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DNA methylation-derived epigenetic clocks offer the opportunity to examine aspects of age acceleration (i.e., the difference between an individual’s biological age and chronological age), which vary among individuals and may better account for age-related changes in cognitive function than chronological age. Leveraging existing ambulatory cognitive assessments in daily life from a genetically diverse sample of 142 adults in midlife, we examined associations between five measures of epigenetic age acceleration and performance on tasks of processing speed and working memory. Covarying for chronological age, we used multilevel models to examine associations of epigenetic age acceleration (Horvath 1, Horvath 2, Hannum, PhenoAge, GrimAge clocks) with both average-level and variability of cognitive performance. Positive age acceleration (i.e., epigenetic age greater than chronological age) was associated with poorer mean processing speed (Horvath 1 and 2) and working memory (GrimAge). Higher chronological age was also associated with poorer mean processing speed and working memory performance. Further, positive age acceleration was generally associated with greater intraindividual variability in working memory and processing speed tasks, whereas being chronologically older was associated with less intraindividual variability. Although further work is needed, our results indicate age acceleration effects have comparable or greater size as those for chronological age differences, suggesting that epigenetic age acceleration may be a better marker of risk and interindividual variation in cognitive performance than chronological age.

Transcriptome-wide association studies (TWAS) are a powerful approach to identify genes whose expression associates with complex disease risk. However, non-causal genes can exhibit association signals due to confounding by linkage disequilibrium patterns (LD) and eQTL pleiotropy at genomic risk regions which necessitates fine-mapping of TWAS signals. Here, we present MA-FOCUS, a multi-ancestry framework for the improved identification of genes underlying traits of interest. We demonstrate that by leveraging differences in ancestry-specific patterns of LD and eQTL signals, MA-FOCUS consistently outperforms single-ancestry fine-mapping approaches with equivalent total sample size across multiple metrics. We perform 15 blood trait TWAS using genome-wide summary statistics (average NEA=511k, NAA=13k) and lymphoblastoid cell line eQTL data from cohorts of primarily European and African continental ancestries. We recapitulate evidence demonstrating shared genetic architectures for eQTL and blood traits between the two ancestry groups and observe that gene-level effects correlate 20% more strongly across ancestries compared with SNP-level effects. We perform fine-mapping using MA-FOCUS and find evidence that genes at TWAS risk regions are more likely to be shared across ancestries rather than ancestry-specific. Using multiple lines of evidence to validate our findings, we find gene sets produced by MA-FOCUS are more enriched in hematopoietic categories compared to alternative approaches (P = 1.73 × 10−16). Our work demonstrates that including, and appropriately accounting for, genetic diversity can drive deeper insights into the genetic architecture of complex traits.

Questions surrounding the timing, extent, and evolutionary consequences of archaic admixture into human populations have a long history in evolutionary anthropology. More recently, advances in human genetics, particularly in the field of ancient DNA, have shed new light on the question of whether or not Homo sapiens interbred with other hominin groups. By the late 1990s, published genetic work had largely concluded that archaic groups made no lasting genetic contribution to modern humans; less than a decade later, this conclusion was reversed following the successful DNA sequencing of an ancient Neanderthal. This reversal of consensus is noteworthy, but the reasoning behind it is not widely understood across all academic communities. There remains a communication gap between population geneticists and paleoanthropologists. In this review, we endeavor to bridge this gap by outlining how technological advancements, new statistical methods, and notable controversies ultimately led to the current consensus.

