Method for selecting SIRNAs from a plurality of SIRNAs for gene silencing

• US 8,457,902 B2
• Filed: 05/04/2011
• Issued: 06/04/2013
• 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: Jackson, Aimee L., Bartz, Steven R., Burchard, Julja, Linsley, Peter S., Wei, Ge, Cavet, Guy L.
• Primary Examiner(s): ZEMAN, MARY K
• Application Number:
  US13/100,836
• Publication Number:
  US 20110250591A1
• Time in Patent Office: 762 Days
• Field of Search: None
• US Class Current: 702/19
• 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, (i) for each of said siRNA in said plurality of different 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 different 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, wherein at least one of steps (i), (ii) or (iii) is performed by a suitably programmed computer.

2. The method of claim 1, wherein said predicting comprises (i1) evaluating the sequence of each of said plurality of genes according to a predetermined siRNA sequence match pattern;

and (i2) predicting said gene as an off-target gene if said gene comprises a sequence that matches said siRNA according to said sequence match pattern, wherein each said siRNA has L nucleotides in its duplex region, and wherein said sequence 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.

3. The method of claim 2, wherein said step (i1) comprises calculating a position match score pmScore according to equation

4. The method of claim 3, wherein L is 19, and wherein said pmPSSM is given by Table I.

5. The method of claim 4, wherein said plurality of genes comprises all known unique genes of said organism other than said target gene.

6. The method of claim 2, wherein said step of evaluating comprises identifying an alignment of said siRNA to a sequence in a gene by a low stringency FastA alignment.

7. The method of claim 1, wherein said one or more siRNAs comprises at least 3 siRNAs.

8. The method of claim 7, further comprising a step of de-overlapping, said step of de-overlapping comprising selecting a plurality of siRNAs among said at least 3 siRNAs such that siRNAs in said plurality are sufficiently different in a sequence diversity measure.

9. The method of claim 8, wherein said diversity measure is a quantifiable measure, and said selecting in said de-overlapping step comprises selecting siRNAs having a difference in said sequence diversity measure between different selected siRNAs above a given threshold.

10. The method of claim 9, wherein said sequence diversity measure is the overall GC content of said siRNAs.

11. The method of claim 10, wherein said given threshold is 5%.

12. The method of claim 9, wherein said sequence diversity measure is the distance between siRNAs along the length of the transcript sequence.

13. The method of claim 12, wherein said threshold is 100 nucleotides.