U.S. patent application number 16/044374 was filed with the patent office on 2018-11-15 for transposition of native chromatin for personal epigenomics.
The applicant listed for this patent is The Board of Trustees of the Leland Stanford Junior University. Invention is credited to Jason D. BUENROSTRO, Howard Y. CHANG, Paul GIRESI, William J. GREENLEAF.
Application Number | 20180327838 16/044374 |
Document ID | / |
Family ID | 51934332 |
Filed Date | 2018-11-15 |
United States Patent
Application |
20180327838 |
Kind Code |
A1 |
GIRESI; Paul ; et
al. |
November 15, 2018 |
TRANSPOSITION OF NATIVE CHROMATIN FOR PERSONAL EPIGENOMICS
Abstract
Provided herein is a method for analyzing polynucleotides such
as genomic DNA. In certain embodiments, the method comprises: (a)
treating chromatin isolated from a population of cells with an
insertional enzyme complex to produce tagged fragments of genomic
DNA; (b) sequencing a portion of the tagged fragments to produce a
plurality of sequence reads; and (c) making an epigenetic map of a
region of the genome of the cells by mapping information obtained
from the sequence reads to the region. A kit for performing the
method is also provided.
Inventors: |
GIRESI; Paul; (Palo Alto,
CA) ; BUENROSTRO; Jason D.; (Redwood City, CA)
; CHANG; Howard Y.; (Stanford, CA) ; GREENLEAF;
William J.; (Menlo Park, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
The Board of Trustees of the Leland Stanford Junior
University |
Stanford |
CA |
US |
|
|
Family ID: |
51934332 |
Appl. No.: |
16/044374 |
Filed: |
July 24, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14784250 |
Oct 13, 2015 |
10059989 |
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PCT/US14/38825 |
May 20, 2014 |
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16044374 |
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61826728 |
May 23, 2013 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G16H 50/20 20180101;
C12Q 2537/164 20130101; C12Q 2521/301 20130101; C12Q 1/6874
20130101; C12Q 1/6806 20130101; C12Q 1/6869 20130101; G16B 30/00
20190201; G16B 20/00 20190201; C12Q 1/6869 20130101; C12Q 2521/301
20130101; C12Q 2537/164 20130101; C12Q 1/6806 20130101; C12Q
2521/301 20130101; C12Q 2521/507 20130101; C12Q 2525/191 20130101;
C12Q 2535/122 20130101 |
International
Class: |
C12Q 1/6874 20060101
C12Q001/6874; C12Q 1/6869 20060101 C12Q001/6869 |
Goverment Interests
GOVERNMENT SUPPORT
[0002] This invention was made with Government support under
contracts AI057229, HG000044, and NS073015 awarded by the National
Institutes of Health. The Government has certain rights in the
invention.
Claims
1-77. (canceled)
78. A kit for analyzing epigenetic features of a genome region,
comprising: (a) an insertional enzyme that does not comprise an
antibody specific to a protein that is part of a chromatin of said
genome region; (b) an insert element comprising a nucleic acid; and
(c) instructions that direct a user to at least (i) contact
chromatin comprising said genome region with said insertional
enzyme and said insert element to produce tagged fragments of
genomic DNA, and (ii) use said tagged fragments of genomic DNA or
derivatives thereof to generate a representation of said epigenetic
features.
79. The kit of claim 78, further comprising a reagent for
permeabilizing or lysing a cell or a nucleus comprising said
chromatin.
80. The kit of claim 79, wherein said reagent for permeabilizing or
lysing said cell or said nucleus is configured to minimally perturb
said chromatin of said cell or said nucleus.
81. The kit of claim 79, wherein said reagent comprises NP40,
digitonin, tween, streptolysin, or a cationic lipid.
82. The kit of claim 78, wherein said insertional enzyme comprises
a transposase.
83. The kit of claim 82, wherein said transposase is a Tn5
transposase or derived from a Tn5 transposase.
84. The kit of claim 83, wherein said transposase is a hyperactive
Tn5 transposase.
85. The kit of claim 78, wherein said insert element comprising
said nucleic acid comprises an adapter sequence.
86. The kit of claim 85, wherein said adapter sequence comprises a
sequencing adapter sequence.
87. The kit of claim 85, wherein said adapter sequence comprises a
barcode sequence.
88. The kit of claim 85, wherein said adapter sequence comprises a
primer sequence.
89. The kit of claim 78, further comprising an additional insert
element comprising an additional nucleic acid.
90. The kit of claim 89, wherein said insert element comprising
said nucleic acid comprises a first adapter sequence and wherein
said additional insert element comprising said additional nucleic
acid comprises a second adapter sequence.
91. The kit of claim 78, wherein said instructions further direct
said user to at least subject said tagged fragments of genomic DNA
to one or more reactions.
92. The kit of claim 91, wherein said one or more reactions
comprise a nucleic acid amplification reaction.
93. The kit of claim 92, wherein said nucleic acid amplification
reaction is configured to add one or more functional sequences to
said tagged fragments or derivatives thereof, wherein said one or
more functional sequences are compatible with a selected next
generation sequencing platform.
Description
CROSS-REFERENCING
[0001] This application claims the benefit of U.S. Provisional
application Ser. No. 61/826,728, filed on May 23, 2013, which
application is incorporated by reference herein in its
entirety.
BACKGROUND
[0003] Eukaryotic genomes are hierarchically packaged into
chromatin, and the nature of this packaging plays a central role in
gene regulation. Major insights into the epigenetic information
encoded within the nucleoprotein structure of chromatin have come
from high-throughput, genome-wide methods for separately assaying
the chromatin accessibility ("open chromatin"), nucleosome
positioning, and transcription factor (TF) occupancy. While
published protocols exist, those methods require millions of cells
as starting material, complex and time-consuming sample
preparations, and cannot simultaneously probe the interplay of
nucleosome positioning, chromatin accessibility, and TF binding.
These limitations are problematic in three major ways: First,
current methods can average over and "drown out" heterogeneity in
cellular populations. Second, cells must often be grown ex vivo to
obtain sufficient biomaterials, perturbing the in vivo context and
modulating the epigenetic state in unknown ways. Third, input
requirements often prevent application of these assays to
well-defined clinical samples, precluding generation of "personal
epigenomes" in diagnostic timescales. Provided herein are methods
for analyzing polynucleotides, including their accessibility and
their structure, that can overcome these limitation(s). Also
provided are single-cell methods that can provide higher
sensitivity and further information on chromatin accessibility,
including cell-to-cell variability, to potentially enable its use
as a biomarker.
SUMMARY
[0004] Provided herein is a method for analyzing polynucleotides
such as genomic DNA. In certain embodiments, the method comprises:
(a) treating chromatin isolated from a population of cells with a
transposase and molecular tags to produce tagged fragments of
polynucleotides; (b) sequencing a portion of the tagged fragments
to produce a plurality of sequence reads; and (c) making an
epigenetic map of a region of the genome of the cells by mapping
information obtained from the sequence reads to the region.
[0005] In some cases, the information is obtained using the
nucleotide sequences at the beginning and, optionally, the end of a
sequence read. In some cases, the information mapped in (c) is
selected from one or more of: (i) cleavage sites for the
transposase; (ii) the sizes of the fragments produced in step (a);
(iii) sequence read length; (iii) the positions of sequence reads
of a defined range in length; and (iv) sequence read abundance. In
some instances, the fragments of a defined size range are
nucleosome-free fragments.
[0006] In some instances, the epigenetic map shows one or more of:
(i) a profile of chromatin accessibility along the region; (ii) DNA
binding protein occupancy for a binding site in the region; (iii)
nucleosome-free DNA in the region; (iv) positioning of nucleosomes
along the region; and/or (v) chromatin states. In some cases, the
method can further comprise measuring global occupancy of a binding
site for the DNA binding protein. The DNA binding protein can, for
example, be a transcription factor.
[0007] In some cases, the population of cells can be composed of
about 500 to 100,000 cells. The cells can be isolated from an
individual, such as from the blood of the individual. In some
examples, the cells can be of the same cell type. In some examples,
the cells can be FACS-selected cells.
[0008] In some instances, the treating step (a) can comprise:
isolating nuclei from the population of cells; and combining the
isolated nuclei with the insertional enzyme complex, wherein the
combining results in both lysis of the nuclei to release the
chromatin and production of the tagged fragments of genomic DNA. In
some examples, the transposase can be derived from Tn5 transposase.
In other examples, the transposase can be derived from MuA
transposase. In further examples, the transposase can be derived
from Vibhar transposase (e.g. from Vibrio harveyi).
[0009] The present disclosure also provides a method for comparing
two samples comprising: (a) analyzing a first population of cells
to produce a first epigenetic map; and (b) analyzing a second
population of cells to produce a second epigenetic map; and (c)
comparing the first epigenetic map to the second epigenetic map.
For example, the first population of cells and the second
population of cells can be collected from the same individual at
different times. Alternatively, the first population of cells and
the second population of cells can be different populations of
cells collected from different individuals.
[0010] The present disclosure further provides a diagnostic method,
comprising: analyzing chromatin from a patient to produce an
epigenetic map; and providing a diagnosis or prognosis based on the
epigenetic map.
[0011] The present disclosure provides a method for determining
accessibility of a polynucleotide at a site, wherein the
polynucleotide is from a cell sample, comprising: (a) inserting a
plurality of molecular tags with an insertional enzyme into the
polynucleotide; and (b) using the molecular tags to determine
accessibility at the site. The method can further comprise using
the determined accessibility to identify one or more proteins that
are bound to the polynucleotide at the site. In some cases, at
least one of the proteins is a transcription factor. The method can
also comprise using the molecular tags to generate an accessibility
map of the polynucleotide.
[0012] The present disclosure also provides a method for analyzing
the three-dimensional structure of a polynucleotide from a cell
sample, comprising: (a) inserting a plurality of molecular tags
with an insertional enzyme into the polynucleotide; and (b) using
the molecular tags to analyze the three-dimensional structure of
the polynucleotide. In some cases, the insertional enzyme can
comprise two or more enzymatic moieties wherein each of the
enzymatic moieties inserts a common sequence into the
polynucleotide. The enzymatic moieties can be linked together. The
common sequence can comprise a common barcode. The enzymatic
moieties can comprise transposases. The polynucleotide can
fragmented into a plurality of fragments during step (a), wherein
the fragments comprising the common barcode are determined to be in
proximity in the three-dimensional structure of the
polynucleotide.
[0013] The polynucleotide can be fragmented into a plurality of
fragments during the insertion. The method can further comprise
amplifying the fragments. The accessibility can be determined by
sequencing the fragments and thereby generating a plurality of
sequencing reads. The fragments can, for example, be sequenced by a
high-throughput sequencing technique. The method can further
comprise normalizing the sequencing reads based on the sequence
insertion preference of the insertional enzyme. The length of the
sequenced reads can also be used to determine a chromatin state
annotation.
[0014] The cell sample can be permeabilized to allow access for the
insertional enzyme. In some cases, the nuclei in the cell sample
can be minimally perturbed during the permeabilization. The cell
sample can be permeabilized using a permeabilization agent
including, but not limited to, NP40, digitonin, tween,
streptolysin, and/or cationic lipids. The cell sample can also be
permeabilized using hypotonic shock and/or ultrasonication.
[0015] The method can further comprise analyzing a disease state in
a subject based on the accessibility of the specific site, wherein
the cell sample is obtained from the subject. The cell sample
and/or the polynucleotides can also be divided into a plurality of
portions, which may be optionally divided based on the molecular
tags. The method can further comprise analyzing a phenotype of the
cell sample. In some cases, the phenotype can be correlated to the
accessibility of the site.
[0016] The insertion can be facilitated by addition of one or more
divalent cations. In some cases, the one or more divalent cations
can comprise magnesium. In some cases, the one or more divalent
cations can comprise manganese.
[0017] The cell sample can be obtained from a primary source. The
cell sample can consist of less than about 500,000 cells, or even a
single cell. The polynucleotide can be bound to a plurality of
association molecules. The association molecules can comprise
proteins, such as histones. The insertional enzyme can be a
transposase. In some cases, the transposase can be derived from a
Tn5 transposase. In other cases, the transposase can be derived
from a MuA transposase. In further cases, the transposase can be
derived from a Vibhar transposase (e.g. from Vibrio harveyi). In
some cases, the molecular tags can comprise sequencing adaptors,
which may further comprise a barcode label. The barcode label can
comprise a unique sequence. In other cases, the molecular tags can
comprise fluorescence tags. The insertional enzyme can further
comprise an affinity tag, which may optionally be an antibody that
binds to a transcription factor, a modified nucleosome, and/or a
modified nucleic acid. The modified nucleic acid can, for example
be a methylated or hydroxymethylated DNA. The affinity tag can also
be a single-stranded nucleic acid, which may optionally bind to a
target nucleic acid. The insertional enzyme can further comprise a
nuclear localization signal.
[0018] The present disclosure also provides compositions. The
composition can comprise a polynucleotide, an insertional enzyme
and an insert element, wherein: the insert element comprises a
nucleic acid comprising a predetermined sequence; and the
insertional enzyme further comprises an affinity tag. The
composition can also comprise a polynucleotide, an insertional
enzyme and an insert element, wherein: the insertional enzyme
comprises two or more enzymatic moieties; and the enzymatic
moieties are linked together. The affinity tag can be an antibody,
which may optionally be bound to a transcription factor, a modified
nucleosome, and/or a modified nucleic acid. The modified nucleic
acid can be, for example, a methylated or hydroxymethylated DNA.
The affinity tag can also be a single-stranded nucleic acid, which
may be optionally bound to a target nucleic acid. The insert
element can be bound to the insertional enzyme and the insertional
enzyme is bound to the polynucleotide. The polynucleotide can be
further bound to a plurality of association molecules. The
association molecules can comprise proteins such as, for example,
histones.
[0019] The present disclosure further provides kits. The kit can
comprise: (a) reagents for isolating nuclei from a population of
cells; (b) an insertional enzyme complex, and (c) transposase
reaction buffer. In some cases, the components of the kit can be
configured such that, combining the reaction buffer, transposon
tags and adaptors with nuclei in vitro results in both lysis of the
nuclei to release chromatin and production of tagged fragments of
genomic DNA. The kit can also comprise: a cell lysis buffer; an
insertional enzyme comprising an affinity tag; and an insert
element comprising a nucleic acid, wherein the nucleic acid
comprises a predetermined sequence. The kit can further comprise: a
cell lysis buffer; an insertional enzyme comprising two or more
enzymatic moieties, wherein the enzymatic moieties are linked
together; and (c) an insert element. The affinity tag can be an
antibody, which can optionally bind to a transcription factor, a
modified nucleosome, and/or a modified nucleic acid. The modified
nucleic acid can be, for example, a methylated or hydroxymethylated
DNA. The affinity can also be a single-stranded nucleic acid, which
may be optionally bound to a target nucleic acid.
[0020] These and other features of the present teachings are set
forth herein.
INCORPORATION BY REFERENCE
[0021] All publications, patents, and patent applications mentioned
in this specification are herein incorporated by reference to the
same extent as if each individual publication, patent, or patent
application was specifically and individually indicated to be
incorporated by reference.
BRIEF DESCRIPTION OF THE FIGURES
[0022] The skilled artisan will understand that the drawings,
described below, are for illustration purposes only. The drawings
are not intended to limit the scope of the present teachings in any
way.
