes, which exhibit 3'-5' exonuclease
enzymatic activity, that can be employed in particular embodiments
include, but are not limited to: T4 or Exonucleases I, III, V (see
also, Shevelev I V, Hubscher U., "The 3' 5' exonucleases," Nat Rev
Mol Cell Biol. 3(5):364-76 (2002)). In particular embodiments, the
enzyme comprising 3'-5' exonuclease activity is T4 polymerase. In
particular embodiments, an enzyme which exhibits 3'-5' exonuclease
enzymatic activity and is capable of primer template extension can
be employed, including for example T4 or Exonucleases I, III, V.
Id.
[0164] In some embodiments, the methods contemplated herein
comprise performing sequencing and/or PCR on the 3'-5' exonuclease
enzymatically processed complex discussed supra and elsewhere
herein. In particular embodiments, a tail portion of a capture
probe molecule is copied in order to generate a hybrid nucleic acid
molecule. In one embodiment, the hybrid nucleic acid molecule
generated comprises the target region capable of hybridizing to the
capture probe module and the complement of the capture probe module
tail sequence.
[0165] In a particular embodiment, genetic analysis comprises a)
hybridizing one or more capture probe modules to one or more target
genetic loci in a plurality of cfDNA library clones to form one or
more capture probe module-cfDNA library clone complexes; b)
isolating the one or more capture probe module-cfDNA library clone
complexes from a); c) enzymatically processing the one or more
isolated capture probe module-cfDNA library clone complexes from
step b); d) performing PCR on the enzymatically processed complex
from c) wherein the tail portion of the capture probe molecule is
copied in order to generate amplified hybrid nucleic acid
molecules, wherein the amplified hybrid nucleic acid molecules
comprise a target sequence in the target genomic locus capable of
hybridizing to the capture probe and the complement of the capture
probe module tail sequence; and e) performing quantitative genetic
analysis on the amplified hybrid nucleic acid molecules from
d).
[0166] In a particular embodiment, methods for determining copy
number of a specific target genetic locus are contemplated
comprising: a) hybridizing one or more capture probe modules to one
or more target genetic loci in a plurality of cfDNA library clones
to form one or more capture probe module-cfDNA library clone
complexes; b) isolating the one or more capture probe module-cfDNA
library clone complexes from a); c) enzymatically processing the
one or more isolated capture probe module-cfDNA library clone
complexes from step b); d) performing PCR on the enzymatically
processed complex from c) wherein the tail portion of the capture
probe molecule is copied in order to generate amplified hybrid
nucleic acid molecules, wherein the amplified hybrid nucleic acid
molecules comprise a target sequence in the target genetic locus
capable of hybridizing to the capture probe and the complement of
the capture probe module tail sequence; e) performing PCR
amplification of the amplified hybrid nucleic acid molecules in d);
and f) quantitating the PCR reaction in e), wherein the
quantitation allows for a determination of copy number of the
specific target region.
[0167] In one embodiment, the enzymatic processing of step c)
comprises performing 3'-5' exonuclease enzymatic processing on the
one or more capture probe module-cfDNA library clone complexes from
b) using an enzyme with 3'-5' exonuclease activity to remove the
single stranded 3' ends; creating one or more hybrid capture probe
module-cfDNA library clone molecules through the concerted action
of a 5' FLAP endonuclease, DNA polymerization and nick closure by a
DNA ligase; or performing 5'-3' DNA polymerase extension of the
capture probe using the isolated cfDNA clone in the complex as a
template.
[0168] In one embodiment, the enzymatic processing of step c)
comprises performing 5'-3' DNA polymerase extension of the capture
probe using the isolated cfDNA clone in the complex as a
template.
[0169] In particular embodiments, PCR can be performed using any
standard PCR reaction conditions well known to those of skill in
the art. In certain embodiments, the PCR reaction in e) employs two
PCR primers. In one embodiment, the PCR reaction in e) employs a
first PCR primer that hybridizes to a repeat within the target
genetic locus. In a particular embodiment, the PCR reaction in e)
employs a second PCR primer that hybridizes to the hybrid nucleic
acid molecules at the target genetic locus/tail junction. In
certain embodiments, the PCR reaction in e) employs a first PCR
primer that hybridizes to the target genetic locus and a second PCR
primer hybridizes to the amplified hybrid nucleic acid molecules at
the target genetic locus/tail junction. In particular embodiments,
the second primer hybridizes to the target genetic locus/tail
junction such that at least one or more nucleotides of the primer
hybridize to the target genetic locus and at least one or more
nucleotides of the primer hybridize to the tail sequence.
[0170] In certain embodiments, the amplified hybrid nucleic acid
molecules obtained from step e) are sequenced and the sequences
aligned horizontally, i.e., aligned to one another but not aligned
to a reference sequence. In particular embodiments, steps a)
through e) are repeated one or more times with one or more capture
probe modules. The capture probe modules can be the same or
different and designed to target either cfDNA strand of a target
genetic locus. In some embodiments, when the capture probes are
different, they hybridize at overlapping or adjacent target
sequences within a target genetic locus in the tagged cfDNA clone
library. In one embodiment, a high density capture probe strategy
is used wherein a plurality of capture probes hybridize to a target
genetic locus, and wherein each of the plurality of capture probes
hybridizes to the target genetic locus within about 5, 10, 15, 20,
25, 30, 35, 40, 45, 50, 100, 200, bp of any other capture probe
that hybridizes to the target genetic locus in a tagged cfDNA clone
library, including all intervening distances.
[0171] In some embodiments, the method can be performed using two
capture probe modules per target genetic locus, wherein one
hybridizes to the "Watson" strand (non-coding or template strand)
upstream of the target region and one hybridizes to the "Crick"
strand (coding or non-template strand) downstream of the target
region.
[0172] In particular embodiments, the methods contemplated herein
can further be performed multiple times with any number of capture
probe modules, for example 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more
capture probe modules per target genetic locus any number of which
hybridize to the Watson or Crick strand in any combination. In some
embodiments, the sequences obtained can be aligned to one another
in order to identify any of a number of differences.
[0173] In certain embodiments, a plurality of target genetic loci
are interrogated, e.g., 100, 200, 300, 400, 500, 600, 700, 800,
900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 10000,
50000, 100000, 500000 or more in a single reaction, using one or
more capture probe modules.
[0174] (b) Sequencing
[0175] In particular embodiments, the quantitative genetic analysis
comprises sequencing a plurality of hybrid nucleic acid molecules,
as discussed elsewhere herein, supra, to generate sufficient
sequencing depths to obtain a plurality of unique sequencing reads.
A unique read is defined as the single consensus read from a
"family" of reads that all share the same read code and sequence
start point within cfDNA. Each capture probe yields a set of unique
reads that are computationally distilled from total reads by
grouping into families. The unique reads for a given sample are
then computed as the average of all the unique reads observed on a
probe-by-probe basis. Cases where there is an obvious copy number
change are excluded from the data set used to compute the average.
Unique reads are important because each unique read must be derived
from a unique cfDNA clone. Each unique read represents the input
and analysis of a haploid equivalent of genomic DNA. The sum of
unique reads is the sum of haploid genomes analyzed. The number of
genomes analyzed, in turn, defines the sensitivity of the
sequencing assay. By way of a non-limiting example, if the average
unique read count is 100 genome equivalents, then that particular
assay has a sensitivity of being able to detect one mutant read in
100, or 1%. Any observation less than this is not defensible.
[0176] In particular embodiments, the quantitative genetic analysis
comprises multiplex sequencing of hybrid nucleic acid molecules
derived from a plurality of samples.
[0177] In various embodiments, the quantitative genetic analysis
comprises obtaining one or more or a plurality of tagged DNA
library clones, each clone comprising a first DNA sequence and a
second DNA sequence, wherein the first DNA sequence comprises a
sequence in a targeted genetic locus and the second DNA sequence
comprises a capture probe sequence; performing a paired end
sequencing reaction on the one or more clones and obtaining one or
more sequencing reads or performing a sequencing reaction on the
one or more clones in which a single long sequencing read of
greater than about 100, 200, 300, 400, 500 or more nucleotides is
obtained, wherein the read is sufficient to identify both the first
DNA sequence and the second DNA sequence; and ordering or
clustering the sequencing reads of the one or more clones according
to the probe sequences of the sequencing reads.
[0178] (c) Bioinformatics Analysis
[0179] In various embodiments, the quantitative genetic analysis
further comprises bioinformatic analysis of the sequencing reads.
Bioinformatic analysis excludes any purely mental analysis
performed in the absence of a composition or method for sequencing.
In certain embodiments, bioinformatics analysis includes, but is
not limited to: sequence alignments; genome equivalents analysis;
single nucleotide variant (SNV) analysis; gene copy number
variation (CNV) analysis; and detection of genetic lesions. In
particular embodiments, bioinformatics analysis is useful to
quantify the number of genome equivalents analyzed in the cfDNA
clone library; to detect the genetic state of a target genetic
locus; to detect genetic lesions in a target genetic locus; and to
measure copy number fluctuations within a target genetic locus.
[0180] Sequence alignments may be performed between the sequence
reads and one or more human reference DNA sequences. In particular
embodiments, sequencing alignments can be used to detect genetic
lesions in a target genetic locus including, but not limited to
detection of a nucleotide transition or transversion, a nucleotide
insertion or deletion, a genomic rearrangement, a change in copy
number, or a gene fusion. Detection of genetic lesions that are
causal or prognostic indicators may be useful in the diagnosis,
prognosis, treatment, and/or monitoring of a particular genetic
condition or disease.
[0181] Also contemplated herein, are methods for sequence alignment
analysis that can be performed without the need for alignment to a
reference sequence, referred to herein as horizontal sequence
analysis. Such analysis can be performed on any sequences generated
by the methods contemplated herein or any other methods. In
particular embodiments, the sequence analysis comprises performing
sequence alignments on the reads obtained by the methods
contemplated herein.
[0182] In one embodiment, the genome equivalents in a cfDNA clone
library are determined using bioinformatics-based counting after
sequencing is performed. Each sequencing read is associated with a
particular capture probe, and the collection of reads assigned to
each capture probe is parsed into groups. Within a group, sets of
individual reads share the same read code and the same DNA sequence
start position within genomic sequence. These individual reads are
grouped into a "family" and a single consensus representative of
this family is carried forward as a "unique read." All of the
individual reads that constituted a family are derived from a
single ligation event and thus, they are amplification-derived
"siblings" of one another. Each unique read is considered a unique
ligation event and the sum of unique reads is considered equivalent
to the number of genome equivalents analyzed.
[0183] As the number of unique clones approaches the total number
of possible sequence combinations, probability dictates that the
same code and start site combinations will be created by
independent events and that these independent events will be
inappropriately grouped within single families. The net result will
be an underestimate of genome equivalents analyzed, and rare mutant
reads may be discarded as sequencing errors because they overlap
with wild-type reads bearing the same identifiers.
[0184] In particular embodiments, to provide an accurate analysis
for cfDNA clone libraries, the number of genome equivalents
analyzed is about 1/10, about 1/12, about 1/14, about 1/16, about
1/18, about 1/20, about 1/25 or less the number of possible unique
clones. It should be understood that the procedure outlined above
is merely illustrative and not limiting.
[0185] In some embodiments, the number of genome equivalents to be
analyzed may need to be increased. To expand the depth of genome
equivalents, at least two solutions are contemplated. The first
solution is to use more than one adaptor set per sample. By
combining adaptors, it is possible to multiplicatively expand the
total number of possible clones and therefore, expand the
comfortable limits of genomic input. The second solution is to
expand the read code by 1, 2, 3, 4, or 5 or more bases. The number
of possible read codes that differ by at least 2 bases from every
other read code scales as 4.sup.(n-1) where n is the number of
bases within a read code. Thus, in a non-limiting example, if a
read code is 5 nucleotides and 4.sup.(5-1)=256; therefore, the
inclusion of additional bases expands the available repertoire by a
factor of four for each additional base.
[0186] In one embodiment, quantitative genetic analysis comprises
bioinformatic analysis of sequencing reads to identify rare single
nucleotide variants (SNV).
[0187] Next-generation sequencing has an inherent error rate of
roughly 0.02-0.02%, meaning that anywhere from 1/200 to 1/500 base
calls are incorrect. To detect variants and other mutations that
occur at frequencies lower than this, for example at frequencies of
1 per 1000 sequences, it is necessary to invoke molecular
annotation strategies. By way of a non-limiting example, analysis
of 5000 unique molecules using targeted sequence capture technology
would generate--at sufficient sequencing depths of >50,000
reads--a collection of 5000 unique reads, with each unique read
belonging to a "family" of reads that all possess the same read
code. A SNV that occurs within a family is a candidate for being a
rare variant. When this same variant is observed in more than one
family, it becomes a very strong candidate for being a rare variant
that exists within the starting sample. In contrast, variants that
occur sporadically within families are likely to be sequencing
errors and variants that occur within one and only one family are
either rare or the result of a base alteration that occurred ex
vivo (e.g., oxidation of a DNA base or PCR-introduced errors).
[0188] In one embodiment, the methods of detecting SNVs comprise
introducing 10-fold more genomic input (genomes or genome
equivalents) as the desired target sensitivity of the assay. In one
non-limiting example, if the desired sensitivity is 2% (2 in 100),
then the experimental target is an input of 2000 genomes.
[0189] In particular embodiments, bioinformatics analysis of
sequencing data is used to detect or identify SNV associated with a
genetic state, condition or disease, genetic mosaicism, fetal
testing, paternity testing, predicting response to drug treatment,
diagnosing or monitoring a medical condition, microbiome profiling,
pathogen screening, and monitoring organ transplants.
[0190] In various embodiments, a method for copy number
determination analysis is provided comprising obtaining one or more
or a plurality of clones, each clone comprising a first DNA
sequence and a second DNA sequence, wherein the first DNA sequence
comprises a sequence in a targeted genetic locus and the second DNA
sequence comprises a capture probe sequence. In related
embodiments, a paired end sequencing reaction on the one or more
clones is performed and one or more sequencing reads are obtained.
In another embodiment, a sequencing reaction on the one or more
clones is performed in which a single long sequencing read of
greater than about 100 nucleotides is obtained, wherein the read is
sufficient to identify both the first DNA sequence and the second
DNA sequence. The sequencing reads of the one or more clones can be
ordered or clustered according to the probe sequence of the
sequencing reads.
[0191] Copy number analyses include, but are not limited to
analyses, that examine the number of copies of a particular gene or
mutation that occurs in a given genomic DNA sample and can further
include quantitative determination of the number of copies of a
given gene or sequence differences in a given sample. In particular
embodiments, copy number analysis is used to detect or identify
gene amplification associated with genetic states, conditions, or
diseases, fetal testing, genetic mosaicism, paternity testing,
predicting response to drug treatment, diagnosing or monitoring a
medical condition, microbiome profiling, pathogen screening, and
monitoring organ transplants.
[0192] In particular embodiments, bioinformatics analysis of
sequencing data is used to detect or identify one or more sequences
or genetic lesions in a target locus including, but not limited to
detection of a nucleotide transition or transversion, a nucleotide
insertion or deletion, a genomic rearrangement, a change in copy
number, or a gene fusion. Detection of genetic lesions that are
causal or prognostic indicators may be useful in the diagnosis,
prognosis, treatment, and/or monitoring of a particular genetic
condition or disease. In one embodiment, genetic lesions are
associated with genetic states, conditions, or diseases, fetal
testing, genetic mosaicism, paternity testing, predicting response
to drug treatment, diagnosing or monitoring a medical condition,
microbiome profiling, pathogen screening, and monitoring organ
transplants.
D. Clinical Applications of Quantitative Genetic Analysis
[0193] In various embodiments, the present invention contemplates a
method of detecting, identifying, predicting, diagnosing, or
monitoring a condition or disease in a subject.
[0194] In particular embodiments, a method of detecting,
identifying, predicting, diagnosing, or monitoring a genetic state,
condition or disease in a subject comprises performing a
quantitative genetic analysis of one or more target genetic loci in
a cfDNA clone library to detect or identify a change in the
sequence at the one or more target genetic loci.
[0195] In one embodiment, a method of detecting, identifying,
predicting, diagnosing, or monitoring a genetic state, condition or
disease comprises isolating or obtaining cfDNA from a biological
sample of a subject; treating the cfDNA with one or more end-repair
enzymes to generate end-repaired cfDNA; ligating one or more
adaptors to each end of the end-repaired cfDNA to generate a cfDNA
library; amplifying the cfDNA library to generate a cfDNA clone
library; determining the number of genome equivalents in the cfDNA
clone library; and performing a quantitative genetic analysis of
one or more target genetic loci in a cfDNA clone library to detect
or identify a change in the sequence at the one or more target
genetic loci.
[0196] In particular embodiments, a method of detecting,
identifying, predicting, diagnosing, or monitoring a genetic state,
or genetic condition or disease selected from the group consisting
of: genetic diseases; genetic mosaicism; fetal testing; paternity
testing; paternity testing; predicting response to drug treatment;
diagnosing or monitoring a medical condition; microbiome profiling;
pathogen screening; and organ transplant monitoring comprising
isolating or obtaining cfDNA from a biological sample of a subject;
treating the cfDNA with one or more end-repair enzymes to generate
end-repaired cfDNA; ligating one or more adaptors to each end of
the end-repaired cfDNA to generate a cfDNA library; amplifying the
cfDNA library to generate a cfDNA clone library; determining the
number of genome equivalents in the cfDNA clone library; and
performing a quantitative genetic analysis of one or more target
genetic loci in a cfDNA clone library to detect or identify a
nucleotide transition or transversion, a nucleotide insertion or
deletion, a genomic rearrangement, a change in copy number, or a
gene fusion in the sequence at the one or more target genetic
loci.
[0197] Illustrative examples of genetic diseases that can be
detected, identified, predicted, diagnosed, or monitored with the
compositions and methods contemplated herein include, but are not
limited to cancer, Alzheimer's disease (APOE1), Charcot-Marie-Tooth
disease, Leber hereditary optic neuropathy (LHON), Angelman
syndrome (UBE3A, ubiquitin-protein ligase E3A), Prader-Willi
syndrome (region in chromosome 15), .beta.-Thalassaemia (HBB,
.beta.-Globin), Gaucher disease (type I) (GBA, Glucocerebrosidase),
Cystic fibrosis (CFTR Epithelial chloride channel), Sickle cell
disease (HBB, .beta.-Globin), Tay-Sachs disease (HEXA,
Hexosaminidase A), Phenylketonuria (PAH, Phenylalanine hydrolyase),
Familial hypercholesterolaemia (LDLR, Low density lipoprotein
receptor), Adult polycystic kidney disease (PKD1, Polycystin),
Huntington disease (HDD, Huntingtin), Neurofibromatosis type I
(NF1, NF1 tumour suppressor gene), Myotonic dystrophy (DM,
Myotonin), Tuberous sclerosis (TSC1, Tuberin), Achondroplasia
(FGFR3, Fibroblast growth factor receptor), Fragile X syndrome
(FMR1, RNA-binding protein), Duchenne muscular dystrophy (DMD,
Dystrophin), Haemophilia A (F8C, Blood coagulation factor VIII),
Lesch-Nyhan syndrome (HPRT1, Hypoxanthine guanine
ribosyltransferase 1), and Adrenoleukodystrophy (ABCD1).
[0198] Illustrative examples of cancers that can be detected,
identified, predicted, diagnosed, or monitored with the
compositions and methods contemplated herein include, but are not
limited to: B cell cancer, e.g., multiple myeloma, melanomas,
breast cancer, lung cancer (such as non-small cell lung carcinoma
or NSCLC), bronchus cancer, colorectal cancer, prostate cancer,
pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder
cancer, brain or central nervous system cancer, peripheral nervous
system cancer, esophageal cancer, cervical cancer, uterine or
endometrial cancer, cancer of the oral cavity or pharynx, liver
cancer, kidney cancer, testicular cancer, biliary tract cancer,
small bowel or appendix cancer, salivary gland cancer, thyroid
gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma,
cancer of hematological tissues, adenocarcinomas, inflammatory
myofibroblastic tumors, gastrointestinal stromal tumor (GIST),
colon cancer, multiple myeloma (MM), myelodysplastic syndrome
(MDS), myeloproliferative disorder (MPD), acute lymphocytic
leukemia (ALL), acute myelocytic leukemia (AML), chronic myelocytic
leukemia (CML), chronic lymphocytic leukemia (CLL), polycythemia
Vera, Hodgkin lymphoma, non-Hodgkin lymphoma (NHL), soft-tissue
sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic
sarcoma, chordoma, angiosarcoma, endotheliosarcoma,
lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma,
mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma,
squamous cell carcinoma, basal cell carcinoma, adenocarcinoma,
sweat gland carcinoma, sebaceous gland carcinoma, papillary
carcinoma, papillary adenocarcinomas, medullary carcinoma,
bronchogenic carcinoma, renal cell carcinoma, hepatoma, bile duct
carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms'
tumor, bladder carcinoma, epithelial carcinoma, glioma,
astrocytoma, medulloblastoma, craniopharyngioma, ependymoma,
pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma,
meningioma, neuroblastoma, retinoblastoma, follicular lymphoma,
diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular
carcinoma, thyroid cancer, gastric cancer, head and neck cancer,
small cell cancers, essential thrombocythemia, agnogenic myeloid
metaplasia, hypereosinophilic syndrome, systemic mastocytosis,
familiar hypereosinophilia, chronic eosinophilic leukemia,
neuroendocrine cancers, carcinoid tumors, and the like.
[0199] In one embodiment, the genetic lesion is a lesion annotated
in the Cosmic database (the lesions and sequence data can be
downloaded from cancer.sanger.ac.uk/cosmic/census) or a lesion
annotated in the Cancer Genome Atlas (the lesions and sequence data
can be downloaded from
tcga-data.nci.nih.gov/tcga/tcgaDownload.jsp).
[0200] Illustrative examples of genes that harbor one or more
genetic lesions associated with cancer that can be detected,
identified, predicted, diagnosed, or monitored with the
compositions and methods contemplated herein include, but are not
limited to ABCB1, ABCC2, ABCC4, ABCG2, ABL1, ABL2, AKT1, AKT2,
AKT3, ALDH4A1, ALK, APC, AR, ARAF, ARFRP1, ARID1A, ATM, ATR, AURKA,
AURKB, BCL2, BCL2A1, BCL2L1, BCL2L2, BCL6, BRAF, BRCA1, BRCA2,
Clorf144, CARD11, CBL, CCND1, CCND2, CCND3, CCNE1, CDH1, CDH2,
CDH2O, CDH5, CDK4, CDK6, CDK8, CDKN2A, CDKN2B, CDKN2C, CEBPA,
CHEK1, CHEK2, CRKL, CRLF2, CTNNB1, CYP1B1, CYP2C19, CYP2C8, CYP2D6,
CYP3A4, CYP3A5, DNMT3A, DOT1L, DPYD, EGFR, EPHA3, EPHA5, EPHA6,
EPHA7, EPHB1, EPHB4, EPHB6, EPHX1, ERBB2, ERBB3, ERBB4, ERCC2, ERG,
ESR1, ESR2, ETV1, ETV4, ETV5, ETV6, EWSR1, EZH2, FANCA, FBXW7,
FCGR3A, FGFR1, FGFR2, FGFR3, FGFR4, FLT1, FLT3, FLT4, FOXP4, GATA1,
GNA11, GNAQ, GNAS, GPR124, GSTP1, GUCY1A2, HOXA3, HRAS, HSP90AA1,
IDH1, IDH2, IGF1R, IGF2R, IKBKE, IKZF1, INHBA, IRS2, ITPA, JAK1,
JAK2, JAK3, JUN, KDR, KIT, KRAS, LRP1B, LRP2, LTK, MAN1B1, MAP2K1,
MAP2K2, MAP2K4, MCL1, MDM2, MDM4, MEN1, MET, MITF, MLH1, MLL, MPL,
MRE11A, MSH2, MSH6, MTHFR, MTOR, MUTYH, MYC, MYCL1, MYCN, NF1, NF2,
NKX2-1, NOTCH1, NPM1, NQO1, NRAS, NRP2, NTRK1, NTRK3, PAK3, PAX5,
PDGFRA, PDGFRB, PIK3CA, PIK3R1, PKHD1, PLCG1, PRKDC, PTCH1, PTEN,
PTPN11, PTPRD, RAF1, RARA, RB1, RET, RICTOR, RPTOR, RUNX1, SLC19A1,
SLC22A2, SLCO1B3, SMAD2, SMAD3, SMAD4, SMARCA4, SMARCB1, SMO, SOD2,
SOX10, SOX2, SRC, STK11, SULT1A1, TBX22, TET2, TGFBR2, TMPRSS2,
TNFRSF14, TOP1, TP53, TPMT, TSC1, TSC2, TYMS, UGT1A1, UMPS, USP9X,
VHL, and WT1.
[0201] In particular embodiments, the genetic lesion comprises a
nucleotide transition or transversion, a nucleotide insertion or
deletion, a genomic rearrangement, a change in copy number, or a
gene fusion.
[0202] In one embodiment, the genetic lesion is a gene fusion that
fuses the 3' coding region of the ALK gene to another gene.
[0203] In one embodiment, the genetic lesion is a gene fusion that
fuses the 3' coding region of the ALK gene to the EML4 gene.
[0204] Illustrative examples of conditions suitable for fetal
testing that can be detected, identified, predicted, diagnosed, or
monitored with the compositions and methods contemplated herein
include but are not limited to: Down Syndrome (Trisomy 21), Edwards
Syndrome (Trisomy 18), Patau Syndrome (Trisomy 13), Klinefelter's
Syndrome (XXY), Triple X syndrome, XYY syndrome, Trisomy 8, Trisomy
16, Turner Syndrome (XO), Robertsonian translocation, DiGeorge
Syndrome and Wolf-Hirschhorn Syndrome.
