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Updated: May 23, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Estimating gene conversion rates from population data using multi-individual identity by descent.

Sharon R Browning1, Brian L Browning1,2

  • 1Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA.

Biorxiv : the Preprint Server for Biology
|March 10, 2025
PubMed
Summary
This summary is machine-generated.

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Articles linked to this work by shared authors, journal, and citation graph.

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Same author

Modeling the length distribution of gene conversion tracts in humans from the UK Biobank sequence data.

PLoS genetics·2025
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Identity-By-Descent Mapping Using Multi-Individual IBD With Genome-Wide Multiple Testing Adjustment.

Genetic epidemiology·2025
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Multiple-testing corrections in selection scans using identity-by-descent segments.

bioRxiv : the preprint server for biology·2025
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Modeling the length distribution of gene conversion tracts in humans from the UK Biobank sequence data.

bioRxiv : the preprint server for biology·2025
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Fast simulation of identity-by-descent segments.

bioRxiv : the preprint server for biology·2025
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Adjusting for principal components can induce collider bias in genome-wide association studies.

PLoS genetics·2024

We developed a new method to map human gene conversion rates, revealing hotspots that quickly return to baseline. This method also suggests PRDM9 influences gene conversion more than crossover recombination.

Area of Science:

  • Genetics
  • Genomics
  • Population Genetics

Background:

  • Homologous gene conversion occurs more frequently than crossovers in humans, but its small tract size complicates rate estimation.
  • Existing methods struggle to accurately quantify gene conversion rates due to these challenges.

Purpose of the Study:

  • To develop and apply a novel method for multi-individual identity-by-descent (IBD) inference to detect recent gene conversion events.
  • To generate high-resolution autosome-wide maps of human gene conversion rates using large-scale genetic data.

Main Methods:

  • Implemented a multi-individual IBD inference technique accounting for genotype errors and gene conversion.
  • Analyzed data from the TOPMed and UK Biobank studies to infer IBD and identify gene conversion events.

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  • Correlated inferred gene conversion rates with crossover maps and PRDM9 binding enrichment across various window sizes.

    • Main Results:

    • Generated novel autosome-wide gene conversion maps from TOPMed and UK Biobank data.
    • Identified strong gene conversion hotspots that diminish within 1 kb.
    • Observed a stronger correlation between gene conversion and PRDM9 binding than between crossover and PRDM9 binding, suggesting a greater PRDM9 influence on gene conversion.

    Conclusions:

    • The developed method enables more accurate estimation and mapping of human gene conversion rates.
    • Gene conversion hotspots are localized and transient.
    • PRDM9 may play a more significant role in regulating gene conversion than in crossover recombination.