A Database-Based Two-Phase Algorithm for Efficient and Complete Detection of siRNA Off-Target Homology (Informatica, 2014)
Since the discovery of RNA Interference (RNAi), a cellular phenomenon in which a small double stranded RNA induces the degradation of its sequence specific target mRNA, using a computer-aided software tool to help design functional small interfering RNA (siRNA) or small hairpin RNA (shRNA) has become a standard procedure in applying RNAi to silence a target gene. A critical consideration in siRNA design is to avoid any possible off-target effect, i.e. to avoid sequence homology with untargeted genes. Though BLAST is the most powerful sequence alignment tool, it can overlook some significant homologies. Therefore, Smith-Waterman algorithm is the only approach that can guarantee to find all possible mismatch alignments that may cause off-target effect. However, Smith-Waterman alignment suffers from its inefficiency in searching through a large sequence database. A two-phase search algorithm was previously reported in which the first phase is used to identify local regions where the second phase, a bona fide Smith-Waterman alignment, is absolutely needed. Though such a two-phase homology search can improve the efficiency up to two orders of magnitude over the original Smith-Waterman alignment algorithm, it is still not efficient enough to be used alone for siRNA off-target homology search over a large sequence database. In this paper, we propose several improvements that dramatically speed up the reported two-phase algorithm while still guaranteeing the complete identification of siRNA off-target homologies.