[0205] Illustrative examples of alleles suitable for paternity
testing that can be detected, identified, predicted, diagnosed, or
monitored with the compositions and methods contemplated herein
include but are not limited to 16 or more of: D20S1082, D6S474,
D12ATA63, D22S1045, D10S1248, D1S1677, D11S4463, D4S2364, D9S1122,
D2S1776, D10S1425, D3S3053, D5S2500, D1S1627, D3S4529, D2S441,
D175974, D6S1017, D4S2408, D9S2157, Amelogenin, D17S1301,
D1GATA113, D18S853, D20S482, and D14S1434.
[0206] Illustrative examples of genes suitable for predicting the
response to drug treatment that can be detected, identified,
predicted, diagnosed, or monitored with the compositions and
methods contemplated herein include, but are not limited to, one or
more of the following genes: ABCB1 (ATP-binding cassette,
sub-family B (MDR/TAP), member 1), ACE (angiotensin I converting
enzyme), ADH1A (alcohol dehydrogenase 1A (class I), alpha
polypeptide), ADH1B (alcohol dehydrogenase IB (class I), beta
polypeptide), ADH1C (alcohol dehydrogenase 1C (class I), gamma
polypeptide), ADRB1 (adrenergic, beta-1-, receptor), ADRB2
(adrenergic, beta-2-, receptor, surface), AHR (aryl hydrocarbon
receptor), ALDH1A1 (aldehyde dehydrogenase 1 family, member A1),
ALOX5 (arachidonate 5-lipoxygenase), BRCA1 (breast cancer 1, early
onset), COMT (catechol-O-methyltransferase), CYP2A6 (cytochrome
P450, family 2, subfamily A, polypeptide 6), CYP2B6 (cytochrome
P450, family 2, subfamily B, polypeptide 6), CYP2C9 (cytochrome
P450, family 2, subfamily C, polypeptide 9), CYP2C19 (cytochrome
P450, family 2, subfamily C, polypeptide 19), CYP2D6 (cytochrome
P450, family 2, subfamily D, polypeptide 6), CYP2J2 (cytochrome
P450, family 2, subfamily J, polypeptide 2), CYP3A4 (cytochrome
P450, family 3, subfamily A, polypeptide 4), CYP3A5 (cytochrome
P450, family 3, subfamily A, polypeptide 5), DPYD
(dihydropyrimidine dehydrogenase), DRD2 (dopamine receptor D2), F5
(coagulation factor V), GSTP1 (glutathione S-transferase pi), HMGCR
(3-hydroxy-3-methylglutaryl-Coenzyme A reductase), KCNH2 (potassium
voltage-gated channel, subfamily H (eag-related), member 2), KCNJ11
(potassium inwardly-rectifying channel, subfamily J, member 11),
MTHFR (5,10-methylenetetrahydrofolate reductase (NADPH)), NQO1
(NAD(P)H dehydrogenase, quinone 1), P2RY1 (purinergic receptor P2Y,
G-protein coupled, 1), P2RY12 (purinergic receptor P2Y, G-protein
coupled, 12), PTGIS (prostaglandin I2 (prostacyclin) synthase),
SCN5A (sodium channel, voltage-gated, type V, alpha (long QT
syndrome 3)), SLC19A1 (solute carrier family 19 (folate
transporter), member 1), SLCO1B1 (solute carrier organic anion
transporter family, member 1B1), SULT1A1 (sulfotransferase family,
cytosolic, 1A, phenol-preferring, member 1), TPMT (thiopurine
S-methyltransferase), TYMS (thymidylate synthetase), UGT1A1 (UDP
glucuronosyltransferase 1 family, polypeptide A1), VDR (vitamin D
(1,25-dihydroxyvitamin D3) receptor), VKORC1 (vitamin K epoxide
reductase complex, subunit 1).
[0207] Illustrative examples of medical conditions that can be
detected, identified, predicted, diagnosed, or monitored with the
compositions and methods contemplated herein include, but are not
limited to: stroke, transient ischemic attack, traumatic brain
injury, heart disease, heart attack, angina, atherosclerosis, and
high blood pressure.
[0208] Illustrative examples of pathogens that can be screened for
with the compositions and methods contemplated herein include, but
are not limited to: bacteria fungi, and viruses.
[0209] Illustrative examples of bacterial species that can be
screened for with the compositions and methods contemplated herein
include, but are not limited to: a Mycobacterium spp., a
Pneumococcus spp., an Escherichia spp., a Campylobacter spp., a
Corynebacterium spp., a Clostridium spp., a Streptococcus spp., a
Staphylococcus spp., a Pseudomonas spp., a Shigella spp., a
Treponema spp., or a Salmonella spp.
[0210] Illustrative examples of fungal species that can be screened
for with the compositions and methods contemplated herein include,
but are not limited to: an Aspergillis spp., a Blastomyces spp., a
Candida spp., a Coccicioides spp., a Cryptococcus spp.,
dermatophytes, a Tinea spp., a Trichophyton spp., a Microsporum
spp., a Fusarium spp., a Histoplasma spp., a Mucoromycotina spp., a
Pneumocystis spp., a Sporothrix spp., an Exserophilum spp., or a
Cladosporium spp.
[0211] Illustrative examples of viruses that can be screened for
with the compositions and methods contemplated herein include, but
are not limited to: Influenza A such as H1N1, H1N2, H3N2 and H5N1
(bird flu), Influenza B, Influenza C virus, Hepatitis A virus,
Hepatitis B virus, Hepatitis C virus, Hepatitis D virus, Hepatitis
E virus, Rotavirus, any virus of the Norwalk virus group, enteric
adenoviruses, parvovirus, Dengue fever virus, Monkey pox,
Mononegavirales, Lyssavirus such as rabies virus, Lagos bat virus,
Mokola virus, Duvenhage virus, European bat virus 1 & 2 and
Australian bat virus, Ephemerovirus, Vesiculovirus, Vesicular
Stomatitis Virus (VSV), Herpesviruses such as Herpes simplex virus
types 1 and 2, varicella zoster, cytomegalovirus, Epstein-Bar virus
(EBV), human herpesviruses (HHV), human herpesvirus type 6 and 8,
Moloney murine leukemia virus (M-MuLV), Moloney murine sarcoma
virus (MoMSV), Harvey murine sarcoma virus (HaMuSV), murine mammary
tumor virus (MuMTV), gibbon ape leukemia virus (GaLV), feline
leukemia virus (FLV), Spumavirus, Friend murine leukemia virus,
Murine Stem Cell Virus (MSCV) and Rous Sarcoma Virus (RSV), HIV
(human immunodeficiency virus; including HIV type 1, and HIV type
2), visna-maedi virus (VMV) virus, the caprine
arthritis-encephalitis virus (CAEV), equine infectious anemia virus
(EIAV), feline immunodeficiency virus (FIV), bovine immune
deficiency virus (BIV), and simian immunodeficiency virus (SIV),
papilloma virus, murine gammaherpesvirus, Arenaviruses such as
Argentine hemorrhagic fever virus, Bolivian hemorrhagic fever
virus, Sabia-associated hemorrhagic fever virus, Venezuelan
hemorrhagic fever virus, Lassa fever virus, Machupo virus,
Lymphocytic choriomeningitis virus (LCMV), Bunyaviridiae such as
Crimean-Congo hemorrhagic fever virus, Hantavirus, hemorrhagic
fever with renal syndrome causing virus, Rift Valley fever virus,
Filoviridae (filovirus) including Ebola hemorrhagic fever and
Marburg hemorrhagic fever, Flaviviridae including Kaysanur Forest
disease virus, Omsk hemorrhagic fever virus, Tick-borne
encephalitis causing virus and Paramyxoviridae such as Hendra virus
and Nipah virus, variola major and variola minor (smallpox),
alphaviruses such as Venezuelan equine encephalitis virus, eastern
equine encephalitis virus, western equine encephalitis virus,
SARS-associated coronavirus (SARS-CoV), West Nile virus, and any
encephaliltis causing virus.
[0212] Illustrative examples of genes suitable for monitoring an
organ transplant in a transplant recipient that can be detected,
identified, predicted, diagnosed, or monitored with the
compositions and methods contemplated herein include, but are not
limited to, one or more of the following genes: HLA-A, HLA-B,
HLA-C, HLA-DR, HLA-DP, and HLA-DQ.
[0213] In particular embodiments, a bioinformatic analysis is used
to quantify the number of genome equivalents analyzed in the cfDNA
clone library; detect genetic variants in a target genetic locus;
detect mutations within a target genetic locus; detect genetic
fusions within a target genetic locus; or measure copy number
fluctuations within a target genetic locus.
E. Companion Diagnostics
[0214] In various embodiments, a companion diagnostic for a genetic
disease is provided, comprising: isolating or obtaining cfDNA from
a biological sample of a subject; treating the cfDNA with one or
more end-repair enzymes to generate end-repaired cfDNA; ligating
one or more adaptors to each end of the end-repaired cfDNA to
generate a cfDNA library; amplifying the cfDNA library to generate
a cfDNA clone library; determining the number of genome equivalents
in the cfDNA clone library; and performing a quantitative genetic
analysis of one or more biomarkers associated with the genetic
disease in the cfDNA clone library, wherein detection of, or
failure to detect, at least one of the one or more biomarkers
indicates whether the subject should be treated for the genetic
disease.
[0215] As used herein, the term "companion diagnostic" refers to a
diagnostic test that is linked to a particular anti-cancer therapy.
In a particular embodiment, the diagnostic methods comprise
detection of genetic lesion in a biomarker associated with in a
biological sample, thereby allowing for prompt identification of
patients should or should not be treated with the anti-cancer
therapy.
[0216] Anti-cancer therapy includes, but is not limited to surgery,
radiation, chemotherapeutics, anti-cancer drugs, and
immunomodulators.
[0217] Illustrative examples of anti-cancer drugs include, but are
not limited to: alkylating agents such as thiotepa and
cyclophosphamide (CYTOXAN.TM.); alkyl sulfonates such as busulfan,
improsulfan and piposulfan; aziridines such as benzodopa,
carboquone, meturedopa, and uredopa; ethylenimines and
methylamelamines including altretamine, triethylenemelamine,
trietylenephosphoramide, triethylenethiophosphaoramide and
trimethylolomelamine resume; nitrogen mustards such as
chlorambucil, chlornaphazine, cholophosphamide, estramustine,
ifosfamide, mechlorethamine, mechlorethamine oxide hydrochloride,
melphalan, novembichin, phenesterine, prednimustine, trofosfamide,
uracil mustard; nitrosureas such as carmustine, chlorozotocin,
fotemustine, lomustine, nimustine, ranimustine; antibiotics such as
aclacinomysins, actinomycin, authramycin, azaserine, bleomycins,
cactinomycin, calicheamicin, carabicin, carminomycin,
carzinophilin, chromomycins, dactinomycin, daunorubicin,
detorubicin, 6-diazo-5-oxo-L-norleucine, doxorubicin and its
pegylated formulations, epirubicin, esorubicin, idarubicin,
marcellomycin, mitomycins, mycophenolic acid, nogalamycin,
olivomycins, peplomycin, potfiromycin, puromycin, quelamycin,
rodorubicin, streptonigrin, streptozocin, tubercidin, ubenimex,
zinostatin, zorubicin; anti-metabolites such as methotrexate and
5-fluorouracil (5-FU); folic acid analogues such as denopterin,
methotrexate, pteropterin, trimetrexate; purine analogs such as
fludarabine, 6-mercaptopurine, thiamiprine, thioguanine; pyrimidine
analogs such as ancitabine, azacitidine, 6-azauridine, carmofur,
cytarabine, dideoxyuridine, doxifluridine, enocitabine,
floxuridine, 5-FU; androgens such as calusterone, dromostanolone
propionate, epitiostanol, mepitiostane, testolactone; anti-adrenals
such as aminoglutethimide, mitotane, trilostane; folic acid
replenisher such as frolinic acid; aceglatone; aldophosphamide
glycoside; aminolevulinic acid; amsacrine; bestrabucil; bisantrene;
edatraxate; defofamine; demecolcine; diaziquone; elformithine;
elliptinium acetate; etoglucid; gallium nitrate; hydroxyurea;
lentinan; lonidamine; mitoguazone; mitoxantrone; mopidamol;
nitracrine; pentostatin; phenamet; pirarubicin; podophyllinic acid;
2-ethylhydrazide; procarbazine; PSK.RTM.; razoxane; sizofiran;
spirogermanium; tenuazonic acid; triaziquone;
2,2',2''-trichlorotriethylamine; urethan; vindesine; dacarbazine;
mannomustine; mitobronitol; mitolactol; pipobroman; gacytosine;
arabinoside ("Ara-C"); cyclophosphamide; thiotepa; taxoids, e.g.,
paclitaxel (TAXOL.RTM., Bristol-Myers Squibb Oncology, Princeton,
N.J.) and doxetaxel (TAXOTERE.RTM.., Rhne-Poulenc Rorer, Antony,
France); chlorambucil; gemcitabine; 6-thioguanine; mercaptopurine;
methotrexate; platinum analogs such as cisplatin and carboplatin;
vinblastine; platinum; etoposide (VP-16); ifosfamide; mitomycin C;
mitoxantrone; vincristine; vinorelbine; navelbine; novantrone;
teniposide; aminopterin; xeloda; ibandronate; CPT-11; topoisomerase
inhibitor RFS 2000; difluoromethylomithine (DMFO); retinoic acid
derivatives such as Targretin.TM. (bexarotene), Panretin.TM.
(alitretinoin); ONTAK.TM. (denileukin diftitox); esperamicins;
capecitabine; and pharmaceutically acceptable salts, acids or
derivatives of any of the above. Also included in this definition
are anti-hormonal agents that act to regulate or inhibit hormone
action on cancers such as anti-estrogens including for example
tamoxifen, raloxifene, aromatase inhibiting 4(5)-imidazoles,
4-hydroxytamoxifen, trioxifene, keoxifene, LY117018, onapristone,
and toremifene (Fareston); and anti-androgens such as flutamide,
nilutamide, bicalutamide, leuprolide, and goserelin; and
pharmaceutically acceptable salts, acids or derivatives of any of
the above.
[0218] Illustrative examples of immunomodulators include, but are
not limited to: cyclosporine, tacrolimus, tresperimus,
pimecrolimus, sirolimus, verolimus, laflunimus, laquinimod and
imiquimod, as well as analogs, derivatives, salts, ions and
complexes thereof.
[0219] All publications, patent applications, and issued patents
cited in this specification are herein incorporated by reference as
if each individual publication, patent application, or issued
patent were specifically and individually indicated to be
incorporated by reference.
[0220] Although the foregoing invention has been described in some
detail by way of illustration and example for purposes of clarity
of understanding, it will be readily apparent to one of ordinary
skill in the art in light of the teachings of this invention that
certain changes and modifications may be made thereto without
departing from the spirit or scope of the appended claims. The
following examples are provided by way of illustration only and not
by way of limitation. Those of skill in the art will readily
recognize a variety of noncritical parameters that could be changed
or modified to yield essentially similar results.
EXAMPLES
Example 1
Accurate Detection of Rare Mutations using Targeted Sequence
Capture Technology
Purpose
[0221] The purpose of this experiment was to provide a direct
proof-of-principle demonstration of rare variant detection using
targeted sequence capture technology.
Background
[0222] Target sequence capture technology provides quantitative,
sequence-based genetic analysis of nucleic acids and can be
exploited to perform a combined mutational and copy number analysis
of drug metabolism genes. The present inventors used targeted
sequence capture technology and subsequence genetic analysis to
detect rare sequence variants.
[0223] Genomic DNA inputs play a central role in rare variant
detection, but quantitative analysis and control of genomic inputs
places bounds on the estimated sensitivity of rare variant
analysis. A genomic qPCR assay was used by the present inventors to
estimate genomic inputs.
[0224] One experimental goal for rare variant analysis is to
introduce 10-fold more genomic input as the target sensitivity of
the assay. In other words, to measure variants with a sensitivity
of 1% (1 in 100), then the experimental target is to input 1000
genomes. Downstream of sequencing, bioinformatics analysis reveals
the number of unique reads, and this has the desirable quality of
being both an orthogonal and a more direct measure of genomic
inputs.
Summary
[0225] A cell line (ZR75-30) with known SNVs was admixed with a
germ line DNA sample (NA12878) in a dilution series ranging from
1-to-1 through 1-to-1000. Target regions corresponding to known
sequence differences were retrieved using targeted sequence capture
technology and sequenced. Sequence variants that occur at a
frequency of less than 1 per 1000 sequences were detected.
Methods
[0226] Capture Probes
[0227] The following table shows a collection of 62 capture probes
that were used in this experiment.
TABLE-US-00001 TABLE 1 60 base probe sequences used in the admix
proof- of-concept study SEQ ID Target NO: Probe Sequence BRAF 1
TAAACATTGGAAAGGTTTCTAATTAACCAGG AGATCCAAAAGAAAGCGGTTCAAGTAGCA 2
GATCTCAGTTTTTTTGGTTAACTATGTATTT TGGTATATGAAGCTTCTGGGTTTTGCACA MYCN
3 GACAGATAAGCATACATATTAACATGGATAT ATATGTGAATTTCATTCAAATGGTTCTCA 4
AGCTCTTAGCCTTTGGGGGGATGACACTCTT GAGCGGACGTGGGGACGCCTCGCTCTTTA BRAF
5 AAGCCCCCACCGCCGCCTCTTTCCAAAATAA ACACCAGCCAGCCGCCGAGCCCGGAGTCG 6
GCCTCCCTTCCCCCTCCCCGCCCGACAGCGG CCGCTCGGGCCCCGGCTCTCGGTTATAAG CDH1
7 GGTGTGGCAGCCAGGGGGGCGCACTCTGCTC TGGCTGGGCCCCTTCTCCCATGTTTTCTT 8
TTACACAACCTTTGGGCTTGGACAACACTTT GGGGTCCAAAGAACCTAAGAGTCTTTCTG EPHX2
9 TGATGAAACTTGGGCTGGATGGGGCACAGGT AGGGTGCTTGTTGCTTTCAGTCAGATGAA 10
AATGAAAGAAAAGGAGGCCAGATTGCTACTC CTGGTCCCTGCCACACACTAGGTACCCTA BRCA1
11 ATTGACAATACCTACATAAAACTCTTTCCAG AATGTTGTTAAGTCTTAGTCATTAGGGAG 12
GGATTTCCACCAACACTGTATTCATGTACCC ATTTTTCTCTTAACCTAACTTTATTGGTC BRCA2
13 CAAAGGGGGAAAACCATCAGGACATTATTTA ACAACGGAAATATCTAACTGAAAGGCAAA 14
CAGGCAGACCAACCAAAGTCTTTGTTCCACC TTTTAAAACTAAATCACATTTTCACAGAG MYCN
15 CCCCAGCCAGCGGTCCGCAACCCTTGCCGCA TCCACGAAACTTTGCCCATAGCAGCGGGC
MYCr1_F1 16 CGACTCATCTCAGCATTAAAGTGATAAAAAA
ATAAATTAAAAGGCAAGTGGACTTCGGTG MYCr1_R1 17
CTGTGGCGCGCACTGCGCGCTGCGCCAGGTT TCCGCACCAAGACCCCTTTAACTCAAGAC
MYC_r2_F1 18 TTCTACTGCGACGAGGAGGAGAACTTCTACC
AGCAGCAGCAGCAGAGCGAGCTGCAGCCC MYC_r2_F2 19
ACCGAGCTGCTGGGAGGAGACATGGTGAACC AGAGTTTCATCTGCGACCCGGACGACGAG
MYC_r2_F3 20 GCCGCCGCCTCAGAGTGCATCGACCCCTCGG
TGGTCTTCCCCTACCCTCTCAACGACAGC MYC_r2_F4 21
GGCGGCTAGGGGACAGGGGCGGGGTGGGCAG CAGCTCGAATTTCTTCCAGATATCCTCGC
MYC_r2_R1 22 AGACGAGCTTGGCGGCGGCCGAGAAGCCGCT
CCACATACAGTCCTGGATGATGATGTTTT MYC_r2_R2 23
AGGAGAGCAGAGAATCCGAGGACGGAGAGAA GGCGCTGGAGTCTTGCGAGGCGCAGGACT
MYC_r2_R3 24 TAAGAGTGGCCCGTTAAATAAGCTGCCAATG
AAAATGGGAAAGGTATCCAGCCGCCCACT MYC_r2_R4 25
TTGTATTTGTACAGCATTAATCTGGTAATTG ATTATTTTAATGTAACCTTGCTAAAGGAG
MYC_r3_F1 26 GAGGCCACAGCAAACCTCCTCACAGCCCACT
GGTCCTCAAGAGGTGCCACGTCTCCACAC MYC_r3_F2 27
AGAGGAGGAACGAGCTAAAACGGAGCTTTTT TGCCCTGCGTGACCAGATCCCGGAGTTGG
MYC_r3_F3 28 TCCAACTTGACCCTCTTGGCAGCAGGATAGT
CCTTCCGAGTGGAGGGAGGCGCTGCGTAG MYC_r3_R1 29
GCTTGGACGGACAGGATGTATGCTGTGGCTT TTTTAAGGATAACTACCTTGGGGGCCTTT
MYC_r3_R2 30 GCATTTGATCATGCATTTGAAACAAGTTCAT
AGGTGATTGCTCAGGACATTTCTGTTAGA MYC_r3_R3 31
CGCCCCGCGCCCTCCCAGCCGGGTCCAGCCG GAGCCATGGGGCCGGAGCCGCAGTGAGCA
ERBB2r1r 32 CTCTGGCCCCGCCGGCCGCGGGACCTCGGCG
GGGCATCCACAGGGCAGGGTCCCGCCGCT ERBB2r2f 33
GGCATGACTTGGAGTGAGTTTGGATGGGGTG GCCAGGTCTGAGAAGGTCCCCCGCCAGTG
ERBB2r2r 34 GCAGGGCACCTTCTTCTGCCACCCACCTGTA
AACAGAGGGCTCAGCCCAGCTGGAGGCAG ERBB2r3f 35
CCCAAGATCTCCAAGTACTGGGGAACCCCAG GGAGGCCCTGGGGGGTGGCAGTGTTCCTA
ERBB2r3r 36 CTAATGCACACAAAGCCTCCCCCTGGTTAGC
AGTGGCCCTGGTCAGCTCTGAATAACCAA ERBB2r4f 37
CTGCTCCTCTTTTAGAAGGCAGGAGGGCCCC AAGGGAAGCAGAAGGTGACAGAAGGGGAA
ERBB2r4r 38 TGGGGCAGTGGCGGGCAGGCACTGGGTTGTA
AGTTGGGAGTTTGCGGCTGGGGTCAGGCT ERBB2r5f 39
TCTGCTGCTGTTTGTGCCTCTCTCTGTTACT AACCCGTCCTCTCGCTGTTAGACATCTCT
ERBB2r5r 40 CCCACCCCTCCCATGTCACCTGTATGACACC
TGCATTCCACCCGGCCCCAGCCCTCCCCT ERBB2r6f 41
TGGGCCAGGTAGTCTCCCTAGAAGGTGATGC TGATGAGGGTCTGGTGCCCAGGGCGCCAC
ERBB2r6r 42 GGTGCCCACCCCTTGCATCCTGGGGGGTAGA
GCACATTGGGCACAAAGCAGAGGCACATA ERBB2r7f 43
CACCCTGCCTGGTACTGCCCTATTGCCCCTG GCACACCAGGGCAAAACAGCACAGTGAAA
ERBB2r7r 44 CCATTTACAGAAACAAACCTCCCCACCAAAA
TGAGAAAACTGTGTTTCTCCCTGGCACTC ERBB2r8f 45
TTATTCTTCTTGTGCCTGGGCACGGTAATGC TGCTCATGGTGGTGCACGAAGGGCCAGGG
ERBB2r8r 46 GAAGGATAGGACAGGGTGGGCTGGGCCAGGC
TGCATGCGCAGAGGGACAGGAACTGCAGC ERBB2r9f 47
GGGCCCGGACCCTGATGCTCATGTGGCTGTT GACCTGTCCCGGTATGAAGGCTGAGACGG
ERBB2r9r 48 TCTGTCTCCTGCCATCCCCAAGAGATGCTGC
CACATCTGGATCCTCAGGACTCTGTCTGC TYMSr2f 49
TCACGTCCCAGGGCAGTTTTCTTCCCTGAAG AAAGTTGGATGGCATGATCTGTCTTCCCA
TYMSr2r 50 GTGTTGAGAACAGACTACTGACTTCTAATAG
CAGCGACTTCTTTACCTTGATAAACCACA TYMSr3f 51
AAAAAAAGGATGGGTTCCATATGGGTGGTGT CAAGTGCCCACCTCCTAGCAAGTCAGCAG
TYMSr3r 52 CCCTCACAAGGTCAAAGCTATACATCAGCTC
CTGTGACATTGACTCATCCCCCAGACCTT TYMSr4f 53
AACCCACCGAGATCTGCAAACTTTGCAGGAT GCACCAGATGTCTTGTAGCCATGGGTCAA
TYMSr4r 54 TGCCTCCCTCAGGTGCCTCTGCACAAAACCA
GATTGCTTCCCTCTAAGAGTATGGTTAGT TYM Sr5f 55
GTTTTACTTTGCCTTTAGCTGTGGTCTTTCA AACCACCATCCCTCCTTATCTTCCTCTGC TYM
Sr5r 56 CTCTGCAATTTGTTTTCCCATATTAAAGAAC
TGAAGAGCTCAGTGTGGTAGGCTGGCAAG TYMSr6f 57
TTTTAAATGATGTTTTAAAGAATTGAAACTA ACATACTGTTCTGCTTTCTCCCCCGGGTT
TYMSr6r 58 CCTGCCCACCACTTCTCCCTAAACTGAAGCC
CCACATTTGGAGCAGTCATCTTTATCTTG TYMSr7f 59
GGTTGCGCTCCAATCATGTTACATAACCTAC GGCAAGGTATCGACAGGATCATACTCCTG
TYMSr7r 60 GCACAGTTACATTTGCCAGTGGCAACATCCT
TAAAAATTAATAACTGATAGGTCACGGAC TYMSr1f 61
CGTCCCGCCGCGCCACTTGGCCTGCCTCCGT CCCGCCGCGCCACTTCGCCTGCCTCCGTC
TYMSr1r 62 CTGTAAGGCGAGGAGGACGATGCGTCCCCTC
CCTCGCAGGATTGAGGTTAGGACTAAACG
[0228] Capture probe modules were pooled from stock plates,
combined with partner oligo #138 (SEQ ID NO:63)
(GTGAAAACCAGGATCAACTCCCGTGCCAGTCACAT/3BioTEG/) and diluted to a
final working concentration of 1 nM.
