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A new comparative framework for estimating selection on synonymous substitutions.

Hannah Verdonk1, Alyssa Pivirotto2, Vitor Pavinato2

  • 1Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, Philadelphia, Pennsylvania, USA.

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Summary
This summary is machine-generated.

This study introduces Multiclass Synonymous Substitution (MSS) models to account for selection on codon usage, revealing significant rate variations in Drosophila species. These models improve our understanding of evolutionary forces shaping synonymous substitutions.

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Area of Science:

  • Evolutionary Biology
  • Genomics
  • Population Genetics

Background:

  • Selection on synonymous codon usage is a known evolutionary phenomenon.
  • Existing models often fail to account for this selection and its impact on substitution rates.
  • This gap hinders a comprehensive understanding of molecular evolution.

Purpose of the Study:

  • To develop and enhance Multiclass Synonymous Substitution (MSS) models.
  • To accurately estimate relative synonymous substitution rates while accounting for mutation bias.
  • To investigate selection on synonymous codon usage across diverse taxa.

Main Methods:

  • Partitioning synonymous substitutions into multiple classes.
  • Estimating relative substitution rates for each class within MSS models.
  • Utilizing a large empirical dataset of ~12,000 gene alignments from twelve Drosophila species.
  • Validating model performance with forward population genetic simulations.

Main Results:

  • Identified extensive heterogeneity in relative synonymous substitution rates within Drosophila.
  • Demonstrated the robustness of MSS models to model misspecification through simulations.
  • Found significant correlations between MSS rates and codon usage covariates (polymorphism data, tRNA abundance).

Conclusions:

  • MSS models effectively detect selection on synonymous codon usage, even weak signals.
  • These models provide a powerful tool to study selection on synonymous substitutions across diverse taxa.
  • The approach is independent of prior assumptions about the driving forces of selection.