Evidence map›Paper›PMID 40740855›Full record

ArticleVirus evolution2025

Estimates of HIV-1 within-host recombination rates across the whole genome.

Harriet Longley, David Bonsall, Joshua Herbeck, George MacIntyre-Cockett, Sandra E Chaudron, Laura Thomson, Nicholas Grayson, Andrew Mujugira, PANGEA consortium, Christophe Fraser and 2 more

Abstract read
In one paragraph

Article in Virus evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Harriet LongleyBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, United Kingdom.ORCID https://orcid.org/0009-0005-7413-5869
David BonsallBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, United Kingdom.
Joshua HerbeckInstitute for Disease Modelling, Bill & Melinda Gates Foundation, Seattle, WA 98109, United States.
George MacIntyre-CockettBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, United Kingdom.
Sandra E ChaudronBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, United Kingdom.
Laura ThomsonBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, United Kingdom.
Nicholas GraysonBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, United Kingdom.
Andrew MujugiraDepartment of Global Health, University of Washington Seattle, Seattle, WA 98195, United States.
PANGEA consortium
Christophe FraserBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, United Kingdom.
Jairam LingappaDepartment of Global Health, Medicine and Paediatrics, University of Washington, Seattle, WA 98195, United States.
Katrina LythgoeBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recombination plays a pivotal role in generating within-host diversity and enabling HIV's evolutionary success, particularly in evading the host immune response. Despite this, the variability in recombination rates across different settings and the underlying factors that drive these differences remain poorly understood. In this study, we analysed a large dataset encompassing hundreds of untreated, longitudinally sampled infections using both whole-genome long-read and short-read sequencing datasets. By quantifying recombination rates, we uncover substantial variation across subtypes, viral loads, and stages of infection. We also map recombination hot and cold spots across the genome using a sliding window approach, finding that previously reported inter-subtype regions of high or low recombination are replicated at the within-host level. Importantly, our findings reveal the significant influence of selection on recombination, showing that the presence and success of recombinant genomes is strongly interconnected with the fitness landscape. These results offer valuable insights into the contribution of recombination to evolutionary dynamics and demonstrate the enhanced resolution that long-read sequencing offers for studying viral evolution.

Indexed as

HIVintrahostrecombination

Identifiers

PMID40740855
PMCPMC12309388

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LicenceCC BY
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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.