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Identifying loci under selection via explicit demographic models.

Hirzi Luqman1, Alex Widmer1, Simone Fior1

  • 1Institute of Integrative Biology, ETH Zurich, Zürich, Switzerland.

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Summary
This summary is machine-generated.

Identifying adaptive genetic loci requires accounting for demographic history. A new framework, Loci Under Selection (LSD), uses explicit demographic models to detect selection signatures and infer the direction of environmental adaptation.

Keywords:
approximate Bayesian computationdemographygenetic trade-offsgenome scanlocal adaptationselection

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Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Genomics

Background:

  • Adaptive genetic variation arises from both selective and neutral evolutionary forces.
  • Accurate identification of adaptive loci necessitates accounting for a population's demographic history.
  • Coalescent theory suggests selection signatures can be inferred from deviations in genealogies from neutral expectations.

Purpose of the Study:

  • To develop an analytical framework, Loci Under Selection (LSD), for identifying loci under selection using explicit demographic models.
  • To infer signatures of selection through deviations in demographic parameters, explicitly accounting for demographic history.
  • To leverage demographic models' directionality to understand the environmental context of selection and characterize genetic trade-offs.

Main Methods:

  • Development of the Loci Under Selection (LSD) analytical framework.
  • Implementation of LSD using approximate Bayesian computation.
  • Simulation studies to assess LSD's performance across various demographic-selection regimes and compare it with genome-scan methods.
  • Characterization of isolation-with-migration models for local adaptation studies.

Main Results:

  • LSD demonstrates high power in identifying selected loci across diverse demographic-selection scenarios.
  • LSD outperforms common genome-scan methods, especially under complex demographic histories.
  • LSD accurately infers the directionality of selection for candidate loci.
  • Simulations elucidated the behavior of isolation-with-migration models relevant to local adaptation.

Conclusions:

  • The LSD framework provides a robust method for detecting loci under selection by explicitly modeling demographic history.
  • LSD facilitates the characterization of genetic trade-offs and the understanding of selective processes driving local adaptation.
  • The study successfully applied LSD to identify loci and genetic trade-offs related to flower color in Antirrhinum majus.