Overview
The "off-target" silencing effect hinders the development of siRNA-based therapeutic and research applications. For each human gene, there are parts that are unique, i.e. has no similarity to other human genes and shared, i.e. present in other transcribed sequences. When we are talking about DNA strings of 17 bp and larger, sorting unique sequences from shared ones is trivial task. For a short stretch of nucleotides, the situation is different. For example, every human gene contains at least one triplet ATG; therefore this sequence can not be unique and will always contribute to off-target hybridizations. The trade-off between the length of oligonucleotide and the requirement of no off-target hybridization is obvious.
This database will help you to design siRNA with minimized off-target hybridization by highlighting the best siRNA locations within your favorite gene ("siRNA seats"). We had pre-computed optimized "seats" for siRNA using complete set of human genes. It important to realize that the potential seat for 21-nucleotide siRNA comprised of a total of 8 overlapping 14-nucleotide sequences has lower potential for off-traget hybridization that the seat comprised of 7 overlapping 15-nucleotide sequences. Therefore, to find the best seat for gene-specific siRNA design, one should start the search with minimal length of nucleotide available (n=12). If these seats are not found in given gene, one should move up to a higher number of nucleotides (n=13) or (n=14).
This set of "siRNA seats" with minimized off-target hybridization has been computed using a novel approach to sort all possible short string subsequences within the large sequence (in this case, complete set of human genes). This algorithm reduces the computational time using tree-based storage while simultaneously delivering a comprehensive analysis of the genomic distribution of all possible exact matches within the input set of the sequences.
Reference:
A. Baranova, J. Bode, G. Manyam and M. Emelianenko "A Tree-based Algorithm for systematic analysis of siRNA Sequences", in submission