The rich diversity of morphology and behavior displayed across primate species provides an informative context in which to study the impact of genomic diversity on fundamental biological processes. Analysis of that diversity provides insight into long-standing questions in evolutionary and conservation biology and is urgent given severe threats these species are facing. Here, we present high-coverage whole-genome data from 233 primate species representing 86% of genera and all 16 families. This dataset was used, together with fossil calibration, to create a nuclear DNA phylogeny and to reassess evolutionary divergence times among primate clades. We found within-species genetic diversity across families and geographic regions to be associated with climate and sociality, but not with extinction risk. Furthermore, mutation rates differ across species, potentially influenced by effective population sizes. Lastly, we identified extensive recurrence of missense mutations previously thought to be human specific. This study will open a wide range of research avenues for future primate genomic research.

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

Karstic landscapes are immense reservoirs of biodiversity and range-restricted endemism. Nowhere is this more evident than in the world’s third-largest vertebrate genus Cyrtodactylus (Gekkonidae) which contains well over 300 species. A stochastic character mapping analysis of 10 different habitat preferences across a phylogeny containing 344 described and undescribed species recovered a karst habitat preference occurring in 25.0% of the species, whereas that of the other eight specific habitat preferences occurred in only 0.2–11.0% of the species. The tenth category—general habitat preference—occurred in 38.7% of the species and was the ancestral habitat preference for Cyrtodactylus and the ultimate origin of all other habitat preferences. This study echoes the results of a previous study illustrating that karstic landscapes are generators of species diversity within Cyrtodactylus and not simply “imperiled arks of biodiversity” serving as refugia for relics. Unfortunately, the immense financial returns of mineral extraction to developing nations largely outweighs concerns for biodiversity conservation, leaving approximately 99% of karstic landscapes with no legal protection. This study continues to underscore the urgent need for their appropriate management and conservation. Additionally, this analysis supports the monophyly of the recently proposed 31 species groups and adds one additional species group.

The gekkonid genus Cyrtodactylus is the third most speciose vertebrate genus in the world, containing well over 300 species that collectively range from South Asia to Melanesia across some of the most diverse landscapes and imperiled habitats on the planet. A genus-wide phylogeny of the group has never been presented because researchers working on different groups were using different genetic markers to construct phylogenies that could not be integrated. We present here Maximum likelihood and Bayesian inference mitochondrial and mito-nuclear phylogenies incorporating of 310 species that include dozens of species that had never been included in a genus-wide analysis. Based on the mitochondrial phylogeny, we partition Cyrtodactylus into 31 well-supported monophyletic species groups which, if used as recommended herein, will increase the information content of future integrative taxonomic analyses that continue to add new species to this genus at an ever-increasing annual rate. Data presented here reiterate the outcome of several previous studies indicating that Cyrtodactylus comprises an unprecedented number of narrow-range endemics restricted to single mountain tops, small islands, or karst formations that still remain unprotected. This phylogeny can provide a platform for various comparative ecological studies that can be integrated with conservation management programs across the broad diversity of landscapes and habitats occupied by this genus. Additionally, these data indicate that the true number of Cyrtodactylus remains substantially underrepresented.

The gekkonid genus Cyrtodactylus is the third most speciose vertebrate genus in the world, containing well over 300 species that collectively range from South Asia to Melanesia across some of the most diverse landscapes and imperiled habitats on the planet. A genus-wide phylogeny of the group has never been presented because researchers working on different groups were using different genetic markers to construct phylogenies that could not be integrated. We present here Maximum likelihood and Bayesian inference mitochondrial and mito-nuclear phylogenies incorporating of 310 species that include dozens of species that had never been included in a genus-wide analysis. Based on the mitochondrial phylogeny, we partition Cyrtodactylus into 31 well-supported monophyletic species groups which, if used as recommended herein, will increase the information content of future integrative taxonomic analyses that continue to add new species to this genus at an ever-increasing annual rate. Data presented here reiterate the outcome of several previous studies indicating that Cyrtodactylus comprises an unprecedented number of narrow-range endemics restricted to single mountain tops, small islands, or karst formations that still remain unprotected. This phylogeny can provide a platform for various comparative ecological studies that can be integrated with conservation management programs across the broad diversity of landscapes and habitats occupied by this genus. Additionally, these data indicate that the true number of Cyrtodactylus remains substantially underrepresented.

Aim: Unsustainable hunting is leading to widespread defaunation across the tropics. To mitigate against this threat with limited conservation resources, stakeholders must make decisions on where to focus anti‐poaching activities. Identifying priority areas in a robust way allows decision‐makers to target areas of conservation importance, therefore maximizing the impact of conservation interventions.Location: Annamite mountains, Vietnam and Laos.Methods: We conducted systematic landscape‐scale surveys across five study sites (four protected areas, one unprotected area) using camera‐trapping and leech‐derived environmental DNA. We analysed detections within a Bayesian multispecies occupancy framework to evaluate species responses to environmental and anthropogenic influences. Species responses were then used to predict occurrence to unsampled regions. We used predicted species richness maps and occurrence of endemic species to identify areas of conservation importance for targeted conservation interventions.Results: Analyses showed that habitat‐based covariates were uninformative. Our final model therefore incorporated three anthropogenic covariates as well as elevation, which reflects both ecological and anthropogenic factors. Conservation‐priority species tended to found in areas that are more remote now or have been less accessible in the past, and at higher elevations. Predicted species richness was low and broadly similar across the sites, but slightly higher in the more remote site. Occupancy of the three endemic species showed a similar trend.Main conclusion: Identifying spatial patterns of biodiversity in heavily defaunated landscapes may require novel methodological and analytical approaches. Our results indicate that to build robust prediction maps it is beneficial to sample over large spatial scales, use multiple detection methods to increase detections for rare species, include anthropogenic covariates that capture different aspects of hunting pressure and analyse data within a Bayesian multispecies framework. Our models further suggest that more remote areas should be prioritized for anti‐poaching efforts to prevent the loss of rare and endemic species.