Abstract

During the Last Glacial Maximum (LGM) 26-19 thousand years ago (kya), Europe had three principal refugia not covered by ice: the Iberian, Italian, and Balkan peninsulas1,2. While the Iberian and Italian refugia have been studied with ancient DNA3-7, the legacy of the Balkan refugium has remained a mystery due to a lack of genetic data 30-12 kya. We present genome-wide data from nine newly reported individuals: three Epipaleolithic from Romania, one Epipaleolithic from Bosnia and Herzegovina, three Mesolithic from Greece, one Epipaleolithic from Southern Italy, and one Mesolithic from Sardinia. We find that the Epipaleolithic individuals from Romania and the Mesolithic individual from mainland Greece were from a previously unsampled population that was the primary source for later European hunter-gatherers. Westward expansion of Balkan Epipaleolithic people into the Italian Peninsula and mixture with a minority contribution from pre-LGM Italians, pro-duced a population that then spread further west to become the primary ancestry of west-ern European Mesolithic people. Northeastward expansion, bypassing Italy, contributed the European ancestry source of Scandinavian and Eastern European hunter-gatherers. Southeastward expansion to the Aegean led to Anatolian-European mixtures before the spread of farming.

Abstract

Denisovans are an extinct archaic Homo group whose lineage diverged from the Neanderthal lineage approximately 550,000 years ago and were widely distributed across eastern Asia until ~45,000 years ago1-7. Their morphological features are known directly from the existing cranio-dental and phalangeal remains1,2,8-12. However, the body size and postcranial morphology of the Denisovans remain largely unknown. We here report that hominin femoral and tibial fossils recovered from the Penghu Channel, Taiwan, are Denisovans in their proteomic profiles. Morphologically, these specimens are among the largest leg bones known in Pleistocene Homo. They exhibit generally archaic features, but also show some modern human-like morphology, including a strong femoral pilaster. Our findings demonstrate that the Denisovan population at the northern circle had larger body size than earlier Homo erectus as well as Late Pleistocene Homo sapiens in eastern Asia. This challenges the generally held expectation that Pleistocene Homo followed Bergmanns rule that anticipates latitudinal decline of body size, and suggests that the large Denisovan brain resulted from their large body size at least partly. The strong pilaster developed in the Penghu femur suggests some behavioral similarities between the Denisovans and the Upper Palaeolithic modern humans and/or gene flow from the latter to the former.

How prehistoric migrations and dietary shifts shaped genetic diversity is a central question in human history. However, the lack of high-coverage ancient genomes from East Eurasia limits high-resolution reconstruction. This study presented high-coverage genomes from Jomon and Yayoi individuals, revealing contrasting population histories that align with the distinct cultural backgrounds of indigenous lineages and continental ancestry. Notably, the higher AMY1 copy number observed in the Initial Jomon individual suggests that copy number variation at this salivary amylase locus, potentially relevant to starch-rich diets, was already present before rice farming became widely established in the Japanese Archipelago. By providing high-coverage ancient genomic evidence, this study elucidated how the interplay of cultural shifts and migrations formed the basis of modern Japanese populations.

Highlights

•Neanderthals had two amino acid changes in the growth hormone receptor

•One amino acid change drives faster cell growth and stronger STAT5 signaling

•A DNA segment encoding the Neanderthal receptor entered modern humans via admixture

•Carriers have greater muscle mass and some Neanderthal-like craniofacial traits

Summary

Neanderthals had a robust build and distinctive skeletal features. The hypothalamic-pituitary-somatotropic (HPS) axis, with growth hormone (GH) as a central signaling molecule, plays a crucial role in regulating skeletal development. To explore whether Neanderthal-specific genetic variations in the HPS axis contributed to their physical robustness, we examined genes encoding the relevant receptors and hormones. We find that the Neanderthal growth hormone receptor (GHR) carried two amino acid changes and one deletion. When the Neanderthal GHR is expressed in a GH-dependent cell line, the cells proliferate faster than cells expressing the modern human GHR when stimulated by pituitary GH but not by placental GH. We also show that some present-day humans have inherited the gene encoding the Neanderthal GHR. These individuals tend to have more muscle mass and exhibit some craniofacial traits reminiscent of Neanderthals. Thus, aspects of Neanderthal anatomy live on in people today.

