The second plague pandemic (early 14th-early 19th centuries), which was caused by Yersinia pestis, had a profound demographic, socio-economic and cultural impact across Eurasia and North Africa. Many regions in Europe and the Middle East are estimated to have lost 40-60% of their human populations, with some areas suffering even higher mortality. Whether exposure to Y. pestis drove strong positive selection on protective genetic variants in the human genome, and how it shaped migration patterns, remains debated, despite several recent studies based on ancient DNA. Here, we analyse a markedly larger, higher coverage, and geographically diverse dataset based on shotgun sequencing of genomes from 529 ancient individuals to a mean depth 8.8x dating to either before or after the arrival of the pandemic at three sites in northern Europe: Trondheim (Norway), Lund (Sweden) and Vilnius (Lithuania). Genome-wide scans for signatures of selection provide no evidence for strong positive selection acting on specific genetic variants driven by Y. pestis exposure: we neither replicate selection signatures reported by previous studies nor identify new genome-wide significant candidates. However, for all three sites, we observe evidence for a reduction in long-range immigration, indicated by a drop in the diversity of ancestry that followed the arrival of Y. pestis and broadly coincided with the end of the Viking Age, Christianisation and the onset of the Little Ice Age. Our results shed important light on the demographic impact of major sociohistorical changes that occurred during the late Medieval period in Scandinavia and the Baltic region and link Christianisation to increased diversity in ancestry before the pandemic.

The giant forest hog (GFH; Hylochoerus meinertzhageni), the largest and most elusive wild pig, is found in a disjunct range across tropical Africa, from Guinea to the Ethiopian highlands. The GFH has three morphologically defined subspecies. Here, we present the first whole-genome data for nine samples from Guinea and Uganda, its two most geographically distant subspecies. We identify the GFH as sister to warthogs among African suids, diverging around 4.6 Mya, with the two GFH populations splitting between 1.7 and 0.5 Mya and following distinct demographic trajectories. The deep evolutionary split is confirmed by species-level genetic differentiation and the lowest heterozygosity level in the Guinean population compared with all the African suids, likely reflecting long-term low effective population size and isolation. Our findings have implications for understanding the habitat-change consequences in African rainforests and reveal a deep evolutionary divergence within the GFH with potential conservation relevance.

Polygenic risk scores (PRS) hold prognostic value for identifying individuals at higher risk of type 2 diabetes (T2D). However, further characterization is needed to understand the generalizability of T2D PRS in diverse populations across various contexts. We characterized a multi-ancestry T2D PRS among 244,637 cases and 637,891 controls across eight populations from the Population Architecture Genomics and Epidemiology (PAGE) Study and 13 additional biobanks and cohorts. PRS performance was context dependent, with better performance in those who were younger, male, with a family history of T2D, without hypertension, and not obese or overweight. Additionally, the PRS was associated with various diabetes-related cardiometabolic traits and T2D complications, suggesting its utility for stratifying risk of complications and identifying shared genetic architecture between T2D and other diseases. These findings highlight the need to account for context when evaluating PRS as a tool for T2D risk prognostication and potentially generalizable associations of T2D PRS with diabetes-related traits despite differential performance in T2D prediction across diverse populations.

Circulating proteins play essential roles in complex diseases, yet protein quantitative trait locus (pQTL) studies in non-European, isolated populations remain limited. We analyzed genotypes and plasma proteomics data (Olink Target 96 Inflammation and Cardiovascular II panels) from 3,707 Greenlandic individuals (mean age: 47.9 years; 54.5% female), using linear mixed models to account for relatedness and population structure. Among 177 proteins, we identified 251 primary pQTLs—235 additive (84 cis, 8 semi-cis, 12 semi-trans, and 131 trans) and 16 recessive (1 cis, 2 semi-trans, and 13 trans)—48 secondary pQTLs, and 70 (28%) novel associations. Several common pQTLs in Greenlanders explained a substantial proportion of variance in protein levels (>30% for interleukin [IL]-27, IgG Fc receptor II-b, IL-16, and Galectin-9) compared to Europeans. A novel cis pQTL for IL-6 (rs7802307) was associated with increased cardiovascular disease risk based on registry data. Associations between Arctic-enriched variants in CPT1A (rs80356779), HNF1A (rs2135845768), TBC1D4 (rs61736969), LDLR (rs730882082), and PCSK9 (rs4609471) and altered protein abundance provide mechanistic insights into cardiometabolic disease in this population. These findings underscore the importance of pQTL studies in genetically diverse populations.

