ArticleNucleic acids research2017
Separation and assembly of deep sequencing data into discrete sub-population genomes.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- ViReMa: a virus recombination mapper of next-generation sequencing data characterizes diverse recombinant viral nucleic acids.GigaScience · 2023Article
- Article
- Genome-wide analyses of human noroviruses provide insights on evolutionary dynamics and evidence of coexisting viral populations evolving under recombination constraints.PLoS pathogens · 2021Article
- Article
- Design and Testing of Vector-Producing HEK293T Cells Bearing a Genomic Deletion of the SV40 T Antigen Coding Region.Molecular therapy. Methods & clinical development · 2020Article
- Molecular Characterization ofGenes · 2019Article
- Evolution of echovirus 11 in a chronically infected immunodeficient patient.PLoS pathogens · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sequence heterogeneity is a common characteristic of RNA viruses that is often referred to as sub-populations or quasispecies. Traditional techniques used for assembly of short sequence reads produced by deep sequencing, such as de-novo assemblers, ignore the underlying diversity. Here, we introduce a novel algorithm that simultaneously assembles discrete sequences of multiple genomes present in populations. Using in silico data we were able to detect populations at as low as 0.1% frequency with complete global genome reconstruction and in a single sample detected 16 resolved sequences with no mismatches. We also applied the algorithm to high throughput sequencing data obtained for viruses present in sewage samples and successfully detected multiple sub-populations and recombination events in these diverse mixtures. High sensitivity of the algorithm also enables genomic analysis of heterogeneous pathogen genomes from patient samples and accurate detection of intra-host diversity, enabling not just basic research in personalized medicine but also accurate diagnostics and monitoring drug therapies, which are critical in clinical and regulatory decision-making process.
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Registered trials
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