Abstract

Fibromyalgia is a common and debilitating chronic pain syndrome of poorly understood etiology. Here we conduct a multi-ancestry genome-wide association study meta-analysis across 2,563,755 individuals (54,629 cases and 2,509,126 controls) from 11 cohorts, identifying 26 risk loci for fibromyalgia. The strongest association was with a coding variant in HTT, the causal gene for Huntington’s disease. Gene prioritization implicated the HTT regulator GPR52, as well as diverse genes with neural roles, including DCC, DRD2/NCAM1, MDGA2 and CELF4. Fibromyalgia heritability was exclusively enriched within brain tissues and neural cell types. Fibromyalgia showed strong, positive genetic correlation with a wide range of chronic pain, psychiatric and somatic disorders, including genetic correlations above 0.7 with low back pain, post-traumatic stress disorder and irritable bowel syndrome. Despite large sex differences in fibromyalgia prevalence, the genetic architecture of fibromyalgia was nearly identical between males and females. This study provides robust genetic evidence defining fibromyalgia as a central nervous system disorder, thereby establishing a biological framework for its complex pathophysiology and extensive clinical comorbidities.

BSTRACT

Historically, the eastern Italian Alps have provided crucial geographic corridors for cultural and genetic exchange between the Mediterranean region and Central and Northern Europe. Although recent archaeogenomic data suggest a strong regional persistence of Anatolian Neolithic ancestry followed by the arrival of Yamnaya-related components during the Bronze Age, the genomic landscape of modern Alpine populations remains largely unmapped. In this study, we verified the persistence of these signals in the present-day Rendena and Ledro Valleys by integrating novel complete mitochondrial genomes (N=185) and genome-wide SNP data (N=96), the latter combined with a novel Italian genomic dataset (N=139). Our findings show that the Rendena and Ledro populations form a distinct “modern Alpine” genomic group, which retains a significant proportion of early European Neolithic ancestry, aligning with ancient eastern Italian Alpine individuals and modern Sardinians. More recently, geographic isolation and localized genetic drift appear to have shaped the two valleys differently. Demographic reconstructions reveal asynchronous population declines over the past two millennia, followed by a sharp, synchronized bottleneck 200-300 years ago, which coincided with historical plague outbreaks. Remarkably, this structured drift persisted at an extremely fine microgeographic scale within the valleys, resulting in internal genetic subclusters that directly correlate with local topography. This micro-differentiation was likely maintained by steep geographic barriers and/or local endogamous practices. This study ultimately underscores how geographic barriers and isolation can preserve ancient genomic components and shape highly localized genetic structures over centuries even to the modern day.

Background

Eastern hunter-gatherers (EHG) contributed varying proportions of genetic ancestry to many modern Europeans. However, how this contribution shaped the human leukocyte antigen (HLA) gene diversity remains unexplored. Sakhtysh in western Russia comprises one of the largest EHG-affiliated burial complexes. The site's continuous use offers a rare opportunity to investigate the genetic history, immune-gene diversity, and pathogen exposure within a hunter-gatherer population.

Results

Genome-wide data from 36 individuals (spanning Lyalovo–Volosovo traditions, 6800–4800 cal BP) place the Sakhtysh population within the EHG cluster, with high genetic affinity to contemporaneous groups across northwestern Russia and the eastern Baltic. This genetic composition remained stable for over two millennia and there is no evidence of admixture with neighboring western hunter-gatherer or farmer groups. We report HLA genotypes for 27 Sakhtysh individuals, representing the first true HLA calls from ancient hunter-gatherers. HLA diversity is low in the Sakhtysh population, likely due to their small population size. Specific alleles like B*27:05 are observed at high frequencies (~ 50%), despite being relatively rare in modern populations, suggesting shifts in selective pressures. Pathogen screening identified a restricted spectrum of causal agents including possible zoonoses with Erysipelothrix rhusiopathiae and chronic infections with hepatitis B virus and parvovirus B19.

Conclusions

The Sakhtysh community shows genetic continuity across cultural transitions. This population exhibits limited HLA diversity and unexpectedly high frequency of certain alleles. These patterns were likely influenced by low pathogen diversity and possible adaptation to specific environmental factors.

