U.S. patent application number 11/974878 was filed with the patent office on 2008-05-15 for functional and hyperfunctional sirna directed against bcl-2.
This patent application is currently assigned to DHARMACON INC.. Invention is credited to Anastasia Khvorova, Devin Leake, William Marshall, Angela Reynolds, Stephen Scaringe.
Application Number | 20080114162 11/974878 |
Document ID | / |
Family ID | 32329096 |
Filed Date | 2008-05-15 |
United States Patent
Application |
20080114162 |
Kind Code |
A1 |
Khvorova; Anastasia ; et
al. |
May 15, 2008 |
Functional and hyperfunctional siRNA directed against Bcl-2
Abstract
Efficient sequence specific gene silencing is possible through
the use of siRNA technology. By selecting particular siRNAs by
rationale design, one can maximize the generation of an effective
gene silencing reagent, as well as methods for silencing Bcl-2.
Inventors: |
Khvorova; Anastasia;
(Boulder, CO) ; Reynolds; Angela; (Conifer,
CO) ; Leake; Devin; (Denver, CO) ; Marshall;
William; (Boulder, CO) ; Scaringe; Stephen;
(Lafayette, CO) |
Correspondence
Address: |
KALOW & SPRINGUT LLP
488 MADISON AVENUE
19TH FLOOR
NEW YORK
NY
10022
US
|
Assignee: |
DHARMACON INC.
Lafayette
CO
|
Family ID: |
32329096 |
Appl. No.: |
11/974878 |
Filed: |
October 16, 2007 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11083784 |
Mar 18, 2005 |
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11974878 |
Oct 16, 2007 |
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10714333 |
Nov 14, 2003 |
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11083784 |
Mar 18, 2005 |
|
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60426137 |
Nov 14, 2002 |
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60502050 |
Sep 10, 2003 |
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Current U.S.
Class: |
536/24.5 |
Current CPC
Class: |
C12N 2320/11 20130101;
C12N 15/1048 20130101; C12Y 502/01008 20130101; A61P 21/00
20180101; C12N 15/1137 20130101; A61K 31/713 20130101; C12N 15/1136
20130101; C12N 15/111 20130101; C12N 15/113 20130101; C12N 15/1135
20130101; A61P 25/28 20180101; C12Y 113/12007 20130101; C12N
2310/14 20130101; G16B 20/00 20190201; A61P 13/12 20180101; A61P
3/10 20180101; A61P 35/02 20180101; A61P 37/02 20180101; C12N
2320/10 20130101; C12N 15/1138 20130101; A61P 35/00 20180101 |
Class at
Publication: |
536/024.5 |
International
Class: |
C07H 21/02 20060101
C07H021/02 |
Claims
1. An siRNA molecule effective at silencing Bcl-2 expression,
wherein said molecule comprises a sense region and an antisense
region, wherein said sense region and said antisense region
together form a duplex region comprising 19-30 base pairs and said
antisense region comprises a sequence that is the reverse
complement of SEQ. ID NO. 305.
2. The siRNA of claim 1, wherein said antisense region and said
sense region are each 19-25 nucleotides in length.
3. The siRNA of claim 1, wherein said antisense region and said
sense region are each 19 nucleotides in length.
4. The siRNA of claim 1, wherein said antisense region is 100%
complementary to a target Bcl-2 RNA.
5. The siRNA molecule of claim 1, wherein said siRNA molecule
comprises at least one overhang region, wherein said overhang
region comprises six or fewer nucleotides.
6. The siRNA molecule of claim 1 wherein said siRNA molecule
comprises no overhang regions.
7. The siRNA molecule of claim 2 wherein said siRNA molecule
comprises at least one overhang region, wherein said overhang
region comprises six or fewer nucleotides.
8. The siRNA molecule of claim 2 wherein said siRNA molecule
comprises no overhang regions.
9. The siRNA molecule of claim 3 wherein said siRNA molecule
comprises at least one overhang region, wherein said overhang
region comprises six or fewer nucleotides.
10. The siRNA molecule of claim 3 wherein said siRNA molecule
comprises no overhang regions.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of the filing dates of
U.S. patent application Ser. No. 11/083,784, filed Mar. 18, 2005
entitled, "Functional and Hyperfunctional siRNA Directed Against
Bcl-2," U.S. patent application Ser. No. 10/714,333, filed Nov. 14,
2003 entitled, "Functional and Hyperfunctional siRNA," U.S.
Provisional Application Ser. No. 60/426,137, filed Nov. 14, 2002,
entitled "Combinatorial Pooling Approach for siRNA Induced Gene
Silencing and Methods for Selecting siRNA," and U.S. Provisional
Application Ser. No. 60/502,050, filed Sep. 10, 2003, entitled
"Methods for Selecting siRNA," the entire disclosures of which are
hereby incorporated by reference into the present disclosure.
SEQUENCE LISTING
[0002] The sequence listing for this application has been submitted
in accordance with 37 CFR .sctn. 1.52(e) and 37 CFR .sctn. 1.821 on
CD-ROM in lieu of paper on a disk containing the sequence listing
file entitled "DHARMA.sub.--0100-US24_CRF.txt" created Oct. 16,
2007, 80 kb. Applicants hereby incorporate by reference the
sequence listing provided on CD-ROM in lieu of paper into the
instant specification.
FIELD OF INVENTION
[0003] The present invention relates to RNA interference
("RNAi").
BACKGROUND OF THE INVENTION
[0004] Relatively recently, researchers observed that double
stranded RNA ("dsRNA") could be used to inhibit protein expression.
This ability to silence a gene has broad potential for treating
human diseases, and many researchers and commercial entities are
currently investing considerable resources in developing therapies
based on this technology.
[0005] Double stranded RNA induced gene silencing can occur on at
least three different levels: (i) transcription inactivation, which
refers to RNA guided DNA or histone methylation; (ii) siRNA induced
mRNA degradation; and (iii) mRNA induced transcriptional
attenuation.
[0006] It is generally considered that the major mechanism of RNA
induced silencing (RNA interference, or RNAi) in mammalian cells is
mRNA degradation. Initial attempts to use RNAi in mammalian cells
focused on the use of long strands of dsRNA. However, these
attempts to induce RNAi met with limited success, due in part to
the induction of the interferon response, which results in a
general, as opposed to a target-specific, inhibition of protein
synthesis. Thus, long dsRNA is not a viable option for RNAi in
mammalian systems.
[0007] More recently it has been shown that when short (18-30 bp)
RNA duplexes are introduced into mammalian cells in culture,
sequence-specific inhibition of target mRNA can be realized without
inducing an interferon response. Certain of these short dsRNAs,
referred to as small inhibitory RNAs ("siRNAs"), can act
catalytically at sub-molar concentrations to cleave greater than
95% of the target mRNA in the cell. A description of the mechanisms
for siRNA activity, as well as some of its applications are
described in Provost et al., Ribonuclease Activity and RNA Binding
of Recombinant Human Dicer, E.M.B.O. J., 2002 Nov. 1; 21(21):
5864-5874; Tabara et al., The dsRNA Binding Protein RDE-4 Interacts
with RDE-1, DCR-1 and a DexH-box Helicase to Direct RNAi in C.
elegans, Cell 2002, June 28; 109(7):861-71; Ketting et al., Dicer
Functions in RNA Interference and in Synthesis of Small RNA
Involved in Developmental Timing in C. elegans; Martinez et al.,
Single-Stranded Antisense siRNAs Guide Target RNA Cleavage in RNAi,
Cell 2002, September. 6; 110(5):563; Hutvagner & Zamore, A
microRNA in a multiple-turnover RNAi enzyme complex, Science 2002,
297:2056.
[0008] From a mechanistic perspective, introduction of long double
stranded RNA into plants and invertebrate cells is broken down into
siRNA by a Type III endonuclease known as Dicer. Sharp, RNA
interference--2001, Genes Dev. 2001, 15:485. Dicer, a
ribonuclease-III-like enzyme, processes the dsRNA into 19-23 base
pair short interfering RNAs with characteristic two base 3'
overhangs. Bernstein, Caudy, Hammond, & Hannon, Role for a
bidentate ribonuclease in the initiation step of RNA interference,
Nature 2001, 409:363. The siRNAs are then incorporated into an
RNA-induced silencing complex (RISC) where one or more helicases
unwind the siRNA duplex, enabling the complementary antisense
strand to guide target recognition. Nykanen, Haley, & Zamore,
ATP requirements and small interfering RNA structure in the RNA
interference pathway, Cell 2001, 107:309. Upon binding to the
appropriate target mRNA, one or more endonucleases within the RISC
cleaves the target to induce silencing. Elbashir, Lendeckel, &
Tuschl, RNA interference is mediated by 21- and 22-nucleotide RNAs,
Genes Dev 2001, 15:188, FIG. 1.
[0009] The interference effect can be long lasting and may be
detectable after many cell divisions. Moreover, RNAi exhibits
sequence specificity. Kisielow, M. et al. (2002) Isoform-specific
knockdown and expression of adaptor protein ShcA using small
interfering RNA, J. of Biochemistry 363: 1-5. Thus, the RNAi
machinery can specifically knock down one type of transcript, while
not affecting closely related mRNA. These properties make siRNA a
potentially valuable tool for inhibiting gene expression and
studying gene function and drug target validation. Moreover, siRNAs
are potentially useful as therapeutic agents against: (1) diseases
that are caused by over-expression or misexpression of genes; and
(2) diseases brought about by expression of genes that contain
mutations.
[0010] Successful siRNA-dependent gene silencing depends on a
number of factors. One of the most contentious issues in RNAi is
the question of the necessity of siRNA design, i.e., considering
the sequence of the siRNA used. Early work in C. elegans and plants
circumvented the issue of design by introducing long dsRNA (see,
for instance, Fire, A. et al. (1998) Nature 391:806-811). In this
primitive organism, long dsRNA molecules are cleaved into siRNA by
Dicer, thus generating a diverse population of duplexes that can
potentially cover the entire transcript. While some fraction of
these molecules are non-functional (i.e. induce little or no
silencing) one or more have the potential to be highly functional,
thereby silencing the gene of interest and alleviating the need for
siRNA design. Unfortunately, due to the interferon response, this
same approach is unavailable for mammalian systems. While this
effect can be circumvented by bypassing the Dicer cleavage step and
directly introducing siRNA, this tactic carries with it the risk
that the chosen siRNA sequence may be non-functional or
semi-functional.
[0011] A number of researches have expressed the view that siRNA
design is not a crucial element of RNAi. On the other hand, others
in the field have begun to explore the possibility that RNAi can be
made more efficient by paying attention to the design of the siRNA.
Unfortunately, none of the reported methods have provided a
satisfactory scheme for reliably selecting siRNA with acceptable
levels of functionality. Accordingly, there is a need to develop
rational criteria by which to select siRNA with an acceptable level
of functionality, and to identify siRNA that have this improved
level of functionality, as well as to identify siRNAs that are
hyperfunctional.
SUMMARY OF THE INVENTION
[0012] The present invention is directed to increasing the
efficiency of RNAi, particularly in mammalian systems. Accordingly,
the present invention provides kits, siRNAs and methods for
increasing siRNA efficacy.
[0013] According to one embodiment, the present invention provides
a kit for gene silencing, wherein said kit is comprised of a pool
of at least two siRNA duplexes, each of which is comprised of a
sequence that is complementary to a portion of the sequence of one
or more target messenger RNA.
[0014] According to a second embodiment, the present invention
provides a method for optimizing RNA interference by using one or
more siRNAs that are optimized according to a formula (or
algorithm) selected from: Relative functionality of
siRNA=-(GC/3)+(AU.sub.15-19)-(Tm.sub.20.degree.
C.)*3-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.sub.3)+(U.sub.10)+(A.sub.14-
)-(U.sub.5)-(A.sub.11) Formula I Relative functionality of
siRNA=-(GC/3)-(AU.sub.15-19)*3-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.su-
b.3) Formula II Relative functionality of
siRNA=-(GC/3)+(AU.sub.15-19)-(Tm.sub.20.degree. C.)*3 Formula III
Relative functionality of
siRNA=-GC/2+(AU.sub.15-19)/2-(Tm.sub.20.degree.
C.)*2-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.sub.3)+(U.sub.10)+(A.sub.14-
)-(U.sub.5)-(A.sub.11) Formula IV Relative functionality of
siRNA=-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.sub.3)+(U.sub.10)+(A.sub.1-
4)-(U.sub.5)-(A.sub.11) Formula V Relative functionality of
siRNA=-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.sub.3) Formula VI
Relative functionality of
siRNA=-(GC/2)+(AU.sub.15-19)/2-(Tm.sub.20.degree.
C.)*1-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*3+(A.sub.3)*3+(U.sub.10)/2+(A.su-
b.14)/2-(U.sub.5)/2-(A.sub.11)/2 Formula VII wherein in Formulas
I-VII:
[0015] Tm.sub.20.degree. C.=1 if the Tm is greater than 20.degree.
C.;
[0016] A.sub.19=1 if A is the base at position 19 on the sense
strand, otherwise its value is 0;
[0017] AU.sub.15-19=0-5 depending on the number of A or U bases on
the sense strand at [0018] positions 15-19;
[0019] G.sub.13=1 if G is the base at position 13 on the sense
strand, otherwise its value is 0;
[0020] C.sub.19=1 if C is the base at position 19 of the sense
strand, otherwise its value is 0;
[0021] GC=the number of G and C bases in the entire sense
strand;
[0022] A.sub.3=1 if A is the base at position 3 on the sense
strand, otherwise its value is 0;
[0023] A.sub.11=1 if A is the base at position 11 on the sense
strand, otherwise its value is 0;
[0024] A.sub.14=1 if A is the base at position 14 on the sense
strand, otherwise its value is 0;
[0025] U.sub.10=1 if U is the base at position 10 on the sense
strand, otherwise its value is 0;
[0026] U.sub.5=1 if U is the base at position 5 on the sense
strand, otherwise its value is 0; or
Formula VIII Relative functionality of siRNA=
(-14)*G.sub.13-13*A.sub.1-12*U.sub.7-11*U.sub.2-10*A.sub.11-10*U.sub.4-10-
*C.sub.3-10*C.sub.5-10*C.sub.6-9*A.sub.10-9*U.sub.9-9*C.sub.18-8*G.sub.10--
7*U.sub.1-7*U.sub.16-7*C.sub.17-7*C.sub.19+7*U.sub.17+8*A.sub.2+8*A.sub.4+-
8*A.sub.5+8*C.sub.4+9*G.sub.8+10*A.sub.7+10*U.sub.18+1*A.sub.19+11*C.sub.9-
+15*G.sub.1+18*A.sub.3+19*U.sub.10-Tm-3*(GC.sub.total)-6*(GC.sub.15-19)-30-
*X; and Formula IX Relative functionality of siRNA=
(14.1)*A.sub.3+(14.9)*A.sub.6+(17.6)*A.sub.13+(24.7)*A.sub.19+(14.2)*U.su-
b.10+(10.5)*C.sub.9+(23.9)*G.sub.1+(16.3)*G.sub.2+(-12.3)*A.sub.11+(-19.3)-
*U.sub.1+(-12.1)*U.sub.2+(-11)*U.sub.3+(-15.2)*U.sub.15+(-11.3)*U.sub.16+(-
-11.8)*C.sub.3+(-17.4)*C.sub.6+(-10.5)
*C.sub.7+(-13.7)*G.sub.13+(-25.9)*G.sub.19-Tm-3*(GC.sub.total)-6*(GC.sub.-
15-19)-30*X wherein [0027] A.sub.1=1 if A is the base at position 1
of the sense strand, otherwise its value is 0; [0028] A.sub.2=1 if
A is the base at position 2 of the sense strand, otherwise its
value is 0; [0029] A.sub.3=1 if A is the base at position 3 of the
sense strand, otherwise its value is 0; [0030] A.sub.4=1 if A is
the base at position 4 of the sense strand, otherwise its value is
0; [0031] A.sub.5=1 if A is the base at position 5 of the sense
strand, otherwise its value is 0; [0032] A.sub.6=1 if A is the base
at position 6 of the sense strand, otherwise its value is 0; [0033]
A.sub.7=1 if A is the base at position 7 of the sense strand,
otherwise its value is 0; [0034] A.sub.10=1 if A is the base at
position 10 of the sense strand, otherwise its value is 0; [0035]
A.sub.11=1 if A is the base at position 11 of the sense strand,
otherwise its value is 0; [0036] A.sub.13=1 if A is the base at
position 13 of the sense strand, otherwise its value is 0; [0037]
A.sub.19=1 if A is the base at position 19 of the sense strand,
otherwise if another base is present or the sense strand is only 18
base pairs in length, its value is 0; [0038] C.sub.3=1 if C is the
base at position 3 of the sense strand, otherwise its value is 0;
[0039] C.sub.4=1 if C is the base at position 4 of the sense
strand, otherwise its value is 0; [0040] C.sub.5=1 if C is the base
at position 5 of the sense strand, otherwise its value is 0; [0041]
C.sub.6=1 if C is the base at position 6 of the sense strand,
otherwise its value is 0; [0042] C.sub.7=1 if C is the base at
position 7 of the sense strand, otherwise its value is 0; [0043]
C.sub.9=1 if C is the base at position 9 of the sense strand,
otherwise its value is 0; [0044] C.sub.17=1 if C is the base at
position 17 of the sense strand, otherwise its value is 0; [0045]
C.sub.18=1 if C is the base at position 18 of the sense strand,
otherwise its value is 0; [0046] C.sub.19=1 if C is the base at
position 19 of the sense strand, otherwise if another base is
present or the sense strand is only 18 base pairs in length, its
value is 0; [0047] G.sub.1=1 if G is the base at position 1 on the
sense strand, otherwise its value is 0; [0048] G.sub.2=1 if G is
the base at position 2 of the sense strand, otherwise its value is
0; [0049] G.sub.8=1 if G is the base at position 8 on the sense
strand, otherwise its value is 0; [0050] G.sub.10=1 if G is the
base at position 10 on the sense strand, otherwise its value is 0;
[0051] G.sub.13=1 if G is the base at position 13 on the sense
strand, otherwise its value is 0; [0052] G.sub.19=1 if G is the
base at position 19 of the sense strand, otherwise if another base
is present or the sense strand is only 18 base pairs in length, its
value is 0; [0053] U.sub.1=1 if U is the base at position 1 on the
sense strand, otherwise its value is 0; [0054] U.sub.2=1 if U is
the base at position 2 on the sense strand, otherwise its value is
0; [0055] U.sub.3=1 if U is the base at position 3 on the sense
strand, otherwise its value is 0; [0056] U.sub.4=1 if U is the base
at position 4 on the sense strand, otherwise its value is 0; [0057]
U.sub.7=1 if U is the base at position 7 on the sense strand,
otherwise its value is 0; [0058] U.sub.9=1 if U is the base at
position 9 on the sense strand, otherwise its value is 0; [0059]
U.sub.10=1 if U is the base at position 10 on the sense strand,
otherwise its value is 0; [0060] U.sub.15=1 if U is the base at
position 15 on the sense strand, otherwise its value is 0; [0061]
U.sub.16=1 if U is the base at position 16 on the sense strand,
otherwise its value is 0; [0062] U.sub.17=1 if U is the base at
position 17 on the sense strand, otherwise its value is 0; [0063]
U.sub.18=1 if U is the base at position 18 on the sense strand,
otherwise its value is 0; [0064] GC.sub.15-19=the number of G and C
bases within positions 15-19 of the sense strand or within
positions 15-18 if the sense strand is only 18 base pairs in
length; [0065] GC.sub.total=the number of G and C bases in the
sense strand; [0066] Tm=100 if the targeting site contains an
inverted repeat longer than 4 base pairs, otherwise its value is 0;
and [0067] X=the number of times that the same nucleotide repeats
four or more times in a row.
[0068] According to a third embodiment, the present invention is
directed to a kit comprised of at least one siRNA that contains a
sequence that is optimized according to one of the formulas above.
Preferably the kit contains at least two optimized siRNA, each of
which comprises a duplex, wherein one strand of each duplex
comprises at least eighteen contiguous bases that are complementary
to a region of a target messenger RNA. For mammalian systems, the
siRNA preferably comprises between 18 and 30 nucleotide base
pairs.
[0069] The ability to use the above algorithms, which are not
sequence or species specific, allows for the cost-effective
selection of optimized siRNAs for specific target sequences.
Accordingly, there will be both greater efficiency and reliability
in the use of siRNA technologies.
[0070] According to a fourth embodiment, the present invention
provides a method for developing an siRNA algorithm for selecting
functional and hyperfunctional siRNAs for a given sequence. The
method comprises: [0071] (a) selecting a set of siRNAs; [0072] (b)
measuring the gene silencing ability of each siRNA from said set;
[0073] (c) determining the relative functionality of each siRNA;
[0074] (d) determining the amount of improved functionality by the
presence or absence of at least one variable selected from the
group consisting of the total GC content, melting temperature of
the siRNA, GC content at positions 15-19, the presence or absence
of a particular nucleotide at a particular position and the number
of times that the same nucleotide repeats within a given sequence;
and [0075] (e) developing an algorithm using the information of
step (d).
[0076] According to this embodiment, preferably the set of siRNAs
comprises at least 90 siRNAs from at least one gene, more
preferably at least 180 siRNAs from at least two different genes,
and most preferably at least 270 and 360 siRNAs from at least three
and four different genes, respectively. Additionally, in step (d)
the determination is made with preferably at least two, more
preferably at least three, even more preferably at least four, and
most preferably all of the variables. The resulting algorithm is
not target sequence specific.
[0077] In a fifth embodiment, the present invention provides
rationally designed siRNAs identified using the formulas above.
[0078] In a sixth embodiment, the present invention is directed to
hyperfunctional siRNA.
[0079] For a better understanding of the present invention together
with other and further advantages and embodiments, reference is
made to the following description taken in conjunction with the
examples, the scope of which is set forth in the appended
claims.
BRIEF DESCRIPTION OF THE FIGURES
[0080] FIG. 1 shows a model for siRNA-RISC interactions. RISC has
the ability to interact with either end of the siRNA or miRNA
molecule. Following binding, the duplex is unwound, and the
relevant target is identified, cleaved, and released.
[0081] FIG. 2 is a representation of the functionality of two
hundred and seventy siRNA duplexes that were generated to target
human cyclophilin, human diazepam-binding inhibitor (DB), and
firefly luciferase.
[0082] FIG. 3A is a representation of the silencing effect of 30
siRNAs in three different cells lines, HEK293, DU145, and Hela.
FIG. 3B shows the frequency of different functional groups (>95%
silencing (black), >80% silencing (gray), >50% silencing
(dark gray), and <50% silencing (white)) based on GC content. In
cases where a given bar is absent from a particular GC percentage,
no siRNA were identified for that particular group. FIG. 3C shows
the frequency of different functional groups based on melting
temperature (Tm). Again, each group has four different divisions:
>95% (black), >80% (gray), >50% (dark gray), and <50%
(white) silencing.
[0083] FIGS. 4A-4E are representations of a statistical analysis
that revealed correlations between silencing and five
sequence-related properties of siRNA: (4A) an A at position 19 of
the sense strand, (4B) an A at position 3 of the sense strand, (4C)
a U at position 10 of the sense strand, (4D) a base other than G at
position 13 of the sense strand, and (4E) a base other than C at
position 19 of the sense strand. All variables were correlated with
siRNA silencing of firefly luciferase and human cyclophilin. SiRNAs
satisfying the criterion are grouped on the left (Selected) while
those that do not, are grouped on the right (Eliminated). Y-axis is
"% Silencing of Control." Each position on the X-axis represents a
unique siRNA.
[0084] FIGS. 5 A and 5 B are representations of firefly luciferase
and cyclophilin siRNA panels sorted according to functionality and
predicted values using Formula VIII. The siRNA found within the
circle represent those that have Formula VIII values
(SMARTscores.TM.) above zero. SiRNA outside the indicated area have
calculated Formula VIII values that are below zero. Y-axis is
"Expression (% Control)." Each position on the X-axis represents a
unique siRNA.
[0085] FIG. 6A is a representation of the average internal
stability profile (AISP) derived from 270 siRNAs taken from three
separate genes (cyclophilin B, DBI and firefly luciferase). Graphs
represent AISP values of highly functional, functional, and
non-functional siRNA. FIG. 6B is a comparison between the AISP of
naturally derived GFP siRNA (filled squares) and the AISP of siRNA
from cyclophilin B, DBI, and luciferase having >90% silencing
properties (no fill) for the antisense strand. "DG" is the symbol
for AG, free energy.
[0086] FIG. 7 is a histogram showing the differences in duplex
functionality upon introduction of basepair mismatches. The X-axis
shows the mismatch introduced not the siRNA and the position it is
introduced (e.g., 8C->A reveals that position 8 (which normally
has a C) has been changed to an A). The Y-axis is "% Silencing
(Normalized to Control)."
[0087] FIG. 8 is histogram that shows the effects of 5'sense and
antisense strand modification with 2'-O-methylation on
functionality.
[0088] FIG. 9 shows a graph of SMARTscores.TM. versus RNAi
silencing values for more than 360 siRNA directed against 30
different genes. SiRNA to the right of the vertical bar represent
those siRNA that have desirable SMARTscores.TM..
[0089] FIGS. 10A-E compare the RNAi of five different genes (SEAP,
DBI, PLK, Firefly Luciferase, and Renila Luciferase) by varying
numbers of randomly selected siRNA and four rationally designed
(SMART-selected) siRNA chosen using the algorithm described in
Formula VIII. In addition, RNAi induced by a pool of the four
SMART-selected siRNA is reported at two different concentrations
(100 and 400 nM). 10F is a comparison between a pool of randomly
selected EGFR siRNA (Pool 1) and a pool of SMART selected EGFR
siRNA (Pool 2). Pool 1, S1-S4 and Pool 2 S1-S4 represent the
individual members that made up each respective pool. Note that
numbers for random siRNAs represent the position of the 5' end of
the sense strand of the duplex. The Y-axis represents the %
expression of the control(s). The X-axis is the percent expression
of the control.
[0090] FIG. 11 shows the Western blot results from cells treated
with siRNA directed against twelve different genes involved in the
clathrin-dependent endocytosis pathway (CHC, DynII, CALM, CLCa,
CLCb, Eps15, Eps15R, Rab5a, Rab5b, Rab5c, .beta.2 subunit of AP-2
and EEA.1). SiRNA were selected using Formula VIII. "Pool"
represents a mixture of duplexes 1-4. Total concentration of each
siRNA in the pool is 25 nM. Total concentration=4.times.25=100
nM.
[0091] FIG. 12 is a representation of the gene silencing
capabilities of rationally-selected siRNA directed against ten
different genes (human and mouse cyclophilin, C-myc, human lamin
A/C, QB (ubiquinol-cytochrome c reductase core protein I), MEK1 and
MEK2, ATE1 (arginyl-tRNA protein transferase), GAPDH, and Eg5). The
Y-axis is the percent expression of the control. Numbers 1, 2, 3
and 4 represent individual rationally selected siRNA. "Pool"
represents a mixture of the four individual siRNA.
[0092] FIG. 13 is the sequence of the top ten Bcl2 siRNAs as
determined by Formula VIII. Sequences are listed 5' to 3'.
[0093] FIG. 14 is the knockdown by the top ten Bcl2 siRNAs at 100
nM concentrations. The Y-axis represents the amount of expression
relative to the non-specific (ns) and transfection mixture
control.
[0094] FIG. 15 represents a functional walk where siRNA beginning
on every other base pair of a region of the luciferase gene are
tested for the ability to silence the luciferase gene. The Y-axis
represents the percent expression relative to a control. The X-axis
represents the position of each individual siRNA. Reading from left
to right across the X-axis, the position designations are 1, 3, 5,
7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39,
41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73,
75, 77, 79, 81, 83, 85, 87, 89, and Plasmid.
[0095] FIGS. 16A and 16B are histograms demonstrating the
inhibition of target gene expression by pools of 2 (16A) and 3
(16B) siRNA duplexes taken from the walk described in FIG. 15. The
Y-axis in each represents the percent expression relative to
control. The X-axis in each represents the position of the first
siRNA in paired pools, or trios of siRNAs. For instance, the first
paired pool contains siRNAs 1 and 3. The second paired pool
contains siRNAs 3 and 5. Pool 3 (of paired pools) contains siRNAs 5
and 7, and so on. For each of 16A and 16B, the X-axis from left to
right reads 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29,
31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63,
65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, and
Plasmid.
