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Understanding the impacts of selection pressures influencing modern-day genomic diversity is a major goal of evolutionary genomics. In particular, the contribution of selective sweeps to adaptation remains an open question, with persistent statistical limitations on the power and specificity of sweep detection methods. Sweeps with subtle genomic signals have been particularly challenging to detect. Although many existing methods powerfully detect specific types of sweeps and/or those with strong signals, their power comes at the expense of versatility. We present Flex-sweep, a machine learning–based tool designed to detect sweeps with a variety of subtle signals, including those thousands of generations old. It is especially valuable for nonmodel organisms, for which we have neither expectations about the overall characteristics of sweeps nor outgroups with population-level sequencing to otherwise facilitate detecting very old sweeps. We show that Flex-sweep has the power to detect sweeps with subtle signals, even in the face of demographic model misspecification, recombination rate heterogeneity, and background selection. Flex-sweep detects sweeps up to 0.125*4Ne generations old, including those that are weak, soft, and/or incomplete; it can also detect strong, complete sweeps up to 0.25*4Ne generations old. We apply Flex-sweep to the 1000 Genomes Yoruba data set and, in addition to recovering previously identified sweeps, show that sweeps disproportionately occur within genic regions and are close to regulatory regions. In addition, we show that virus-interacting proteins (VIPs) are strongly enriched for selective sweeps, recapitulating previous results that demonstrate the importance of viruses as a driver of adaptive evolution in humans.

Lifespan is one of the most variable traits across the entire tree of life, and especially in mammals. Differences in lifespans between closely-related species provides a promising avenue for discovering novel pro-longevity pathways using evolutionary techniques. Previous studies focused on the evolution of longevity-associated traits, such as DNA damage response, have been hampered by a combination of low-quality genomes, low-phylogenetic coverage, or long evolutionary times, all of which can negatively affect their power to detect genes associated with longevity. In order to comprehensively study the evolution of aging and aging-associated traits in bats, we generated chromosome-level reference genomes and primary cell line libraries from a 10-million-year-old clade of 9 California Myotis species spanning a 3-fold range of lifespans. Increases and decreases in longevity independent of body size have evolved multiple times in this clade, providing a dynamic range which can be studied through functional genomics. Leveraging both genomes and cell lines, we identify several pathways specifically associated with longevity, in addition to other longevity-associated traits such as DNA repair and immunity; and show that these changes are associated with cellular resistance to various forms of chemically-induced DNA damage. These pathways represent new targets for exploration using primary cell cultures, and contribute to our understanding of how both agonistic and antagonistic pleiotropy play a role in the evolution of longevity.

NSF PRFB 2109915 NIH 5R35GM142916-03.

This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic data sets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and to the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than three-fold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Several bat species act as asymptomatic reservoirs for many viruses that are highly pathogenic in other mammals. Here, we have characterized the functional diversification of the protein kinase R (PKR), a major antiviral innate defense system. Our data indicate that PKR has evolved under positive selection and has undergone repeated genomic duplications in bats in contrast to all studied mammals that have a single copy of the gene. Functional testing of the relationship between PKR and poxvirus antagonists revealed how an evolutionary conflict with ancient pathogenic poxviruses has shaped a specific bat host-virus interface. We determined that duplicated PKRs of theMyotisspecies have undergone genetic diversification, allowing them to collectively escape from and enhance the control of DNA and RNA viruses. These findings suggest that viral-driven adaptations in PKR contribute to modern virus-bat interactions and may account for bat-specific immunity.