[0023] FIGS. 1A-1C: ATAC-seq is a sensitive, accurate probe of open
chromatin state. (a) ATAC-seq reaction schematic. Transposase
(green), loaded with sequencing adapters (red and blue), inserts
only in regions of open chromatin (nucleosomes in grey) and
generates sequencing library fragments that can be PCR amplified.
(b) Approximate reported input material and sample preparation time
requirements for genome-wide methods of open chromatin analysis.
(c) A comparison of ATAC-seq to other open chromatin assays at a
locus in GM12878 lymphoblastoid cells displaying high concordance.
Lower ATAC-seq track was generated from 500 FACS-sorted cells.
[0024] FIGS. 2A-2B: ATAC-seq provides genome-wide information on
chromatin compaction. (a) ATAC-seq fragment sizes generated from
GM12878 nuclei (red) indicate chromatin-dependent periodicity with
a spatial frequency consistent with nucleosomes, as well as a high
frequency periodicity consistent with the pitch of the DNA helix
for fragments less than 200 bp. (Inset) log-transformed histogram
shows clear periodicity persists to 6 nucleosomes. (b) Normalized
read enrichments for 7 classes of chromatin state previously
defined.
[0025] FIGS. 3A-3E: ATAC-seq provides genome-wide information on
nucleosome positioning in regulatory regions. (a) An example locus
containing two transcription start sites (TSSs) showing nucleosome
free read track, calculated nucleosome track (Methods), as well as
DNase, MNase, and H3K27ac, H3K4me3, and H2A.Z tracks for
comparison. (b) ATAC-seq (198 million paired reads) and MNase-seq
(4 billion single-end reads from ref 23) nucleosome signal shown
for all active TSSs (n=64,836), TSSs are sorted by CAGE expression.
(c) TSSs are enriched for nucleosome free fragments, and show
phased nucleosomes similar to those seen by MNase-seq at the -2,
-1, +1, +2, +3 and +4 positions. (d) Relative fraction of
nucleosome associated vs. nucleosome free (NFR) bases in TSS and
distal sites (see Methods). (e) Hierarchical clustering of DNA
binding factor position with respect to the nearest nucleosome dyad
within accessible chromatin reveals distinct classes of DNA binding
factors. Factors strongly associated with nucleosomes are enriched
for chromatin remodelers.
[0026] FIGS. 4A-4C: ATAC-seq assays genome-wide factor occupancy.
(a) CTCF footprints observed in ATAC-seq and DNase-seq data, at a
specific locus on chrl. (b) Aggregate ATAC-seq footprint for CTCF
(motif shown) generated over binding sites within the genome (c)
CTCF predicted binding probability inferred from ATAC-seq data,
position weight matrix (PWM) scores for the CTCF motif, and
evolutionary conservation (PhyloP). Right-most column is the CTCF
ChIP-seq data (ENCODE) for this GM12878 cell line, demonstrating
high concordance with predicted binding probability.
[0027] FIGS. 5A-5D: ATAC-seq enables real-time personal
epigenomics. (a) Work flow from standard blood draws. (b) Serial
ATAC-seq data from proband T-cells over three days. (c) Example of
application of ATAC-seq data (green track) to prioritize candidate
TF drug targets. Among identified TF binding sites proximal to
cytokine gene IL2 that can be targeted by FDA-approved drugs, only
NFAT is engaged in proband T-cells. ATAC-seq footprint prediction
is confirmed by alignment with published NFAT ChIP-seq data (blue
track, data from ref.sup.35). (d) Cell type-specific regulatory
network from proband T cells compared with GM12878 B-cell line.
Each row or column is the footprint profile of a TF versus that of
all other TFs in the same cell type. Color indicates relative
similarity (yellow) or distinctiveness (blue) in T versus B cells.
NFAT is one of the most highly differentially regulated TFs (red
box) whereas canonical CTCF binding is essentially similar in T and
B cells.
[0028] FIG. 6: ATAC-seq peak intensity correlates well with
DNase-seq peak intensity. Peaks in Duke DNase-seq (down sampled to
60.times.10.sup.6 reads), UW DNase-seq (40.times.10.sup.6 reads),
and ATAC-seq data (60.times.10.sup.6 paired-end reads) were called
using ZINBA (Rashid et al Genome Biol. 2011 12: R67). Because each
data set has different read lengths we chose to filter for peaks
within mappable regions (Duke DNase-seq=20 bp reads, UW
DNase-Seq=36 bp reads and ATAC-Seq=paired-end 50 bp reads). The log
10(read intensity) was compared for (A) Duke DNase-seq and
ATAC-seq, (B) UW DNase-seq and ATAC-seq, and (C) UW DNAse-seq and
Duke DNase-seq. Technical reproducibility of ATAC-seq data is shown
in D.
[0029] FIG. 7: ATAC-seq captures a large fraction of DNase
identified peaks. Peaks were called for all data sets using ZINBA.
The venn-diagram shows overlap of the peak calls between each
method. Below: The majority of ATAC-seq reads are in intense peaks
that intersect with Duke and UW DNase-seq peaks. The total fraction
of reads within peaks called from ATAC-seq, UW DNase-seq, and Duke
DNase-seq, as well as the intersections of these data are shown.
More than 65% of reads from all three methods are found in the
intersection of the three methods' peaks, suggesting that strong
well-stereotyped peaks are detected by all methods. Table cell
color is proportional to fraction of reads.
[0030] FIG. 8: Graphs of the number of reads overlapping the set of
open chromatin regions identified by Duke DNase, UW DNase and FAIRE
in GM12878 cells compared to a set of background regions, wherein
to determine the read depth required for detecting open chromatin
sites sensitivity and specificity was assessed at varying read
depths, including 50k, 100k, 500k, 10 million and 50 million reads.
The bottom graph shows the performance of ATAC-seq in GM12878 cells
was assessed using 500, 5,000 or 50,000 cells as starting
material.
[0031] FIG. 9: Tn5 insertion preferences in genomic DNA and
chromatin. Nucleotide frequency scores represent the observed
nucleotide frequency of each base, nucleotide frequencies are
normalized to 1. The x=0 position represents the read start, and
the dotted line represents the symmetry axis of the Tn5 dimer. We
see no substantial differences between Tn5 insertion preferences
between purified genomic DNA and human chromatin, suggesting that
the local insertion preference into chromatin is identical to that
found in naked genomic DNA. These reported sequence preferences are
similar to those previously reported (main text ref 11).
[0032] FIG. 10: Graph of the average intensity per base of each
feature at every ATAC-seq peak; all ENCODE ChIP data was normalized
to input; data has been processed using a sliding window of 200
peaks.
[0033] FIG. 11: ATAC-seq of various cell numbers. A representative
UCSC genome browser track of data from different starting numbers
of cells for ATAC-seq. This same locus is also shown in FIG. 1b of
the main text. In order: 500 cells were isolated using FACS and two
replicates of 500 cells and 5,000 cells were done by a simple
dilution from cell culture. For comparison, the bottom track
represents 50,000 cells, also show in FIG. 1b. This figure
demonstrates that we are able to capture open chromatin sites from
as few as 500 cells.
[0034] FIG. 12: Fitting nucleosome peaks in ATAC-seq fragment size
distribution to enable nucleosome occupancy measurements. The
observed fragment distribution was partitioned into four
populations of reads--reads expected to originate from open DNA,
and reads that span 1, 2 or 3 putative nucleosomes. To enable this
partitioning of the data, the ATAC-seq fragment distribution was
fit to the sum of 1) an exponential function for fragment
distribution pattern at insert sizes below one nucleosome, and 2) 5
Gaussians to the distributions arising from protection from one,
two, three, four and five nucleosomes. The sum of these fits is
shown (black dotted line) is similar to the observed fragment
distribution (blue line). Vertical dotted lines are boundaries for
identification of fragments as originating from the nucleosome-free
(<100 bps), 1-nucleosome, 2-nucleosome and 3-nucleosome regions.
Dotted lines were set to ensure that <10% of fragments originate
from neighboring, as defined by our fit.
[0035] FIG. 13: Select set of transcription factor footprints
detected by ATAC-seq in GM12878 cells. For the indicated
transcription factors the aggregate signal of ATAC-seq reads were
computed using CENTIPEDE on the genome-wide sets of sites matching
the corresponding motif. Reads were calculated in the region +/-100
bp of the motif boundary. The vertical dashed lines indicate the
boundaries of the motifs.
[0036] FIG. 14: Prediction of CTCF binding sites using ATAC-seq and
DNase footprinting with CENTIPEDE. Prediction of CTCF binding sites
was assessed using the genome-wide set of CTCF motifs sorted by the
posterior probability reported by CENTIPEDE. Those overlapping CTCF
ChIP-seq peaks were used as the positive set and all others were
considered as the negative set. This yielded an area under the
curve (AUC) of 0.92, which suggests specific and sensitive binding
inference for CTCF. Duke DNase and UW DNase data were used with the
same settings of CENTIPEDE, and ROC plots are shown. ATAC-seq data
consisted of 198.times.10.sup.6 paired reads, Duke DNase-comprised
245.times.10.sup.6 reads, and UW DNase comprised 48.times.10.sup.6
reads.
[0037] FIG. 15: T-cell specific NFAT regulation: Examples of
T-cell-specific NFAT target genes predicted by ATAC-seq and
confirmed by alignment with NFAT ChIP-seq (data from main text ref
35).
[0038] FIG. 16: ATAC-seq of FACS-purified cell populations from
human blood. (A) From a standard blood draw, we used
Fluorescence-Activated Cell Sorting (FACS) to purify CD4+ T-cells,
CD8+ T-cells, and CD14+ monocytes. Each population generated
successful ATAC-seq data (B) and revealed cell-type specific open
chromatin sites at known lineage-specific genes.
[0039] FIG. 17: Detection of allele specific open chromatin in
GM12878 cells with ATAC-seq. Using publicly available variant data,
we measured the allele frequency in open chromatin regions at
putative heterozygous loci. Because of potential for spurious
heterozygous sites, we required more than two reads to validate the
heterozygosity of the allele. Red points (n=167) are candidate
allele specific open chromatin sites at p<10.sup.-5, while grey
(n=900) represent candidates at p<0.01. P-values were calculated
using a Bayesian model developed by Audic et al (Genome Research
1997 7, 986-995).
[0040] FIG. 18: Transposases can serve as an open-chromatin stain.
By loading Tn5 transposes with fluorescently labeled DNA adapters,
transposition events, shown in green, are primarily localized to
the nucleus, and exhibit a punctate pattern consistent with higher
order organization.
[0041] FIG. 19: Single-cell ATAC-seq data from a single nucleus
(blue) show clear peak at the expected positions of open-chromatin
genome wide compared to 50,000 cells.
[0042] FIG. 20: Single cell insert length distribution matches that
from 50,000 cells showing periodicity due to the presence of
nucleosomes.
DEFINITIONS
[0043] Unless defined otherwise herein, all technical and
scientific terms used herein have the same meaning as commonly
understood by one of ordinary skill in the art to which this
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, the preferred methods and
materials are described.
[0044] All patents and publications, including all sequences
disclosed within such patents and publications, referred to herein
are expressly incorporated by reference.
[0045] Numeric ranges are inclusive of the numbers defining the
range. Unless otherwise indicated, nucleic acids are written left
to right in 5' to 3' orientation; amino acid sequences are written
left to right in amino to carboxy orientation, respectively.
[0046] The headings provided herein are not limitations of the
various aspects or embodiments of the invention. Accordingly, the
terms defined immediately below are more fully defined by reference
to the specification as a whole.
[0047] Unless defined otherwise, all technical and scientific terms
used herein have the same meaning as commonly understood by one of
ordinary skill in the art to which this invention belongs.
Singleton, et al., DICTIONARY OF MICROBIOLOGY AND MOLECULAR
BIOLOGY, 2D ED., John Wiley and Sons, New York (1994), and Hale
& Markham, THE HARPER COLLINS DICTIONARY OF BIOLOGY, Harper
Perennial, N.Y. (1991) provide one of skill with the general
meaning of many of the terms used herein. Still, certain terms are
defined below for the sake of clarity and ease of reference.
[0048] The term "sample" as used herein relates to a material or
mixture of materials, typically containing one or more analytes of
interest. In one embodiment, the term as used in its broadest
sense, refers to any plant, animal or viral material containing DNA
or RNA, such as, for example, tissue or fluid isolated from an
individual (including without limitation plasma, serum,
cerebrospinal fluid, lymph, tears, saliva and tissue sections) or
from in vitro cell culture constituents, as well as samples from
the environment.
[0049] The term "nucleic acid sample," as used herein, denotes a
sample containing nucleic acids. Nucleic acid samples used herein
may be complex in that they contain multiple different molecules
that contain sequences. Genomic DNA samples from a mammal (e.g.,
mouse or human) are types of complex samples. Complex samples may
have more than about 10.sup.4, 10.sup.5, 10.sup.6 or 10.sup.7,
10.sup.8, 10.sup.9 or 10.sup.10 different nucleic acid molecules. A
DNA target may originate from any source such as genomic DNA, or an
artificial DNA construct. Any sample containing nucleic acid, e.g.,
genomic DNA from tissue culture cells or a sample of tissue, may be
employed herein.
[0050] The term "mixture," as used herein, refers to a combination
of elements, that are interspersed and not in any particular order.
A mixture is heterogeneous and not spatially separable into its
different constituents. Examples of mixtures of elements include a
number of different elements that are dissolved in the same aqueous
solution and a number of different elements attached to a solid
support at random positions (i.e., in no particular order). A
mixture is not addressable. To illustrate by example, an array of
spatially separated surface-bound polynucleotides, as is commonly
known in the art, is not a mixture of surface-bound polynucleotides
because the species of surface-bound polynucleotides are spatially
distinct and the array is addressable.
[0051] The term "nucleotide" is intended to include those moieties
that contain not only the known purine and pyrimidine bases, but
also other heterocyclic bases that have been modified. Such
modifications include methylated purines or pyrimidines, acylated
purines or pyrimidines, alkylated riboses or other heterocycles. In
addition, the term "nucleotide" includes those moieties that
contain hapten or fluorescent labels and may contain not only
conventional ribose and deoxyribose sugars, but other sugars as
well. Modified nucleosides or nucleotides also include
modifications on the sugar moiety, e.g., wherein one or more of the
hydroxyl groups are replaced with halogen atoms or aliphatic
groups, or are functionalized as ethers, amines, or the like.
[0052] The term "nucleic acid" and "polynucleotide" are used
interchangeably herein to describe a polymer of any length, e.g.,
greater than about 2 bases, greater than about 10 bases, greater
than about 100 bases, greater than about 500 bases, greater than
1000 bases, greater than 10,000 bases, greater than 100,000 bases,
greater than about 1,000,000, up to about 10.sup.10 or more bases
composed of nucleotides, e.g., deoxyribonucleotides or
ribonucleotides, and may be produced enzymatically or synthetically
(e.g., PNA as described in U.S. Pat. No. 5,948,902 and the
references cited therein) which can hybridize with naturally
occurring nucleic acids in a sequence specific manner analogous to
that of two naturally occurring nucleic acids, e.g., can
participate in Watson-Crick base pairing interactions.