[0096] FIGS. 17A and 17B are histograms demonstrating the
inhibition of target gene expression by pools of 4 (17A) and 5
(17B) siRNA duplexes. The Y-axis in each represents the percent
expression relative to control. The X-axis in each represents the
position of the first siRNA in each pool. For each of 17A and 17B,
the X-axis from left to right reads 1, 3, 5, 7, 9, 11, 13, 15, 17,
19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51,
53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85,
87, 89, and Plasmid.
[0097] FIGS. 18A and 18B are histograms demonstrating the
inhibition of target gene expression by siRNAs that are ten (18A)
and twenty (18B) base pairs apart. The Y-axis represents the
percent expression relative to a control. The X-axis represents the
position of the first siRNA in each pool. For each of 18A and 18B,
the X-axis from left to right reads 1, 3, 5, 7, 9, 11, 13, 15, 17,
19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51,
53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85,
87, 89, and Plasmid.
[0098] FIG. 19 shows that pools of siRNAs (dark gray bar) work as
well (or better) than the best siRNA in the pool (light gray bar).
The Y-axis represents the percent expression relative to a control.
The X-axis represents the position of the first siRNA in each pool.
The X-axis from left to right reads 1, 3, 5, 7, 9, 11, 13, 15, 17,
19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51,
53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85,
87, 89, and Plasmid.
[0099] FIG. 20 shows that the combination of several semifunctional
siRNAs (dark gray) result in a significant improvement of gene
expression inhibition over individual (semi-functional; light gray)
siRNA. The Y-axis represents the percent expression relative to a
control.
[0100] FIG. 21 shows both pools (Library, Lib) and individual
siRNAs in inhibition of gene expression of Beta-Galactosidase,
Renilla Luciferase and SEAP (alkaline phosphatase). Numbers on the
X-axis indicate the position of the 5'-most nucleotide of the sense
strand of the duplex. The Y-axis represents the percent expression
of each gene relative to a control. Libraries contain siRNAs that
begin at the following nucleotides: Seap: Lib 1: 206, 766, 812,
923, Lib 2: 1117, 1280, 1300, 1487, Lib 3: 206, 766, 812, 923,
1117, 1280, 1300, 1487, Lib 4: 206, 812, 1117, 1300, Lib 5: 766,
923, 1280, 1487, Lib 6: 206, 1487; Bgal: Lib 1: 979, 1339, 2029,
2590, Lib 2: 1087, 1783, 2399, 3257, Lib 3: 979, 1783, 2590, 3257,
Lib 4: 979, 1087, 1339, 1783, 2029, 2399, 2590, 3257, Lib 5: 979,
1087, 1339, 1783, Lib 6: 2029, 2399, 2590, 3257; Renilla: Lib 1:
174, 300, 432, 568, Lib 2: 592, 633, 729, 867, Lib 3: 174, 300,
432, 568, 592, 633, 729, 867, Lib 4: 174, 432, 592, 729, Lib 5:
300, 568, 633, 867, Lib 6: 592, 568.
[0101] FIG. 22 shows the results of an EGFR and TfnR
internalization assay when single gene knockdowns are performed.
The Y-axis represents percent internalization relative to
control.
[0102] FIG. 23 shows the results of an EGFR and TfnR
internalization assay when multiple genes are knocked down (e.g.
RabSa, b, c). The Y-axis represents the percent internalization
relative to control.
[0103] FIG. 24 shows the simultaneous knockdown of four different
genes. SiRNAs directed against G6PD, GAPDH, PLK, and UBQ were
simultaneously introduced into cells. Twenty-four hours later,
cultures were harvested and assayed for mRNA target levels for each
of the four genes. A comparison is made between cells transfected
with individual siRNAs vs. a pool of siRNAs directed against all
four genes.
[0104] FIG. 25 shows the functionality of ten siRNAs at 0.3 nM
concentrations.
DETAILED DESCRIPTION
Definitions
[0105] Unless stated otherwise, the following terms and phrases
have the meanings provided below:
siRNA
[0106] The term "siRNA" refers to small inhibitory RNA duplexes
that induce the RNA interference (RNAi) pathway. These molecules
can vary in length (generally between 18-30 basepairs) and contain
varying degrees of complementarity to their target mRNA in the
antisense strand. Some, but not all, siRNA have unpaired
overhanging bases on the 5' or 3' end of the sense strand and/or
the antisense strand. The term "siRNA" includes duplexes of two
separate strands, as well as single strands that can form hairpin
structures comprising a duplex region.
[0107] SiRNA may be divided into five (5) groups (non-functional,
semi-functional, functional, highly functional, and
hyper-functional) based on the level or degree of silencing that
they induce in cultured cell lines. As used herein, these
definitions are based on a set of conditions where the siRNA is
transfected into said cell line at a concentration of 100 nM and
the level of silencing is tested at a time of roughly 24 hours
after transfection, and not exceeding 72 hours after transfection.
In this context, "non-functional siRNA" are defined as those siRNA
that induce less than 50% (<50%) target silencing.
"Semi-functional siRNA" induce 50-79% target silencing. "Functional
siRNA" are molecules that induce 80-95% gene silencing.
"Highly-functional siRNA" are molecules that induce greater than
95% gene silencing. "Hyperfunctional siRNA" are a special class of
molecules. For purposes of this document, hyperfunctional siRNA are
defined as those molecules that: (1) induce greater than 95%
silencing of a specific target when they are transfected at
subnanomolar concentrations (i.e., less than one nanomolar); and/or
(2) induce functional (or better) levels of silencing for greater
than 96 hours. These relative functionalities (though not intended
to be absolutes) may be used to compare siRNAs to a particular
target for applications such as functional genomics, target
identification and therapeutics.
miRNA
[0108] The term "miRNA" refers to microRNA.
Gene Silencing
[0109] The phrase "gene silencing" refers to a process by which the
expression of a specific gene product is lessened or attenuated.
Gene silencing can take place by a variety of pathways. Unless
specified otherwise, as used herein, gene silencing refers to
decreases in gene product expression that results from RNA
interference (RNAi), a defined, though partially characterized
pathway whereby small inhibitory RNA (siRNA) act in concert with
host proteins (e.g. the RNA induced silencing complex, RISC) to
degrade messenger RNA (mRNA) in a sequence-dependent fashion. The
level of gene silencing can be measured by a variety of means,
including, but not limited to, measurement of transcript levels by
Northern Blot Analysis, B-DNA techniques, transcription-sensitive
reporter constructs, expression profiling (e.g. DNA chips), and
related technologies. Alternatively, the level of silencing can be
measured by assessing the level of the protein encoded by a
specific gene. This can be accomplished by performing a number of
studies including Western Analysis, measuring the levels of
expression of a reporter protein that has e.g. fluorescent
properties (e.g. GFP) or enzymatic activity (e.g. alkaline
phosphatases), or several other procedures.
Transfection
[0110] The term "transfection" refers to a process by which agents
are introduced into a cell. The list of agents that can be
transfected is large and includes, but is not limited to, siRNA,
sense and/or anti-sense sequences, DNA encoding one or more genes
and organized into an expression plasmid, proteins, protein
fragments, and more. There are multiple methods for transfecting
agents into a cell including, but not limited to, electroporation,
calcium phosphate-based transfections, DEAE-dextran-based
transfections, lipid-based transfections, molecular conjugate-based
transfections (e.g. polylysine-DNA conjugates), microinjection and
others.
Target
[0111] The term "target" is used in a variety of different forms
throughout this document and is defined by the context in which it
is used. "Target mRNA" refers to a messenger RNA to which a given
siRNA can be directed against. "Target sequence" and "target site"
refer to a sequence within the mRNA to which the sense strand of an
siRNA shows varying degrees of homology and the antisense strand
exhibits varying degrees of complementarity. The term "siRNA
target" can refer to the gene, mRNA, or protein against which an
siRNA is directed. Similarly "target silencing" can refer to the
state of a gene, or the corresponding mRNA or protein.
Off-Target Silencing and Off-Target Interference
[0112] The phrases "off-target silencing" and "off-target
interference" are defined as degradation of mRNA other than the
intended target mRNA due to overlapping and/or partial homology
with secondary mRNA messages.
SMARTscore.TM.
[0113] The term "SMARTscore.TM." refers to a number determined by
applying any of the Formulas I-Formula IX to a given siRNA
sequence. The term "SMART-selected" or "rationally selected" or
"rational selection" refers to siRNA that have been selected on the
basis of their SMARTscores.TM..
Complementary
[0114] The term "complementary" refers to the ability of
polynucleotides to form base pairs with one another. Base pairs are
typically formed by hydrogen bonds between nucleotide units in
antiparallel polynucleotide strands. Complementary polynucleotide
strands can base pair in the Watson-Crick manner (e.g., A to T, A
to U, C to G), or in any other manner that allows for the formation
of duplexes. As persons skilled in the art are aware, when using
RNA as opposed to DNA, uracil rather than thymine is the base that
is considered to be complementary to adenosine. However, when a U
is denoted in the context of the present invention, the ability to
substitute a T is implied, unless otherwise stated.
[0115] Perfect complementarity or 100% complementarity refers to
the situation in which each nucleotide unit of one polynucleotide
strand can hydrogen bond with a nucleotide unit of a second
polynucleotide strand. Less than perfect complementarity refers to
the situation in which some, but not all, nucleotide units of two
strands can hydrogen bond with each other. For example, for two
20-mers, if only two base pairs on each strand can hydrogen bond
with each other, the polynucleotide strands exhibit 10%
complementarity. In the same example, if 18 base pairs on each
strand can hydrogen bond with each other, the polynucleotide
strands exhibit 90% complementarity.
Deoxynucleotide
[0116] The term "deoxynucleotide" refers to a nucleotide or
polynucleotide lacking a hydroxyl group (OH group) at the 2' and/or
3' position of a sugar moiety. Instead, it has a hydrogen bonded to
the 2' and/or 3' carbon. Within an RNA molecule that comprises one
or more deoxynucleotides, "deoxynucleotide" refers to the lack of
an OH group at the 2' position of the sugar moiety, having instead
a hydrogen bonded directly to the 2' carbon.
Deoxyribonucleotide
[0117] The terms "deoxyribonucleotide" and "DNA" refer to a
nucleotide or polynucleotide comprising at least one sugar moiety
that has an H, rather than an OH, at its 2' and/or 3'position.
Substantially Similar
[0118] The phrase "substantially similar" refers to a similarity of
at least 90% with respect to the identity of the bases of the
sequence.
Duplex Region
[0119] The phrase "duplex region" refers to the region in two
complementary or substantially complementary polynucleotides that
form base pairs with one another, either by Watson-Crick base
pairing or any other manner that allows for a stabilized duplex
between polynucleotide strands that are complementary or
substantially complementary. For example, a polynucleotide strand
having 21 nucleotide units can base pair with another
polynucleotide of 21 nucleotide units, yet only 19 bases on each
strand are complementary or substantially complementary, such that
the "duplex region" has 19 base pairs. The remaining bases may, for
example, exist as 5' and 3' overhangs. Further, within the duplex
region, 100% complementarity is not required; substantial
complementarity is allowable within a duplex region. For example, a
mismatch in a duplex region consisting of 19 base pairs results in
94.7% complementarity, rendering the duplex region substantially
complementary.
Nucleotide
[0120] The term "nucleotide" refers to a ribonucleotide or a
deoxyribonucleotide or modified form thereof, as well as an analog
thereof. Nucleotides include species that comprise purines, e.g.,
adenine, hypoxanthine, guanine, and their derivatives and analogs,
as well as pyrimidines, e.g., cytosine, uracil, thymine, and their
derivatives and analogs.
[0121] Nucleotide analogs include nucleotides having modifications
in the chemical structure of the base, sugar and/or phosphate,
including, but not limited to, 5-position pyrimidine modifications,
8-position purine modifications, modifications at cytosine
exocyclic amines, and substitution of 5-bromo-uracil; and
2'-position sugar modifications, including but not limited to,
sugar-modified ribonucleotides in which the 2'-OH is replaced by a
group such as an H, OR, R, halo, SH, SR, NH.sub.2, NHR, NR.sub.2,
or CN, wherein R is an alkyl moiety. Nucleotide analogs are also
meant to include nucleotides with bases such as inosine, queuosine,
xanthine, sugars such as 2'-methyl ribose, non-natural
phosphodiester linkages such as methylphosphonates,
phosphorothioates and peptides.
[0122] Modified bases refer to nucleotide bases such as, for
example, adenine, guanine, cytosine, thymine, uracil, xanthine,
inosine, and queuosine that have been modified by the replacement
or addition of one or more atoms or groups. Some examples of types
of modifications that can comprise nucleotides that are modified
with respect to the base moieties include but are not limited to,
alkylated, halogenated, thiolated, aminated, amidated, or
acetylated bases, individually or in combination. More specific
examples include, for example, 5-propynyluridine,
5-propynylcytidine, 6-methyladenine, 6-methylguanine,
N,N,-dimethyladenine, 2-propyladenine, 2-propylguanine,
2-aminoadenine, 1-methylinosine, 3-methyluridine, 5-methylcytidine,
5-methyluridine and other nucleotides having a modification at the
5 position, 5-(2-amino)propyl uridine, 5-halocytidine,
5-halouridine, 4-acetylcytidine, 1-methyladenosine,
2-methyladenosine, 3-methylcytidine, 6-methyluridine,
2-methylguanosine, 7-methylguanosine, 2,2-dimethylguanosine,
5-methylaminoethyluridine, 5-methyloxyuridine, deazanucleotides
such as 7-deaza-adenosine, 6-azouridine, 6-azocytidine,
6-azothymidine, 5-methyl-2-thiouridine, other thio bases such as
2-thiouridine and 4-thiouridine and 2-thiocytidine, dihydrouridine,
pseudouridine, queuosine, archaeosine, naphthyl and substituted
naphthyl groups, any O- and N-alkylated purines and pyrimidines
such as N6-methyladenosine, 5-methylcarbonylmethyluridine, uridine
5-oxyacetic acid, pyridine-4-one, pyridine-2-one, phenyl and
modified phenyl groups such as aminophenol or 2,4,6-trimethoxy
benzene, modified cytosines that act as G-clamp nucleotides,
8-substituted adenines and guanines, 5-substituted uracils and
thymines, azapyrimidines, carboxyhydroxyalkyl nucleotides,
carboxyalkylaminoalkyl nucleotides, and alkylcarbonylalkylated
nucleotides. Modified nucleotides also include those nucleotides
that are modified with respect to the sugar moiety, as well as
nucleotides having sugars or analogs thereof that are not ribosyl.
For example, the sugar moieties may be, or be based on, mannoses,
arabinoses, glucopyranoses, galactopyranoses, 4'-thioribose, and
other sugars, heterocycles, or carbocycles.
[0123] The term nucleotide is also meant to include what are known
in the art as universal bases. By way of example, universal bases
include but are not limited to 3-nitropyrrole, 5-nitroindole, or
nebularine. The term "nucleotide" is also meant to include the N3'
to P5' phosphoramidate, resulting from the substitution of a
ribosyl 3' oxygen with an amine group.
[0124] Further, the term nucleotide also includes those species
that have a detectable label, such as for example a radioactive or
fluorescent moiety, or mass label attached to the nucleotide.
Polynucleotide
[0125] The term "polynucleotide" refers to polymers of nucleotides,
and includes but is not limited to DNA, RNA, DNA/RNA hybrids
including polynucleotide chains of regularly and/or irregularly
alternating deoxyribosyl moieties and ribosyl moieties (i.e.,
wherein alternate nucleotide units have an --OH, then and --H, then
an --OH, then an --H, and so on at the 2' position of a sugar
moiety), and modifications of these kinds of polynucleotides,
wherein the attachment of various entities or moieties to the
nucleotide units at any position are included.
Polyribonucleotide
[0126] The term "polyribonucleotide" refers to a polynucleotide
comprising two or more modified or unmodified ribonucleotides
and/or their analogs. The term "polyribonucleotide" is used
interchangeably with the term "oligoribonucleotide."
Ribonucleotide and Ribonucleic Acid
[0127] The term "ribonucleotide" and the phrase "ribonucleic acid"
(RNA), refer to a modified or unmodified nucleotide or
polynucleotide comprising at least one ribonucleotide unit. A
ribonucleotide unit comprises an hydroxyl group attached to the 2'
position of a ribosyl moiety that has a nitrogenous base attached
in N-glycosidic linkage at the 1' position of a ribosyl moiety, and
a moiety that either allows for linkage to another nucleotide or
precludes linkage.
DETAILED DESCRIPTION OF THE INVENTION
[0128] The present invention is directed to improving the
efficiency of gene silencing by siRNA. Through the inclusion of
multiple siRNA sequences that are targeted to a particular gene
and/or selecting an siRNA sequence based on certain defined
criteria, improved efficiency may be achieved.
[0129] The present invention will now be described in connection
with preferred embodiments. These embodiments are presented in
order to aid in an understanding of the present invention and are
not intended, and should not be construed, to limit the invention
in any way. All alternatives, modifications and equivalents that
may become apparent to those of ordinary skill upon reading this
disclosure are included within the spirit and scope of the present
invention.
[0130] Furthermore, this disclosure is not a primer on RNA
interference. Basic concepts known to persons skilled in the art
have not been set forth in detail.
Optimizing siRNA
[0131] According to one embodiment, the present invention provides
a method for improving the effectiveness of gene silencing for use
to silence a particular gene through the selection of an optimal
siRNA. An siRNA selected according to this method may be used
individually, or in conjunction with the first embodiment, i.e.,
with one or more other siRNAs, each of which may or may not be
selected by this criteria in order to maximize their
efficiency.
[0132] The degree to which it is possible to select an siRNA for a
given mRNA that maximizes these criteria will depend on the
sequence of the mRNA itself. However, the selection criteria will
be independent of the target sequence. According to this method, an
siRNA is selected for a given gene by using a rational design. That
said, rational design can be described in a variety of ways.
Rational design is, in simplest terms, the application of a proven
set of criteria that enhance the probability of identifying a
functional or hyperfunctional siRNA. In one method, rationally
designed siRNA can be identified by maximizing one or more of the
following criteria: [0133] 1. A low GC content, preferably between
about 30-52%. [0134] 2. At least 2, preferably at least 3 A or U
bases at positions 15-19 of the siRNA on the sense strand. [0135]
3. An A base at position 19 of the sense strand. [0136] 4. An A
base at position 3 of the sense strand. [0137] 5. A U base at
position 10 of the sense strand. [0138] 6. An A base at position 14
of the sense strand. [0139] 7. A base other than C at position 19
of the sense strand. [0140] 8. A base other than G at position 13
of the sense strand. [0141] 9. A Tm, which refers to the character
of the internal repeat that results in inter- or intramolecular
structures for one strand of the duplex, that is preferably not
stable at greater than 50.degree. C., more preferably not stable at
greater than 37.degree. C., even more preferably not stable at
greater than 30.degree. C. and most preferably not stable at
greater than 20.degree. C. [0142] 10. A base other than U at
position 5 of the sense strand. [0143] 11. A base other than A at
position 11 of the sense strand.
[0144] Criteria 5, 6, 10 and 11 are minor criteria, but are
nonetheless desirable. Accordingly, preferably an siRNA will
satisfy as many of the aforementioned criteria as possible, more
preferably at least 1-4 and 7-9, and most preferably all of the
criteria
[0145] With respect to the criteria, GC content, as well as a high
number of AU in positions 15-19, may be important for easement of
the unwinding of double stranded siRNA duplex. Duplex unwinding has
been shown to be crucial for siRNA functionality in vivo.
[0146] With respect to criterion 9, the internal structure is
measured in terms of the melting temperature of the single strand
of siRNA, which is the temperature at which 50% of the molecules
will become denatured. With respect to criteria 2-8 and 10-11, the
positions refer to sequence positions on the sense strand, which is
the strand that is identical to the mRNA.
[0147] In one preferred embodiment, at least criteria 1 and 8 are
satisfied. In another preferred embodiment, at least criteria 7 and
8 are satisfied. In still another preferred embodiment, at least
criteria 1, 8 and 9 are satisfied.
[0148] It should be noted that all of the aforementioned criteria
regarding sequence position specifics are with respect to the 5'
end of the sense strand. Reference is made to the sense strand,
because most databases contain information that describes the
information of the mRNA. Because according to the present invention
a chain can be from 18 to 30 bases in length, and the
aforementioned criteria assumes a chain 19 base pairs in length, it
is important to keep the aforementioned criteria applicable to the
correct bases.
[0149] When there are only 18 bases, the base pair that is not
present is the base pair that is located at the 3' of the sense
strand. When there are twenty to thirty bases present, then
additional bases are added at the 5' end of the sense chain and
occupy positions .sup.-1 to .sup.-11. Accordingly, with respect to
SEQ. ID NO. 0001. NNANANNNNUCNAANNNNA and SEQ. ID NO. 0028.
GUCNNANANNNNUCNAANNNNA, both would have A at position 3, A at
position 5, U at position 10, C at position 11, A and position 13,
A and position 14 and A at position 19. However, SEQ. ID NO. 0028
would also have C at position -1, U at position -2 and G at
position -3.
[0150] For a 19 base pair siRNA, an optimal sequence of one of the
strands may be represented below, where N is any base, A, C, G, or
U: TABLE-US-00001 SEQ. ID NO. 0001. NNANANNNNUCNAANNNNA SEQ. ID NO.
0002. NNANANNNNUGNAANNNNA SEQ. ID NO. 0003. NNANANNNNUUNAANNNNA
SEQ. ID NO. 0004. NNANANNNNUCNCANNNNA SEQ. ID NO. 0005.
NNANANNNNUGNCANNNNA SEQ. ID NO. 0006. NNANANNNNUUNCANNNNA SEQ. ID
NO. 0007. NNANANNNNUCNUANNNNA SEQ. ID NO. 0008..
NNANANNNNUGNUANNNNA SEQ. ID NO. 0009. NNANANNNNUUNUANNNNA SEQ. ID
NO. 0010. NNANCNNNNUCNAANNNNA SEQ. ID NO. 0011. NNANCNNNNUGNAANNNNA
SEQ. ID NO. 0012. NNANCNNNNUUNAANNNNA SEQ. ID NO. 0013.
NNANCNNNNUCNCANNNNA SEQ. ID NO. 0014. NNANCNNNNUGNCANNNNA SEQ. ID
NO. 0015. NNANCNNNNUUNCANNNNA SEQ. ID NO. 0016. NNANCNNNNUCNUANNNNA
SEQ. ID NO. 0017. NNANCNNNNUGNUANNNNA SEQ. ID NO. 0018.
NNANCNNNNUUNUANNNNA SEQ. ID NO. 0019. NNANGNNNNUCNAANNNNA SEQ. ID
NO. 0020. NNANGNNNNUGNAANNNNA SEQ. ID NO. 0021. NNANGNNNNUUNAANNNNA
SEQ. ID NO. 0022. NNANGNNNNUCNCANNNNA SEQ. ID NO. 0023.
NNANGNNNNUGNCANNNNA SEQ. ID NO. 0024. NNANGNNNNUUNCANNNNA SEQ. ID
NO. 0025. NNANGNNNNUCNUANNNNA SEQ. ID NO. 0026. NNANGNNNNUGNUANNNNA
SEQ. ID NO. 0027. NNANGNNNNUUNUANNNNA
[0151] In one embodiment, the sequence used as an siRNA is selected
by choosing the siRNA that score highest according to one of the
following seven algorithms that are represented by Formulas I-VII:
Relative functionality of
siRNA=-(GC/3)+(AU.sub.15-19)-(Tm.sub.20.degree.
C.)*3-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.sub.3)+(U.sub.10)+(A.sub.14-
)-(U.sub.5)-(A.sub.11) Formula I Relative functionality of
siRNA=-(GC/3)-(AU.sub.15-19)*3-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.su-
b.3) Formula II Relative functionality of
siRNA=-(GC/3)+(AU.sub.15-19)-(Tm.sub.20.degree. C.)*3 Formula III
Relative functionality of
siRNA=-GC/2+(AU.sub.15-19)/2-(Tm.sub.20.degree.
C.)*2-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.sub.3)+(U.sub.10)+(A.sub.14-
)-(U.sub.5)-(A.sub.11) Formula IV Relative functionality of
siRNA=-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.sub.3)+(U.sub.10)+(A.sub.1-
4)-(U.sub.5)-(A.sub.11) Formula V Relative functionality of
siRNA=-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*2+(A.sub.3) Formula VI
Relative functionality of
siRNA=-(GC/2)+(AU.sub.15-19)/2-(Tm.sub.20.degree.
C.)*1-(G.sub.13)*3-(C.sub.19)+(A.sub.19)*3+(A.sub.3)*3+(U.sub.10)/2+(A.su-
b.14)/2-(U.sub.5)/2-(A.sub.11)/2 Formula VII In Formulas I-VII:
wherein A.sub.19=1 if A is the base at position 19 on the sense
strand, otherwise its value is 0, [0152] AU.sub.15-19=0-5 depending
on the number of A or U bases on the sense strand at [0153]
positions 15-19; [0154] G.sub.13=1 if G is the base at position 13
on the sense strand, otherwise its value is 0; [0155] C.sub.19=1 if
C is the base at position 19 of the sense strand, otherwise its
value is 0; [0156] GC=the number of G and C bases in the entire
sense strand; [0157] Tm.sub.20.degree. C.=1 if the Tm is greater
than 20.degree. C.; [0158] A.sub.3=1 if A is the base at position 3
on the sense strand, otherwise its value is 0; [0159] U.sub.10=1 if
U is the base at position 10 on the sense strand, otherwise its
value is 0; [0160] A.sub.14=1 if A is the base at position 14 on
the sense strand, otherwise its value is 0; [0161] U.sub.5=1 if U
is the base at position 5 on the sense strand, otherwise its value
is 0; and
[0162] A.sub.11=1 if A is the base at position 11 of the sense
strand, otherwise its value is 0.
[0163] Formulas I-VII provide relative information regarding
functionality. When the values for two sequences are compared for a
given formula, the relative functionality is ascertained; a higher
positive number indicates a greater functionality. For example, in
many applications a value of 5 or greater is beneficial.
[0164] Additionally, in many applications, more than one of these
formulas would provide useful information as to the relative
functionality of potential siRNA sequences. However, it is
beneficial to have more than one type of formula, because not every
formula will be able to help to differentiate among potential siRNA
sequences. For example, in particularly high GC mRNAs, formulas
that take that parameter into account would not be useful and
application of formulas that lack GC elements (e.g., formulas V and
VI) might provide greater insights into duplex functionality.
Similarly, formula II might by used in situations where hairpin
structures are not observed in duplexes, and formula IV might be
applicable for sequences that have higher AU content. Thus, one may
consider a particular sequence in light of more than one or even
all of these algorithms to obtain the best differentiation among
sequences. In some instances, application of a given algorithm may
identify an unususally large number of potential siRNA sequences,
and in those cases, it may be appropriate to re-analyze that
sequence with a second algorithm that is, for instance, more
stringent. Alternatively, it is conceivable that analysis of a
sequence with a given formula yields no acceptable siRNA sequences
(i.e. low SMARTscores.TM.). In this instance, it may be appropriate
to re-analyze that sequences with a second algorithm that is, for
instance, less stringent. In still other instances, analysis of a
single sequence with two separate formulas may give rise to
conflicting results (i.e. one formula generates a set of siRNA with
high SMARTscores.TM. while the other formula identifies a set of
siRNA with low SMARTscores.TM.). In these instances, it may be
necessary to determine which weighted factor(s) (e.g. GC content)
are contributing to the discrepancy and assessing the sequence to
decide whether these factors should or should not be included.
Alternatively, the sequence could be analyzed by a third, fourth,
or fifth algorithm to identify a set of rationally designed
siRNA.
