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Advances in genome sequencing have improved our understanding of the genetic basis of human diseases, and thousands of human genes have been associated with different diseases. Recent genomic adaptation at disease genes has not been well characterized. Here, we compare the rate of strong recent adaptation in the form of selective sweeps between mendelian, non-infectious disease genes and non-disease genes across distinct human populations from the 1000 Genomes Project. We find that mendelian disease genes have experienced far less selective sweeps compared to non-disease genes especially in Africa. Investigating further the possible causes of the sweep deficit at disease genes, we find that this deficit is very strong at disease genes with both low recombination rates and with high numbers of associated disease variants, but is almost non-existent at disease genes with higher recombination rates or lower numbers of associated disease variants. Because segregating recessive deleterious variants have the ability to interfere with adaptive ones, these observations strongly suggest that adaptation has been slowed down by the presence of interfering recessive deleterious variants at disease genes. These results suggest that disease genes suffer from a transient inability to adapt as fast as the rest of the genome.

SummaryThe current SARS-CoV-2 pandemic has emphasized the vulnerability of human populations to novel viral pressures, despite the vast array of epidemiological and biomedical tools now available. Notably, modern human genomes contain evolutionary information tracing back tens of thousands of years, which may help identify the viruses that have impacted our ancestors – pointing to which viruses have future pandemic potential. Here, we apply evolutionary analyses to human genomic datasets to recover selection events involving tens of human genes that interact with coronaviruses, including SARS-CoV-2, that likely started more than 20,000 years ago. These adaptive events were limited to the population ancestral to East Asian populations. Multiple lines of functional evidence support an ancient viral selective pressure, and East Asia is the geographical origin of several modern coronavirus epidemics. An arms race with an ancient coronavirus, or with a different virus that happened to use similar interactions as coronaviruses with human hosts, may thus have taken place in ancestral East Asian populations. By learning more about our ancient viral foes, our study highlights the promise of evolutionary information to better predict the pandemics of the future. Importantly, adaptation to ancient viral epidemics in specific human populations does not necessarily imply any difference in genetic susceptibility between different human populations, and the current evidence points toward an overwhelming impact of socioeconomic factors in the case of COVID-19.

Gene duplication is a key source of evolutionary innovation, and multigene families evolve in a birth-death process, continuously duplicating and pseudogenizing through time. To empirically test hypotheses about adaptive expansion and contraction of multigene families across species, models infer gene gain and loss in light of speciation events and these inferred gene family expansions may lead to interpretations of adaptations in particular lineages. While the relative abundance of a gene subfamily in the subgenome may reflect its functional importance, tests based on this expectation can be confounded by the complex relationship between the birth-death process of gene subfamily evolution and the species phylogeny. Using simulations, we confirmed tree heterogeneity as a confounding factor in inferring multi-gene adaptation, causing spurious associations between shifts in birth-death rate and lineages with higher branching rates. We then used the olfactory receptor (OR) repertoire, the largest gene family in the mammalian genome, of different bat species with divergent diets to test whether expansions in olfactory receptors are associated with shifts to frugivorous diets. After accounting for tree heterogeneity, we robustly inferred that certain OR subfamilies exhibited expansions associated with dietary shifts to frugivory. Taken together, these results suggest ecological correlates of individual OR gene subfamilies can be identified, setting the stage for detailed inquiry into within-subfamily functional differences.

The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the vulnerability of human populations to novel viral pressures, despite the vast array of epidemiological and biomedical tools now available. Notably, modern human genomes contain evolutionary information tracing back tens of thousands of years, which may help identify the viruses that have impacted our ancestors—pointing to which viruses have future pandemic potential. Here, we apply evolutionary analyses to human genomic datasets to recover selection events involving tens of human genes that interact with coronaviruses, including SARS-CoV-2, that likely started more than 20,000 years ago. These adaptive events were limited to the population ancestral to East Asian populations. Multiple lines of functional evidence support an ancient viral selective pressure, and East Asia is the geographical origin of several modern coronavirus epidemics. An arms race with an ancient coronavirus, or with a different virus that happened to use similar interactions as coronaviruses with human hosts, may thus have taken place in ancestral East Asian populations. By learning more about our ancient viral foes, our study highlights the promise of evolutionary information to better predict the pandemics of the future. Importantly, adaptation to ancient viral epidemics in specific human populations does not necessarily imply any difference in genetic susceptibility between different human populations, and the current evidence points toward an overwhelming impact of socioeconomic factors in the case of coronavirus disease 2019 (COVID-19)., Graphical abstract, Souilmi et al. find that strong genetic adaptation occurred in human East Asian populations, at multiple genes that interact with coronaviruses, including SARS-CoV-2. The adaptation started 25,000 years ago, and functional analysis of the adapting genes supports the occurrence of a corona- or related virus epidemic around that time in East Asia.

Several taxonomically distinct mammalian groups—certain microbats and cetaceans (e.g., dolphins)—share both morphological adaptations related to echolocation behavior and strong signatures of convergent evolution at the amino acid level across seven genes related to auditory processing. Aye-ayes (Daubentonia madagascariensis) are nocturnal lemurs with a specialized auditory processing system. Aye-ayes tap rapidly along the surfaces of trees, listening to reverberations to identify the mines of wood-boring insect larvae; this behavior has been hypothesized to functionally mimic echolocation. Here we investigated whether there are signals of convergence in auditory processing genes between aye-ayes and known mammalian echolocators. We developed a computational pipeline (Basic Exon Assembly Tool) that produces consensus sequences for regions of interest from shotgun genomic sequencing data for nonmodel organisms without requiring de novo genome assembly. We reconstructed complete coding region sequences for the seven convergent echolocating bat–dolphin genes for aye-ayes and another lemur. We compared sequences from these two lemurs in a phylogenetic framework with those of bat and dolphin echolocators and appropriate nonecholocating outgroups. Our analysis reaffirms the existence of amino acid convergence at these loci among echolocating bats and dolphins; some methods also detected signals of convergence between echolocating bats and both mice and elephants. However, we observed no significant signal of amino acid convergence between aye-ayes and echolocating bats and dolphins, suggesting that aye-aye tap-foraging auditory adaptations represent distinct evolutionary innovations. These results are also consistent with a developing consensus that convergent behavioral ecology does not reliably predict convergent molecular evolution.