Method of designing siRNAs for gene silencing
View Patent ↗The present invention provides a method for identifying siRNA target motifs in a transcript using a position-specific score matrix approach. The invention also provides a method for identifying off-target genes of an siRNA using a position-specific score matrix approach. The invention further provides a method for designing siRNAs with higher silencing efficacy and specificity. The invention also provides a library of siRNAs comprising siRNAs with high silencing efficacy and specificity.
1. A method for selecting from a plurality of different siRNAs one or more siRNAs for silencing a target gene in an organism, each different siRNA in said plurality of different siRNAs targeting a different target sequence in a transcript of said target gene, said method comprising
(a) calculating a score for a corresponding targeted sequence motif in said transcript, for each said different siRNA in said plurality of different siRNAs, wherein said score is calculated using a position-specific score matrix (PSSM), wherein each said sequence motif is a nucleotide sequence of L nucleotides, L being an integer, and wherein said PSSM is {log(e ij /p ij )}, where e ij is the weight of nucleotide i at position j, p ij is the weight of nucleotide i at position j in a random sequence, and i=G or C, A, U(T), j=1, . . . L, wherein each of said targeted sequence motifs comprises at least a portion of the target sequence of the corresponding siRNA and/or a second sequence in a sequence region flanking said target sequence;
(b) ranking said plurality of different siRNAs according to said scores; and
(c) selecting one or more siRNAs from said ranked siRNAs, wherein at least one of steps (a), (b) or (c) is performed by a suitably programmed computer.
2. The method of claim 1 , wherein each said sequence motif comprises said target sequence of said targeting siRNA.
3. The method of claim 1 , wherein said score for each said siRNA is calculated according to equation
Score
=
∑
t
=
1
L
ln
(
e
t
/
p
t
)
wherein said e t and p t are respectively weights of the nucleotide at position t in said sequence motif as determined according to said position-specific score matrix and in a random sequence.
4. The method of claim 3 , wherein each said sequence motif comprises said target sequence of said targeting siRNA and at least one flanking sequence.
5. The method of claim 4 , wherein each said sequence motif comprises said target sequence of said targeting siRNA and a 5′ flanking sequence and a 3′ flanking sequence.
6. The method of claim 5 , wherein said 5′ flanking sequence and said 3′ flanking sequence are each a sequence of D nucleotides, D being an integer.
7. The method of claim 6 , wherein each said target sequence is a sequence of 19 nucleotides, and each said 5′ flanking sequence and 3′ flanking sequence are a sequence of 10 nucleotides.
8. The method of claim 5 , wherein each said target sequence is a sequence of 19 nucleotides, and each said 5′ flanking sequence and 3′ flanking sequence are a sequence of 50 nucleotides.
9. The method of claim 1 , further comprising a step of selecting one or more siRNAs based on silencing specificity, said step of selecting based on silencing specificity comprising, (i) for each of said plurality of siRNAs, predicting off-target genes of said siRNA from among a plurality of genes, wherein said off-target genes are genes other than said target gene and are directly silenced by said siRNA; (ii) ranking said plurality of siRNAs according to the number of off-target genes; and (iii) selecting one or more siRNAs for which said number of off-target genes is below a given threshold.
10. The method of claim 9 , wherein said predicting comprises (il) evaluating sequence of each of said plurality of genes based on a predetermined siRNA sequence match pattern; and (i2) predicting said gene as an off-target gene if said gene comprise a sequence that matches said siRNA based on said sequence match pattern.
11. The method of claim 10 , wherein said step of evaluating comprises identifying an alignment of said siRNA to a sequence in a gene by a low stringency FASTA alignment.
12. The method of claim 11 , wherein each said siRNA has L nucleotides in its duplex region, and wherein said match pattern is represented by a position match position-specific score matrix (pmPSSM), said position match position-specific score matrix consisting of weights of different positions in an siRNA to match transcript sequence positions in an off-target transcript {P j }, where j=1, . . . , L, P j is the weight of a match at position j.
13. The method of claim 12 , wherein said step (i1) comprises calculating a position match score pmScore according to equation
pmScore
=
∑
i
=
1
L
ln
(
E
i
/
0.25
)
where E i =P i if position i is a match and E i =(1-P i )/3 if position i is a mismatch; and said step (i2) comprises predicting said gene as an off-target gene if said position match score is greater than a given threshold.
14. The method of claim 13 , wherein L is 19, and wherein said pmPSSM is given by Table I.
15. The method of claim 14 , wherein said plurality of genes comprises all known unique genes of said organism other than said target gene.