Over the past 50 years, geneticists have made great strides in understanding how our species' evolutionary history gave rise to current patterns of human genetic diversity classically summarized by Lewontin in his 1972 paper, ‘The Apportionment of Human Diversity’. One evolutionary process that requires special attention in both population genetics and statistical genetics is admixture: gene flow between two or more previously separated source populations to form a new admixed population. The admixture process introduces ancestry-based structure into patterns of genetic variation within and between populations, which in turn influences the inference of demographic histories, identification of genetic targets of selection and prediction of complex traits. In this review, we outline some challenges for admixture population genetics, including limitations of applying methods designed for populations without recent admixture to the study of admixed populations. We highlight recent studies and methodological advances that aim to overcome such challenges, leveraging genomic signatures of admixture that occurred in the past tens of generations to gain insights into human history, natural selection and complex trait architecture. This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

Despite rapid progress in characterizing the role of host genetics in SARS-Cov-2 infection, there is limited understanding of genes and pathways that contribute to COVID-19. Here, we integrate a genome-wide association study of COVID-19 hospitalization (7,885 cases and 961,804 controls from COVID-19 Host Genetics Initiative) with mRNA expression, splicing, and protein levels (n = 18,502). We identify 27 genes related to inflammation and coagulation pathways whose genetically predicted expression was associated with COVID-19 hospitalization. We functionally characterize the 27 genes using phenome- and laboratory-wide association scans in Vanderbilt Biobank (n = 85,460) and identified coagulation-related clinical symptoms, immunologic, and blood-cell-related biomarkers. We replicate these findings across trans-ethnic studies and observed consistent effects in individuals of diverse ancestral backgrounds in Vanderbilt Biobank, pan-UK Biobank, and Biobank Japan. Our study highlights and reconfirms putative causal genes impacting COVID-19 severity and symptomology through the host inflammatory response., Genome-wide association studies of COVID-19 have identified genetic loci affecting disease severity, but the mechanisms remain to be fully described. Here, the authors use genetically predicted transcriptome, splicing and proteome data to identify potential genes and pathways underlying COVID- 19 severity.

Despite rapid progress in characterizing the role of host genetics in SARS-Cov-2 infection, there is limited understanding of genes and pathways that contribute to COVID-19. Here, we integrated a genome-wide association study of COVID-19 hospitalization (7,885 cases and 961,804 controls from COVID-19 Host Genetics Initiative) with mRNA expression, splicing, and protein levels (n=18,502). We identified 27 genes related to inflammation and coagulation pathways whose genetically predicted expression was associated with COVID-19 hospitalization. We functionally characterized the 27 genes using phenome- and laboratory-wide association scans in Vanderbilt Biobank (BioVU; n=85,460) and identified coagulation-related clinical symptoms, immunologic, and blood-cell-related biomarkers. We replicated these findings across trans-ethnic studies and observed consistent effects in individuals of diverse ancestral backgrounds in BioVU, pan-UK Biobank, and Biobank Japan. Our study highlights putative causal genes impacting COVID-19 severity and symptomology through the host inflammatory response.

Himba have an extrapair paternity rate of 48% with both men and women highly accurate at detecting cases of EPP., Among nonhuman species, social monogamy is rarely accompanied by complete fidelity. Evolutionary theory predicts that the rate of extrapair paternity (EPP) should vary according to socioecological conditions. In humans, however, geneticists contend that EPP is negligible and relatively invariable. This conclusion is based on a limited set of studies, almost all of which describe European-descent groups. Using a novel, double-blind method designed in collaboration with a community of Himba pastoralists, we find that the rate of EPP in this population is 48%, with 70% of couples having at least one EPP child. Both men and women were very accurate at detecting cases of EPP. These data suggest that the range of variation in EPP across human populations is substantially greater than previously thought. We further show that a high rate of EPP can be accompanied by high paternity confidence, which highlights the importance of disaggregating EPP from the notion of “cuckoldry.”

