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: Contribution to journalArticlepeer-review

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 article, we present two single-nucleotide variants (2SNV), a method able to tolerate the high error rate of the single-molecule 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.

Original languageEnglish (US)
Pages (from-to)558-570
Number of pages13
JournalJournal of Computational Biology
Volume24
Issue number6
DOIs
StatePublished - Jun 2017
Externally publishedYes

Keywords

  • RNA viral variants
  • Single-nucleotide variation
  • SMRT reads

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics

Fingerprint Dive into the research topics of 'Long Single-Molecule Reads Can Resolve the Complexity of the Influenza Virus Composed of Rare, Closely Related Mutant Variants'. Together they form a unique fingerprint.

Cite this