16. The method of claim 7 , wherein said position-specific score matrix (PSSM) is obtained by a method comprising
(aa) identifying a plurality of N siRNAs consisting of siRNAs having 19-nucleotide duplex region and having a silencing efficacy above a chosen threshold;
(bb) identifying for each said siRNA a functional sequence motif, said functional sequence motif comprising a 19-nucleotide target sequence of said siRNA and a 10-nucleotide 5′ flanking sequence and a 10-nucleotide 3′ flanking sequence;
(cc) calculating a frequency matrix {f ij }, where i=G, C, A, U(T); j=1, 2, . . . , L, and where f ij is the frequency of the ith nucleotide at the jth position, based on said siRNAs functional sequence motifs according to equation
f
ij
=
∑
k
=
1
N
δ
ik
(
j
)
,
where
δ
ik
(
j
)
=
{
1
,
if
k
=
i
0
,
if
k
≠
i
,
and
(dd) determining said PSSM by calculating e ij according to equation
e
ij
=
f
ij
N
.
17. The method of claim 16 , wherein said plurality of N siRNAs target a plurality of different genes having different transcript abundances in a cell.
18. The method of claim 17 , wherein said step (c) is carried out by selecting one or more siRNAs having the highest scores.
19. The method of claim 17 , wherein said step (c) is carried out by selecting one or more siRNAs having a score closest to a predetermined value, wherein said predetermined value is the score value corresponding to the maximum median silencing efficacy of a plurality of siRNA sequence motifs.
20. The method of claim 19 , wherein said plurality of siRNA sequence motifs are sequence motifs in transcript having abundance level of less than about 3-5 copies per cell.
21. The method of claim 17 , wherein said step (c) is carried out by selecting one or more siRNAs having a score within a predetermined range, wherein said predetermined range is a score range corresponding to a plurality of siRNAs sequence motifs having a given level of silencing efficacy.
22. The method of claim 21 , wherein said silencing efficacy is above 50% at an siRNA dose of about 100 nM.
23. The method of claim 22 , wherein said plurality of siRNA sequence motifs are sequence motifs in transcript having abundance level of less than about 3-5 copies per cell.
24. The method of claim 1 , wherein said position-specific score matrix (PSSM) is obtained by a method comprising
(aa) initializing said PSSM with random weights;
(bb) selecting randomly a weight w ij obtained in (aa);
(cc) changing the value of said selected weight to generate a test psPSSM comprising said selected weight having said changed value;
(dd) calculating a score for each of a plurality of siRNAs functional sequence motifs using said test PSSM according to equation
Score
=
∑
k
=
1
L
ln
(
w
k
/
p
k
)
wherein said w k and p k are respectively weights of a nucleotide at position k in said functional sequence motif and in a random sequence;
(ee) calculating correlation of said score and a metric of a characteristic of an siRNA among said plurality of siRNAs functional sequence motifs;
(ff) repeating steps (cc)-(ee) for a plurality of different values of said selected weight in a given range and retain the value that corresponds to the best correlation for said selected weight; and
(gg) repeating steps (bb)-(ff) for a chosen number of times; thereby determining said PSSM.
25. The method of claim 24 , further comprising selecting said plurality of siRNA functional sequence motifs by a method comprising
(i) identifying a plurality of siRNAs consisting of siRNAs having different values in said metric;
(ii) identifying a plurality of siRNA functional sequence motifs each corresponding to an siRNA in said plurality of siRNAs.
26. The method of claim 25 , wherein said characteristic is silencing efficacy.
27. The method of claim 26 , wherein said plurality of N siRNAs target a plurality of different genes having different transcript abundances in a cell.
28. The method of claim 27 , wherein said step (c) is carried out by selecting one or more siRNAs having the highest scores.
29. The method of claim 27 , wherein said step (bb) is carried out by selecting one or more siRNAs having a score closest to a predetermined value, wherein said predetermined value is the score value corresponding to the maximum median silencing efficacy of a plurality of siRNA sequence motifs.
30. The method of claim 29 , wherein said plurality of siRNA sequence motifs are sequence motifs in transcript having abundance level of less than about 3-5 copies per cell.
31. The method of claim 27 , wherein said step (bb) is carried out by selecting one or more siRNAs having a score within a predetermined range, wherein said predetermined range is a score range corresponding to a plurality of siRNAs sequence motifs having a given level of silencing efficacy.
32. The method of claim 31 , wherein said silencing efficacy is above 50% at an siRNA dose of about 100 nM.
33. The method of claim 32 , wherein said plurality of siRNA sequence motifs are sequence motifs in transcript having abundance level of less than about 3-5 copies per cell.
34. The method of claim 24 , wherein said position-specific score matrix (PSSM) comprises w k , k=1, . . . , L, w k being a difference in probability of finding nucleotide G or C at sequence position k between a first type of siRNA and a second type of siRNA, and wherein said score for each said strand is calculated according to equation
Score
=
∑
k
=
1
L
w
k
.
35. The method of claim 34 , wherein said first type of siRNA consists of one or more siRNAs having silencing efficacy no less than a first threshold and said second type of siRNA consists of one or more siRNAs having silencing efficacy less than a second threshold.
36. The method of claim 35 , wherein said difference in probability is described by a sum of Gaussian curves, each of said Gaussian curves representing the difference in probability of finding a G or C at a different sequence position.
37. The method of claim 36 , wherein said first and second thresholds are both 75% at an siRNA dose of 100 nM.