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An Integrated Approach for Microprotein Identification and Sequence Analysis
Published on: July 12, 2022
Interaction between selection and biased gene conversion in mammalian protein-coding sequence evolution revealed by a
1Centre Robert-Cedergren pour la Bioinformatique, Département de Biochimie, Université de Montréal, Québec, Canada. nicolas.lartillot@umontreal.ca
Molecular Biology and Evolution
|October 2, 2012
Summary
The nearly-neutral model predicts linked evolution of population size and substitution rates. GC-biased gene conversion complicates this, but focusing on GC-conservative sites supports the nearly-neutral model in mammals.
Area of Science:
- Evolutionary Biology
- Genomics
- Molecular Evolution
Background:
- The nearly-neutral theory posits that effective population size influences protein-coding sequence evolution.
- GC-biased gene conversion (gBGC) is a significant force altering genome composition and may interact with neutral evolution.
- Previous studies in mammals largely supported the nearly-neutral model's predictions.
Purpose of the Study:
- To investigate phylogenetic correlations between substitution rates (dN/dS), GC content (GC*), and life-history/karyotypic traits in placental mammals.
- To assess the impact of GC-biased gene conversion on the interpretation of evolutionary dynamics.
- To explore interactions between selection, mutation, drift, and gene conversion.
Main Methods:
- Phylogenetic comparative analysis of dN/dS, GC*, and various traits across placental mammals.
- Examination of correlations under different evolutionary models, including those accounting for gBGC.
- Focused analysis of dN/dS using GC-conservative substitutions to mitigate gBGC effects.
Main Results:
- Equilibrium GC composition (GC*) correlates inversely with body mass and directly with chromosome number, suggesting modulation by effective population size and recombination rates.
- Observed variation in dN/dS partially aligns with the nearly-neutral theory.
- Estimating dN/dS using only GC-conservative transversions yields results more consistent with nearly-neutral predictions.
Conclusions:
- Genome nucleotide composition is influenced by life-history and karyotypic traits, indicating modulation of gBGC.
- Interactions between selection and gBGC are complex and affect evolutionary rate estimations.
- Further research is needed to fully disentangle the roles of mutation, selection, drift, and conversion in molecular evolution.
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