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Multiple-testing corrections in selection scans using identity-by-descent segments.

Seth D Temple1,2,3, Sharon R Browning4

  • 1Department of Statistics, University of Washington, Seattle, Washington, USA.

Biorxiv : the Preprint Server for Biology
|February 20, 2025
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Summary
This summary is machine-generated.

Accurate detection of genetic adaptation requires correcting for multiple testing. We developed an efficient method using identity-by-descent (IBD) rates to control false discoveries in selection scans, successfully identifying recent human adaptations.

Keywords:
identity-by-descentmean-reverting processesmultiple testingnatural selection

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Area of Science:

  • Population Genetics
  • Genomics
  • Evolutionary Biology

Background:

  • Selection scans aim to identify recent genetic adaptations.
  • Multiple testing correction is crucial to avoid false discoveries.
  • Current methods struggle with complex statistics for genome-wide significance.

Purpose of the Study:

  • To propose a computationally efficient method for determining genome-wide significance levels in identity-by-descent (IBD) based selection scans.
  • To control the family-wise error rate (FWER) in detecting recent positive selection.
  • To identify statistically significant signals of recent selection in human populations.

Main Methods:

  • Modeling the autocorrelation of identity-by-descent (IBD) rates.
  • Developing a computationally efficient method for significance level determination.
  • Utilizing whole genome simulations to validate the method's performance.
  • Analyzing large-scale human genetic data from TOPMed and UK Biobank.

Main Results:

  • The proposed method demonstrates approximate control of the family-wise error rate (FWER).
  • The method adapts to varying test spacing across the genome.
  • High power (>50%) was observed for detecting hard sweeps with specific selection coefficients and allele frequencies.
  • Statistically significant excesses of IBD segments were found in human genes across African, European, and South Asian ancestry groups.
  • Many identified selection signals were shared across different ancestry groups.
  • A particularly strong signal of recent selection was detected in a skeletal cell development gene in African ancestry samples.

Conclusions:

  • The developed IBD-based method provides a computationally efficient and reliable approach for detecting recent positive selection.
  • The findings highlight shared and ancestry-specific signals of recent human adaptation.
  • The study identifies specific genes and gene complexes under recent selection, with notable signals in African populations.