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A genomic selection component analysis characterizes migration-selection balance.

Patrick J Monnahan1, Jack Colicchio1, John K Kelly2

  • 1Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, 66045.

Evolution; International Journal of Organic Evolution
|June 18, 2015
PubMed
Summary
This summary is machine-generated.

Local adaptation in Mimulus guttatus rapidly evolves through standing genetic variation, not new mutations. This study reveals how selection and gene flow shape adaptation in newly invaded habitats.

Keywords:
AdaptationRADseqmigrationmimulusselection

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Area of Science:

  • Evolutionary Biology
  • Population Genetics
  • Genomics

Background:

  • Understanding the speed and genomic extent of local adaptation is crucial.
  • Key evolutionary forces like natural selection and gene flow are central to adaptation.
  • The role of standing genetic variation versus new mutations in rapid adaptation remains debated.

Purpose of the Study:

  • To investigate the rate and genomic scope of local adaptation in a plant species.
  • To quantify the interplay between natural selection and gene flow during colonization.
  • To determine the source of genetic variation driving adaptation in a novel environment.

Main Methods:

  • Whole-genome genotyping of Mimulus guttatus in a recently invaded habitat.
  • Direct measurement of survival and reproductive success.
  • Renovation of the selection component method for genomic data analysis.

Main Results:

  • Single nucleotide polymorphisms (SNPs) under viability selection showed increased divergence.
  • Evidence of gene flow was detected through subtle allele frequency shifts towards neighboring populations.
  • Local adaptation was attributed to the utilization of pre-existing genetic variation (standing genetic variation).

Conclusions:

  • Local adaptation can occur rapidly, within 30-40 generations, in newly colonized habitats.
  • Standing genetic variation is a primary source for rapid local adaptation.
  • Genomic data combined with classic methods effectively reveal selection and gene flow dynamics.