DNA methylation is an epigenetic modification of cytosine nucleotides that represents a promising suite of aging markers with broad potential applications. In particular, determining an individual’s age from their skeletal remains is an enduring problem in the field of forensic anthropology, and one that epigenetic markers are particularly well-suited to address. However, all DNA methylation-based age prediction methods published so far focus on tissues other than bone. While high accuracy has been achieved for saliva, blood and sperm, which are easily accessible in living individuals, the highly tissue-specific nature of DNA methylation patterns means that age prediction models trained on these particular tissues may not be directly applicable to other tissues. Bone is a prime target for the development of DNA methylation-based forensic identification tools as skeletal remains are often recoverable for years post-mortem, and well after soft tissues have decomposed. In this study, we generate genome-wide DNA methylation data from 32 individual bone samples. We analyze this new dataset alongside published data from 133 additional bone donors, both living and deceased. We perform an epigenome-wide association study on this combined dataset to identify 108 sites of DNA methylation that show a significant relationship with age (FDR < 0.05). We also develop an age-prediction model using lasso regression that produces highly accurate estimates of age from bone spanning an age range of 49-112 years. Our study demonstrates that DNA methylation levels at specific CpG sites can serve as powerful markers of aging, and can yield more accurate predictions of chronological age in human adults than morphometric markers.

The fate of hunting and gathering populations following the rise of agriculture and pastoralism remains a topic of debate in the study of human prehistory. Studies of ancient and modern genomes have found that autochthonous groups were largely replaced by expanding farmer populations with varying levels of gene flow, a characterization that is influenced by the almost universal focus on the European Neolithic(1–5). We sought to understand the demographic impact of an ongoing shift to farming in Southwest Ethiopia, one of the last regions in Africa to experience such shifts(6). Importantly, Southwest Ethiopia is home to several of the world’s remaining hunter-gatherer groups, including the Chabu people, who are currently transitioning away from their traditional mode of subsistence(7). We generated genome-wide data from the Chabu and four neighboring populations, the Majang, Shekkacho, Bench, and Sheko, to characterize their genetic ancestry and estimate their effective population sizes throughout the last 60 generations. We show that the Chabu are a distinct population closely related to ancient peoples who occupied Southwest Ethiopia >4,500 years ago. Furthermore, the Chabu are undergoing a severe population bottleneck which began approximately 1,400 years ago. In studying eleven Eastern African populations, we find evidence for divergent demographic trajectories among hunter-gatherer-descendant groups. Our results illustrate that although foragers respond to encroaching agriculture and pastoralism with multiple strategies, including cultural adoption of agropastoralism, gene flow and economic specialization, they often face population decline.

A major outstanding question in human prehistory is the fate of hunting and gathering populations following the rise of agriculture and pastoralism. Genomic analysis of ancient and contemporary Europeans suggests that autochthonous groups were either absorbed into or replaced by expanding farmer populations. Many of the hunter-gatherer populations persisting today live in Africa, perhaps because agropastoral transitions occurred later on the continent. Here, we present the first genomic data from the Chabu, a relatively isolated and marginalized hunting-and-gathering group from the Southwestern Ethiopian highlands. The Chabu are a distinct genetic population that carry the highest levels of Southwestern Ethiopian ancestry of any extant population studied thus far. This ancestry has been in situ for at least 4,500 years. We show that the Chabu are undergoing a severe population bottleneck which began around 40 generations ago. We also study other Eastern African populations and demonstrate divergent patterns of historical population size change over the past 60 generations between even closely related groups. We argue that these patterns demonstrate that, unlike in Europe, Africans hunter-gatherers responded to agropastoralism with diverse strategies.

Europe has played a major role in dog evolution, harbouring the oldest uncontested Palaeolithic remains and having been the centre of modern dog breed creation. Here we sequence the genomes of an Early and End Neolithic dog from Germany, including a sample associated with an early European farming community. Both dogs demonstrate continuity with each other and predominantly share ancestry with modern European dogs, contradicting a previously suggested Late Neolithic population replacement. We find no genetic evidence to support the recent hypothesis proposing dual origins of dog domestication. By calibrating the mutation rate using our oldest dog, we narrow the timing of dog domestication to 20,000–40,000 years ago. Interestingly, we do not observe the extreme copy number expansion of the AMY2B gene characteristic of modern dogs that has previously been proposed as an adaptation to a starch-rich diet driven by the widespread adoption of agriculture in the Neolithic., The European continent is thought to have played a major role in the origins of modern dogs. Here, analysing two ancient dog genomes from Germany, the authors find significant genetic continuity throughout the Neolithic period and time dog domestication to ∼20,000–40,000 years ago.