[0229] Genomic Samples
[0230] Commercially-purchased genomic DNA from germ line sample
NA12878 and cell line ZR75-30 was fragmented at a concentration of
10-20 ng/.mu.l to a target fragment size of 500 bp on a Covaris
sonication instrument. The DNA was purified with a 1:1
concentration of DNA purification beads and end-repaired using the
New England Biolabs (NEB) Quick blunt kit at a final concentration
of 15-30 ng/.mu.L. The germ line and cell line DNAs were blended at
ratios of 1:1, 10:1, 100:1 and 1000:1, respectively. Libraries were
constructed, purified and quantified. The sample codes, library
quantitation and inputs used for library construction are shown in
Table 2.
TABLE-US-00002 TABLE 2 Adaptors and genomic analysis of libraries
used as inputs # .mu.L genomes/ desired into Admix Adaptor code
.mu.l genomes PCR 1:1 NNNNNNNNCATGGCCGCA 55 200 4 GG (SEQ ID NO:
64) 10:1 NNNNNNNNATCTTAGTGG 66 200 3 CA (SEQ ID NO: 65) 100:1
NNNNNNNNCGGAACTCGG 64 1000 16 AG (SEQ ID NO: 66) 1000:1
NNNNNNNNGACTCCGATC 77 10000 130 CC (SEQ ID NO: 67)
[0231] Genomic libraries were pooled, denatured, combined with
probe, hybridized and washed. The washed capture probe-tagged
genomic library complexes were amplified with forward and reverse
full-length primers, purified, and size-selected for 225-600 bp
fragments on a Pippin-prep instrument. Finally, the captured
material was sequenced using a 150-V3 Illumina sequencing kit.
Results
[0232] The paired capture probes that target BRAF (in two loci),
MYCN and CDH1 were used to analyze the SNVs in these loci. The
results are shown in Table 3.
TABLE-US-00003 TABLE 3 Bioinformatic summary ##STR00001##
##STR00002##
[0233] Column 3 shows the total number unique read counts, which in
turn provide bounds on the sensitivity of the assay. The estimated
and measured genomic inputs were well within range of one another.
The lightly shaded boxes highlight the SNV where the cell line
sequence differed from the germ line sequence. In the absence of
unique read filtering--shown on the right portion of the
table--random base changes at these four selected positions
occurred with measurable, non-zero frequencies. FIG. 1. By
requiring that changes occur within unique read families, it became
possible to sort true signal from error-prone noise. FIG. 2.
Example 2
A Novel Probe Design Effective for Comprehensive Sequencing of
Target Regions in Highly Fragmented gDNA
Purpose
[0234] The purpose of these experiments is to develop an assay
system to reliably and reproducibly interrogate circulating
DNAs.
Background
[0235] Analysis of circulating DNA from body fluids represents an
exciting, but as yet, unrealized opportunity in molecular
diagnostics. Genomic DNA is highly intact. Literature suggest that
the average size of circulating DNA is about 150 bp, which
correlates well to the size of DNAs wrapped around a single
nucleosomal histone complex.
Summary
[0236] The technical parameters of targeted sequence capture
technology contemplated herein were designed to accommodate highly
fragmented DNA and to retain the ability to generate comprehensive
sequence coverage of targeted DNA. Capture probe density was
increased and the length of capture probe sequences was reduced
from 60 nucleotide to 40 nucleotide to minimize uninformative
sequence generation in the clone library. The human genome is
littered with repetitive sequences and drastic fluctuations in base
composition, thus, the suitability of implementing higher capture
probe densities and shorter capture probes could not be conceded
but required empirical validation of the new assay.
[0237] Conditions were established in which the shorter 40 mer
capture probe sequences exhibit reliable and robust assay
performance. In a first set of experiments, the assays were used to
query two large regions--the coding regions for the tumor
suppressor gene TP53 and the long, contiguous, intron 19 of the ALK
oncogene, both of which are central to cancer diagnostics. In a
second set of experiments, several high density pairwise capture
probes that possess shorter 40 nucleotide capture probe sequences
were used to interrogate known SNVs that reside in the NCI-H69 cell
line.
[0238] The new high density shorter capture probes were
successfully used to query short fragmented DNAs and the results
indicated that the assay design is well suited to sequencing of
circulating DNAs that are found in the plasma fraction of
blood.
Methods--Modified 40 Mer Capture Probes
[0239] The capture probe sequences used to empirically validate the
performance of the 40 mer capture probes are shown in Table 4.
TABLE-US-00004 SEQ ID Name NO: Sequence 60 mer Capture Probes
PLP1_ex2_ 68 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGGTTTGAGT F
GGCATGAGCTACCTACTGGATGTGCCTGACTGTTTCCCCTTCTTCT TCCC PLP1_ex2_ 69
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTATCTCCAG R
GATGGAGAGAGGGAAAAAAAAGATGGGTCTGTGTGGGAGGGCA7 0GGTACTT PLP1_ex3_ 70
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAAAGAAGCC F
AGGTCTTCAATTAATAAGATTCCCTGGTCTCGTTTGTCTACCTGTT AATG PLP1_ex3_ 71
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCAGACTCGCG M
CCCAATTTTCCCCCACCCCTTGTTATTGCCACAAAATCCTGAGGAT GATC CYP2D6_F 72
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAAGCACCTAG
CCCCATTCCTGCTGAGCAGGAGGTGGCAGGTACCCCAGACTGGGA GGTAA CYP2D6_R 73
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGTCGGTGGG
GCCAGGATGAGGCCCAGTCTGTTCACACATGGCTGCTGCCTCTCA GCTCT chrX_15_ 74
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTGGCCCTC F
AGCCAGTACAGAAAGTCATTTGTCAAGGCCTTCAGTTGGCAGACG TGCTC chrX_15_ 75
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGAATTCATT R
GCCAGCTATAAATCTGTGGAAACGCTGCCACACAATCTTAGCACA CAAGA chrX_69_ 76
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTACTTCCCTC F
CAGTTTTGTTGCTTGCAAAACAACAGAATCTTCTCTCCATGAAATC ATG chrX_69_ 77
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCAGGGGTATC R
TATTATCCCCATTTTCTCACAAAGGAAACCAAGATAAAAGGTTTA AATGG KRAS_ex1_ 78
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGTTACCTTTA F
AAAGACATCTGCTTTCTGCCAAAATTAATGTGCTGAACTTAAACT TACC KRAS_ex1_ 79
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTCCCAGTAA R
ATTACTCTTACCAATGCAACAGACTTTAAAGAAGTTGTGTTTTAC AATGC KRAS_ex2_ 80
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTAAATGACAT F
AACAGTTATGATTTTGCAGAAAACAGATCTGTATTTATTTCAGTGT TACT KRAS_ex2_ 81
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGACAGGTTTT R
GAAAGATATTTGTGTTACTAATGACTGTGCTATAACTTTTTTTTCT TTCC MYC_r2_ 82
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTGTGGCGCG F1
CACTGCGCGCTGCGCCAGGTTTCCGCACCAAGACCCCTTTAACTC AAGAC MYC_r2_ 83
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGCGGCTAGG R1
GGACAGGGGCGGGGTGGGCAGCAGCTCGAATTTCTTCCAGATATC CTCGC MYC_r2_ 84
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACACCGAGCTGC F3
TGGGAGGAGACATGGTGAACCAGAGTTTCATCTGCGACCCGGAC GACGAG MYC_r2_ 85
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGGAGAGCAG R3
AGAATCCGAGGACGGAGAGAAGGCGCTGGAGTCTTGCGAGGCGC AGGACT SRY_r1_F 86
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTGTAAGTTA
TCGTAAAAAGGAGCATCTAGGTAGGTCTTTGTAGCCAATGTTACC CGATT SRY_r1_ 87
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAATGGCCATT M3
CTTCCAGGAGGCACAGAAATTACAGGCCATGCACAGAGAGAAAT ACCCGA VHL_r3_F 88
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTTGTTCGTTC
CTTGTACTGAGACCCTAGTCTGCCACTGAGGATTTGGTTTTTGCCC TTC VHL_r3_R 89
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATCAAGACTC
ATCAGTACCATCAAAAGCTGAGATGAAACAGTGTAAGTTTCAACA GAAAT UGT1A1_ 90
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGTGTCCAGC r_4F
TGTGAAACTCAGAGATGTAACTGCTGACATCCTCCCTATTTTGCAT CTCA UGT1A1_ 91
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATTTGAAACA r_4R
ATTTTATCATGAATGCCATGACCAAAGTATTCTTCTGTATCTTCTT TCTT TNFRSF14_ 92
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGATGGGTGG r3_F
GCTCCCGAAGGGGCCTCCCGCAGACTTGCGAAGTTCCCACTCTCT GGGCG TNFRSF14_ 93
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCAGGGTGCGG r3_R
GGGCATCCAGGCTGCCCAAGCGGAGGCTGGGCCGGCTGTGCTGG CCTCTT RUNX1r4_ 94
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTTTGAAATGT F
GGGTTTGTTGCCATGAAACGTGTTTCAAGCATAGTTTTGACAGAT AACG RUNX1r4_ 95
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGCCCTAAAA R
GTGTATGTATAACATCCCTGATGTCTGCATTTGTCCTTTGACTGGT GTTT RHD_r5_ 96
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAACCCCTCGA F
GGCTCAGACCTTTGGAGCAGGAGTGTGATTCTGGCCAACCACCCT CTCTG RHD_r5_ 97
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCATAAATATG R
TGTGCTAGTCCTGTTAGACCCAAGTGCTGCCCAAGGGCAGCGCCC TGCTC PTEN_r5_ 98
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTACTTGTTAAT F
TAAAAATTCAAGAGTTTTTTTTTCTTATTCTGAGGTTATCTTTTTAC CA PTEN_r5_ 99
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCAAAATCTG R
TTTTCCAATAAATTCTCAGATCCAGGAAGAGGAAAGGAAAAACA TCAAAA EP300r18_ 100
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATACTCCATCT F
CCCGTAAAAATAGTGAGACTTGAGTAATGTTTGATGTCACTTGTC TTTC EP300r18_ 101
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCAGTCACCAC R
TATATTATTCTAGGTATCCCAGAAAAGTTAAAGTCAAATCTGAAA CACAT VHL_r1_F 102
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCGCCCCGCGT
CCGACCCGCGGATCCCGCGGCGTCCGGCCCGGGTGGTCTGGATCG CGGAG VHL_r1_R 103
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCATACGGGC
AGCACGACGCGCGGACTGCGATTGCAGAAGATGACCTGGGAGGG CTCGCG VHL_r1_ 104
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTAGAGGGGCT M1
TCAGACCGTGCTATCGTCCCTGCTGGGTCGGGCCTAAGCGCCGGG CCCGT VHL_r1_ 105
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGCGCCGAGG M2
AGGAGATGGAGGCCGGGCGGCCGCGGCCCGTGCTGCGCTCGGTG AACTCG VHL_r2_F 106
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGTGTGGGCC
ACCGTGCCCAGCCACCGGTGTGGCTCTTTAACAACCTTTGCTTGTC CCGA VHL_r2_ 107
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAAGTGGTCTA R
TCCTGTACTTACCACAACAACCTTATCTTTTTAAAAAGTAAAACGT CAGT VHL_r3_F 108
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTTGTTCGTTC
CTTGTACTGAGACCCTAGTCTGCCACTGAGGATTTGGTTTTTGCCC TTC VHL_r3_R 109
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATCAAGACTC
ATCAGTACCATCAAAAGCTGAGATGAAACAGTGTAAGTTTCAACA GAAAT 40 mers
PLP1_ex2_ 110 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACACCTACTGGA F_40
TGTGCCTGACTGTTTCCCCTTCTTCTTCCC PLP1_ex2_ 111
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGGAAAAAAA R_40
AGATGGGTCTGTGTGGGAGGGCAGGTACTT PLP1_ex3_ 112
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTAATAAGAT F_40
TCCCTGGTCTCGTTTGTCTACCTGTTAATG PLP1_ex3_ 113
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCCCACCCCTT M_40
GTTATTGCCACAAAATCCTGAGGATGATC CYP2D6_ 114
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCTGAGCAGG F40
AGGTGGCAGGTACCCCAGACTGGGAGGTAA CYP2D6_ 115
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGCCCAGTCT R_40
GTTCACACATGGCTGCTGCCTCTCAGCTCT chrX_15_ 116
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAAAGTCATT F40
TGTCAAGGCCTTCAGTTGGCAGACGTGCTC chrX_15_ 117
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAATCTGTGGA R_40
AACGCTGCCACACAATCTTAGCACACAAGA chrX_69_ 118
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGCTTGCAAA F40
ACAACAGAATCTTCTCTCCATGAAATCATG chrX_69_ 119
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATTTTCTCACA R_40
AAGGAAACCAAGATAAAAGGTTTAAATGG KRAS_ex1_ 120
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGCTTTCTGCC F_40
AAAATTAATGTGCTGAACTTAAACTTACC KRAS_ex1_ 121
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCAATGCAAC R_40
AGACTTTAAAGAAGTTGTGTTTTACAATGC KRAS_ex2_ 122
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATTTTGCAGA F_40
AAACAGATCTGTATTTATTTCAGTGTTACT KRAS_ex2_ 123
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGTGTTACTA R_40
ATGACTGTGCTATAACTTTTTTTTCTTTCC MYC_r2_ 124
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGCGCCAGGT F140
TTCCGCACCAAGACCCCTTTAACTCAAGAC MYC_r2_ 125
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGGGTGGGCA R140
GCAGCTCGAATTTCTTCCAGATATCCTCGC MYC_r2_ 126
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCATGGTGAAC F340
CAGAGTTTCATCTGCGACCCGGACGACGAG MYC_r2_ 127
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGACGGAGAGA R340
AGGCGCTGGAGTCTTGCGAGGCGCAGGACT SRY_r1_F 128
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAGCATCTAG 40
GTAGGTCTTTGTAGCCAATGTTACCCGATT SRY_r1_ 129
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCACAGAAAT M340
TACAGGCCATGCACAGAGAGAAATACCCGA VHL_r3_F 130
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGACCCTAGT 40
CTGCCACTGAGGATTTGGTTTTTGCCCTTC VHL_r3_ 131
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTCAAAAGCTG R_40
AGATGAAACAGTGTAAGTTTCAACAGAAAT UGT1A1_ 132
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGAGATGTAA r_4F_40
CTGCTGACATCCTCCCTATTTTGCATCTCA UGT1A1_ 133
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAATGCCATG r_4R_40
ACCAAAGTATTCTTCTGTATCTTCTTTCTT TNFRSF14_ 134
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGGCCTCCCG r3_F_40
CAGACTTGCGAAGTTCCCACTCTCTGGGCG TNFRSF14_ 135
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCTGCCCAAG
r3_R_40 CGGAGGCTGGGCCGGCTGTGCTGGCCTCTT RUNX1r4_ 136
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCCATGAAAC F_40
GTGTTTCAAGCATAGTTTTGACAGATAACG RUNX1r4_ 137
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAACATCCCTG R_40
ATGTCTGCATTTGTCCTTTGACTGGTGTTT RHD_r5_ 138
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTTGGAGCAG F40
GAGTGTGATTCTGGCCAACCACCCTCTCTG RHD_r5_ 139
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTGTTAGACC R_40
CAAGTGCTGCCCAAGGGCAGCGCCCTGCTC PTEN_r5_ 140
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAAGAGTTTTTT F40
TTTCTTATTCTGAGGTTATCTTTTTACCA PTEN_r5_ 141
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAATTCTCAGA R_40
TCCAGGAAGAGGAAAGGAAAAACATCAAAA EP300r18_ 142
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATAGTGAGAC F_40
TTGAGTAATGTTTGATGTCACTTGTCTTTC EP300r18_ 143
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTAGGTATCCC R_40
AGAAAAGTTAAAGTCAAATCTGAAACACAT VHL_r1_F 144
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGATCCCGCGG 40
CGTCCGGCCCGGGTGGTCTGGATCGCGGAG VHL_r1_ 145
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCGGACTGCG R_40
ATTGCAGAAGATGACCTGGGAGGGCTCGCG VHL_r1_ 146
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTATCGTCCCT M140
GCTGGGTCGGGCCTAAGCGCCGGGCCCGT VHL_r1_ 147
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGCCGGGCGG M240
CCGCGGCCCGTGCTGCGCTCGGTGAACTCG VHL_r2_F 148
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCCACCGGTG 40
TGGCTCTTTAACAACCTTTGCTTGTCCCGA VHL_r2_ 149
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACACCACAACAA R_40
CCTTATCTTTTTAAAAAGTAAAACGTCAGT VHL_r3_F 150
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGACCCTAGT 40
CTGCCACTGAGGATTTGGTTTTTGCCCTTC VHL_r3_ 151
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTCAAAAGCTG R_40
AGATGAAACAGTGTAAGTTTCAACAGAAAT
[0240] The performance of 40 mer capture probes was compared to
that of 60 mer capture probes. The 40 mer was designed from the 60
mer by removing 20 nucleotides from the 5' end of the 60 mer.
Although the 3' end of both capture probe sets are identical with
respect to the sequences that are copied from captured genomic
clones, the probe sequence signature (Read 2 of the paired end
read) is different between the 60 mer and 40 mer probe sets. This
design is useful because it allows the capture probes to be
multiplexed during sequencing and their performance subsequently
analyzed during downstream bioinformatics deconvolution.
[0241] Genomic Samples
[0242] A pool of 12 genomic DNA samples (chosen from a Coriell
human panel of 112 human genomic DNAs) was used as the target DNA.
The 12 samples were broken into four sets of four samples each, as
shown in detail in Table 5.
TABLE-US-00005 Capture Wash Sample probes temp. Code Samples 60mer
50 C. AAT GM20291 M Americas AFRICAN ANCESTRY IN SOUTHWEST USA CTA
GM19373 M WAfrican LUHYA IN WEBUYE, KENYA GGG HG00428 F AsianE HAN
CHINESE SOUTH TCC HG01624 M Euro IBERIAN POPULATIONS IN SPAIN 40mer
50 C. AAT GM20291 M Americas AFRICAN ANCESTRY IN SOUTHWEST USA CTA
GM19373 M WAfrican LUHYA IN WEBUYE, KENYA GGG HG00428 F AsianE HAN
CHINESE SOUTH TCC HG01624 M Euro IBERIAN POPULATIONS IN SPAIN 60mer
47 C. AGA HG02489 M Americas AFRICAN CARIBBEAN IN BARBADOS CCT
HG01108 F Americas PUERTO RICAN IN PUERTO RICO GAC GM19011 F AsianE
JAPANESE IN TOKYO, JAPAN TTG GM18946 F AsianE JAPANESE IN TOKYO,
JAPAN 40mer 47 C. AGA HG02489 M Americas AFRICAN CARIBBEAN IN
BARBADOS CCT HG01108 F Americas PUERTO RICAN IN PUERTO RICO GAC
GM19011 F AsianE JAPANESE IN TOKYO, JAPAN TTG GM18946 F AsianE
JAPANESE IN TOKYO, JAPAN 60mer 44 C. ATC NA13783 F NA13783 GM13783
CAG HG03700 F AsianS PUNJABI IN LAHORE, PAKISTAN GCA HG03367 M
WAfrican ESAN FROM NIGERIA TGT NA22991 F NA22991 GM22991 40mer 44
C. ATC NA13783 F NA13783 GM13783 CAG HG03700 F AsianS PUNJABI IN
LAHORE, PAKISTAN GCA HG03367 M WAfrican ESAN FROM NIGERIA TGT
NA22991 F NA22991 GM22991
[0243] Hybridization, Washing and Sequencing
[0244] Six different hybridization conditions were used to
hybridize the 60 mer and 40 mer probes to the genomic target
DNA:
[0245] 1) 60mer probes washed at 50.degree. C.
[0246] 2) 40mer probes washed at 50.degree. C.
[0247] 3) 60mer probes washed at 47.degree. C.
[0248] 4) 40mer probes washed at 47.degree. C.
[0249] 5) 60mer probes washed at 44.degree. C.
[0250] 6) 40mer probes washed at 44.degree. C.
For each experiment, the capture probe oligos were combined with
partner oligo; the final concentration of duplex capture probe was
1 nM for each capture probe.
[0251] Each hybridization reaction had .about.2.5 .mu.g of genomic
library in 40 .mu.l total volume. Each sample was heated to
98.degree. C. for 2 min then cooled on ice. 20 .mu.l of capture
probe and 90 .mu.l of hybridization buffer were added and the
hybridization mix was incubated for 24 hours starting at 80.degree.
C. and decreasing one degree every 48 minutes to 50.degree. C. The
complexes were bound to 20 ul of streptavidin beads in 1 mL total
volume of TEzero buffer+0.05% Tween20 (TT). The beads were washed 3
times, 5 min each with 200 ul of TT, and once at 45.degree. C. for
5 min in wash buffer. The beads were then washed with TEzero and
each reaction was resuspended in 20 .mu.l TEzero. The complexes
were then PCR amplified with full length forward (ACA2_FLFP; SEQ ID
NO:152; AATGATACGGCGACCACCGAGATCTACACGTCATGCAGGACCAGAGAATTCGA
ATACA) and full length reverse (CAC3_FLRP; SEQ ID NO:153;
CAAGCAGAAGACGGCATACGAGATGTGACTGGCACGGGAGTTGATCCTGGTTT TCAC)
primers.
[0252] Following amplification and purification, the resulting
product masses were measured and equal masses were pooled for
sequencing.
Results--Modified 40Mer Primers
[0253] The capture probe performance as a function of length and
wash temperature is shown graphically in FIG. 3. Overall, the 40
mer capture probes performed as well as the 60 mer capture probes
with 44.degree. C. and 47.degree. C. washes. With the 50.degree. C.
wash, the 40 mer capture probes exhibit sporadic behavior. These
data empirically validate the use of 40 mer capture probes and wash
temperatures in the 44.degree. C. to 47.degree. C. range when using
these reagents.
Methods--High Density 40 Mers
[0254] In general, sequence capture probes are designed using
specific "rules." For example, regions of redundant sequence or
that exhibit extreme base composition biases are generally avoided.
One key implication of the requirement for high probe density and
close spacing of probes along target regions is that there is
little or no latitude to move probes in order to accommodate any
such probe design rules. In this study, probes were designed based
solely on their position relative to one another with no
consideration of probe binding sequences; thus, use of this high
density approach required empirically validating that the
hybridization and processing methods would accommodate such a
collection of probes.
[0255] The human ALK gene encodes a protein kinase important in
early development, but normal ALK gene expression is essentially
undetectable in normal adults. Oncogenic ALK fusions are created
when intron 19 of ALK undergoes illegitimate recombination to fuse
the kinase encoding portion of ALK to the 5' end of another gene.
Such gene fusions often cause ectopic expression of the ALK kinase,
which in turn is important in driving the inappropriate cell
proliferation observed in pulmonary tumors. In lung cancer, this
"other gene" is often EML4, but other fusion partners have also
been detected. To create an assay that can detect any possible ALK
gene fusion event, 40 nucleotide probes were designed that were
placed at 80 nucleotide intervals in intron 19 of ALK. These probes
were oriented such that they are antisense relative to the gene
(FIG. 4). This means that their 3' terminus extends and copies
genic regions that are 5' to their hybridization site. When fusion
genes are present, probe extension from probes positioned near the
fusion junction copy junction sequences. The DNA sequences
resulting from these junction clones have fusion partner sequences
at their 5' end, the fusion junction sequence, and ALK intron 19
sequences at their 3' ends (FIG. 4B).
[0256] Another important diagnostic target in cancer is the TP53
gene. It encodes a tumor suppressor, and it is often inactivated by
mutations in cancers. Mutations that can inactivate gene function
are scattered throughout the gene, and hence conclusive
sequence-based assays for TP53 inactivating mutations must address
the entire coding region and untranslated regions (UTRs) of the
gene. Because circulating DNA fragments are short, high density
probes were used to interrogate all target regions of the TP53
gene. Unlike ALK, probes for TP53 are placed in both possible
orientations (FIG. 5). At high probe densities, the cumulative
coverage from multiple probes provides uniform deep sequencing
coverage of target regions.
