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Ancestral Population Genomics.

Julien Y Dutheil1, Asger Hobolth2

  • 1Department of Evolutionary Genetics, Max Planck Institute of Evolutionary Biology, Plön, Germany. dutheil@evolbio.mpg.de.

Methods in Molecular Biology (Clifton, N.J.)
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Summary
This summary is machine-generated.

Population genomics uses full genome data to study species evolution and genetic history. This field models sequence evolution to estimate ancestral population sizes and uncover selection forces.

Keywords:
Ancestral populationCoalescenceDemographyDivergenceMarkov modelMigrationRecombinationSelectionSpeciation

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Area of Science:

  • Evolutionary Biology
  • Genetics

Background:

  • Population genomics integrates population genetics and phylogenetics.
  • Availability of complete genomes from closely related species enabled its emergence.
  • Resequencing technologies enhance the study of recent genetic history and genome-wide diversity.

Purpose of the Study:

  • To discuss basic models of genomes in populations, including speciation.
  • To highlight the information content of a few complete genomes due to recombination.
  • To survey modeling strategies for inferring demography and selection from genomic data.

Main Methods:

  • Modeling sequence evolution within populations undergoing speciation.
  • Utilizing the coalescent with recombination process.
  • Developing scalable analyses for genomic datasets.

Main Results:

  • Few complete genomes provide substantial information about population history due to recombination.
  • Genomic regions can have distinct evolutionary histories within a few genomes.
  • Inference of demographic scenarios and selective pressures is possible.

Conclusions:

  • Population genomics offers powerful tools to estimate key population genetics parameters.
  • Understanding the mosaic of genomic histories is crucial for inferring past events.
  • Advanced modeling strategies are essential for analyzing large-scale genomic variation.