Evaluation of Methods to Detect Shifts in Directional Selection at the Genome Scale

Abstract

Identifying the footprints of selection in coding sequences can inform about the importance and function of individual sites. Analyses of the ratio of non-synonymous to synonymous substitutions (dN/dS) have been widely used to pinpoint changes in the intensity of selection, but cannot distinguish them from changes in the direction of selection, i.e., changes in the fitness of specific amino acids at a given position. A few methods that rely on amino acid profiles to detect changes in directional selection have been designed, but their performance have not been well characterized. In this paper, we investigate the performance of 6 of these methods.We evaluate them on simulations along empirical phylogenies in which transition events have been annotated, and compare their ability to detect sites that have undergone changes in the direction or intensity of selection to that of a widely used dN/dS approach, codeml’s branch-site model A. We show that all methods have reduced performance in the presence of biased gene conversion but not CpG hypermutability. The best profile method, Pelican, a new implementation of (Tamuri et al., 2009), performs as well as codeml in a range of conditions except for detecting relaxations of selection, and performs better when tree length increases, or in the presence of persistent positive selection. It is fast, enabling genome-scale searches for site-wise changes in the direction of selection associated with phenotypic changes.

The fitness cost of spurious phosphorylation

“…Animal species in blue, fungal species in yellow. f) Difference between the inferred preference for Y in fungal species and metazoa species, calculated as their difference in equilibrium frequencies ( π ) by the Pelican software (Duchemin et al , 2023). The results are given for pY and non-pY tyrosines and separated according to their solvent accessibility (buried: RSA > 0.2, intermediate: 0.2 < RSA < 0.4, exposed: RSA > 0.4).…”

“…Testing for pY counter-selection at the site-specific level was performed using Pelican software (Duchemin et al , 2023). This software takes as an input a multiple sequence alignment (MSA) and a phylogenetic tree with trait values annotated to each tip and ancestral node.…”

“…We required that the fungal and metazoan sequences were successfully resolved in the phylogenetic tree by excluding trees where the fungal clade contained >2.5% metazoan sequences or vice versa . The annotation of binary ancestral traits (‘fungi’ or ‘metazoa’) was performed using the parsimony method within Pelican (Duchemin et al , 2023). Pelican was executed with the ‘pelican scan discrete’ command using an amino acid alphabet.…”

“… a) For spuriously phosphorylated tyrosines (pY) and non-phosphorylated tyrosines (non-pY), the percentage with a significant shift in amino acid profile between animal and fungal species, as inferred by Pelican software (Duchemin et al , 2023) . b) The same analysis as in Figure 5f but after excluding non-pY sites that are poor candidates for Y phosphorylation on the basis of their sequence motif.…”

Increased positive selection in highly recombining genes does not necessarily reflect an evolutionary advantage of recombination

“…In this sense, there is also accumulating evidence for convergent adaptation at the molecular level (Christin et al, 2007;Zhen et al, 2012;Davies et al, 2012;Wu et al, 2020;Duchemin et al, 2023;Fukushima and Pollock, 2023), suggesting that there is sometimes a limited number of mutations that can lead to a given phenotype, and thus limited opportunities for compensatory mutations. Moreover, an important role Increased positive selection in highly recombining genes does not necessarily reflect an evolutionary advantage of recombination of beneficial back mutations have been reported in plants (Chen et al, 2021) and mammals (Moses and Durbin, 2009;Latrille et al, 2023).…”