Computational framework for next-generation sequencing of heterogeneous viral populations using combinatorial pooling

Skums, Pavel; Artyomenko, Alexander; Glebova, Olga; Ramachandran, Sumathi; Măndoiu, Ion; Campo, David S.; Dimitrova, Zoya; Zelikovsky, Alexander; Khudyakov, Yuri

doi:10.1093/bioinformatics/btu726

Cited by 14 publications

(16 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Viral RNAs and vsiRNAs both congruently portrayed the mutational landscape of the virus within the plant host ( Kutnjak et al, 2015 ). Next generation sequencing (NGS) technology has previously been shown to be a powerful tool for studying viral ecology ( Stobbe and Roossinck, 2014 ) and viral populations ( Beerenwinkel and Zagordi, 2011 ; Palmer et al, 2014 ; Chateigner et al, 2015 ; Skums et al, 2015 ). Nowadays, many population genetics experts prefer to study plant virus ecology or populations by sequencing the vsiRNAs.…”

Section: The Application Of Virus-derived Small Rnasmentioning

confidence: 99%

Biogenesis, Function, and Applications of Virus-Derived Small RNAs in Plants

Zhang

et al. 2015

Front. Microbiol.

115

View full text Add to dashboard Cite

RNA silencing, an evolutionarily conserved and sequence-specific gene-inactivation system, has a pivotal role in antiviral defense in most eukaryotic organisms. In plants, a class of exogenous small RNAs (sRNAs) originating from the infecting virus called virus-derived small interfering RNAs (vsiRNAs) are predominantly responsible for RNA silencing-mediated antiviral immunity. Nowadays, the process of vsiRNA formation and the role of vsiRNAs in plant viral defense have been revealed through deep sequencing of sRNAs and diverse genetic analysis. The biogenesis of vsiRNAs is analogous to that of endogenous sRNAs, which require diverse essential components including dicer-like (DCL), argonaute (AGO), and RNA-dependent RNA polymerase (RDR) proteins. vsiRNAs trigger antiviral defense through post-transcriptional gene silencing (PTGS) or transcriptional gene silencing (TGS) of viral RNA, and they hijack the host RNA silencing system to target complementary host transcripts. Additionally, several applications that take advantage of the current knowledge of vsiRNAs research are being used, such as breeding antiviral plants through genetic engineering technology, reconstructing of viral genomes, and surveying viral ecology and populations. Here, we will provide an overview of vsiRNA pathways, with a primary focus on the advances in vsiRNA biogenesis and function, and discuss their potential applications as well as the future challenges in vsiRNAs research.

show abstract

Section: The Application Of Virus-derived Small Rnasmentioning

confidence: 99%

Biogenesis, Function, and Applications of Virus-Derived Small RNAs in Plants

Zhang

et al. 2015

Front. Microbiol.

115

View full text Add to dashboard Cite

show abstract

“…C 1 consists of reads with the linked pair of SNVs C 2 consists of the remaining reads of C. We further modify C 1 and C 2 by replacing them with the Voronoi regions of their consensuses, where the Voronoi region of the consensus c 1 of C 1 consists of reads that are closer to c 1 than to the consensus of C 2 . Finally, kGEM finds maximum likelihood estimates of frequencies of haplotypes represented by cluster consensuses using expectation-maximization algorithm [33].…”

Section: Snv Methods For Viral Variant Reconstructionmentioning

confidence: 99%

“…2SNV was compared with 2 tools originally tuned to handle HIV variants (Pre-dictHaplo [32] and Quasirecomb [36]) and kGEM [33] tuned for a short HCV amplicon. We could not compare with HaploClique [35] since it is no longer maintained by the authors.…”

Section: Reconstruction Of Viral Variantsmentioning

confidence: 99%

“…Viral variants were reconstructed from the original and sub-sampled datasets. 2SNV was compared with PredictHaplo [16], Quasirecomb [15], and kGEM [18]. Quasirecomb and kGEM were able to reconstruct no more than two most frequent true variants.…”

Section: Reconstruction Of Viral Variantsmentioning

confidence: 99%

“…Recently, this problem has been addressed using various computational and statistical approaches implemented in Quasirecomb [36], PredictHaplo [32], Hap-loClique [35], VGA [24], and kGEM [33]. These methods perform reasonably well on short reads with high coverage and low error rate, but our experimental validation shows far from satisfactory performance on the sequencing data provided by single-molecule technologies.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Artyomenko

Mangul

et al. 2016

Preprint

Self Cite

View full text Add to dashboard Cite

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 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. The open source implementation of 2SNV is freely available for download at

show abstract