Evolution is not Uniform Along Coding Sequences

Abstract

Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. Notably, amino-acids located at the surface of proteins are known to evolve more rapidly than those in the core. In particular, amino-acids at the N- and C-termini of protein sequences are likely to be more exposed than those at the core of the folded protein due to their location in the peptidic chain, and they are known to be less structured. Because of these reasons, we would expect that amino-acids located at protein termini would evolve faster than residues located inside the chain. Here we test this hypothesis and found that amino acids evolve almost twice as fast at protein termini compared to those in the centre, hinting at a strong topological bias along the sequence length. We further show that the distribution of solvent-accessible residues and functional domains in proteins readily explain how structural and functional constraints are weaker at their termini, leading to the observed excess of amino-acid substitutions. Finally, we show that the specific evolutionary rates at protein termini may have direct consequences, notably misleading in silico methods used to infer sites under positive selection within genes. These results suggest that accounting for positional information should improve evolutionary models.

Simulations of sequence evolution: how (un)realistic they are and why

“…This also seemed to be the case for other substitution models (results not shown). This result is in agreement with Bricout et al [10] who also found this pattern in a large scale analysis of empirical alignments.…”

“…We computed the number of stop codons in all genes in the database and at all three phases, and did not observe an excess of alignments with 0 or 1 stop codons per sequence (Supplementary Figure S17). Instead, it seems to correspond to the pattern found by Bricout et al [10]. However, in the future it will be interesting to investigate the realism of existing codon models, on a data set of coding DNA sequences.…”

“…We used the next six features to highlight one of the recurrent problems of simulated sequence generators: a common simplification used in generators is the assumption that substitutions occur at uniformly distributed random locations in the sequence, which appears to not be the case in real-world genetic data [10]. Thus, we expected empirical MSAs to be less uniform than simulated MSAs, and we henceforth attempted to confirm this hypothesis.…”

Terminal regions of a protein are a hotspot for low complexity regions and selection

“…However, it's important to note that the reduced alignment coverage does not necessarily result in the detection of a lower number of PSS within the region. Apart from our finding, a study detected a similar trend of a faster evolutionary rate at the termini of a protein sequence even after removing poorly aligned regions [71]. This further enhances the presence of malleable regions at the termini of protein sequences to harbour evolutionarily innovative opportunities.…”

The fitness cost of spurious phosphorylation

“…Values close to 1 correspond to cases where Y is strongly preferred in the fungi but not in the metazoa, and vice versa for negative values. We also stratify the data according to accessibility (buried, intermediate, exposed) given established relationships between residue exposure and the rate of evolution (Echave et al , 2016; Bricout et al , 2023), and that the molecular impact of phosphorylation will likely depend upon the accessibility of the phosphosite (Figure S5f). This analysis does not reveal any significant evidence for Y counter-selection for pYs relative to non-pYs ( Figure 5f, Table S14) .…”