[0257] The collection of 105 probes used in this study is shown in
Table 6. In addition to probes that target the fusion-prone region
of ALK and the coding regions of TP53, probes that cover known SNVs
in the cell line DNA were also included.
TABLE-US-00006 TABLE 6 SEQ Name_target region ID NO: Probe sequence
ALK_chr2:29446208_ 154 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCGAAT
fusion_f GAGGGTGATGTTTTTCCGCGGCACCTCCTTCAGGT ALK_chr2:29446288_ 155
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGTTGT fusion_f
AGTCGGTCATGATGGTCGAGGTGCGGAGCTTGCTC ALK_chr2:29446368_ 156
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCAGC fusion_f
TCCTGGTGCTTCCGGCGGTACACTGCAGGTGGGTG ALK_chr2:29446448_ 157
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTACA fusion_f
CAGGCCACTTCCTACAGGAAGCCTCCCTGGATCTC ALK_chr2:29446528_ 158
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAAAT fusion_f
ACTAATAAAATGATTAAAGAAGGTGTGTCTTTAAT ALK_chr2:29446608_ 159
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTATAT fusion_f
GGAAAATAATTATTTGTATTATATAGGGCAGAGTC ALK_chr2:29446688_ 160
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATTAG fusion_f
ACCCAATATGGTCTGCAGATTTTATTAGAAGAAAT ALK_chr2:29446768_ 161
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGTGAA fusion_f
CCAGCAGACTGTGTTGCAAGTATAACCCCACGTGA ALK_chr2:29446848_ 162
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCCAT fusion_f
GGAGCCTAAGGAAGTTTCAGCAAGGCCCTAAGGGG ALK_chr2:29446928_ 163
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCCAG fusion_f
GAATTGGCCTGCCTTAGTATTTCTGCTGTGCTCAG ALK_chr2:29447008_ 164
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTTGA fusion_f
GGGTGCAGCTGGGATCTTGGTCAGTTGTGTTTCCT ALK_chr2:29447088_ 165
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCACAT fusion_f
CATGAAAAGATCTCTGAATTGGTGTCTGGGGATCT ALK_chr2:29447168_ 166
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGAGG fusion_f
ACCAGGTCACAGGACCTCTTTGGACTGCAGTTTCC ALK_chr2:29447248_ 167
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTAACC fusion_f
ACTGCCACTCCCCACCCTCTAGGGTTGTCAATGAA ALK_chr2:29447328_ 168
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAGCT fusion_f
CTACCAATGTGAGTGACCATTATCACTCCTACATG ALK_chr2:29447408_ 169
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAAAAT fusion_f
TGTGATTCAGTGGGTAGATTCTGTGTGTAAAGCCC ALK_chr2:29447488_ 170
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTATGT fusion_f
GCTCAGTTCCCTCCTCTATGCAATGGACCGACCGT ALK_chr2:29447568_ 171
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGTGTA fusion_f
AATTGCCGAGCACGTAGTAACCATGCAACAAGTGT ALK_chr2:29447648_ 172
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGGGG fusion_f
ACACAGTGTGTGCTGCCATCTCCCTTCTACCGGCA ALK_chr2:29447728_ 173
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAAGAG fusion_f
CCTTTCCCTCTGCCCTTTTCAAGCCTCTGCCCATC ALK_chr2:29447808_ 174
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGACCA fusion_f
CACTGAGTTCTCTGTGACCTGCAGGTCAGCTCACC ALK_chr2:29447888_ 175
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTTCCT fusion_f
ATCTCTCTGCCTGGAGGGTGGTGGAGGGCTGGTT ALK_chr2:29447968_ 176
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAAACA fusion_f
GGAGCTGCGCCGGTGGAAGCATGTGGGAGCTAGAA ALK_chr2:29448048_ 177
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGACA fusion_f
CTGAAGGAGCTCCCCACCCCCTGATCAGCCAGGAG ALK_chr2:29448128_ 178
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGGAA fusion_f
CTGCAGCTGCTCTGGTGGGGGGAAGGTTGGGAGCT ALK_chr2:29448208_ 179
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACACCCA fusion_f
ATTCCAGGGACTAGCATAACGAAGTGACACCTTGG ALK_chr2:29448288_ 180
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTGC fusion_f
CCCCTTGGGAGTCCCTGGGGCTCTGTGCACTCACC MYCNr1f_40 181
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGAAG
CACCCCCGGTATTAAAACGAACGGGGCGGAAAGAA MYCNr1r_40 182
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTAAC
AAAGGGGACGCGACCCGGGGTCCAGTGCCCCAGGG MYCNr1f2_40 183
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTGG
GGGGACTGGGTGGCCTCACCCCCAACCCGGTCATC MYCNr1r2_40 184
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCGCGC
TCCAGCTTCTCGCGGGCGGAGAAGCCGCTCCACAT MYCNr1f3_40 185
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCCAC
CCGGCCGCCGAGTGCGTGGATCCCGCCGTGGTCTT MYCNr1r3_40 186
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGGCA
CGGGCGCTGGCTCGCGCTTGTTCACGGGAAAGGGG MYCNr2f_40 187
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAACAT
GGATATATATGTGAATTTCATTCAAATGGTTCTCA MYCNr2r_40 188
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTAAAC
CAACATTCTTAATGTCAACACAATGTTTGTTTAAA MYCNr2f2_40 189
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCCTA
CGTGGAGAGTGAGGATGCACCCCCACAGAAGAAGA MYCNr2r2_40 190
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATGAC
ACTCTTGAGCGGACGTGGGGACGCCTCGCTCTTTA MYCNr2f3_40 191
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTCTCA
CGCTCAGGGACCACGTGCCGGAGTTGGTAAAGAAT MYCNr2r3_40 192
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCAGTG
GCCTTTTTCAAAATGACCACCTTGGCGGCCTTCTC TP53_chr17:7579779: 193
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCTAG region_1:75nt:-59:-20:f
GGGGCTGGGGTTGGGGTGGGGGTGGTGGGCCTGCC TP53_chr17:7579838: 194
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCAGTT region_1:75nt:1:40:f
TCCATAGGTCTGAAAATGTTTCCTGACTCAGAGGG TP53_chr17:7579878: 195
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTGCC region_1:75nt:41:+5:r
ATGGAGGAGCCGCAGTCAGATCCTAGCGTCGAGCC TP53_chr17:7579932: 196
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTCATG region_1:75nt:+20:+59:r
CTGGATCCCCACTTTTCCTCTTGCAGCAGCCAGAC TP53_chr17:7579640: 197
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGCCC region_2:23nt:-59:-20:f
CCCAGCCCTCCAGGTCCCCAGCCCTCCAGGTCCCC TP53_chr17:7579741: 198
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCAGA region_2:23nt:+20:+59:r
GACCTGTGGGAAGCGAAAATTCCATGGGACTGACT TP53_chr17:7579252: 199
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCAGG region_3:280nt:-59:-20:f
GGGATACGGCCAGGCATTGAAGTCTCATGGAAGCC TP53_chr17:7579311: 200
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCGTG region_3:280111:1:40:f
CAAGTCACAGACTTGGCTGTCCCAGAATGCAAGAA TP53_chr17:7579351: 201
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCAGA region_3:280nt:41:80:r
AAACCTACCAGGGCAGCTACGGTTTCCGTCTGGGC TP53_chr17:7579391: 202
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAAGG region_3:280nt:81:120:f
GACAGAAGATGACAGGGGCCAGGAGGGGGCTGGTG TP53_chr17:7579431: 203
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGTGGC region_3:280nt:121:160:r
CCCTGCACCAGCAGCTCCTACACCGGCGGCCCCTG TP53_chr17:7579471: 204
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGGGG region_3:280n-1:161:200:f
GAGCAGCCTCTGGCATTCTGGGAGCTTCATCTGGA TP53_chr17:7579511: 205
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCCCG region_3:280nt:201:240:r
GACGATATTGAACAATGGTTCACTGAAGACCCAGG TP53_chr17:7579610: 206
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTGGG region_3:280nt:020:+59:r
GGGCTGGGGGGCTGAGGACCTGGTCCTCTGACTGC TP53_chr17:7578327: 207
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTGG region_4:185nt:-43:-4:f
GCAACCAGCCCTGTCGTCTCTCCAGCCCCAGCTGC TP53_chr17:7578370: 208
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCATC region_4:185111:1:40:f
GCTATCTGAGCAGCGCTCATGGTGGGGGCAGCGCC TP53_chr17:7578410: 209
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGCCAT region_4:185n1:41:80:r
CTACAAGCAGTCACAGCACATGACGGAGGTTGTGA TP53_chr17:7578450: 210
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCATGG region_4:185n1:81:120:f
CGCGGACGCGGGTGCCGGGCGGGGGTGTGGAATCA TP53_chr17:7578490: 211
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTTGC region_4:185n1:121:160:r
CAACTGGCCAAGACCTGCCCTGTGCAGCTGTGGGT TP53_chr17:7578574: 212
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGCTTT region_4:185nt:+20:+59:r
ATCTGTTCACTTGTGCCCTGACTTTCAACTCTGT TP53_chr17:7578117: 213
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAGGG region_5:114nt:-59:-20:f
CCACTGACAACCACCCTTAACCCCTCCTCCCAGAG TP53_chr17:7578176: 214
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTCA region_5:114111:1:40:f
GGCGGCTCATAGGGCACCACCACACTATGTCGAAA TP53_chr17:7578216: 215
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGGAA region_5:114nt:41:80:r
ATTTGCGTGTGGAGTATTTGGATGACAGAAACACT TP53_chr17:7578292: 216
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCAGG region_5:114nt:+3:+42:r
GTCCCCAGGCCTCTGATTCCTCACTGATTGCTCTT TP53_chr17:7577439: 217
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAGGC region_6:111nt:-59:-20:f
AAGCAGAGGCTGGGGCACAGCAGGCCAGTGTGCAG TP53_chr17:7577498: 218
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTGG region_6:111nt:1:40:f
AGTCTTCCAGTGTGATGATGGTGAGGATGGGCCTC TP53_chr17:7577538: 219
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACACTAC region_6:111nt:41:80:r
ATGTGTAACAGTTCCTGCATGGGCGGCATGAACCG TP53_chr17:7577628: 220
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTTGC region_6:111nt:+20:+59:r
CACAGGTCTCCCCAAGGCGCACTGGCCTCATCTTG TP53_chr17:7576974: 221
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTGCA region_7:138nt:-44:-5:f
CCCTTGGTCTCCTCCACCGCTTCTTGTCCTGCTTG TP53_chr17:7577018: 222
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTCG region_7:138nt:1:40:f
CTTAGTGCTCCCTGGGGGCAGCTCGTGGTGAGGCT TP53_chr17:7577058: 223
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGACCG region_7:138nt:41:80:r
GCGCACAGAGGAAGAGAATCTCCGCAAGAAAGGGG TP53_chr17:7577098: 224
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTCTCC region_7:138n1:81:120:f
CAGGACAGGCACAAACACGCACCTCAAAGCTGTTC TP53_chr17:7577138: 225
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTCTCTT region_7:138n1:121:+22:r
TTCCTATCCTGAGTAGTGGTAATCTACTGGGACG TP53_chr17:7577175: 226
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGACA region_7:138nt:+20:+59:r
GGTAGGACCTGATTTCCTTACTGCCTCTTGCTTCT TP53_chr17:7576793: 227
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGCAT region_8:75nt:-59:-20:f
TTTGAGTGTTAGACTGGAAACTTTCCACTTGATAA TP53_chr17:7576852: 228
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTGA region_8:75nt:1:40:f
AGGGTGAAATATTCTCCATCCAGTGGTTTCTTCTT TP53_chr17:7576892: 229
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTAG region_8:75nt:41:+5:r
CACTGCCCAACAACACCAGCTCCTCTCCCCAGCCA TP53_chr17:7576931: 230
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGCCT region_8:75nt:+5:+44:r
CAGATTCACTTTTATCACCTTTCCTTGCCTCTTTC TP53_chr17:7573867: 231
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACATGGC region_9:108nt:-59:-20:f
TTTCCAACCTAGGAAGGCAGGGGAGTAGGGCCAGG TP53_chr17:7573926: 232
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTGG region_9:108nt:1:40:f
AGTGAGCCCTGCTCCCCCCTGGCTCCTTCCCAGCC TP53_chr17:7573966: 233
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTCCGA region_9:108nt:41:80:r
GAGCTGAATGAGGCCTTGGAACTCAAGGATGCCCA TP53_chr17:7574053: 234
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCATCT region_9:108nt:+20:+59:r
TTTAACTCAGGTACTGTGTATATACTTACTTCTCC TP53_chr17:7572867: 235
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGCAG region_10:83nt:-59:-20:f
GGGAGGGAGAGATGGGGGTGGGAGGCTGTCAGTGG
TP53_chr17:7572926: 236 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGTCAG
region_10:83nt:1:40:f TCTGAGTCAGGCCCTTCTGTCTTGAACATGAGTTT
TP53_chr17:7572966: 237 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCTGA
region_10:83nt:41:80:r AGTCCAAAAAGGGTCAGTCTACCTCCCGCCATAAA
TP53_chr17:7573028: 238 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGCAC
region_10:83nt:+20:+59:r AGACCCTCTCACTCATGTGATGTCATCTCTCCTCC
ALDH4A1_chr1:1919 239 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCAGGG
9369_rs61757683:G:T:f GCTTATGTGTCTCCTTGATGACCTGCGGCGACGTC
ALDH4A1_chr1:1919 240 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCATC
9488_rs61757683:G:T:r ATCTCCTCCCTTCCCCTTCTGCCCAGGCTGTTGCA
BRCA1_chr17:412230 241 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAATTC
15_rs1799966:T:A,C:f TGGCTTCTCCCTGCTCACACTTTCTTCCATTGCAT
BRCA1_chr17:412231 242 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGTCAG
34_rs1799966:T:A,C:r CTCGTGTTGGCAACATACCATCTTCAACCTCTGCA
BRCA1_chr17:412439 243 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTAATT
21_rs16942:T:C:f TCTTGGCCCCTCTTCGGTAACCCTGAGCCAAATGT
BRCA1_chr17:412440 244 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGTGA
40_rs16942:T:C:r AATAAAGGAAGATACTAGTTTTGCTGAAAATGACA
BRCA2_chr13:329066 245 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACACTCA
70_rs144848:A:C:f TTTGTATCTGAAGTGGAACCAAATGATACTGATCC
BRCA2_chr13:329067 246 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGTTG
69_rs144848:A:C:r AGACCATTCACAGGCCAAAGACGGTACAACTTCCT
CDKN2A_chr9:21970 247 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGAAAA
837_rs3731249:C:T:f TGAATGCTCTGAGCTTTGGAAGCTCTCAGGGTACA
CDKN2A_chr9:21970 248 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGGGCC
956_rs3731249:C:T:r ATCGCGATGTCGCACGGTACCTGCGCGCGGCTGCG
DPYD_chr1:97981316_ 249 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCCCA
rs1801159:T:C:f TCCAGCTTCAAAAGCTCTTCGAATCATTGATGTGC
DPYD_chr1:97981435_ 250 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTGCCA
rs1801159:T:C:r AGCCTGAACTACCCCTCTTTTACACTCCTATTGAT
EPHX1_chr1:2260263 251 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCCACC
27_rs2234922:A:G:f CTGACTGTGCTCTGTCCCCCCAGGGCTGGACATCC
EPHX1_chr1:2260264 252 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACAGTCA
46_rs2234922:A:G:r GGAGTGGGATGATCTTATAAAACTCGTAGAAAGAG
MYC_chr8:12875075 253 ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCTTCG
2_G123E:f GGGAGACAACGACGGCGGTGGCGGGAGCTTCTCCA MYC_chr8:12875087 254
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACCATAC 1_G123E:r
AGTCCTGGATGATGATGTTTTTGATGAAGGTCTCG RB1_chr13:49039115_ 255
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACTTTTAC rs121913297:G:T:f
TGTTCTTCCTCAGACATTCAAACGTGTTTTGATC RB1_chr13:49039204_ 256
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGTGGA rs121913297:G:T:r
AGCATACTGCAAAATATTTGTTTTCAGTCTCTGCA TNFRSF14_chr1:2491 257
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACACGTA 227_rs2234163:G:A:f
CCCCTCTCAGCCCCTCCTCTTGGACTCCAGCCATG TNFRSF14_chr1:2491 258
ATGTGACTGGCACGGGAGTTGATCCTGGTTTTCACGTGGC 346_rs2234163:G:A:r
GTAAGCGCGGCACGCGGCGCAGTGGTCCCCGTCCT
[0258] Genomic Samples
[0259] Three samples of genomic DNA were analyzed: [0260] 1)
Germline sample NA 06994--a normal human sample obtained from the
Coriell repository; [0261] 2) Cancer cell line NCI-H69--a cell line
known to harbor a mutation in TP53, an amplification of the MYCN
locus, and SNVs in ALDH4A1, BRCA1, BRCA2, CDKN2A, DPYD, EPHX1, MYC,
RB1 and TNFRSF14 that were included in the target probe set; [0262]
3) Cancer cell line ZR-75-1, which was reported to harbor an
EML4-ALK fusion gene (Lin et al., Mol. Cancer Res. 7(9):1466,
2009).
[0263] DNA sequencing libraries are generally constructed from
sheared DNA fragments. Acoustic disruption was used to generate DNA
fragments that ranged in size from 200 to >500 bp. Enzymatic
fragmentation of the acoustically fragmented DNA was performed in
an effort to emulate circulating DNA, which is reputed to be
composed of nucleosomal, .about.150 bp fragments. Briefly, DNA at
20-40 ng/.mu.l was sonicated on the 200 bp setting, which yields
fragments that range in size from 150 bp to 400 bp in a broad
smear. The DNA was further fragmented by the addition of 0.01 and
0.02 .mu.l of DNAse enzyme (New England Biolabs recombinant bovine
DNAse) to 50 .mu.l aliquots of DNA in DNAse buffer (10 mM Tris pH
8.0, 2.5 mM MnCl.sub.2, 0.5 mM CaCl.sub.2). The DNAse reaction was
incubated at 37.degree. C. for 10 min and stopped with the addition
of 0.5 M EDTA to a final concentration of 25 mM. DNA with an
average size of 150 bp was purified by "two-sided" bead selection
by first adding 0.9 volumes of beads to 1 volume of DNA. The beads
bind unwanted larger fragments and are discarded, and an additional
1.6 volumes of beads are added to the supernatant. The bound
material is then purified and quantified. An agarose gel of the
resulting, highly fragmented, short DNA used for library
construction is shown in FIG. 6.
[0264] Fragmented DNA was end-repaired using the Quick Blunt kit
form NEB and blended in the ratios shown in Table 7. Ten nanograms
of blended DNA were then ligated to adaptors with the sequences
shown in Table 7. For mixes 9 and 15, two ligation reactions with
10 ng each were performed and subsequently pooled. For mix 16, four
reactions were done. An estimate of genomic inputs into each
library using a qPCR assay is also shown in Table 7.
TABLE-US-00007 TABLE 7 Samples and admixture ratios Admix SEQ ID
Genomic Sample ratio Code NO: inputs 1)NA06994 = GL pure
NNNNNAAGATCTTAGTGGCAC 259 202 2)NCI-H69 = N pure
NNNNNCGACAGAACTATTGCC 260 149 3)ZR-75-1 = Z pure
NNNNNACTATCTTAGTGGCAC 261 242 4)GL:N 1:1 NNNNNCTCCAGAACTATTGCC 262
200 5)GL:N 2:1 NNNNNAGCATCTTAGTGGCAC 263 83 6)GL:N 4:1
NNNNNCATCAGAACTATTGCC 264 186 7)GL:N 10:1 NNNNNATAATCTTAGTGGCAC 265
264 8)GL:N 20:1 NNNNNAAGAAGGTAGACCCTC 266 203 9)GL:N 100:1
NNNNNTTTCTCTACTCGTGAC 267 436 10)GL:Z 1:1 NNNNNACTAAGGTAGACCCTC 268
297 11)GL:Z 2:1 NNNNNGAAGCTACGAGTATCC 269 224 12)GL:Z 4:1
NNNNNAGCAAGGTAGACCCTC 270 73 13)GL:Z 10:1 NNNNNCATTGACGTCTAGAGC 271
181 14)GL:Z 20:1 NNNNNTCACTCTACTCGTGAC 272 224 15)GL:Z 100:1
NNNNNATAAAGGTAGACCCTC 273 580 16)GL:N:Z 500:1:1
NNNNNTACCTCTACTCGTGAC 274 1324
[0265] Targeted Sequencing
[0266] One microgram of each of the sixteen DNA libraries shown in
Table 7 were pooled and adjusted to a final volume of 160 .mu.L.
Eight identical 20 .mu.L aliquots were denatured at 98.degree. C.,
cooled on ice, and 20 .mu.L of probes (Table 6) at 1 nM/probe and
50 .mu.L of CF hyb buffer were added. The samples were annealed for
24 hours from 80.degree. C. to 50.degree. C., washed, and
amplified. Following amplification of the resulting captured and
processed fragments, the final sequencing library was size selected
using the Pippin Prep.TM. instrument with a size selection of
175-400 bp. The library was sequenced on an Illumina MiSeq using a
150 read V3 kit.
Results
[0267] Capture probe performance of high density capture probes
that were chosen based on their position with target sequences were
monitored. A graphical display of the performance of each capture
probe is shown in FIG. 7. These data demonstrate that: [0268] 1)
all capture probes chosen strictly by positional constraint
provided on-target sequence information; [0269] 2) most capture
probes exhibit very little off-target and unmappable read capture;
and [0270] 3) the yield of useful, on-target reads was
substantially uniform. Capture probes that captured a high
proportion of off-target and unmappable reads were analyzed
further. These capture probes were generally positioned in regions
of low sequence complexity/high sequence redundancy. Here, however,
such capture probes had no significant detrimental impact on the
sequencing depth because the high level of probe redundancy (high
density probes) means that all regions are covered by reads derived
from several probes. The net effect was excellent uniformity of
coverage. See, e.g., FIG. 8, probe coverage for the TP53 gene using
the 40 mer capture probes.
Conclusion
[0271] Taken together, these data demonstrate that capture probe
length can be reduced from 60 nucleotides to 40 nucleotides with
little or no discernible loss of probe performance (once capture
wash temperatures are adjusted). They also show that probe design
can follow positional constraints and can generally ignore sequence
context or composition. Even though this methodology produces the
occasional poor-performing probe, the high redundancy at close
probe spacing more than compensates for individual probe
deficiencies.
Example 3
Genetic Analysis of Circulating DNA
Purpose
[0272] The purpose of this example was to benchmark the genetic
analysis of cfDNA using an efficient cloning procedure for cfDNA
and target retrieval system.
Background
[0273] While there is tremendous enthusiasm in the scientific and
health-care community for "liquid biopsies"--analysis of
circulating DNA (cfDNA) for markers associated with potential
disease states, there is remarkably little practical information
about this potential analyte.
Summary
[0274] Plasma samples collected from healthy donors and individuals
suffering from either ovarian or colon cancers were used to perform
the genetic analysis of circulating DNA. The amount and the overall
character of circulating cfDNA can vary widely from individual to
individual. Surprisingly, the present inventors found that cfDNA is
readily clonable with an efficiency indistinguishable from highly
purified and fragmented genomic DNA; that the fragment size was
remarkably consistent, with an average clone insert size of
170.+-.10 bp (in 7/8 samples); and that the genome representation
from such samples was uniform and comparable to experiments
performed using purified gDNA. It was further established that by
counting unique reads, the depth of representation in each library
provided an estimate of minor allele frequency for tumor markers
present in the cfDNA of diseased patients. This study established
that construction and target retrieval systems contemplated herein
were effectively applied to the quantitative genetic analysis of
cfDNA.
Methods
[0275] DNA Purification
[0276] Eight sets of plasma samples were purchased from
Proteogenex, Inc., Culver City, Calif. (Table 8). Circulating DNA
was extracted from the samples (on two separate occasions) using
the Circulating Nucleic Acid Purification kit from Qiagen. Samples
were passed through DNA mini-columns using centrifugation. The
specimen IDs and yield of DNA are shown in Table 8.
