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The Lambda Select cII Mutation Detection System
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Background selection and FST : Consequences for detecting local adaptation.

Remi Matthey-Doret1, Michael C Whitlock1

  • 1Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada.

Molecular Ecology
|July 27, 2019
PubMed
Summary
This summary is machine-generated.

Background selection, a process reducing genetic diversity, does not significantly impact FST outlier scans for local adaptation. This finding suggests that identifying adaptive variants is still feasible despite background selection effects.

Keywords:
adaptationevolutionary theorylocal adaptationpopulation genetics-theoreticalpopulation structure

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Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Genomics

Background:

  • Background selection, driven by deleterious mutations, reduces genetic diversity at linked sites.
  • Concerns exist that background selection intensity variations may skew genome-wide FST scans, potentially masking local adaptation signals.

Purpose of the Study:

  • To investigate the impact of varying background selection intensity on population differentiation statistics.
  • To assess the reliability of FST outlier scans for detecting local adaptation in the presence of background selection.

Main Methods:

  • Realistic simulations of DNA sequences were conducted.
  • Recombination maps from humans and sticklebacks were utilized.
  • The effects on FST and dXY were analyzed in sexual, outcrossing species with gene flow.

Main Results:

  • The FST estimator by Weir and Cockerham (1984) showed insensitivity to locus-specific background selection intensity.
  • dXY exhibited a negative correlation with background selection intensity.
  • Background selection had minimal impact on the false-positive rates in FST outlier studies.

Conclusions:

  • Background selection is unlikely to significantly interfere with genome scans aimed at identifying local adaptation.
  • FST outlier methods remain a viable approach for detecting adaptive variants in populations with gene flow, even with background selection.