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 language | English (US) |
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Pages (from-to) | 558-570 |
Number of pages | 13 |
Journal | Journal of Computational Biology |
Volume | 24 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2017 |
Externally published | Yes |
Keywords
- RNA viral variants
- SMRT reads
- Single-nucleotide variation
ASJC Scopus subject areas
- Computational Mathematics
- Genetics
- Molecular Biology
- Computational Theory and Mathematics
- Modeling and Simulation