[0165] The above-referenced criteria are particularly advantageous
when used in combination with pooling techniques as depicted in
Table I: TABLE-US-00002 TABLE I Functional Probability Oligos Pools
Criteria >95% >80% <70% >95% >80% <70% Current
33.0 50.0 23.0 79.5 97.3 0.3 New 50.0 88.5 8.0 93.8 99.98 0.005
(GC) 28.0 58.9 36.0 72.8 97.1 1.6
The term "current" refers to Tuschl's conventional siRNA parameters
(Elbashir, S. M. et al. (2002) "Analysis of gene function in
somatic mammalian cells using small interfering RNAs" Methods 26:
199-213). "New" refers to the design parameters described in
Formulas I-VII. "GC" refers to criteria that select siRNA solely on
the basis of GC content.
[0166] As Table I indicates, when more functional siRNA duplexes
are chosen, siRNAs that produce <70% silencing drops from 23% to
8% and the number of siRNA duplexes that produce >80% silencing
rises from 50% to 88.5%. Further, of the siRNA duplexes with
>80% silencing, a larger portion of these siRNAs actually
silence >95% of the target expression (the new criteria
increases the portion from 33% to 50%). Using this new criteria in
pooled siRNAs, shows that, with pooling, the amount of silencing
>95% increases from 79.5% to 93.8% and essentially eliminates
any siRNA pool from silencing less than 70%.
[0167] Table II similarly shows the particularly beneficial results
of pooling in combination with the aforementioned criteria.
However, Table II, which takes into account each of the
aforementioned variables, demonstrates even a greater degree of
improvement in functionality. TABLE-US-00003 TABLE II Functional
Probability Oligos Pools Non- Non- Functional Average functional
Functional Average functional Random 20 40 50 67 97 3 Criteria 1 52
99 0.1 97 93 0.0040 Criteria 4 89 99 0.1 99 99 0.0000
The terms "functional," "Average," and "Non-functional" refer to
siRNA that exhibit >80%, >50%, and <50% functionality,
respectively. Criteria 1 and 4 refer to specific criteria described
above.
[0168] The above-described algorithms may be used with or without a
computer program that allows for the inputting of the sequence of
the mRNA and automatically outputs the optimal siRNA. The computer
program may, for example, be accessible from a local terminal or
personal computer, over an internal network or over the
Internet.
[0169] In addition to the formulas above, more detailed algorithms
may be used for selecting siRNA. Preferably, at least one RNA
duplex of between 18 and 30 base pairs is selected such that it is
optimized according a formula selected from:
(-14)*G.sub.13-13*A.sub.1-12*U.sub.7-11*U.sub.2-10*A.sub.11-10*U.sub.4-10-
*C.sub.3-10*C.sub.5-10*C.sub.6-9*A.sub.10-9*U.sub.9-9*C.sub.18-8*G.sub.10--
7*U.sub.1-7*U.sub.16-7*C.sub.17-7*C.sub.19+7*U.sub.17+8*A.sub.2+8*A.sub.4+-
8*A.sub.5+8*C.sub.4+9*G.sub.8+10*A.sub.7+10*U.sub.18+1*A.sub.19+11*C.sub.9-
+15*G.sub.1+18*A.sub.3+19*U.sub.10-Tm-3*(GC.sub.total)-6*(GC.sub.15-19)-30-
*X; and Formula VIII
(14.1)*A.sub.3+(14.9)*A.sub.6+(17.6)*A.sub.13+(24.7)*A.sub.19+(14.2)*U.su-
b.10+(10.5)*C.sub.9+(23.9)*G.sub.1+(16.3)*G.sub.2+(-12.3)*A.sub.11+(-19.3)-
*U.sub.1+(-12.1)*U.sub.2+(-11)*U.sub.3+(-15.2)*U.sub.15+(-11.3)*U.sub.16+(-
-11.8)*C.sub.3+(-17.4)*C.sub.6+(-10.5)
*C.sub.7+(-13.7)*G.sub.13+(-25.9)*G.sub.19-Tm-3*(GC.sub.total)-6*(GC.sub.-
15-19)-30*X Formula IX wherein [0170] A.sub.1=1 if A is the base at
position 1 of the sense strand, otherwise its value is 0; [0171]
A.sub.2=1 if A is the base at position 2 of the sense strand,
otherwise its value is 0; [0172] A.sub.3=1 if A is the base at
position 3 of the sense strand, otherwise its value is 0; [0173]
A.sub.4=1 if A is the base at position 4 of the sense strand,
otherwise its value is 0; [0174] A.sub.5=1 if A is the base at
position 5 of the sense strand, otherwise its value is 0; [0175]
A.sub.6=1 if A is the base at position 6 of the sense strand,
otherwise its value is 0; [0176] A.sub.7=1 if A is the base at
position 7 of the sense strand, otherwise its value is 0; [0177]
A.sub.10=1 if A is the base at position 10 of the sense strand,
otherwise its value is 0; [0178] A.sub.11=1 if A is the base at
position 11 of the sense strand, otherwise its value is 0; [0179]
A.sub.13=1 if A is the base at position 13 of the sense strand,
otherwise its value is 0; [0180] A.sub.19=1 if A is the base at
position 19 of the sense strand, otherwise if another base is
present or the sense strand is only 18 base pairs in length, its
value is 0; [0181] C.sub.3=1 if C is the base at position 3 of the
sense strand, otherwise its value is 0; [0182] C.sub.4=1 if C is
the base at position 4 of the sense strand, otherwise its value is
0; [0183] C.sub.5=1 if C is the base at position 5 of the sense
strand, otherwise its value is 0; [0184] C.sub.6=1 if C is the base
at position 6 of the sense strand, otherwise its value is 0; [0185]
C.sub.7=1 if C is the base at position 7 of the sense strand,
otherwise its value is 0; [0186] C.sub.9=1 if C is the base at
position 9 of the sense strand, otherwise its value is 0; [0187]
C.sub.17=1 if C is the base at position 17 of the sense strand,
otherwise its value is 0; [0188] C.sub.18=1 if C is the base at
position 18 of the sense strand, otherwise its value is 0; [0189]
C.sub.19=1 if C is the base at position 19 of the sense strand,
otherwise if another base is present or the sense strand is only 18
base pairs in length, its value is 0; [0190] G.sub.1=1 if G is the
base at position 1 on the sense strand, otherwise its value is 0;
[0191] G.sub.2=1 if G is the base at position 2 of the sense
strand, otherwise its value is 0; [0192] G.sub.8=1 if G is the base
at position 8 on the sense strand, otherwise its value is 0; [0193]
G.sub.10=1 if G is the base at position 10 on the sense strand,
otherwise its value is 0; [0194] G.sub.13=1 if G is the base at
position 13 on the sense strand, otherwise its value is 0; [0195]
G.sub.19=1 if G is the base at position 19 of the sense strand,
otherwise if another base is present or the sense strand is only 18
base pairs in length, its value is 0; [0196] U.sub.1=1 if U is the
base at position 1 on the sense strand, otherwise its value is 0;
[0197] U.sub.2=1 if U is the base at position 2 on the sense
strand, otherwise its value is 0; [0198] U.sub.3=1 if U is the base
at position 3 on the sense strand, otherwise its value is 0; [0199]
U.sub.4=1 if U is the base at position 4 on the sense strand,
otherwise its value is 0; [0200] U.sub.7=1 if U is the base at
position 7 on the sense strand, otherwise its value is 0; [0201]
U.sub.9=1 if U is the base at position 9 on the sense strand,
otherwise its value is 0; [0202] U.sub.10=1 if U is the base at
position 10 on the sense strand, otherwise its value is 0; [0203]
U.sub.15=1 if U is the base at position 15 on the sense strand,
otherwise its value is 0; [0204] U.sub.16=1 if U is the base at
position 16 on the sense strand, otherwise its value is 0; [0205]
U.sub.17=1 if U is the base at position 17 on the sense strand,
otherwise its value is 0; [0206] U.sub.18=1 if U is the base at
position 18 on the sense strand, otherwise its value is 0; [0207]
GC.sub.15-19=the number of G and C bases within positions 15-19 of
the sense strand, or within positions 15-18 if the sense strand is
only 18 base pairs in length; [0208] GC.sub.total=the number of G
and C bases in the sense strand; [0209] Tm=100 if the siRNA oligo
has the internal repeat longer then 4 base pairs, otherwise its
value is 0; and [0210] X=the number of times that the same
nucleotide repeats four or more times in a row.
[0211] The above formulas VIII and IX, as well as formulas I-VII,
provide methods for selecting siRNA in order to increase the
efficiency of gene silencing. A subset of variables of any of the
formulas may be used, though when fewer variables are used, the
optimization hierarchy becomes less reliable.
[0212] With respect to the variables of the above-referenced
formulas, a single letter of A or C or G or U followed by a
subscript refers to a binary condition. The binary condition is
that either the particular base is present at that particular
position (wherein the value is "1") or the base is not present
(wherein the value is "0"). Because position 19 is optional, i.e.
there might be only 18 base pairs, when there are only 18 base
pairs, any base with a subscript of 19 in the formulas above would
have a zero value for that parameter. Before or after each variable
is a number followed by *, which indicates that the value of the
variable is to be multiplied or weighed by that number.
[0213] The numbers preceding the variables A, or G, or C, or U in
Formulas VIII and IX (or after the variables in Formula I-VII) were
determined by comparing the difference in the frequency of
individual bases at different positions in functional siRNA and
total siRNA. Specifically, the frequency in which a given base was
observed at a particular position in functional groups was compared
with the frequency that that same base was observed in the total,
randomly selected siRNA set. If the absolute value of the
difference between the functional and total values was found to be
greater than 6%, that parameter was included in the equation. Thus
for instance, if the frequency of finding a "G" at position 13
(G.sub.13) is found to be 6% in a given functional group, and the
frequency of G.sub.13 in the total population of siRNAs is 20%, the
difference between the two values is 6%-20%=-14%. As the absolute
value is greater than six (6), this factor (-14) is included in the
equation. Thus in Formula VIII, in cases where the siRNA under
study has a G in position 13, the accrued value is (-14)*(1)=-14.
In contrast, when a base other than G is found at position 13, the
accrued value is (-14)*(0)=0.
[0214] When developing a means to optimize siRNAs, the inventors
observed that a bias toward low internal thermodynamic stability of
the duplex at the 5'-antisense (AS) end is characteristic of
naturally occurring miRNA precursors. The inventors extended this
observation to siRNAs for which functionality had been assessed in
tissue culture.
[0215] With respect to the parameter GC.sub.15-19, a value of 0-5
will be ascribed depending on the number of G or C bases at
positions 15 to 19. If there are only 18 base pairs, the value is
between 0 and 4.
[0216] With respect to the criterion GC.sub.total content, a number
from 0-30 will be ascribed, which correlates to the total number of
G and C nucleotides on the sense strand, excluding overhangs.
Without wishing to be bound by any one theory, it is postulated
that the significance of the GC content (as well as AU content at
positions 15-19, which is a parameter for formulas III-VII) relates
to the easement of the unwinding of a double-stranded siRNA duplex.
Duplex unwinding is believed to be crucial for siRNA functionality
in vivo and overall low internal stability, especially low internal
stability of the first unwound base pair is believed to be
important to maintain sufficient processivity of RISC
complex-induced duplex unwinding. If the duplex has 19 base pairs,
those at positions 15-19 on the sense strand will unwind first if
the molecule exhibits a sufficiently low internal stability at that
position. As persons skilled in the art are aware, RISC is a
complex of approximately twelve proteins; Dicer is one, but not the
only, helicase within this complex. Accordingly, although the GC
parameters are believed to relate to activity with Dicer, they are
also important for activity with other RISC proteins.
[0217] The value of the parameter Tm is 0 when there are no
internal repeats longer than (or equal to) four base pairs present
in the siRNA duplex; otherwise the value is 1. Thus for example, if
the sequence ACGUACGU, or any other four nucleotide (or more)
palindrome exists within the structure, the value will be one (1).
Alternatively if the structure ACGGACG, or any other 3 nucleotide
(or less) palindrome exists, the value will be zero (0).
[0218] The variable "X" refers to the number of times that the same
nucleotide occurs contiguously in a stretch of four or more units.
If there are, for example, four contiguous As in one part of the
sequence and elsewhere in the sequence four contiguous Cs, X=2.
Further, if there are two separate contiguous stretches of four of
the same nucleotides or eight or more of the same nucleotides in a
row, then X=2. However, X does not increase for five, six or seven
contiguous nucleotides.
[0219] Again, when applying Formula VIII or Formula IX to a given
mRNA, (the "target RNA" or "target molecule"), one may use a
computer program to evaluate the criteria for every sequence of
18-30 base pairs or only sequences of a fixed length, e.g., 19 base
pairs. Preferably the computer program is designed such that it
provides a report ranking of all of the potential siRNAs between 18
and 30 base pairs, ranked according to which sequences generate the
highest value. A higher value refers to a more efficient siRNA for
a particular target gene. The computer program that may be used,
may be developed in any computer language that is known to be
useful for scoring nucleotide sequences, or it may be developed
with the assistance of commercially available product such as
Microsoft's product net. Additionally, rather than run every
sequence through one and/or another formula, one may compare a
subset of the sequences, which may be desirable if for example only
a subset are available. For instance, it may be desirable to first
perform a BLAST (Basic Local Alignment Search Tool) search and to
identify sequences that have no homology to other targets.
Alternatively, it may be desirable to scan the sequence and to
identify regions of moderate GC context, then perform relevant
calculations using one of the above-described formulas on these
regions. These calculations can be done manually or with the aid of
a computer.
[0220] As with Formulas I-VII, either Formula VIII or Formula IX
may be used for a given mRNA target sequence. However, it is
possible that according to one or the other formula more than one
siRNA will have the same value. Accordingly, it is beneficial to
have a second formula by which to differentiate sequences. Formula
IX was derived in a similar fashion as Formula VIII, yet used a
larger data set and thus yields sequences with higher statistical
correlations to highly functional duplexes. The sequence that has
the highest value ascribed to it may be referred to as a "first
optimized duplex." The sequence that has the second highest value
ascribed to it may be referred to as a "second optimized duplex."
Similarly, the sequences that have the third and fourth highest
values ascribed to them may be referred to as a third optimized
duplex and a fourth optimized duplex, respectively. When more than
one sequence has the same value, each of them may, for example, be
referred to as first optimized duplex sequences or co-first
optimized duplexes.
[0221] SiRNA sequences identified using Formula VIII are contained
within the enclosed compact disks. The data included on the
enclosed compact disks is described more fully below. The sequences
identified by Formula VIII that are disclosed in the compacts disks
may be used in gene silencing applications.
[0222] It should be noted that for Formulas VIII and IX all of the
aforementioned criteria are identified as positions on the sense
strand when oriented in the 5' to 3' direction as they are
identified in connection with Formulas I-VII unless otherwise
specified.
[0223] Formulas I-IX, may be used to select or to evaluate one, or
more than one, siRNA in order to optimize silencing. Preferably, at
least two optimized siRNAs that have been selected according to at
least one of these formulas are used to silence a gene, more
preferably at least three and most preferably at least four. The
siRNAs may be used individually or together in a pool or kit.
Further, they may be applied to a cell simultaneously or
separately. Preferably, the at least two siRNAs are applied
simultaneously. Pools are particularly beneficial for many research
applications. However, for therapeutics, it may be more desirable
to employ a single hyperfunctional siRNA as described elsewhere in
this application.
[0224] When planning to conduct gene silencing, and it is necessary
to choose between two or more siRNAs, one should do so by comparing
the relative values when the siRNA are subjected to one of the
formulas above. In general a higher scored siRNA should be
used.
[0225] Useful applications include, but are not limited to, target
validation, gene functional analysis, research and drug discovery,
gene therapy and therapeutics. Methods for using siRNA in these
applications are well known to persons of skill in the art.
[0226] Because the ability of siRNA to function is dependent on the
sequence of the RNA and not the species into which it is
introduced, the present invention is applicable across a broad
range of species, including but not limited to all mammalian
species, such as humans, dogs, horses, cats, cows, mice, hamsters,
chimpanzees and gorillas, as well as other species and organisms
such as bacteria, viruses, insects, plants and C. elegans.
[0227] The present invention is also applicable for use for
silencing a broad range of genes, including but not limited to the
roughly 45,000 genes of a human genome, and has particular
relevance in cases where those genes are associated with diseases
such as diabetes, Alzheimer's, cancer, as well as all genes in the
genomes of the aforementioned organisms.
[0228] The siRNA selected according to the aforementioned criteria
or one of the aforementioned algorithms are also, for example,
useful in the simultaneous screening and functional analysis of
multiple genes and gene families using high throughput strategies,
as well as in direct gene suppression or silencing.
Development of the Algorithms
[0229] To identify siRNA sequence features that promote
functionality and to quantify the importance of certain currently
accepted conventional factors--such as G/C content and target site
accessibility--the inventors synthesized an siRNA panel consisting
of 270 siRNAs targeting three genes, Human Cyclophilin, Firefly
Luciferase, and Human DBI. In all three cases, siRNAs were directed
against specific regions of each gene. For Human Cyclophilin and
Firefly Luciferase, ninety siRNAs were directed against a 199 bp
segment of each respective mRNA. For DBI, 90 siRNAs were directed
against a smaller, 109 base pair region of the mRNA. The sequences
to which the siRNAs were directed are provided below.
[0230] It should be noted that in certain sequences, "t" is
present. This is because many databases contain information in this
manner. However, the t denotes a uracil residue in mRNA and siRNA.
Any algorithm will, unless otherwise specified, process at in a
sequence as a u. TABLE-US-00004 Human cyclophilin: 193-390, M60857
SEQ. ID NO. 29: gttccaaaaacagtggataattttgtggccttagctacaggagagaaagg
atttggctacaaaaacagcaaattccatcgtgtaatcaaggacttcatga
tccagggcggagacttcaccaggggagatggcacaggaggaaagagcatc
tacggtgagcgcttccccgatgagaacttcaaactgaagcactacgggcc tggctggg
[0231] TABLE-US-00005 Firefly luciferase: 1434-1631, U47298 (pGL3,
Promega) SEQ. ID NO. 30:
tgaacttcccgccgccgttgttgttttggagcacggaaagacgatgacgg
aaaaagagatcgtggattacgtcgccagtcaagtaacaaccgcgaaaaag
ttgcgcggaggagttgtgtttgtggacgaagtaccgaaaggtcttaccgg
aaaactcgacgcaagaaaaatcagagagatcctcataaaggccaagaagg
[0232] TABLE-US-00006 DBI, NM_020548 (202-310) (every position)
SEQ. ID NO. 0031:
acgggcaaggccaagtgggatgcctggaatgagctgaaagggacttccaa
ggaagatgccatgaaagcttacatcaacaaagtagaagagctaaagaaaa aatacggg
A list of the siRNAs appears in Table III (see Examples Section,
Example II)
[0233] The set of duplexes was analyzed to identify correlations
between siRNA functionality and other biophysical or thermodynamic
properties. When the siRNA panel was analyzed in functional and
non-functional subgroups, certain nucleotides were much more
abundant at certain positions in functional or non-functional
groups. More specifically, the frequency of each nucleotide at each
position in highly functional siRNA duplexes was compared with that
of nonfunctional duplexes in order to assess the preference for or
against any given nucleotide at every position. These analyses were
used to determine important criteria to be included in the siRNA
algorithms (Formulas VIII and IX).
[0234] The data set was also analyzed for distinguishing
biophysical properties of siRNAs in the functional group, such as
optimal percent of GC content, propensity for internal structures
and regional thermodynamic stability. Of the presented criteria,
several are involved in duplex recognition, RISC activation/duplex
unwinding, and target cleavage catalysis.
[0235] The original data set that was the source of the
statistically derived criteria is shown in FIG. 2. Additionally,
this figure shows that random selection yields siRNA duplexes with
unpredictable and widely varying silencing potencies as measured in
tissue culture using HEK293 cells. In the figure, duplexes are
plotted such that each x-axis tick-mark represents an individual
siRNA, with each subsequent siRNA differing in target position by
two nucleotides for Human Cyclophilin and Firefly Luciferase, and
by one nucleotide for Human DBI. Furthermore, the y-axis denotes
the level of target expression remaining after transfection of the
duplex into cells and subsequent silencing of the target.
[0236] SiRNA identified and optimized in this document work equally
well in a wide range of cell types. FIG. 3A shows the evaluation of
thirty siRNAs targeting the DBI gene in three cell lines derived
from different tissues. Each DBI siRNA displays very similar
functionality in HEK293 (ATCC, CRL-1573, human embryonic kidney),
HeLa (ATCC, CCL-2, cervical epithelial adenocarcinoma) and DU145
(HTB-81, prostate) cells as determined by the B-DNA assay. Thus,
siRNA functionality is determined by the primary sequence of the
siRNA and not by the intracellular environment. Additionally, it
should be noted that although the present invention provides for a
determination of the functionality of siRNA for a given target, the
same siRNA may silence more than one gene. For example, the
complementary sequence of the silencing siRNA may be present in
more than one gene. Accordingly, in these circumstances, it may be
desirable not to use the siRNA with highest SMARTscore.TM.. In such
circumstances, it may be desirable to use the siRNA with the next
highest SMARTscore.TM..
[0237] To determine the relevance of G/C content in siRNA function,
the G/C content of each duplex in the panel was calculated and the
functional classes of siRNAs (<F50, .gtoreq.F50, .gtoreq.F80,
.gtoreq.F95 where F refers to the percent gene silencing) were
sorted accordingly. The majority of the highly-functional siRNAs
(.gtoreq.F95) fell within the G/C content range of 36%-52% (FIG.
3B). Twice as many non-functional (<F50) duplexes fell within
the high G/C content groups (>57% GC content) compared to the
36%-52% group. The group with extremely low GC content (26% or
less) contained a higher proportion of non-functional siRNAs and no
highly-functional siRNAs. The G/C content range of 30%-52% was
therefore selected as Criterion I for siRNA functionality,
consistent with the observation that a G/C range 30%-70% promotes
efficient RNAi targeting. Application of this criterion alone
provided only a marginal increase in the probability of selecting
functional siRNAs from the panel: selection of F50 and F95 siRNAs
was improved by 3.6% and 2.2%, respectively. The siRNA panel
presented here permitted a more systematic analysis and
quantification of the importance of this criterion than that used
previously.
[0238] A relative measure of local internal stability is the A/U
base pair (bp) content; therefore, the frequency of A/U bp was
determined for each of the five terminal positions of the duplex
(5' sense (S)/5' antisense (AS)) of all siRNAs in the panel.
Duplexes were then categorized by the number of A/U bp in positions
1-5 and 15-19 of the sense strand. The thermodynamic flexibility of
the duplex 5'-end (positions 1-5; S) did not appear to correlate
appreciably with silencing potency, while that of the 3'-end
(positions 15-19; S) correlated with efficient silencing. No
duplexes lacking A/U bp in positions 15-19 were functional. The
presence of one A/U bp in this region conferred some degree of
functionality, but the presence of three or more A/Us was
preferable and therefore defined as Criterion II. When applied to
the test panel, only a marginal increase in the probability of
functional siRNA selection was achieved: a 1.8% and 2.3% increase
for F50 and F95 duplexes, respectively (Table IV).
[0239] The complementary strands of siRNAs that contain internal
repeats or palindromes may form internal fold-back structures.
These hairpin-like structures exist in equilibrium with the
duplexed form effectively reducing the concentration of functional
duplexes. The propensity to form internal hairpins and their
relative stability can be estimated by predicted melting
temperatures. High Tm reflects a tendency to form hairpin
structures. Lower Tm values indicate a lesser tendency to form
hairpins. When the functional classes of siRNAs were sorted by
T.sub.m (FIG. 3C), the following trends were identified: duplexes
lacking stable internal repeats were the most potent silencers (no
F95 duplex with predicted hairpin structure T.sub.m>60.degree.
C.). In contrast, about 60% of the duplexes in the groups having
internal hairpins with calculated T.sub.m values less than
20.degree. C. were F80. Thus, the stability of internal repeats is
inversely proportional to the silencing effect and defines
Criterion III (predicted hairpin structure
T.sub.m.ltoreq.20.degree. C.).
Sequence-Based Determinants of siRNA Functionality
[0240] When the siRNA panel was sorted into functional and
non-functional groups, the frequency of a specific nucleotide at
each position in a functional siRNA duplex was compared with that
of a nonfunctional duplex in order to assess the preference for or
against a certain nucleotide. FIG. 4 shows the results of these
queries and the subsequent resorting of the data set (from FIG. 2).
The data is separated into two sets: those duplexes that meet the
criteria, a specific nucleotide in a certain position--grouped on
the left (Selected) and those that do not--grouped on the right
(Eliminated). The duplexes are further sorted from most functional
to least functional with the y-axis of FIGS. 4A-E representing the
% expression i.e. the amount of silencing that is elicited by the
duplex (Note: each position on the X-axis represents a different
duplex). Statistical analysis revealed correlations between
silencing and several sequence-related properties of siRNAs. FIGS.
4A-4E and Table IV show quantitative analysis for the following
five sequence-related properties of siRNA: (4A) an A at position 19
of the sense strand; (4B) an A at position 3 of the sense strand;
(4C) a U at position 10 of the sense strand; (4D) a base other than
G at position 13 of the sense strand; and (4E) a base other than C
at position 19 of the sense strand.
[0241] When the siRNAs in the panel were evaluated for the presence
of an A at position 19 of the sense strand, the percentage of
non-functional duplexes decreased from 20% to 11.8%, and the
percentage of F95 duplexes increased from 21.7% to 29.4% (Table
IV). Thus, the presence of an A in this position defined Criterion
IV.
[0242] Another sequence-related property correlated with silencing
was the presence of an A in position 3 of the sense strand (FIG.
4B). Of the siRNAs with A3, 34.4% were F95, compared with 21.7%
randomly selected siRNAs. The presence of a U base in position 10
of the sense strand exhibited an even greater impact (FIG. 4C). Of
the duplexes in this group, 41.7% were F95. These properties became
criteria V and VI, respectively.
[0243] Two negative sequence-related criteria that were identified
also appear on FIG. 4. The absence of a G at position 13 of the
sense strand, conferred a marginal increase in selecting functional
duplexes (FIG. 4D). Similarly, lack of a C at position 19 of the
sense strand also correlated with functionality (FIG. 4E). Thus,
among functional duplexes, position 19 was most likely occupied by
A, and rarely occupied by C. These rules were defined as criteria
VII and VIII, respectively.
[0244] Application of each criterion individually provided marginal
but statistically significant increases in the probability of
selecting a potent siRNA. Although the results were informative,
the inventors sought to maximize potency and therefore consider
multiple criteria or parameters. Optimization is particularly
important when developing therapeutics. Interestingly, the
probability of selecting a functional siRNA based on each
thermodynamic criteria was 2%-4% higher than random, but 4%-8%
higher for the sequence-related determinates. Presumably, these
sequence-related increases reflect the complexity of the RNAi
mechanism and the multitude of protein-RNA interactions that are
involved in RNAi-mediated silencing. TABLE-US-00007 TABLE IV
Improvement Criterion % Functional over Random I. 30%-52% G/C
content <F50 16.4% -3.6% .gtoreq.F50 83.6% 3.6% .gtoreq.F80
60.4% 4.3% .gtoreq.F95 23.9% 2.2% II. At least 3 A/U bases at
positions <F50 18.2% -1.8% 15-19 of the sense strand .gtoreq.F50
81.8% 1.8% .gtoreq.F80 59.7% 3.6% .gtoreq.F95 24.0% 2.3% III.
Absence of internal repeats, <F50 16.7% -3.3% as measured by
T.sub.m of .gtoreq.F50 83.3% 3.3% secondary structure
.ltoreq.20.degree. C. .gtoreq.F80 61.1% 5.0% .gtoreq.F95 24.6% 2.9%
IV. An A base at position 19 <F50 11.8% -8.2% of the sense
strand .gtoreq.F50 88.2% 8.2% .gtoreq.F80 75.0% 18.9% .gtoreq.F95
29.4% 7.7% V. An A base at position 3 <F50 17.2% -2.8% of the
sense strand .gtoreq.F50 82.8% 2.8% .gtoreq.F80 62.5% 6.4%
.gtoreq.F95 34.4% 12.7% VI. A U base at position 10 <F50 13.9%
-6.1% of the sense strand .gtoreq.F50 86.1% 6.1% .gtoreq.F80 69.4%
13.3% .gtoreq.F95 41.7% 20% VII. A base other than C at <F50
18.8% -1.2% position 19 of the sense strand .gtoreq.F50 81.2% 1.2%
.gtoreq.F80 59.7% 3.6% .gtoreq.F95 24.2% 2.5% VIII. A base other
than G at <F50 15.2% -4.8% position 13 of the sense strand
.gtoreq.F50 84.8% 4.8% .gtoreq.F80 61.4% 5.3% .gtoreq.F95 26.5%
4.8%
The siRNA Selection Algorithm
[0245] In an effort to improve selection further, all identified
criteria, including but not limited to those listed in Table IV
were combined into the algorithms embodied in Formula VIII and
Formula IX. Each siRNA was then assigned a score (referred to as a
SMARTscore.TM.) according to the values derived from the formulas.
