The underground environment imposes unique demands on life that have led subterranean species to evolve specialized traits, many of which evolved convergently. We studied convergence in evolutionary rate in subterranean mammals in order to associate phenotypic evolution with specific genetic regions. We identified a strong excess of vision- and skin-related genes that changed at accelerated rates in the subterranean environment due to relaxed constraint and adaptive evolution. We also demonstrate that ocular-specific transcriptional enhancers were convergently accelerated, whereas enhancers active outside the eye were not. Furthermore, several uncharacterized genes and regulatory sequences demonstrated convergence and thus constitute novel candidate sequences for congenital ocular disorders. The strong evidence of convergence in these species indicates that evolution in this environment is recurrent and predictable and can be used to gain insights into phenotype–genotype relationships.

When different lineages of organisms independently adapt to similar environments, selection often acts repeatedly upon the same genes, leading to signatures of convergent evolutionary rate shifts at these genes. With the increasing availability of genome sequences for organisms displaying a variety of convergent traits, the ability to identify genes with such convergent rate signatures would enable new insights into the molecular basis of these traits. Here we present the R package RERconverge, which tests for association between relative evolutionary rates of genes and the evolution of traits across a phylogeny. RERconverge can perform associations with binary and continuous traits, and it contains tools for visualization and enrichment analyses of association results. RERconverge source code, documentation and a detailed usage walk-through are freely available at https://github.com/nclark-lab/RERconverge. Datasets for mammals, Drosophila and yeast are available at https://bit.ly/2J2QBnj. Supplementary data are available at Bioinformatics online.

Although lifespan in mammals varies over 100-fold, the precise evolutionary mechanisms underlying variation in longevity remain unknown. Species-specific genetic changes have been observed in long-lived species including the naked mole-rat, bats, and the bowhead whale, but these adaptations do not generalize to other mammals. We present a novel method to identify associations between rates of protein evolution and continuous phenotypes across the entire mammalian phylogeny. Unlike previous analyses that focused on individual species, we treat absolute and relative longevity as quantitative traits and demonstrate that these lifespan traits affect the evolutionary constraint on hundreds of genes. Specifically, we find that genes related to cell cycle, DNA repair, cell death, the IGF1 pathway, and immunity are under increased evolutionary constraint in large and long-lived mammals. For mammals exceptionally long-lived for their body size, we find increased constraint in inflammation, DNA repair, and NFKB-related pathways. Strikingly, these pathways have considerable overlap with those that have been previously reported to have potentially adaptive changes in single-species studies, and thus would be expected to show decreased constraint in our analysis. This unexpected finding of increased constraint in many longevity-associated pathways underscores the power of our quantitative approach to detect patterns that generalize across the mammalian phylogeny.

Adaptive conflicts with the modern world: Mammals evolved in terrestrial environments. Those that now live in the marine environment have had to adapt to the particular selective pressures that this environment imposes. Meyeret al.surveyed the genomes of several marine mammal species to identify regions of convergent change. Multiple losses of theParaoxonase 1gene are evident in marine mammals, likely resulting from remodeling of lipid metabolism or antioxidant networks. The multiple occurrences of this loss of function across taxa indicate an evolutionary benefit. However,Paraoxonase 1is the primary mammalian defense against organophosphorus toxicity. Marine mammals may be at a great disadvantage in the Anthropocene if run-off of this agricultural product into the marine environment continues.Science, this issue p.591

Identifying genomic elements underlying phenotypic adaptations is an important problem in evolutionary biology. Comparative analyses learning from convergent evolution of traits are gaining momentum in accurately detecting such elements. We previously developed a method for predicting phenotypic associations of genetic elements by contrasting patterns of sequence evolution in species showing a phenotype with those that do not. Using this method, we successfully demonstrated convergent evolutionary rate shifts in genetic elements associated with two phenotypic adaptations, namely the independent subterranean and marine transitions of terrestrial mammalian lineages. Our original method calculates gene-specific rates of evolution on branches of phylogenetic trees using linear regression. These rates represent the extent of sequence divergence on a branch after removing the expected divergence on the branch due to background factors. The rates calculated using this regression analysis exhibit an important statistical limitation, namely heteroscedasticity. We observe that the rates on branches that are longer on average show higher variance, and describe how this problem adversely affects the confidence with which we can make inferences about rate shifts. Using a combination of data transformation and weighted regression, we have developed an updated method that corrects this heteroscedasticity in the rates. We additionally illustrate the improved performance offered by the updated method at robust detection of convergent rate shifts in phylogenetic trees of protein-coding genes across mammals, as well as using simulated tree data sets. Overall, we present an important extension to our evolutionary-rates-based method that performs more robustly and consistently at detecting convergent shifts in evolutionary rates.