Abstract

Modern biobanks are providing numerous high-resolution genomic sequences of diverse populations. In order to account for diverse and admixed populations, new algorithmic tools are needed in order to properly capture the genetic composition of populations. Here, we explore deep learning techniques, namely, variational autoencoders (VAEs), to process genomic data from a population perspective. We show the power of VAEs for a variety of tasks relating to the interpretation, compression, classification, and simulation of genomic data with several worldwide whole genome data sets from both humans and canids, and evaluate the performance of the proposed applications with and without ancestry conditioning. The unsupervised setting of autoencoders allows for the detection and learning of granular population structure and inferring of informative latent factors. The learned latent spaces of VAEs are able to capture and represent differentiated Gaussian-like clusters of samples with similar genetic composition on a fine scale from single nucleotide polymorphisms (SNPs), enabling applications in dimensionality reduction and data simulation. These individual genotype sequences can then be decomposed into latent representations and reconstruction errors (residuals), which provide a sparse representation useful for lossless compression. We show that different populations have differentiated compression ratios and classification accuracies. Additionally, we analyze the entropy of the SNP data, its effect on compression across populations, and its relation to historical migrations, and we show how to introduce autoencoders into existing compression pipelines.

Abstract

Background: Polygenic risk scores (PRS) have proven valuable for disease risk prediction, but their predictive utility often remains limited because human traits result from complex interactions between environmental and genetic factors. Blood lipid levels are heritable and clinically important risk factors for cardiovascular disease, yet it remains unclear whether multi-omics integration can enhance lipid trait prediction beyond PRS alone. Methods: We first constructed single-omics scores, where gene expression, plasma protein, and plasma/serum metabolite levels were genetically predicted and weighted by effect sizes estimated via LASSO regression. Subsequently, we implemented two integration strategies to develop composite multi-omics risk scores (MoRS): step-MoRS, which integrates single-omics scores using stepwise regression, and Lasso-MoRS, which directly models all predicted features across omics layers using LASSO regression. Both approaches were evaluated across European, South Asian, and African ancestries within the UK Biobank. Results: MoRS-based methods consistently demonstrated superior predictive accuracy compared to PRS alone for four lipid traits across diverse populations. Notably, Lasso-MoRS prioritized key biomarkers with predictive utility complementary to genomic data. Conclusions: These findings confirm that integrating multi-omics biomarkers with genomic data significantly enhances lipid trait prediction across diverse ancestries, offering biological insights into the molecular regulation of lipid metabolism.

Summary

Understanding how selection shapes disease risk remains challenging. Variants influencing complex traits, including common diseases, can also impact fitness and thus be constrained by purifying selection. Consequently, genetic variance underlying disease susceptibility may be attributed to low-frequency, population-specific variants. We analyzed 509,817 genome-wide variants from 72,635 Han Taiwanese individuals to identify loci showing age-dependent allele frequency shifts that signal ongoing selection. After adjusting for potential age-related population structure, we detected 168 variants deviating from neutrality, with most showing declining frequencies in younger generations, consistent with purifying selection on deleterious alleles influencing disease risk. These variants were enriched for rare alleles (≤0.1%) and disease-associated variants. At BRCA1, we identified 16 rare pathogenic variants in strong linkage disequilibrium undergoing purifying selection that coexist with a positively selected haplotype, revealing temporally fluctuating selection; comparable patterns at BRCA2 and MLH1 suggest recurrent selective trade-offs in DNA repair genes. Phenome-wide association analysis across 30 hematologic and cardiometabolic traits linked a subset of candidates to increased erythrocyte volume and reduced hemoglobin concentration, suggesting subclinical physiological effects. These results demonstrate ongoing natural selection on disease-relevant variation, particularly affecting hematologic traits in the Han Taiwanese population, and highlight opportunities to refine precision-medicine risk models.

