Abstract
BackgroundThe "off-target" silencing effect hinders the development of siRNA-based therapeutic and research applications. Existing solutions for finding possible locations of siRNA seats within a large database of genes are either too slow, miss a portion of the targets, or are simply not designed to handle a very large number of queries. We propose a new approach that reduces the computational time as compared to existing techniques.FindingsThe proposed method employs tree-based storage in a form of a modified truncated suffix tree to sort all possible short string substrings within given set of strings (i.e. transcriptome). Using the new algorithm, we pre-computed a list of the best siRNA locations within each human gene ("siRNA seats"). siRNAs designed to reside within siRNA seats are less likely to hybridize off-target. These siRNA seats could be used as an input for the traditional "set-of-rules" type of siRNA designing software. The list of siRNA seats is available through a publicly available database located at http://web.cos.gmu.edu/~gmanyam/siRNA_db/search.phpConclusionsIn attempt to perform top-down prediction of the human siRNA with minimized off-target hybridization, we developed an efficient algorithm that employs suffix tree based storage of the substrings. Applications of this approach are not limited to optimal siRNA design, but can also be useful for other tasks involving selection of the characteristic strings specific to individual genes. These strings could then be used as siRNA seats, as specific probes for gene expression studies by oligonucleotide-based microarrays, for the design of molecular beacon probes for Real-Time PCR and, generally, any type of PCR primers.
Highlights
Data structure and problem formulation Let us explain in details the type of structure our algorithm for sorting and analyzing the substrings within the entire transcriptome is based on
These strings could be used as specific doublestrand RNA molecules (siRNAs) seats, as specific probes for gene expression studies by oligonucleotide-based microarrays, for the design of molecular beacon probes for Real-Time PCR and, generally, any type of PCR primers
The complete list of siRNA locations with minimized off-target hybridization is available at http://web.cos.gmu.edu/~gmanyam/siRNA_db/search. php). These siRNA seats could be used as an input for the traditional “set-of-rules” type of siRNA designing software
Summary
Data structure and problem formulation Let us explain in details the type of structure our algorithm for sorting and analyzing the substrings within the entire transcriptome is based on. The “off-target” silencing effect hinders the development of siRNA-based therapeutic and research applications. Most important part of this process involves an interaction of target mRNA with string-specific doublestrand RNA molecules (siRNAs) of about 21 nt with 3’-overhangs [2]. E.g. when siRNA is applied as an antiviral treatment, it may lead to imbalance of the normal cellular functions that could, in turn, manifests as side effects of the therapy. This phenomenon, called ‘off-target’ silencing, is known as one of the most serious problems in RNA interference (RNAi) [3,5]. Until major improvement in siRNA design occurs, both the development of siRNA-based therapeutic applications and interpretation of gene function and phenotypes resulting from RNAi experiments will be hindered
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