Evidence map›Paper›PMID 27092241›Full record

ArticleF1000Research2015

ve-SEQ: Robust, unbiased enrichment for streamlined detection and whole-genome sequencing of HCV and other highly diverse pathogens.

David Bonsall, M Azim Ansari, Camilla Ip, Amy Trebes, Anthony Brown, Paul Klenerman, David Buck, STOP-HCV Consortium, Paolo Piazza, Eleanor Barnes and 1 more

Abstract read
In one paragraph

Article in F1000Research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

David Bonsall *Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX1 4BH, UK.
M Azim Ansari *Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX1 4BH, UK.
Camilla Ip *Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX1 4BH, UK.
Amy TrebesOxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX1 4BH, UK.
Anthony BrownPeter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX1 4BH, UK.
Paul KlenermanPeter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX1 4BH, UK.
David BuckOxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX1 4BH, UK.
STOP-HCV Consortium
Paolo PiazzaOxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX1 4BH, UK.
Eleanor BarnesPeter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, OX1 4BH, UK.
Rory BowdenOxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX1 4BH, UK.

Funding

Virology CoreU19AI082630 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI RAYMOND T CHUNG, GEORG Michael LAUER · 2009 to 2026
$48.1M
Medical Research Council MR/K010239/1Medical Research Council MR/K01532X/1NIAID NIH HHS U19 AI082630Wellcome Trust
6 · The paper itself

Abstract

The routine availability of high-depth virus sequence data would allow the sensitive detection of resistance-associated variants that can jeopardize HIV or hepatitis C virus (HCV) treatment. We introduce ve-SEQ, a high-throughput method for sequence-specific enrichment and characterization of whole-virus genomes at up to 20% divergence from a reference sequence and 1,000-fold greater sensitivity than direct sequencing. The extreme genetic diversity of HCV led us to implement an algorithm for the efficient design of panels of oligonucleotide probes to capture any sequence among a defined set of targets without detectable bias. ve-SEQ enables efficient detection and sequencing of any HCV genome, including mixtures and intra-host variants, in a single experiment, with greater tolerance of sequence diversity than standard amplification methods and greater sensitivity than metagenomic sequencing, features that are directly applicable to other pathogens or arbitrary groups of target organisms, allowing the combination of sensitive detection with sequencing in many settings.

Indexed as

Anti-viral resistanceHepatitis C virusSequence capture and enrichmentVirus genome sequencing

Identifiers

PMID27092241
PMCPMC4821293

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.