Naturally-occurring nucleotides include guanine, cytosine, adenine,
thymine, uracil (G, C, A, T and U respectively). DNA and RNA have a
deoxyribose and ribose sugar backbone, respectively, whereas PNA's
backbone is composed of repeating N-(2-aminoethyl)-glycine units
linked by peptide bonds. In PNA various purine and pyrimidine bases
are linked to the backbone by methylenecarbonyl bonds. A locked
nucleic acid (LNA), often referred to as inaccessible RNA, is a
modified RNA nucleotide. The ribose moiety of an LNA nucleotide is
modified with an extra bridge connecting the 2' oxygen and 4'
carbon. The bridge "locks" the ribose in the 3'-endo (North)
conformation, which is often found in the A-form duplexes. LNA
nucleotides can be mixed with DNA or RNA residues in the
oligonucleotide whenever desired. The term "unstructured nucleic
acid," or "UNA," is a nucleic acid containing non-natural
nucleotides that bind to each other with reduced stability. For
example, an unstructured nucleic acid may contain a G' residue and
a C' residue, where these residues correspond to non-naturally
occurring forms, i.e., analogs, of G and C that base pair with each
other with reduced stability, but retain an ability to base pair
with naturally occurring C and G residues, respectively.
Unstructured nucleic acid is described in US20050233340, which is
incorporated by reference herein for disclosure of UNA.
[0053] The term "oligonucleotide" as used herein denotes a
single-stranded multimer of nucleotide of from about 2 to 200
nucleotides, up to 500 nucleotides in length. Oligonucleotides may
be synthetic or may be made enzymatically, and, in some
embodiments, are 30 to 150 nucleotides in length. Oligonucleotides
may contain ribonucleotide monomers (i.e., may be
oligoribonucleotides) or deoxyribonucleotide monomers, or both
ribonucleotide monomers and deoxyribonucleotide monomers. An
oligonucleotide may be 10 to 20, 21 to 30, 31 to 40, 41 to 50, 51
to 60, 61 to 70, 71 to 80, 80 to 100, 100 to 150 or 150 to 200
nucleotides in length, for example.
[0054] "Primer" means an oligonucleotide, either natural or
synthetic, that is capable, upon forming a duplex with a
polynucleotide template, of acting as a point of initiation of
nucleic acid synthesis and being extended from its 3' end along the
template so that an extended duplex is formed. The sequence of
nucleotides added during the extension process is determined by the
sequence of the template polynucleotide. Usually primers are
extended by a DNA polymerase. Primers are generally of a length
compatible with their use in synthesis of primer extension
products, and are usually in the range of between 8 to 100
nucleotides in length, such as 10 to 75, 15 to 60, 15 to 40, 18 to
30, 20 to 40, 21 to 50, 22 to 45, 25 to 40, and so on. Typical
primers can be in the range of between 10-50 nucleotides long, such
as 15-45, 18-40, 20-30, 21-25 and so on, and any length between the
stated ranges. In some embodiments, the primers are usually not
more than about 10, 12, 15, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
30, 35, 40, 45, 50, 55, 60, 65, or 70 nucleotides in length.
[0055] Primers are usually single-stranded for maximum efficiency
in amplification, but may alternatively be double-stranded. If
double-stranded, the primer is usually first treated to separate
its strands before being used to prepare extension products. This
denaturation step is typically effected by heat, but may
alternatively be carried out using alkali, followed by
neutralization. Thus, a "primer" is complementary to a template,
and complexes by hydrogen bonding or hybridization with the
template to give a primer/template complex for initiation of
synthesis by a polymerase, which is extended by the addition of
covalently bonded bases linked at its 3' end complementary to the
template in the process of DNA synthesis.
[0056] The term "hybridization" or "hybridizes" refers to a process
in which a region of nucleic acid strand anneals to and forms a
stable duplex, either a homoduplex or a heteroduplex, under normal
hybridization conditions with a second complementary nucleic acid
strand, and does not form a stable duplex with unrelated nucleic
acid molecules under the same normal hybridization conditions. The
formation of a duplex is accomplished by annealing two
complementary nucleic acid strand region in a hybridization
reaction. The hybridization reaction can be made to be highly
specific by adjustment of the hybridization conditions (often
referred to as hybridization stringency) under which the
hybridization reaction takes place, such that two nucleic acid
strands will not form a stable duplex, e.g., a duplex that retains
a region of double-strandedness under normal stringency conditions,
unless the two nucleic acid strands contain a certain number of
nucleotides in specific sequences which are substantially or
completely complementary. "Normal hybridization or normal
stringency conditions" are readily determined for any given
hybridization reaction. See, for example, Ausubel et al., Current
Protocols in Molecular Biology, John Wiley & Sons, Inc., New
York, or Sambrook et al., Molecular Cloning: A Laboratory Manual,
Cold Spring Harbor Laboratory Press. As used herein, the term
"hybridizing" or "hybridization" refers to any process by which a
strand of nucleic acid binds with a complementary strand through
base pairing.
[0057] A nucleic acid is considered to be "selectively
hybridizable" to a reference nucleic acid sequence if the two
sequences specifically hybridize to one another under moderate to
high stringency hybridization and wash conditions. Moderate and
high stringency hybridization conditions are known (see, e.g.,
Ausubel, et al., Short Protocols in Molecular Biology, 3rd ed.,
Wiley & Sons 1995 and Sambrook et al., Molecular Cloning: A
Laboratory Manual, Third Edition, 2001 Cold Spring Harbor, N.Y.).
One example of high stringency conditions include hybridization at
about 42.degree. C. in 50% formamide, 5.times.SSC,
5.times.Denhardt's solution, 0.5% SDS and 100 .mu.g/ml denatured
carrier DNA followed by washing two times in 2.times.SSC and 0.5%
SDS at room temperature and two additional times in 0.1.times.SSC
and 0.5% SDS at 42.degree. C.
[0058] The term "duplex," or "duplexed," as used herein, describes
two complementary polynucleotide region that are base-paired, i.e.,
hybridized together.
[0059] The term "amplifying" as used herein refers to the process
of synthesizing nucleic acid molecules that are complementary to
one or both strands of a template nucleic acid. Amplifying a
nucleic acid molecule may include denaturing the template nucleic
acid, annealing primers to the template nucleic acid at a
temperature that is below the melting temperatures of the primers,
and enzymatically elongating from the primers to generate an
amplification product. The denaturing, annealing and elongating
steps each can be performed one or more times. In certain cases,
the denaturing, annealing and elongating steps are performed
multiple times such that the amount of amplification product is
increasing, often times exponentially, although exponential
amplification is not required by the present methods. Amplification
typically requires the presence of deoxyribonucleoside
triphosphates, a DNA polymerase enzyme and an appropriate buffer
and/or co-factors for optimal activity of the polymerase enzyme.
The term "amplification product" refers to the nucleic acids, which
are produced from the amplifying process as defined herein.
[0060] The terms "determining," "measuring," "evaluating,"
"assessing," "assaying," and "analyzing" are used interchangeably
herein to refer to any form of measurement, and include determining
if an element is present or not. These terms include both
quantitative and/or qualitative determinations. Assessing may be
relative or absolute. "Assessing the presence of" includes
determining the amount of something present, as well as determining
whether it is present or absent.
[0061] The term "using" has its conventional meaning, and, as such,
means employing, e.g., putting into service, a method or
composition to attain an end. For example, if a program is used to
create a file, a program is executed to make a file, the file
usually being the output of the program. In another example, if a
computer file is used, it is usually accessed, read, and the
information stored in the file employed to attain an end. Similarly
if a unique identifier, e.g., a barcode is used, the unique
identifier is usually read to identify, for example, an object or
file associated with the unique identifier.
[0062] The term "ligating," as used herein, refers to the
enzymatically catalyzed joining of the terminal nucleotide at the
5' end of a first DNA molecule to the terminal nucleotide at the 3'
end of a second DNA molecule.
[0063] A "plurality" contains at least 2 members. In certain cases,
a plurality may have at least 2, at least 5, at least 10, at least
100, at least 100, at least 10,000, at least 100,000, at least
10.sup.6, at least 10.sup.7, at least 10.sup.8 or at least 10.sup.9
or more members.
[0064] If two nucleic acids are "complementary," they hybridize
with one another under high stringency conditions. The term
"perfectly complementary" is used to describe a duplex in which
each base of one of the nucleic acids base pairs with a
complementary nucleotide in the other nucleic acid. In many cases,
two sequences that are complementary have at least 10, e.g., at
least 12 or 15 nucleotides of complementarity.
[0065] An "oligonucleotide binding site" refers to a site to which
an oligonucleotide hybridizes in a target polynucleotide. If an
oligonucleotide "provides" a binding site for a primer, then the
primer may hybridize to that oligonucleotide or its complement. The
term "strand" as used herein refers to a nucleic acid made up of
nucleotides covalently linked together by covalent bonds, e.g.,
phosphodiester bonds. In a cell, DNA usually exists in a
double-stranded form, and as such, has two complementary strands of
nucleic acid referred to herein as the "top" and "bottom" strands.
In certain cases, complementary strands of a chromosomal region may
be referred to as "plus" and "minus" strands, the "first" and
"second" strands, the "coding" and "noncoding" strands, the
"Watson" and "Crick" strands or the "sense" and "antisense"
strands. The assignment of a strand as being a top or bottom strand
is arbitrary and does not imply any particular orientation,
function or structure. The nucleotide sequences of the first strand
of several exemplary mammalian chromosomal regions (e.g., BACs,
assemblies, chromosomes, etc.) is known, and may be found in NCBI's
Genbank database, for example.
[0066] The term "top strand," as used herein, refers to either
strand of a nucleic acid but not both strands of a nucleic acid.
When an oligonucleotide or a primer binds or anneals "only to a top
strand," it binds to only one strand but not the other. The term
"bottom strand," as used herein, refers to the strand that is
complementary to the "top strand." When an oligonucleotide binds or
anneals "only to one strand," it binds to only one strand, e.g.,
the first or second strand, but not the other strand.
[0067] The term "sequencing," as used herein, refers to a method by
which the identity of at least 10 consecutive nucleotides (e.g.,
the identity of at least 20, at least 50, at least 100 or at least
200 or more consecutive nucleotides) of a polynucleotide is
obtained.
[0068] The terms "next-generation sequencing" or "high-throughput
sequencing" refer to the so-called parallelized
sequencing-by-synthesis or sequencing-by-ligation platforms
currently employed by Illumina, Life Technologies, and Roche, etc.
Next-generation sequencing methods may also include nanopore
sequencing methods or electronic-detection based methods such as
Ion Torrent technology commercialized by Life Technologies or
single-molecule fluorescence-based method commercialized by Pacific
Biosciences.
[0069] The term "barcode sequence" or "molecular barcode," as used
herein, refers to a unique sequence of nucleotides used to a)
identify and/or track the source of a polynucleotide in a reaction
and/or b) count how many times an initial molecule is sequenced
(e.g., in cases where substantially every molecule in a sample is
tagged with a different sequence, and then the sample is
amplified). A barcode sequence may be at the 5'-end, the 3'-end or
in the middle of an oligonucleotide. Barcode sequences may vary
widely in size and composition; the following references provide
guidance for selecting sets of barcode sequences appropriate for
particular embodiments: Brenner, U.S. Pat. No. 5,635,400; Brenner
et al, Proc. Natl. Acad. Sci., 97: 1665-1670 (2000); Shoemaker et
al, Nature Genetics, 14: 450-456 (1996); Morris et al, European
patent publication 0799897A1; Wallace, U.S. Pat. No. 5,981,179; and
the like. In particular embodiments, a barcode sequence may have a
length in range of from 4 to 36 nucleotides, or from 6 to 30
nucleotides, or from 8 to 20 nucleotides.
[0070] The term "in vitro" refers to a reaction that occurs in a
vessel with isolated components, not in cells.
[0071] The term "distributed" in the context of cleavage sites that
are distributed along the length of a target nucleic acid molecule,
refers to insertions that are spaced from another along the length
of the target nucleic acid molecule. There is no requirement that
all of the insertions are spaced by the same amount. Rather,
spacing between insertions may be random, semi-random, or not
random.
[0072] The term "chromatin," as used herein, refers to a complex of
molecules including proteins and polynucleotides (e.g. DNA, RNA),
as found in a nucleus of a eukaryotic cell. Chromatin is composed
in part of histone proteins that form nucleosomes, genomic DNA, and
other DNA binding proteins (e.g., transcription factors) that are
generally bound to the genomic DNA.
[0073] The term "treating," as used herein, refers to combining
under conditions (e.g., a suitable temperature, time and
conditions) that result in a reaction, e.g., cleavage.
[0074] The term "chromatin isolated from a population of cells," as
used herein, refers to a source of chromatin that is caused to be
made available. Isolated nuclei (which can be lysed to produce
chromatin) as well as isolated chromatin (i.e., the product of
lysed nuclei) are both considered types of chromatin isolated from
a population of cells.
[0075] The term "transcription factor", as used herein, refers to
any polypeptide that may act by itself or in combination with at
least one other polypeptide to regulate gene expression levels. The
term includes, but is not limited to, polypeptides that directly
bind DNA sequences. Transcription factors can either increases or
suppress expression levels. Examples of transcription factors
include, but are not limited to Myc/Max, AP-1 (Jun, Fos, ATF),
CREB, SMAD, 1-IIF, ETS, ERG, ELK, STAT, estrogen receptor (ER),
androgen receptor (AR), glucocorticoid receptor (GR), progesterone
receptor (PR), NF.kappa.B, p53, OCT, SOX and PAX. The transcription
factor may be a transcription factor identified by sequence
analysis or a naturally-occurring reading frame sequence that has
not been previously characterized as a transcription factor. The
polypeptide may also be an artificially generated or chemically or
enzymatically modified polypeptide.
[0076] The term "insertional enzyme complex," as used herein,
refers to a complex comprising an insertional enzyme and two
adaptor molecules (the "transposon tags") that are combined with
polynucleotides to fragment and add adaptors to the
polynucleotides. Such a system is described in a variety of
publications, including Caruccio (Methods Mol. Biol. 2011 733:
241-55) and US20100120098, which are incorporated by reference
herein.
[0077] The term "tagged fragments," as used herein, refers to
polynucleotide fragments that are attached to tags.
[0078] The term "region," as used herein, refers to a contiguous
length of nucleotides in a genome of an organism. A chromosomal
region may be in the range of 1 bp to the length of an entire
chromosome. In some instances, a region may have a length of at
least 200 bp, at least 500 bp, at least 1 kb, at least 10 kb or at
least 100 kb or more (e.g., up to 1 Mb or 10 Mb or more). The
genome may be from any eukaryotic organism, e.g., an animal or
plant genome such as the genome of a human, monkey, rat, fish or
insect.
[0079] The term "epigenetic map," as used herein, refers to any
representation of epigenetic features, e.g., sites of nucleosomes,
nucleosome-free regions, binding sites for transcription factors,
etc. A map can be physically displayed, e.g., on a computer
monitor. Exemplary epigenetic maps are shown in FIGS. 1C, 3A, 4A,
4B, 5B and 5C.
[0080] The term "mapping information," as used herein, refers to
assembling experimentally-obtained information about an area to a
physical map of the area.
[0081] The term "sequence read abundance," as used herein, refers
to the number of times a particular sequence or nucleotide is
observed in a collection of sequence reads.
[0082] The term "nucleosome-free fragments," as used herein, refers
to fragments of genomic DNA that are relatively depleted or devoid
of nucleosomes, i.e., between nucleosomes.
[0083] The term "chromatin accessibility," as used herein, refers
to how accessible a nucleic acid site is within a polynucleotide,
such as in genomic DNA, i.e., how "open" the chromatin is. A
nucleic acid site associated with a polypeptide, such as with
genomic DNA in nucleosomes, is usually inaccessible. A nucleic acid
site not complexed with a polypeptide is generally accessible, such
as with genomic DNA between nucleosomes (with the exception of
nucleic acid sites complexed with transcription factors and other
DNA binding proteins).
