Abstract
The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.
Highlights
Targeted gene therapy provides an efficient approach to the development of anti-bacterial and antiviral drugs
We present a proposed bioinformatics pipeline based on the original scheme of the search for the conserved targets and including the original statistical criteria for mutational analysis with deep sequencing data
In the majority of bioinformatic pipelines, the mutations are detected against fixed predetermined targets
Summary
Targeted gene therapy provides an efficient approach to the development of anti-bacterial and antiviral drugs. In such therapies, the drugs bind to specific targets within bacterial and viral proteins or genomes and suppress the activity of the pathogen [1,2,3]. Mutations in DNA fragments corresponding to the drug targets destroy the binding specificity and produce so-called mutational escape from the particular drug. As mutations are often induced during replication, the rate of replication may affect the frequency of mutations. The mutational escape becomes especially significant for viruses that have relatively small genomes and high replication rates [4,5]. According to the World Health Organization, the annual global burden of communicable diseases (of which viral diseases play a major part) amounts to ~15 million cases [6]
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