Motivation: Designing highly effective short interfering RNA (siRNA) sequences with maximum target-specificity for mammalian RNA interference (RNAi) is one of the hottest topics in molecular biology. The relationship between siRNA sequences and RNAi activity has been studied extensively to establish rules for selecting highly effective sequences. However, there is a pressing need to compute siRNA sequences that minimize off-target silencing effects efficiently and to match any non-targeted sequences with mismatches.
Results: The enumeration of potential cross-hybridization candidates is non-trivial, because siRNA sequences are short, ca. 19 nt in length, and at least three mismatches with non-targets are required. With at least three mismatches, there are typically four or five contiguous matches, so that a BLAST search frequently overlooks off-target candidates. By contrast, existing accurate approaches are expensive to execute; thus we need to develop an accurate, efficient algorithm that uses seed hashing, the pigeonhole principle, and combinatorics to identify mismatch patterns. Tests show that our method can list potential cross-hybridization candidates for any siRNA sequence of selected human gene rapidly, outperforming traditional methods by orders of magnitude in terms of computational performance.
Availability: http://design.RNAi.jp
Contact: yamada@cb.k.u-tokyo.ac.jp.