Greenlandic Inuit and other indigenous populations are underrepresented in genetic research1,2, leading to inequity in healthcare opportunities. To address this, we performed analyses of sequenced or imputed genomes of 5,996 Greenlanders with extensive phenotypes. We quantified their historical population bottleneck and how it has shaped their genetic architecture to have fewer, but more common, variable sites. Consequently, we find twice as many high-impact genome-wide associations to metabolic traits in Greenland compared with Europe. We infer that the high-impact variants arose after the population split from Native Americans and thus are Arctic-specific, and show that some of them are common due to not only genetic drift but also selection. We also find that European-derived polygenic scores for metabolic traits are only half as accurate in Greenlanders as in Europeans, and that adding Arctic-specific variants improves the overall accuracy to the same level as in Europeans. Similarly, lack of representation in public genetic databases makes genetic clinical screening harder in Greenlandic Inuit, but inclusion of Greenlandic data remedies this by reducing the number of non-causal candidate variants by sixfold. Finally, we identify pronounced genetic fine structure that explains differences in prevalence of monogenic diseases in Greenland and, together with recent changes in mobility, leads to a predicted future reduction in risk for certain recessive diseases. These results illustrate how including data from Greenlanders can greatly reduce inequity in genomic-based healthcare.

Polygenic risk scores hold prognostic value for identifying individuals at higher risk of type 2 diabetes. However, further characterization is needed to understand the generalizability of type 2 diabetes polygenic risk scores in diverse populations across various contexts. We systematically characterize a multi-ancestry type 2 diabetes polygenic risk score among 244,637 cases and 637,891 controls across diverse populations from the Population Architecture Genomics and Epidemiology Study and 13 additional biobanks and cohorts. Polygenic risk score performance is context dependent, with better performance in those who are younger, male, without hypertension, and not obese or overweight. Additionally, the polygenic risk score is associated with various diabetes-related cardiometabolic traits and type 2 diabetes complications, suggesting its utility for stratifying risk of complications and identifying shared genetic architecture between type 2 diabetes and other diseases. These findings highlight the need to account for context when evaluating polygenic risk score as a tool for type 2 diabetes risk prognostication and the potentially generalizable associations of type 2 diabetes polygenic risk score with diabetes-related traits, despite differential performance in type 2 diabetes prediction across diverse populations. Our study provides a comprehensive resource to characterize a type 2 diabetes polygenic risk score.

The saola is one of the most elusive large mammals, standing at the brink of extinction. We constructed a reference genome and resequenced 26 saola individuals, confirming the saola as a basal member of the Bovini. Despite its small geographic range, we found that the saola is partitioned into two populations with high genetic differentiation (FST = 0.49). We estimate that these populations diverged and started declining 5,000-20,000 years ago, possibly due to climate changes and exacerbated by increasing human activities. The saola has long tracts without genomic diversity; however, most of these tracts are not shared by the two populations. Saolas carry a high genetic load, yet their gradual decline resulted in the purging of the most deleterious genetic variation. Finally, we find that combining the two populations, e.g., in an eventual captive breeding program, would mitigate the genetic load and increase the odds of species survival.