[0084] The term "DNA binding protein occupancy," as used herein,
refers to whether a binding site for a sequence specific DNA
binding protein (e.g., a binding site for a transcription factor)
is occupied by the DNA binding protein. DNA binding protein
occupancy can be measured quantitatively or qualitatively.
[0085] The term "global occupancy," as used herein, refers to
whether a plurality of different binding sites for a DNA binding
protein that are distributed throughout the genome (e.g., a binding
sites for a transcription factor) are bound by the DNA binding
protein. DNA binding protein occupancy can be measured
quantitatively or qualitatively.
[0086] The term "diagnosis," as used herein, refers to a
determination of whether a subject has a particular disease or
condition.
[0087] The term "prognosis," as used herein, refers to prediction
of a clinical outcome, e.g., disease recurrence, recovery from a
disease, death, as well as a prediction of how a subject that has a
particular disease or condition will respond to a particular
treatment.
[0088] Other definitions of terms may appear throughout the
specification.
DESCRIPTION OF EXEMPLARY EMBODIMENTS
[0089] In one aspect, a method for analyzing chromatin is provided.
In certain embodiments, the method comprises: (a) treating
chromatin isolated from a population of cells with an insertional
enzyme complex to produce tagged fragments of genomic DNA. In this
step, the chromatin is tagmented (i.e., cleaved and tagged in the
same reaction) using an insertional enzyme such as Tn5 or MuA that
cleaves the genomic DNA in open regions in the chromatin and adds
adaptors to both ends of the fragments. Methods for tagmenting
isolated genomic DNA are known in the art (see, e.g., Caruccio
Methods Mol. Biol. 2011 733: 241-55; Kaper et al, Proc. Natl. Acad.
Sci. 2013 110: 5552-7; Marine et al, Appl. Environ. Microbiol. 2011
77: 8071-9 and US20100120098) and are commercially available from
Illumina (San Diego, Calif.) and other vendors. Such systems may be
readily adapted for use herein. In some cases, the conditions may
be adjusted to obtain a desirable level of insertion in the
chromatin (e.g., an insertion that occurs, on average, every 50 to
200 base pairs in open regions). The chromatin used in the method
may be made by any suitable method. In some embodiments, nuclei may
be isolated, lysed, and the chromatin may be further purified,
e.g., from the nuclear envelope. In other embodiments, the
chromatin may be isolated by contacting isolated nuclei with the
reaction buffer. In these embodiments, the isolated nuclei may lyse
when it makes contact with the reaction buffer (which comprises
insertional enzyme complexes and other necessary reagents), which
allows the insertional enzyme complexes access to the chromatin. In
these embodiments, the method may comprise isolating nuclei from a
population of cells; and combining the isolated nuclei with the
transposase and adaptors, wherein the combining results in both
lysis of the nuclei to release said chromatin and production of the
adaptor-tagged fragments of genomic DNA. The chromatin does not
require cross-linking as in other methods (e.g., ChIP-SEQ
methods).
[0090] After the chromatin has been fragmented and tagged to
produce tagged fragments of genomic DNA, at least some of the
adaptor tagged fragments are sequenced to produce a plurality of
sequence reads. The fragments may be sequenced using any convenient
method. For example, the fragments may be sequenced using
Illumina's reversible terminator method, Roche's pyrosequencing
method (454), Life Technologies' sequencing by ligation (the SOLiD
platform) or Life Technologies' Ion Torrent platform. Examples of
such methods are described in the following references: Margulies
et al (Nature 2005 437: 376-80); Ronaghi et al (Analytical
Biochemistry 1996 242: 84-9); Shendure et al (Science 2005 309:
1728-32); Imelfort et al (Brief Bioinform. 2009 10:609-18); Fox et
al (Methods Mol Biol. 2009; 553:79-108); Appleby et al (Methods Mol
Biol. 2009; 513:19-39) and Morozova et al (Genomics. 2008
92:255-64), which are incorporated by reference for the general
descriptions of the methods and the particular steps of the
methods, including all starting products, methods for library
preparation, reagents, and final products for each of the steps. As
would be apparent, forward and reverse sequencing primer sites that
are compatible with a selected next generation sequencing platform
can be added to the ends of the fragments during the amplification
step. In certain embodiments, the fragments may be amplified using
PCR primers that hybridize to the tags that have been added to the
fragments, where the primer used for PCR have 5' tails that are
compatible with a particular sequencing platform. In certain cases,
the primers used may contain a molecular barcode (an "index") so
that different pools can be pooled together before sequencing, and
the sequence reads can be traced to a particular sample using the
barcode sequence.
[0091] In another aspect, the present disclosure provides a method
for determining accessibility of a polynucleotide at a site,
wherein the polynucleotide is from a cell sample, said method
comprising: inserting a plurality of molecular tags with an
insertional enzyme into the polynucleotide and using the molecular
tags to determine accessibility at the site. The cell sample can be
from a primary source. The cell sample may consist of a single
cell. The cell sample may consist of a finite number of cells (e.g.
less than about 500,000 cells).
[0092] The method can further comprise using the determined
accessibility to identify one or more proteins that are bound to
the polynucleotide at the site. In some instances, at least one of
the proteins is a transcription factor. Additionally, the method
can comprise using the molecular tags to generate an accessibility
map of the polynucleotide.
[0093] The polynucleotide may be fragmented into a plurality of
fragments during the insertion of the molecular tags. In some
cases, the fragments may be amplified. In some cases, the fragments
can be sequenced to generate a plurality of sequencing reads. This
may be used to determine the accessibility of the polynucleotide at
any given site. The fragments may be sequenced using a
high-throughput sequencing technique. In some cases, the sequencing
reads can be normalized based on the sequence insertion preference
of the insertional enzyme. The length of the sequenced reads can be
used to determine a chromatin state annotation.
[0094] The polynucleotide can be bound to a plurality of
association molecules. The association molecules can be, for
example, proteins, nucleic acids or saccharides. In some cases, the
association molecules can comprise histones. In other cases, the
association molecules can comprise aptamers.
[0095] The insertional enzyme can be any enzyme capable of
inserting a nucleic acid sequence into a polynucleotide. In some
cases, the insertional enzyme can insert the nucleic acid sequence
into the polynucleotide in a substantially sequence-independent
manner. The insertional enzyme can be prokaryotic or eukaryotic.
Examples of insertional enzymes include, but are not limited to,
transposases, HERMES, and HIV integrase. The transposase can be a
Tn transposase (e.g. Tn3, Tn5, Tn7, Tn10, Tn552, Tn903), a MuA
transposase, a Vibhar transposase (e.g. from Vibrio harveyi),
Ac-Ds, Ascot-1, Bs1, Cin4, Copia, En/Spm, F element, hobo, Hsmar1,
Hsmar2, IN (HIV), IS1, IS2, IS3, IS4, IS5, IS6, IS10, IS21, IS30,
IS50, IS51, IS150, IS256, IS407, IS427, IS630, IS903, IS911, IS982,
IS1031, ISL2, L1, Mariner, P element, Tam3, Tc1, Tc3, Te1, THE-1,
Tn/O, TnA, Tn3, Tn5, Tn7, Tn10, Tn552, Tn903, Tol1, Tol2, TnlO,
Ty1, any prokaryotic transposase, or any transposase related to
and/or derived from those listed above. In certain instances, a
transposase related to and/or derived from a parent transposase can
comprise a peptide fragment with at least about 50%, about 55%,
about 60%, about 65%, about 70%, about 75%, about 80%, about 85%,
about 90%, about 91%, about 92%, about 93%, about 94%, about 95%,
about 96%, about 97%, about 98%, or about 99% amino acid sequence
homology to a corresponding peptide fragment of the parent
transposase. The peptide fragment can be at least about 10, about
15, about 20, about 25, about 30, about 35, about 40, about 45,
about 50, about 60, about 70, about 80, about 90, about 100, about
150, about 200, about 250, about 300, about 400, or about 500 amino
acids in length. For example, a transposase derived from Tn5 can
comprise a peptide fragment that is 50 amino acids in length and
about 80% homologous to a corresponding fragment in a parent Tn5
transposase. In some cases, the insertion can be facilitated and/or
triggered by addition of one or more cations. The cations can be
divalent cations such as, for example, Ca.sup.2+, Mg.sup.2+ and
Mn.sup.2+.
[0096] The molecular tags can comprise sequencing adaptors, locked
nucleic acids (LNAs), zip nucleic acids (ZNAs), RNAs, affinity
reactive molecules (e.g. biotin, dig), self-complementary
molecules, phosphorothioate modifications, azide or alkyne groups.
In some cases, the sequencing adaptors can further comprise a
barcode label. Further, the barcode labels can comprises a unique
sequence. The unique sequences can be used to identify the
individual insertion events. Any of the tags can further comprise
fluorescence tags (e.g. fluorescein, rhodamine, Cy3, Cy5, thiazole
orange, etc.).
[0097] Additionally, the insertional enzyme can further comprise an
affinity tag. In some cases, the affinity tag can be an antibody.
The antibody can bind to, for example, a transcription factor, a
modified nucleosome or a modified nucleic acid. Examples of
modified nucleic acids include, but are not limited to, methylated
or hydroxymethylated DNA. In other cases, the affinity tag can be a
single-stranded nucleic acid (e.g. ssDNA, ssRNA). In some examples,
the single-stranded nucleic acid can bind to a target nucleic acid.
In further cases, the insertional enzyme can further comprise a
nuclear localization signal. In some cases, the cell sample can be
permeabilized to allow access for the insertional enzyme. The
permeabilization can be performed in a way to minimally perturb the
nuclei in the cell sample. In some instances, the cell sample can
be permeabilized using a permeabilization agent. Examples of
permeabilization agents include, but are not limited to, NP40,
digitonin, tween, streptolysin, and cationic lipids. In other
instances, the cell sample can be permeabilized using hypotonic
shock and/or ultrasonication. In other cases, the insertional
enzyme can be highly charged, which may allow it to permeabilize
through cell membranes.
[0098] In yet another aspect, the present disclosure provides a
method for analyzing the three-dimensional structure of a
polynucleotide from a cell sample, comprising: inserting a
plurality of molecular tags with an insertional enzyme into the
polynucleotide; and using the molecular tags to analyze the
three-dimensional structure of the polynucleotide. The insertional
enzyme can comprise two or more enzymatic moieties, which may be
optionally linked together. The enzymatic moieties can be linked by
using any suitable chemical synthesis or bioconjugation methods.
For example, the enzymatic moieties can be linked via an
ester/amide bond, a thiol addition into a maleimide, Native
Chemical Ligation (NCL) techniques, Click Chemistry (i.e. an
alkyne-azide pair), or a biotin-streptavidin pair. In some cases,
each of the enzymatic moieties can insert a common sequence into
the polynucleotide. The common sequence can comprise a common
barcode. The enzymatic moieties can comprise transposases or
derivatives thereof. In some embodiments, the polynucleotide may be
fragmented into a plurality of fragments during the insertion. The
fragments comprising the common barcode can be determined to be in
proximity in the three-dimensional structure of the
polynucleotide.
[0099] The polynucleotide can be genomic DNA. The polynucleotide
can be further bound to proteins, such as histones, and may be
optionally packaged in the form of chromatin. In particular cases,
DNA fragments corresponding to one or more regions of a genome
(e.g., 2 or more, 10 or more, 50 or more, 100 or more, up to 1,000
or more regions) may be enriched, i.e., selected, by hybridization
prior to sequencing. In these embodiments, the entire library does
not need to be sequenced. Depending on the desired result and
length of the selected region (if a selection step has been
performed), this step of the method may result in at least 1,000
sequencing (e.g., at least 10,000, at least 100,000, at least
500,000, at least 10.sup.6, at least 5.times.10.sup.6, up to
10.sup.7 or more sequencing reads). The sequence reads are
generally stored in computer memory.
[0100] Some embodiments of the methods involve making an epigenetic
map of a region of the genome of the cells. This step may be done
by mapping information obtained from the sequence reads to the
region. In these embodiments, the sequence reads are analyzed
computationally to produce a number of numerical outputs that are
mapped to a representation (e.g., a graphical representation) of a
region of interest. As will be explained in greater detail below,
many types of information may be mapped, including, but not limited
to: (i) cleavage sites for the transposase; (ii) the sizes of the
fragments produced in step a); (iii) fragment length; (iii) the
positions of sequence reads of a defined range in length; and (iv)
sequence read abundance.
[0101] For example, the sequence reads may be analyzed
computationally to identify the ends of the fragments (from which
the transposon cleavage sites can be inferred). In these
embodiments, one end of a fragment can be defined by sequence that
is at the beginning of a sequencing read and the other end of the
fragment can be defined by sequence that is at the beginning of a
second sequencing read, where the first and second sequencing reads
were obtained by paired end sequencing (e.g., using Illumina's
sequencing platform). The same information can be obtained from
examining the beginning and end of longer sequence reads (which
should, in theory, have the sequence of both adaptors; one at one
end and the other at the other end). In these embodiments, a single
sequence read may contain both adaptor sequences, in which case
both ends of a fragment (which correspond to two cleavage sites for
the two separate transposases) can be inferred from a single
sequence read. The lengths of the fragments can be calculated by,
e.g., mapping the fragment ends onto the nucleotide sequence of the
region of interest, and counting the number of base pairs between
those positions. The information used may be obtained using the
nucleotide sequences at the beginning and/or the end of a sequence
read.
[0102] In certain cases, the sequence reads can be placed into
groups by length. In some embodiments, some sequences can be
annotated as being a nucleosome-free sequence (i.e., a sequence
from a fragment that is predicted to be between nucleosomes) based
on its size. Reads that are associated with mononucleosomes,
dinucleosomes and trinucleosomes can also be identified. These
cutoffs can be determined using the data shown in FIG. 12. Fragment
lengths (which provide the same information as sequence read
lengths) can also be processed in the same way. In certain cases,
sequence read abundance, i.e., the number of times a particular
sequence in a genomic region is represented in the sequence reads,
may be calculated.
[0103] The resultant epigenetic map can provide an analysis of the
chromatin in the region of interest. For example, depending on
which information is mapped, the map can show one or more of the
following: a profile of chromatin accessibility along the region;
DNA binding protein (e.g., transcription factor) occupancy for a
site in the region; nucleosome-free DNA in the region; positioning
of nucleosomes along the region; and a profile of chromatin states
along the region. In some embodiments, the method may further
comprise measuring global occupancy of a binding site for the DNA
binding protein by, e.g., aggregating data for one DNA binding
protein over a plurality of sites to which that protein binds. In
certain instances, the map can also be annotated with sequence
information, and information about the sequence (e.g., the
positions of promoters, introns, exons, known enhancers,
transcriptional start sites, untranslated regions, terminators,
etc.) so that the epigenetic information can be viewed in context
with the annotation.
[0104] In certain embodiments, the epigenetic map can provide
information regarding active regulatory regions and/or the
transcription factors that are bound to the regulatory regions. For
example, nucleosome positions can be inferred from the lengths of
sequencing reads generated. Alternatively, transcription factor
binding sites can be inferred from the size, distribution and/or
position of the sequencing reads generated. In some cases, novel
transcription factor binding sites can be inferred from sequencing
reads generated. In other cases, novel transcription factors can be
inferred from sequencing reads generated.