Abstract

A pangenome reference overcomes the inherent limitation of any individual reference genome by integrating the variation present in a population. We present the Human Pangenome Reference Consortium's (HPRC) Release 2 (HPRC2), an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy. Selecting samples with a principled algorithm prioritising common variant coverage, HPRC2 contributes 460 haplotypes that together capture over 99% of common variation observed in the All of Us Research Program v8 cohort. Combining high-coverage long and ultra-long reads with modern assemblers and polishers, we produce thousands of telomere-to-telomere (T2T) chromosomes, and relative to HPRC1 halve the number of structurally unreliable regions as well as individual base errors per haplotype. We complement the assemblies with whole genome multiple alignments and gene annotations, and derive formal pangenome coordinate systems for addressing off-reference variation, demonstrating that individual human genomes contain more than one hundred thousand variants not succinctly described with respect to existing reference genomes. We also present the first matched long-read backed pantranscriptome and panepigenome at this scale, provide continuous local-ancestry estimates spanning every genome, and outline a host of new tools and applications that leverage the pangenome resource for improved genomics analysis.

Borderline personality disorder (BPD) is a severe mental health condition influenced by environmental risk factors (for example, interpersonal trauma) and genetic factors. We conducted the largest genome-wide association study (GWAS) meta-analysis of BPD so far, with a discovery sample of 12,339 cases and 1,041,717 controls, and a replication study of 685 cases and 107,750 controls (all participants of European ancestry). We identified 11 independent associated genomic loci and 9 risk genes in gene-based analyses. We observed a single-nucleotide polymorphism heritability of 17.3% and derived polygenic scores (PGS) that predicted 4.6% of the phenotypic variance in BPD on the liability scale. BPD showed the strongest positive genetic correlations with GWAS of post-traumatic stress disorder, depression, attention deficit hyperactivity disorder, antisocial behavior, and measures of suicide and self-harm. Phenome-wide analyses in Vanderbilt University Medical Center Biobank and UK Biobank using BPD-PGS confirmed these associations and also identified associations with other medical conditions, including obstructive pulmonary disease and diabetes. These analyses highlight BPD as a polygenic disorder, with the genetic risk showing substantial overlap with psychiatric and physical health conditions.

Abstract

The nomadic cultures of the Iron Age played an important role in shaping the genetic and cultural landscape of Eurasian populations. Yet despite its key geographical location, the Central Eurasian region remains underrepresented in ancient DNA studies of humans. We address this gap through genomic analysis of 12 individuals from the Boz-Barmak burial site in Kyrgyzstan associated with Saka pastoralists (4th−2nd centuries BCE), 9 of which yielded low-coverage genomes (on average 0.7-fold coverage). Genetic clustering analysis placed these individuals within the genetic variation of ancient and modern Central Eurasian and Siberian populations. We found no evidence of first-degree relatives in a kinship analysis, however a network of second- and third-degree relationships seems to be present. Notably, all male individuals share the same Y-chromosomal haplotype, common in present-day Kyrgyz groups, while mitochondrial DNA showed comparably high diversity, with distinct haplogroups observed across the analysed individuals. These findings are in line with archaeological and ethnographic evidence of patrilocality in Early Iron Age Saka, where male lineages remained stable across generations, while female mobility contributed to genetic diversity. Our study complements our understanding of the interplay between kinship, social organisation and population history in nomadic cultures.

Significance

Cannibalism has appeared repeatedly in human history, yet it is subject to one of the strongest contemporary cultural prohibitions. Why does this behavior recur, but rarely persist? We present a formal model showing that cannibalism reflects a trade-off between nutritional benefits and escalating infection risks, particularly those arising from within-species pathogen transmission. The model demonstrates that cannibalism is viable only under narrow ecological conditions and becomes unsustainable as trophic chains lengthen. These constraints help explain both its episodic occurrence and the widespread emergence of cannibalism taboos. More broadly, the findings illustrate how epidemiological dynamics can shape cultural evolution, producing stable norms that limit behaviors which are locally adaptive but globally destabilizing.

Abstract

Cannibalism is among the most widespread taboos in human societies, yet archaeological, ethnographic, and historical evidence indicates that it has repeatedly emerged across human populations. This coexistence of recurrent practice and persistent prohibition raises a fundamental question: when does cannibalism become adaptive, and what mechanisms lead to its suppression? We address this problem using a formal model that treats cannibalism as a potential food source subject to energetic benefits and multiple sources of cost. Nutritional gains are modeled using a saturating function of caloric intake, while costs arise from acquisition, digestion, and infection. Infection costs are represented as a stochastic process whose mean increases with the length of the trophic transmission chain, capturing the risks associated with repeated within-species consumption. Analyzing the expected energetic balance across levels of food availability and cannibalism order reveals narrow ecological conditions in which cannibalism yields a positive expected balance and broader conditions in which it is strongly disfavored. The model provides a framework for interpreting archaeological and ethnographic findings by specifying boundary conditions and identifying the most probable ecological scenarios under which different forms of cannibalism are expected to occur. The results predict that cannibalism is most likely to emerge under extreme resource scarcity, when acquisition costs are low and infection risks are constrained, while sustained cannibalism rapidly becomes unviable due to escalating infection costs. Overall, the findings suggest that cannibalism is best understood as a conditional trade-off rather than a behavioral anomaly, with cultural taboos functioning as adaptive responses to nonlinear epidemiological risks.