Duplexes that scored higher than 0 or 20, for Formulas VIII and IX,
respectively, effectively selected a set of functional siRNAs and
excluded all non-functional siRNAs. Conversely, all duplexes
scoring lower than 0 and 20 according to formulas VIII and IX,
respectively, contained some functional siRNAs but included all
non-functional siRNAs. A graphical representation of this selection
is shown in FIG. 5.
[0246] The methods for obtaining the seven criteria embodied in
Table IV are illustrative of the results of the process used to
develop the information for Formulas VIII and IX. Thus similar
techniques were used to establish the other variables and their
multipliers. As described above, basic statistical methods were use
to determine the relative values for these multipliers.
[0247] To determine the value for "Improvement over Random" the
difference in the frequency of a given attribute (e.g. GC content,
base preference) at a particular position is determined between
individual functional groups (e.g. <F50) and the total siRNA
population studied (e.g. 270 siRNA molecules selected randomly).
Thus, for instance, in Criterion I (30%-52% GC content) members of
the <F50 group were observed to have GC contents between 30-52%
in 16.4% of the cases. In contrast, the total group of 270 siRNAs
had GC contents in this range, 20% of the time. Thus for this
particular attribute, there is a small negative correlation between
30%-52% GC content and this functional group (i.e.
16.4%-20%=-3.6%). Similarly, for Criterion VI, (a "U" at position
10 of the sense strand), the >F95 group contained a "U" at this
position 41.7% of the time. In contrast, the total group of 270
siRNAs had a "U" at this position 21.7% of the time, thus the
improvement over random is calculated to be 20% (or
41.7%-21.7%).
Identifying the Average Internal Stability Profile of Strong
siRNA
[0248] In order to identify an internal stability profile that is
characteristic of strong siRNA, 270 different siRNAs derived from
the cyclophilin B, the diazepam binding inhibitor (DBI), and the
luciferase gene were individually transfected into HEK293 cells and
tested for their ability to induce RNAi of the respective gene.
Based on their performance in the in vivo assay, the sequences were
then subdivided into three groups, (i) >95% silencing; (ii)
80-95% silencing; and (iii) less than 50% silencing. Sequences
exhibiting 51-84% silencing were eliminated from further
consideration to reduce the difficulties in identifying relevant
thermodynamic patterns.
[0249] Following the division of siRNA into three groups, a
statistical analysis was performed on each member of each group to
determine the average internal stability profile (AISP) of the
siRNA. To accomplish this the Oligo 5.0 Primer Analysis Software
and other related statistical packages (e.g. Excel) were exploited
to determine the internal stability of pentamers using the nearest
neighbor method described by Freier et al., (1986) Improved
free-energy parameters for predictions of RNA duplex stability,
Proc Natl. Acad. Sci. U.S.A. 83(24): 9373-7. Values for each group
at each position were then averaged, and the resulting data were
graphed on a linear coordinate system with the Y-axis expressing
the .DELTA.G (free energy) values in kcal/mole and the X-axis
identifying the position of the base relative to the 5' end.
[0250] The results of the analysis identified multiple key regions
in siRNA molecules that were critical for successful gene
silencing. At the 3'-most end of the sense strand (5'antisense),
highly functional siRNA (>95% gene silencing, see FIG. 6A,
>F95) have a low internal stability (AISP of position
19=.about.-7.6 kcal/mol). In contrast low-efficiency siRNA (i.e.
those exhibiting less than 50% silencing, <F50) display a
distinctly different profile, having high .DELTA.G values
(.about.-8.4 kcal/mol) for the same position. Moving in a 5' (sense
strand) direction, the internal stability of highly efficient siRNA
rises (position 12=.about.-8.3 kcal/mole) and then drops again
(position 7=.about.-7.7 kcal/mol) before leveling off at a value of
approximately -8.1 kcal/mol for the 5' terminus. SiRNA with poor
silencing capabilities show a distinctly different profile. While
the AISP value at position 12 is nearly identical with that of
strong siRNAs, the values at positions 7 and 8 rise considerably,
peaking at a high of .about.-9.0 kcal/mol. In addition, at the 5'
end of the molecule the AISP profile of strong and weak siRNA
differ dramatically. Unlike the relatively storing values exhibited
by siRNA in the >95% silencing group, siRNAs that exhibit poor
silencing activity have weak AISP values (-7.6, -7.5, and -7.5
kcal/mol for positions 1, 2 and 3 respectively).
[0251] Overall the profiles of both strong and weak siRNAs form
distinct sinusoidal shapes that are roughly 180.degree.
out-of-phase with each other. While these thermodynamic
descriptions define the archetypal profile of a strong siRNA, it
will likely be the case that neither the .DELTA.G values given for
key positions in the profile or the absolute position of the
profile along the Y-axis (i.e. the .DELTA.G-axis) are absolutes.
Profiles that are shifted upward or downward (i.e. having on an
average, higher or lower values at every position) but retain the
relative shape and position of the profile along the X-axis can be
foreseen as being equally effective as the model profile described
here. Moreover, it is likely that siRNA that have strong or even
stronger gene-specific silencing effects might have exaggerated
.DELTA.G values (either higher or lower) at key positions. Thus,
for instance, it is possible that the 5'-most position of the sense
strand (position 19) could have .DELTA.G values of 7.4 kcal/mol or
lower and still be a strong siRNA if, for instance, a
G-C.fwdarw.G-T/U mismatch were substituted at position 19 and
altered duplex stability. Similarly, position 12 and position 7
could have values above 8.3 kcal/mol and below 7.7 kcal/mole,
respectively, without abating the silencing effectiveness of the
molecule. Thus, for instance, at position 12, a stabilizing
chemical modification (e.g. a chemical modification of the 2'
position of the sugar backbone) could be added that increases the
average internal stability at that position. Similarly, at position
7, mismatches similar to those described previously could be
introduced that would lower the .DELTA.G values at that
position.
[0252] Lastly, it is important to note that while functional and
non-functional siRNA were originally defined as those molecules
having specific silencing properties, both broader or more limiting
parameters can be used to define these molecules. As used herein,
unless otherwise specified, "non-functional siRNA" are defined as
those siRNA that induce less than 50% (<50%) target silencing,
"semi-functional siRNA" induce 50-79% target silencing, "functional
siRNA" are molecules that induce 80-95% gene silencing, and
"highly-functional siRNA" are molecules that induce great than 95%
gene silencing. These definitions are not intended to be rigid and
can vary depending upon the design and needs of the application.
For instance, it is possible that a researcher attempting to map a
gene to a chromosome using a functional assay, may identify an
siRNA that reduces gene activity by only 30%. While this level of
gene silencing may be "non-functional" for e.g. therapeutic needs,
it is sufficient for gene mapping purposes and is, under these uses
and conditions, "functional." For these reasons, functional siRNA
can be defined as those molecules having greater than 10%, 20%,
30%, 40%, 50%, 60%, 70%, 80%, or 90% silencing capabilities at 100
nM transfection conditions. Similarly, depending upon the needs of
the study and/or application, non-functional and semi-functional
siRNA can be defined as having different parameters. For instance,
semi-functional siRNA can be defined as being those molecules that
induce 20%, 30%, 40%, 50%, 60%, or 70% silencing at 100 nM
transfection conditions. Similarly, non-functional siRNA can be
defined as being those molecules that silence gene expression by
less than 70%, 60%, 50%, 40%, 30%, or less. Nonetheless, unless
otherwise stated, the descriptions stated in the "Definitions"
section of this text should be applied.
[0253] Functional attributes can be assigned to each of the key
positions in the AISP of strong siRNA. The low 5' (sense strand)
AISP values of strong siRNAs may be necessary for determining which
end of the molecule enters the RISC complex. In contrast, the high
and low AISP values observed in the central regions of the molecule
may be critical for siRNA-target mRNA interactions and product
release, respectively.
[0254] If the AISP values described above accurately define the
thermodynamic parameters of strong siRNA, it would be expected that
similar patterns would be observed in strong siRNA isolated from
nature. Natural siRNAs exist in a harsh, RNase-rich environment and
it can be hypothesized that only those siRNA that exhibit
heightened affinity for RISC (i.e. siRNA that exhibit an average
internal stability profile similar to those observed in strong
siRNA) would survive in an intracellular environment. This
hypothesis was tested using GFP-specific siRNA isolated from N.
benthamiana. Llave et al. (2002) Endogenous and
Silencing-Associated Small RNAs in Plants, The Plant Cell 14,
1605-1619, introduced long double-stranded GFP-encoding RNA into
plants and subsequently re-isolated GFP-specific siRNA from the
tissues. The AISP of fifty-nine of these GFP-siRNA were determined,
averaged, and subsequently plotted alongside the AISP profile
obtained from the cyclophilin B/DBI/luciferase siRNA having >90%
silencing properties (FIG. 6B). Comparison of the two groups show
that profiles are nearly identical. This finding validates the
information provided by the internal stability profiles and
demonstrates that: (1) the profile identified by analysis of the
cyclophilin B/DBI/luciferase siRNAs are not gene specific; and (2)
AISP values can be used to search for strong siRNAs in a variety of
species.
[0255] Both chemical modifications and base-pair mismatches can be
incorporated into siRNA to alter the duplex's AISP and
functionality. For instance, introduction of mismatches at
positions 1 or 2 of the sense strand destabilized the 5' end of the
sense strand and increases the functionality of the molecule (see
Luc, FIG. 7). Similarly, addition of 2'-O-methyl groups to
positions 1 and 2 of the sense strand can also alter the AISP and
(as a result) increase both the functionality of the molecule and
eliminate off-target effects that results from sense strand
homology with the unrelated targets (FIG. 8).
Rationale for Criteria in a Biological Context
[0256] The fate of siRNA in the RNAi pathway may be described in 5
major steps: (1) duplex recognition and pre-RISC complex formation;
(2) ATP-dependent duplex unwinding/strand selection and RISC
activation; (3) mRNA target identification; (4) mRNA cleavage, and
(5) product release (FIG. 1). Given the level of nucleic
acid-protein interactions at each step, siRNA functionality is
likely influenced by specific biophysical and molecular properties
that promote efficient interactions within the context of the
multi-component complexes. Indeed, the systematic analysis of the
siRNA test set identified multiple factors that correlate well with
functionality. When combined into a single algorithm, they proved
to be very effective in selecting active siRNAs.
[0257] The factors described here may also be predictive of key
functional associations important for each step in RNAi. For
example, the potential formation of internal hairpin structures
correlated negatively with siRNA functionality. Complementary
strands with stable internal repeats are more likely to exist as
stable hairpins thus decreasing the effective concentration of the
functional duplex form. This suggests that the duplex is the
preferred conformation for initial pre-RISC association. Indeed,
although single complementary strands can induce gene silencing,
the effective concentration required is at least two orders of
magnitude higher than that of the duplex form.
[0258] siRNA-pre-RISC complex formation is followed by an
ATP-dependent duplex unwinding step and "activation" of the RISC.
The siRNA functionality was shown to correlate with overall low
internal stability of the duplex and low internal stability of the
3' sense end (or differential internal stability of the 3' sense
compare to the 5' sense strand), which may reflect strand selection
and entry into the RISC. Overall duplex stability and low internal
stability at the 3' end of the sense strand were also correlated
with siRNA functionality. Interestingly, siRNAs with very high and
very low overall stability profiles correlate strongly with
non-functional duplexes. One interpretation is that high internal
stability prevents efficient unwinding while very low stability
reduces siRNA target affinity and subsequent mRNA cleavage by the
RISC.
[0259] Several criteria describe base preferences at specific
positions of the sense strand and are even more intriguing when
considering their potential mechanistic roles in target recognition
and mRNA cleavage. Base preferences for A at position 19 of the
sense strand but not C, are particularly interesting because they
reflect the same base preferences observed for naturally occurring
miRNA precursors. That is, among the reported miRNA precursor
sequences 75% contain a U at position 1 which corresponds to an A
in position 19 of the sense strand of siRNAs, while G was
under-represented in this same position for miRNA precursors. These
observations support the hypothesis that both miRNA precursors and
siRNA duplexes are processed by very similar if not identical
protein machinery. The functional interpretation of the
predominance of a U/A base pair is that it promotes flexibility at
the 5'antisense ends of both siRNA duplexes and miRNA precursors
and facilitates efficient unwinding and selective strand entrance
into an activated RISC.
[0260] Among the criteria associated with base preferences that are
likely to influence mRNA cleavage or possibly product release, the
preference for U at position 10 of the sense strand exhibited the
greatest impact, enhancing the probability of selecting an F80
sequence by 13.3%. Activated RISC preferentially cleaves target
mRNA between nucleotides 10 and 11 relative to the 5' end of the
complementary targeting strand. Therefore, it may be that U, the
preferred base for most endoribonucleases, at this position
supports more efficient cleavage. Alternatively, a U/A bp between
the targeting siRNA strand and its cognate target mRNA may create
an optimal conformation for the RISC-associated "slicing"
activity.
Pooling
[0261] According to another embodiment, the present invention
provides a pool of at least two siRNAs, preferably in the form of a
kit or therapeutic reagent, wherein one strand of each of the
siRNAs, the sense strand comprises a sequence that is substantially
similar to a sequence within a target mRNA. The opposite strand,
the antisense strand, will preferably comprise a sequence that is
substantially complementary to that of the target mRNA. More
preferably, one strand of each siRNA will comprise a sequence that
is identical to a sequence that is contained in the target mRNA.
Most preferably, each siRNA will be 19 base pairs in length, and
one strand of each of the siRNAs will be 100% complementary to a
portion of the target mRNA.
[0262] By increasing the number of siRNAs directed to a particular
target using a pool or kit, one is able both to increase the
likelihood that at least one siRNA with satisfactory functionality
will be included, as well as to benefit from additive or
synergistic effects. Further, when two or more siRNAs directed
against a single gene do not have satisfactory levels of
functionality alone, if combined, they may satisfactorily promote
degradation of the target messenger RNA and successfully inhibit
translation. By including multiple siRNAs in the system, not only
is the probability of silencing increased, but the economics of
operation are also improved when compared to adding different
siRNAs sequentially. This effect is contrary to the conventional
wisdom that the concurrent use of multiple siRNA will negatively
impact gene silencing (e.g. Holen, T. et al. (2003) "Similar
behavior of single strand and double strand siRNAs suggests they
act through a common RNAi pathway." NAR 31: 2401-21407).
[0263] In fact, when two siRNAs were pooled together, 54% of the
pools of two siRNAs induced more than 95% gene silencing. Thus, a
2.5-fold increase in the percentage of functionality was achieved
by randomly combining two siRNAs. Further, over 84% of pools
containing two siRNAs induced more than 80% gene silencing.
[0264] More preferably, the kit is comprised of at least three
siRNAs, wherein one strand of each siRNA comprises a sequence that
is substantially similar to a sequence of the target mRNA and the
other strand comprises a sequence that is substantially
complementary to the region of the target mRNA. As with the kit
that comprises at least two siRNAs, more preferably one strand will
comprise a sequence that is identical to a sequence that is
contained in the mRNA and another strand that is 100% complementary
to a sequence that is contained in the mRNA. During experiments,
when three siRNAs were combined together, 60% of the pools induced
more than 95% gene silencing and 92% of the pools induced more than
80% gene silencing.
[0265] Further, even more preferably, the kit is comprised of at
least four siRNAs, wherein one strand of each siRNA comprises a
sequence that is substantially similar to a region of the sequence
of the target mRNA, and the other strand comprises a sequence that
is substantially complementary to the region of the target mRNA. As
with the kit or pool that comprises at least two siRNAs, more
preferably one strand of each of the siRNA duplexes will comprise a
sequence that is identical to a sequence that is contained in the
mRNA, and another strand that is 100% complementary to a sequence
that is contained in the mRNA.
[0266] Additionally, kits and pools with at least five, at least
six, and at least seven siRNAs may also be useful with the present
invention. For example, pools of five siRNA induced 95% gene
silencing with 77% probability and 80% silencing with 98.8%
probability. Thus, pooling of siRNAs together can result in the
creation of a target-specific silencing reagent with almost a 99%
probability of being functional. The fact that such high levels of
success are achievable using such pools of siRNA, enables one to
dispense with costly and time-consuming target-specific validation
procedures.
[0267] For this embodiment, as well as the other aforementioned
embodiments, each of the siRNAs within a pool will preferably
comprise between 18 and 30 base pairs, more preferably between 18
and 25 base pairs, and most preferably 19 base pairs. Within each
siRNA, preferably at least 18 contiguous bases of the antisense
strand will be 100% complementary to the target mRNA. More
preferably, at least 19 contiguous bases of the antisense strand
will be 100% complementary to the target mRNA. Additionally, there
may be overhangs on either the sense strand or the antisense
strand, and these overhangs may be at either the 5' end or the 3'
end of either of the strands, for example there may be one or more
overhangs of 1-6 bases. When overhangs are present, they are not
included in the calculation of the number of base pairs. The two
nucleotide 3' overhangs mimic natural siRNAs and are commonly used
but are not essential. Preferably, the overhangs should consist of
two nucleotides, most often dTdT or UU at the 3' end of the sense
and antisense strand that are not complementary to the target
sequence. The siRNAs may be produced by any method that is now
known or that comes to be known for synthesizing double stranded
RNA that one skilled in the art would appreciate would be useful in
the present invention. Preferably, the siRNAs will be produced by
Dharmacon's proprietary ACE.RTM. technology. However, other methods
for synthesizing siRNAs are well known to persons skilled in the
art and include, but are not limited to, any chemical synthesis of
RNA oligonucleotides, ligation of shorter oligonucleotides, in
vitro transcription of RNA oligonucleotides, the use of vectors for
expression within cells, recombinant Dicer products and PCR
products.
[0268] The siRNA duplexes within the aforementioned pools of siRNAs
may correspond to overlapping sequences within a particular mRNA,
or non-overlapping sequences of the mRNA. However, preferably they
correspond to non-overlapping sequences. Further, each siRNA may be
selected randomly, or one or more of the siRNA may be selected
according to the criteria discussed above for maximizing the
effectiveness of siRNA.
[0269] Included in the definition of siRNAs are siRNAs that contain
substituted and/or labeled nucleotides that may, for example, be
labeled by radioactivity, fluorescence or mass. The most common
substitutions are at the 2' position of the ribose sugar, where
moieties such as H (hydrogen) F, NH.sub.3, OCH.sub.3 and other
O-alkyl, alkenyl, alkynyl, and orthoesters, may be substituted, or
in the phosphorous backbone, where sulfur, amines or hydrocarbons
may be substituted for the bridging of non-bridging atoms in the
phosphodiester bond. Examples of modified siRNAs are explained more
fully in commonly assigned U.S. patent application Ser. No.
10/613,077, filed Jul. 1, 2003, which is incorporated by reference
herein.
[0270] Additionally, as noted above, the cell type into which the
siRNA is introduced may affect the ability of the siRNA to enter
the cell; however, it does not appear to affect the ability of the
siRNA to function once it enters the cell. Methods for introducing
double-stranded RNA into various cell types are well known to
persons skilled in the art.
[0271] As persons skilled in the art are aware, in certain species,
the presence of proteins such as RdRP, the RNA-dependent RNA
polymerase, may catalytically enhance the activity of the siRNA.
For example, RdRP propagates the RNAi effect in C. elegans and
other non-mammalian organisms. In fact, in organisms that contain
these proteins, the siRNA may be inherited. Two other proteins that
are well studied and known to be a part of the machinery are
members of the Argonaute family and Dicer, as well as their
homologues. There is also initial evidence that the RISC complex
might be associated with the ribosome so the more efficiently
translated mRNAs will be more susceptible to silencing than
others.
[0272] Another very important factor in the efficacy of siRNA is
mRNA localization. In general, only cytoplasmic mRNAs are
considered to be accessible to RNAi to any appreciable degree.
However, appropriately designed siRNAs, for example, siRNAs
modified with internucleotide linkages, may be able to cause
silencing by acting in the nucleus. Examples of these types of
modifications are described in commonly assigned U.S. patent
application Ser. Nos. 10/431,027 and 10/613,077, each of which is
incorporated by reference herein.
[0273] As described above, even when one selects at least two
siRNAs at random, the effectiveness of the two may be greater than
one would predict based on the effectiveness of two individual
siRNAs. This additive or synergistic effect is particularly
noticeable as one increases to at least three siRNAs, and even more
noticeable as one moves to at least four siRNAs. Surprisingly, the
pooling of the non-functional and semi-functional siRNAs,
particularly more than five siRNAs, can lead to a silencing mixture
that is as effective if not more effective as any one particular
functional siRNA.
[0274] Within the kit of the present invention, preferably each
siRNA will be present in a concentration of between 0.001 and 200
.mu.M, more preferably between 0.01 and 200 nM, and most preferably
between 0.1 and 10 nM.
[0275] In addition to preferably comprising at least four or five
siRNAs, the kit of the present invention will also preferably
comprise a buffer to keep the siRNA duplex stable. Persons skilled
in the art are aware of buffers suitable for keeping siRNA stable.
For example, the buffer may be comprised of 100 mM KCl, 30 mM
HEPES-pH 7.5, and 1 mM MgCl.sub.2. Alternatively, kits might
contain complementary strands that contain any one of a number of
chemical modifications (e.g. a 2'-O-ACE) that protect the agents
from degradation by nucleases. In this instance, the user may (or
may not) remove the modifying protective group (e.g. deprotect)
before annealing the two complementary strands together.
[0276] By way of example, the kit may be organized such that pools
of siRNA duplexes are provided on an array or microarray of wells
or drops for a particular gene set or for unrelated genes. The
array may, for example, be in 96 wells, 384 wells or 1284 wells
arrayed in a plastic plate or on a glass slide using techniques now
known or that come to be known to persons skilled in the art.
Within an array, preferably there will be controls such as
functional anti-lamin A/C, cyclophilin and two siRNA duplexes that
are not specific to the gene of interest.
[0277] In order to ensure stability of the siRNA pools prior to
usage, they may be retained in lyophilized form at minus twenty
degrees (-20.degree. C.) until they are ready for use. Prior to
usage, they should be resuspended; however, even once resuspended,
for example, in the aforementioned buffer, they should be kept at
minus twenty degrees, (-20.degree. C.) until used. The
aforementioned buffer, prior to use, may be stored at approximately
4.degree. C. or room temperature. Effective temperatures at which
to conduct transfections are well known to persons skilled in the
art and include for example, room temperature.
[0278] The kit may be applied either in vivo or in vitro.
Preferably, the siRNA of the pools or kits is applied to a cell
through transfection, employing standard transfection protocols.
These methods are well known to persons skilled in the art and
include the use of lipid-based carriers, electroporation, cationic
carriers, and microinjection. Further, one could apply the present
invention by synthesizing equivalent DNA sequences (either as two
separate, complementary strands, or as hairpin molecules) instead
of siRNA sequences and introducing them into cells through vectors.
Once in the cells, the cloned DNA could be transcribed, thereby
forcing the cells to generate the siRNA. Examples of vectors
suitable for use with the present application include but are not
limited to the standard transient expression vectors, adenoviruses,
retroviruses, lentivirus-based vectors, as well as other
traditional expression vectors. Any vector that has an adequate
siRNA expression and procession module may be used. Furthermore,
certain chemical modifications to siRNAs, including but not limited
to conjugations to other molecules, may be used to facilitate
delivery. For certain applications it may be preferable to deliver
molecules without transfection by simply formulating in a
physiological acceptable solution.
[0279] This embodiment may be used in connection with any of the
aforementioned embodiments. Accordingly, the sequences within any
pool may be selected by rational design.
Multigene Silencing
[0280] In addition to developing kits that contain multiple siRNA
directed against a single gene, another embodiment includes the use
of multiple siRNA targeting multiple genes. Multiple genes may be
targeted through the use of high- or hyper-functional siRNA. High-
or hyper-functional siRNA that exhibit increased potency, require
lower concentrations to induce desired phenotypic (and thus
therapeutic) effects. This circumvents RISC saturation. It
therefore reasons that if lower concentrations of a single siRNA
are needed for knockout or knockdown expression of one gene, then
the remaining (uncomplexed) RISC will be free and available to
interact with siRNA directed against two, three, four, or more,
genes. Thus in this embodiment, the authors describe the use of
highly functional or hyper-functional siRNA to knock out three
separate genes. More preferably, such reagents could be combined to
knockout four distinct genes. Even more preferably, highly
functional or hyperfunctional siRNA could be used to knock out five
distinct genes. Most preferably, siRNA of this type could be used
to knockout or knockdown the expression of six or more genes.
Hyperfunctional siRNA
[0281] The term hyperfunctional siRNA (hf-siRNA) describes a subset
of the siRNA population that induces RNAi in cells at low- or
sub-nanomolar concentrations for extended periods of time. These
traits, heightened potency and extended longevity of the RNAi
phenotype, are highly attractive from a therapeutic standpoint.
Agents having higher potency require lesser amounts of the molecule
to achieve the desired physiological response, thus reducing the
probability of side effects due to "off-target" interference. In
addition to the potential therapeutic benefits associated with
hyperfunctional siRNA, hf-siRNA are also desirable from an economic
position. Hyperfunctional siRNA may cost less on a per-treatment
basis, thus reducing the overall expenditures to both the
manufacturer and the consumer.
[0282] Identification of hyperfunctional siRNA involves multiple
steps that are designed to examine an individual siRNA agent's
concentration- and/or longevity-profiles. In one non-limiting
example, a population of siRNA directed against a single gene are
first analyzed using the previously described algorithm (Formula
VIII). Individual siRNA are then introduced into a test cell line
and assessed for the ability to degrade the target mRNA. It is
important to note that when performing this step it is not
necessary to test all of the siRNA. Instead, it is sufficient to
test only those siRNA having the highest SMARTscores.TM. (i.e.
SMARTscore.TM. >-10). Subsequently, the gene silencing data is
plotted against the SMARTscores.TM. (see FIG. 9). SiRNA that (1)
induce a high degree of gene silencing (i.e. they induce greater
than 80% gene knockdown) and (2) have superior SMARTscores.TM.
(i.e. a SMARTscore.TM. of >-10, suggesting a desirable average
internal stability profile) are selected for further investigations
designed to better understand the molecule's potency and longevity.
In one, non-limiting study dedicated to understanding a molecule's
potency, an siRNA is introduced into one (or more) cell types in
increasingly diminishing concentrations (e.g. 3.0.fwdarw.0.3 nM).
Subsequently, the level of gene silencing induced by each
concentration is examined and siRNA that exhibit hyperfunctional
potency (i.e. those that induce 80% silencing or greater at e.g.
picomolar concentrations) are identified. In a second study, the
longevity profiles of siRNA having high (>-10) SMARTscoreS.TM.
and greater than 80% silencing are examined. In one non-limiting
example of how this is achieved, siRNA are introduced into a test
cell line and the levels of RNAi are measured over an extended
period of time (e.g. 24-168 hrs). SiRNAs that exhibit strong RNA
interference patterns (i.e. >80% interference) for periods of
time greater than, e.g., 120 hours are thus identified. Studies
similar to those described above can be performed on any and all of
the >10.sup.6 siRNA included in this document to further define
the most functional molecule for any given gene. Molecules
possessing one or both properties (extended longevity and
heightened potency) are labeled "hyperfunctional siRNA," and
earmarked as candidates for future therapeutic studies.
[0283] While the example(s) given above describe one means by which
hyperfunctional siRNA can be isolated, neither the assays
themselves nor the selection parameters used are rigid and can vary
with each family of siRNA. Families of siRNA include siRNAs
directed against a single gene, or directed against a related
family of genes.
