title: Long Single-Molecule Reads Can Resolve the Complexity of the Influenza Virus Composed of Rare, Closely Related Mutant Variants.
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.
authors.affiliation: 1 Department of Computer Science, Georgia State University , Atlanta, Georgia .
authors.forename: Alexander
authors.initials: A
authors.lastname: Artyomenko
authors.affiliation: 2 Department of Integrative Structural and Computational Biology, The Scripps Research Institute , La Jolla, California.
authors.forename: Nicholas C
authors.initials: NC
authors.lastname: Wu
authors.affiliation: 3 Department of Computer Science, University of California , Los Angeles, Los Angeles, California.|4 Institute for Quantitative and Computational Biosciences, University of California Los Angeles , Los Angeles, California.
authors.forename: Serghei
authors.initials: S
authors.lastname: Mangul
authors.affiliation: 3 Department of Computer Science, University of California , Los Angeles, Los Angeles, California.
authors.forename: Eleazar
authors.initials: E
authors.lastname: Eskin
authors.affiliation: 5 Molecular and Medical Pharmacology, University of California , Los Angeles, Los Angeles, California.
authors.forename: Ren
authors.initials: R
authors.lastname: Sun
authors.affiliation: 1 Department of Computer Science, Georgia State University , Atlanta, Georgia .
authors.forename: Alex
authors.initials: A
authors.lastname: Zelikovsky
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D016679:Genome, Viral; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D009154:Mutation; D009975:Orthomyxoviridae / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*
keywords: RNA viral variants; SMRT reads; single-nucleotide variation