[0105] The population of cells used in the assay may be composed of
any number of cells, e.g., about 500 to about 10.sup.6 or more
cells, about 500 to about 100,000 cells, about 500 to about 50,000
cells, about 500 to about 10,000 cells, about 50 to 1000 cells,
about 1 to 500 cells, about 1 to 100 cells, about 1 to 50 cells, or
a single cell. In some cases, the cell sample can consist of less
than about 1000, about 2000, about 3000, about 4000, about 5000,
about 6000, about 7000, about 8000, about 9000, about 10,000, about
15,000, about 20,000, about 25,000, about 30,000, about 40,000,
about 50,000, about 60,000, about 70,000, about 80,000, about
90,000, about 100,000, about 120,000, about 140,000, about 160,000,
about 180,000, about 200,000, about 250,000, about 300,000, about
350,000, about 400,000, about 450,000, about 500,000, about
600,000, about 700,000, about 800,000, about 900,000, or about
1,000,000 cells. In other cases, the cell sample can consist of
more than about 1000, about 2000, about 3000, about 4000, about
5000, about 6000, about 7000, about 8000, about 9000, about 10,000,
about 15,000, about 20,000, about 25,000, about 30,000, about
40,000, about 50,000, about 60,000, about 70,000, about 80,000,
about 90,000, about 100,000, about 120,000, about 140,000, about
160,000, about 180,000, about 200,000, about 250,000, about
300,000, about 350,000, about 400,000, about 450,000, about
500,000, about 600,000, about 700,000, about 800,000, about
900,000, or about 1,000,000 cells.
[0106] The cells can be from any source. In certain cases, the
cells may be obtained from a culture of cells, e.g., a cell line.
In other cases, the cells may be isolated from an individual (e.g.,
a patient or the like). The cells may be isolated from a soft
tissue or from a bodily fluid, or from a cell culture that is grown
in vitro. In particular embodiments, the chromatin may be isolated
from a soft tissue such as brain, adrenal gland, skin, lung,
spleen, kidney, liver, spleen, lymph node, bone marrow, bladder
stomach, small intestine, large intestine or muscle, etc. Bodily
fluids include blood, plasma, saliva, mucous, phlegm, cerebral
spinal fluid, pleural fluid, tears, lactal duct fluid, lymph,
sputum, cerebrospinal fluid, synovial fluid, urine, amniotic fluid,
and semen, etc.
[0107] In some embodiments, the polynucleotide (e.g. genomic DNA,
chromosomal DNA) used in the method may be from blood cells,
wherein blood cells refers to a sample of whole blood or a
sub-population of cells in whole blood. Sub-populations of cells in
whole blood include platelets, red blood cells (erythrocytes),
platelets and white blood cells (i.e., peripheral blood leukocytes,
which are made up of neutrophils, lymphocytes, eosinophils,
basophils and monocytes). These five types of white blood cells can
be further divided into two groups, granulocytes (which are also
known as polymorphonuclear leukocytes and include neutrophils,
eosinophils and basophils) and mononuclear leukocytes (which
include monocytes and lymphocytes). Lymphocytes can be further
divided into T cells, B cells and NK cells. Peripheral blood cells
are found in the circulating pool of blood and not sequestered
within the lymphatic system, spleen, liver, or bone marrow. Other
cells are present in blood that can be isolated. If blood is first
contacted with an agent and then a sample of the blood is used in
an assay, then a portion or all of the contacted blood may be used
in the assay.
[0108] In certain embodiments, the cell sample can be isolated
directly from a primary source. For example, the cell sample can be
isolated directly from fresh tissues. In other cases, the cell
sample can be isolated directly from frozen tissues. In yet other
cases, the cell sample can be isolated directly from fixed tissues.
Further examples of primary sources of cell samples include, but
are not limited to, cells dissociated from tissues, blood cells,
FFPE tissues, bacterial, viral, mitochondria, chloroplast, in vitro
assembled protein DNA complexes, neutrophil extracellular
traps.
[0109] Using the methods provided in the present disclosure, the
disease state in a subject can be analyzed based on the
accessibility of a polynucleotide site in a cell sample obtained
from the subject. For example, transcription factor occupancy at
any given site can result in the lack of accessibility at the site.
Based on the transcription factor occupancy, the subject can then
be treated with a suitable agent (e.g. a transcription factor
inhibitor).
[0110] In certain cases, the cell samples can be further analyzed
phenotypically. For example, the cell samples can be analyzed using
fluorescence activated cell sorting (FACS) and/or laser capture
microdissection (LCM). In some cases, the cell sample and/or
polynucleotides may be divided into a plurality of portions. The
portions can be divided based on the molecular tags (e.g.
fluorescence tags). In some cases, the cell sample and/or
polynucleotides can be sorted. The sorting can be performed after
the molecular tags are inserted into the polynucleotide. The
sorting can be performed before the fragments are sequenced. The
gene transcription of the cell samples can also be analyzed using
techniques such as fluorescence in situ hybridization (FISH). The
chromatin accessibility can be correlated with the phenotypical,
transcriptional or translational analysis.
[0111] In some embodiments, the cells are of the same cell type. In
these embodiments, the population of cells may be selected by MACS
or FACS from a heterogeneous population of cells, e.g., blood, by
known methods using labeled antibodies to cells surface markers. A
wide variety of cells can be isolated using these methods,
including stem cells, cancer stem cells and subsets of blood cells.
In particular embodiments the following cells may be isolated from
blood by FACS or MACS; T cells (CD3.sup.+ CD4.sup.+ CD8.sup.+), B
cells (CD19.sup.+ CD20.sup.+), dendritic cells (CD11c.sup.+
CD20.sup.+), NK Cell (CD56.sup.+), stem cells/precursor cells
(CD34.sup.+; hematopoietic stem cells only), macrophage/monocytes
(CD14.sup.+ CD33.sup.+), granulocytes (CD66b.sup.+), platelet
(CD41.sup.+ CD61.sup.+ CD62.sup.+), erythrocytes (CD235a.sup.+,
endothelial cells (CD146.sup.+) and epithelial cells (CD326.sup.+).
Subsets of these cells can be isolated using antibodies to further
cell surface markers.
[0112] In some embodiments, the method can be used to compare two
samples. In these embodiments, the method may comprise analyzing a
first population of cells using the above-described method to
produce a first epigenetic map; and analyzing a second population
of cells using the above-described method to produce a second
epigenetic map; and comparing the first epigenetic map to the
second epigenetic map, e.g., to see if there are any changes in
chromatin openness or transcription factor occupancy, for
example.
[0113] In some embodiments, the first population of cells and the
second population of cells are collected from the same individual
at different times. In other embodiments, the first population of
cells and the second population of cells are different populations
of cells collected from tissues or different individuals.
[0114] Exemplary cell types that can be used in the method include,
for example, cells isolated from a tissue biopsy (e.g., from a
tissue having a disease such as colon, breast, prostate, lung, skin
cancer, or infected with a pathogen etc.) and normal cells from the
same tissue, e.g., from the same patient; cells grown in tissue
culture that are immortal (e.g., cells with a proliferative
mutation or an immortalizing transgene), infected with a pathogen,
or treated (e.g., with environmental or chemical agents such as
peptides, hormones, altered temperature, growth condition, physical
stress, cellular transformation, etc.), and normal cells (e.g.,
cells that are otherwise identical to the experimental cells except
that they are not immortalized, infected, or treated, etc.); cells
isolated from a mammal with a cancer, a disease, a geriatric
mammal, or a mammal exposed to a condition, and cells from a mammal
of the same species, e.g., from the same family, that is healthy or
young; and differentiated cells and non-differentiated cells from
the same mammal (e.g., one cell being the progenitor of the other
in a mammal, for example). In one embodiment, cells of different
types, e.g., neuronal and non-neuronal cells, or cells of different
status (e.g., before and after a stimulus on the cells) may be
compared. In another embodiment, the experimental material is cells
susceptible to infection by a pathogen such as a virus, e.g., human
immunodeficiency virus (HIV), etc., and the control material is
cells resistant to infection by the pathogen. In another embodiment
of the invention, the sample pair is represented by
undifferentiated cells, e.g., stem cells, and differentiated cells.
Cells from yeast, plants and animals, such as fish, birds,
reptiles, amphibians and mammals may be used in the subject
methods. In certain embodiments, mammalian cells, i.e., cells from
mice, rabbits, primates, or humans, or cultured derivatives
thereof, may be used.
[0115] In some exemplary embodiments, the method may be used to
identify the effect of a test agent, e.g., a drug, or to determine
if there are differences in the effect of two or more different
test agents. In these embodiments, two or more identical
populations of cells may be prepared and, depending on how the
experiment is to be performed, one or more of the populations of
cells may be incubated with the test agent for a defined period of
time. After incubation with the test agent, the chromatin of the
populations of cells can be analyzed using the methods set forth
above, and the results can be compared. In a particular embodiment,
the cells may be blood cells, and the cells can be incubated with
the test agent ex vivo. These methods can be used to determine the
mode of action of a test agent, to identify changes in chromatin
structure or transcription factor occupancy in response to the
drug, for example.
[0116] The method described above may also be used as a diagnostic
(which term is intended to include methods that provide a diagnosis
as well as methods that provide a prognosis). These methods may
comprise, e.g., analyzing chromatin from a patient using the method
described above to produce an epigenetic map; and providing a
diagnosis or prognosis based on the epigenetic map.
[0117] The method set forth herein may be used to provide a
reliable diagnostic to any condition associated with altered
chromatin or DNA binding protein occupancy. The method can be
applied to the characterization, classification, differentiation,
grading, staging, diagnosis, or prognosis of a condition
characterized by an epigenetic pattern (e.g., a pattern of
chromatin accessibility or DNA binding protein occupancy). For
example, the method can be used to determine whether the epigenetic
map of a sample from an individual suspected of being affected by a
disease or condition is the same or different compared to a sample
that is considered "normal" with respect to the disease or
condition. In particular embodiments, the method can be directed to
diagnosing an individual with a condition that is characterized by
an epigenetic pattern at a particular locus in a test sample, where
the pattern is correlated with the condition. The methods can also
be used for predicting the susceptibility of an individual to a
condition.
[0118] Exemplary conditions that are suitable for analysis using
the methods set forth herein can be, for example, cell
proliferative disorder or predisposition to cell proliferative
disorder; metabolic malfunction or disorder; immune malfunction,
damage or disorder; CNS malfunction, damage or disease; symptoms of
aggression or behavioral disturbance; clinical, psychological and
social consequences of brain damage; psychotic disturbance and
personality disorder; dementia or associated syndrome;
cardiovascular disease, malfunction and damage; malfunction, damage
or disease of the gastrointestinal tract; malfunction, damage or
disease of the respiratory system; lesion, inflammation, infection,
immunity and/or convalescence; malfunction, damage or disease of
the body as an abnormality in the development process; malfunction,
damage or disease of the skin, the muscles, the connective tissue
or the bones; endocrine and metabolic malfunction, damage or
disease; headache or sexual malfunction, and combinations
thereof.
[0119] In some embodiments, the method can provide a prognosis,
e.g., to determine if a patient is at risk for recurrence. Cancer
recurrence is a concern relating to a variety of types of cancer.
The prognostic method can be used to identify surgically treated
patients likely to experience cancer recurrence so that they can be
offered additional therapeutic options, including preoperative or
postoperative adjuncts such as chemotherapy, radiation, biological
modifiers and other suitable therapies. The methods are especially
effective for determining the risk of metastasis in patients who
demonstrate no measurable metastasis at the time of examination or
surgery.
[0120] The method can also be used to determining a proper course
of treatment for a patient having a disease or condition, e.g., a
patient that has cancer. A course of treatment refers to the
therapeutic measures taken for a patient after diagnosis or after
treatment. For example, a determination of the likelihood for
recurrence, spread, or patient survival, can assist in determining
whether a more conservative or more radical approach to therapy
should be taken, or whether treatment modalities should be
combined. For example, when cancer recurrence is likely, it can be
advantageous to precede or follow surgical treatment with
chemotherapy, radiation, immunotherapy, biological modifier
therapy, gene therapy, vaccines, and the like, or adjust the span
of time during which the patient is treated. In a particular
embodiment, a lab will receive a sample (e.g., blood) from a remote
location (e.g., a physician's office or hospital), the lab will
analyze cells in the sample as described above to produce data, and
the data may be forwarded to the remote location for analysis.
[0121] Compositions
[0122] In one aspect, the present disclosure provides compositions
related to the methods provided herein. The composition can
comprise a polynucleotide, an insertional enzyme and an insert
element, wherein: the insert element can comprise a nucleic acid
comprising a predetermined sequence and the insertional enzyme can
further comprise an affinity tag. The polynucleotide can be further
bound to a plurality of association molecules. The association
molecules can be proteins (e.g. histones) or nucleic acids (e.g.
aptamers). The affinity tag can be an antibody. In some cases, the
antibody can be bound to a transcription factor. In other cases,
the antibody can be bound to a modified nucleosome. In further
cases, the antibody can be bound to a modified nucleic acid.
Examples of modified nucleic acids include, but are not limited to,
methylated or hydroxymethylated DNA. The affinity tag can also be a
single-stranded nucleic acid (e.g. ssDNA, ssRNA). In some cases,
the single-stranded nucleic acid can be bound to a target nucleic
acid. In some instances, the insertional enzyme can further
comprise a nuclear localization signal.
[0123] The composition can comprise a polynucleotide, an
insertional enzyme and an insert element, wherein: the insertional
enzyme comprises two or more enzymatic moieties and the enzymatic
moieties are linked together. The insert element can be bound to
the insertional enzyme. The insertional enzyme can also be bound to
the polynucleotide. In some cases, the polynucleotide can be
further bound to a plurality of association molecules. The
association molecules can be proteins (e.g. histones) or nucleic
acids (e.g. aptamers).
Kits
[0124] In yet another aspect, the present disclosure provides kits
that contain reagents for practicing the subject methods, as
described above. The subject kits can comprise: (a) reagents for
isolating nuclei from a population of cells; (b) transposase and
transposon tags, and (c) transposase reaction buffer, wherein the
components of the kit are configured such that, combining the
reaction buffer, transposase and adaptors with nuclei in vitro
results in both lysis of the nuclei to release chromatin and
production of adaptor-tagged fragments of genomic DNA.
[0125] In some cases, the kit can comprise: (a) a cell lysis
buffer; (b) an insertional enzyme comprising an affinity tag; and
(c) an insert element comprising a nucleic acid, wherein said
nucleic acid comprises a predetermined sequence. The insertional
enzyme can be, for example, a transposase. The insertional enzyme
can also comprise two or more enzymatic moieties that are linked
together. In some cases, the affinity tag can be an antibody. The
antibody can bind to a transcription factor, a modified nucleosome,
or a modified nucleic acid. Examples of modified nucleic acids
include, but are not limited to, methylated or hydroxymethylated
DNA. In other cases, the affinity tag can be a single-stranded
nucleic acid (e.g. ssDNA, ssRNA).
[0126] The kit may optionally contain other components, for
example: PCR primers, PCR reagents such as polymerase, buffer,
nucleotides etc., as described above. The various components of the
kit may be present in separate containers or certain compatible
components may be precombined into a single container, as
desired.
[0127] In addition to above-mentioned components, the subject kits
may further include instructions for using the components of the
kit to practice the subject methods, i.e., instructions for sample
analysis. The instructions for practicing the subject methods are
generally recorded on a suitable recording medium. For example, the
instructions may be printed on a substrate, such as paper or
plastic, etc. As such, the instructions may be present in the kits
as a package insert, in the labeling of the container of the kit or
components thereof (i.e., associated with the packaging or
subpackaging) etc. In other embodiments, the instructions are
present as an electronic storage data file present on a suitable
computer readable storage medium, e.g., CD-ROM, diskette, etc. In
yet other embodiments, the actual instructions are not present in
the kit, but means for obtaining the instructions from a remote
source, e.g., via the internet, are provided. An example of this
embodiment is a kit that includes a web address where the
instructions can be viewed and/or from which the instructions can
be downloaded. As with the instructions, this means for obtaining
the instructions is recorded on a suitable substrate.
