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PoMo-cod: a polymorphism-aware phylogenetic codon model

PoMo-cod: a polymorphism-aware phylogenetic codon model

Rui Carlos Pinto Borges (ORCID: 0000-0002-5905-3778)
  • Grant DOI 10.55776/P34524
  • Funding program Principal Investigator Projects
  • Status ended
  • Start July 1, 2021
  • End September 30, 2025
  • Funding amount € 404,148
  • Project website

Disciplines

Biology (75%); Computer Sciences (25%)

Keywords

    Diversifying Selection, Codon Models, Species Evolution, Adaptation, Phylogeny

Abstract

A major goal in evolutionary biology is to understand the forces that operate in the genomic sequences and are responsible for the adaptation of species to different environments. Codon models are one of the main tools used to infer selection on protein-coding genes. These have been popularized in comparative genomic studies by their extensive use in genome-wide scans of diversifying selection. However, models of codon evolution have significant limitations that are increasingly being recognized. The main one being that current codon models make simplistic assumptions, such as ignoring species demography and nucleotide usage bias. This project offers a new polymorphism-aware model, PoMo-cod, to detect signatures of natural selection acting on protein-coding sequences. PoMo-cod will address codon evolution in a unique way by properly reconciling the neutral and adaptive population-level processes by which coding sequences evolve. More importantly, PoMo-cod will allow us to tell apart the sole action of natural selection from known confounding forces (e.g., fluctuating demography and GC-biased gene conversion), ultimately producing more accurate genome-wide maps of diversifying evolving genes. Selection maps have impactful applications in other fields. They permit developing species-specific conservation strategies to mitigate the anthropogenic action on biodiversity or characterize the genome functionally, which has direct implications for medical research.

Research institution(s)
  • University of St. Andrews - 100%
International project participants
  • Bastien Boussau, Université de Lyon - France
  • Carolin Kosiol, University of St. Andrews

Research Output

  • 9 Citations
  • 4 Publications
Publications
  • 2025
    Title Phylogenetic Methods Meet Deep Learning
    DOI 10.1093/gbe/evaf177
    Type Journal Article
    Author Braichenko S
    Journal Genome Biology and Evolution
    Link Publication
  • 2025
    Title The rarity of mutations and the inflation of bacterial effective population sizes
    DOI 10.1111/2041-210x.14501
    Type Journal Article
    Author Borges R
    Journal Methods in Ecology and Evolution
    Pages 722-732
    Link Publication
  • 2024
    Title The Patterns of Codon Usage between Chordates and Arthropods are Different but Co-evolving with Mutational Biases
    DOI 10.1093/molbev/msae080
    Type Journal Article
    Author Kotari I
    Journal Molecular Biology and Evolution
    Link Publication
  • 2024
    Title Polymorphism-Aware Models in RevBayes: Species Trees, Disentangling Balancing Selection, and GC-Biased Gene Conversion
    DOI 10.1093/molbev/msae138
    Type Journal Article
    Author Braichenko S
    Journal Molecular Biology and Evolution
    Link Publication

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