Detecting macroevolutionary genotype-phenotype associations using error-corrected rates of protein convergence.
Nat Ecol Evol
; 7(1): 155-170, 2023 01.
Article
in En
| MEDLINE
| ID: mdl-36604553
ABSTRACT
On macroevolutionary timescales, extensive mutations and phylogenetic uncertainty mask the signals of genotype-phenotype associations underlying convergent evolution. To overcome this problem, we extended the widely used framework of non-synonymous to synonymous substitution rate ratios and developed the novel metric ωC, which measures the error-corrected convergence rate of protein evolution. While ωC distinguishes natural selection from genetic noise and phylogenetic errors in simulation and real examples, its accuracy allows an exploratory genome-wide search of adaptive molecular convergence without phenotypic hypothesis or candidate genes. Using gene expression data, we explored over 20 million branch combinations in vertebrate genes and identified the joint convergence of expression patterns and protein sequences with amino acid substitutions in functionally important sites, providing hypotheses on undiscovered phenotypes. We further extended our method with a heuristic algorithm to detect highly repetitive convergence among computationally non-trivial higher-order phylogenetic combinations. Our approach allows bidirectional searches for genotype-phenotype associations, even in lineages that diverged for hundreds of millions of years.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Genome
/
Evolution, Molecular
Type of study:
Risk_factors_studies
Language:
En
Journal:
Nat Ecol Evol
Year:
2023
Document type:
Article
Affiliation country:
Alemania