EMBODIMENTS
[0128] A method of mapping chromatin is provided. In some
embodiments, this method comprises the steps of: fragmenting the
chromatin of rare or abundant cells with a transposase which
inserts sequencing adapters into the polynucleotides within the
chromatin, and amplifying and sequencing the fragments to generate
a cell-specific map.
[0129] In certain embodiments, the cell-specific map provides
information regarding active regulatory regions and the
transcription factors that are bound to said regulatory
regions.
[0130] In certain embodiments, the number of said rare cells is
between 1 and 100,000.
[0131] In certain embodiments, the transposase is derived from Tn5
transposase.
[0132] In certain embodiments, the transposase is derived from MuA
transposase.
[0133] In certain embodiments, nucleosome positions are inferred
from the lengths of sequencing reads generated.
[0134] In certain embodiments, transcription factor binding sites
are inferred from sequencing reads generated.
[0135] In certain embodiments, chromatin is isolated directly from
fresh tissues.
[0136] In certain embodiments, chromatin is isolated directly from
frozen tissues.
[0137] In certain embodiments, chromatin is isolated directly from
fixed tissues.
[0138] In certain embodiments, sequences are added to the
sequencing adapter to uniquely identify the fragments for
multiplexing (barcoding).
[0139] In certain embodiments, an affinity tag is used to target
the transposase to a specific macromolecule of interest.
[0140] In certain embodiments, sequences are added to the
sequencing adapter to uniquely identify the fragments for
multiplexing (barcoding), and an affinity tag is used to target the
transposase to a specific macromolecule of interest.
[0141] In certain embodiments the affinity tag is an antibody
targeted to a transcription factor.
[0142] In certain embodiments the affinity tag is an antibody
targeted to a modified nucleosome.
[0143] In certain embodiments, the insert size distribution at a
specific genomic locus is used to infer chromatin openness.
[0144] In certain embodiments, the insert size distribution and
positions of insertion are used to infer transcription factor
binding.
[0145] In certain embodiments, the number of sequencing reads
obtained is normalized by measured sequence insertion preference of
the transposase.
[0146] In certain embodiments, novel transcription factor binding
sites are inferred from sequencing reads generated.
[0147] In certain embodiments, novel transcription factors are
inferred from sequencing reads generated.
[0148] In certain embodiments, causal variants can be inferred by
looking at allele specific generation of sequencing reads.
[0149] In certain embodiments, chromatin state annotations are
inferred from the distribution of lengths of sequencing reads.
EXAMPLES
[0150] Aspects of the present teachings can be further understood
in light of the following examples, which should not be construed
as limiting the scope of the present teachings in any way.
Example 1. Assay for Transposase Accessible Chromatin Using
Sequencing (ATAC-Seq)
[0151] Described herein is an Assay for Transposase Accessible
Chromatin using sequencing (ATAC-seq)--based on direct in vitro
transposition of sequencing adapters into native chromatin--as a
rapid and sensitive method for integrative epigenomic analysis.
ATAC-seq captures open chromatin sites using a simple 2-step
protocol from 500 to 50,000 cells, and reveals the interplay
between genomic locations of open chromatin, DNA binding proteins,
individual nucleosomes, and higher-order compaction at regulatory
regions with nucleotide resolution. Classes of DNA binding factor
that strictly avoid, can tolerate, or tend to overlap with
nucleosomes have been discovered. Using ATAC-seq, the serial daily
epigenomes of resting human T cells was measured and evaluated from
a proband via standard blood draws, demonstrating the feasibility
of reading personal epigenomes in clinical timescales for
monitoring health and disease.
Materials and Methods
[0152] An exemplary implementation of ATAC-seq protocol has three
major steps:
[0153] 1) Prepare Nuclei:
[0154] To prepare nuclei, 50,000 cells were spun at 500.times.g for
5 minutes, followed by a wash using 50 .mu.L of cold 1.times.PBS
and centrifugation at 500.times.g for 5 minutes. Cells were lysed
using cold lysis buffer (10 mM Tris-Cl, pH 7.4, 10 mM NaCl, 3 mM
MgCl.sub.2 and 0.1% IGEPAL CA-630). Immediately after lysis, nuclei
were spun at 500.times.g for 10 minutes using a refrigerated
centrifuge. To avoid losing cells during the nuclei prep, a fixed
angle centrifuge was used and they were carefully pipetted away
from the pellet after centrifugations.
[0155] 2) Transpose and Purify:
[0156] Immediately following the nuclei prep, the pellet was
resuspended in the transposase reaction mix (25 .mu.L 2.times.TD
buffer, 2.5 .mu.L Transposase (Illumina) and 22.5 .mu.L of nuclease
free water). The transposition reaction was carried out for 30
minutes at 37.degree. C. Directly following transposition the
sample was purified using a Qiagen Minelute kit.
[0157] 3) PCR:
[0158] Following purification, we amplified library fragments using
1.times.NEBnext PCR master mix and 1.25 .mu.M of custom Nextera PCR
primers 1 and 2 (see table below), using the following PCR
conditions: 72.degree. C. for 5 minutes, 98.degree. C. for 30
seconds, followed by thermocycling at 98.degree. C. for 10 seconds,
63.degree. C. for 30 seconds and 72.degree. C. for 1 minute. To
reduce GC and size bias in PCR, the PCR reactions were monitored
using qPCR in order to stop amplification prior to saturation. To
do this, the full libraries were amplified for 5 cycles, after 5
cycles an aliquot of the PCR reaction was taken and added to 10
.mu.l of the PCR cocktail with Sybr Green at a final concentration
of 0.6.times.. We ran this reaction for 20 cycles, to determine the
additional number of cycles needed for the remaining 45 .mu.L
reaction. The libraries were purified using a Qiagen PCR cleanup
kit yielding a final library concentration of .about.30 nM in 20
.mu.L. Libraries were amplified for a total of 10-12 cycles.
TABLE-US-00001 Ad1_noMX: AATGATACGGCGACCACCGAGATCTACACTCGTCGGCAGC
GTCAGATGTG (SEQ ID NO: 1) Ad2.1_
CAAGCAGAAGACGGCATACGAGATTCGCCTTAGTCTCGTG TAAGGCGA GGCTCGGAGATGT
(SEQ ID NO: 2) Ad2.2_ CAAGCAGAAGACGGCATACGAGATCTAGTACGGTCTCGTG
CGTACTAG GGCTCGGAGATGT (SEQ ID NO: 3) Ad2.3_
CAAGCAGAAGACGGCATACGAGATTTCTGCCTGTCTCGTG AGGCAGAA GGCTCGGAGATGT
(SEQ ID NO: 4) Ad2.4_ CAAGCAGAAGACGGCATACGAGATGCTCAGGAGTCTCGTG
TCCTGAGC GGCTCGGAGATGT (SEQ ID NO: 5) Ad2.5_
CAAGCAGAAGACGGCATACGAGATAGGAGTCCGTCTCGTG GGACTCCT GGCTCGGAGATGT
(SEQ ID NO: 6) Ad2.6_ CAAGCAGAAGACGGCATACGAGATCATGCCTAGTCTCGTG
TAGGCATG GGCTCGGAGATGT (SEQ ID NO: 7) Ad2.7_
CAAGCAGAAGACGGCATACGAGATGTAGAGAGGTCTCGTG CTCTCTAC GGCTCGGAGATGT
(SEQ ID NO: 8) Ad2.8_ CAAGCAGAAGACGGCATACGAGATCCTCTCTGGTCTCGTG
CAGAGAGG GGCTCGGAGATGT (SEQ ID NO: 9) Ad2.9_
CAAGCAGAAGACGGCATACGAGATAGCGTAGCGTCTCGTG GCTACGCT GGCTCGGAGATGT
(SEQ ID NO: 10) Ad2.10_ CAAGCAGAAGACGGCATACGAGATCAGCCTCGGTCTCGTG
CGAGGCTG GGCTCGGAGATGT (SEQ ID NO: 11) Ad2.11_
CAAGCAGAAGACGGCATACGAGATTGCCTCTTGTCTCGTG AAGAGGCA GGCTCGGAGATGT
(SEQ ID NO: 12) Ad2.12_ CAAGCAGAAGACGGCATACGAGATTCCTCTACGTCTCGTG
GTAGAGGA GGCTCGGAGATGT (SEQ ID NO: 13) Ad2.13_
CAAGCAGAAGACGGCATACGAGATATCACGACGTCTCGTG GTCGTGAT GGCTCGGAGATGT
(SEQ ID NO: 14) Ad2.14_ CAAGCAGAAGACGGCATACGAGATACAGTGGTGTCTCGTG
ACCACTGT GGCTCGGAGATGT (SEQ ID NO: 15) Ad2.15_
CAAGCAGAAGACGGCATACGAGATCAGATCCAGTCTCGTG TGGATCTG GGCTCGGAGATGT
(SEQ ID NO: 16) Ad2.16_ CAAGCAGAAGACGGCATACGAGATACAAACGGGTCTCGTG
CCGTTTGT GGCTCGGAGATGT (SEQ ID NO: 17) Ad2.17_
CAAGCAGAAGACGGCATACGAGATACCCAGCAGTCTCGTG TGCTGGGT GGCTCGGAGATGT
(SEQ ID NO: 18) Ad2.18_ CAAGCAGAAGACGGCATACGAGATAACCCCTCGTCTCGTG
GAGGGGTT GGCTCGGAGATGT (SEQ ID NO: 19) Ad2.19_
CAAGCAGAAGACGGCATACGAGATCCCAACCTGTCTCGTG AGGTTGGG GGCTCGGAGATGT
(SEQ ID NO: 20) Ad2.20_ CAAGCAGAAGACGGCATACGAGATCACCACACGTCTCGTG
GTGTGGTG GGCTCGGAGATGT (SEQ ID NO: 21) Ad2.21_
CAAGCAGAAGACGGCATACGAGATGAAACCCAGTCTCGTG TGGGTTTC GGCTCGGAGATGT
(SEQ ID NO: 22) Ad2.22_ CAAGCAGAAGACGGCATACGAGATTGTGACCAGTCTCGTG
TGGTCACA GGCTCGGAGATGT (SEQ ID NO: 23) Ad2.23_
CAAGCAGAAGACGGCATACGAGATAGGGTCAAGTCTCGTG TTGACCCT GGCTCGGAGATGT
(SEQ ID NO: 24) Ad2.24_ CAAGCAGAAGACGGCATACGAGATAGGAGTGGGTCTCGTG
CCACTCCT GGCTCGGAGATGT (SEQ ID NO: 25)
[0159] Low Cell Number Protocol:
[0160] To prepare the 500 and 5,000 cell reactions the same
protocol was used with some notable exceptions: The transposition
reaction was done in a 5 .mu.L instead of 50 .mu.L reaction. Also,
the Qiagen Minelute purification was eliminated prior to PCR and
instead took the 5 .mu.L reaction immediately after transposition
directly into the 50 .mu.L PCR.
[0161] Library QC and Quantitation:
[0162] During the ATAC-seq protocol, the size selection step was
avoided to maximize the library complexity. The sequenced insert
size is a distribution between 40 bp to 1 kb with a mean of
.about.120 bps. From bioanalyzer and gels we observed fragments
>2 kb, which would make Qubit and other mass-based quantitation
methods hard to interpret. For this reason we quantified our
libraries using qPCR based methods.
[0163] CD4.sup.+ Enrichment from Peripheral Blood:
[0164] One green-top tube of whole blood was obtained from 1 normal
volunteer three times over a 72-hour period, under a Stanford
University IRB-approved protocol. Informed consent was obtained. 5
mL of blood at each timepoint was negatively selected for CD4+
cells, using RosetteSep Human CD4.sup.+ T Cell Enrichment Cocktail
(StemCell Technology). RosetteSep cocktail was incubated with the
blood at 50 .mu.L/mL for 20 min, diluted in an equal volume of PBS
with 2% FBS, and underlayed with 15 mL Ficol-Paque Plus (GE). Blood
was centrifuged for 20 minutes at 1200.times.g without break,
negatively selected cells were removed from the density medium:
plasma interface, and cells were washed .times.2 in PBS with 2%
FBS.
[0165] FACS Sorting Peripheral Blood Leukocytes and GM Cells:
[0166] GM 12878 cells were stained with DAPI NucBlue Fixed Cell
Stain (molecular probes) and live cells were sorted using a
FACSAria (BD Biosciences) using a 100 .mu.m nozzle. One peripheral
blood sample (buffy coat) was stained with BD Bioscience antibodies
CD14-A-488 (M5E2, 1:20), CD3-PE-Cy7 (SK7, 1:20), CD4-APC-Cy7
(RPA-T4, 1:20), and CD8 (RPA-T8, 1:20) for 20 minutes in the dark
at RT. Cells were lysed using BDpharmLyse 1:10 dil in diH20 (BD)
for 15 min, centrifuged for 5 minutes, washed with PBS 2%
FBS.times.2, and resuspended in PBS with 2% FBS. 50,000
CD3.sup.+CD8.sup.+, CD3.sup.+CD4.sup.+, and CD14.sup.+ cell
populations were sorted into PBS with 10% FBS.
Data Analysis
[0167] Primary Data Processing:
[0168] Data was collected using either 34.times.8.times.34 reads
from a MiSeq or 50.times.8.times.50 reads on a HiSeq. Reads were
aligned to hg19 using BOWTIE (Langmead et al Genome Biol. 2009 10,
R25) using the parameters -X2000 and -m1. These parameters ensured
that fragments up to 2 kb were allowed to align (-X2000) and that
only unique aligning reads were collected (-m1). For all data files
duplicates were removed using Picard.
[0169] For peak calling and footprinting, the read start sites were
adjusted to represent the center of the transposon binding event.
Previous descriptions of the Tn5 transposase show that the
transposon binds as a dimer and inserts two adapters separated by 9
bps (Adey, A. et al. Genome Biol 2010 11: R119). Therefore, all
reads aligning to the + strand were offset by +4 bps, and all reads
aligning to the--strand were offset -5 bps.
[0170] ATAC-Seq Peak Calling:
[0171] We used ZINBA to call all reported ATAC-seq peaks in this
manuscript. ZINBA was run using a window size of 300 bp and an
offset 75 bp. Alignability was used to model the zero-inflated
component and the ATAC-seq read count for the background and
enriched components. Enriched regions were identified as those with
a posterior probability >0.8.
[0172] ATAC-Seq Insertion Size Enrichment Analysis within Chromatin
Annotations:
[0173] First, the distribution of paired-end sequencing fragment
sizes overlapping each chromatin state (see the ensemble.org
website) were computed. The distributions were then normalized to
the percent maximal within each state and enrichment was computed
relative to the genome-wide set of fragment sizes.
[0174] Nucleosome Positioning:
[0175] To generate the nucleosome position data track, we chose to
split reads into various bins. Reads below 100 bps were considered
nucleosome free, reads between 180 and 247 bps were considered to
be mononucleosomes, reads between 315 and 473 bps were considered
to be dinucleosomes and reads between 558 and 615 were considered
to be trinucleosomes (for determining cutoffs see FIG. 12).
