Long single-molecule reads can resolve the complexity of the influenza virus composed of rare, closely related mutant variants

Alexander Artyomenko, Nicholas C. Wu, Serghei Mangul, Eleazar Eskin, Ren Sun, Alex Zelikovsky

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As a result of a high rate of mutations and recombination events, an RNA-virus exists as a heterogeneous “swarm” of mutant variants. The long read length offered by single-molecule sequencing technologies allows each mutant variant to be sequenced in a single pass. However, high error rate limits the ability to reconstruct heterogeneous viral population composed of rare, related mutant variants. In this paper, we present 2SNV, a method able to tolerate the high error-rate of the singlemolecule protocol and reconstruct mutant variants. 2SNV uses linkage between single nucleotide variations to efficiently distinguish them from read errors. To benchmark the sensitivity of 2SNV, we performed a single-molecule sequencing experiment on a sample containing a titrated level of known viral mutant variants. Our method is able to accurately reconstruct clone with frequency of 0.2% and distinguish clones that differed in only two nucleotides distantly located on the genome. 2SNV outperforms existing methods for full-length viral mutant reconstruction. The open source implementation of 2SNV is freely available for download at http://alan.cs.gsu.edu/NGS/?q=content/2snv.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 20th Annual Conference, RECOMB 2016, Proceedings
EditorsMona Singh
PublisherSpringer
Pages164-175
Number of pages12
ISBN (Print)9783319319568
DOIs
StatePublished - 2016
Externally publishedYes
Event20th Annual Conference on Research in Computational Molecular Biology, RECOMB 2016 - Santa Monica, United States
Duration: Apr 17 2016Apr 21 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9649
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Annual Conference on Research in Computational Molecular Biology, RECOMB 2016
Country/TerritoryUnited States
CitySanta Monica
Period4/17/164/21/16

Keywords

  • RNA viral variants
  • Single nucleotide Variation
  • SMRT reads

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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