[0284] The highest quality siRNA achievable for any given gene may
vary considerably. Thus, for example, in the case of one gene (gene
X), rigorous studies such as those described above may enable the
identification of an siRNA that, at picomolar concentrations,
induces 99.sup.+% silencing for a period of 10 days. Yet identical
studies of a second gene (gene Y) may yield an siRNA that at high
nanomolar concentrations (e.g. 100 nM) induces only 75% silencing
for a period of 2 days. Both molecules represent the very optimum
siRNA for their respective gene targets and therefore are
designated "hyperfunctional." Yet due to a variety of factors
including but not limited to target concentration, siRNA stability,
cell type, off-target interference, and others, equivalent levels
of potency and longevity are not achievable. Thus, for these
reasons, the parameters described in the before mentioned assays,
can vary. While the initial screen selected siRNA that had
SMARTscores.TM.above -10 and a gene silencing capability of greater
than 80%, selections that have stronger (or weaker) parameters can
be implemented. Similarly, in the subsequent studies designed to
identify molecules with high potency and longevity, the desired
cutoff criteria (i.e. the lowest concentration that induces a
desirable level of interference, or the longest period of time that
interference can be observed) can vary. The experimentation
subsequent to application of the rational criteria of this
application is significantly reduced where one is trying to obtain
a suitable hyperfunctional siRNA for, for example, therapeutic use.
When, for example, the additional experimentation of the type
described herein is applied by one skilled in the art with this
disclosure in hand, a hyperfunctional siRNA is readily
identified.
[0285] The siRNA may be introduced into a cell by any method that
is now known or that comes to be known and that from reading this
disclosure, persons skilled in the art would determine would be
useful in connection with the present invention in enabling siRNA
to cross the cellular membrane. These methods include, but are not
limited to, any manner of transfection, such as for example
transfection employing DEAE-Dextran, calcium phosphate, cationic
lipids/liposomes, micelles, manipulation of pressure,
microinjection, electroporation, immunoporation, use of vectors
such as viruses, plasmids, cosmids, bacteriophages, cell fusions,
and coupling of the polynucleotides to specific conjugates or
ligands such as antibodies, antigens, or receptors, passive
introduction, adding moieties to the siRNA that facilitate its
uptake, and the like.
[0286] Having described the invention with a degree of
particularity, examples will now be provided. These examples are
not intended to and should not be construed to limit the scope of
the claims in any way.
EXAMPLES
General Techniques and Nomenclatures
[0287] siRNA nomenclature. All siRNA duplexes are referred to by
sense strand. The first nucleotide of the 5'-end of the sense
strand is position 1, which corresponds to position 19 of the
antisense strand for a 19-mer. In most cases, to compare results
from different experiments, silencing was determined by measuring
specific transcript mRNA levels or enzymatic activity associated
with specific transcript levels, 24 hours post-transfection, with
siRNA concentrations held constant at 100 nM. For all experiments,
unless otherwise specified transfection efficiency was ensured to
be over 95%, and no detectable cellular toxicity was observed. The
following system of nomenclature was used to compare and report
siRNA-silencing functionality: "F" followed by the degree of
minimal knockdown. For example, F50 signifies at least 50%
knockdown, F80 means at least 80%, and so forth. For this study,
all sub-F50 siRNAs were considered non-functional.
[0288] Cell culture and transfection. 96-well plates are coated
with 50 .mu.l of 50 mg/ml poly-L-lysine (Sigma) for 1 hr, and then
washed 3.times. with distilled water before being dried for 20 min.
HEK293 cells or HEK293Lucs or any other cell type of interest are
released from their solid support by trypsinization, diluted to
3.5.times.10.sup.5 cells/ml, followed by the addition of 100 .mu.L
of cells/well. Plates are then incubated overnight at 37.degree.
C., 5% CO.sub.2. Transfection procedures can vary widely depending
on the cell type and transfection reagents. In one non-limiting
example, a transfection mixture consisting of 2 mL Opti-MEM I
(Gibco-BRL), 80 .mu.l Lipofectamine 2000 (Invitrogen), 15 .mu.L
SUPERNasin at 20 U/.mu.l (Ambion), and 1.5 .mu.l of reporter gene
plasmid at 1 .mu.g/.mu.l is prepared in 5-ml polystyrene round
bottom tubes. 100 .mu.l of transfection reagent is then combined
with 100 .mu.l of siRNAs in polystyrene deep-well titer plates
(Beckman) and incubated for 20 to 30 min at room temp. 550 .mu.l of
Opti-MEM is then added to each well to bring the final siRNA
concentration to 100 nM. Plates are then sealed with parafilm and
mixed. Media is removed from HEK293 cells and replaced with 95
.mu.l of transfection mixture. Cells are incubated overnight at
37.degree. C., 5% CO.sub.2.
[0289] Quantification of gene knockdown. A variety of
quantification procedures can be used to measure the level of
silencing induced by siRNA or siRNA pools. In one non-limiting
example: to measure mRNA levels 24 hrs post-transfection,
QuantiGene branched-DNA (bDNA) kits (Bayer) (Wang, et al,
Regulation of insulin preRNA splicing by glucose. Proc Natl Acad
Sci 1997, 94:4360.) are used according to manufacturer
instructions. To measure luciferase activity, media is removed from
HEK293 cells 24 hrs post-transfection, and 50 .mu.l of Steady-GLO
reagent (Promega) is added. After 5 min, plates are analyzed on a
plate reader.
Example I
Sequences Used to Develop the Algorithm
[0290] Anti-Firefly and anti-Cyclophilin siRNAs panels (FIGS. 5A,
B) sorted according to using Formula VIII predicted values. All
siRNAs scoring more than 0 (formula VIII) and more then 20 (formula
IX) are fully functional. All ninety sequences for each gene (and
DBI) appear below in Table III. TABLE-US-00008 TABLE III Cyclo 1
SEQ. ID 0032 GUUCCAAAAACAGUGGAUA Cyclo 2 SEQ. ID 0033
UCCAAAAACAGUGGAUAAU Cyclo 3 SEQ. ID 0034 CAAAAACAGUGGAUAAUUU Cyclo
4 SEQ. ID 0035 AAAACAGUGGAUAAUUUUG Cyclo 5 SEQ. ID 0036
AACAGUGGAUAAUUUUGUG Cyclo 6 SEQ. ID 0037 CAGUGGAUAAUUUUGUGGC Cyclo
7 SEQ. ID 0038 GUGGAUAAUUUUGUGGCCU Cyclo 8 SEQ. ID 0039
GGAUAAUUUUGUGGCCUUA Cyclo 9 SEQ. ID 0040 AUAAUUUUGUGGCCUUAGC Cyclo
10 SEQ. ID 0041 AAUUUUGUGGCCUUAGCUA Cyclo 11 SEQ. ID 0042
UUUUGUGGCCUUAGCUACA Cyclo 12 SEQ. ID 0043 UUGUGGCCUUAGCUACAGG Cyclo
13 SEQ. ID 0044 GUGGCCUUAGCUACAGGAG Cyclo 14 SEQ. ID 0045
GGCCUUAGCUACAGGAGAG Cyclo 15 SEQ. ID 0046 CCUUAGCUACAGGAGAGAA Cyclo
16 SEQ. ID 0047 UUAGCUACAGGAGAGAAAG Cyclo 17 SEQ. ID 0048
AGCUACAGGAGAGAAAGGA Cyclo 18 SEQ. ID 0049 CUACAGGAGAGAAAGGAUU Cyclo
19 SEQ. ID 0050 ACAGGAGAGAAAGGAUUUG Cyclo 20 SEQ. ID 0051
AGGAGAGAAAGGAUUUGGC Cyclo 21 SEQ. ID 0052 GAGAGAAAGGAUUUGGCUA Cyclo
22 SEQ. ID 0053 GAGAAAGGAUUUGGCUACA Cyclo 23 SEQ. ID 0054
GAAAGGAUUUGGCUACAAA Cyclo 24 SEQ. ID 0055 AAGGAUUUGGCUACAAAAA Cyclo
25 SEQ. ID 0056 GGAUUUGGCUACAAAAACA Cyclo 26 SEQ. ID 0057
AUUUGGCUACAAAAACAGC Cyclo 27 SEQ. ID 0058 UUGGCUACAAAAACAGCAA Cyclo
28 SEQ. ID 0059 GGCUACAAAAACAGCAAAU Cyclo 29 SEQ. ID 0060
CUACAAAAACAGCAAAUUC Cyclo 30 SEQ. ID 0061 ACAAAAACAGCAAAUUCCA Cyclo
31 SEQ. ID 0062 AAAAACAGCAAAUUCCAUC Cyclo 32 SEQ. ID 0063
AAACAGCAAAUUCCAUCGU Cyclo 33 SEQ. ID 0064 ACAGCAAAUUCCAUCGUGU Cyclo
34 SEQ. ID 0065 AGCAAAUUCCAUCGUGUAA Cyclo 35 SEQ. ID 0066
CAAAUUCCAUCGUGUAAUC Cyclo 36 SEQ. ID 0067 AAUUCCAUCGUGUAAUCAA Cyclo
37 SEQ. ID 0068 UUCCAUCGUGUAAUCAAGG Cyclo 38 SEQ. ID 0069
CCAUCGUGUAAUCAAGGAC Cyclo 39 SEQ. ID 0070 AUCGUGUAAUCAAGGACUU Cyclo
40 SEQ. ID 0071 CGUGUAAUCAAGGACUUCA Cyclo 41 SEQ. ID 0072
UGUAAUCAAGGACUUCAUG Cyclo 42 SEQ. ID 0073 UAAUCAAGGACUUCAUGAU Cyclo
43 SEQ. ID 0074 AUCAAGGACUUCAUGAUCC Cyclo 44 SEQ. ID 0075
CAAGGACUUCAUGAUCCAG Cyclo 45 SEQ. ID 0076 AGGACUUCAUGAUCCAGGG Cyclo
46 SEQ. ID 0077 GACUUCAUGAUCCAGGGCG Cyclo 47 SEQ. ID 0078
CUUCAUGAUCCAGGGCGGA Cyclo 48 SEQ. ID 0079 UCAUGAUCCAGGGCGGAGA Cyclo
49 SEQ. ID 0080 AUGAUCCAGGGCGGAGACU Cyclo 50 SEQ. ID 0081
GAUCCAGGGCGGAGACUUC Cyclo 51 SEQ. ID 0082 UCCAGGGCGGAGACUUCAC Cyclo
52 SEQ. ID 0083 CAGGGCGGAGACUUCACCA Cyclo 53 SEQ. ID 0084
GGGCGGAGACUUCACCAGG Cyclo 54 SEQ. ID 0085 GCGGAGACUUCACCAGGGG Cyclo
55 SEQ. ID 0086 GGAGACUUCACCAGGGGAG Cyclo 56 SEQ. ID 0087
AGACUUCACCAGGGGAGAU Cyclo 57 SEQ. ID 0088 ACUUCACCAGGGGAGAUGG Cyclo
58 SEQ. ID 0089 UUCACCAGGGGAGAUGGCA Cyclo 59 SEQ. ID 0090
CACCAGGGGAGAUGGCACA Cyclo 60 SEQ. ID 0091 CCAGGGGAGAUGGCACAGG Cyclo
61 SEQ. ID 0092 AGGGGAGAUGGCACAGGAG Cyclo 62 SEQ. ID 0093
GGGAGAUGGCACAGGAGGA Cyclo 63 SEQ. ID 0437 GAGAUGGCACAGGAGGAAA Cyclo
64 SEQ. ID 0095 GAUGGCACAGGAGGAAAGA Cyclo 65 SEQ. ID 0094
UGGCACAGGAGGAAAGAGC Cyclo 66 SEQ. ID 0096 GCACAGGAGGAAAGAGCAU Cyclo
67 SEQ. ID 0097 ACAGGAGGAAAGAGCAUCU Cyclo 68 SEQ. ID 0098
AGGAGGAAAGAGCAUCUAC Cyclo 69 SEQ. ID 0099 GAGGAAAGAGCAUCUACGG Cyclo
70 SEQ. ID 0100 GGAAAGAGCAUCUACGGUG Cyclo 71 SEQ. ID 0101
AAAGAGCAUCUACGGUGAG Cyclo 72 SEQ. ID 0102 AGAGCAUCUACGGUGAGCG Cyclo
73 SEQ. ID 0103 AGCAUCUACGGUGAGCGCU Cyclo 74 SEQ. ID 0104
CAUCUACGGUGAGCGCUUC Cyclo 75 SEQ. ID 0105 UCUACGGUGAGCGCUUCCC Cyclo
76 SEQ. ID 0106 UACGGUGAGCGCUUCCCCG Cyclo 77 SEQ. ID 0107
CGGUGAGCGCUUCCCCGAU Cyclo 78 SEQ. ID 0108 GUGAGCGCUUCCCCGAUGA Cyclo
79 SEQ. ID 0109 GAGCGCUUCCCCGAUGAGA Cyclo 80 SEQ. ID 0110
GCGCUUCCCCGAUGAGAAC Cyclo 81 SEQ. ID 0111 GCUUCCCCGAUGAGAACUU Cyclo
82 SEQ. ID 0112 UUCCCCGAUGAGAACUUCA Cyclo 83 SEQ. ID 0113
CCCCGAUGAGAACUUCAAA Cyclo 84 SEQ. ID 0114 CCGAUGAGAACUUCAAACU Cyclo
85 SEQ. ID 0115 GAUGAGAACUUCAAACUGA Cyclo 86 SEQ. ID 0116
UGAGAACUUCAAACUGAAG Cyclo 87 SEQ. ID 0117 AGAACUUCAAACUGAAGCA Cyclo
88 SEQ. ID 0118 AACUUCAAACUGAAGCACU Cyclo 89 SEQ. ID 0119
CUUCAAACUGAAGCACUAC Cyclo 90 SEQ. ID 0120 UCAAACUGAAGCACUACGG DB 1
SEQ. ID 0121 ACGGGCAAGGCCAAGUGGG DB 2 SEQ. ID 0122
CGGGCAAGGCCAAGUGGGA DB 3 SEQ. ID 0123 GGGCAAGGCCAAGUGGGAU DB 4 SEQ.
ID 0124 GGCAAGGCCAAGUGGGAUG DB 5 SEQ. ID 0125 GCAAGGCCAAGUGGGAUGC
DB 6 SEQ. ID 0126 CAAGGCCAAGUGGGAUGCC DB 7 SEQ. ID 0127
AAGGCCAAGUGGGAUGCCU DB 8 SEQ. ID 0128 AGGCCAAGUGGGAUGCCUG DB 9 SEQ.
ID 0129 GGCCAAGUGGGAUGCCUGG DB 10 SEQ. ID 0130 GCCAAGUGGGAUGCCUGGA
DB 11 SEQ. ID 0131 CCAAGUGGGAUGCCUGGAA DB 12 SEQ. ID 0132
CAAGUGGGAUGCCUGGAAU DB 13 SEQ. ID 0133 AAGUGGGAUGCCUGGAAUG DB 14
SEQ. ID 0134 AGUGGGAUGCCUGGAAUGA DB 15 SEQ. ID 0135
GUGGGAUGCCUGGAAUGAG DB 16 SEQ. ID 0136 UGGGAUGCCUGGAAUGAGC DB 17
SEQ. ID 0137 GGGAUGCCUGGAAUGAGCU DB 18 SEQ. ID 0138
GGAUGCCUGGAAUGAGCUG DB 19 SEQ. ID 0139 GAUGCCUGGAAUGAGCUGA DB 20
SEQ. ID 0140 AUGCCUGGAAUGAGCUGAA DB 21 SEQ. ID 0141
UGCCUGGAAUGAGCUGAAA DB 22 SEQ. ID 0142 GCCUGGAAUGAGCUGAAAG DB 23
SEQ. ID 0143 CCUGGAAUGAGCUGAAAGG DB 24 SEQ. ID 0144
CUGGAAUGAGCUGAAAGGG DB 25 SEQ. ID 0145 UGGAAUGAGCUGAAAGGGA DB 26
SEQ. ID 0146 GGAAUGAGCUGAAAGGGAC DB 27 SEQ. ID 0147
GAAUGAGCUGAAAGGGACU DB 28 SEQ. ID 0148 AAUGAGCUGAAAGGGACUU DB 29
SEQ. ID 0149 AUGAGCUGAAAGGGACUUC DB 30 SEQ. ID 0150
UGAGCUGAAAGGGACUUCC DB 31 SEQ. ID 0151 GAGCUGAAAGGGACUUCCA DB 32
SEQ. ID 0152 AGCUGAAAGGGACUUCCAA
DB 33 SEQ. ID 0153 GCUGAAAGGGACUUCCAAG DB 34 SEQ. ID 0154
CUGAAAGGGACUUCCAAGG DB 35 SEQ. ID 0155 UGAAAGGGACUUCCAAGGA DB 36
SEQ. ID 0156 GAAAGGGACUUCCAAGGAA DB 37 SEQ. ID 0157
AAAGGGACUUCCAAGGAAG DB 38 SEQ. ID 0158 AAGGGACUUCCAAGGAAGA DB 39
SEQ. ID 0159 AGGGACUUCCAAGGAAGAU DB 40 SEQ. ID 0160
GGGACUUCCAAGGAAGAUG DB 41 SEQ. ID 0161 GGACUUCCAAGGAAGAUGC DB 42
SEQ. ID 0162 GACUUCCAAGGAAGAUGCC DB 43 SEQ. ID 0163
ACUUCCAAGGAAGAUGCCA DB 44 SEQ. ID 0164 CUUCCAAGGAAGAUGCCAU DB 45
SEQ. ID 0165 UUCCAAGGAAGAUGCCAUG DB 46 SEQ. ID 0166
UCCAAGGAAGAUGCCAUGA DB 47 SEQ. ID 0167 CCAAGGAAGAUGCCAUGAA DB 48
SEQ. ID 0168 CAAGGAAGAUGCCAUGAAA DB 49 SEQ. ID 0169
AAGGAAGAUGCCAUGAAAG DB 50 SEQ. ID 0170 AGGAAGAUGCCAUGAAAGC DB 51
SEQ. ID 0171 GGAAGAUGCCAUGAAAGCU DB 52 SEQ. ID 0172
GAAGAUGCCAUGAAAGCUU DB 53 SEQ. ID 0173 AAGAUGCCAUGAAAGCUUA DB 54
SEQ. ID 0174 AGAUGCCAUGAAAGCUUAC DB 55 SEQ. ID 0175
GAUGCCAUGAAAGCUUACA DB 56 SEQ. ID 0176 AUGCCAUGAAAGCUUACAU DB 57
SEQ. ID 0177 UGCCAUGAAAGCUUACAUC DB 58 SEQ. ID 0178
GCCAUGAAAGCUUACAUCA DB 59 SEQ. ID 0179 CCAUGAAAGCUUACAUCAA DB 60
SEQ. ID 0180 CAUGAAAGCUUACAUCAAC DB 61 SEQ. ID 0181
AUGAAAGCUUACAUCAACA DB 62 SEQ. ID 0182 UGAAAGCUUACAUCAACAA DB 63
SEQ. ID 0183 GAAAGCUUACAUCAACAAA DB 64 SEQ. ID 0184
AAAGCUUACAUCAACAAAG DB 65 SEQ. ID 0185 AAGCUUACAUCAACAAAGU DB 66
SEQ. ID 0186 AGCUUACAUCAACAAAGUA DB 67 SEQ. ID 0187
GCUUACAUCAACAAAGUAG DB 68 SEQ. ID 0188 CUUACAUCAACAAAGUAGA DB 69
SEQ. ID 0189 UUACAUCAACAAAGUAGAA DB 70 SEQ. ID 0190
UACAUCAACAAAGUAGAAG DB 71 SEQ. ID 0191 ACAUCAACAAAGUAGAAGA DB 72
SEQ. ID 0192 CAUCAACAAAGUAGAAGAG DB 73 SEQ. ID 0193
AUCAACAAAGUAGAAGAGC DB 74 SEQ. ID 0194 UCAACAAAGUAGAAGAGCU DB 75
SEQ. ID 0195 CAACAAAGUAGAAGAGCUA DB 76 SEQ. ID 0196
AACAAAGUAGAAGAGCUAA DB 77 SEQ. ID 0197 ACAAAGUAGAAGAGCUAAA DB 78
SEQ. ID 0198 CAAAGUAGAAGAGCUAAAG DB 79 SEQ. ID 0199
AAAGUAGAAGAGCUAAAGA DB 80 SEQ. ID 0200 AAGUAGAAGAGCUAAAGAA DB 81
SEQ. ID 0201 AGUAGAAGAGCUAAAGAAA DB 82 SEQ. ID 0202
GUAGAAGAGCUAAAGAAAA DB 83 SEQ. ID 0203 UAGAAGAGCUAAAGAAAAA DB 84
SEQ. ID 0204 AGAAGAGCUAAAGAAAAAA DB 85 SEQ. ID 0205
GAAGAGCUAAAGAAAAAAU DB 86 SEQ. ID 0206 AAGAGCUAAAGAAAAAAUA DB 87
SEQ. ID 0207 AGAGCUAAAGAAAAAAUAC DB 88 SEQ. ID 0208
GAGCUAAAGAAAAAAUACG DB 89 SEQ. ID 0209 AGCUAAAGAAAAAAUACGG DB 90
SEQ. ID 0210 GCUAAAGAAAAAAUACGGG Luc 1 SEQ. ID 0211
AUCCUCAUAAAGGCCAAGA Luc 2 SEQ. ID 0212 AGAUCCUCAUAAAGGCCAA Luc 3
SEQ. ID 0213 AGAGAUCCUCAUAAAGGCC Luc 4 SEQ. ID 0214
AGAGAGAUCCUCAUAAAGG Luc 5 SEQ. ID 0215 UCAGAGAGAUCCUCAUAAA Luc 6
SEQ. ID 0216 AAUCAGAGAGAUCCUCAUA Luc 7 SEQ. ID 0217
AAAAUCAGAGAGAUCCUCA Luc 8 SEQ. ID 0218 GAAAAAUCAGAGAGAUCCU Luc 9
SEQ. ID 0219 AAGAAAAAUCAGAGAGAUC Luc 10 SEQ. ID 0220
GCAAGAAAAAUCAGAGAGA Luc 11 SEQ. ID 0221 ACGCAAGAAAAAUCAGAGA Luc 12
SEQ. ID 0222 CGACGCAAGAAAAAUCAGA Luc 13 SEQ. ID 0223
CUCGACGCAAGAAAAAUCA Luc 14 SEQ. ID 0224 AACUCGACGCAAGAAAAAU Luc 15
SEQ. ID 0225 AAAACUCGACGCAAGAAAA Luc 16 SEQ. ID 0226
GGAAAACUCGACGCAAGAA Luc 17 SEQ. ID 0227 CCGGAAAACUCGACGCAAG Luc 18
SEQ. ID 0228 UACCGGAAAACUCGACGCA Luc 19 SEQ. ID 0229
CUUACCGGAAAACUCGACG Luc 20 SEQ. ID 0230 GUCUUACCGGAAAACUCGA Luc 21
SEQ. ID 0231 AGGUCUUACCGGAAAACUC Luc 22 SEQ. ID 0232
AAAGGUCUUACCGGAAAAC Luc 23 SEQ. ID 0233 CGAAAGGUCUUACCGGAAA Luc 24
SEQ. ID 0234 ACCGAAAGGUCUUACCGGA Luc 25 SEQ. ID 0235
GUACCGAAAGGUCUUACCG Luc 26 SEQ. ID 0236 AAGUACCGAAAGGUCUUAC Luc 27
SEQ. ID 0237 CGAAGUACCGAAAGGUCUU Luc 28 SEQ. ID 0238
GACGAAGUACCGAAAGGUC Luc 29 SEQ. ID 0239 UGGACGAAGUACCGAAAGG Luc 30
SEQ. ID 0240 UGUGGACGAAGUACCGAAA Luc 31 SEQ. ID 0241
UUUGUGGACGAAGUACCGA Luc 32 SEQ. ID 0242 UGUUUGUGGACGAAGUACC Luc 33
SEQ. ID 0243 UGUGUUUGUGGACGAAGUA Luc 34 SEQ. ID 0244
GUUGUGUUUGUGGACGAAG Luc 35 SEQ. ID 0245 GAGUUGUGUUUGUGGACGA Luc 36
SEQ. ID 0246 AGGAGUUGUGUUUGUGGAC Luc 37 SEQ. ID 0247
GGAGGAGUUGUGUUUGUGG Luc 38 SEQ. ID 0248 GCGGAGGAGUUGUGUUUGU Luc 39
SEQ. ID 0249 GCGCGGAGGAGUUGUGUUU Luc 40 SEQ. ID 0250
UUGCGCGGAGGAGUUGUGU Luc 41 SEQ. ID 0251 AGUUGCGCGGAGGAGUUGU Luc 42
SEQ. ID 0252 AAAGUUGCGCGGAGGAGUU Luc 43 SEQ. ID 0253
AAAAAGUUGCGCGGAGGAG Luc 44 SEQ. ID 0254 CGAAAAAGUUGCGCGGAGG Luc 45
SEQ. ID 0255 CGCGAAAAAGUUGCGCGGA Luc 46 SEQ. ID 0256
ACCGCGAAAAAGUUGCGCG Luc 47 SEQ. ID 0257 CAACCGCGAAAAAGUUGCG Luc 48
SEQ. ID 0258 AACAACCGCGAAAAAGUUG Luc 49 SEQ. ID 0259
GUAACAACCGCGAAAAAGU Luc 50 SEQ. ID 0260 AAGUAACAACCGCGAAAAA Luc 51
SEQ. ID 0261 UCAAGUAACAACCGCGAAA Luc 52 SEQ. ID 0262
AGUCAAGUAACAACCGCGA Luc 53 SEQ. ID 0263 CCAGUCAAGUAACAACCGC Luc 54
SEQ. ID 0264 CGCCAGUCAAGUAACAACC Luc 55 SEQ. ID 0265
GUCGCCAGUCAAGUAACAA Luc 56 SEQ. ID 0266 ACGUCGCCAGUCAAGUAAC Luc 57
SEQ. ID 0267 UUACGUCGCCAGUCAAGUA Luc 58 SEQ. ID 0268
GAUUACGUCGCCAGUCAAG Luc 59 SEQ. ID 0269 UGGAUUACGUCGCCAGUCA Luc 60
SEQ. ID 0270 CGUGGAUUACGUCGCCAGU Luc 61 SEQ. ID 0271
AUCGUGGAUUACGUCGCCA Luc 62 SEQ. ID 0272 AGAUCGUGGAUUACGUCGC Luc 63
SEQ. ID 0273 AGAGAUCGUGGAUUACGUC Luc 64 SEQ. ID 0274
AAAGAGAUCGUGGAUUACG Luc 65 SEQ. ID 0275 AAAAAGAGAUCGUGGAUUA Luc 66
SEQ. ID 0276 GGAAAAAGAGAUCGUGGAU Luc 67 SEQ. ID 0277
ACGGAAAAAGAGAUCGUGG
Luc 68 SEQ. ID 0278 UGACGGAAAAAGAGAUCGU Luc 69 SEQ. ID 0279
GAUGACGGAAAAAGAGAUC Luc 70 SEQ. ID 0280 ACGAUGACGGAAAAAGAGA Luc 71
SEQ. ID 0281 AGACGAUGACGGAAAAAGA Luc 72 SEQ. ID 0282
AAAGACGAUGACGGAAAAA Luc 73 SEQ. ID 0283 GGAAAGACGAUGACGGAAA Luc 74
SEQ. ID 0284 ACGGAAAGACGAUGACGGA Luc 75 SEQ. ID 0285
GGACGGAAAGACGAUGACG Luc 76 SEQ. ID 0286 GAGCACGGAAAGACGAUGA Luc 77
SEQ. ID 0287 UGGAGCACGGAAAGACGAU Luc 78 SEQ. ID 0288
UUUGGAGCACGGAAAGACG Luc 79 SEQ. ID 0289 GUUUUGGAGCACGGAAAGA Luc 80
SEQ. ID 0290 UUGUUUUGGAGCACGGAAA Luc 81 SEQ. ID 0291
UGUUGUUUUGGAGCACGGA Luc 82 SEQ. ID 0292 GUUGUUGUUUUGGAGCACG Luc 83
SEQ. ID 0293 CCGUUGUUGUUUUGGAGCA Luc 84 SEQ. ID 0294
CGCCGUUGUUGUUUUGGAG Luc 85 SEQ. ID 0295 GCCGCCGUUGUUGUUUUGG Luc 86
SEQ. ID 0296 CCGCCGCCGUUGUUGUUUU Luc 87 SEQ. ID 0297
UCCCGCCGCCGUUGUUGUU Luc 88 SEQ. ID 0298 CUUCCCGCCGCCGUUGUUG Luc 89
SEQ. ID 0299 AACUUCCCGCCGCCGUUGU Luc 90 SEQ. ID 0300
UGAACUUCCCGCCGCCGUU
Example II
Validation of the Algorithm Using DBI, Luciferase, PLK, EGFR, and
SEAP
[0291] The algorithm (Formula VIII) identified siRNAs for five
genes, human DBI, firefly luciferase (fLuc), renilla luciferase
(rLuc), human PLK, and human secreted alkaline phosphatase (SEAP).
