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Toward an Evolutionarily Appropriate Null Model: Jointly Inferring Demography and Purifying Selection.

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A new statistical framework helps disentangle adaptive and nonadaptive evolution by incorporating genetic drift and purifying selection. This provides a crucial null model for understanding evolutionary forces shaping genomic variation.

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Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Genomics

Background:

  • The relative importance of adaptive versus nonadaptive processes in evolution is a long-standing debate.
  • Existing models and statistical methods lack a comprehensive null model that includes key evolutionary forces like genetic drift and purifying selection.

Purpose of the Study:

  • To develop and validate a novel statistical framework for inferring evolutionary parameters.
  • To investigate the impact of population size changes and purifying selection on genomic variation patterns.
  • To establish an appropriate null model for assessing the role of adaptive evolution.

Main Methods:

  • Proposed a novel statistical framework for joint inference of selective and demographic parameters.
  • Conducted extensive performance analyses to evaluate the framework's utility and identify key statistics.
  • Reanalyzed genome-wide data from *Drosophila melanogaster*.

Main Results:

  • The new framework effectively infers demographic and selective parameters.
  • Population size changes and purifying selection significantly affect patterns of variation near functional elements.
  • *Drosophila melanogaster* experienced slower population growth than previously inferred when purifying selection was ignored.

Conclusions:

  • The developed statistical framework serves as an appropriate null model for evolutionary studies.
  • Accurate assessment of adaptive evolution requires accounting for both demographic history and purifying selection.
  • This approach refines our understanding of evolutionary forces shaping genetic diversity.