Dataset Information

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

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.

SUBMITTER: Kravatsky Y

PROVIDER: S-EPMC5744132 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

Kravatsky Yuri Y Chechetkin Vladimir V Fedoseeva Daria D Gorbacheva Maria M Kravatskaya Galina G Kretova Olga O Tchurikov Nickolai N

Viruses 20171123 12

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 millio ...[more]

PMID: 29168754

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Project description:The recent pandemic of SARS-CoV-2 infection has affected more than 3.0 million people worldwide with more than 200 thousand reported deaths. The SARS-CoV-2 genome has the capability of gaining rapid mutations as the virus spreads. Whole-genome sequencing data offers a wide range of opportunities to study mutation dynamics. The advantage of an increasing amount of whole-genome sequence data of SARS-CoV-2 intrigued us to explore the mutation profile across the genome, to check the genome diversity, and to investigate the implications of those mutations in protein stability and viral transmission. We have identified frequently mutated residues by aligning ~660 SARS-CoV-2 genomes and validated in 10,000 datasets available in GISAID Nextstrain. We further evaluated the potential of these frequently mutated residues in protein structure stability of spike glycoprotein and their possible functional consequences in other proteins. Among the 11 genes, surface glycoprotein, nucleocapsid, ORF1ab, and ORF8 showed frequent mutations, while envelop, membrane, ORF6, ORF7a and ORF7b showed conservation in terms of amino acid substitutions. Combined analysis with the frequently mutated residues identified 20 viral variants, among which 12 specific combinations comprised more than 97% of the isolates considered for the analysis. Some of the mutations across different proteins showed co-occurrences, suggesting their structural and/or functional interaction among different SARS-COV-2 proteins, and their involvement in adaptability and viral transmission. Analysis of protein structure stability of surface glycoprotein mutants indicated the viability of specific variants and are more prone to be temporally and spatially distributed across the globe. A similar empirical analysis of other proteins indicated the existence of important functional implications of several variants. Identification of frequently mutated variants among COVID-19 patients might be useful for better clinical management, contact tracing, and containment of the disease.

Dataset Information

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

Publications

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

Similar Datasets

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