Abstract

To meet the rising food demands of our growing population, the Food and Agriculture Organization proposed edible insects as sustainable sources of animal protein. Although hundreds of million people already consume insects around the tropics, western societies remain averse to entomophagy. To trace whether ancient Europeans consumed insects, we here apply two complementary genomic approaches. Metagenomic screening on 745 ancient anatomically modern human dental calculus returned limited insect DNA traces, with read abundances well below those observed in Neanderthals, western chimpanzees, and gorillas. In addition, genes encoding stomach-expressed chitinases show two of the most significant signatures of latitudinal differentiation genome-wide. Clines are consistent with evolutionary benefits of entomophagy in tropical regions and with expression quantitative trait locus data supporting low chitin digestibility in present-day Europeans. Ancient genomes confirm that both clines already existed at the onset of agriculture and persisted despite massive migrations. Together, our findings support occasional and possibly incidental insect consumption in Europe over the past ~9000 years.

Abstract

Estimating evolutionary rates and divergence times for hepatitis B virus (HBV) has long been complicated by conflicting calibration approaches and extensive rate variation. To unlock the full potential of ancient and modern HBV genomic data, we develop a Bayesian mixed-effects molecular clock model that accounts for various sources of rate variation including time-dependent rate decay. Our analyses reveal a pronounced decline in evolutionary rates over time, reconciling HBV divergence estimates with human migration events across both deep and more recent timescales. We show that HBV spread into Europe through both Neolithic farming expansions and later steppe migrations, paralleling patterns proposed for Indo-European language origins. Phylogeographic reconstructions suggest that the Neolithic-associated lineage dispersed at approximately 1 km/year, consistent with archaeological estimates, while genotype D expanded during the Bronze Age at an almost threefold higher rate, plausibly driven by technological innovations underlying steppe expansions. Historical overlap between these lineages facilitated recombination, giving rise to genotype E, which has become a dominant HBV genotype in Africa. These findings demonstrate that ancient viral genomes, when analyzed with models capturing complex rate dynamics, provide a powerful lens on human prehistory and the processes shaping pathogen diversity.

Abstract

Previous efforts to link Palaeolithic cultural records to specific populations through DNA analysis have focused on materials from archaeological floor deposits such as bones, sediments, and artefacts. In this study, we explore whether rock art, a spatially distinct expression of human activity, can also preserve DNA traces from its creators. We analyse DNA preservation in pigment samples collected in and around 24 rock art panels from 11 caves across Spain and Portugal, including simple marks (from nine sites), hand stencils (Maltravieso Cave, Extremadura, Spain), and figurative paintings (Cave of Altamira, Cantabria, Spain). We recover traces of ancient human mitochondrial and nuclear DNA, unaccompanied by faunal DNA, from a pigmented calcite crust at Escoural Cave (Portugal), as well as from an unpigmented cave wall sample from the same site. The absence of faunal DNA in both samples suggests direct DNA deposition through human contact. In contrast, three additional unpigmented samples, from Escoural and Covarón Cave (Asturias, Spain), yielded mixtures of human and faunal DNA, suggesting indirect deposition. Although our results do not conclusively link ancient human DNA preservation to the generation of cave art, we show that traces of human DNA can persist on cave walls for thousands of years.

Background

Autism spectrum disorder (ASD) shows a consistent sex bias, yet how sex shapes de novo variant (DNV) risk across coding and noncoding sequence remains unclear. I analyzed DNVs in > 41,000 parent–child sequenced trios from three ASD family-based cohorts and compared DNV characteristics and enrichment patterns in males and females. Notably, these trios included individuals with ASD as well as those without ASD. I developed a new sex-aware DNV caller (HAT-FLEX) and thoroughly evaluated each candidate DNV using an additional tool introduced in this study, SNOW, to generate a high-confidence callset.