Aging is associated with widespread changes in genome-wide patterns of DNA methylation. Thousands of CpG sites whose tissue-specific methylation levels are strongly correlated with chronological age have been previously identified. However, the majority of these studies have focused primarily on cosmopolitan populations living in the developed world; it is not known if age-related patterns of DNA methylation at these loci are similar across a broad range of human genetic and ecological diversity. We investigated genome-wide methylation patterns using saliva- and whole blood-derived DNA from two traditionally hunting and gathering African populations: the Baka of the western Central African rain forest and the ≠Khomani San of the South African Kalahari Desert. We identified hundreds of CpG sites whose methylation levels are significantly associated with age, thousands that are significant in a meta-analysis, and replicate trends previously reported in populations of non-African descent. We confirmed that an age-associated site in the promoter of the gene ELOVL2 shows a remarkably congruent relationship with aging in humans, despite extensive genetic and environmental variation across populations. We also demonstrate that genotype state at methylation quantitative trait loci (meQTLs) can affect methylation trends at some age-associated CpG sites. Our study explores the relationship between CpG methylation and chronological age in populations of African hunter-gatherers, who rely on different diets across diverse ecologies. While many age-related CpG sites replicate across populations, we show that considering common genetic variation at meQTLs further improves our ability to detect previously identified age associations.

WOS: 000378272400038, PubMed ID: 27274049, Farming and sedentism first appeared in southwestern Asia during the early Holocene and later spread to neighboring regions, including Europe, along multiple dispersal routes. Conspicuous uncertainties remain about the relative roles of migration, cultural diffusion, and admixture with local foragers in the early Neolithization of Europe. Here we present paleogenomic data for five Neolithic individuals from northern Greece and northwestern Turkey spanning the time and region of the earliest spread of farming into Europe. We use a novel approach to recalibrate raw reads and call genotypes from ancient DNA and observe striking genetic similarity both among Aegean early farmers and with those from across Europe. Our study demonstrates a direct genetic link between Mediterranean and Central European early farmers and those of Greece and Anatolia, extending the European Neolithic migratory chain all the way back to southwestern Asia., Marie Curie Initial Training Network (BEAN/Bridging the European and Anatolian Neolithic) [GA 289966]; DFGGerman Research Foundation (DFG) [BU 1403/6-1, BO 4119/1]; Alexander von Humboldt FoundationAlexander von Humboldt Foundation; European Union (EU) SYNTHESYS/Synthesis of Systematic Resources [GA 226506-CP-CSA-INFRA]; VolkswagenstiftungVolkswagen [FKZ: 87161]; Irish Research CouncilIrish Research Council for Science, Engineering and Technology [GOIPG/2013/1219]; EU CodeX Project [295729]; EU Social Fund; Greek national funds research funding program THALES; Greek national funds research funding program ARISTEIA II; Swiss NSFSwiss National Science Foundation (SNSF) [31003A_156853, 31003A_149920]; BBSRCBiotechnology and Biological Sciences Research Council (BBSRC) [BB/L009382/1]; CoMPLEX via EPSRC [EP/F500351/1]; Sir Henry Dale Fellowship - Wellcome Trust [098386/Z/12/Z]; Sir Henry Dale Fellowship - Royal Society [098386/Z/12/Z]; National Institute for Health Research University College London Hospitals Biomedical Research Centre; Wellcome TrustWellcome Trust [100719/Z/12/Z]; University of Mainz; HPC cluster MOGON - DFG [INST 247/602-1 FUGG]; Netherlands Organization for Scientific ResearchNetherlands Organization for Scientific Research (NWO) [380-62-005]; Biotechnology and Biological Sciences Research CouncilBiotechnology and Biological Sciences Research Council (BBSRC) [BB/L009382/1]; Engineering and Physical Sciences Research CouncilEngineering & Physical Sciences Research Council (EPSRC) [1357822], We thank Songul Alpaslan for help with sampling in Barcin and Eleni Stravopodi for help with sampling in Theopetra. Z.H. and R.M. are supported by a Marie Curie Initial Training Network (BEAN/Bridging the European and Anatolian Neolithic, GA 289966) awarded to M.C., S.J.S., D.G.B., M.G.T., and J. Burger. C.P., J. Burger and S.K. received funding from DFG (BU 1403/6-1). C.P. and J. Burger received funding from the Alexander von Humboldt Foundation. C.S. and M.S. were supported by the European Union (EU) SYNTHESYS/Synthesis of Systematic Resources GA 226506-CP-CSA-INFRA, DFG: (BO 4119/1) and Volkswagenstiftung (FKZ: 87161). L.M.C. is funded by the Irish Research Council (GOIPG/2013/1219). A.S. was supported by the EU CodeX Project 295729. K. Kotsakis, S.T., D.U.-K., P.H., and C.P. were cofinanced by the EU Social Fund and Greek national funds research funding program THALES. C.P., M.U., K. Kotsakis, S.T., and D.U.-K. were cofinanced by the EU Social Fund and the Greek national funds research funding program ARISTEIA II. M.C. was supported by Swiss NSF Grant 31003A_156853. A. K. and D.W. were supported by Swiss NSF Grant 31003A_149920. S.L. is supported by the BBSRC (Grant BB/L009382/1). L.v.D. is supported by CoMPLEX via EPSRC (Grant EP/F500351/1). G.H. is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant 098386/Z/12/Z) and by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. M.G.T. and Y.D. are supported by a Wellcome Trust Senior Research Fellowship Grant 100719/Z/12/Z (to M.G.T.). J. Burger is grateful for support by the University of Mainz and the HPC cluster MOGON (funded by DFG; INST 247/602-1 FUGG). F.G. was supported by Grant 380-62-005 of the Netherlands Organization for Scientific Research.