Dinucleosome reads were split into two reads and Trinucleosome
reads were split into three reads. Reads were analyzed using Danpos
and Dantools using the parameters -p 1, -a 1, -d 20, -clonalcut 0.
The background used was nucleosome free reads (reads less than 100
bps), allowing an effective negative weighting of these reads. This
analysis allows calling multiple overlapping nucleosomes. Although
generating nucleosome tracks using simple insert size cutoffs may
yield false positives due to other nucleosome sized features, i.e.
enhanaceosomes, we observed that we faithfully recapitulated global
features on nucleosome position genome-wide (FIG. 2c,d main
text).
[0176] ChIP-Seq Peak Calling and Clustering:
[0177] ChIP-seq data was downloaded from the UCSC ENCODE
repository. Peaks where called using GEM (Guo et al, PLoS Comput.
Biol. 2012 8: e1002638), the parameters used where -k_min 6-k_max
20. Inputs where used as a control for peak calling. Binding events
were annotated by distance to the nearest dyad in bins of 10 bps.
Factors were then hierarchically clustered using Euclidean distance
and normalized by gene and centered by mean. (Eisen et al. Proc.
Natl. Acad. Sci. 1998 95: 14863-14868).
[0178] Footprinting Using CENTIPEDE:
[0179] The genome-wide set of motifs were obtained from the ENCODE
motif repository (at the website of broadinstitute.org). The input
for CENTIPEDE included the PWM score, conservation (PhyloP) and
ATAC-seq counts within +/-100 bp of each genomic region matching a
motif. ChIP-seq data was obtained from the UCSC ENCODE
repository.
[0180] Comparison of Transcription Factor Regulatory Networks:
[0181] Transcription factor regulatory networks were constructed by
comparing the GENCODE v14 genes with the genome-wide set of
posterior probabilities estimated by CENTIPEDE for the respective
cell-types. The extent of a transcription factor regulating each
gene was determined by taking the sum of the weighed posterior
probabilities for a given transcription factor mapping to the same
chromosome. For each mapped motif the posterior probability was
weighted based on the distance to the transcription start site for
each gene. Comparison of transcription factor regulatory networks
was computed as the correlation of each transcription factor in a
given cell type with all transcription factors in the other cell
type. The resulting correlation matrix was hierarchically clustered
using the Pearson correlation coefficient and complete linkage.
[0182] Candidate IL2 Enhancer Analysis:
[0183] ENCODE data on the UCSC genome browser was inspected to
identify putative IL2 enhancers in one or more cell types that may
be responsive to FDA approved immomodulatory drugs. We scanned the
intergenic region upstream of IL2 in hg19 for (i)
enhancer-associated histone marks (H3K4me1 and H3K27ac), (ii)
binding by one or more TFs as confirmed by ChIP-seq, and (iii) the
TF pathway can be targeted by a human therapeutic. This analysis
identified IRF4 and STAT3 binding sites in addition to the known
NFAT-responsive elements.
Results
[0184] ATAC-Seq Probes Chromatin Accessibility with Transposons
[0185] Hyperactive Tn5 transposase (Goryshin, J Biol Chem. 1998
273: 7367-7374; Adey, A. et al. Genome Biol 2010 11: R119, loaded
in vitro with adapters for high-throughput DNA sequencing, can
simultaneously fragment and tag a genome with sequencing adapters
(previously described as "tagmentation"). It was hypothesized that
transposition by purified Tn5, a prokaryotic transposase, on small
numbers of unfixed eukaryotic nuclei would interrogate regions of
accessible chromatin. An Assay for Transposase Accessible Chromatin
followed by high-throughput sequencing (ATAC-seq) is described.
ATAC-seq uses Tn5 transposase to integrate its adapter payload into
regions of accessible chromatin, whereas steric hindrance less
accessible chromatin makes transposition less probable. Therefore,
amplifiable DNA fragments suitable for high-throughput sequencing
are preferentially generated at locations of open chromatin (FIG.
1a). The entire assay and library construction can be carried out
in a simple two-step process involving Tn5 insertion and PCR. In
contrast, published DNase- and FAIRE-seq protocols for assaying
chromatin accessibility involve multi-step protocols and many
potentially loss-prone steps, such as adapter ligation, gel
purification, and crosslink reversal. For instance, a published
DNase-seq protocol calls for approximately 44 steps, and two
overnight incubations, while published FAIRE-seq protocols require
two overnight incubations carried out over at least 3 days.
Furthermore, these protocols require 1-50 million cells (FAIRE) or
50 million cells (DNase-seq), perhaps because of these complex
workflows (FIG. 1b). In comparison to established methods, ATAC-seq
enables rapid and efficient library generation because assay and
library preparation are carried out in a single enzymatic step.
[0186] Extensive analyses show that ATAC-seq provides accurate and
sensitive measure of chromatin accessibility genome-wide. ATAC-seq
was carried out on 50,000 and 500 unfixed nuclei isolated from
GM12878 lymphoblastoid cell line (ENCODE Tier 1) for comparison and
validation with chromatin accessibility data sets, including
DNase-seq and FAIRE-seq. At a locus previously highlighted by
others, (FIG. 1c), ATAC-seq has a signal-to-noise ratio similar to
DNase-seq, which was generated from approximately 3 to 5
orders-of-magnitude more cells. Peak intensities were highly
reproducible between technical replicates (R=0.98), and highly
correlated between ATAC-seq and DNase-seq (R=0.79 and R=0.83, FIG.
6), and it is noted that the majority of reads within peaks come
from intersections of DNase and ATAC-seq peaks (FIG. 7). Comparing
our data to DHSs identified in ENCODE DNase-seq data, receiver
operating characteristic (ROC) curves demonstrate a similar
sensitivity and specificity as DNase-seq (FIG. 8). It is also noted
that ATAC-seq peak intensities correlate well with markers of
active chromatin and not with transposase sequence preference
(FIGS. 9 and 10). Highly sensitive open chromatin detection is
maintained even when using 5,000 or 500 human nuclei as starting
material (FIGS. 8 and 11), although, under the conditions used,
sensitivity is diminished for smaller numbers of input material, as
can be seen in FIG. 1c.
ATAC-Seq Insert Sizes Disclose Nucleosome Positions
[0187] It was found that ATAC-seq paired-end reads produce detailed
information about nucleosome packing and positioning. The insert
size distribution of sequenced fragments from human chromatin has
clear periodicity of approximately 200 base pairs, suggesting many
fragments are protected by integer multiples of nucleosomes (FIG.
2a). This fragment size distribution also shows clear periodicity
equal to the helical pitch of DNA. By partitioning insert size
distribution according to functional classes of chromatin as
defined by previous models (Hoffman et al. Nucleic Acids Res. 2013
41: 827-841), and normalizing to the global insert distribution we
observe clear class-specific enrichments across this insert size
distribution (FIG. 2b), demonstrating that these functional states
of chromatin have an accessibility "fingerprint" that can be read
out with ATAC-seq. These differential fragmentation patterns are
consistent with the putative functional state of these classes, as
CTCF-bound regions are enriched for short fragments of DNA, while
transcription start sites are differentially depleted for mono-,
di- and tri-nucleosome associated fragments. Transcribed and
promoter flanking regions are enriched for longer multi-nucleosomal
fragments, suggesting they may represent more compacted forms of
chromatin. Finally, prior studies have shown that certain DNA
sequences are refractory to nuclease digestion and released as
large, multi-nucleosome-sized fragments; subsequent studies showed
that such fragments are condensed heterochromatin. Indeed repressed
regions were found to be depleted for short fragments and enriched
for phased multi-nucleosomal inserts, consistent with their
expected inaccessible state. These data suggest that ATAC-seq
reveals differentially accessible forms of chromatin, which have
been long hypothesized to exist in vivo.
[0188] To explore nucleosome positioning within accessible
chromatin in the GM12878 cell line, data was partitioned into reads
generated from putative nucleosome free regions of DNA, and reads
likely derived from nucleosome associated DNA (see FIG. 12). Using
a simple heuristic that positively weights nucleosome associated
fragments and negatively weights nucleosome free fragments (see
Methods), we calculated a data track used to call nucleosome
positions within regions of accessible chromatin (Chen, K. et al.
Genome Research 2013 23, 341-351). An example locus (FIG. 3a)
contains a putative bidirectional promoter with CAGE data showing
two transcription start sites (TSS) separated by .about.700 bps.
ATAC-seq reveals in fact two distinct nucleosome free regions,
separated by a single well-positioned mononucleosome (FIG. 3a).
Compared to MNase-seq, ATAC-seq data is more amenable to detecting
nucleosomes within putative regulatory regions, as the majority of
reads are concentrated within accessible regions of chromatin (FIG.
3b). By averaging signal across all active TSSs, it is noted that
nucleosome-free fragments are enriched at a canonical
nucleosome-free promoter region overlapping the TSS, while the
nucleosome signal is enriched both upstream and downstream of the
active TSS, and displays characteristic phasing of upstream and
downstream nucleosomes (FIG. 3c). Because ATAC-seq reads are
concentrated at regions of open chromatin, a strong nucleosome
signal is seen at the +1 nucleosome, which decreases at the +2, +3
and +4 nucleosomes, in contrast, MNase-seq nucleosome signal
increases at larger distances from the TSS likely due to over
digestion of more accessible nucleosomes. Additionally, MNase-seq
(4 billion reads) assays all nucleosomes, whereas reads generated
from ATAC-seq (198 million paired reads) are concentrated at
regulatory nucleosomes (FIG. 3b,c). Using the nucleosome calls,
putative distal regulatory regions and TSSs were further
partititioned into regions that were nucleosome free and regions
that were predicted to be nucleosome bound. It is noted that TSSs
were enriched for nucleosome free regions when compared to distal
elements, which tend to remain nucleosome rich (FIG. 3d). These
data suggest ATAC-seq can provide high-resolution readout of
nucleosome associated and nucleosome free regions in regulatory
elements genome wide.
ATAC-Seq Reveals Patterns of Nucleosome-TF Spacing
[0189] ATAC-seq high-resolution regulatory nucleosome maps can be
used to understand the relationship between nucleosomes and DNA
binding factors. Using ChIP-seq data, we plotted the position of a
variety of DNA binding factors with respect to the dyad of the
nearest nucleosome. Unsupervised hierarchical clustering (FIG. 3e)
revealed major classes of binding with respect to the proximal
nucleosome, including 1) a strongly nucleosome avoiding group of
factors with binding events stereotyped at .about.180 bases from
the nearest nucleosome dyad (comprising C-FOS, NFYA and IRF3), 2) a
class of factors that "nestle up" precisely to the expected end of
nucleosome DNA contacts, which notably includes chromatin looping
factors CTCF and cohesion complex subunits RAD21 and SMC3; 3) a
large class of primarily TFs that have gradations of nucleosome
avoiding or nucleosome-overlapping binding behavior, and 4) a class
whose binding sites tend to overlap nucleosome-associated DNA.
Interestingly, this final class includes chromatin remodeling
factors such as CHD1 and SIN3A as well as RNA polymerase II, which
appears to be enriched at the nucleosome boundary. The interplay
between precise nucleosome positioning and locations of DNA binding
factor immediately suggests specific hypotheses for mechanistic
studies, a potential advantage of ATAC-seq.
ATAC-Seq Footprints Infer Factor Occupancy Genome-Wide
[0190] ATAC-seq enables accurate inference of DNA binding factor
occupancy genome-wide. DNA sequences directly occupied by
DNA-binding proteins should be protected from transposition; the
resulting sequence "footprint" reveals the presence of the
DNA-binding protein at each site, analogous to DNase digestion
footprints. At a specific CTCF binding site on chromosome 1, we
observed a clear footprint (a deep notch of ATAC-seq signal),
similar to footprints seen by DNase-seq, at the precise location of
the CTCF motif that coincides with the summit of the CTCF ChIP-seq
signal in GM12878 cells (FIG. 4a). The ATAC-seq signal was averaged
over all expected locations of CTCF within the genome and observed
a well-stereotyped "footprint" (FIG. 4b). Similar results were
obtained for a variety of common TFs (for examples see FIG. 13). We
inferred the CTCF binding probability from motif consensus score,
evolutionary conservation, and ATAC-seq insertion data to generate
a posterior probability of CTCF binding at all loci (FIG. 4c)
(Pique-Regi et al. Genome Research 2011 21 447-455). Results using
ATAC-seq closely recapitulate ChIP-seq binding data in this cell
line and compare favorably to DNase-based factor occupancy
inference (see FIG. 14), suggesting that factor occupancy data can
be extracted from these ATAC-seq data allowing reconstruction of
regulatory networks.
ATAC-Seq Enables Epigenomic Analysis on Clinical Timescales
[0191] ATAC-seq is rapid, information rich, and compatible with
small numbers of cells and may serve as a powerful tool for
personalized epigenomics in the clinic. Specifically, one can
envision "personal epigenomics" as genome-scale information about
chromatin generated from an individual from a standard clinical
sample in a clinical timescale. ATAC-seq was applised to assay the
personal T-cell epigenome of a healthy volunteer via standard
serial blood draws, to demonstrate a workflow capable of generating
ATAC-seq libraries in clinical timescales. Using rapid T-cell
enrichment and sample handling protocols, the total required time
from blood draw to sequencing was approximately 275 minutes (FIG.
5a). When coupled with ongoing improvements to sequencing and
analysis turn-around times, ATAC-seq can offer the possibility of a
daily turn-around time for a personal epigenomic map. To explore
this possibility, ATAC-seq was performed on three consecutive days
via standard blood draws from a single individual (FIG. 5b). As an
exercise to consider how personal epigenomic maps may contain
personalized regulatory information, we investigated ATAC-seq
profile at the IL2 locus. IL-2 is a key cytokine that drives T-cell
growth and functions in inflammatory and autoimmune diseases.
Furthermore, distinct drugs inhibit the activities of different
transcription factors that bind putative IL2 enhancers in a
context-dependent manner. In principle, one might wish to identify
the causal transcription factor pathway in order to rationally
target inhibition without exposing the patient to drugs unlikely to
serve the therapeutic goal of IL-2 blockade. ATAC-seq shows that in
the proband's T-cells, only NFAT, but not two other drug targets,
is engaging IL2 (FIG. 5c), providing clinically relevant
information on the regulatory state of this individual.
[0192] Using ATAC-seq footprints the occupancy profiles of 89
transcription factors in proband T-cells were generated, enabling
systematic reconstruction of regulatory networks. With this
personalized regulatory map, we compared the genomic distribution
of the same 89 transcription factors between GM12878 and proband
CD4+ T-cells. Transcription factors that exhibit large variation in
distribution between T-cells and B-cells are enriched for T-cell
specific factors (FIG. 5d). This analysis shows NFAT is
differentially regulating, while canonical CTCF occupancy is highly
correlated within these two cell types (FIG. 5d). Supporting this
interpretation, it is noted that specific loci where NFAT is
localized nearby to known T-cell specific genes such as CD28 and a
novel lincRNA RP11-229C3.2 (FIG. 15). Additionally, ATAC-seq of
CD4.sup.+ and CD8.sup.+ T-cells, and monocytes isolated by
fluorescence-activated cell sorting (FACS) from a single blood draw
created an interpretative framework for the personal epigenomes,
and demonstrated that ATAC-seq is compatible with cellular
enrichment using surface markers (FIG. 16). Separately,
allele-specific chromatin accessibility has been shown to be
particularly relevant to our understanding of human disease. As a
proof of principle we also used ATAC-seq to identify candidate
allele-specific open chromatin regions within the GM12878 cell line
(FIG. 17). These results demonstrate the feasibility of generating
detailed personalized gene regulatory networks from clinical
samples, opening the door for future diagnostic applications.