Objectives: Population studies have identified common genetic variants contributing substantially to the burden of diabetes in Greenland. However, the handling of suspected monogenic diabetes in diabetes clinics in Greenland has not been described. In this study we aimed to describe the referral rate, prevalence, and genetic causes of clinically identified monogenic diabetes in Greenland. Methods: All diabetes patients in Greenland referred for genetic testing due to suspected monogenic diabetes between 2014 and July 2022 were tallied. Targeted short-read sequencing and Sanger sequencing of probands and their family members were used to screen for potentially deleterious variants in the maturity-onset diabetes of the young (MODY) genes GCK, HNF1A, HNF1B, and HNF4A. Clinical data were extracted from the electronic medical records, and whole-genome sequencing was performed for families with potentially deleterious variants for genetic ancestry analysis. Results: Between 2014 and July 2022, 58 probands were referred for genetic testing, equivalent to 0.1% of the population. Five variants were identified: GCK p.F133L, GCK p.D205E, HNF1A c.1108G>T, HNF1B p.Q182*, and HNF4A -178A>G. These variants were found in 11 probands and 19 family members, equivalent to a population prevalence of monogenic diabetes of 0.05%. Local ancestry analysis revealed that all the variants were found exclusively in Inuit haplotypes, despite all individuals being admixed with both Inuit and European genetic ancestry. Conclusions: The rate of referral and prevalence of monogenic diabetes is substantially higher in Greenland than in other populations, and both rare and more common population-specific variants of (c) 2025 The Author(s). Published on behalf of the Canadian Diabetes Association. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Throughout history, populations across species have been decimated by epidemic outbreaks. Recent studies have raised the enticing idea that such outbreaks have led to strong natural selection acting on disease-protective genetic variants in the host population. However, so far few, if any, clear examples of such selection exist. This could be because previous studies were underpowered to detect the type of selection an outbreak must induce: extremely short-term selection on standing variation. Here we present a simulation-based framework that allows users to explore under what circumstances selection scan methods like FST have power to detect epidemic-driven selection on a variant. Using two examples, we illustrate how the framework can be used. The examples also show that comparing those who died from an outbreak to survivors has the potential to render higher power than more commonly used sampling schemes. And importantly, they show that even for severe outbreaks, like the Black Death (≈50% mortality), selection may have led to only a modest increase in allele frequency, suggesting large sample sizes are required to obtain appropriate power. We hope this framework can help in designing well-powered future studies and thus help clarify the evolutionary role epidemic-driven selection has played in different species.

The combination of decreasing food intake and increasing energy expenditure represents a powerful strategy for counteracting cardiometabolic diseases such as obesity and type 2 diabetes1. Yet current pharmacological approaches require conjugation of multiple receptor agonists to achieve both effects2-4, and so far, no safe energy-expending option has reached the clinic. Here we show that activation of neurokinin 2 receptor (NK2R) is sufficient to suppress appetite centrally and increase energy expenditure peripherally. We focused on NK2R after revealing its genetic links to obesity and glucose control. However, therapeutically exploiting NK2R signalling has previously been unattainable because its endogenous ligand, neurokinin A, is short-lived and lacks receptor specificity5,6. Therefore, we developed selective, long-acting NK2R agonists with potential for once-weekly administration in humans. In mice, these agonists elicit weight loss by inducing energy expenditure and non-aversive appetite suppression that circumvents canonical leptin signalling. Additionally, a hyperinsulinaemic-euglycaemic clamp reveals that NK2R agonism acutely enhances insulin sensitization. In diabetic, obese macaques, NK2R activation significantly decreases body weight, blood glucose, triglycerides and cholesterol, and ameliorates insulin resistance. These findings identify a single receptor target that leverages both energy-expending and appetite-suppressing programmes to improve energy homeostasis and reverse cardiometabolic dysfunction across species.