Supplementary figures and tables. This files includes supplementary tables and figures to the main manuscript. (PDF 4085kb)

BackgroundA fundamental and enduring problem in evolutionary biology is to understand how populations differentiate in the wild, yet little is known about what role organismal development plays in this process. Organismal development integrates environmental inputs with the action of gene regulatory networks to generate the phenotype. Core developmental gene networks have been highly conserved for millions of years across all animals, and therefore, organismal development may bias variation available for selection to work on. Biased variation may facilitate repeatable phenotypic responses when exposed to similar environmental inputs and ecological changes. To gain a more complete understanding of population differentiation in the wild, we integrated evolutionary developmental biology with population genetics, morphology, paleoecology and ecology. This integration was made possible by studying how populations of the ant speciesMonomorium emersonirespond to climatic and ecological changes across five ‘Sky Islands’ in Arizona, which are mountain ranges separated by vast ‘seas’ of desert. Sky Islands represent a replicated natural experiment allowing us to determine how repeatable is the response ofM. emersonipopulations to climate and ecological changes at the phenotypic, developmental, and gene network levels.ResultsWe show that a core developmental gene network and its phenotype has kept pace with ecological and climate change on each Sky Island over the last ∼90,000 years before present (BP). This response has produced two types of evolutionary change within an ant species: one type is unpredictable and contingent on the pattern of isolation of Sky lsland populations by climate warming, resulting in slight changes in gene expression, organ growth, and morphology. The other type is predictable and deterministic, resulting in the repeated evolution of a novel wingless queen phenotype and its underlying gene network in response to habitat changes induced by climate warming.ConclusionOur findings reveal dynamics of developmental gene network evolution in wild populations. This holds important implications: (1) for understanding how phenotypic novelty is generated in the wild; (2) for providing a possible bridge between micro- and macroevolution; and (3) for understanding how development mediates the response of organisms to past, and potentially, future climate change.

Supplementary figures and tables. This files includes supplementary tables and figures to the main manuscript. (PDF 4085kb)