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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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On estimating evolutionary probabilities of population variants.

Ravi Patel1,2, Sudhir Kumar3,4,5

  • 1Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, 19122, USA.

BMC Evolutionary Biology
|June 27, 2019
PubMed
Summary

We developed a new method to calculate evolutionary probability (EP) without needing known species evolutionary trees. This approach reliably estimates EP, enabling the identification of neutral, deleterious, and adaptive alleles in populations.

Keywords:
Evolutionary probabilityForbidden allelesGeneralized methodPotential adaptation

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Area of Science:

  • Evolutionary biology
  • Bioinformatics
  • Population genetics

Background:

  • Evolutionary probability (EP) predicts permissible and forbidden alleles based on substitution patterns.
  • Comparing EP with population frequencies helps identify neutral and non-neutral alleles.
  • Previous EP calculations required known species phylogenies and divergence times, limiting general application.

Purpose of the Study:

  • To present a modified approach for calculating EP by inferring phylogeny and divergence times directly from sequence alignments.
  • To evaluate the accuracy of the modified EP approach compared to the original method.

Main Methods:

  • Inferred phylogeny and divergence times from sequence alignments prior to EP calculation.
  • Compared EP estimates from the modified approach with a ground truth dataset using over 18,000 vertebrate protein sequence alignments.

Main Results:

  • The modified EP approach produced reasonable EP estimates comparable to the original method.
  • Reliable EP estimates can be obtained without prior knowledge of species phylogeny and divergence times.
  • Using diverse, large sequence datasets is crucial for robust EP estimation.

Conclusions:

  • The modified EP approach is generally applicable to sequence alignments.
  • This method facilitates the detection of neutral, deleterious, and adaptive alleles in populations.