African antelope diversity is a globally unique vestige of a much richer world-wide Pleistocene megafauna. Despite this, the evolutionary processes leading to the prolific radiation of African antelopes are not well understood. Here, we sequenced 145 whole genomes from both subspecies of the waterbuck (Kobus ellipsiprymnus), an African antelope believed to be in the process of speciation. We investigated genetic structure and population divergence and found evidence of a mid-Pleistocene separation on either side of the eastern Great Rift Valley, consistent with vicariance caused by a rain shadow along the so-called ‘Kingdon’s Line’. However, we also found pervasive evidence of both recent and widespread historical gene flow across the Rift Valley barrier. By inferring the genome-wide landscape of variation among subspecies, we found 14 genomic regions of elevated differentiation, including a locus that may be related to each subspecies’ distinctive coat pigmentation pattern. We investigated these regions as candidate speciation islands. However, we observed no significant reduction in gene flow in these regions, nor any indications of selection against hybrids. Altogether, these results suggest a pattern whereby climatically driven vicariance is the most important process driving the African antelope radiation, and suggest that reproductive isolation may not set in until very late in the divergence process. This has a significant impact on taxonomic inference, as many taxa will be in a gray area of ambiguous systematic status, possibly explaining why it has been hard to achieve consensus regarding the species status of many African antelopes. Our analyses demonstrate how population genetics based on low-depth whole genome sequencing can provide new insights that can help resolve how far lineages have gone along the path to speciation

Background Disease prevalence and mean phenotype values differ between many populations, including Inuit and Europeans. Whether these differences are partly explained by genetic differences or solely due to differences in environmental exposures is still unknown, because estimates of the genetic contribution to these means, which we will here refer to as mean genotypic values, are easily confounded, and because studies across genetically diverse populations are lacking.Methods Leveraging the unique genetic properties of the small, admixed and historically isolated Greenlandic population, we estimated the differences in mean genotypic value between Inuit and European genetic ancestry using an admixed sibling design. Analyses were performed across 26 metabolic phenotypes, in 1474 admixed sibling pairs present in a cohort of 5996 Greenlanders.Results After FDR correction for multiple testing, we found significantly lower mean genotypic values in Inuit genetic ancestry compared to European genetic ancestry for body weight (effect size per percentage of Inuit genetic ancestry (se), -0.51 (0.16) kg/%), body mass index (-0.20 (0.06) kg/m2/%), fat percentage (-0.38 (0.13) %/%), waist circumference (-0.42 (0.16) cm/%), hip circumference (-0.38 (0.11) cm/%) and fasting serum insulin levels (-1.07 (0.51) pmol/l/%). The direction of the effects was consistent with the observed mean phenotype differences between Inuit and European genetic ancestry. No difference in mean genotypic value was observed for height, markers of glucose homeostasis, or circulating lipid levels.Conclusions We show that mean genotypic values for some metabolic phenotypes differ between two human populations using a method not easily confounded by possible differences in environmental exposures. Our study illustrates the importance of performing genetic studies in diverse populations.

The blue wildebeest (Connochaetes taurinus) is a keystone species in savanna ecosystems from southern to eastern Africa, and is well known for its spectacular migrations and locally extreme abundance. In contrast, the black wildebeest (C. gnou) is endemic to southern Africa, barely escaped extinction in the 1900s and is feared to be in danger of genetic swamping from the blue wildebeest. Despite the ecological importance of the wildebeest, there is a lack of understanding of how its unique migratory ecology has affected its gene flow, genetic structure and phylogeography. Here, we analyze whole genomes from 121 blue and 22 black wildebeest across the genus' range. We find discrete genetic structure consistent with the morphologically defined subspecies. Unexpectedly, our analyses reveal no signs of recent interspecific admixture, but rather a late Pleistocene introgression of black wildebeest into the southern blue wildebeest populations. Finally, we find that migratory blue wildebeest populations exhibit a combination of long-range panmixia, higher genetic diversity and lower inbreeding levels compared to neighboring populations whose migration has recently been disrupted. These findings provide crucial insights into the evolutionary history of the wildebeest, and tangible genetic evidence for the negative effects of anthropogenic activities on highly migratory ungulates. The evolutionary genetics of a keystone savannah species the blue wildebeest, and the related black wildebeest, remain largely unexplored. This study finds evidence for archaic introgression of black wildebeest to blue wildebeest and detrimental effects of human activities on migratory populations.