[0193] Epigenomic studies of chromatin accessibility have yielded
tremendous biological insights, but are currently limited in
application by their complex workflows and large cell number
requirements. While, improvements of existing methods may enable
them to reach the similar performance, ATAC-seq in certain cases
can offer substantial advantages over existing technologies due to
its speed, simplicity, and low input cell number requirement.
ATAC-seq is an information rich assay, allowing simultaneous
interrogation of factor occupancy, nucleosome positions in
regulatory sites, and chromatin accessibility genome-wide. These
insights are derived from both the position of insertion and the
distribution of insert lengths captured during the transposition
reaction. While extant methods such as DNase- and MNase-seq can
provide some subsets of the information in ATAC-seq, they each
require separate assays with large cell numbers, which increases
the time, cost, and limits applicability to many systems. ATAC-seq
also provides insert size "fingerprints" of biologically relevant
genomic regions, suggesting that it capture information on
chromatin compaction. ATAC-seq may have broad applicability,
significantly add to the genomics toolkit, and improve our
understanding of gene regulation, particularly when integrated with
other powerful rare cell techniques, such as FACS, laser capture
microdissection (LCM) and recent advancements in RNA-seq.
[0194] ATAC-seq may be used to generate "personal epigenomic"
profiles on a timescale compatible with clinical decision-making.
Optimized procedures can transform a clinical blood sample to
completed sequencing library in 275 minutes. The reduced input
requirements and rapid workflows, when coupled with the recent
introduction of rapid-turnaround high-throughput sequencing
instruments, such as the MiSeq and HiSeq2500, should enable
investigation of personalized epigenetic landscapes of selected
tissues both in the lab and the clinic. ATAC-seq is compatible with
FACS, enabling studies on carefully sorted and rare subpopulations
from primary tissues. Cellular subpopulations selected at different
points in development and aging, and human diseases, including
cancer, autoimmunity, and neuropsychiatric disorders are viable
applications.
Example 2. Single-Cell ATAC-Seq
[0195] Single-cell chromatin accessibility datasets were obtained
using the ATAC-seq protocol. To ensure that the ratio of
transposase molecules to open chromatin sites was kept nearly
constant, the single-cell ATAC-seq assay was carried out by
manipulating individual cells after an initial transposition
reaction.
Transposases can Serve as an Open-Chromatin Stain
[0196] It was observed that after in vitro insertion of sequencing
adapter, the Tn5 transposase remained tightly bound to the DNA and
formed a high-affinity macromolecular complex that prevented
dissociation of the generated ATAC-seq DNA fragments. To support
this observation, Tn5 transposase was loaded with fluorescently
labeled DNA adapters, and allowed for visualization of regions of
open chromatin within the nucleus of individual cells (FIG. 18).
Additional electrophoretic mobility shift assays also indicated
that the transposase remained associated to DNA after
transposition.
Single-Cell ATAC-Seq Provides Unique Reads Characteristic of
Chromosomal DNA
[0197] Since this fluorescence signal localized to the nucleus and
was detectable even after transposition, the single-cell ATAC-seq
experiment was performed by keeping the transposed fragments in the
nucleus during subsequent sorting and cell selection steps. A group
of cells were permeabilized, and the chromosomal DNA was transposed
with Tn5 transposase. The cells were kept under conditions that
prevented the resulting ATAC-seq fragments from leaving the cell
nucleus, (i.e. divalent cation was not chelated), and the
individual cells were sorted into independent PCR reactions for
library preparation, as described above. This workflow
significantly simplified the workflow for single-cell analysis and
provided two additional advantages. First, this abrogated any
effect of the sorting process on the chromatin state because
transposition preceded sorting. Second, it provided more robust
ATAC-seq signal, as cells were sorted directly into a PCR master
mix and amplified. Using this workflow, .about.2,000-5,000 unique
ATAC-seq reads per cell were generated. These reads were enriched
for known open chromatin sites in GM12878 cells (FIG. 19) and
displayed characteristic periodic enrichments indicative of
nucleosomes (FIG. 20).
Example 3. Quality Control
[0198] Assay for Transposase Accessible Chromatin (ATAC-seq) has
been shown to be compatible with many methods for cell collection
and has also worked effectively across many cell types and species.
However, the following protocol has been optimized for human
lymphoblastoid cells. Minor variations (i.e. cell number,
centrifugation speeds, and lysis conditions) may optimized for
particular applications.
[0199] I. Cell Preparation [0200] 1. Harvest cells (no fixation),
protocol to be defined by the user. [0201] 2. Spin down 50,000
cells at 500.times.g for 5 min, 4.degree. C. [0202] 3. Wash once
with 50 .mu.L of cold 1.times.PBS buffer. Spin down at 500.times.g
for 5 min, 4.degree. C. [0203] 4. Gently pipette to resuspend the
cell pellet in 50 .mu.L of cold lysis buffer (10 mM Tris-HCl, pH
7.4, 10 mM NaCl, 3 mM MgCl.sub.2, 0.1% IGEPAL CA-630). Spin down
immediately at 500.times.g for 10 min, 4.degree. C. [0204] 5.
Discard the supernatant, and immediately continue to transposition
reaction.
[0205] II. Transposition Reaction and Purification [0206] 1. Make
sure the cell pellet is set on ice. [0207] 2. To make the
transposition reaction mix, combine the following: [0208] 25 .mu.L
2.times.TD Buffer (Illumina Cat #FC-121-1030) [0209] 2.5 .mu.L Tn5
Transposes (Illumina Cat #FC-121-1030) [0210] 22.5 .mu.L Nuclease
Free H.sub.2O [0211] 50 .mu.l Total [0212] 3. Gently pipette to
resuspend nuclei in the transposition reaction mix. [0213] 4.
Incubate the transposition reaction at 37.degree. C. for 30 min.
[0214] 5. Immediately following transposition, purify using a
Qiagen MinElute Kit. [0215] 6. Elute transposed DNA in 10 .mu.L
Elution Buffer (10 mM Tris buffer, pH 8). [0216] 7. Purified DNA
can be stored at -20.degree. C.
[0217] III. PCR Amplification [0218] 1. To amplify transposed DNA
fragments, combine the following in a PCR tube: [0219] 10 .mu.L
Transposed DNA [0220] 9.7 .mu.L Nuclease Free H.sub.2O [0221] 2.5
.mu.L 25 .mu.M Customized Nextera PCR Primer 1* [0222] 2.5 .mu.L 25
.mu.M Customized Nextera PCR Primer 2* [Barcode]* Complete list of
primers are shown above. [0223] 0.3 .mu.L 100.times.SYBR Green I**
(Invitrogen Cat #S-7563) **10,000.times.SYBR Green I is diluted in
10 mM Tris buffer, pH 8 to make a 100.times. working solution.
[0224] 25 .mu.L NEBNext High-Fidelity 2.times.PCR Master Mix (New
England Labs Cat #M0541) [0225] 50 .mu.L Total [0226] 2. Cycle as
follows: [0227] (1) 72.degree. C., 5 min [0228] (2) 98.degree. C.,
30 sec [0229] (3) 98.degree. C., 10 sec [0230] (4) 63.degree. C.,
30 sec [0231] (5) 72.degree. C., 1 min [0232] (6) Repeat steps 3-5,
4.times. [0233] (7) Hold at 4.degree. C. [0234] 3. In order to
reduce GC and size bias in PCR, the PCR reaction is monitored using
qPCR to stop amplification prior to saturation. To run a qPCR side
reaction, combine the following: [0235] 5 .mu.L 5 cycles PCR
amplified DNA [0236] 4.44 .mu.L Nuclease Free H.sub.2O [0237] 0.25
.mu.L 25 .mu.M Customized Nextera PCR Primer 1* [0238] 0.25 .mu.L
25 .mu.M Customized Nextera PCR Primer 2* * Complete list of
primers available in Section VI of this protocol [0239] 0.06 .mu.L
100.times.SYBR Green I [0240] 5 .mu.L NEBNext High-Fidelity
2.times.PCR Master Mix [0241] 15 .mu.L Total [0242] 4. qPCR cycle
as follows: [0243] (1) 98.degree. C., 30 sec [0244] (2) 98.degree.
C., 10 sec [0245] (3) 63.degree. C., 30 sec [0246] (4) 72.degree.
C., 1 min [0247] (5) Repeat steps 2-4, 19.times. [0248] (6) Hold at
4.degree. C. [0249] 5. The additional number of cycles needed for
the remaining 45 .mu.L PCR reaction is determined as following:
[0250] (1) Plot linear Rn vs. Cycle [0251] (2) Set 5000 RF
threshold [0252] (3) Calculate the # of cycle that is corresponded
to 1/4 of maximum fluorescent intensity [0253] If the # of cycle to
be added lies in between two cycles, the # is determined by taking
the smaller integer as the # of cycle to be added (i.e., blue and
pink samples) [0254] If two samples have similar Ct values but
differs in the fluorescent intensities, calculate the # of cycle
using the sample with lower fluorescent intensity (i.e., red and
blue samples) [0255] 6. Run the remaining 45 .mu.L PCR reaction to
the correct # of cycle. Cycle as follows: [0256] (1) 98.degree. C.,
30 sec (2) 98.degree. C., 10 sec (3) [0257] 63.degree. C., 30 sec
(4) 72.degree. C., 1 min [0258] (5) Repeat steps 2-4, x times
[0259] (6) Hold at [0260] 4.degree. C. [0261] 7. Purify amplified
library using Qiagen PCR Cleanup Kit. Elute the purified library in
20 .mu.L Elution Buffer (10 mM Tris Buffer, pH 8). Be sure to dry
the column before adding elution buffer.
[0262] IV. Library QC using Gel Electrophoresis [0263] 1. Dilute
1:20 100 bp NEB DNA ladder with 10 mM Tris Buffer, pH 8. [0264] 2.
Add 0.6 .mu.L 10.times.SYBR Green I to every 5 .mu.L of diluted
ladder. [0265] 3. Mix 1:1 of the diluted ladder with 2.times.DNA
loading dye. [0266] 4. Mix 1:1 of amplified library with
2.times.DNA loading dye. [0267] 5. Run amplified library on 5%
Bio-Rad Mini-Protean TBE Precast Gel (stored at 4.degree. C.). Load
5 .mu.L diluted ladder/DNA loading dye mixture. Load 10 .mu.L
amplified library/DNA loading dye mixture. [0268] 6. Run at
.about.100 mV for 45 min. [0269] 7. SYBR Green I dye has an
excitation maximum at .about.488 nm and has an emission maximum at
.about.520 nm. DNA stained with SYBR Green I dye can be visualized
using a blue-light source or imaging systems equipped with laser
that emits at 488 nm. We typically use Typhoon TRIO Variable Mode
Imager from Amersham Biosciences for visualization. Images are best
obtained by digitizing at 100 microns pixel size resolution with a
520 nm band-pass emission filter to screen out reflected and
scattered excitation light and background fluorescence.
[0270] V. Library Quantitation
[0271] We use qPCR based methods to quantify our ATAC-seq
libraries. We have found that other methods, such as Bioanalyzer
and Qubit, can give misleading and inaccurate results due to the
large distribution of insert sizes. We recommend quantifying
libraries using the KAPA Library Quant Kit for Illumina Sequencing
Platforms (KAPABiosystems).
[0272] Although the foregoing embodiments have been described in
some detail by way of illustration and example for purposes of
clarity of understanding, it is readily apparent to those of
ordinary skill in the art in light of the above teachings that
certain changes and modifications can be made thereto without
departing from the spirit or scope of the appended claims.
Sequence CWU 1
1
25150DNAArtificial Sequencesynthetic polynucleotide 1aatgatacgg
cgaccaccga gatctacact cgtcggcagc gtcagatgtg 50253DNAArtificial
sequencesynthetic polynucleotide 2caagcagaag acggcatacg agattcgcct
tagtctcgtg ggctcggaga tgt 53353DNAArtificial sequencesynthetic
polynucleotide 3caagcagaag acggcatacg agatctagta cggtctcgtg
ggctcggaga tgt 53453DNAArtificial sequencesynthetic polynucleotide
4caagcagaag acggcatacg agatttctgc ctgtctcgtg ggctcggaga tgt
53553DNAArtificial sequencesynthetic polynucleotide 5caagcagaag
acggcatacg agatgctcag gagtctcgtg ggctcggaga tgt 53653DNAArtificial
sequencesynthetic polynucleotide 6caagcagaag acggcatacg agataggagt
ccgtctcgtg ggctcggaga tgt 53753DNAArtificial sequencesynthetic
polynucleotide 7caagcagaag acggcatacg agatcatgcc tagtctcgtg
ggctcggaga tgt 53853DNAArtificial sequencesynthetic polynucleotide
8caagcagaag acggcatacg agatgtagag aggtctcgtg ggctcggaga tgt
53953DNAArtificial sequencesynthetic polynucleotide 9caagcagaag
acggcatacg agatcctctc tggtctcgtg ggctcggaga tgt 531053DNAArtificial
sequencesynthetic polynucleotide 10caagcagaag acggcatacg agatagcgta
gcgtctcgtg ggctcggaga tgt 531153DNAArtificial sequencesynthetic
polynucleotide 11caagcagaag acggcatacg agatcagcct cggtctcgtg
ggctcggaga tgt 531253DNAArtificial sequencesynthetic polynucleotide
12caagcagaag acggcatacg agattgcctc ttgtctcgtg ggctcggaga tgt
531353DNAArtificial sequencesynthetic polynucleotide 13caagcagaag
acggcatacg agattcctct acgtctcgtg ggctcggaga tgt 531453DNAArtificial
sequencesynthetic polynucleotide 14caagcagaag acggcatacg agatatcacg
acgtctcgtg ggctcggaga tgt 531553DNAArtificial sequencesynthetic
polynucleotide 15caagcagaag acggcatacg agatacagtg gtgtctcgtg
ggctcggaga tgt 531653DNAArtificial sequencesynthetic polynucleotide
16caagcagaag acggcatacg agatcagatc cagtctcgtg ggctcggaga tgt
531753DNAArtificial sequencesynthetic polynucleotide 17caagcagaag
acggcatacg agatacaaac gggtctcgtg ggctcggaga tgt 531853DNAArtificial
sequencesynthetic polynucleotide 18caagcagaag acggcatacg agatacccag
cagtctcgtg ggctcggaga tgt 531953DNAArtificial sequencesynthetic
polynucleotide 19caagcagaag acggcatacg agataacccc tcgtctcgtg
ggctcggaga tgt 532053DNAArtificial sequencesynthetic polynucleotide
20caagcagaag acggcatacg agatcccaac ctgtctcgtg ggctcggaga tgt
532153DNAArtificial sequencesynthetic polynucleotide 21caagcagaag
acggcatacg agatcaccac acgtctcgtg ggctcggaga tgt 532253DNAArtificial
sequencesynthetic polynucleotide 22caagcagaag acggcatacg agatgaaacc
cagtctcgtg ggctcggaga tgt 532353DNAArtificial sequencesynthetic
polynucleotide 23caagcagaag acggcatacg agattgtgac cagtctcgtg
ggctcggaga tgt 532453DNAArtificial sequencesynthetic polynucleotide
24caagcagaag acggcatacg agatagggtc aagtctcgtg ggctcggaga tgt
532553DNAArtificial sequencesynthetic polynucleotide 25caagcagaag
acggcatacg agataggagt gggtctcgtg ggctcggaga tgt 53
* * * * *