Determinants of the rate of protein sequence evolution

Abstract

The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what constitutes functional constraint has remained unclear. The increasing availability of genomic data has allowed for much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses have identified multiple mechanisms behind these observations and demonstrated a prominent role that selection against errors in molecular and cellular processes plays in protein evolution.

Expression Differentiation Is Constrained to Low-Expression Proteins over Ecological Timescales

“…The authors speculated that highly expressed proteins performed generic killing functions and that low-expression proteins were not only prey specific but also more evolvable, consistent with our findings. The greater evolvability of low-expression proteins relative to highexpression proteins may allow them to respond more rapidly to novel selective pressures, and although the optimal expression of these proteins is relatively low, the fitness effects of a regulatory mutation affecting expression may be high (Gout et al 2010).Although our results are consistent with theoretical predictions (Gout et al 2010) and previous work in mammalian systems (Liao and Zhang 2006;Zhang and Yang 2015), these findings contradict previous work showing that venom loci expressed at all levels contribute to protein expression divergence among adult C. adamanteus (Margres et al 2015a). This study, however, used range-wide sampling with much older divergence times than the current study [i.e., 1.27 million years vs. ,5000 years (Margres et al 2015b)].…”

“…Although our results are consistent with theoretical predictions (Gout et al 2010) and previous work in mammalian systems (Liao and Zhang 2006;Zhang and Yang 2015), these findings contradict previous work showing that venom loci expressed at all levels contribute to protein expression divergence among adult C. adamanteus (Margres et al 2015a). This study, however, used range-wide sampling with much older divergence times than the current study [i.e., 1.27 million years vs. ,5000 years (Margres et al 2015b)].…”

“…Analyses of microarray data have shown that expression evolutionary rate is also negatively correlated with expression level across human and mouse orthologs (Liao and Zhang 2006). Although the selective constraints imposed on the sequences of highly expressed proteins are well documented (Zhang and Yang 2015), the mechanistic basis of the negative correlation between expression evolutionary rate and expression level remains unclear (Liao and Zhang 2006). This relationship between expression level and expression evolutionary rate has only been documented when comparing orthologous genes across species with relatively long divergence times [e.g., human and mouse diverged approximately 100 million years ago (Liao and Zhang 2006)].…”

Gene Duplicability of Core Genes Is Highly Consistent across All Angiosperms

“…The observed patterns of gene duplicability are indeed consistent with the idea of the existence of a conserved core that needs to remain untouched ("single-copy" group) and the existence of processes that are more amenable to modifications and that might be responsible for adaptations to new environments and the evolution of distinct morphological features ("multicopy" group) (Kitano, 2004). Gene duplication in itself can indeed modulate gene function in a negative way and as such impact core gene function by, for instance, increasing absolute gene dosage of genes with strict gene expression constraints (Siegel and Amon, 2012) through the accumulation of mutations in duplicate copies with potential pleiotropic negative effects on wild-type fitness (Bridgham et al, 2008;Dean et al, 2008;De Smet et al, 2013;Kaltenegger and Ober, 2015) or potential cytotoxic effects (e.g., protein misfolding) (Zhang and Yang, 2015). As a result, duplicates of genes sensitive to these processes might be eradicated quickly, also after WGD.…”

Computational Methods for Annotation Transfers from Sequence

“…However, this rule of thumb can either be too stringent or too lax, because biological sequences evolve at differing rates due to the need to maintain physiological function on the one hand, and to avoid deregulated gene expression, protein translation, folding, or physical interactions on the other [ 21 ]. Ideally, these cutoff values should be specifi c to individual families or even functional categories, but usually the number of labelled examples is not suffi cient to allow reliable calibration.…”