Impalas are unusual among bovids because they have remained morphologically similar over millions of years-a phenomenon referred to as evolutionary stasis. Here, we sequenced 119 whole genomes from the two extant subspecies of impala, the common (Aepyceros melampus melampus) and black-faced (A. m. petersi) impala. We investigated the evolutionary forces working within the species to explore how they might be associated with its evolutionary stasis as a taxon. Despite being one of the most abundant bovid species, we found low genetic diversity overall, and a phylogeographic signal of spatial expansion from southern to eastern Africa. Contrary to expectations under a scenario of evolutionary stasis, we found pronounced genetic structure between and within the two subspecies with indications of ancient, but not recent, gene flow. Black-faced impala and eastern African common impala populations had more runs of homozygosity than common impala in southern Africa, and, using a proxy for genetic load, we found that natural selection is working less efficiently in these populations compared to the southern African populations. Together with the fossil record, our results are consistent with a fixed-optimum model of evolutionary stasis, in which impalas in the southern African core of the range are able to stay near their evolutionary fitness optimum as a generalist ecotone species, whereas eastern African impalas may struggle to do so due to the effects of genetic drift and reduced adaptation to the local habitat, leading to recurrent local extinction in eastern Africa and re-colonisation from the South.

Strong genetic structure has prompted discussion regarding giraffe taxonomy,1,2,3 including a suggestion to split the giraffe into four species: Northern (Giraffa c. camelopardalis), Reticulated (G. c. reticulata), Masai (G. c. tippelskirchi), and Southern giraffes (G. c. giraffa).4,5,6 However, their evolutionary history is not yet fully resolved, as previous studies used a simple bifurcating model and did not explore the presence or extent of gene flow between lineages. We therefore inferred a model that incorporates various evolutionary processes to assess the drivers of contemporary giraffe diversity. We analyzed whole-genome sequencing data from 90 wild giraffes from 29 localities across their current distribution. The most basal divergence was dated to 280 kya. Genetic differentiation, FST, among major lineages ranged between 0.28 and 0.62, and we found significant levels of ancient gene flow between them. In particular, several analyses suggested that the Reticulated lineage evolved through admixture, with almost equal contribution from the Northern lineage and an ancestral lineage related to Masai and Southern giraffes. These new results highlight a scenario of strong differentiation despite gene flow, providing further context for the interpretation of giraffe diversity and the process of speciation in general. They also illustrate that conservation measures need to target various lineages and sublineages and that separate management strategies are needed to conserve giraffe diversity effectively. Given local extinctions and recent dramatic declines in many giraffe populations, this improved understanding of giraffe evolutionary history is relevant for conservation interventions, including reintroductions and reinforcements of existing populations.

Encompassing regions that were amongst the first inhabited by humans following the out-of-Africa expansion, hosting populations with the highest levels of archaic hominid introgression, and including Pacific islands that are the most isolated inhabited locations on the planet, Oceania has a rich, but understudied, human genomic landscape. Here we describe the first region-wide analysis of genome-wide data from population groups spanning Oceania and its surroundings, from island and peninsular southeast Asia to Papua New Guinea, east across the Pacific through Melanesia, Micronesia, and Polynesia, and west across the Indian Ocean to related island populations in the Andamans and Madagascar. In total we generate and analyze genome-wide data from 981 individuals from 92 different populations, 58 separate islands, and 30 countries, representing the most expansive study of Pacific genetics to date. In each sample we disentangle the Papuan and more recent Austronesian ancestries, which have admixed in various proportions across this region, using ancestry-specific analyses, and characterize the distinct patterns of settlement, migration, and archaic introgression separately in these two ancestries. We also focus on the patterns of clinically relevant genetic variation across Oceania--a landscape rippled with strong founder effects and island-specific genetic drift in allele frequencies--providing an atlas for the development of precision genetic health strategies in this understudied region of the world.

