Method of designing siRNAs for gene silencing

• US 7,962,316 B2
• Filed: 10/27/2004
• Issued: 06/14/2011
• Est. Priority Date: 10/27/2003
• Status: Active Grant

• Current Assignee: Merck Sharp & Dohme LLC (Merck & Co., Inc.)
• Original Assignee: Merck Sharp & Dohme Corporation (Merck & Co., Inc.)
• Inventors: Burchard, Julja, Jackson, Aimee L., Bartz, Steven R., Ge, Wei, Linsley, Peter S., Cavet, Guy L.
• Primary Examiner(s): Smith; Carolyn L.
• Application Number:
  US10/577,696
• Publication Number:
  US 20080234941A1
• Time in Patent Office: 2,421 Days
• Field of Search: None
• US Class Current: 703/2
• CPC Class Codes: C12N 15/111 General methods applicable to biologically active non-coding nucleic acids
• CPC Class Codes: C12N 2310/14 interfering N.A.
• CPC Class Codes: C12N 2320/11 for the determination of target sites, i.e. of active nucleic acids
• CPC Class Codes: C12N 2330/31 Libraries, arrays
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 20/30 Detection of binding sites or motifs
• CPC Class Codes: G16B 20/50 Mutagenesis
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 30/10 Sequence alignment; Homology search

Abstract

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.

Claims

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

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

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

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

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

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.