4.7 Review

Analysis of selection in protein-coding sequences accounting for common biases

Journal

BRIEFINGS IN BIOINFORMATICS
Volume 22, Issue 5, Pages -

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbaa431

Keywords

molecular adaptation; codon evolution; codon frequencies; dN/dS estimation; dN/dS interpretation; recombination

Funding

  1. Spanish Ministry of Economy and Competitiveness [RYC-2015-18241, IJCI-2016-29550]
  2. Xunta de Galicia [ED431F 2018/08]
  3. Portuguese Government by the Fundacao para a Ciencia e a Tecnologia [SFRH/BD/143607/2019]
  4. Fundação para a Ciência e a Tecnologia [SFRH/BD/143607/2019] Funding Source: FCT

Ask authors/readers for more resources

The evolution of protein-coding genes is driven by selective processes, optimizing protein stability and activity. Estimating dN/dS ratio may have biases, but can be corrected using advanced methods. It is important to consider the impact of observed substitutions on protein stability and function when interpreting dN/dS estimates.
The evolution of protein-coding genes is usually driven by selective processes, which favor some evolutionary trajectories over others, optimizing the subsequent protein stability and activity. The analysis of selection in this type of genetic data is broadly performed with the metric nonsynonymous/synonymous substitution rate ratio (dN/dS). However, most of the well-established methodologies to estimate this metric make crucial assumptions, such as lack of recombination or invariable codon frequencies along genes, which can bias the estimation. Here, we review the most relevant biases in the dN/dS estimation and provide a detailed guide to estimate this metric using state-of-the-art procedures that account for such biases, along with illustrative practical examples and recommendations. We also discuss the traditional interpretation of the estimated dN/dS emphasizing the importance of considering complementary biological information such as the role of the observed substitutions on the stability and function of proteins. This review is oriented to help evolutionary biologists that aim to accurately estimate selection in protein-coding sequences.

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