TABLE-US-00008 TABLE 8 Plasma samples and cfDNA yields. Sample
Patient Specimen DNA yield (ng per mL ID diagnosis type Volume of
input) D5930P Healthy donor plasma 4 mL 11 D5942P Healthy donor
plasma 4 mL 68 023407P Colorectal plasma 4 mL 10 cancer 023406P
Colorectal plasma 4 mL 63 cancer 023185P Colorectal plasma 4 mL 171
cancer 023149P Colorectal plasma 4 mL 36 cancer 032667P Ovarian
cancer plasma 4 mL 24 032676P Ovarian cancer plasma 4 mL 13
[0277] Library Construction
[0278] Purified DNA from 4 mL of plasma was collected in 100 .mu.l
elution buffer. For the four samples collected from colon cancer
patients (CRC), the DNA was split in half and one 50 .mu.l aliquot
from each patient was sonicated to 200 bp. One 50 .mu.l aliquot of
untreated cfDNA and one 50 .mu.l fragmented cfDNA from each patient
(the entire sample from each patient) was end repaired by adding
(per sample): [0279] 6 .mu.l of 10.times. quick blunt buffer (New
England Biolabs (NEB)) [0280] 0.6 .mu.l of 10 mM dNTPs [0281] 2.4
.mu.l of quick blunt enzyme mix [0282] 1.2 .mu.l of PreCR enzyme
mix. Samples were incubated at 20.degree. C. for 30 min and at
70.degree. C. for 10 min. Ligations with adaptors (Table 2) were
performed by combining: [0283] 60 .mu.l end-repaired cfDNA [0284]
12 .mu.l adaptor duplex (10 .mu.M) [0285] 10 .mu.l 10.times. ligase
buffer (NEB) [0286] 15 .mu.l 50% PEG.sub.8000 [0287] 3 .mu.l HC T4
DNA ligase
TABLE-US-00009 [0287] TABLE 9 Samples and codes used for four CRC
plasma samples Progenex Sample Pre- ID # treatment Adapter 23149 1
none NNNNNTTTTGTGTGTGTGTG (SEQ ID NO: 275) 23407 2 none
NNNNNACTACACACACACAC (SEQ ID NO: 276) 23406 3 none
NNNNNCTCGTGTGTGTGTGT (SEQ ID NO: 277) 23185 4 none
NNNNNGAACACACACACACA (SEQ ID NO: 278) 23149 5 frag
NNNNNCATGTGTGTGTGTGT (SEQ ID NO: 279) 23407 6 frag
NNNNNGTGCACACACACACA (SEQ ID NO: 280) 23406 7 frag
NNNNNATAACACACACACAC (SEQ ID NO: 281) 23185 8 frag
NNNNNTACTGTGTGTGTGTG (SEQ ID NO: 282)
[0288] Reactions were incubated at 22.degree. C. for one hour and
65.degree. C. for 10 min. Ligation products were purified by the
addition of 100 .mu.l beads, washing, and elution in 40 .mu.l
TEzero. All 40 .mu.l of ligation product was amplified by PCR with
primer ACA2 (SEQ ID NO:283) and the samples were combined in equal
mass for targeted capture.
[0289] Targeted Sequence Capture and Sequencing
[0290] The four unfragmented and four fragmented colon plasma
samples (FIG. 9C) were hybridized with our high-density, 40
nucleotide probe set that targets TP53, ALK, among others. The
capture complexes were processed as described above in Example
2.
Results
[0291] Library Appearance
[0292] A false-color picture of a 2% agarose gel loaded with 50 ng
of each library is shown in FIG. 9A. The average fragment size was
in a tight range of 260.+-.20 bp. These data indicated that the
clonable fraction of cfDNA is present predominantly as nucleosomal
fragments. In addition, the size of the cfDNA libraries had the
same basic superficial appearance as cfDNA in kidney dialysis
patients (Atamaniuk et al., Clinical Chemistry 52(3):pp. 523-26
(2006)) except that the cfDNA libraries were shifted to higher mass
by the addition of adaptor sequences (FIG. 9B). In contrast, the
cfDNA libraries differed dramatically from sonicated gDNA
libraries, which appear as broad smears.
[0293] Four additional sets of cfDNA libraries were constructed
from the two ovarian cancer patient plasma samples and two plasma
samples from healthy volunteers. 38 .mu.l aliquots of cfDNA were
end-repaired in 50 .mu.l total volume. Ligations included 40 .mu.l
of end-repaired fragment, 16 .mu.l of adaptor (10 .mu.M), 8 ul of
10.times. ligase buffer, 16 .mu.l of 50% PEG and 4 .mu.l of HC T4
DNA ligase in a total volume of 80 .mu.l. The ligation reaction was
incubated at 20.degree. C. for 1 hour and 65.degree. C. for 10 min.
For purification, 20 .mu.l of TEzero and 150 .mu.l of beads were
added. The purified ligation products were resuspended in 40 .mu.l,
all of which was used in a subsequent 200 .mu.l library
amplification by PCR. The resulting amplified libraries are shown
in FIG. 9C.
[0294] Sequencing Data Analysis
[0295] The average unique read count observed in each of the eight
libraries ranges from .about.700 unique reads to >3000 unique
reads, defining a range of sensitivities from .about.0.15% to
.about.0.03%. FIG. 10. A rare mutant read will likely be observed
more than once, meaning minimum sensitivities are less than those
calculated above. In preferred embodiments, unique reads provide
the lower bound on statistically defensible observation
frequencies.
[0296] cfDNA Cloning Efficiency
[0297] Sample 23407 was used as a benchmark. 10 ng/mL of cfDNA was
recovered from the plasma sample and 20 ng of the isolated cfDNA
was used in each of two library construction efforts. The unique
read counts indicated that we recovered an average of 700 unique
reads (genome equivalents) from unfragmented DNA ("23407" in FIG.
10). Given that each genome contains 0.003 ng of gDNA, 2.1 ng of
input DNA in this library (10% cloning efficiency) was
recovered.
[0298] Fragmentation prior to library construction with this sample
increased the library yield by more than two-fold ("23407 frag" in
FIG. 10). This indicates that much of the DNA present in the 23407
sample was high molecular weight DNA that required fragmentation in
order to be clonable. Thus, the library cloning efficiency was
likely far greater than 10% and was likely in the range of 20% for
input cfDNA. This cloning efficiency is comparable to highly
purified genomic DNA and indicates that cfDNA was not likely
modified in any way that is deleterious to downstream cloning
efforts.
[0299] Library Coverage
[0300] The cfDNA libraries resembled a set of discrete bands with
random coverage of target regions. FIG. 11 shows a random sampling
of sequence data. A random set of reads from sample 23407 that was
not fragmented prior to cloning (see FIG. 10), and that were
captured by the TP53 probe
"chr17:7579351:region.sub.--3:280nt:41:80:r" (SEQ ID NO:201) were
aligned using BLAT. Given the way that the sample was prepared,
these are likely a reflection of cfDNA fragments in general because
the left hand portion of these reads (the read start sites) are
randomly distributed across the target region. This random
distribution indicates the random breakage of genomic DNA, and it
demonstrates that despite the band-like appearance of cfDNA
libraries, the sequencing output was a random coverage of the
target region. The random distribution is important for effective
genetic analysis using technology contemplated herein.
[0301] FIG. 12 provides a more high resolution overview of TP53
coding region sequencing for a typical cfDNA library. The elements
of targeted sequencing--coverage across all target regions and
uniform depth at each sequenced base--are readily apparent. At this
depth of >4000 unique reads per base, and with a requirement
that legitimate candidate base changes must be encountered at least
twice, it is possible to estimate that the mutation detection
sensitivity for this particular library was about 1 mutation in
2000 sequences, or 0.05%. This level of sensitivity represents a
surprising and unexpected outstanding technical achievement.
Conclusion
[0302] cfDNA was isolated and cloned from plasma clones with an
efficiency comparable to highly purified gDNA isolated from cell
lines (the gold standard). The cfDNA libraries resembled
circulating nucleosomal-sized DNA fragments+adaptors and the ends
possessed sufficiently random character, which enabled efficient
genetic analysis. In addition, the highly uniform size
characteristic of plasma cfDNA libraries allows designing capture
strategies and underlying probe sequences to maximize reliable
coverage of targets as far as 120 bp (=160-40) from the ends of
probes.
Example 4
Measurement of Genome Equivalents in Circulating DNA Libraries
Purpose and Background
[0303] One of the major challenges in the analysis of circulating,
cell-free DNA is achieving sufficient assay sensitivity. If
sufficient sensitivity is not achieved then analysis of the cfDNA
libraries is confounded: if a sample is sequenced and no mutational
events are detected, that result could be interpreted to mean that
no mutations are present, or that significant events were missed
because the sampling depth was too small. The sensitivity of an
assay is defined in statistical terms as the false negative rate.
In the context of sequencing circulating, cell-free DNA, a
significant obstacle is the detection of a rare sequence that is
blended in a large excess of reference sequence.
[0304] One method for determining assay sensitivity is to measure
the occurrences of mutant sequence in a set of samples where mutant
sequence is progressively diluted into non-mutant, reference
sequence. The dilution at which mutant sequences are no longer
detected defines assay sensitivity. This method is adequate if both
the identity of the mutant sequence and the extent of dilution are
known. Unfortunately, clinical samples do not generally provide
either parameter. Often the identity of the mutant sequence is not
known, and the extent of dilution varies from sample to sample. In
this context, assay sensitivity is established on a
sample-by-sample basis.
[0305] To assign a sensitivity value on a sample-by-sample basis,
the numbers of different and distinct sequences that are present in
each sample are measured, by measuring the number of genome
equivalents that are present in a sequencing library. By way of a
non-limiting example, if a DNA sequencing library is known to
contain 3 ng (3000 pg) of human genomic DNA and each human genome
has a mass of 3 pg, then the library possesses 3000/3=1000 genome
equivalents of DNA. If a mutant DNA sequence must be detected twice
to be statistically significant, then an estimate of the best
possible sensitivity of detection for this particular library is 2
mutant sequences/1000 total sequences=0.002=0.2%. To establish
sensitivity, the number of genome equivalents must be measured for
each sample library.
Summary
[0306] Two methods were used to measure genome equivalents. The
first method is based on quantitative PCR (qPCR). A genomic library
was constructed using ligation of adaptors to genomic fragments and
a pair of PCR primers, one that is specific to a common genomic
sequence (e.g., Alu I repeat) and one that is specific to the
adaptor. The abundance of ligated adaptor: fragment sequences of
these cfDNA libraries was measured. A standard library of known
concentration was used to construct a standard curve and the
measurements were fit to the resulting standard curve and a value
for genome equivalents was derived from the fit.
[0307] The second method to measure genome equivalents used
bioinformatics counting after sequencing was performed. Each unique
sequence in a library was identified by its random sequence label
and the starting nucleotide of the genomic sequence. Moreover, each
unique sequence must be derived from an independent genome.
Therefore, the sum of unique sequences present in sequence data
established a precise quantitative measurement of the number of
genome equivalents present in a sample.
Methods and Results
[0308] qPCR Assay Development
[0309] The first version of a qPCR-based genome equivalence assay
used the ACA2 primer (Table 10), but this assay chronically
under-reports the number of genome equivalents that are present in
a cfDNA library (FIG. 13).
TABLE-US-00010 TABLE 10 PCR primers used in the development of the
genome equivalent qPCR assay SEQ ID Name NO: Sequence ACA2 283
TGCAGGACCAGAGAATTCGAATACA ACA2_FL 284
AATGATACGGCGACCACCGAGATCTACACGTCA FP TGCAGGACCAGAGAATTCGAATACA
Alu_F1 285 CGGTGGCTCACGCCTGTA Alu_R1 286 GCCTCGGCCTCCCAAAGT A1u_F2
287 GAGGCTGAGGCAGGAGAATCG A1u_R2 288 GTCGCCCAGGCTGGAGTG
[0310] The improved version of the assay was based on endogenous
repeats (e.g., Alu repeats) that are found at very high frequency
throughout the human genome. By coupling an Alu-specific primer
with an adaptor-specific primer, the frequency with which adaptors
are joined to genomic fragments was reliably measured. Standard
curves using libraries of known genome equivalents were generated,
and the number of genome equivalents in cloned libraries was
measure by fitting to the curve.
[0311] The PCR primers used to develop an Alu+adaptor-based qPCR
assay are shown in Table 10. The PCR primers for Alu amplification
were designed from consensus a consensus human Alu sequence (Batzer
& Deininger, Nat Rev Genet. 3(5):370-9 (2002)) using PRIMER3
(Alu_F1 & Alu_R1, SEQ ID NOs:285 and 286, respectively). The
remaining two Alu primers (Alu_F2 and Alu_R2, SEQ ID NOs:287 and
288, respectively) were reported in the literature (Marullo et al.,
Genome Biology 11:R9 (2010)).
[0312] A schematic of the assay design is provided in FIG. 14.
Because a single PCR primer can used to amplify the genomic DNA
libraries (FIG. 14A), a primer that recognizes the adaptor sequence
but that cannot amplify genomic clones was used. The 58 nucleotide
ACA2-FLFP primer (henceforth abbreviated AF, SEQ ID NO:284) fills
these criteria because its length induces strong stem-loop PCR
suppression (FIG. 14B). Additionally, a functional pair of Alu
primers were used (FIG. 14C). Moreover, a primer pair consisting of
one Alu primer and the long ACA2 primer that did not amplify
genomic DNA used (FIG. 14D). These same primers also amplified
genomic library clones (FIG. 14E).
[0313] All of the required elements for a functional Alu-based
assay were validated. FIG. 15. Specifically, the long primer alone
was inert, both sets of Alu primer pairs recognized human genomic
DNA, and any combination of one Alu primer and the long ACA2 primer
amplified genomic library clones (FIG. 15A). Finally, the ability
of Alu primer plus long ACA2 primer pair to discriminate between
genomic DNA and genomic library clones is shown in FIG. 15B. The
combination of Alu_R1 and AF primers were used for measuring genome
equivalents in the newly constructed libraries.
[0314] A direct comparison between the ACA2-based and the Alu-based
qPCR assays is shown in FIG. 16. An 8-fold difference in genome
equivalents was found. In addition the Alu-based assays provided a
more consistent performance library-to-library and a better
alignment between qPCR derived equivalents and bioinformatically
counted tag equivalents in sequencing runs (Table 11).
TABLE-US-00011 TABLE 11 qPCR vs counted sequencing tags Sample
Alu-based qPCR counted tags Run_68 50 to 1 6962 3459 Run_68 1000 to
1 10937 4641
[0315] High-Sensitivity Library Adaptors for Sequence-Based
Counting of Genome Equivalents
[0316] As discussed above, the reality of disease surveillance
using cfDNA is that mutant sequences may be rare constituents in an
otherwise vast excess of "normal" (meaning germline) DNA sequences.
Thus, highly sensitive and quantifiable sequencing assays are
needed. Assay sensitivity could be made by counting the number of
unique sequences present in a sequencing library. However, such
counting would lead to a false underestimate of sensitivity because
cfDNA fragments are rather short (.about.165 bp) and may lead to
identical reads that were actually derived from independent cloning
events. One solution to this problem is to mark each independent
sequencing clone during library construction by including, for
example, a set of DNA tags in the adaptors used to construct
libraries.
[0317] A set of such library construction adaptors was specifically
designed to measure the number of genome equivalents present in
cfDNA libraries, and, by extension, the sensitivity of sequencing
assays used to monitor mutant sequences.
[0318] The architecture of high-sensitivity library adaptors that
were configured to accommodate large numbers of genome equivalents
in cfDNA libraries is shown in FIG. 17. There is a substantial
amount of molecular engineering within the 45 nucleotide ligation
strand, which is the strand that becomes attached to end repaired
cfDNA fragments. The adaptors comprise at least five elements.
[0319] Element 1 is a PCR primer binding site for the single-primer
library amplification primer ACA2 (Table 12).
TABLE-US-00012 TABLE 12 Number SEQ of Sequences ID Element Function
sequences (5' .fwdarw. 3') NO: Element PCR 1 TGCAGGACC 289 1 primer
AGAGAATTCG binding AATACA site
[0320] Element 2 is a 5 nucleotide read code. The combination of
this code with the genomic DNA sequence constitutes the DNA tag
that was used to uniquely identify each read. The 5 nucleotide
codes consist of 256 possible unique sequences that were chosen to
be 2 base changes different from every other code in the set. This
feature enabled unique and distinct reads to be differentiated from
reads that appeared to be unique owing to a sequencing error in the
code region. Seven codes in which G residues are over-represented
and that were shown empirically to interfere with adaptor function
were removed, leaving 249 random codes. Table 13.
TABLE-US-00013 TABLE 13 Number of Element Function sequences
Element 2 Distinct sequence labels 249 Sequences SEQ ID Sequences
SEQ ID Sequences SEQ ID Sequences SEQ ID (5' .fwdarw. 3') NO: (5'
.fwdarw. 3') NO: (5' .fwdarw. 3') NO: (5' .fwdarw. 3') NO: CGGGT
290 GGGTC 354 AGAGA 418 CCGGA 482 CGGTG 291 GGTCG 355 AGCCG 419
CGACG 483 CGTGG 292 GGTGC 356 AGCGC 420 CGAGC 484 GCGGT 293 GTCGG
357 AGGAA 421 CGCAG 485 GCGTG 294 GTGCG 358 AGGCC 422 CGCGA 486
GCTGG 295 GTGGC 359 AGGTT 423 CGGAC 487 GGCGT 296 TGCGG 360 AGTGT
424 CGGCA 488 GGCTG 297 TGGCG 361 AGTTG 425 GAAAG 489 GGGCT 298
TGGGC 362 ATGGT 426 GAAGA 490 TTAAA 299 AAAGG 363 ATGTG 427 GACCG
491 TTACC 300 AAGAG 364 ATTGG 428 GACGC 492 TTATT 301 AAGGA 365
CACGG 429 GAGAA 493 TTCAC 302 ACCGG 366 CAGCG 430 GAGCC 494 TTCCA
303 ACGCG 367 CAGGC 431 GAGTT 495 TTTAT 304 ACGGC 368 CCAGG 432
GATGT 496 TTTTA 305 AGAAG 369 CCGAG 433 GATTG 497 GCACG 306 GTGTA
370 AACTG 434 AGTCA 498 GCAGC 307 GTTAG 371 AAGCT 435 ATACG 499
GCCAG 308 GTTGA 372 AAGTC 436 ATAGC 500 GCCGA 309 TAGGT 373 AATCG
437 ATCAG 501 GCGAC 310 TAGTG 374 AATGC 438 ATCGA 502 GCGCA 311
TATGG 375 ACAGT 439 ATGAC 503 GGAAA 312 TGAGT 376 ACATG 440 ATGCA
504 GGACC 313 TGATG 377 ACGAT 441 CAAGT 505 GGATT 314 TGGAT 378
ACGTA 442 CAATG 506 GGCAC 315 TGGTA 379 ACTAG 443 CAGAT 507 GGCCA
316 TGTAG 380 ACTGA 444 CAGTA 508 GGTAT 317 TGTGA 381 AGACT 445
CATAG 509 GGTTA 318 TTAGG 382 AGATC 446 CATGA 510 GTAGT 319 TTGAG
383 AGCAT 447 CCCGT 511 GTATG 320 TTGGA 384 AGCTA 448 CCCTG 512
GTGAT 321 AACGT 385 AGTAC 449 CCGCT 513 CCGTC 322 CTGTT 386 GTAAC
450 TCCGC 514 CCTCG 323 CTTGT 387 GTACA 451 TCGAA 515 CCTGC 324
CTTTG 388 GTCAA 452 TCGCC 516 CGAAT 325 GAACT 389 GTCCC 453 TCGTT
517 CGATA 326 GAATC 390 GTCTT 454 TCTGT 518 CGCCT 327 GACAT 391
GTTCT 455 TCTTG 519 CGCTC 328 GACTA 392 GTTTC 456 TGAAC 520 CGTAA
329 GATAC 393 TAACG 457 TGACA 521 CGTCC 330 GATCA 394 TAAGC 458
TGCAA 522 CGTTT 331 GCAAT 395 TACAG 459 TGCCC 523 CTAAG 332 GCATA
396 TACGA 460 TGCTT 524 CTAGA 333 GCCCT 397 TAGAC 461 TGTCT 525
CTCCG 334 GCCTC 398 TAGCA 462 TGTTC 526 CTCGC 335 GCTAA 399 TCAAG
463 TTCGT 527 CTGAA 336 GCTCC 400 TCAGA 464 TTCTG 528 CTGCC 337
GCTTT 401 TCCCG 465 TTGCT 529 TTGTC 338 ACTTC 402 CCACC 466 TATAA
530 TTTCG 339 ATAAT 403 CCATT 467 TATCC 531 TTTGC 340 ATATA 404
CCCAC 468 TATTT 532 AAAAA 341 ATCCT 405 CCCCA 469 TCACT 533 AAACC
342 ATCTC 406 CCTAT 470 TCATC 534 AAATT 343 ATTAA 407 CCTTA 471
TCCAT 535 AACAC 344 ATTCC 408 CTACT 472 TCCTA 536 AACCA 345 ATTTT
409 CTATC 473 TCTAC 537 AATAT 346 CAAAC 410 CTCAT 474 TCTCA 538
AATTA 347 CAACA 411 CTCTA 475 ACAAC 348 CACAA 412 CTTAC 476 ACACA
349 CACCC 413 CTTCA 477 ACCAA 350 CACTT 414 TAAAT 478 ACCCC 351
CATCT 415 TAATA 479 ACCTT 352 CATTC 416 TACCT 480 ACTCT 353 CCAAA
417 TACTC 481
[0321] Element 3 is a 3 nucleotide sample code that differ by at
least two base changes. This element was used to identify different
samples and enabled sample multiplexing within a sequencing run.
Table 14.
TABLE-US-00014 TABLE 14 Number SEQ of Sequences ID Element Fuction
sequences (5' .fwdarw. 3') NO: Element Distinct sample 16 AAG 539 3
labels; sample multiplexing CTC 540 GGT 541 TCA 542 ACT 543 CGA 544
GTG 545 TAC 546 AGC 547 CCG 548 GAA 549 TTT 550 ATA 551 CAT 552 GCC
553 TGG 554
[0322] Element 4 is a 12 nucleotide anchor sequence with three
important characteristics with respect to library construction and
downstream sequencing. Table 15. These are A) each 12 base
extension is part of a family of four 12 base extensions that
collectively represent each of the four possible DNA bases at each
site within extension. This feature, balanced base representation,
is required by the Illumina sequencing instrument in order to
calibrate proper base calling in sequencing reads. B) Each
extension is composed of only two of four possible bases, and these
are specifically chosen to be either 6 A's+6 C's or 6 G's+6 T's.
This extension formed from only two bases greatly reduces the
possibility that the extension sequence will participate in
secondary structure formation that would preclude proper adaptor
function. C) Because each extension is composed of equal numbers of
A+C or G+T, each extension shares roughly the same melting
temperature and duplex stability as every other extension in a set
of four.
TABLE-US-00015 TABLE 15 Number SEQ of Sequences ID Element Fuction
sequences (5' .fwdarw. 3') NO: Element 12 nucleotide 4 ACCCACACCAAA
555 4 extension that provides a duplexing site for the partner
oligo- nucleotide CAAACACAACCC 556 GTGTGGGTTGTT 557 TGTGTTTGGTGG
557
[0323] Element 5 is the two base sequence found at the 3' end of
Element 4. The particular two base extensions were chosen based on
empirical data that shows that these two base sequences are
efficient substrates for ligation. Table 15.
[0324] The adaptor module is hybridized to a partner
oligonucleotide. Table 16. The hybridization takes place between
the sequence within Element 4 and the partner oligonucleotide. The
double-stranded adaptor was ligated to end-repaired cfDNA.
TABLE-US-00016 TABLE 16 Number SEQ of Sequences ID Element Fuction
sequences (5' .fwdarw. 3') NO: Element 12 nucleotide 4 TTTGGTGTGGGT
559 4 extension that provides a duplexing site for the partner
oligo- nucleotide GGGTTGTGTTTG 560 AACAACCCACAC 561 CCACCAAACACA
562
[0325] To convert a set of 256 independently synthesized and pooled
ligation strands (each of which shares a common sample code and
therefore constitutes a single sample adaptor set) to duplexes
suitable for ligation, the 45 nucleotide ligation strand was
combined with the appropriate complementary 12 nucleotide partner
strand, heated to 95.degree. C., cooled to 65.degree. C. for 5 min,
then cooled to room temperature. This duplex formed a blunt end
ligation substrate as shown in FIG. 17B. Following ligation and DNA
purification, a DNA polymerase-mediated step that occurs prior to
PCR amplification displaced the partner strand and copied the
ligation strand to form a double-strand adaptor that was suitable
for exponential amplification by single-primer PCR.
[0326] The quantitative analysis of genome equivalents derived from
targeted sequencing data was then performed. Each unique read was
considered a unique ligation event and the sum of unique reads was
considered equivalent to the number of genome equivalents
analyzed.
[0327] A rough, "back-of-the-envelope", "rule-of-thumb" calculation
was performed to determine the number of genome equivalents that
could be analyzed. Each cfDNA clone was approximately 150 base
pairs, 50 base pairs of which were required for binding to capture
probes. This left roughly 100 possible sequence start sites within
any captured cfDNA clone. The attachment of 249 random codes to
each of the 100 possible start sites created a total repertoire of
.about.249,000 possible unique clones. As the number of unique
clones approaches the total number of possible sequence
combinations, probability dictates that the same code and start
site combinations will be created by independent events and that
these independent events will be inappropriately grouped within
single families. The net result will be an underestimate of genome
equivalents analyzed, and rare mutant reads may be discarded as
sequencing errors because they overlap with wild-type reads bearing
the same identifiers. To avoid this, efforts were made using the
qPCR assay to constrain genomic inputs to one tenth or less the
number of possible unique clones. For example, a single adaptor has
24,900 possible clones and thus, has a reliable capacity to provide
accurate analysis for libraries consisting of 2500 or fewer genome
equivalents.
[0328] The procedure that is outlined is provided as an example and
the methods contemplated herein are not meant to be bound by this
example. In some cases, the number of genome equivalents to be
analyzed may well exceed the 2500 limit illustrated in the
preceding paragraph. To expand the depth of genome equivalents, two
solutions to this problem are readily available. The first solution
is to use more than one adaptor set per sample. By combining
adaptors, it is possible to expand the total number of possible
clones and therefore, expand the comfortable limits of genomic
input. As a non-limiting example, the combination of four adaptor
sets used for one sample would expand the analysis to
24,900.times.4=99,600 possible sequences and 10,000 reasonably
analyzed genome equivalents. The second solution is to expand the
code in Element 2 of FIG. 17A to 6, 7, or more bases. The number of
possible codes that differ by at least 2 bases from every other
code scales as 4.sup.(n-1) where n is the number of bases within
Element 2. Thus, in the non-limiting example presented here, n=5
and 4.sup.(5-1)=256; therefore, the inclusion of additional bases
expands the available repertoire by a factor of four for each
additional base.