Populations of the Eastern Highlands of Papua New Guinea (EHPNG, area 11,157 km2) lived in relative isolation from the rest of the world until the mid-20th century, and the region contains a wealth of linguistic and cultural diversity. Notably, several populations of EHPNG were devastated by an epidemic prion disease, kuru, which at its peak in the mid-twentieth century led to some villages being almost depleted of adult women. Until now, population genetic analyses to learn about genetic diversity, migration, admixture, and the impact of the kuru epidemic have been restricted to a small number of variants or samples. Here, we present a population genetic analysis of the region based on genome-wide genotype data of 943 individuals from 21 linguistic groups and 68 villages in EHPNG, including 34 villages in the South Fore linguistic group, the group most affected by kuru. We find a striking degree of genetic population structure in the relatively small region (average FST between linguistic groups 0.024). The genetic population structure correlates well with linguistic grouping, with some noticeable exceptions that reflect the clan system of community organization that has historically existed in EHPNG. We also detect the presence of migrant individuals within the EHPNG region and observe a significant excess of females among migrants compared to among non-migrants in areas of high kuru exposure (p = 0.0145, chi-squared test). This likely reflects the continued practice of patrilocality despite documented fears and strains placed on communities as a result of kuru and its associated skew in female incidence.

Throughout history, populations from numerous species have been decimated by epidemic outbreaks, like the 19th-century rinderpest outbreak in Cape buffalo ( ≈ 90% mortality) and Black Death in humans ( ≈ 50% mortality). Recent studies have raised the enticing idea that such epidemic outbreaks have led to strong natural selection acting on disease-protective variants in the host populations. However, so far there are few, if any, clear examples of such selection having taken place. This could be because so far studies have not had sufficient power to detect the type of selection an epidemic outbreak must induce: strong but extremely short-term selection on standing variation. We present here a simulation-framework that allows users to explore under what circumstances it is possible to detect epidemic-driven selection using standard selection scan methods like FST and iHS. Using two examples, we illustrate how the framework can be used. Furthermore, via these examples, we show that comparing survivors to the dead has the potential to render higher power than more commonly used sampling schemes. And importantly, we show that even for outbreaks with high mortality, like the Black Death, strong selection may have led to only modest shifts in allele frequency, suggesting large sample sizes are required to obtain appropriate power to detect the selection. We hope this framework can help in designing well-powered future studies and thus lead to a clarification of the role epidemic-driven selection has played in the evolution of different species. Significance Statement Our study introduces a simulation-based framework, SimOutbreakSelection (SOS), which enables researchers to design studies that have power to detect epidemic-driven selection while taking sampling time points and demographic history into account. We use rinderpest in African Buffalo and the Black Death in Medieval Sweden as examples to showcase the framework. Via these examples we also show that large sample sizes are needed even for severe epidemics like the Black Death and that the often used sampling strategy where samples from before the epidemic and samples from after are compared is not always optimal. ### Competing Interest Statement The authors have declared no competing interest.

Several African mammals exhibit a phylogeographic pattern where closely related taxa are split between West/Central and East/Southern Africa, but their evolutionary relationships and histories remain controversial. Bushpigs ( Potamochoerus larvatus ) and red river hogs ( P. porcus ) are recognised as separate species due to morphological distinctions, a perceived lack of interbreeding at contact, and putatively old divergence times, but historically, they were considered conspecific. Moreover, the presence of Malagasy bushpigs as the sole large terrestrial mammal shared with the African mainland raises intriguing questions about its origin and arrival in Madagascar. Analyses of 67 whole genomes revealed a genetic continuum between the two species, with putative signatures of historical gene flow, variable F ST values, and a recent divergence time (<500,000 years). Thus, our study challenges key arguments for splitting Potamochoerus into two species and suggests their speciation might be incomplete. Our findings also indicate that Malagasy bushpigs diverged from southern African populations and underwent a limited bottleneck 1000-5000 years ago, concurrent with human arrival in Madagascar. These results shed light on the evolutionary history of an iconic and widespread African mammal and provide insight into the longstanding biogeographic puzzle surrounding the bushpig’s presence in Madagascar.