Four individual siRNAs were selected on the basis of their
SMARTscores.TM. derived by analysis of their sequence using Formula
VIII (all of the siRNAs would be selected with Formula IX as well)
and analyzed for their ability to silence their targets'
expression. In addition to the scoring, a BLAST search was
conducted for each siRNA. To minimize the potential for off-target
silencing effects, only those target sequences with more than three
mismatches against un-related sequences were selected. Semizarov,
et al, Specificity of short interfering RNA determined through gene
expression signatures. Proc. Natl. Acad. Sci. U.S.A. 2003,
100:6347. These duplexes were analyzed individually and in pools of
4 and compared with several siRNAs that were randomly selected. The
functionality was measured a percentage of targeted gene knockdown
as compared to controls. All siRNAs were transfected as described
by the methods above at 100 nM concentration into HEK293 using
Lipofectamine 2000. The level of the targeted gene expression was
evaluated by B-DNA as described above and normalized to the
non-specific control. FIG. 10 shows that the siRNAs selected by the
algorithm disclosed herein were significantly more potent than
randomly selected siRNAs. The algorithm increased the chances of
identifying an F50 siRNA from 48% to 91%, and an F80 siRNA from 13%
to 57%. In addition, pools of SMART siRNA silence the selected
target better than randomly selected pools (see FIG. 10F).
Example III
Validation of the Algorithm Using Genes Involved in
Clathrin-Dependent Endocytosis
[0292] Components of clathrin-mediated endocytosis pathway are key
to modulating intracellular signaling and play important roles in
disease. Chromosomal rearrangements that result in fusion
transcripts between the Mixed-Lineage Leukemia gene (MLL) and CALM
(Clathrin assembly lymphoid myeloid leukemia gene) are believed to
play a role in leukemogenesis. Similarly, disruptions in Rab7 and
Rab9, as well as HIP1 (Huntingtin-interacting protein), genes that
are believed to be involved in endocytosis, are potentially
responsible for ailments resulting in lipid storage, and neuronal
diseases, respectively. For these reasons, siRNA directed against
clathrin and other genes involved in the clathrin-mediated
endocytotic pathway are potentially important research and
therapeutic tools.
[0293] siRNAs directed against genes involved in the
clathrin-mediated endocytosis pathways were selected using Formula
VIII. The targeted genes were clathrin heavy chain (CHC, accession
# NM.sub.--004859), clathrin light chain A (CLCa, NM.sub.--001833),
clathrin light chain B (CLCb, NM.sub.--001834), CALM (U45976),
.beta.2 subunit of AP-2 (.beta.2, NM.sub.--001282), Eps15
(NM.sub.--001981), Eps15R(NM.sub.--021235), dynamin II (DYNII,
NM.sub.--004945), Rab5a (BC001267), Rab5b (NM.sub.--002868), Rab5c
(AF141304), and EEA.1 (XM.sub.--018197).
[0294] For each gene, four siRNAs duplexes with the highest scores
were selected and a BLAST search was conducted for each of them
using the Human EST database. In order to minimize the potential
for off-target silencing effects, only those sequences with more
than three mismatches against un-related sequences were used. All
duplexes were synthesized at Dharmacon, Inc. as 21-mers with 3'-UU
overhangs using a modified method of 2'-ACE chemistry Scaringe,
Advanced 5'-silyl-2'-orthoester approach to RNA oligonitcleoticle
synthesis, Methods Enzymol 2000, 317:3 and the antisense strand was
chemically phosphorylated to insure maximized activity.
[0295] HeLa cells were grown in Dulbecco's modified Eagle's medium
(DMEM) containing 10% fetal bovine serum, antibiotics and
glutamine. siRNA duplexes were resuspended in 1.times.siRNA
Universal buffer (Dharmacon, Inc.) to 20 .mu.M prior to
transfection. HeLa cells in 12-well plates were transfected twice
with 4 .mu.l of 20 .mu.M siRNA duplex in 3 .mu.l Lipofectamine 2000
reagent (Invitrogen, Carlsbad, Calif., USA) at 24-hour intervals.
For the transfections in which 2 or 3 siRNA duplexes were included,
the amount of each duplex was decreased, so that the total amount
was the same as in transfections with single siRNAs. Cells were
plated into normal culture medium 12 hours prior to experiments,
and protein levels were measured 2 or 4 days after the first
transfection.
[0296] Equal amounts of lysates were resolved by electrophoresis,
blotted, and stained with the antibody specific to targeted
protein, as well as antibodies specific to unrelated proteins, PPI
phosphatase and Tsg101 (not shown). The cells were lysed in Triton
X-100/glycerol solubilization buffer as described previously.
Tebar, Bohlander, & Sorkin, Clathrin Assembly Lymphoid Myeloid
Leukemia (CALM) Protein: Localization in Endocytic-coated Pits,
Interactions with Clathrin, and the Impact of Overexpression on
Clathrin-mediated Traffic, Mol. Biol. Cell August 1999, 10:2687.
Cell lysates were electrophoresed, transferred to nitrocellulose
membranes, and Western blotting was performed with several
antibodies followed by detection using enhanced chemiluminescence
system (Pierce, Inc). Several x-ray films were analyzed to
determine the linear range of the chemiluminescence signals, and
the quantifications were performed using densitometry and
AlphaImager v5.5 software (Alpha lnnotech Corporation). In
experiments with Eps15R-targeted siRNAs, cell lysates were
subjected to immunoprecipitation with Ab860, and Eps15R was
detected in immunoprecipitates by Western blotting as described
above.
[0297] The antibodies to assess the levels of each protein by
Western blot were obtained from the following sources: monoclonal
antibody to clathrin heavy chain (TD.1) was obtained from American
Type Culture Collection (Rockville, Md., USA); polyclonal antibody
to dynamin II was obtained from Affinity Bioreagents, Inc. (Golden,
Colo., USA); monoclonal antibodies to EEA. 1 and Rab5a were
purchased from BD Transduction Laboratories (Los Angeles, Calif.,
USA); the monoclonal antibody to Tsg101 was purchased from Santa
Cruz Biotechnology, Inc. (Santa Cruz, Calif., USA); the monoclonal
antibody to GFP was from ZYMED Laboratories Inc. (South San
Francisco, Calif., USA); the rabbit polyclonal antibodies Ab32
specific to .alpha.-adaptins and Ab20 to CALM were described
previously Sorkin, et al, Stoichiometric Interaction of the
Epidermal Growth Factor Receptor with the Clathrin-associated
Protein Complex AP-2, J. Biol. Chem. January 1995, 270:619, the
polyclonal antibodies to clathrin light chains A and B were kindly
provided by Dr. F. Brodsky (UCSF); monoclonal antibodies to PP1 (BD
Transduction Laboratories) and .alpha.-Actinin (Chemicon) were
kindly provided by Dr. M. Dell'Acqua (University of Colorado);
Eps15 Ab577 and Eps15R Ab860 were kindly provided by Dr. P. P. Di
Fiore (European Cancer Institute).
[0298] FIG. 11 demonstrates the in vivo functionality of 48
individual siRNAs, selected using Formula VIII (most of them will
meet the criteria incorporated by Formula IX as well) targeting 12
genes. Various cell lines were transfected with siRNA duplexes
(Dupl-4) or pools of siRNA duplexes (Pool), and the cells were
lysed 3 days after transfection with the exception of CALM (2 days)
and .beta.2 (4 days).
[0299] Note a .beta.1-adaptin band (part of AP-1 Golgi adaptor
complex) that runs slightly slower than .beta.2 adaptin. CALM has
two splice variants, 66 and 72 kD. The full-length Eps15R (a
doublet of .about.130 kD) and several truncated spliced forms of
.about.100 kD and .about.70 kD were detected in Eps15R
immunoprecipitates (shown by arrows). The cells were lysed 3 days
after transfection. Equal amounts of lysates were resolved by
electrophoresis and blotted with the antibody specific to a
targeted protein (GFP antibody for YFP fusion proteins) and the
antibody specific to unrelated proteins PP1 phosphatase or
.alpha.-actinin, and TSG101. The amount of protein in each specific
band was normalized to the amount of non-specific proteins in each
lane of the gel. Nearly all of them appear to be functional, which
establishes that Formula VIII and IX can be used to predict siRNAs'
functionality in general in a genome wide manner.
[0300] To generate the fusion of yellow fluorescent protein (YFP)
with Rab5b or Rab5c (YFP-Rab5b or YFP-Rab5c), a DNA fragment
encoding the full-length human Rab5b or Rab5c was obtained by PCR
using Pfu polymerase (Stratagene) with a SacI restriction site
introduced into the 5' end and a KpnI site into the 3' end and
cloned into pEYFP-C1 vector (CLONTECH, Palo Alto, Calif., USA).
GFP-CALM and YFP-Rab5a were described previously Tebar, Bohlander,
& Sorkin, Clathrin Assembly Lymphoid Myeloid Leukemia (CALM)
Protein: Localization in Endocytic-coated Pits, Interactins with
Clathrin, and the Impact of Overexpression on Clathrin-mediated
Traffic, Mol. Biol. Cell August 1999, 10:2687.
Example IV
Validation of the Algorithm Using Eg5, GADPH, ATE1, MEK2, MEK1, QB,
LaminA/C, c-myc, Human Cyclophilin, and Mouse Cyclophilin
[0301] A number of genes have been identified as playing
potentially important roles in disease etiology. Expression
profiles of normal and diseased kidneys has implicated Edg5 in
immunoglobulin A neuropathy, a common renal glomerular disease.
Myc1, MEK1/2 and other related kinases have been associated with
one or more cancers, while lamins have been implicated in muscular
dystrophy and other diseases. For these reasons, siRNA directed
against the genes encoding these classes of molecules would be
important research and therapeutic tools.
[0302] FIG. 12 illustrates four siRNAs targeting 10 different genes
(Table V for sequence and accession number information) that were
selected according to the Formula VIII and assayed as individuals
and pools in HEK293 cells. The level of siRNA induced silencing was
measured using the B-DNA assay. These studies demonstrated that
thirty-six out of the forty individual SMART-selected siRNA tested
are functional (90%) and all 10 pools are fully functional.
TABLE-US-00009 TABLE V Gene Accession Formula Formula Name Number
SEQ. ID NO. FTllSeqTence VIII IX CLTC NM_004859 SEQ. ID NO. 0427
GAAAGAATCTGTAGAGAAA 76 94.2 CLTC NM_004859 SEQ. ID NO. 0428
GCAATGAGCTGTTTGAAGA 65 39.9 CLTC NM_004859 SEQ. ID NO. 0429
TGACAAAGGTGGATAAATT 57 38.2 CLTC NM_004859 SEQ. ID NO. 0430
GGAAATGGATCTCTTTGAA 54 49.4 CLTA NM_001833 SEQ. ID NO. 0431
GGAAAGTAATGGTCCAACA 22 55.5 CLTA NM_001833 SEQ. ID NO. 0432
AGACAGTTATGCAGCTATT 4 22.9 CLTA NM_001833 SEQ. ID NO. 0433
CCAATTCTCGGAAGCAAGA 1 17 CLTA NM_001833 SEQ. ID NO. 0434
GAAAGTAATGGTCCAACAG -1 -13 CLTB NM_001834 SEQ. ID NO. 0435
GCGCCAGAGTGAACAAGTA 17 57.5 CLTB NM_001834 SEQ. ID NO. 0436
GAAGGTGGCCCAGCTATGT 15 -8.6 CLTB NM_001834 SEQ. ID NO. 0311
GGAACCAGCGCCAGAGTGA 13 40.5 CLTB NM_001834 SEQ. ID NO. 0312
GAGCGAGATTGCAGGCATA 20 61.7 CALM U45976 SEQ. ID NO. 0313
GTTAGTATCTGATGACTTG 36 -34.6 CALM U45976 SEQ. ID NO. 0314
GAAATGGAACCACTAAGAA 33 46.1 CALM U45976 SEQ. ID NO. 0315
GGAAATGGAACCACTAAGA 30 61.2 CALM U45976 SEQ. ID NO. 0316
CAACTACACTTTCCAATGC 28 6.8 EPS15 NM_001981 SEQ. ID NO. 0317
CCACCAAGATTTCATGATA 48 25.2 EPS15 NM_001981 SEQ. ID NO. 0318
GATCGGAACTCCAACAAGA 43 49.3 EPS15 NM_001981 SEQ. ID NO. 0319
AAACGGAGCTACAGATTAT 39 11.5 EPS15 NM_001981 SEQ. ID NO. 0320
CCACACAGCATTCTTGTAA 33 -23.6 EPS15R NM_021235 SEQ. ID NO. 0321
GAAGTTACCTTGAGCAATC 48 33 EPS15R NM_021235 SEQ. ID NO. 0322
GGACTTGGCCGATCCAGAA 27 33 EPS15R NM_021235 SEQ. ID NO. 0323
GCACTTGGATCGAGATGAG 20 1.3 EPS15R NM_021235 SEQ. ID NO. 0324
CAAAGACCAATTCGCGTTA 17 27.7 DNM2 NM_004945 SEQ. ID NO. 0325
CCGAATCAATCGCATCTTC 6 -29.6 DNM2 NM_004945 SEQ. ID NO. 0326
GACATGATCCTGCAGTTCA 5 -14 DNM2 NM_004945 SEQ. ID NO. 0327
GAGCGAATCGTCACCACTT 5 24 DNM2 NM_004945 SEQ. ID NO. 0328
CCTCCGAGCTGGCGTCTAC -4 -63.6 ARF6 AF93885 SEQ. ID NO. 0329
TCACATGGTTAACCTCTAA 27 -21.1 ARF6 AF93885 SEQ. ID NO. 0330
GATGAGGGACGCCATAATC 7 -38.4 ARF6 AF93885 SEQ. ID NO. 0331
CCTCTAACTACAAATCTTA 4 16.9 ARF6 AF93885 SEQ. ID NO. 0332
GGAAGGTGCTATCCAAAAT 4 11.5 RAB5A BC001267 SEQ. ID NO. 0333
GCAAGCAAGTCCTAACATT 40 25.1 RAB5A BC001267 SEQ. ID NO. 0334
GGAAGAGGAGTAGACCTTA 17 50.1 RAB5A BC001267 SEQ. ID NO. 0335
AGGAATCAGTGTTGTAGTA 16 11.5 RAB5A BC001267 SEQ. ID NO. 0336
GAAGAGGAGTAGACCTTAC 12 7 RAB5B NM_002868 SEQ. ID NO. 0337
GAAAGTCAAGCCTGGTATT 14 18.1 RAB5B NM_002868 SEQ. ID NO. 0338
AAAGTCAAGCCTGGTATTA 6 -17.8 RAB5B NM_002868 SEQ. ID NO. 0339
GCTATGAACGTGAATGATC 3 -21.1 RAB5B NM_002868 SEQ. ID NO. 0340
GAAGCCTGGTATTACGTTT -7 -37.5 RAB5C AF141304 SEQ. ID NO. 0341
GGAACAAGATCTGTCAATT 38 51.9 RAB5C AF141304 SEQ. ID NO. 0342
GCAATGAACGTGAACGAAA 29 43.7 RAB5C AF141304 SEQ. ID NO. 0343
CAATGAACGTGAACGAAAT 18 43.3 RAB5C AF141304 SEQ. ID NO. 0344
GGACAGGAGCGGTATCACA 6 18.2 EEA1 XM_018197 SEQ. ID NO. 0345
AGACAGAGCTTGAGAATAA 67 64.1 EEA1 XM_018197 SEQ. ID NO. 0346
GAGAAGATCTTTATGCAAA 60 48.7 EEA1 XM_018197 SEQ. ID NO. 0347
GAAGAGAAATCAGCAGATA 58 45.7 EEA1 XM_018197 SEQ. ID NO. 0348
GCAAGTAACTCAACTAACA 56 72.3 AP2B1 NM_001282 SEQ. ID NO. 0349
GAGCTAATCTGCCACATTG 49 -12.4 AP2B1 NM_001282 SEQ. ID NO. 0350
GCAGATGAGTTACTAGAAA 44 48.9 AP2B1 NM_001282 SEQ. ID NO. 0351
CAACTTAATTGTCCAGAAA 41 28.2 AP2B1 NM_001282 SEQ. ID NO. 0352
CAACACAGGATTCTGATAA 33 -5.8 PLK NM_005030 SEQ. ID NO. 0353
AGATTGTGCCTAAGTCTCT -35 -3.4 PLK NM_005030 SEQ. ID NO. 0354
ATGAAGATCTGGAGGTGAA 0 -4.3 PLK NM_005030 SEQ. ID NO. 0355
TTTGAGACTTCTTGCCTAA -5 -27.7 PLK NM_005030 SEQ. ID NO. 0356
AGATCACCCTCCTTAAATA 15 72.3 GAPDH NM_002046 SEQ. ID NO. 0357
CAACGGATTTGGTCGTATT 27 -2.8 GAPDH NM_002046 SEQ. ID NO. 0358
GAAATCCCATCACCATCTT 24 3.9 GAPDH NM_002046 SEQ. ID NO. 0359
GACCTCAACTACATGGTTT 22 -22.9 GAPDH NM_002046 SEQ. ID NO. 0360
TGGTTTACATGTTCCAATA 9 9.8 c-Myc SEQ. ID NO. 0361
GAAGAAATCGATGTTGTTT 31 -11.7 c-Myc SEQ. ID NO. 0362
ACACAAACTTGAACAGCTA 22 51.3 c-Myc SEQ. ID NO. 0363
GGAAGAAATCGATGTTGTT 18 26 c-Myc SEQ. ID NO. 0364
GAAACGACGAGAACAGTTG 18 -8.9 MAP2K1 NM_002755 SEQ. ID NO. 0365
GCACATGGATGGAGGTTCT 26 16 MAP2K1 NM_002755 SEQ. ID NO. 0366
GCAGAGAGAGCAGATTTGA 16 0.4 MAP2K1 NM_002755 SEQ. ID NO. 0367
GAGGTTCTCTGGATCAAGT 14 15.5 MAP2K1 NM_002755 SEQ. ID NO. 0368
GAGCAGATTTGAAGCAACT 14 18.5 MAP2K2 NM_030662 SEQ. ID NO. 0369
CAAAGACGATGACTTCGAA 37 26.4 MAP2K2 NM_030662 SEQ. ID NO. 0370
GATCAGCATTTGCATGGAA 24 -0.7 MAP2K2 NM_030662 SEQ. ID NO. 0371
TCCAGGAGTTTGTCAATAA 17 -4.5 MAP2K2 NM_030662 SEQ. ID NO. 0372
GGAAGCTGATCCACCTTGA 16 59.2 KNSL1(EG5) NM_004523 SEQ. ID NO. 0373
GCAGAAATCTAAGGATATA 53 35.8 KNSL1(EG5) NM_004523 SEQ. ID NO. 0374
CAACAAGGATGAAGTCTAT 50 18.3 KNSL1(EG5) NM_004523 SEQ. ID NO. 0375
CAGCAGAAATCTAAGGATA 41 32.7 KNSL1(EG5) NM_004523 SEQ. ID NO. 0376
CTAGATGGCTTTCTCAGTA 39 3.9 CyclophilinA_ NM_021130 SEQ. ID NO. 0377
AGACAAGGTCCCAAAGACA -16 58.1 CyclophilinA_ NM_021130 SEQ. ID NO.
0378 GGAATGGCAAGACCAGCAA -6 36 CyclophilinA_ NM_021130 SEQ. ID NO.
0379 AGAATTATTCCAGGGTTTA -3 16.1 CyclophilinA_ NM_021130 SEQ. ID
NO. 0380 GCAGACAAGGTCCCAAAGA 8 8.9 LAMIN A/C NM_170707 SEQ. ID NO.
0381 AGAAGCAGCTTCAGGATGA 31 38.8 LAMIN A/C NM_170707 SEQ. ID NO.
0382 GAGCTTGACTTCCAGAAGA 33 22.4 LAMIN A/C NM_170707 SEQ. ID NO.
0383 CCACCGAAGTTCACCCTAA 21 27.5 LAMIN A/C NM_170707 SEQ. ID NO.
0384 GAGAAGAGCTCCTCCATCA 55 30.1 CyclophilinB M60857 SEQ. ID NO.
0385 GAAAGAGCATCTACGGTGA 41 83.9 CyclophilinB M60857 SEQ. ID NO.
0386 GAAAGGATTTGGCTACAAA 53 59.1 CyclophilinB M60857 SEQ. ID NO.
0387 ACAGCAAATTCCATCGTGT -20 28.8 CyclophilinB M60857 SEQ. ID NO.
0388 GGAAAGACTGTTCCAAAAA 2 27 DBI1 NM_020548 SEQ. ID NO. 0389
CAACACGCCTCATCCTCTA 27 -7.6 DBI2 NM_020548 SEQ. ID NO. 0390
CATGAAAGCTTACATCAAC 25 -30.8 DBI3 NM_020548 SEQ. ID NO. 0391
AAGATGCCATGAAAGCTTA 17 22 DBI4 NM_020548 SEQ. ID NO. 0392
GCACATACCGCCTGAGTCT 15 3.9 rLUC1 SEQ. ID NO. 0393
GATCAAATCTGAAGAAGGA 57 49.2 rLUC2 SEQ. ID NO. 0394
GCCAAGAAGTTTCCTAATA 50 13.7 rLUC3 SEQ. ID NO. 0395
CAGCATATCTTGAACCATT 41 -2.2 rLUC4 SEQ. ID NO. 0396
GAACAAAGGAAACGGATGA 39 29.2 SeAP1 NM_031313 SEQ. ID NO. 0397
CGGAAACGGTCCAGGCTAT 6 26.9 SeAP2 NM_031313 SEQ. ID NO. 0398
GCTTCGAGCAGACATGATA 4 -11.2 SeAP3 NM_031313 SEQ. ID NO. 0399
CCTACACGGTCCTCCTATA 4 4.9 SeAP4 NM_031313 SEQ. ID NO. 0400
GCCAAGAACCTCATCATCT 1 -9.9 fLUC1 SEQ. ID NO. 0401
GATATGGGCTGAATACAAA 54 40.4 fLUC2 SEQ. ID NO. 0402
GCACTCTGATTGACAAATA 47 54.7 fLUC3 SEQ. ID NO. 0403
TGAAGTCTCTGATTAAGTA 46 34.5 fLUC4 SEQ. ID NO. 0404
TCAGAGAGATCCTCATAAA 40 11.4 mCyclo_1 NM_008907 SEQ. ID NO. 0405
GCAAGAAGATCACCATTTC 52 46.4 mCyclo_2 NM_008907 SEQ. ID NO. 0406
GAGAGAAATTTGAGGATGA 36 70.7 mCyclo_3 NM_008907 SEQ. ID NO. 0407
GAAAGGATTTGGCTATAAG 35 -1.5 mCyclo_4 NM_008907 SEQ. ID NO. 0408
GAAAGAAGGCATGAACATT 27 10.3 BCL2_1 NM_000633 SEQ. ID NO. 0409
GGGAGATAGTGATGAAGTA 21 72 BCL2_2 NM_000633 SEQ. ID NO. 0410
GAAGTACATCCATTATAAG 1 3.3 BCL2_3 NM_000633 SEQ. ID NO. 0411
GTACGACAACCGGGAGATA 1 35.9 BCL2_4 NM_000633 SEQ. ID NO. 0412
AGATAGTGATGAAGTACAT -12 22.1 BCL2_5 NM_000633 SEQ. ID NO. 0413
TGAAGACTCTGCTCAGTTT 36 19.1 BCL2_6 NM_000633 SEQ. ID NO. 0414
GCATGCGGCCTCTGTTTGA 5 -9.7 QB1 NM_003365.1 SEQ. ID NO. 0415
GCACACAGCUUACUACAUC 52 -4.8 QB2 NM_003365.1 SEQ. ID NO. 0416
GAAAUGCCCUGGUAUCUCA 49 22.1 QB3 NM_003365.1 SEQ. ID NO. 0417
GAAGGAACGUGAUGUGAUC 34 22.9 QB4 NM_003365.1 SEQ. ID NO. 0418
GCACUACUCCUGUGUGUGA 28 20.4 ATE1-1 NM_007041 SEQ. ID NO. 0419
GAACCCAGCUGGAGAACUU 45 15.5
ATE1-2 NM_007041 SEQ. ID NO. 0420 GAUAUACAGUGUGAUCUUA 40 12.2
ATE1-3 NM_007041 SEQ. ID NO. 0421 GUACUACGAUCCUGAUUAU 37 32.9
ATE1-4 NM_007041 SEQ. ID NO. 0422 GUGCCGACCUUUACAAUUU 35 18.2
EGFR-1 NM_005228 SEQ. ID NO. 0423 GAAGGAAACTGAATTCAAA 68 79.4
EGFR-1 NM_005228 SEQ. ID NO. 0424 GGAAATATGTACTACGAAA 49 49.5
EGFR-1 NM_005228 SEQ. ID NO. 0425 CCACAAAGCAGTGAATTTA 41 7.6 EGFR-1
NM_005228 SEQ. ID NO. 0426 GTAACAAGCTCACGCAGTT 40 25.9
Example V
Validation of the Algorithm Using Bcl2
[0303] Bcl-2 is a .about.25 kD, 205-239 amino acid, anti-apoptotic
protein that contains considerable homology with other members of
the BCL family including BCLX, MCLI, BAX, BAD, and BIK. The protein
exists in at least two forms (Bcl2a, which has a hydrophobic tail
for membrane anchorage, and Bcl2b, which lacks the hydrophobic
tail) and is predominantly localized to the mitochondrial membrane.
While Bcl2 expression is widely distributed, particular interest
has focused on the expression of this molecule in B and T cells.
Bcl2 expression is down-regulated in normal germinal center B cells
yet in a high percentage of follicular lymphomas, Bcl2 expression
has been observed to be elevated. Cytological studies have
identified a common translocation ((14;18)(q32;q32)) amongst a high
percentage (>70%) of these lymphomas. This genetic lesion places
the Bcl2 gene in juxtaposition to immunoglobulin heavy chain gene
(IgH) encoding sequences and is believed to enforce inappropriate
levels of gene expression, and resistance to programmed cell death
in the follicle center B cells. In other cases, hypomethylation of
the Bcl2 promoter leads to enhanced expression and again,
inhibition of apoptosis. In addition to cancer, dysregulated
expression of Bcl-2 has been correlated with multiple sclerosis and
various neurological diseases.
[0304] The correlation between Bcl-2 translocation and cancer makes
this gene an attractive target for RNAi. Identification of siRNA
directed against the bcl2 transcript (or Bc12-IgH fusions) would
further our understanding Bcl2 gene function and possibly provide a
future therapeutic agent to battle diseases that result from
altered expression or function of this gene.
In Silico Identification of Functional siRNA
[0305] To identify functional and hyperfunctional siRNA against the
Bcl2 gene, the sequence for Bcl-2 was downloaded from the NCBI
Unigene database and analyzed using the Formula VIII algorithm. As
a result of these procedures, both the sequence and SMARTscores.TM.
of the Bcl2 siRNA were obtained and ranked according to their
functionality. Subsequently, these sequences were BLAST'ed
(database) to insure that the selected sequences were specific and
contained minimal overlap with unrealated genes. The
SMARTscores.TM. for the top 10 Bcl-2 siRNA are identified in FIG.
13.