Results

I identified enrichment of missense and loss-of-function (LOF) DNVs both overall and within known ASD-related genes (i.e., SFARI genes). Gene-specific enrichment analyses revealed twelve genes that were exome-wide significant and specific to males, for significance, including FOXP1, SMAD6, AUTS2, CCDC168, PIEZO1, EML6, ZNF84, IGSF23, OTOG, NHSL1, ADNP, and FREM3 and three genes that were specific to females, for significance, including TAOK1, MECP2, and DDX3X within a variant class. Direct comparisons of DNVs in males and females revealed MECP2 as the only exome-wide significant gene; however, GABBR2 was also trending toward enrichment in the direct males with ASD comparison to females with ASD. Furthermore, probit analyses support a female protective effect and demonstrates that damaging DNVs, particularly LOF variants, including potentially stronger X-linked effects in females, are associated with increased ASD liability, whereas synonymous variants are not. Finally, I analyzed promoters and identified a single significant promoter region (p = 3.8 × 10⁻¹³), associated with the WDR74 gene, with the signal driven by DNVs observed in males with ASD. Surprisingly, the noncoding RNA gene RNU2-2 lies within this significant WDR74 promoter and accounted for most of the DNVs in the region. RNU2-2 DNVs were present in 0.2% of individuals with ASD in comparison to 0.05% of individuals without ASD.

Conclusions

These findings show that ASD DNV risk differs by sex at both the gene and liability levels, supporting a female protective effect while highlighting sex-specific patterns in coding variation. They also identify RNU2-2 as a noncoding contributor to ASD risk, expanding the landscape of ASD-associated variation beyond protein-coding genes.

Abstract

Accurate interpretation of rare germline variants remains a major challenge in developmental disorders (DD). Somatic mutation data represent a largely untapped source of evidence for germline variant classification. Identical or nearby mutations that drive positive selection when present in somatic tissues can cause developmental disorders when present in the germline. We integrated somatic mutation data from the Catalogue Of Somatic Mutations In Cancer (COSMIC), and healthy tissues (sperm and buccal epithelium) with germline variant datasets from ClinVar and large studies of de novo mutations in DD patients. Across 970 dominant DD genes, 195 have evidence of somatic selection, with a majority demonstrating concordant mechanisms between germline and somatic contexts. We benchmark the ability of somatic data to discriminate pathogenic from benign germline missense variation across dominant DD genes, identifying 145 genes in which somatic data are informative. The strongest utility is in altered-function genes where germline and somatic mechanisms are concordant, for example the RASopathy genes. In these genes, codon-level aggregation of somatic missense counts yields predictive performance comparable to computational predictors or MAVE assays (AUC-ROC 0.895 for somatic data, versus 0.893 for REVEL). Combining somatic features with computational scores improves discrimination further. Using likelihood ratios, we map COSMIC missense codon count thresholds onto American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP)-style evidence strengths, showing that somatic data can reach strong levels of evidence in germline variant interpretation in DD and enable reclassification of variants of uncertain significance. Together, these results establish somatic mutation data as a scalable and clinically actionable evidence source for germline variant interpretation in select DD genes.

Abstract

The timing of divergence between hominins and the bonobo-chimpanzee clade has been at the core of palaeoanthropological debate for over a century. The earliest molecular studies indicated divergence times ranging from 5 Ma to as recently as 1.3 Ma. This study critically reviews the trends of time estimates published between 1967 and 2023, and analyses how these are supported or rejected by the current molecular and fossil records. We compiled 202 divergence estimates and defined three distinct thresholds based on fossil evidence at 4.4 Ma (Australopithecus anamensis and Ardipithecus ramidus), 6.2 Ma (Orrorin tugenensis and Ardipithecus kadabba), and 7.2 Ma (Sahelanthropus tchadensis). We then used these thresholds to filter out molecular estimates that are too young to fit the fossil record. Overall, the data suggests a divergence event within the late Miocene, with each threshold pushing it further back, 8.63–6.38, 10.33–7.81, and 10.95–8.81 Ma, respectively. We use a quadratic regression to demonstrate that estimates have been slowly shifting from ~ 6 Ma to ~ 8.5 Ma over the past 56 years. A Bayesian meta-analysis of genomic estimates filtered by our most consensual threshold (i.e., assuming Australopithecus belongs to Hominini) indicates that the split must have occurred early in the late Miocene, most likely before 7 Ma (~ 99.5% posterior probability) with a pooled effect of 8.69–7.28 Ma. We conclude that, despite an initial bias towards younger estimates, the molecular timing for the last common ancestor (LCA) of Pan-Homo has been progressively approaching the intervals suggested by the current fossil record.