Conclusion
[0329] The results from this example showed that two independent
methods for the determination of genome equivalents have utility in
sample processing workflow. The first method, qPCR, was implemented
during the library construction phase of cfDNA analysis and it was
used as a quality control step to ensure that adequate numbers of
genome equivalents are moved through library amplification,
targeted sequence capture, and DNA sequencing. The other method use
explicit counting of unique reads as a more direct measure of the
actual number of genome equivalents that fell under informatics
consideration.
Example 5
Quantitative Genetic Analysis
Purpose
[0330] The purpose of this example was to apply quantitative
genetic analysis to normal DNA admixed cancer genomes and to
uncharacterized cfDNA isolated from the plasma of cancer
patients.
Background
[0331] Three types of genomic events are prevalent in human
cancers. These are somatic mutations that alter the function of the
affected gene and its expressed protein product(s); genomic
rearrangements that create chimeric gene fusions and therefore
expressed fusion proteins with novel biological properties; and
changes in gene copy number that lead to gene loss and under
expression of gene product(s), or, conversely, amplification of
genes and over-representation of the corresponding gene product(s).
In the circulating DNA of a cancer patient, these aberrant loci,
many of which have critical significance in guiding patient care,
are admixed (blended) with the patient's normal, germline DNA.
Summary
[0332] In the previous examples, technology has been described that
was configured for the analysis of circulating, cell-free DNA
(cfDNA), with an aim toward cancer surveillance. However, the
technology is widely applicable to any analytical, diagnostic and
monitoring paradigm including, but not limited to r genetic
diseases; fetal testing; mendelian disorders; pathogen screening;
and organ transplant monitoring in which circulating DNA is a
potential analyte. In this example, the technical features
highlighted in previous examples are applied to the analysis of
admixed cancer samples. In the first phase of this validation,
cancer-derived cell lines were admixed with normal human DNA at
defined dilutions, and quantitative genetic analysis was performed.
In the second phase of this study, uncharacterized cfDNA was
isolated from the plasma of cancer patients and subsequently
examined using quantitative genetic analysis.
Methods
[0333] Admixtures of Cell Line Genomic DNA with Normal Human
DNA
[0334] The following DNA samples were used: [0335] NA06994--normal
human genomic DNA (Coriell repository); [0336] NCI-H2228--non-small
cell lung cancer cell line (ATCC), harbors mutation in TP53 (Q331*)
and EML4-ALK gene fusion (breakpoint unknown); and [0337]
NCI-H69--small cell lung cancer cell line (ATCC), harbors
amplification of the MYCN gene (.about.100 copies).
[0338] Library preparation: Genomic DNA isolated from cell lines
(all three above) is high molecular weight material that is
dissimilar to the small size of cfDNA. To mimic cfDNA in these
validation experiments, genomic DNAs were first fragmented on the
"150 bp" setting using a Covaris Acoustic Sonicator. The sonication
generally produces a broad smear, and the DNA was further processed
using "two sided" bead selection. A dilute solution of DNA
purification beads were added to the sample and the higher
molecular mass fragments that adhere to the beads were discarded
(the size of purified DNA is proportional to the amount of beads
added). An additional aliquot of beads are added to the remaining
supernatant and in this second round, DNA that adheres to the beads
that (in a higher overall concentration of binding buffer) are
purified. This "two-sided" purification produces a narrow size
distribution that is a reasonable proxy for cfDNA (FIG. 18).
[0339] Fragmented genomic DNA was end repaired, quantified, and
mixed in the various ratios shown in Table 17 and described in the
results section below.
TABLE-US-00017 TABLE 17 Samples and admixtures used for validation
studies Sample, Admixture genome equivalents (qPCR) Pure H2228 2248
NA06994:H2228 4:1 2616 NA06994:H2228 10:1 2600 NA06994:H2228 20:1
2968 NA06994:H2228 50:1 5000 NA06994:H2228 1000:1 10000 Pure H69
2472 NA06994:H69 4:1 2768 NA06994:H69 10:1 3088 NA06994:H69 20:1
2944 NA06994:H69 40:1 1616 NA06994:H69 100:1 1920 NA06994:H69 200:1
2920 NA06994:H69 500:1 17520
[0340] cfDNA libraries may have limited DNA inputs. The amount of
cfDNA obtained per mL of patient plasma is widely variable, but the
lower limits (e.g., Example 3) are generally .about.10 ng/mL, which
is equivalent to 3300 human genomes. To guard against limited cfDNA
quantities, the admixture experiments were modeled to reflect the
lower limits of cfDNA that were routinely collected from patients.
This constraint was applied to all but the most extreme admixtures.
In these latter admixtures, libraries were made to mimic inputs
from 4 mLs (NA06994:H2228 1000:1) or 8 mLs (NA06994:H69 500:1) of
low yield patient cfDNA. Admixed samples were then ligated to the
adaptor sets described in Example 4. Measurement of the genome
equivalents in each purified library using qPCR (Example 4) is also
shown in Table 17. Libraries were amplified, quantified, and
equivalent masses of each library were pooled (500 ng of each). The
pooled sample was hybridized with the proof-of-concept,
high-density 40 mer capture probes listed in Table 6 of Example 2.
The resulting complexes were captured on streptavidin-coated beads,
washed, processed, amplified, purified and size-selected as
described in previous examples. The resulting library was analyzed
using an Illumina 150 bp-V3 Miseq sequencing kit on the Illumina
MiSeq instrument.
[0341] For bioinformatics analysis, a rare somatic variant caller
was used to detect mutations, a split read aligner was used to
detect fusion genes, and in-house analysis that quantifies and
statistically fits tags was used to call copy number variation
(CNV).
[0342] The detection of an admixed point mutation in the TP53 gene
is shown in FIG. 19. The "expected" frequency deviates from the
admix ratio because it is known that TP53 is hemizygous in the
NCI-H2228 cell line. Automated software was able to call the mutant
allele in the 50:1 admixture. Manual curation was required to call
the mutant event at 1000:1. With respect to specificity, the tag
filtering described in Example 1 was applied to the analysis, and
no other mutation calls in TP53 were detected after applying this
tag filter.
[0343] Cell line NCI-H2228 is known to harbor a fusion gene between
EML4 and ALK; the cell line serves as a positive control in both
fluorescence in situ hybridization assays and in detection of
fusion gene transcripts using RT-PCR. There are no published
reports of the exact location of the gene fusion junction. Using
dense probe coverage of the intron 19 region of ALK, sequence
analysis revealed precise location and sequence of the junction
formed when the two genes fused (FIG. 20). The frequency of normal
reads versus junction reads in the NCI-H2228 cell line (378 vs 249,
respectively) suggests that the fusion gene is heterozygous with a
normal copy of ALK.
[0344] Detection of junction reads as a function of admixture is
shown in FIG. 21. As with point mutation detection, the expected
values were adjusted to reflect the fact that the mutant allele is
found in one copy per diploid genome. No fusion reads were detected
in the 1000:1 admixed sample.
[0345] FIG. 22 shows the results of CNV determination for the MYCN
gene as a function of admixture. The NCI-H69 cell line harbors a
highly amplified MYCN gene. MYCN is normally found as a single copy
gene, two per diploid genome, and thus the expected result for
progressively more dilute admixtures is that the tag-calculated CNV
should asymptotically approach 2 copies (the asymptote is
highlighted in the figure). The validation experiment shown here
indicated that the assay system described in this invention is
robustly sensitive to highly amplified genes.
[0346] Variant Discovery in cfDNA from Cancer Patients
[0347] The most rigorous validation of the technology contemplated
herein is to apply it to cfDNA samples in which the spectrum of
mutations is unknown. An analysis was performed by sequencing
matched cfDNA, tumor and normal adjacent tissue (NAT) samples from
two ovarian cancer patients. In addition, two cfDNA samples from
colorectal cancer (CRC) patients and two cfDNA samples from healthy
volunteers were analyzed. In no case, were mutations, fusions or
abnormal CNV detected in the healthy volunteer samples.
[0348] Libraries of cfDNA from the four cancer patients were
initially screened using the targeted probes described in Table 6
of Example 2. These probes were primarily configured to detect
point mutations in the TP53 gene, gene fusions with ALK and
amplifications of the MYCN. The results of this initial sequencing
screen are shown in FIG. 23. A point mutation occurring at the same
base position was found in the cfDNA, tumor, and NAT of one ovarian
patient. No TP53 mutations were found in the other set of ovarian
cancer patient matched samples. Point mutations were also detected
in the two CRC cfDNA libraries for which matching tissues were
unavailable. All of these point mutations have been previously
identified in tumors and all are known to be causal drivers of
tumorogenesis. The mutant sequence detection in cfDNA library
CRC406 of 0.9% was well within the scope of assay sensitivity.
Sensitivity is defined by the presence of multiple families of
tagged reads, all of which possess the mutant sequence. These data
highlight the clinical utility of the system contemplated
herein.
[0349] To further explore the detection of cancer-related changes
in cfDNA libraries and associated tissues, the same libraries were
hybridized to a set of 679 probes that are directed to a total of
20 different cancer-related genes (Table 18). In this probe set,
all of the coding regions of 14 genes were targeted while select
loci were targeted in the remaining 6 genes.
TABLE-US-00018 TABLE 18 Cancer genes targeted Genes: coding region
targeted Genes: select regions targeted BRCA1 ALK BRCA2 DPYD BRAF
EPHX1 CDH1 MYC ERBB2 TNFRSF14 JAK2 ALDH4A1 NF2 PIK3CA RB1 CDKN2A
KRAS MYCN PTEN TP53
[0350] As shown in FIG. 24, the OVAL sample, which lacked any
detectable changes in TP53, carried a mutation in KRAS that was
found in both cfDNA and in the corresponding tumor. This
observation highlights a significant feature of the assay system
described here. Libraries created from cfDNA can be interrogated
with hundreds (as in this example), and even thousands, of
targeting probes. The sequencing of the resulting targeted
libraries revealed somatic mutations that reside within the tumor
and not within the germline of the affected individual. These
tumor-associated somatic markers can also be used to quantify the
amount of circulating DNA that is shed from the tumor (as opposed
to cfDNA that has germline sequence). Thus, the discovery of
mutations, regardless of their biological significance, also
provides an estimate of tumor content in admixed cfDNA.
[0351] Many targeted therapies are most successful in the presence
of normal genes (e.g., EGFR inhibitors work only in the presence of
wild-type KRAS). A quantitative assessment of circulating tumor DNA
levels becomes especially significant in these cases where
mutations in genes are not found. In other words, the demonstrable
presence of circulating tumor DNA coupled with a wild-type
sequencing result at a particular target gene suggests that the
target gene is normal within the tumor, and such results can have a
significant influence in guiding the choice of therapies. Such is
the case with the OVAL sample highlighted in FIG. 24. The presence
of the KRAS mutation in the cfDNA library suggested that this
patient's tumor harbors a wild-type TP53 gene(s).
[0352] Another example of aberrant gene discovery is shown in FIG.
25. The targeted quantitative genetic analysis system revealed the
presence of a significant amplification in the ERBB2 gene,
otherwise referred to as HER-2/neu. While this type of
amplification has been much publicized in breast cancer, it is
occasionally identified in colorectal carcinomas as well.
Conclusion
[0353] Validation experiments with cell line DNA revealed the
thresholds of detection of three types of genetic variation that
are central to driving neoplastic growth in cancers.
Characterization of cfDNA derived from cancer patients revealed
tumor-associated genetic changes that were well above the
thresholds set by reconstruction experiments in all four samples
analyzed. These data indicated that the quantitative analysis
system contemplated herein may have significant clinical utility,
especially in settings where liquid biopsies are most
appropriate.
[0354] In general, in the following claims, the terms used should
not be construed to limit the claims to the specific embodiments
disclosed in the specification and the claims, but should be
construed to include all possible embodiments along with the full
scope of equivalents to which such claims are entitled.
Accordingly, the claims are not limited by the disclosure.
Sequence CWU 1
1
562160DNAArtificial SequenceProbe 1taaacattgg aaaggtttct aattaaccag
gagatccaaa agaaagcggt tcaagtagca 60260DNAArtificial SequenceProbe
2gatctcagtt tttttggtta actatgtatt ttggtatatg aagcttctgg gttttgcaca
60360DNAArtificial SequenceProbe 3gacagataag catacatatt aacatggata
tatatgtgaa tttcattcaa atggttctca 60460DNAArtificial SequenceProbe
4agctcttagc ctttgggggg atgacactct tgagcggacg tggggacgcc tcgctcttta
60560DNAArtificial SequenceProbe 5aagcccccac cgccgcctct ttccaaaata
aacaccagcc agccgccgag cccggagtcg 60660DNAArtificial SequenceProbe
6gcctcccttc cccctccccg cccgacagcg gccgctcggg ccccggctct cggttataag
60760DNAArtificial SequenceProbe 7ggtgtggcag ccaggggggc gcactctgct
ctggctgggc cccttctccc atgttttctt 60860DNAArtificial SequenceProbe
8ttacacaacc tttgggcttg gacaacactt tggggtccaa agaacctaag agtctttctg
60960DNAArtificial SequenceProbe 9tgatgaaact tgggctggat ggggcacagg
tagggtgctt gttgctttca gtcagatgaa 601060DNAArtificial SequenceProbe
10aatgaaagaa aaggaggcca gattgctact cctggtccct gccacacact aggtacccta
601160DNAArtificial SequenceProbe 11attgacaata cctacataaa
actctttcca gaatgttgtt aagtcttagt cattagggag 601260DNAArtificial
SequenceProbe 12ggatttccac caacactgta ttcatgtacc catttttctc
ttaacctaac tttattggtc 601360DNAArtificial SequenceProbe
13caaaggggga aaaccatcag gacattattt aacaacggaa atatctaact gaaaggcaaa
601460DNAArtificial SequenceProbe 14caggcagacc aaccaaagtc
tttgttccac cttttaaaac taaatcacat tttcacagag 601560DNAArtificial
SequenceProbe 15ccccagccag cggtccgcaa cccttgccgc atccacgaaa
ctttgcccat agcagcgggc 601660DNAArtificial SequenceProbe
16cgactcatct cagcattaaa gtgataaaaa aataaattaa aaggcaagtg gacttcggtg
601760DNAArtificial SequenceProbe 17ctgtggcgcg cactgcgcgc
tgcgccaggt ttccgcacca agaccccttt aactcaagac 601860DNAArtificial
SequenceProbe 18ttctactgcg acgaggagga gaacttctac cagcagcagc
agcagagcga gctgcagccc 601960DNAArtificial SequenceProbe
19accgagctgc tgggaggaga catggtgaac cagagtttca tctgcgaccc ggacgacgag
602060DNAArtificial SequenceProbe 20gccgccgcct cagagtgcat
cgacccctcg gtggtcttcc cctaccctct caacgacagc 602160DNAArtificial
SequenceProbe 21ggcggctagg ggacaggggc ggggtgggca gcagctcgaa
tttcttccag atatcctcgc 602260DNAArtificial SequenceProbe
22agacgagctt ggcggcggcc gagaagccgc tccacataca gtcctggatg atgatgtttt
602360DNAArtificial SequenceProbe 23aggagagcag agaatccgag
gacggagaga aggcgctgga gtcttgcgag gcgcaggact 602460DNAArtificial
SequenceProbe 24taagagtggc ccgttaaata agctgccaat gaaaatggga
aaggtatcca gccgcccact 602560DNAArtificial SequenceProbe
25ttgtatttgt acagcattaa tctggtaatt gattatttta atgtaacctt gctaaaggag
602660DNAArtificial SequenceProbe 26gaggccacag caaacctcct
cacagcccac tggtcctcaa gaggtgccac gtctccacac 602760DNAArtificial
SequenceProbe 27agaggaggaa cgagctaaaa cggagctttt ttgccctgcg
tgaccagatc ccggagttgg 602860DNAArtificial SequenceProbe
28tccaacttga ccctcttggc agcaggatag tccttccgag tggagggagg cgctgcgtag
602960DNAArtificial SequenceProbe 29gcttggacgg acaggatgta
tgctgtggct tttttaagga taactacctt gggggccttt 603060DNAArtificial
SequenceProbe 30gcatttgatc atgcatttga aacaagttca taggtgattg
ctcaggacat ttctgttaga 603160DNAArtificial SequenceProbe
31cgccccgcgc cctcccagcc gggtccagcc ggagccatgg ggccggagcc gcagtgagca
603260DNAArtificial SequenceProbe 32ctctggcccc gccggccgcg
ggacctcggc ggggcatcca cagggcaggg tcccgccgct 603360DNAArtificial
SequenceProbe 33ggcatgactt ggagtgagtt tggatggggt ggccaggtct
gagaaggtcc cccgccagtg 603460DNAArtificial SequenceProbe
34gcagggcacc ttcttctgcc acccacctgt aaacagaggg ctcagcccag ctggaggcag
603560DNAArtificial SequenceProbe 35cccaagatct ccaagtactg
gggaacccca gggaggccct ggggggtggc agtgttccta 603660DNAArtificial
SequenceProbe 36ctaatgcaca caaagcctcc ccctggttag cagtggccct
ggtcagctct gaataaccaa 603760DNAArtificial SequenceProbe
37ctgctcctct tttagaaggc aggagggccc caagggaagc agaaggtgac agaaggggaa
603860DNAArtificial SequenceProbe 38tggggcagtg gcgggcaggc
actgggttgt aagttgggag tttgcggctg gggtcaggct 603960DNAArtificial
SequenceProbe 39tctgctgctg tttgtgcctc tctctgttac taacccgtcc
tctcgctgtt agacatctct 604060DNAArtificial SequenceProbe
40cccacccctc ccatgtcacc tgtatgacac ctgcattcca cccggcccca gccctcccct
604160DNAArtificial SequenceProbe 41tgggccaggt agtctcccta
gaaggtgatg ctgatgaggg tctggtgccc agggcgccac 604260DNAArtificial
SequenceProbe 42ggtgcccacc ccttgcatcc tggggggtag agcacattgg
gcacaaagca gaggcacata 604360DNAArtificial SequenceProbe
43caccctgcct ggtactgccc tattgcccct ggcacaccag ggcaaaacag cacagtgaaa
604460DNAArtificial SequenceProbe 44ccatttacag aaacaaacct
ccccaccaaa atgagaaaac tgtgtttctc cctggcactc 604560DNAArtificial
SequenceProbe 45ttattcttct tgtgcctggg cacggtaatg ctgctcatgg
tggtgcacga agggccaggg 604660DNAArtificial SequenceProbe
46gaaggatagg acagggtggg ctgggccagg ctgcatgcgc agagggacag gaactgcagc
604760DNAArtificial SequenceProbe 47gggcccggac cctgatgctc
atgtggctgt tgacctgtcc cggtatgaag gctgagacgg 604860DNAArtificial
SequenceProbe 48tctgtctcct gccatcccca agagatgctg ccacatctgg
atcctcagga ctctgtctgc 604960DNAArtificial SequenceProbe
49tcacgtccca gggcagtttt cttccctgaa gaaagttgga tggcatgatc tgtcttccca
605060DNAArtificial SequenceProbe 50gtgttgagaa cagactactg
acttctaata gcagcgactt ctttaccttg ataaaccaca 605160DNAArtificial
SequenceProbe 51aaaaaaagga tgggttccat atgggtggtg tcaagtgccc
acctcctagc aagtcagcag 605260DNAArtificial SequenceProbe
52ccctcacaag gtcaaagcta tacatcagct cctgtgacat tgactcatcc cccagacctt
605360DNAArtificial SequenceProbe 53aacccaccga gatctgcaaa
ctttgcagga tgcaccagat gtcttgtagc catgggtcaa 605460DNAArtificial
SequenceTYMSr4r probe 54tgcctccctc aggtgcctct gcacaaaacc agattgcttc
cctctaagag tatggttagt 605560DNAArtificial SequenceProbe
55gttttacttt gcctttagct gtggtctttc aaaccaccat ccctccttat cttcctctgc
605660DNAArtificial SequenceProbe 56ctctgcaatt tgttttccca
tattaaagaa ctgaagagct cagtgtggta ggctggcaag 605760DNAArtificial
SequenceProbe 57ttttaaatga tgttttaaag aattgaaact aacatactgt
tctgctttct cccccgggtt 605860DNAArtificial SequenceProbe
58cctgcccacc acttctccct aaactgaagc cccacatttg gagcagtcat ctttatcttg
605960DNAArtificial SequenceProbe 59ggttgcgctc caatcatgtt
acataaccta cggcaaggta tcgacaggat catactcctg 606060DNAArtificial
SequenceProbe 60gcacagttac atttgccagt ggcaacatcc ttaaaaatta
ataactgata ggtcacggac 606160DNAArtificial SequenceProbe
61cgtcccgccg cgccacttgg cctgcctccg tcccgccgcg ccacttcgcc tgcctccgtc
606260DNAArtificial SequenceProbe 62ctgtaaggcg aggaggacga
