[siRNAs with high specificity to the target: a systematic design by CRM algorithm].
'Off-target' silencing effect hinders the development of siRNA-based therapeutic and research applications. Common solution to this problem is an employment of the BLAST that may miss significant alignments or an exhaustive Smith-Waterman algorithm that is very time-consuming. We have developed a Comprehensive Redundancy Minimizer (CRM) approach for mapping all unique sequences ("targets") 9-to-15 nt in size within large sets of sequences (e.g. transcriptomes). CRM outputs a list of potential siRNA candidates for every transcript of the particular species. These candidates could be further analyzed by traditional "set-of-rules" types of siRNA designing tools. For human, 91% of transcripts are covered by candidate siRNAs with kernel targets of N = 15. We tested our approach on the collection of previously described experimentally assessed siRNAs and found that the correlation between efficacy and presence in CRM-approved set is significant (r = 0.215, p-value = 0.0001). An interactive database that contains a precompiled set of all human siRNA candidates with minimized redundancy is available at http://129.174.194.243. Application of the CRM-based filtering minimizes potential "off-target" silencing effects and could improve routine siRNA applications.
Alsheddi
T
T
Vasin
L
L
Meduri
R
R
Randhawa
M
M
Glazko
G
G
Baranova
A
A
D000465:Algorithms; D000818:Animals; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D020407:Internet; D051379:Mice; D034741:RNA, Small Interfering / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods
D034741:RNA, Small Interfering