In Vivo Testing of Bcl-2 SiRNA
[0306] Bcl-2 siRNAs having the top ten SMARTscores.TM. were
selected and tested in a functional assay to determine silencing
efficiency. To accomplish this, each of the ten duplexes were
synthesized using 2'-O-ACE chemistry and transfected at 100 nM
concentrations into cells. Twenty-four hours later assays were
performed on cell extracts to assess the degree of target
silencing. Controls used in these experiments included mock
transfected cells, and cells that were transfected with a
non-specific siRNA duplex.
[0307] The results of these experiments are presented below (and in
FIG. 14) and show that all ten of the selected siRNA induce 80% or
better silencing of the Bcl2 message at 100 nM concentrations.
These data verify that the algorithm successfully identified
functional Bcl2 siRNA and provide a set of functional agents that
can be used in experimental and therapeutic environments.
TABLE-US-00010 siRNA 1 GGGAGAUAGUGAUGAAGUA SEQ. ID NO. 301 siRNA 2
GAAGUACAUCCAUUAUAAG SEQ. ID NO. 302 siRNA 3 GUACGACAACCGGGAGAUA
SEQ. ID NO. 303 siRNA 4 AGAUAGUGAUGAAGUACAU SEQ. ID NO. 304 siRNA 5
UGAAGACUCUGCUCAGUUU SEQ. ID NO. 305 siRNA 6 GCAUGCGGCCUCUGUUUGA
SEQ. ID NO. 306 siRNA 7 UGCGGCCUCUGUUUGAUUU SEQ. ID NO. 307 siRNA 8
GAGAUAGUGAUGAAGUACA SEQ. ID NO. 308 siRNA 9 GGAGAUAGUGAUGAAGUAC
SEQ. ID NO. 309 siRNA 10 GAAGACUCUGCUCAGUUUG SEQ. ID NO. 310 Bcl2
siRNA: Sense Strand, 5'.fwdarw.3'
Example VI
Evidence for the Benefits of Pooling
[0308] Evidence for the benefits of pooling have been demonstrated
using the reporter gene, luciferase. Ninety siRNA duplexes were
synthesized using Dharmacon proprietary ACE.RTM. chemistry against
one of the standard reporter genes: firefly luciferase. The
duplexes were designed to start two base pairs apart and to cover
approximately 180 base pairs of the luciferase gene (see sequences
in Table III). Subsequently, the siRNA duplexes were co-transfected
with a luciferase expression reporter plasmid into HEK293 cells
using standard transfection protocols and luciferase activity was
assayed at 24 and 48 hours.
[0309] Transfection of individual siRNAs showed standard
distribution of inhibitory effect. Some duplexes were active, while
others were not. FIG. 15 represents a typical screen of ninety
siRNA duplexes (SEQ. ID NO. 0032-0120) positioned two base pairs
apart. As the figure suggests, the functionality of the siRNA
duplex is determined more by a particular sequence of the
oligonucleotide than by the relative oligonucleotide position
within a gene or excessively sensitive part of the mRNA, which is
important for traditional anti-sense technology.
[0310] When two continuous oligonucleotides were pooled together, a
significant increase in gene silencing activity was observed (see
FIGS. 16A and 16B). A gradual increase in efficacy and the
frequency of pools functionality was observed when the number of
siRNAs increased to 3 and 4 (see FIGS. 16A, 16B, 17A, and 17B).
Further, the relative positioning of the oligonucleotides within a
pool did not determine whether a particular pool was functional
(see FIGS. 18A and 18B, in which 100% of pools of oligonucleotides
distanced by 2, 10 and 20 base pairs were functional).
[0311] However, relative positioning may nonetheless have an
impact. An increased functionality may exist when the siRNA are
positioned continuously head to toe (5' end of one directly
adjacent to the 3' end of the others).
[0312] Additionally, siRNA pools that were tested performed at
least as well as the best oligonucleotide in the pool, under the
experimental conditions whose results are depicted in FIG. 19.
Moreover, when previously identified non-functional and marginally
(semi) functional siRNA duplexes were pooled together in groups of
five at a time, a significant functional cooperative action was
observed. (See FIG. 20) In fact, pools of semi-active
oligonucleotides were 5 to 25 times more functional than the most
potent oligonucleotide in the pool. Therefore, pooling several
siRNA duplexes together does not interfere with the functionality
of the most potent siRNAs within a pool, and pooling provides an
unexpected significant increase in overall functionality
Example VII
Pooling Across Species
[0313] Experiments were performed on the following genes:
.beta.-galactosidase, Renilla luciferase, and Secreted alkaline
phosphatase, which demonstrate the benefits of pooling. (see FIG.
21) Approximately 50% of individual siRNAs designed to silence the
above-specified genes were functional, while 100% of the pools that
contain the same siRNA duplexes were functional.
Example VIII
Highly Functional siRNA
[0314] Pools of five siRNAs in which each two siRNAs overlap to
10-90% resulted in 98% functional entities (>80% silencing).
Pools of siRNAs distributed throughout the mRNA that were evenly
spaced, covering an approximate 20-2000 base pair range, were also
functional. When the pools of siRNA were positioned continuously
head to tail relative to mRNA sequences and mimicked the natural
products of Dicer cleaved long double stranded RNA, 98% of the
pools evidenced highly functional activity (>95% silencing).
Example IX
Human Cyclophyline
[0315] Table III above lists the siRNA sequences for the human
cyclophyline protein. A particularly functional siRNA may be
selected by applying these sequences to any of Formula I to VII
above.
[0316] Alternatively, one could pool 2, 3, 4, 5 or more of these
sequences to create a kit for silencing a gene. Preferably, within
the kit there would be at least one sequence that has a relatively
high predicted functionality when any of Formulas I-VII is
applied.
Example X
Validation of Multigene Knockout Using Rab5 and Eps
[0317] Two or more genes having similar, overlapping functions
often leads to genetic redundancy. Mutations that knockout only one
of, e.g., a pair of such genes (also referred to as homologs)
result in little or no phenotype due to the fact that the remaining
intact gene is capable of fulfilling the role of the disrupted
counterpart. To fully understand the function of such genes in
cellular physiology, it is often necessary to knockout or knockdown
both homologs simultaneously. Unfortunately, concomitant knockdown
of two or more genes is frequently difficult to achieve in higher
organisms (e.g. mice) thus it is necessary to introduce new
technologies dissect gene function. One such approach to knocking
down multiple genes simultaneously is by using siRNA. For example,
FIG. 11 showed that rationally designed siRNA directed against a
number of genes involved in the clathrin-mediated endocytosis
pathway resulted in significant levels of protein reduction (e.g.
>80%). To determine the effects of gene knockdown on
clathrin-related endocytosis, internalization assays were performed
using epidermal growth factor and transferrin. Specifically, mouse
receptor-grade EGF (Collaborative Research Inc.) and iron-saturated
human transferrin (Sigma) were iodinated as described previously
(Jiang, X., Huang, F., Marusyk, A. & Sorkin, A. (2003) Mol Biol
Cell 14, 858-70). HeLa cells grown in 12-well dishes were incubated
with .sup.125I-EGF (1 ng/ml) or .sup.125I-transferrin (1 .mu.g/ml)
in binding medium (DMEM, 0.1% bovine serum albumin) at 37.degree.
C., and the ratio of internalized and surface radioactivity was
determined during 5-min time course to calculate specific
internalization rate constant k.sub.e as described previously
(Jiang, X et al.). The measurements of the uptakes of radiolabeled
transferrin and EGF were performed using short time-course assays
to avoid influence of the recycling on the uptake kinetics, and
using low ligand concentration to avoid saturation of the
clathrin-dependent pathway (for EGF Lund, K. A., Opresko, L. K.,
Strarbuck, C., Walsh, B. J. & Wiley, H. S. (1990) J. Biol.
Chem. 265, 15713-13723).
[0318] The effects of knocking down Rab5a, 5b, 5c, Eps, or Eps 15R
(individually) are shown in FIG. 22 and demonstrate that disruption
of single genes has little or no effect on EGF or Tfn
internalization. In contrast, simultaneous knock down of Rab5a, 5b,
and 5c, or Eps and Eps 15R, leads to a distinct phenotype (note:
total concentration of siRNA in these experiments remained constant
with that in experiments in which a single siRNA was introduced,
see FIG. 23). These experiments demonstrate the effectiveness of
using rationally designed siRNA to knockdown multiple genes and
validates the utility of these reagents to override genetic
redundancy.
Example XI
Validation of Multigene Targeting Using G.sub.6PD, GAPDH, PLK, and
UQC
[0319] Further demonstration of the ability to knock down
expression of multiple genes using rationally designed siRNA was
performed using pools of siRNA directed against four separate
genes. To achieve this, siRNA were transfected into cells (total
siRNA concentration of 100 nM) and assayed twenty-four hours later
by B-DNA. Results shown in FIG. 24 show that pools of rationally
designed molecules are capable of simultaneously silencing four
different genes.
Example XII
Identifying Hyperfunctional siRNA
Identification of Hyperfunctional Bcl-2 siRNA
[0320] The ten rationally designed Bcl2 siRNA (identified in FIGS.
13, 14) were tested to identify hyperpotent reagents. To accomplish
this, each of the ten Bcl-2 siRNA were individually transfected
into cells at a 300 pM (0.3 nM) concentrations. Twenty-four hours
later, transcript levels were assessed by B-DNA assays and compared
with relevant controls. As shown in FIG. 25, while the majority of
Bcl-2 siRNA failed to induce functional levels of silencing at this
concentration, siRNA 1 and 8 induced >80% silencing, and siRNA 6
exhibited greater than 90% silencing at this subnanomolar
concentration.
Example XIII
Gene Silencing: Prophetic Example
[0321] Below is an example of how one might transfect a cell.
[0322] a. Select a cell line. The selection of a cell line is
usually determined by the desired application. The most important
feature to RNAi is the level of expression of the gene of interest.
It is highly recommended to use cell lines for which siRNA
transfection conditions have been specified and validated. [0323]
b. Plate the cells. Approximately 24 hours prior to transfection,
plate the cells at the appropriate density so that they will be
approximately 70-90% confluent, or approximately 1.times.10.sup.5
cells/ml at the time of transfection. Cell densities that are too
low may lead to toxicity due to excess exposure and uptake of
transfection reagent-siRNA complexes. Cell densities that are too
high may lead to low transfection efficiencies and little or no
silencing. Incubate the cells overnight. Standard incubation
conditions for mammalian cells are 37.degree. C. in 5% CO.sub.2.
Other cell types, such as insect cells, require different
temperatures and CO.sub.2 concentrations that are readily
ascertainable by persons skilled in the art. Use conditions
appropriate for the cell type of interest. [0324] c. SiRNA
re-suspension. Add 20 .mu.l siRNA universal buffer to each siRNA to
generate a final concentration of 50 .mu.M.
[0325] d. SiRNA-lipid complex formation. Use RNase-free solutions
and tubes. Using the following table, Table VI: TABLE-US-00011
TABLE VI 96-well 24-well Mixture 1 (TransIT-TKO-Plasmid dilution
mixture) Opti-MEM 9.3 .mu.l 46.5 .mu.l TransIT-TKO (1 .mu.g/.mu.l)
0.5 .mu.l 2.5 .mu.l Mixture 1 Final Volume 10.0 .mu.l 50.0 .mu.l
Mixture 2 (siRNA dilution mixture) Opti-MEM 9.0 .mu.l 45.0 .mu.l
siRNA (1 .mu.M) 1.0 .mu.l 5.0 .mu.l Mixture 2 Final Volume 10.0
.mu.l 50.0 .mu.l Mixture 3 (siRNA-Transfection reagent mixture)
Mixture 1 10 .mu.l 50 .mu.l Mixture 2 10 .mu.l 50 .mu.l Mixture 3
Final Volume 20 .mu.l 100 .mu.l Incubate 20 minutes at room
temperature. Mixture 4 (Media-siRNA/Transfection reagent mixture)
Mixture 3 20 .mu.l 100 .mu.l Complete media 80 .mu.l 400 .mu.l
Mixture 4 Final Volume 100 .mu.l 500 .mu.l Incubate 48 hours at
37.degree. C.
[0326] Transfection. Create a Mixture 1 by combining the specified
amounts of OPTI-MEM serum free media and transfection reagent in a
sterile polystyrene tube. Create a Mixture 2 by combining specified
amounts of each siRNA with OPTI-MEM media in sterile 1 ml tubes.
Create a Mixture 3 by combining specified amounts of Mixture 1 and
Mixture 2. Mix gently (do not vortex) and incubate at room
temperature for 20 minutes. Create a Mixture 4 by combining
specified amounts of Mixture 3 to complete media. Add appropriate
volume to each cell culture well. Incubate cells with transfection
reagent mixture for 24-72 hours at 37.degree. C. This incubation
time is flexible. The ratio of silencing will remain consistent at
any point in the time period. Assay for gene silencing using an
appropriate detection method such as RT-PCR, Western blot analysis,
immunohistochemistry, phenotypic analysis, mass spectrometry,
fluorescence, radioactive decay, or any other method that is now
known or that comes to be known to persons skilled in the art and
that from reading this disclosure would useful with the present
invention. The optimal window for observing a knockdown phenotype
is related to the mRNA turnover of the gene of interest, although
24-72 hours is standard. Final Volume reflects amount needed in
each well for the desired cell culture format. When adjusting
volumes for a Stock Mix, an additional 10% should be used to
accommodate variability in pipetting, etc. Duplicate or triplicate
assays should be carried out when possible.
[0327] While the invention has been described in connection with
specific embodiments thereof, it will be understood that it is
capable of further modifications and this application is intended
to cover any variations, uses, or adaptations of the invention
following, in general, the principles of the invention and
including such departure from the present disclosure as come within
known or customary practice within the art to which the invention
pertains and as may be applied to the essential features
hereinbefore set forth and as follows in the scope of the appended
claims.
Sequence CWU 1
1
437 1 19 RNA Artificial Sequence Synthetic misc_feature 1-2, 4,
6-9, 12, 15-18 n is any nucleotide 1 nnanannnnu cnaannnna 19 2 19
RNA Artificial Sequence Synthetic misc_feature 1-2, 4, 6-9, 12,
15-18 n is any nucleotide 2 nnanannnnu gnaannnna 19 3 19 RNA
Artificial Sequence Synthetic misc_feature 1-2, 4, 6-9, 12, 15-18 n
is any nucleotide 3 nnanannnnu unaannnna 19 4 19 RNA Artificial
Sequence Synthetic misc_feature 1-2, 4, 6-9, 12, 15-18 n is any
nucleotide 4 nnanannnnu cncannnna 19 5 19 RNA Artificial Sequence
Synthetic misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 5
nnanannnnu gncannnna 19 6 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 6
nnanannnnu uncannnna 19 7 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 7
nnanannnnu cnuannnna 19 8 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 8
nnanannnnu gnuannnna 19 9 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 9
nnanannnnu unuannnna 19 10 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 10
nnancnnnnu cnaannnna 19 11 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 11
nnancnnnnu gnaannnna 19 12 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 12
nnancnnnnu unaannnna 19 13 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 13
nnancnnnnu cncannnna 19 14 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 14
nnancnnnnu gncannnna 19 15 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 15
nnancnnnnu uncannnna 19 16 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 16
nnancnnnnu cnuannnna 19 17 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 17
nnancnnnnu gnuannnna 19 18 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 18
nnancnnnnu unuannnna 19 19 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 19
nnangnnnnu cnaannnna 19 20 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 20
nnangnnnnu gnaannnna 19 21 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 21
nnangnnnnu unaannnna 19 22 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 22
nnangnnnnu cncannnna 19 23 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 23
nnangnnnnu gncannnna 19 24 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 24
nnangnnnnu uncannnna 19 25 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 25
nnangnnnnu cnuannnna 19 26 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 26
nnangnnnnu gnuannnna 19 27 19 RNA Artificial Sequence Synthetic
misc_feature 1-2, 4, 6-9, 12, 15-18 n is any nucleotide 27
nnangnnnnu unuannnna 19 28 22 RNA Artificial Sequence Synthetic
misc_feature 4-5,7,9-12,15,18-21 n is any nucleotide 28 gucnnanann
nnucnaannn na 22 29 208 DNA Homo sapiens misc_feature (1)...(208)
human cyclophilin fragment 29 gttccaaaaa cagtggataa ttttgtggcc
ttagctacag gagagaaagg atttggctac 60 aaaaacagca aattccatcg
tgtaatcaag gacttcatga tccagggcgg agacttcacc 120 aggggagatg
gcacaggagg aaagagcatc tacggtgagc gcttccccga tgagaacttc 180
aaactgaagc actacgggcc tggctggg 208 30 200 DNA Photinus pyralis
misc_feature (1)...(200) firefly luciferase fragment 30 tgaacttccc
gccgccgttg ttgttttgga gcacggaaag acgatgacgg aaaaagagat 60
cgtggattac gtcgccagtc aagtaacaac cgcgaaaaag ttgcgcggag gagttgtgtt
120 tgtggacgaa gtaccgaaag gtcttaccgg aaaactcgac gcaagaaaaa
tcagagagat 180 cctcataaag gccaagaagg 200 31 108 DNA Homo sapiens
misc_feature (1)...(108) human DBL fragment 31 acgggcaagg
ccaagtggga tgcctggaat gagctgaaag ggacttccaa ggaagatgcc 60
atgaaagctt acatcaacaa agtagaagag ctaaagaaaa aatacggg 108 32 19 RNA
Artificial Sequence Synthetic 32 guuccaaaaa caguggaua 19 33 19 RNA
Artificial Sequence Synthetic 33 uccaaaaaca guggauaau 19 34 19 RNA
Artificial Sequence Synthetic 34 caaaaacagu ggauaauuu 19 35 19 RNA
Artificial Sequence Synthetic 35 aaaacagugg auaauuuug 19 36 19 RNA
Artificial Sequence Synthetic 36 aacaguggau aauuuugug 19 37 19 RNA
Artificial Sequence Synthetic 37 caguggauaa uuuuguggc 19 38 19 RNA
Artificial Sequence Synthetic 38 guggauaauu uuguggccu 19 39 19 RNA
Artificial Sequence Synthetic 39 ggauaauuuu guggccuua 19 40 19 RNA
Artificial Sequence Synthetic 40 auaauuuugu ggccuuagc 19 41 19 RNA
Artificial Sequence Synthetic 41 aauuuugugg ccuuagcua 19 42 19 RNA
Artificial Sequence Synthetic 42 uuuuguggcc uuagcuaca 19 43 19 RNA
Artificial Sequence Synthetic 43 uuguggccuu agcuacagg 19 44 19 RNA
Artificial Sequence Synthetic 44 guggccuuag cuacaggag 19 45 19 RNA
Artificial Sequence Synthetic 45 ggccuuagcu acaggagag 19 46 19 RNA
Artificial Sequence Synthetic 46 ccuuagcuac aggagagaa 19 47 19 RNA
Artificial Sequence Synthetic 47 uuagcuacag gagagaaag 19 48 19 RNA
Artificial Sequence Synthetic 48 agcuacagga gagaaagga 19 49 19 RNA
Artificial Sequence Synthetic 49 cuacaggaga gaaaggauu 19 50 19 RNA
Artificial Sequence Synthetic 50 acaggagaga aaggauuug 19 51 19 RNA
Artificial Sequence Synthetic 51 aggagagaaa ggauuuggc 19 52 19 RNA
Artificial Sequence Synthetic 52 gagagaaagg auuuggcua 19 53 19 RNA
Artificial Sequence Synthetic 53 gagaaaggau uuggcuaca 19 54 19 RNA
Artificial Sequence Synthetic 54 gaaaggauuu ggcuacaaa 19 55 19 RNA
Artificial Sequence Synthetic 55 aaggauuugg cuacaaaaa 19 56 19 RNA
Artificial Sequence Synthetic 56 ggauuuggcu acaaaaaca 19 57 19 RNA
Artificial Sequence Synthetic 57 auuuggcuac aaaaacagc 19 58 19 RNA
Artificial Sequence Synthetic 58 uuggcuacaa aaacagcaa 19 59 19 RNA
Artificial Sequence Synthetic 59 ggcuacaaaa acagcaaau 19 60 19 RNA
Artificial Sequence Synthetic 60 cuacaaaaac agcaaauuc 19 61 19 RNA
Artificial Sequence Synthetic 61 acaaaaacag caaauucca 19 62 19 RNA
Artificial Sequence Synthetic 62 aaaaacagca aauuccauc 19 63 19 RNA
Artificial Sequence Synthetic 63 aaacagcaaa uuccaucgu 19 64 19 RNA
Artificial Sequence Synthetic 64 acagcaaauu ccaucgugu 19 65 19 RNA
Artificial Sequence Synthetic 65 agcaaauucc aucguguaa 19 66 19 RNA
Artificial Sequence Synthetic 66 caaauuccau cguguaauc 19 67 19 RNA
Artificial Sequence Synthetic 67 aauuccaucg uguaaucaa 19 68 19 RNA
Artificial Sequence Synthetic 68 uuccaucgug uaaucaagg 19 69 19 RNA
Artificial Sequence Synthetic 69 ccaucgugua aucaaggac 19 70 19 RNA
Artificial Sequence Synthetic 70 aucguguaau caaggacuu 19 71 19 RNA
Artificial Sequence Synthetic 71 cguguaauca aggacuuca 19 72 19 RNA
Artificial Sequence Synthetic 72 uguaaucaag gacuucaug 19 73 19 RNA
Artificial Sequence Synthetic 73 uaaucaagga cuucaugau 19 74 19 RNA
Artificial Sequence Synthetic 74 aucaaggacu ucaugaucc 19 75 19 RNA
Artificial Sequence Synthetic 75 caaggacuuc augauccag 19 76 19 RNA
Artificial Sequence Synthetic 76 aggacuucau gauccaggg 19 77 19 RNA
Artificial Sequence Synthetic 77 gacuucauga uccagggcg 19 78 19 RNA
Artificial Sequence Synthetic 78 cuucaugauc cagggcgga 19 79 19 RNA
Artificial Sequence Synthetic 79 ucaugaucca gggcggaga 19 80 19 RNA
Artificial Sequence Synthetic 80 augauccagg gcggagacu 19 81 19 RNA
Artificial Sequence Synthetic 81 gauccagggc ggagacuuc 19 82 19 RNA
Artificial Sequence Synthetic 82 uccagggcgg agacuucac 19 83 19 RNA
Artificial Sequence Synthetic 83 cagggcggag acuucacca 19 84 19 RNA
Artificial Sequence Synthetic 84 gggcggagac uucaccagg 19 85 19 RNA
Artificial Sequence Synthetic 85 gcggagacuu caccagggg 19 86 19 RNA
Artificial Sequence Synthetic 86 ggagacuuca ccaggggag 19 87 19 RNA
Artificial Sequence Synthetic 87 agacuucacc aggggagau 19 88 19 RNA
Artificial Sequence Synthetic 88 acuucaccag gggagaugg 19 89 19 RNA
Artificial Sequence Synthetic 89 uucaccaggg gagauggca 19 90 19 RNA
Artificial Sequence Synthetic 90 caccagggga gauggcaca 19 91 19 RNA
Artificial Sequence Synthetic 91 ccaggggaga uggcacagg 19 92 19 RNA
Artificial Sequence Synthetic 92 aggggagaug gcacaggag 19 93 19 RNA
Artificial Sequence Synthetic 93 gggagauggc acaggagga 19 94 19 RNA
Artificial Sequence Synthetic 94 uggcacagga ggaaagagc 19 95 19 RNA
Artificial Sequence Synthetic 95 gauggcacag gaggaaaga 19 96 19 RNA
Artificial Sequence Synthetic 96 gcacaggagg aaagagcau 19 97 19 RNA
Artificial Sequence Synthetic 97 acaggaggaa agagcaucu 19 98 19 RNA
Artificial Sequence Synthetic 98 aggaggaaag agcaucuac 19 99 19 RNA
Artificial Sequence Synthetic 99 gaggaaagag caucuacgg 19 100 19 RNA
Artificial Sequence Synthetic 100 ggaaagagca ucuacggug 19 101 19
RNA Artificial Sequence Synthetic 101 aaagagcauc uacggugag 19 102
19 RNA Artificial Sequence Synthetic 102 agagcaucua cggugagcg 19
103 19 RNA Artificial Sequence Synthetic 103 agcaucuacg gugagcgcu
19 104 19 RNA Artificial Sequence Synthetic 104 caucuacggu
gagcgcuuc 19 105 19 RNA Artificial Sequence Synthetic 105
ucuacgguga gcgcuuccc 19 106 19 RNA Artificial Sequence Synthetic
106 uacggugagc gcuuccccg 19 107 19 RNA Artificial Sequence
Synthetic 107 cggugagcgc uuccccgau 19 108 19 RNA Artificial
Sequence Synthetic 108 gugagcgcuu ccccgauga 19 109 19 RNA