tgcgtcccct ccctcgcagg attgaggtta ggactaaacg 606335DNAArtificial
SequencePartner Oligo #138 63gtgaaaacca ggatcaactc ccgtgccagt cacat
356420DNAArtificial SequenceAdaptor 64nnnnnnnnca tggccgcagg
206520DNAArtificial SequenceAdaptor 65nnnnnnnnat cttagtggca
206620DNAArtificial SequenceAdaptor 66nnnnnnnncg gaactcggag
206720DNAArtificial SequenceAdaptor 67nnnnnnnnga ctccgatccc
206895DNAArtificial SequenceProbe 68atgtgactgg cacgggagtt
gatcctggtt ttcacgggtt tgagtggcat gagctaccta 60ctggatgtgc ctgactgttt
ccccttcttc ttccc 956995DNAArtificial SequenceProbe 69atgtgactgg
cacgggagtt gatcctggtt ttcacctatc tccaggatgg agagagggaa 60aaaaaagatg
ggtctgtgtg ggagggcagg tactt 957095DNAArtificial SequenceProbe
70atgtgactgg cacgggagtt gatcctggtt ttcacgaaag aagccaggtc ttcaattaat
60aagattccct ggtctcgttt gtctacctgt taatg 957195DNAArtificial
SequenceProbe 71atgtgactgg cacgggagtt gatcctggtt ttcaccagac
tcgcgcccaa ttttccccca 60ccccttgtta ttgccacaaa atcctgagga tgatc
957295DNAArtificial SequenceProbe 72atgtgactgg cacgggagtt
gatcctggtt ttcacaagca cctagcccca ttcctgctga 60gcaggaggtg gcaggtaccc
cagactggga ggtaa 957395DNAArtificial SequenceProbe 73atgtgactgg
cacgggagtt gatcctggtt ttcacagtcg gtggggccag gatgaggccc 60agtctgttca
cacatggctg ctgcctctca gctct 957495DNAArtificial SequenceProbe
74atgtgactgg cacgggagtt gatcctggtt ttcaccctgg ccctcagcca gtacagaaag
60tcatttgtca aggccttcag ttggcagacg tgctc 957595DNAArtificial
SequenceProbe 75atgtgactgg cacgggagtt gatcctggtt ttcacagaat
tcattgccag ctataaatct 60gtggaaacgc tgccacacaa tcttagcaca caaga
957695DNAArtificial SequenceProbe 76atgtgactgg cacgggagtt
gatcctggtt ttcacttact tccctccagt tttgttgctt 60gcaaaacaac agaatcttct
ctccatgaaa tcatg 957795DNAArtificial SequenceProbe 77atgtgactgg
cacgggagtt gatcctggtt ttcaccaggg gtatctatta tccccatttt 60ctcacaaagg
aaaccaagat aaaaggttta aatgg 957895DNAArtificial SequenceProbe
78atgtgactgg cacgggagtt gatcctggtt ttcactgtta cctttaaaag acatctgctt
60tctgccaaaa ttaatgtgct gaacttaaac ttacc 957995DNAArtificial
SequenceProbe 79atgtgactgg cacgggagtt gatcctggtt ttcacttccc
agtaaattac tcttaccaat 60gcaacagact ttaaagaagt tgtgttttac aatgc
958095DNAArtificial SequenceProbe 80atgtgactgg cacgggagtt
gatcctggtt ttcactaaat gacataacag ttatgatttt 60gcagaaaaca gatctgtatt
tatttcagtg ttact 958195DNAArtificial SequenceProbe 81atgtgactgg
cacgggagtt gatcctggtt ttcacgacag gttttgaaag atatttgtgt 60tactaatgac
tgtgctataa cttttttttc tttcc 958295DNAArtificial SequenceProbe
82atgtgactgg cacgggagtt gatcctggtt ttcacctgtg gcgcgcactg cgcgctgcgc
60caggtttccg caccaagacc cctttaactc aagac 958395DNAArtificial
SequenceProbe 83atgtgactgg cacgggagtt gatcctggtt ttcacggcgg
ctaggggaca ggggcggggt 60gggcagcagc tcgaatttct tccagatatc ctcgc
958495DNAArtificial SequenceProbe 84atgtgactgg cacgggagtt
gatcctggtt ttcacaccga gctgctggga ggagacatgg 60tgaaccagag tttcatctgc
gacccggacg acgag 958595DNAArtificial SequenceProbe 85atgtgactgg
cacgggagtt gatcctggtt ttcacaggag agcagagaat ccgaggacgg 60agagaaggcg
ctggagtctt gcgaggcgca ggact 958695DNAArtificial SequenceProbe
86atgtgactgg cacgggagtt gatcctggtt ttcacctgta agttatcgta aaaaggagca
60tctaggtagg tctttgtagc caatgttacc cgatt 958795DNAArtificial
SequenceProbe 87atgtgactgg cacgggagtt gatcctggtt ttcacaatgg
ccattcttcc aggaggcaca 60gaaattacag gccatgcaca gagagaaata cccga
958895DNAArtificial SequenceProbe 88atgtgactgg cacgggagtt
gatcctggtt ttcaccttgt tcgttccttg tactgagacc 60ctagtctgcc actgaggatt
tggtttttgc ccttc 958995DNAArtificial SequenceProbe 89atgtgactgg
cacgggagtt gatcctggtt ttcacatcaa gactcatcag taccatcaaa 60agctgagatg
aaacagtgta agtttcaaca gaaat 959095DNAArtificial SequenceProbe
90atgtgactgg cacgggagtt gatcctggtt ttcactgtgt ccagctgtga aactcagaga
60tgtaactgct gacatcctcc ctattttgca tctca 959195DNAArtificial
SequenceProbe 91atgtgactgg cacgggagtt gatcctggtt ttcacatttg
aaacaatttt atcatgaatg 60ccatgaccaa agtattcttc tgtatcttct ttctt
959295DNAArtificial SequenceProbe 92atgtgactgg cacgggagtt
gatcctggtt ttcactgatg ggtgggctcc cgaaggggcc 60tcccgcagac ttgcgaagtt
cccactctct gggcg 959395DNAArtificial SequenceProbe 93atgtgactgg
cacgggagtt gatcctggtt ttcaccaggg tgcgggggca tccaggctgc 60ccaagcggag
gctgggccgg ctgtgctggc ctctt 959495DNAArtificial SequenceProbe
94atgtgactgg cacgggagtt gatcctggtt ttcacttttg aaatgtgggt ttgttgccat
60gaaacgtgtt tcaagcatag ttttgacaga taacg 959595DNAArtificial
SequenceProbe 95atgtgactgg cacgggagtt gatcctggtt ttcactgccc
taaaagtgta tgtataacat 60ccctgatgtc tgcatttgtc ctttgactgg tgttt
959695DNAArtificial SequenceProbe 96atgtgactgg cacgggagtt
gatcctggtt ttcacaaccc ctcgaggctc agacctttgg 60agcaggagtg tgattctggc
caaccaccct ctctg 959795DNAArtificial SequenceProbe 97atgtgactgg
cacgggagtt gatcctggtt ttcaccataa atatgtgtgc tagtcctgtt 60agacccaagt
gctgcccaag ggcagcgccc tgctc 959895DNAArtificial SequenceProbe
98atgtgactgg cacgggagtt gatcctggtt ttcactactt gttaattaaa aattcaagag
60tttttttttc ttattctgag gttatctttt tacca 959995DNAArtificial
SequenceProbe 99atgtgactgg cacgggagtt gatcctggtt ttcacccaaa
atctgttttc caataaattc 60tcagatccag gaagaggaaa ggaaaaacat caaaa
9510095DNAArtificial SequenceProbe 100atgtgactgg cacgggagtt
gatcctggtt ttcacatact ccatctcccg taaaaatagt 60gagacttgag taatgtttga
tgtcacttgt ctttc 9510195DNAArtificial SequenceProbe 101atgtgactgg
cacgggagtt gatcctggtt ttcaccagtc accactatat tattctaggt 60atcccagaaa
agttaaagtc aaatctgaaa cacat 9510295DNAArtificial SequenceProbe
102atgtgactgg cacgggagtt gatcctggtt ttcaccgccc cgcgtccgac
ccgcggatcc 60cgcggcgtcc ggcccgggtg gtctggatcg cggag
9510395DNAArtificial SequenceProbe 103atgtgactgg cacgggagtt
gatcctggtt ttcacccata cgggcagcac gacgcgcgga 60ctgcgattgc agaagatgac
ctgggagggc tcgcg 9510495DNAArtificial SequenceProbe 104atgtgactgg
cacgggagtt gatcctggtt ttcactagag gggcttcaga ccgtgctatc 60gtccctgctg
ggtcgggcct aagcgccggg cccgt 9510595DNAArtificial SequenceProbe
105atgtgactgg cacgggagtt gatcctggtt ttcacggcgc cgaggaggag
atggaggccg 60ggcggccgcg gcccgtgctg cgctcggtga actcg
9510695DNAArtificial SequenceProbe 106atgtgactgg cacgggagtt
gatcctggtt ttcacggtgt gggccaccgt gcccagccac 60cggtgtggct ctttaacaac
ctttgcttgt cccga 9510795DNAArtificial SequenceProbe 107atgtgactgg
cacgggagtt gatcctggtt ttcacaagtg gtctatcctg tacttaccac 60aacaacctta
tctttttaaa aagtaaaacg tcagt 9510895DNAArtificial SequenceProbe
108atgtgactgg cacgggagtt gatcctggtt ttcaccttgt tcgttccttg
tactgagacc 60ctagtctgcc actgaggatt tggtttttgc ccttc
9510995DNAArtificial SequenceProbe 109atgtgactgg cacgggagtt
gatcctggtt ttcacatcaa gactcatcag taccatcaaa 60agctgagatg aaacagtgta
agtttcaaca gaaat 9511075DNAArtificial SequenceProbe 110atgtgactgg
cacgggagtt gatcctggtt ttcacaccta ctggatgtgc ctgactgttt 60ccccttcttc
ttccc 7511175DNAArtificial SequenceProbe 111atgtgactgg cacgggagtt
gatcctggtt ttcacgggaa aaaaaagatg ggtctgtgtg 60ggagggcagg tactt
7511275DNAArtificial SequenceProbe 112atgtgactgg cacgggagtt
gatcctggtt ttcacttaat aagattccct ggtctcgttt 60gtctacctgt taatg
7511375DNAArtificial SequenceProbe 113atgtgactgg cacgggagtt
gatcctggtt ttcaccccca ccccttgtta ttgccacaaa 60atcctgagga tgatc
7511475DNAArtificial SequenceProbe 114atgtgactgg cacgggagtt
gatcctggtt ttcacgctga gcaggaggtg gcaggtaccc 60cagactggga ggtaa
7511575DNAArtificial SequenceProbe 115atgtgactgg cacgggagtt
gatcctggtt ttcacggccc agtctgttca cacatggctg 60ctgcctctca gctct
7511675DNAArtificial SequenceProbe 116atgtgactgg cacgggagtt
gatcctggtt ttcacgaaag tcatttgtca aggccttcag 60ttggcagacg tgctc
7511775DNAArtificial SequenceProbe 117atgtgactgg cacgggagtt
gatcctggtt ttcacaatct gtggaaacgc tgccacacaa 60tcttagcaca caaga
7511875DNAArtificial SequenceProbe 118atgtgactgg cacgggagtt
gatcctggtt ttcactgctt gcaaaacaac agaatcttct 60ctccatgaaa tcatg
7511975DNAArtificial SequenceProbe 119atgtgactgg cacgggagtt
gatcctggtt ttcacatttt ctcacaaagg aaaccaagat 60aaaaggttta aatgg
7512075DNAArtificial SequenceProbe 120atgtgactgg cacgggagtt
gatcctggtt ttcactgctt tctgccaaaa ttaatgtgct 60gaacttaaac ttacc
7512175DNAArtificial SequenceProbe 121atgtgactgg cacgggagtt
gatcctggtt ttcacccaat gcaacagact ttaaagaagt 60tgtgttttac aatgc
7512275DNAArtificial SequenceProbe 122atgtgactgg cacgggagtt
gatcctggtt ttcacatttt gcagaaaaca gatctgtatt 60tatttcagtg ttact
7512375DNAArtificial SequenceProbe 123atgtgactgg cacgggagtt
gatcctggtt ttcactgtgt tactaatgac tgtgctataa 60cttttttttc tttcc
7512475DNAArtificial SequenceProbe 124atgtgactgg cacgggagtt
gatcctggtt ttcactgcgc caggtttccg caccaagacc 60cctttaactc aagac
7512575DNAArtificial SequenceProbe 125atgtgactgg cacgggagtt
gatcctggtt ttcacggggt gggcagcagc tcgaatttct 60tccagatatc ctcgc
7512675DNAArtificial SequenceProbe 126atgtgactgg cacgggagtt
gatcctggtt ttcaccatgg tgaaccagag tttcatctgc 60gacccggacg acgag
7512775DNAArtificial SequenceProbe 127atgtgactgg cacgggagtt
gatcctggtt ttcacgacgg agagaaggcg ctggagtctt 60gcgaggcgca ggact
7512875DNAArtificial
SequenceProbe 128atgtgactgg cacgggagtt gatcctggtt ttcacgagca
tctaggtagg tctttgtagc 60caatgttacc cgatt 7512975DNAArtificial
SequenceProbe 129atgtgactgg cacgggagtt gatcctggtt ttcacgcaca
gaaattacag gccatgcaca 60gagagaaata cccga 7513075DNAArtificial
SequenceProbe 130atgtgactgg cacgggagtt gatcctggtt ttcacagacc
ctagtctgcc actgaggatt 60tggtttttgc ccttc 7513175DNAArtificial
SequenceProbe 131atgtgactgg cacgggagtt gatcctggtt ttcactcaaa
agctgagatg aaacagtgta 60agtttcaaca gaaat 7513275DNAArtificial
SequenceProbe 132atgtgactgg cacgggagtt gatcctggtt ttcacagaga
tgtaactgct gacatcctcc 60ctattttgca tctca 7513375DNAArtificial
SequenceProbe 133atgtgactgg cacgggagtt gatcctggtt ttcacgaatg
ccatgaccaa agtattcttc 60tgtatcttct ttctt 7513475DNAArtificial
SequenceProbe 134atgtgactgg cacgggagtt gatcctggtt ttcacgggcc
tcccgcagac ttgcgaagtt 60cccactctct gggcg 7513575DNAArtificial
SequenceProbe 135atgtgactgg cacgggagtt gatcctggtt ttcacgctgc
ccaagcggag gctgggccgg 60ctgtgctggc ctctt 7513675DNAArtificial
SequenceProbe 136atgtgactgg cacgggagtt gatcctggtt ttcacgccat
gaaacgtgtt tcaagcatag 60ttttgacaga taacg 7513775DNAArtificial
SequenceProbe 137atgtgactgg cacgggagtt gatcctggtt ttcacaacat
ccctgatgtc tgcatttgtc 60ctttgactgg tgttt 7513875DNAArtificial
SequenceProbe 138atgtgactgg cacgggagtt gatcctggtt ttcactttgg
agcaggagtg tgattctggc 60caaccaccct ctctg 7513975DNAArtificial
SequenceProbe 139atgtgactgg cacgggagtt gatcctggtt ttcacctgtt
agacccaagt gctgcccaag 60ggcagcgccc tgctc 7514075DNAArtificial
SequenceProbe 140atgtgactgg cacgggagtt gatcctggtt ttcacaagag
tttttttttc ttattctgag 60gttatctttt tacca 7514175DNAArtificial
SequenceProbe 141atgtgactgg cacgggagtt gatcctggtt ttcacaattc
tcagatccag gaagaggaaa 60ggaaaaacat caaaa 7514275DNAArtificial
SequenceProbe 142atgtgactgg cacgggagtt gatcctggtt ttcacatagt
gagacttgag taatgtttga 60tgtcacttgt ctttc 7514375DNAArtificial
SequenceProbe 143atgtgactgg cacgggagtt gatcctggtt ttcactaggt
atcccagaaa agttaaagtc 60aaatctgaaa cacat 7514475DNAArtificial
SequenceProbe 144atgtgactgg cacgggagtt gatcctggtt ttcacgatcc
cgcggcgtcc ggcccgggtg 60gtctggatcg cggag 7514575DNAArtificial
SequenceProbe 145atgtgactgg cacgggagtt gatcctggtt ttcacgcgga
ctgcgattgc agaagatgac 60ctgggagggc tcgcg 7514675DNAArtificial
SequenceProbe 146atgtgactgg cacgggagtt gatcctggtt ttcacctatc
gtccctgctg ggtcgggcct 60aagcgccggg cccgt 7514775DNAArtificial
SequenceProbe 147atgtgactgg cacgggagtt gatcctggtt ttcacggccg
ggcggccgcg gcccgtgctg 60cgctcggtga actcg 7514875DNAArtificial
SequenceProbe 148atgtgactgg cacgggagtt gatcctggtt ttcacgccac
cggtgtggct ctttaacaac 60ctttgcttgt cccga 7514975DNAArtificial
SequenceProbe 149atgtgactgg cacgggagtt gatcctggtt ttcacaccac
aacaacctta tctttttaaa 60aagtaaaacg tcagt 7515075DNAArtificial
SequenceProbe 150atgtgactgg cacgggagtt gatcctggtt ttcacagacc
ctagtctgcc actgaggatt 60tggtttttgc ccttc 7515175DNAArtificial
SequenceProbe 151atgtgactgg cacgggagtt gatcctggtt ttcactcaaa
agctgagatg aaacagtgta 60agtttcaaca gaaat 7515258DNAArtificial
SequenceACA2_FLFP primer 152aatgatacgg cgaccaccga gatctacacg
tcatgcagga ccagagaatt cgaataca 5815357DNAArtificial
SequenceCAC3_FLRP primer 153caagcagaag acggcatacg agatgtgact
ggcacgggag ttgatcctgg ttttcac 5715475DNAArtificial SequenceProbe
154atgtgactgg cacgggagtt gatcctggtt ttcaccgaat gagggtgatg
tttttccgcg 60gcacctcctt caggt 7515575DNAArtificial SequenceProbe
155atgtgactgg cacgggagtt gatcctggtt ttcacgttgt agtcggtcat
gatggtcgag 60gtgcggagct tgctc 7515675DNAArtificial SequenceProbe
156atgtgactgg cacgggagtt gatcctggtt ttcacgcagc tcctggtgct
tccggcggta 60cactgcaggt gggtg 7515775DNAArtificial SequenceProbe
157atgtgactgg cacgggagtt gatcctggtt ttcacctaca caggccactt
cctacaggaa 60gcctccctgg atctc 7515875DNAArtificial SequenceProbe
158atgtgactgg cacgggagtt gatcctggtt ttcacgaaat actaataaaa
tgattaaaga 60aggtgtgtct ttaat 7515975DNAArtificial SequenceProbe
159atgtgactgg cacgggagtt gatcctggtt ttcactatat ggaaaataat
tatttgtatt 60atatagggca gagtc 7516075DNAArtificial SequenceProbe
160atgtgactgg cacgggagtt gatcctggtt ttcacattag acccaatatg
gtctgcagat 60tttattagaa gaaat 7516175DNAArtificial SequenceProbe
161atgtgactgg cacgggagtt gatcctggtt ttcacgtgaa ccagcagact
gtgttgcaag 60tataacccca cgtga 7516275DNAArtificial SequenceProbe
162atgtgactgg cacgggagtt gatcctggtt ttcacgccat ggagcctaag
gaagtttcag 60caaggcccta agggg 7516375DNAArtificial SequenceProbe
163atgtgactgg cacgggagtt gatcctggtt ttcaccccag gaattggcct
gccttagtat 60ttctgctgtg ctcag 7516475DNAArtificial SequenceProbe
164atgtgactgg cacgggagtt gatcctggtt ttcactttga gggtgcagct
gggatcttgg 60tcagttgtgt ttcct 7516575DNAArtificial SequenceProbe
165atgtgactgg cacgggagtt gatcctggtt ttcaccacat catgaaaaga
tctctgaatt 60ggtgtctggg gatct 7516675DNAArtificial SequenceProbe
166atgtgactgg cacgggagtt gatcctggtt ttcactgagg accaggtcac
aggacctctt 60tggactgcag tttcc 7516775DNAArtificial SequenceProbe
167atgtgactgg cacgggagtt gatcctggtt ttcactaacc actgccactc
cccaccctct 60agggttgtca atgaa 7516875DNAArtificial SequenceProbe
168atgtgactgg cacgggagtt gatcctggtt ttcacgagct ctaccaatgt
gagtgaccat 60tatcactcct acatg 7516975DNAArtificial SequenceProbe
169atgtgactgg cacgggagtt gatcctggtt ttcacaaaat tgtgattcag
tgggtagatt 60ctgtgtgtaa agccc 7517075DNAArtificial SequenceProbe
170atgtgactgg cacgggagtt gatcctggtt ttcactatgt gctcagttcc
ctcctctatg 60caatggaccg accgt 7517175DNAArtificial SequenceProbe
171atgtgactgg cacgggagtt gatcctggtt ttcacgtgta aattgccgag
cacgtagtaa 60ccatgcaaca agtgt 7517275DNAArtificial SequenceProbe
172atgtgactgg cacgggagtt gatcctggtt ttcactgggg acacagtgtg
tgctgccatc 60tcccttctac cggca 7517375DNAArtificial SequenceProbe
173atgtgactgg cacgggagtt gatcctggtt ttcacaagag cctttccctc
tgcccttttc 60aagcctctgc ccatc 7517475DNAArtificial SequenceProbe
174atgtgactgg cacgggagtt gatcctggtt ttcacgacca cactgagttc
tctgtgacct 60gcaggtcagc tcacc 7517575DNAArtificial SequenceProbe
175atgtgactgg cacgggagtt gatcctggtt ttcactttcc tatctctctg
cctggagggt 60ggtggagggc tggtt 7517675DNAArtificial SequenceProbe
176atgtgactgg cacgggagtt gatcctggtt ttcacaaaca ggagctgcgc
cggtggaagc 60atgtgggagc tagaa 7517775DNAArtificial SequenceProbe
177atgtgactgg cacgggagtt gatcctggtt ttcacggaca ctgaaggagc
tccccacccc 60ctgatcagcc aggag 7517875DNAArtificial SequenceProbe
178atgtgactgg cacgggagtt gatcctggtt ttcacgggaa ctgcagctgc
tctggtgggg 60ggaaggttgg gagct 7517975DNAArtificial SequenceProbe
179atgtgactgg cacgggagtt gatcctggtt ttcacaccca attccaggga
ctagcataac 60gaagtgacac cttgg 7518075DNAArtificial SequenceProbe
180atgtgactgg cacgggagtt gatcctggtt ttcaccctgc ccccttggga
gtccctgggg 60ctctgtgcac tcacc 7518175DNAArtificial SequenceProbe
181atgtgactgg cacgggagtt gatcctggtt ttcacggaag cacccccggt
attaaaacga 60acggggcgga aagaa 7518275DNAArtificial SequenceProbe
182atgtgactgg cacgggagtt gatcctggtt ttcacctaac aaaggggacg
cgacccgggg 60tccagtgccc caggg 7518375DNAArtificial SequenceProbe
183atgtgactgg cacgggagtt gatcctggtt ttcaccctgg ggggactggg
tggcctcacc 60cccaacccgg tcatc 7518475DNAArtificial SequenceProbe
184atgtgactgg cacgggagtt gatcctggtt ttcaccgcgc tccagcttct
cgcgggcgga 60gaagccgctc cacat 7518575DNAArtificial SequenceProbe
185atgtgactgg cacgggagtt gatcctggtt ttcaccccac ccggccgccg
agtgcgtgga 60tcccgccgtg gtctt 7518675DNAArtificial SequenceProbe
186atgtgactgg cacgggagtt gatcctggtt ttcacgggca cgggcgctgg
ctcgcgcttg 60ttcacgggaa agggg 7518775DNAArtificial SequenceProbe
187atgtgactgg cacgggagtt gatcctggtt ttcacaacat ggatatatat
gtgaatttca 60ttcaaatggt tctca 7518875DNAArtificial SequenceProbe
188atgtgactgg cacgggagtt gatcctggtt ttcactaaac caacattctt
aatgtcaaca 60caatgtttgt ttaaa 7518975DNAArtificial SequenceProbe
189atgtgactgg cacgggagtt gatcctggtt ttcaccccta cgtggagagt
gaggatgcac 60ccccacagaa gaaga 7519075DNAArtificial SequenceProbe
190atgtgactgg cacgggagtt gatcctggtt ttcacatgac actcttgagc
ggacgtgggg 60acgcctcgct cttta 7519175DNAArtificial SequenceProbe
191atgtgactgg cacgggagtt gatcctggtt ttcactctca cgctcaggga
ccacgtgccg 60gagttggtaa agaat 7519275DNAArtificial SequenceProbe
192atgtgactgg cacgggagtt gatcctggtt ttcaccagtg gcctttttca
aaatgaccac 60cttggcggcc ttctc 7519375DNAArtificial SequenceProbe
193atgtgactgg cacgggagtt gatcctggtt ttcacgctag ggggctgggg
ttggggtggg 60ggtggtgggc ctgcc 7519475DNAArtificial SequenceProbe
194atgtgactgg cacgggagtt gatcctggtt ttcaccagtt tccataggtc
tgaaaatgtt 60tcctgactca gaggg 7519575DNAArtificial SequenceProbe
195atgtgactgg cacgggagtt gatcctggtt ttcacctgcc atggaggagc
cgcagtcaga 60tcctagcgtc gagcc 7519675DNAArtificial SequenceProbe
196atgtgactgg cacgggagtt gatcctggtt ttcactcatg ctggatcccc
acttttcctc 60ttgcagcagc cagac 7519775DNAArtificial SequenceProbe
197atgtgactgg cacgggagtt gatcctggtt ttcacagccc cccagccctc
caggtcccca 60gccctccagg tcccc 7519875DNAArtificial SequenceProbe
198atgtgactgg cacgggagtt gatcctggtt ttcacgcaga gacctgtggg
aagcgaaaat 60tccatgggac tgact 7519975DNAArtificial SequenceProbe
199atgtgactgg cacgggagtt gatcctggtt ttcacgcagg gggatacggc
caggcattga 60agtctcatgg aagcc 7520075DNAArtificial SequenceProbe
200atgtgactgg cacgggagtt gatcctggtt ttcacccgtg caagtcacag
acttggctgt 60cccagaatgc aagaa 7520175DNAArtificial SequenceProbe
201atgtgactgg cacgggagtt gatcctggtt ttcacccaga aaacctacca
gggcagctac 60ggtttccgtc tgggc 7520275DNAArtificial SequenceProbe
202atgtgactgg cacgggagtt gatcctggtt ttcacgaagg gacagaagat
gacaggggcc 60aggagggggc tggtg 7520375DNAArtificial SequenceProbe
203atgtgactgg cacgggagtt gatcctggtt ttcacgtggc ccctgcacca
gcagctccta 60caccggcggc ccctg 7520475DNAArtificial SequenceProbe
204atgtgactgg cacgggagtt gatcctggtt ttcacggggg gagcagcctc
tggcattctg 60ggagcttcat ctgga 7520575DNAArtificial SequenceProbe
205atgtgactgg cacgggagtt gatcctggtt ttcacccccg gacgatattg
aacaatggtt 60cactgaagac ccagg 7520675DNAArtificial SequenceProbe
206atgtgactgg cacgggagtt gatcctggtt ttcacctggg gggctggggg
gctgaggacc 60tggtcctctg actgc 7520775DNAArtificial SequenceProbe
207atgtgactgg cacgggagtt gatcctggtt ttcaccctgg gcaaccagcc
ctgtcgtctc 60tccagcccca gctgc 7520875DNAArtificial SequenceProbe
208atgtgactgg cacgggagtt gatcctggtt ttcacccatc gctatctgag
cagcgctcat 60ggtgggggca gcgcc 7520975DNAArtificial SequenceProbe
209atgtgactgg cacgggagtt gatcctggtt ttcacgccat ctacaagcag
tcacagcaca 60tgacggaggt tgtga 7521075DNAArtificial SequenceProbe
210atgtgactgg cacgggagtt gatcctggtt ttcaccatgg cgcggacgcg
ggtgccgggc 60gggggtgtgg aatca 7521175DNAArtificial SequenceProbe
211atgtgactgg cacgggagtt gatcctggtt ttcactttgc caactggcca
agacctgccc 60tgtgcagctg tgggt 7521275DNAArtificial SequenceProbe
212atgtgactgg cacgggagtt gatcctggtt ttcactgctt tatctgttca
cttgtgccct 60gactttcaac tctgt 7521375DNAArtificial SequenceProbe
213atgtgactgg cacgggagtt gatcctggtt ttcacgaggg ccactgacaa
ccacccttaa 60cccctcctcc cagag 7521475DNAArtificial SequenceProbe
214atgtgactgg cacgggagtt gatcctggtt ttcaccctca ggcggctcat
agggcaccac 60cacactatgt cgaaa 7521575DNAArtificial SequenceProbe
215atgtgactgg cacgggagtt gatcctggtt ttcacaggaa atttgcgtgt
ggagtatttg 60gatgacagaa acact 7521675DNAArtificial SequenceProbe
216atgtgactgg cacgggagtt gatcctggtt ttcacccagg gtccccaggc
ctctgattcc 60tcactgattg ctctt 7521775DNAArtificial SequenceProbe
217atgtgactgg cacgggagtt gatcctggtt ttcacgaggc aagcagaggc
tggggcacag 60caggccagtg tgcag 7521875DNAArtificial SequenceProbe
