Estimates of the Effect of Natural Selection on Protein-Coding Content

Abstract

Analysis of natural selection is key to understanding many core biological processes, including the emergence of competition, cooperation, and complexity, and has important applications in the targeted development of vaccines. Selection is hard to observe directly but can be inferred from molecular sequence variation. For protein-coding nucleotide sequences, the ratio of nonsynonymous to synonymous substitutions (ω) distinguishes neutrally evolving sequences (ω = 1) from those subjected to purifying (ω < 1) or positive Darwinian (ω > 1) selection. We show that current models used to estimate ω are substantially biased by naturally occurring sequence compositions. We present a novel model that weights substitutions by conditional nucleotide frequencies and which escapes these artifacts. Applying it to the genomes of pathogens causing malaria, leprosy, tuberculosis, and Lyme disease gave significant discrepancies in estimates with ∼10–30% of genes affected. Our work has substantial implications for how vaccine targets are chosen and for studying the molecular basis of adaptive evolution.

Dynamic evolution of venom proteins in squamate reptiles

“…The major modification over the original form of Zhang et al 45 is that we employ the conditional nucleotide form of the codon rate matrix 46 . We used the conditional nucleotide form variant that includes terms from the nucleotide general time reversible model, as it was demonstrated as the form most robust to changes in sequence composition 46 . This model assumes codons evolve independently and that the substitution processes is stationary and reversible.…”

Gene Duplicability of Core Genes Is Highly Consistent across All Angiosperms

“…To construct the species tree, we used CodonPhyML (1.0) (Gil et al, 2013) under three different codon models that differ in their instantaneous substitution rates between codons, being the Muse and Gaut (MG) model (Muse and Gaut, 1994), the Goldman and Yang (GY) model (Goldman and Yang, 1994), and the YAP model (Yap et al, 2010). The stationary frequency of codons and the transition-transversion ratio were estimated by maximum likelihood.…”

DNA barcoding of Palaearctic Ulidiidae (Diptera: Tephritoidea): morphology, DNA evolution, and Markov codon models

“…The most important advantages of codon models over DNA models are being achieved by naturally incorporating selection regimes acting on protein and the structure of the genetic code as relevant model parameters. For further phylogenetic inference, the YAP parametric codon model was a priori selected, reasoning that estimation of the non-synonymous to synonymous substitution ratio (ω) is not affected by base composition at each codon compared to other codon models, namely GY and MG (for details, see Yap et al (2010)). The selective variability (distribution of ω ratios) among codon sites was modeled using the model M3 with three discrete site classes (Yang et al 2000).…”