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Conference Paper: Long Single-Molecule Reads Can Resolve the Complexity of the Influenza Virus Composed of Rare, Closely Related Mutant Variants

TitleLong Single-Molecule Reads Can Resolve the Complexity of the Influenza Virus Composed of Rare, Closely Related Mutant Variants
Authors
KeywordsRNA viral variants
SMRT reads
Single-nucleotide variation
Issue Date2017
Citation
Journal of Computational Biology, 2017, v. 24, n. 6, p. 558-570 How to Cite?
Abstract© 2017, Mary Ann Liebert, Inc. 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.
Persistent Identifierhttp://hdl.handle.net/10722/285789
ISSN
2023 Impact Factor: 1.4
2023 SCImago Journal Rankings: 0.659
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorArtyomenko, Alexander-
dc.contributor.authorWu, Nicholas C.-
dc.contributor.authorMangul, Serghei-
dc.contributor.authorEskin, Eleazar-
dc.contributor.authorSun, Ren-
dc.contributor.authorZelikovsky, Alex-
dc.date.accessioned2020-08-18T04:56:39Z-
dc.date.available2020-08-18T04:56:39Z-
dc.date.issued2017-
dc.identifier.citationJournal of Computational Biology, 2017, v. 24, n. 6, p. 558-570-
dc.identifier.issn1066-5277-
dc.identifier.urihttp://hdl.handle.net/10722/285789-
dc.description.abstract© 2017, Mary Ann Liebert, Inc. 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.-
dc.languageeng-
dc.relation.ispartofJournal of Computational Biology-
dc.subjectRNA viral variants-
dc.subjectSMRT reads-
dc.subjectSingle-nucleotide variation-
dc.titleLong Single-Molecule Reads Can Resolve the Complexity of the Influenza Virus Composed of Rare, Closely Related Mutant Variants-
dc.typeConference_Paper-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1089/cmb.2016.0146-
dc.identifier.pmid27901586-
dc.identifier.pmcidPMC5467126-
dc.identifier.scopuseid_2-s2.0-85020439299-
dc.identifier.volume24-
dc.identifier.issue6-
dc.identifier.spage558-
dc.identifier.epage570-
dc.identifier.isiWOS:000402997500009-
dc.identifier.issnl1066-5277-

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