218atgtgactgg cacgggagtt gatcctggtt ttcaccctgg agtcttccag
tgtgatgatg 60gtgaggatgg gcctc 7521975DNAArtificial SequenceProbe
219atgtgactgg cacgggagtt gatcctggtt ttcacactac atgtgtaaca
gttcctgcat 60gggcggcatg aaccg 7522075DNAArtificial SequenceProbe
220atgtgactgg cacgggagtt gatcctggtt ttcaccttgc cacaggtctc
cccaaggcgc 60actggcctca tcttg 7522175DNAArtificial SequenceProbe
221atgtgactgg cacgggagtt gatcctggtt ttcacctgca cccttggtct
cctccaccgc 60ttcttgtcct gcttg 7522275DNAArtificial SequenceProbe
222atgtgactgg cacgggagtt gatcctggtt ttcaccctcg cttagtgctc
cctgggggca 60gctcgtggtg aggct 7522375DNAArtificial SequenceProbe
223atgtgactgg cacgggagtt gatcctggtt ttcacgaccg gcgcacagag
gaagagaatc 60tccgcaagaa agggg 7522475DNAArtificial SequenceProbe
224atgtgactgg cacgggagtt gatcctggtt ttcactctcc caggacaggc
acaaacacgc 60acctcaaagc tgttc 7522575DNAArtificial SequenceProbe
225atgtgactgg cacgggagtt gatcctggtt ttcactctct tttcctatcc
tgagtagtgg 60taatctactg ggacg 7522675DNAArtificial SequenceProbe
226atgtgactgg cacgggagtt gatcctggtt ttcacggaca ggtaggacct
gatttcctta 60ctgcctcttg cttct 7522775DNAArtificial SequenceProbe
227atgtgactgg cacgggagtt gatcctggtt ttcacggcat tttgagtgtt
agactggaaa 60ctttccactt gataa 7522875DNAArtificial SequenceProbe
228atgtgactgg cacgggagtt gatcctggtt ttcaccctga agggtgaaat
attctccatc 60cagtggtttc ttctt 7522975DNAArtificial
SequenceProbe
229atgtgactgg cacgggagtt gatcctggtt ttcaccctag cactgcccaa
caacaccagc 60tcctctcccc agcca 7523075DNAArtificial SequenceProbe
230atgtgactgg cacgggagtt gatcctggtt ttcactgcct cagattcact
tttatcacct 60ttccttgcct ctttc 7523175DNAArtificial SequenceProbe
231atgtgactgg cacgggagtt gatcctggtt ttcacatggc tttccaacct
aggaaggcag 60gggagtaggg ccagg 7523275DNAArtificial SequenceProbe
232atgtgactgg cacgggagtt gatcctggtt ttcaccctgg agtgagccct
gctcccccct 60ggctccttcc cagcc 7523375DNAArtificial SequenceProbe
233atgtgactgg cacgggagtt gatcctggtt ttcactccga gagctgaatg
aggccttgga 60actcaaggat gccca 7523475DNAArtificial SequenceProbe
234atgtgactgg cacgggagtt gatcctggtt ttcaccatct tttaactcag
gtactgtgta 60tatacttact tctcc 7523575DNAArtificial SequenceProbe
235atgtgactgg cacgggagtt gatcctggtt ttcacggcag gggagggaga
gatgggggtg 60ggaggctgtc agtgg 7523675DNAArtificial SequenceProbe
236atgtgactgg cacgggagtt gatcctggtt ttcacgtcag tctgagtcag
gcccttctgt 60cttgaacatg agttt 7523775DNAArtificial SequenceProbe
237atgtgactgg cacgggagtt gatcctggtt ttcaccctga agtccaaaaa
gggtcagtct 60acctcccgcc ataaa 7523875DNAArtificial SequenceProbe
238atgtgactgg cacgggagtt gatcctggtt ttcacggcac agaccctctc
actcatgtga 60tgtcatctct cctcc 7523975DNAArtificial SequenceProbe
239atgtgactgg cacgggagtt gatcctggtt ttcaccaggg gcttatgtgt
ctccttgatg 60acctgcggcg acgtc 7524075DNAArtificial SequenceProbe
240atgtgactgg cacgggagtt gatcctggtt ttcacccatc atctcctccc
ttccccttct 60gcccaggctg ttgca 7524175DNAArtificial SequenceProbe
241atgtgactgg cacgggagtt gatcctggtt ttcacaattc tggcttctcc
ctgctcacac 60tttcttccat tgcat 7524275DNAArtificial SequenceProbe
242atgtgactgg cacgggagtt gatcctggtt ttcacgtcag ctcgtgttgg
caacatacca 60tcttcaacct ctgca 7524375DNAArtificial SequenceProbe
243atgtgactgg cacgggagtt gatcctggtt ttcactaatt tcttggcccc
tcttcggtaa 60ccctgagcca aatgt 7524475DNAArtificial SequenceProbe
244atgtgactgg cacgggagtt gatcctggtt ttcacggtga aataaaggaa
gatactagtt 60ttgctgaaaa tgaca 7524575DNAArtificial SequenceProbe
245atgtgactgg cacgggagtt gatcctggtt ttcacactca tttgtatctg
aagtggaacc 60aaatgatact gatcc 7524675DNAArtificial SequenceProbe
246atgtgactgg cacgggagtt gatcctggtt ttcacagttg agaccattca
caggccaaag 60acggtacaac ttcct 7524775DNAArtificial SequenceProbe
247atgtgactgg cacgggagtt gatcctggtt ttcacgaaaa tgaatgctct
gagctttgga 60agctctcagg gtaca 7524875DNAArtificial SequenceProbe
248atgtgactgg cacgggagtt gatcctggtt ttcacgggcc atcgcgatgt
cgcacggtac 60ctgcgcgcgg ctgcg 7524975DNAArtificial SequenceProbe
249atgtgactgg cacgggagtt gatcctggtt ttcaccccca tccagcttca
aaagctcttc 60gaatcattga tgtgc 7525075DNAArtificial SequenceProbe
250atgtgactgg cacgggagtt gatcctggtt ttcactgcca agcctgaact
acccctcttt 60tacactccta ttgat 7525175DNAArtificial SequenceProbe
251atgtgactgg cacgggagtt gatcctggtt ttcacccacc ctgactgtgc
tctgtccccc 60cagggctgga catcc 7525275DNAArtificial SequenceProbe
252atgtgactgg cacgggagtt gatcctggtt ttcacagtca ggagtgggat
gatcttataa 60aactcgtaga aagag 7525375DNAArtificial SequenceProbe
253atgtgactgg cacgggagtt gatcctggtt ttcaccttcg gggagacaac
gacggcggtg 60gcgggagctt ctcca 7525475DNAArtificial SequenceProbe
254atgtgactgg cacgggagtt gatcctggtt ttcaccatac agtcctggat
gatgatgttt 60ttgatgaagg tctcg 7525575DNAArtificial SequenceProbe
255atgtgactgg cacgggagtt gatcctggtt ttcactttta ctgttcttcc
tcagacattc 60aaacgtgttt tgatc 7525675DNAArtificial SequenceProbe
256atgtgactgg cacgggagtt gatcctggtt ttcacgtgga agcatactgc
aaaatatttg 60ttttcagtct ctgca 7525775DNAArtificial SequenceProbe
257atgtgactgg cacgggagtt gatcctggtt ttcacacgta cccctctcag
cccctcctct 60tggactccag ccatg 7525875DNAArtificial SequenceProbe
258atgtgactgg cacgggagtt gatcctggtt ttcacgtggc gtaagcgcgg
cacgcggcgc 60agtggtcccc gtcct 7525921DNAArtificial SequenceAdaptor
259nnnnnaagat cttagtggca c 2126021DNAArtificial SequenceAdaptor
260nnnnncgaca gaactattgc c 2126121DNAArtificial SequenceAdaptor
261nnnnnactat cttagtggca c 2126221DNAArtificial SequenceAdaptor
262nnnnnctcca gaactattgc c 2126321DNAArtificial SequenceAdaptor
263nnnnnagcat cttagtggca c 2126421DNAArtificial SequenceAdaptor
264nnnnncatca gaactattgc c 2126521DNAArtificial SequenceAdaptor
265nnnnnataat cttagtggca c 2126621DNAArtificial SequenceAdaptor
266nnnnnaagaa ggtagaccct c 2126721DNAArtificial SequenceAdaptor
267nnnnntttct ctactcgtga c 2126821DNAArtificial SequenceAdaptor
268nnnnnactaa ggtagaccct c 2126921DNAArtificial SequenceAdaptor
269nnnnngaagc tacgagtatc c 2127021DNAArtificial SequenceAdaptor
270nnnnnagcaa ggtagaccct c 2127121DNAArtificial SequenceAdaptor
271nnnnncattg acgtctagag c 2127221DNAArtificial SequenceAdaptor
272nnnnntcact ctactcgtga c 2127321DNAArtificial SequenceAdaptor
273nnnnnataaa ggtagaccct c 2127421DNAArtificial SequenceAdaptor
274nnnnntacct ctactcgtga c 2127520DNAArtificial SequenceAdaptor
275nnnnnttttg tgtgtgtgtg 2027620DNAArtificial SequenceAdaptor
276nnnnnactac acacacacac 2027720DNAArtificial SequenceAdaptor
277nnnnnctcgt gtgtgtgtgt 2027820DNAArtificial SequenceAdaptor
278nnnnngaaca cacacacaca 2027920DNAArtificial SequenceAdaptor
279nnnnncatgt gtgtgtgtgt 2028020DNAArtificial SequenceAdaptor
280nnnnngtgca cacacacaca 2028120DNAArtificial SequenceAdaptor
281nnnnnataac acacacacac 2028220DNAArtificial SequenceAdaptor
282nnnnntactg tgtgtgtgtg 2028325DNAArtificial SequencePrimer
283tgcaggacca gagaattcga ataca 2528458DNAArtificial SequencePrimer
284aatgatacgg cgaccaccga gatctacacg tcatgcagga ccagagaatt cgaataca
5828518DNAArtificial SequencePrimer 285cggtggctca cgcctgta
1828618DNAArtificial SequencePrimer 286gcctcggcct cccaaagt
1828721DNAArtificial SequencePrimer 287gaggctgagg caggagaatc g
2128818DNAArtificial SequencePrimer 288gtcgcccagg ctggagtg
1828925DNAArtificial SequenceElement 1 289tgcaggacca gagaattcga
ataca 252905DNAArtificial SequenceElement 2 290cgggt
52915DNAArtificial SequenceElement 2 291cggtg 52925DNAArtificial
SequenceElement 2 292cgtgg 52935DNAArtificial SequenceElement 2
293gcggt 52945DNAArtificial SequenceElement 2 294gcgtg
52955DNAArtificial SequenceElement 2 295gctgg 52965DNAArtificial
SequenceElement 2 296ggcgt 52975DNAArtificial SequenceElement 2
297ggctg 52985DNAArtificial SequenceElement 2 298gggct
52995DNAArtificial SequenceElement 2 299ttaaa 53005DNAArtificial
SequenceElement 2 300ttacc 53015DNAArtificial SequenceElement 2
301ttatt 53025DNAArtificial SequenceElement 2 302ttcac
53035DNAArtificial SequenceElement 2 303ttcca 53045DNAArtificial
SequenceElement 2 304tttat 53055DNAArtificial SequenceElement 2
305tttta 53065DNAArtificial SequenceElement 2 306gcacg
53075DNAArtificial SequenceElement 2 307gcagc 53085DNAArtificial
SequenceElement 2 308gccag 53095DNAArtificial SequenceElement 2
309gccga 53105DNAArtificial SequenceElement 2 310gcgac
53115DNAArtificial SequenceElement 2 311gcgca 53125DNAArtificial
SequenceElement 2 312ggaaa 53135DNAArtificial SequenceElement 2
313ggacc 53145DNAArtificial SequenceElement 2 314ggatt
53155DNAArtificial SequenceElement 2 315ggcac 53165DNAArtificial
SequenceElement 2 316ggcca 53175DNAArtificial SequenceElement 2
317ggtat 53185DNAArtificial SequenceElement 2 318ggtta
53195DNAArtificial SequenceElement 2 319gtagt 53205DNAArtificial
SequenceElement 2 320gtatg 53215DNAArtificial SequenceElement 2
321gtgat 53225DNAArtificial SequenceElement 2 322ccgtc
53235DNAArtificial SequenceElement 2 323cctcg 53245DNAArtificial
SequenceElement 2 324cctgc 53255DNAArtificial SequenceElement 2
325cgaat 53265DNAArtificial SequenceElement 2 326cgata
53275DNAArtificial SequenceElement 2 327cgcct 53285DNAArtificial
SequenceElement 2 328cgctc 53295DNAArtificial SequenceElement 2
329cgtaa 53305DNAArtificial SequenceElement 2 330cgtcc
53315DNAArtificial SequenceElement 2 331cgttt 53325DNAArtificial
SequenceElement 2 332ctaag 53335DNAArtificial SequenceElement 2
333ctaga 53345DNAArtificial SequenceElement 2 334ctccg
53355DNAArtificial SequenceElement 2 335ctcgc 53365DNAArtificial
SequenceElement 2 336ctgaa 53375DNAArtificial SequenceElement 2
337ctgcc 53385DNAArtificial SequenceElement 2 338ttgtc
53395DNAArtificial SequenceElement 2 339tttcg 53405DNAArtificial
SequenceElement 2 340tttgc 53415DNAArtificial SequenceElement 2
341aaaaa 53425DNAArtificial SequenceElement 2 342aaacc
53435DNAArtificial SequenceElement 2 343aaatt 53445DNAArtificial
SequenceElement 2 344aacac 53455DNAArtificial SequenceElement 2
345aacca 53465DNAArtificial SequenceElement 2 346aatat
53475DNAArtificial SequenceElement 2 347aatta 53485DNAArtificial
SequenceElement 2 348acaac 53495DNAArtificial SequenceElement 2
349acaca 53505DNAArtificial SequenceElement 2 350accaa
53515DNAArtificial SequenceElement 2 351acccc 53525DNAArtificial
SequenceElement 2 352acctt 53535DNAArtificial SequenceElement 2
353actct 53545DNAArtificial SequenceElement 2 354gggtc
53555DNAArtificial SequenceElement 2 355ggtcg 53565DNAArtificial
SequenceElement 2 356ggtgc 53575DNAArtificial SequenceElement 2
357gtcgg 53585DNAArtificial SequenceElement 2 358gtgcg
53595DNAArtificial SequenceElement 2 359gtggc 53605DNAArtificial
SequenceElement 2 360tgcgg 53615DNAArtificial SequenceElement 2
361tggcg 53625DNAArtificial SequenceElement 2 362tgggc
53635DNAArtificial SequenceElement 2 363aaagg 53645DNAArtificial
SequenceElement 2 364aagag 53655DNAArtificial SequenceElement 2
365aagga 53665DNAArtificial SequenceElement 2 366accgg
53675DNAArtificial SequenceElement 2 367acgcg 53685DNAArtificial
SequenceElement 2 368acggc 53695DNAArtificial SequenceElement 2
369agaag 53705DNAArtificial SequenceElement 2 370gtgta
53715DNAArtificial SequenceElement 2 371gttag 53725DNAArtificial
SequenceElement 2 372gttga 53735DNAArtificial SequenceElement 2
373taggt 53745DNAArtificial SequenceElement 2 374tagtg
53755DNAArtificial SequenceElement 2 375tatgg 53765DNAArtificial
SequenceElement 2 376tgagt
53775DNAArtificial SequenceElement 2 377tgatg 53785DNAArtificial
SequenceElement 2 378tggat 53795DNAArtificial SequenceElement 2
379tggta 53805DNAArtificial SequenceElement 2 380tgtag
53815DNAArtificial SequenceElement 2 381tgtga 53825DNAArtificial
SequenceElement 2 382ttagg 53835DNAArtificial SequenceElement 2
383ttgag 53845DNAArtificial SequenceElement 2 384ttgga
53855DNAArtificial SequenceElement 2 385aacgt 53865DNAArtificial
SequenceElement 2 386ctgtt 53875DNAArtificial SequenceElement 2
387cttgt 53885DNAArtificial SequenceElement 2 388ctttg
53895DNAArtificial SequenceElement 2 389gaact 53905DNAArtificial
SequenceElement 2 390gaatc 53915DNAArtificial SequenceElement 2
391gacat 53925DNAArtificial SequenceElement 2 392gacta
53935DNAArtificial SequenceElement 2 393gatac 53945DNAArtificial
SequenceElement 2 394gatca 53955DNAArtificial SequenceElement 2
395gcaat 53965DNAArtificial SequenceElement 2 396gcata
53975DNAArtificial SequenceElement 2 397gccct 53985DNAArtificial
SequenceElement 2 398gcctc 53995DNAArtificial SequenceElement 2
399gctaa 54005DNAArtificial SequenceElement 2 400gctcc
54015DNAArtificial SequenceElement 2 401gcttt 54025DNAArtificial
SequenceElement 2 402acttc 54035DNAArtificial SequenceElement 2
403ataat 54045DNAArtificial SequenceElement 2 404atata
54055DNAArtificial SequenceElement 2 405atcct 54065DNAArtificial
SequenceElement 2 406atctc 54075DNAArtificial SequenceElement 2
407attaa 54085DNAArtificial SequenceElement 2 408attcc
54095DNAArtificial SequenceElement 2 409atttt 54105DNAArtificial
SequenceElement 2 410caaac 54115DNAArtificial SequenceElement 2
411caaca 54125DNAArtificial SequenceElement 2 412cacaa
54135DNAArtificial SequenceElement 2 413caccc 54145DNAArtificial
SequenceElement 2 414cactt 54155DNAArtificial SequenceElement 2
415catct 54165DNAArtificial SequenceElement 2 416cattc
54175DNAArtificial SequenceElement 2 417ccaaa 54185DNAArtificial
SequenceElement 2 418agaga 54195DNAArtificial SequenceElement 2
419agccg 54205DNAArtificial SequenceElement 2 420agcgc
54215DNAArtificial SequenceElement 2 421aggaa 54225DNAArtificial
SequenceElement 2 422aggcc 54235DNAArtificial SequenceElement 2
423aggtt 54245DNAArtificial SequenceElement 2 424agtgt
54255DNAArtificial SequenceElement 2 425agttg 54265DNAArtificial
SequenceElement 2 426atggt 54275DNAArtificial SequenceElement 2
427atgtg 54285DNAArtificial SequenceElement 2 428attgg
54295DNAArtificial SequenceElement 2 429cacgg 54305DNAArtificial
SequenceElement 2 430cagcg 54315DNAArtificial SequenceElement 2
431caggc 54325DNAArtificial SequenceElement 2 432ccagg
54335DNAArtificial SequenceElement 2 433ccgag 54345DNAArtificial
SequenceElement 2 434aactg 54355DNAArtificial SequenceElement 2
435aagct 54365DNAArtificial SequenceElement 2 436aagtc
54375DNAArtificial SequenceElement 2 437aatcg 54385DNAArtificial
SequenceElement 2 438aatgc 54395DNAArtificial SequenceElement 2
439acagt 54405DNAArtificial SequenceElement 2 440acatg
54415DNAArtificial SequenceElement 2 441acgat 54425DNAArtificial
SequenceElement 2 442acgta 54435DNAArtificial SequenceElement 2
443actag 54445DNAArtificial SequenceElement 2 444actga
54455DNAArtificial SequenceElement 2 445agact 54465DNAArtificial
SequenceElement 2 446agatc 54475DNAArtificial SequenceElement 2
447agcat 54485DNAArtificial SequenceElement 2 448agcta
54495DNAArtificial SequenceElement 2 449agtac 54505DNAArtificial
SequenceElement 2 450gtaac 54515DNAArtificial SequenceElement 2
451gtaca 54525DNAArtificial SequenceElement 2 452gtcaa
54535DNAArtificial SequenceElement 2 453gtccc 54545DNAArtificial
SequenceElement 2 454gtctt 54555DNAArtificial SequenceElement 2
455gttct 54565DNAArtificial SequenceElement 2 456gtttc
54575DNAArtificial SequenceElement 2 457taacg 54585DNAArtificial
SequenceElement 2 458taagc 54595DNAArtificial SequenceElement 2
459tacag 54605DNAArtificial SequenceElement 2 460tacga
54615DNAArtificial SequenceElement 2 461tagac 54625DNAArtificial
SequenceElement 2 462tagca 54635DNAArtificial SequenceElement 2
463tcaag 54645DNAArtificial SequenceElement 2 464tcaga
54655DNAArtificial SequenceElement 2 465tcccg 54665DNAArtificial
SequenceElement 2 466ccacc 54675DNAArtificial SequenceElement 2
467ccatt 54685DNAArtificial SequenceElement 2 468cccac
54695DNAArtificial SequenceElement 2 469cccca 54705DNAArtificial
SequenceElement 2 470cctat 54715DNAArtificial SequenceElement 2
471cctta 54725DNAArtificial SequenceElement 2 472ctact
54735DNAArtificial SequenceElement 2 473ctatc 54745DNAArtificial
SequenceElement 2 474ctcat 54755DNAArtificial SequenceElement 2
475ctcta 54765DNAArtificial SequenceElement 2 476cttac
54775DNAArtificial SequenceElement 2 477cttca 54785DNAArtificial
SequenceElement 2 478taaat 54795DNAArtificial SequenceElement 2
479taata 54805DNAArtificial SequenceElement 2 480tacct
54815DNAArtificial SequenceElement 2 481tactc 54825DNAArtificial
SequenceElement 2 482ccgga 54835DNAArtificial SequenceElement 2
483cgacg 54845DNAArtificial SequenceElement 2 484cgagc
54855DNAArtificial SequenceElement 2 485cgcag 54865DNAArtificial
SequenceElement 2 486cgcga 54875DNAArtificial SequenceElement 2
487cggac 54885DNAArtificial SequenceElement 2 488cggca
54895DNAArtificial SequenceElement 2 489gaaag 54905DNAArtificial
SequenceElement 2 490gaaga 54915DNAArtificial SequenceElement 2
491gaccg 54925DNAArtificial SequenceElement 2 492gacgc
54935DNAArtificial SequenceElement 2 493gagaa 54945DNAArtificial
SequenceElement 2 494gagcc 54955DNAArtificial SequenceElement 2
495gagtt 54965DNAArtificial SequenceElement 2 496gatgt
54975DNAArtificial SequenceElement 2 497gattg 54985DNAArtificial
SequenceElement 2 498agtca 54995DNAArtificial SequenceElement 2
499atacg 55005DNAArtificial SequenceElement 2 500atagc
55015DNAArtificial SequenceElement 2 501atcag 55025DNAArtificial
SequenceElement 2 502atcga 55035DNAArtificial SequenceElement 2
503atgac 55045DNAArtificial SequenceElement 2 504atgca
55055DNAArtificial SequenceElement 2 505caagt 55065DNAArtificial
SequenceElement 2 506caatg 55075DNAArtificial SequenceElement 2
507cagat 55085DNAArtificial SequenceElement 2 508cagta
55095DNAArtificial SequenceElement 2 509catag 55105DNAArtificial
SequenceElement 2 510catga 55115DNAArtificial SequenceElement 2
511cccgt 55125DNAArtificial SequenceElement 2 512ccctg
55135DNAArtificial SequenceElement 2 513ccgct 55145DNAArtificial
SequenceElement 2 514tccgc 55155DNAArtificial SequenceElement 2
515tcgaa 55165DNAArtificial SequenceElement 2 516tcgcc
55175DNAArtificial SequenceElement 2 517tcgtt 55185DNAArtificial
SequenceElement 2 518tctgt 55195DNAArtificial SequenceElement 2
519tcttg 55205DNAArtificial SequenceElement 2 520tgaac
55215DNAArtificial SequenceElement 2 521tgaca 55225DNAArtificial
SequenceElement 2 522tgcaa 55235DNAArtificial SequenceElement 2
523tgccc 55245DNAArtificial SequenceElement 2 524tgctt
55255DNAArtificial SequenceElement 2 525tgtct 55265DNAArtificial
SequenceElement 2 526tgttc 55275DNAArtificial SequenceElement 2
527ttcgt 55285DNAArtificial SequenceElement 2 528ttctg
55295DNAArtificial SequenceElement 2 529ttgct 55305DNAArtificial
SequenceElement 2 530tataa 55315DNAArtificial SequenceElement 2
531tatcc 55325DNAArtificial SequenceElement 2 532tattt
55335DNAArtificial SequenceElement 2 533tcact 55345DNAArtificial
SequenceElement 2 534tcatc 55355DNAArtificial Sequenceelement 2
535tccat 55365DNAArtificial SequenceElement 2 536tccta
55375DNAArtificial SequenceElement 2 537tctac 55385DNAArtificial
SequenceElement 2 538tctca 55393DNAArtificial SequenceElement 3
539aag 35403DNAArtificial SequenceElement 3 540ctc
35413DNAArtificial SequenceElement 3 541ggt 35423DNAArtificial
SequenceElement 3 542tca 35433DNAArtificial SequenceElement 3
543act
35443DNAArtificial SequenceElement 3 544cga 35453DNAArtificial
SequenceElement 3 545gtg 35463DNAArtificial SequenceElement 3
546tac 35473DNAArtificial SequenceElement 3 547agc
35483DNAArtificial SequenceElement 3 548ccg 35493DNAArtificial
SequenceElement 3 549gaa 35503DNAArtificial SequenceElement 3
550ttt 35513DNAArtificial SequenceElement 3 551ata
35523DNAArtificial SequenceElement 3 552cat 35533DNAArtificial
SequenceElement 3 553gcc 35543DNAArtificial SequenceElement 3
554tgg 355512DNAArtificial SequenceElement 4 555acccacacca aa
1255612DNAArtificial SequenceElement 4 556caaacacaac cc
1255712DNAArtificial SequenceElement 4 557gtgtgggttg tt
1255812DNAArtificial SequenceElement 4 558tgtgtttggt gg
1255912DNAArtificial SequenceElement 4 559tttggtgtgg gt
1256012DNAArtificial SequenceElement 4 560gggttgtgtt tg
1256112DNAArtificial SequenceElement 4 561aacaacccac ac
1256212DNAArtificial SequenceElement 4 562ccaccaaaca ca 12
* * * * *