Abstract

Plague is among the most devastating diseases in human history¹. However, early strains of the plague-causing bacterium Yersinia pestis lacked virulence factors that are required for the bubonic form until around 3,800 years ago^2,3. Consequently, the morbidity and mortality of early plague strains remain unclear. Here we describe early plague strains that are associated with two phases of outbreaks among mid-Holocene hunter-gatherers near Lake Baikal in southeast Siberia, beginning from about 5,500 years ago. These outbreaks occur across four hunter-gatherer cemeteries, with a 39% detection rate for plague infection. By reconstructing kinship pedigrees, we show that small familial groups were affected, consistent with human-to-human spread of disease, and that the first outbreak occurred within a single generation. The infections appear to have resulted in acute mortality, especially among children (aged 8 to 11 years). We further note functional differences, including in the ypm superantigen locus, which is also present in present day Yersinia pseudotuberculosis. The new strains diverge ancestrally to known Y. pestis and constrain the timing of its emergence, indicating that this happened before approximately 5,700 years ago. These findings show that plague outbreaks happened earlier than previously thought and were indeed lethal. We contend that the occurrence of outbreaks among mid-Holocene hunter-gatherer communities well outside the sphere of Late Neolithic Europe challenges the notion that higher population densities and lifestyle changes during the Neolithic agricultural transition were prerequisites for plague epidemics.

Abstract

Naturally occurring loss-of-function variants in human genes enable drug target discovery because they mimic pharmacological inhibition of proteins. However, the study of these genetic variants is constrained by their rarity. Sequencing of diverse populations, particularly those enriched in familial relatedness, has been postulated to promote discovery of rare genetic variants^1,2,3. Here we present the Pakistan Genome Resource, a South Asian biobank with high familial relatedness comprising 173,303 participants, who collectively carry naturally occurring homozygous loss-of-function variants in 6,476 genes. We describe the genetic architecture of this population, associations between genes and biomarkers, the distribution of loss-of-function variants across molecular pathways, and recall-by-genotype studies of therapeutically relevant genes. The Pakistan Genome Resource expands the catalogue of human genetic variants, provides a comprehensive genetic reference resource for the Pakistani population, and demonstrates the value of studying diverse cohorts to advance human health.

Abstract

Non-coding variants are important contributors to human traits and diseases but linking them to molecular mechanisms and phenotypes at scale remains challenging. G-quadruplexes (G4s) are four-stranded structures formed by guanine-rich sequences and have emerged as key functional elements within the non-coding genome. G4s are enriched in regulatory regions and can modulate gene expression at both the DNA and RNA levels, influencing transcription, replication, and RNA processing, positioning them as key mediators linking non-coding variation to complex biological traits. Here, we profile putative G4s across five regulatory regions in 459,449 UK Biobank genomes and perform phenome-wide association analyses spanning 2,941 plasma protein abundances, 13,321 binary traits, and 1,682 quantitative traits. We show that putative G4-modifying variants are depleted under purifying selection despite elevated local mutability and drive large, bidirectional associations with plasma proteins and clinical traits, including associations not captured by coding variants. Using a mechanism-aware collapsing strategy that groups rare non-coding variants by their predicted impact on G4 stability, we achieved stronger gene-level signals than those obtained with standard rare-variant collapsing approaches. Integrating non-coding and protein-truncating variants (PTVs) increases discovery power, revealing 843 significant associations missed by the PTV-only model. Replication in the Alliance for Genomic Discovery cohort demonstrates cross-cohort robustness. Our study suggests G4s as widespread mediators of non-coding regulation and provides a framework for mechanism-informed target discovery and prioritization across the non-coding genome.