Artificial Sequence Synthetic 109 gagcgcuucc ccgaugaga 19 110 19
RNA Artificial Sequence Synthetic 110 gcgcuucccc gaugagaac 19 111
19 RNA Artificial Sequence Synthetic 111 gcuuccccga ugagaacuu 19
112 19 RNA Artificial Sequence Synthetic 112 uuccccgaug agaacuuca
19 113 19 RNA Artificial Sequence Synthetic 113 ccccgaugag
aacuucaaa 19 114 19 RNA Artificial Sequence Synthetic 114
ccgaugagaa cuucaaacu 19 115 19 RNA Artificial Sequence Synthetic
115 gaugagaacu ucaaacuga 19 116 19 RNA Artificial Sequence
Synthetic 116 ugagaacuuc aaacugaag 19 117 19 RNA Artificial
Sequence Synthetic 117 agaacuucaa acugaagca 19 118 19 RNA
Artificial Sequence Synthetic 118 aacuucaaac ugaagcacu 19 119 19
RNA Artificial Sequence Synthetic 119 cuucaaacug aagcacuac 19 120
19 RNA Artificial Sequence Synthetic 120 ucaaacugaa gcacuacgg 19
121 19 RNA Artificial Sequence Synthetic 121 acgggcaagg ccaaguggg
19 122 19 RNA Artificial Sequence Synthetic 122 cgggcaaggc
caaguggga 19 123 19 RNA Artificial Sequence Synthetic 123
gggcaaggcc aagugggau 19 124 19 RNA Artificial Sequence Synthetic
124 ggcaaggcca agugggaug 19 125 19 RNA Artificial Sequence
Synthetic 125 gcaaggccaa gugggaugc 19 126 19 RNA Artificial
Sequence Synthetic 126 caaggccaag ugggaugcc 19 127 19 RNA
Artificial Sequence Synthetic 127 aaggccaagu gggaugccu 19 128 19
RNA Artificial Sequence Synthetic 128 aggccaagug ggaugccug 19 129
19 RNA Artificial Sequence Synthetic 129 ggccaagugg gaugccugg 19
130 19 RNA Artificial Sequence Synthetic 130 gccaaguggg augccugga
19 131 19 RNA Artificial Sequence Synthetic 131 ccaaguggga
ugccuggaa 19 132 19 RNA Artificial Sequence Synthetic 132
caagugggau gccuggaau 19 133 19 RNA Artificial Sequence Synthetic
133 aagugggaug ccuggaaug 19 134 19 RNA Artificial Sequence
Synthetic 134 agugggaugc cuggaauga 19 135 19 RNA Artificial
Sequence Synthetic 135 gugggaugcc uggaaugag
19 136 19 RNA Artificial Sequence Synthetic 136 ugggaugccu
ggaaugagc 19 137 19 RNA Artificial Sequence Synthetic 137
gggaugccug gaaugagcu 19 138 19 RNA Artificial Sequence Synthetic
138 ggaugccugg aaugagcug 19 139 19 RNA Artificial Sequence
Synthetic 139 gaugccugga augagcuga 19 140 19 RNA Artificial
Sequence Synthetic 140 augccuggaa ugagcugaa 19 141 19 RNA
Artificial Sequence Synthetic 141 ugccuggaau gagcugaaa 19 142 19
RNA Artificial Sequence Synthetic 142 gccuggaaug agcugaaag 19 143
19 RNA Artificial Sequence Synthetic 143 ccuggaauga gcugaaagg 19
144 19 RNA Artificial Sequence Synthetic 144 cuggaaugag cugaaaggg
19 145 19 RNA Artificial Sequence Synthetic 145 uggaaugagc
ugaaaggga 19 146 19 RNA Artificial Sequence Synthetic 146
ggaaugagcu gaaagggac 19 147 19 RNA Artificial Sequence Synthetic
147 gaaugagcug aaagggacu 19 148 19 RNA Artificial Sequence
Synthetic 148 aaugagcuga aagggacuu 19 149 19 RNA Artificial
Sequence Synthetic 149 augagcugaa agggacuuc 19 150 19 RNA
Artificial Sequence Synthetic 150 ugagcugaaa gggacuucc 19 151 19
RNA Artificial Sequence Synthetic 151 gagcugaaag ggacuucca 19 152
19 RNA Artificial Sequence Synthetic 152 agcugaaagg gacuuccaa 19
153 19 RNA Artificial Sequence Synthetic 153 gcugaaaggg acuuccaag
19 154 19 RNA Artificial Sequence Synthetic 154 cugaaaggga
cuuccaagg 19 155 19 RNA Artificial Sequence Synthetic 155
ugaaagggac uuccaagga 19 156 19 RNA Artificial Sequence Synthetic
156 gaaagggacu uccaaggaa 19 157 19 RNA Artificial Sequence
Synthetic 157 aaagggacuu ccaaggaag 19 158 19 RNA Artificial
Sequence Synthetic 158 aagggacuuc caaggaaga 19 159 19 RNA
Artificial Sequence Synthetic 159 agggacuucc aaggaagau 19 160 19
RNA Artificial Sequence Synthetic 160 gggacuucca aggaagaug 19 161
19 RNA Artificial Sequence Synthetic 161 ggacuuccaa ggaagaugc 19
162 19 RNA Artificial Sequence Synthetic 162 gacuuccaag gaagaugcc
19 163 19 RNA Artificial Sequence Synthetic 163 acuuccaagg
aagaugcca 19 164 19 RNA Artificial Sequence Synthetic 164
cuuccaagga agaugccau 19 165 19 RNA Artificial Sequence Synthetic
165 uuccaaggaa gaugccaug 19 166 19 RNA Artificial Sequence
Synthetic 166 uccaaggaag augccauga 19 167 19 RNA Artificial
Sequence Synthetic 167 ccaaggaaga ugccaugaa 19 168 19 RNA
Artificial Sequence Synthetic 168 caaggaagau gccaugaaa 19 169 19
RNA Artificial Sequence Synthetic 169 aaggaagaug ccaugaaag 19 170
19 RNA Artificial Sequence Synthetic 170 aggaagaugc caugaaagc 19
171 19 RNA Artificial Sequence Synthetic 171 ggaagaugcc augaaagcu
19 172 19 RNA Artificial Sequence Synthetic 172 gaagaugcca
ugaaagcuu 19 173 19 RNA Artificial Sequence Synthetic 173
aagaugccau gaaagcuua 19 174 19 RNA Artificial Sequence Synthetic
174 agaugccaug aaagcuuac 19 175 19 RNA Artificial Sequence
Synthetic 175 gaugccauga aagcuuaca 19 176 19 RNA Artificial
Sequence Synthetic 176 augccaugaa agcuuacau 19 177 19 RNA
Artificial Sequence Synthetic 177 ugccaugaaa gcuuacauc 19 178 19
RNA Artificial Sequence Synthetic 178 gccaugaaag cuuacauca 19 179
19 RNA Artificial Sequence Synthetic 179 ccaugaaagc uuacaucaa 19
180 19 RNA Artificial Sequence Synthetic 180 caugaaagcu uacaucaac
19 181 19 RNA Artificial Sequence Synthetic 181 augaaagcuu
acaucaaca 19 182 19 RNA Artificial Sequence Synthetic 182
ugaaagcuua caucaacaa 19 183 19 RNA Artificial Sequence Synthetic
183 gaaagcuuac aucaacaaa 19 184 19 RNA Artificial Sequence
Synthetic 184 aaagcuuaca ucaacaaag 19 185 19 RNA Artificial
Sequence Synthetic 185 aagcuuacau caacaaagu 19 186 19 RNA
Artificial Sequence Synthetic 186 agcuuacauc aacaaagua 19 187 19
RNA Artificial Sequence Synthetic 187 gcuuacauca acaaaguag 19 188
19 RNA Artificial Sequence Synthetic 188 cuuacaucaa caaaguaga 19
189 19 RNA Artificial Sequence Synthetic 189 uuacaucaac aaaguagaa
19 190 19 RNA Artificial Sequence Synthetic 190 uacaucaaca
aaguagaag 19 191 19 RNA Artificial Sequence Synthetic 191
acaucaacaa aguagaaga 19 192 19 RNA Artificial Sequence Synthetic
192 caucaacaaa guagaagag 19 193 19 RNA Artificial Sequence
Synthetic 193 aucaacaaag uagaagagc 19 194 19 RNA Artificial
Sequence Synthetic 194 ucaacaaagu agaagagcu 19 195 19 RNA
Artificial Sequence Synthetic 195 caacaaagua gaagagcua 19 196 19
RNA Artificial Sequence Synthetic 196 aacaaaguag aagagcuaa 19 197
19 RNA Artificial Sequence Synthetic 197 acaaaguaga agagcuaaa 19
198 19 RNA Artificial Sequence Synthetic 198 caaaguagaa gagcuaaag
19 199 19 RNA Artificial Sequence Synthetic 199 aaaguagaag
agcuaaaga 19 200 19 RNA Artificial Sequence Synthetic 200
aaguagaaga gcuaaagaa 19 201 19 RNA Artificial Sequence Synthetic
201 aguagaagag cuaaagaaa 19 202 19 RNA Artificial Sequence
Synthetic 202 guagaagagc uaaagaaaa 19 203 19 RNA Artificial
Sequence Synthetic 203 uagaagagcu aaagaaaaa 19 204 19 RNA
Artificial Sequence Synthetic 204 agaagagcua aagaaaaaa 19 205 19
RNA Artificial Sequence Synthetic 205 gaagagcuaa agaaaaaau 19 206
19 RNA Artificial Sequence Synthetic 206 aagagcuaaa gaaaaaaua 19
207 19 RNA Artificial Sequence Synthetic 207 agagcuaaag aaaaaauac
19 208 19 RNA Artificial Sequence Synthetic 208 gagcuaaaga
aaaaauacg 19 209 19 RNA Artificial Sequence Synthetic 209
agcuaaagaa aaaauacgg 19 210 19 RNA Artificial Sequence Synthetic
210 gcuaaagaaa aaauacggg 19 211 19 RNA Artificial Sequence
Synthetic 211 auccucauaa aggccaaga 19 212 19 RNA Artificial
Sequence Synthetic 212 agauccucau aaaggccaa 19 213 19 RNA
Artificial Sequence Synthetic 213 agagauccuc auaaaggcc 19 214 19
RNA Artificial Sequence Synthetic 214 agagagaucc ucauaaagg 19 215
19 RNA Artificial Sequence Synthetic 215 ucagagagau ccucauaaa 19
216 19 RNA Artificial Sequence Synthetic 216 aaucagagag auccucaua
19 217 19 RNA Artificial Sequence Synthetic 217 aaaaucagag
agauccuca 19 218 19 RNA Artificial Sequence Synthetic 218
gaaaaaucag agagauccu 19 219 19 RNA Artificial Sequence Synthetic
219 aagaaaaauc agagagauc 19 220 19 RNA Artificial Sequence
Synthetic 220 gcaagaaaaa ucagagaga 19 221 19 RNA Artificial
Sequence Synthetic 221 acgcaagaaa aaucagaga 19 222 19 RNA
Artificial Sequence Synthetic 222 cgacgcaaga aaaaucaga 19 223 19
RNA Artificial Sequence Synthetic 223 cucgacgcaa gaaaaauca 19 224
19 RNA Artificial Sequence Synthetic 224 aacucgacgc aagaaaaau 19
225 19 RNA Artificial Sequence Synthetic 225 aaaacucgac gcaagaaaa
19 226 19 RNA Artificial Sequence Synthetic 226 ggaaaacucg
acgcaagaa 19 227 19 RNA Artificial Sequence Synthetic 227
ccggaaaacu cgacgcaag 19 228 19 RNA Artificial Sequence Synthetic
228 uaccggaaaa cucgacgca 19 229 19 RNA Artificial Sequence
Synthetic 229 cuuaccggaa aacucgacg 19 230 19 RNA Artificial
Sequence Synthetic 230 gucuuaccgg aaaacucga 19 231 19 RNA
Artificial Sequence Synthetic 231 aggucuuacc ggaaaacuc 19 232 19
RNA Artificial Sequence Synthetic 232 aaaggucuua ccggaaaac 19 233
19 RNA Artificial Sequence Synthetic 233 cgaaaggucu uaccggaaa 19
234 19 RNA Artificial Sequence Synthetic 234 accgaaaggu cuuaccgga
19 235 19 RNA Artificial Sequence Synthetic 235 guaccgaaag
gucuuaccg 19 236 19 RNA Artificial Sequence Synthetic 236
aaguaccgaa aggucuuac 19 237 19 RNA Artificial Sequence Synthetic
237 cgaaguaccg aaaggucuu 19 238 19 RNA Artificial Sequence
Synthetic 238 gacgaaguac cgaaagguc 19 239 19 RNA Artificial
Sequence Synthetic 239 uggacgaagu accgaaagg 19 240 19 RNA
Artificial Sequence Synthetic 240 uguggacgaa guaccgaaa 19 241 19
RNA Artificial Sequence Synthetic 241 uuuguggacg aaguaccga 19 242
19 RNA Artificial Sequence Synthetic 242 uguuugugga cgaaguacc 19
243 19 RNA Artificial Sequence Synthetic 243 uguguuugug gacgaagua
19 244 19 RNA Artificial Sequence Synthetic 244 guuguguuug
uggacgaag 19 245 19 RNA Artificial Sequence Synthetic 245
gaguuguguu uguggacga 19 246 19 RNA Artificial Sequence Synthetic
246 aggaguugug uuuguggac 19 247 19 RNA Artificial Sequence
Synthetic 247 ggaggaguug uguuugugg 19 248 19 RNA Artificial
Sequence Synthetic 248 gcggaggagu uguguuugu 19 249 19 RNA
Artificial Sequence Synthetic 249 gcgcggagga guuguguuu 19 250 19
RNA Artificial Sequence Synthetic 250 uugcgcggag gaguugugu 19 251
19 RNA Artificial Sequence Synthetic 251 aguugcgcgg aggaguugu 19
252 19 RNA Artificial Sequence Synthetic 252 aaaguugcgc ggaggaguu
19 253 19 RNA Artificial Sequence Synthetic 253 aaaaaguugc
gcggaggag 19 254 19 RNA Artificial Sequence Synthetic 254
cgaaaaaguu gcgcggagg 19 255 19 RNA Artificial Sequence Synthetic
255 cgcgaaaaag uugcgcgga 19 256 19 RNA Artificial Sequence
Synthetic 256 accgcgaaaa aguugcgcg 19 257 19 RNA Artificial
Sequence Synthetic 257 caaccgcgaa aaaguugcg 19 258 19 RNA
Artificial Sequence Synthetic 258 aacaaccgcg aaaaaguug 19 259 19
RNA Artificial Sequence Synthetic 259 guaacaaccg cgaaaaagu 19 260
19 RNA Artificial Sequence Synthetic 260 aaguaacaac cgcgaaaaa 19
261 19 RNA Artificial Sequence Synthetic 261 ucaaguaaca accgcgaaa
19 262 19 RNA Artificial Sequence Synthetic 262 agucaaguaa
caaccgcga 19 263 19 RNA Artificial Sequence Synthetic 263
ccagucaagu aacaaccgc 19 264 19 RNA Artificial Sequence Synthetic
264 cgccagucaa guaacaacc 19 265 19 RNA Artificial Sequence
Synthetic 265 gucgccaguc aaguaacaa 19 266 19 RNA Artificial
Sequence Synthetic 266 acgucgccag ucaaguaac 19 267 19 RNA
Artificial Sequence Synthetic 267 uuacgucgcc agucaagua 19 268 19
RNA Artificial Sequence Synthetic 268 gauuacgucg ccagucaag 19 269
19 RNA Artificial Sequence Synthetic 269 uggauuacgu cgccaguca 19
270 19 RNA Artificial Sequence Synthetic 270 cguggauuac gucgccagu
19 271 19 RNA Artificial Sequence Synthetic 271 aucguggauu
acgucgcca 19 272 19 RNA Artificial Sequence Synthetic 272
agaucgugga uuacgucgc 19 273 19 RNA Artificial Sequence Synthetic
273 agagaucgug gauuacguc 19 274 19 RNA Artificial Sequence
Synthetic 274 aaagagaucg uggauuacg 19 275 19 RNA Artificial
Sequence Synthetic 275 aaaaagagau cguggauua 19 276 19 RNA
Artificial Sequence Synthetic 276 ggaaaaagag aucguggau 19 277 19
RNA Artificial Sequence Synthetic 277 acggaaaaag agaucgugg 19 278
19 RNA Artificial Sequence Synthetic 278 ugacggaaaa agagaucgu 19
279 19 RNA Artificial Sequence Synthetic 279 gaugacggaa aaagagauc
19 280 19 RNA Artificial Sequence Synthetic 280 acgaugacgg
aaaaagaga 19 281 19 RNA Artificial Sequence Synthetic 281
agacgaugac ggaaaaaga 19 282 19 RNA Artificial Sequence Synthetic
282 aaagacgaug acggaaaaa 19 283 19 RNA Artificial Sequence
Synthetic 283 ggaaagacga ugacggaaa 19 284 19 RNA Artificial
Sequence Synthetic 284 acggaaagac gaugacgga 19 285 19 RNA
Artificial Sequence Synthetic 285 gcacggaaag acgaugacg 19 286 19
RNA Artificial Sequence Synthetic 286
gagcacggaa agacgauga 19 287 19 RNA Artificial Sequence Synthetic
287 uggagcacgg aaagacgau 19 288 19 RNA Artificial Sequence
Synthetic 288 uuuggagcac ggaaagacg 19 289 19 RNA Artificial
Sequence Synthetic 289 guuuuggagc acggaaaga 19 290 19 RNA
Artificial Sequence Synthetic 290 uuguuuugga gcacggaaa 19 291 19
RNA Artificial Sequence Synthetic 291 uguuguuuug gagcacgga 19 292
19 RNA Artificial Sequence Synthetic 292 guuguuguuu uggagcacg 19
293 19 RNA Artificial Sequence Synthetic 293 ccguuguugu uuuggagca
19 294 19 RNA Artificial Sequence Synthetic 294 cgccguuguu
guuuuggag 19 295 19 RNA Artificial Sequence Synthetic 295
gccgccguug uuguuuugg 19 296 19 RNA Artificial Sequence Synthetic
296 ccgccgccgu uguuguuuu 19 297 19 RNA Artificial Sequence
Synthetic 297 ucccgccgcc guuguuguu 19 298 19 RNA Artificial
Sequence Synthetic 298 cuucccgccg ccguuguug 19 299 19 RNA
Artificial Sequence Synthetic 299 aacuucccgc cgccguugu 19 300 19
RNA Artificial Sequence Synthetic 300 ugaacuuccc gccgccguu 19 301
19 RNA Artificial Sequence Synthetic 301 gggagauagu gaugaagua 19
302 19 RNA Artificial Sequence Synthetic 302 gaaguacauc cauuauaag
19 303 19 RNA Artificial Sequence Synthetic 303 guacgacaac
cgggagaua 19 304 19 RNA Artificial Sequence Synthetic 304
agauagugau gaaguacau 19 305 19 RNA Artificial Sequence Synthetic
305 ugaagacucu gcucaguuu 19 306 19 RNA Artificial Sequence
Synthetic 306 gcaugcggcc ucuguuuga 19 307 19 RNA Artificial
Sequence Synthetic 307 ugcggccucu guuugauuu 19 308 19 RNA
Artificial Sequence Synthetic 308 gagauaguga ugaaguaca 19 309 19
RNA Artificial Sequence Synthetic 309 ggagauagug augaaguac 19 310
19 RNA Artificial Sequence Synthetic 310 gaagacucug cucaguuug 19
311 19 DNA Artificial Sequence Synthetic 311 ggaaccagcg ccagagtga
19 312 19 DNA Artificial Sequence Synthetic 312 gagcgagatt
gcaggcata 19 313 19 DNA Artificial Sequence Synthetic 313
gttagtatct gatgacttg 19 314 19 DNA Artificial Sequence Synthetic
314 gaaatggaac cactaagaa 19 315 19 DNA Artificial Sequence
Synthetic 315 ggaaatggaa ccactaaga 19 316 19 DNA Artificial
Sequence Synthetic 316 caactacact ttccaatgc 19 317 19 DNA
Artificial Sequence Synthetic 317 ccaccaagat ttcatgata 19 318 19
DNA Artificial Sequence Synthetic 318 gatcggaact ccaacaaga 19 319
19 DNA Artificial Sequence Synthetic 319 aaacggagct acagattat 19
320 19 DNA Artificial Sequence Synthetic 320 ccacacagca ttcttgtaa
19 321 19 DNA Artificial Sequence Synthetic 321 gaagttacct
tgagcaatc 19 322 19 DNA Artificial Sequence Synthetic 322
ggacttggcc gatccagaa 19 323 19 DNA Artificial Sequence Synthetic
323 gcacttggat cgagatgag 19 324 19 DNA Artificial Sequence
Synthetic 324 caaagaccaa ttcgcgtta 19 325 19 DNA Artificial
Sequence Synthetic 325 ccgaatcaat cgcatcttc 19 326 19 DNA
Artificial Sequence Synthetic 326 gacatgatcc tgcagttca 19 327 19
DNA Artificial Sequence Synthetic 327 gagcgaatcg tcaccactt 19 328
19 DNA Artificial Sequence Synthetic 328 cctccgagct ggcgtctac 19
329 19 DNA Artificial Sequence Synthetic 329 tcacatggtt aacctctaa
19 330 19 DNA Artificial Sequence Synthetic 330 gatgagggac
gccataatc 19 331 19 DNA Artificial Sequence Synthetic 331
cctctaacta caaatctta 19 332 19 DNA Artificial Sequence Synthetic
332 ggaaggtgct atccaaaat 19 333 19 DNA Artificial Sequence
Synthetic 333 gcaagcaagt cctaacatt 19 334 19 DNA Artificial
Sequence Synthetic 334 ggaagaggag tagacctta 19 335 19 DNA
Artificial Sequence Synthetic 335 aggaatcagt gttgtagta 19 336 19
DNA Artificial Sequence Synthetic 336 gaagaggagt agaccttac 19 337
19 DNA Artificial Sequence Synthetic 337 gaaagtcaag cctggtatt 19
338 19 DNA Artificial Sequence Synthetic 338 aaagtcaagc ctggtatta
19 339 19 DNA Artificial Sequence Synthetic 339 gctatgaacg
tgaatgatc 19 340 19 DNA Artificial Sequence Synthetic 340
caagcctggt attacgttt 19 341 19 DNA Artificial Sequence Synthetic
341 ggaacaagat ctgtcaatt 19 342 19 DNA Artificial Sequence
Synthetic 342 gcaatgaacg tgaacgaaa 19 343 19 DNA Artificial
Sequence Synthetic 343 caatgaacgt gaacgaaat 19 344 19 DNA
Artificial Sequence Synthetic 344 ggacaggagc ggtatcaca 19 345 19
DNA Artificial Sequence Synthetic 345 agacagagct tgagaataa 19 346
19 DNA Artificial Sequence Synthetic 346 gagaagatct ttatgcaaa 19
347 19 DNA Artificial Sequence Synthetic 347 gaagagaaat cagcagata
19 348 19 DNA Artificial Sequence Synthetic 348 gcaagtaact
caactaaca 19 349 19 DNA Artificial Sequence Synthetic 349
gagctaatct gccacattg 19 350 19 DNA Artificial Sequence Synthetic
350 gcagatgagt tactagaaa 19 351 19 DNA Artificial Sequence
Synthetic 351 caacttaatt gtccagaaa 19 352 19 DNA Artificial
Sequence Synthetic 352 caacacagga ttctgataa 19 353 19 DNA
Artificial Sequence Synthetic 353 agattgtgcc taagtctct 19 354 19
DNA Artificial Sequence Synthetic 354 atgaagatct ggaggtgaa 19 355
19 DNA Artificial Sequence Synthetic 355 tttgagactt cttgcctaa 19
356 19 DNA Artificial Sequence Synthetic 356 agatcaccct ccttaaata
19 357 19 DNA Artificial Sequence Synthetic 357 caacggattt
ggtcgtatt 19 358 19 DNA Artificial Sequence Synthetic 358
gaaatcccat caccatctt 19 359 19 DNA Artificial Sequence Synthetic
359 gacctcaact acatggttt 19 360 19 DNA Artificial Sequence
Synthetic 360 tggtttacat gttccaata 19 361 19 DNA Artificial
Sequence Synthetic 361 gaagaaatcg atgttgttt 19 362 19 DNA
Artificial Sequence Synthetic 362 acacaaactt gaacagcta 19 363 19
DNA Artificial Sequence Synthetic 363 ggaagaaatc gatgttgtt 19 364
19 DNA Artificial Sequence Synthetic 364 gaaacgacga gaacagttg 19
365 19 DNA Artificial Sequence Synthetic 365 gcacatggat ggaggttct
19 366 19 DNA Artificial Sequence Synthetic 366 gcagagagag
cagatttga 19 367 19 DNA Artificial Sequence Synthetic 367
gaggttctct ggatcaagt 19 368 19 DNA Artificial Sequence Synthetic
368 gagcagattt gaagcaact 19 369 19 DNA Artificial Sequence
Synthetic 369 caaagacgat gacttcgaa 19 370 19 DNA Artificial
Sequence Synthetic 370 gatcagcatt tgcatggaa 19 371 19 DNA
Artificial Sequence Synthetic 371 tccaggagtt tgtcaataa 19 372 19
DNA Artificial Sequence Synthetic 372 ggaagctgat ccaccttga 19 373
19 DNA Artificial Sequence Synthetic 373 gcagaaatct aaggatata 19
374 19 DNA Artificial Sequence Synthetic 374 caacaaggat gaagtctat
19 375 19 DNA Artificial Sequence Synthetic 375 cagcagaaat
ctaaggata 19 376 19 DNA Artificial Sequence Synthetic 376
ctagatggct ttctcagta 19 377 19 DNA Artificial Sequence Synthetic
377 agacaaggtc ccaaagaca 19 378 19 DNA Artificial Sequence
Synthetic 378 ggaatggcaa gaccagcaa 19 379 19 DNA Artificial
Sequence Synthetic 379 agaattattc cagggttta 19 380 19 DNA
Artificial Sequence Synthetic 380 gcagacaagg tcccaaaga 19 381 19
DNA Artificial Sequence Synthetic 381 agaagcagct tcaggatga 19 382
19 DNA Artificial Sequence Synthetic 382 gagcttgact tccagaaga 19
383 19 DNA Artificial Sequence Synthetic 383 ccaccgaagt tcaccctaa
19 384 19 DNA Artificial Sequence Synthetic 384 gagaagagct
cctccatca 19 385 19 DNA Artificial Sequence Synthetic 385
gaaagagcat ctacggtga 19 386 19 DNA Artificial Sequence Synthetic
386 gaaaggattt ggctacaaa 19 387 19 DNA Artificial Sequence
Synthetic 387 acagcaaatt ccatcgtgt 19 388 19 DNA Artificial
Sequence Synthetic 388 ggaaagactg ttccaaaaa 19 389 19 DNA
Artificial Sequence Synthetic 389 caacacgcct catcctcta 19 390 19
DNA Artificial Sequence Synthetic 390 catgaaagct tacatcaac 19 391
19 DNA Artificial Sequence Synthetic 391 aagatgccat gaaagctta 19
392 19 DNA Artificial Sequence Synthetic 392 gcacataccg cctgagtct
19 393 19 DNA Artificial Sequence Synthetic 393 gatcaaatct
gaagaagga 19 394 19 DNA Artificial Sequence Synthetic 394
gccaagaagt ttcctaata 19 395 19 DNA Artificial Sequence Synthetic
395 cagcatatct tgaaccatt 19 396 19 DNA Artificial Sequence
Synthetic 396 gaacaaagga aacggatga 19 397 19 DNA Artificial
Sequence Synthetic 397 cggaaacggt ccaggctat 19 398 19 DNA
Artificial Sequence Synthetic 398 gcttcgagca gacatgata 19 399 19
DNA Artificial Sequence Synthetic 399 cctacacggt cctcctata 19 400
19 DNA Artificial Sequence Synthetic 400 gccaagaacc tcatcatct 19
401 19 DNA Artificial Sequence Synthetic 401 gatatgggct gaatacaaa
19 402 19 DNA Artificial Sequence Synthetic 402 gcactctgat
tgacaaata 19 403 19 DNA Artificial Sequence Synthetic 403
tgaagtctct gattaagta 19 404 19 DNA Artificial Sequence Synthetic
404 tcagagagat cctcataaa 19 405 19 DNA Artificial Sequence
Synthetic 405 gcaagaagat caccatttc 19 406 19 DNA Artificial
Sequence Synthetic 406 gagagaaatt tgaggatga 19 407 19 DNA
Artificial Sequence Synthetic 407 gaaaggattt ggctataag 19 408 19
DNA Artificial Sequence Synthetic 408 gaaagaaggc atgaacatt 19 409
19 DNA Artificial Sequence Synthetic 409 gggagatagt gatgaagta 19
410 19 DNA Artificial Sequence Synthetic 410 gaagtacatc cattataag
19 411 19 DNA Artificial Sequence Synthetic 411 gtacgacaac
cgggagata 19 412 19 DNA Artificial Sequence Synthetic 412
agatagtgat gaagtacat 19 413 19 DNA Artificial Sequence Synthetic
413 tgaagactct gctcagttt 19 414 19 DNA Artificial Sequence
Synthetic 414 gcatgcggcc tctgtttga 19 415 19 DNA Artificial
Sequence Synthetic 415 gcacacagcu uacuacauc 19 416 19 DNA
Artificial Sequence Synthetic 416 gaaaugcccu gguaucuca 19 417 19
DNA Artificial Sequence Synthetic 417 gaaggaacgu gaugugauc 19 418
19 DNA Artificial Sequence Synthetic 418 gcacuacucc uguguguga 19
419 19 DNA Artificial Sequence Synthetic 419 gaacccagcu ggagaacuu
19 420 19 DNA Artificial Sequence Synthetic 420 gauauacagu
gugaucuua 19 421 19 DNA Artificial Sequence Synthetic 421
guacuacgau ccugauuau 19 422 19 DNA Artificial Sequence Synthetic
422 gugccgaccu uuacaauuu 19 423 19 DNA Artificial Sequence
Synthetic 423 gaaggaaact gaattcaaa 19 424 19 DNA Artificial
Sequence Synthetic 424 ggaaatatgt actacgaaa 19 425 19 DNA
Artificial Sequence Synthetic 425 ccacaaagca gtgaattta 19 426 19
DNA Artificial Sequence Synthetic 426 gtaacaagct cacgcagtt 19 427
19 DNA Artificial Sequence Synthetic 427 gaaagaatct gtagagaaa 19
428 19 DNA Artificial Sequence Synthetic 428 gcaatgagct gtttgaaga
19 429 19 DNA Artificial Sequence Synthetic 429 tgacaaaggt
ggataaatt 19 430 19 DNA Artificial Sequence Synthetic 430
ggaaatggat ctctttgaa 19 431 19 DNA Artificial Sequence Synthetic
431 ggaaagtaat ggtccaaca 19 432 19 DNA Artificial Sequence
Synthetic 432 agacagttat gcagctatt 19 433 19 DNA Artificial
Sequence Synthetic 433 ccaattctcg gaagcaaga 19 434 19 DNA
Artificial Sequence Synthetic 434 gaaagtaatg gtccaacag 19 435 19
DNA Artificial Sequence Synthetic 435 gcgccagagt gaacaagta 19 436
19 DNA Artificial Sequence Synthetic 436 gaaggtggcc cagctatgt
19
437 19 RNA Artificial Sequence Synthetic 437 gagauggcac aggaggaaa
19
* * * * *