Beluga whales play a critical role in the subsistence economies and cultural heritage of Indigenous communities across the Arctic, yet the effects of Indigenous hunting on beluga whales remain unknown. Here, we integrate paleogenomics, genetic simulations, and stable δ13C and δ15N isotope analysis to investigate 700 y of beluga subsistence hunting in the Mackenzie Delta area of northwestern Canada. Genetic identification of the zooarchaeological remains, which is based on radiocarbon dating, span three time periods (1290 to 1440 CE; 1450 to 1650 CE; 1800 to 1870 CE), indicates shifts across time in the sex ratio of the harvested belugas. The equal number of females and males harvested in 1450 to 1650 CE versus more males harvested in the two other time periods may reflect changes in hunting practices or temporal shifts in beluga availability. We find temporal shifts and sex-based differences in δ13C of the harvested belugas across time, suggesting historical adaptability in the foraging ecology of the whales. We uncovered distinct mitochondrial diversity unique to the Mackenzie Delta belugas, but found no changes in nuclear genomic diversity nor any substructuring across time. Our findings indicate the genomic stability and continuity of the Mackenzie Delta beluga population across the 700 y surveyed, indicating the impact of Inuvialuit subsistence harvests on the genetic diversity of contemporary beluga individuals has been negligible.

Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation remains an open question. We evaluated the performance and behavior of two commonly used methods, qpAdm and the f3-statistic, on admixture inference under a diversity of demographic models and data conditions. We performed two complementary simulation approaches - firstly exploring a wide demographic parameter space under four simple demographic models of varying complexities and configurations using branch-length data from two chromosomes - and secondly, we analyzed a model of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudo-haploidization. We observe population differentiation is the primary factor driving qpAdm performance. Notably, whilst complex gene-flow histories influence which models are classified as plausible, they do not reduce overall performance. Under conditions reflective of the historical period, qpAdm most frequently identifies the true model as plausible amongst a small candidate set of closely related populations. To increase the utility for resolving fine-scaled hypotheses, we provide a heuristic for further distinguishing between candidate models that incorporates qpAdm model P-values and f3-statistics. Finally, we demonstrate a significant performance increase for qpAdm using whole-genome branch-length f2-statistics, highlighting the potential for improved demographic inference that could be achieved with future advancements in f-statistic estimations.

A number of species have recently recovered from near-extinction. Although these species have avoided the immediate extinction threat, their long-term viability remains precarious due to the potential genetic consequences of population declines, which are poorly understood on a timescale beyond a few generations. Woolly mammoths (Mammuthus primigenius) became isolated on Wrangel Island around 10,000 years ago and persisted for over 200 generations before becoming extinct around 4,000 years ago. To study the evolutionary processes leading up to the mammoths\' extinction, we analyzed 21 Siberian woolly mammoth genomes. Our results show that the population recovered quickly from a severe bottleneck and remained demographically stable during the ensuing six millennia. We find that mildly deleterious mutations gradually accumulated, whereas highly deleterious mutations were purged, suggesting ongoing inbreeding depression that lasted for hundreds of generations. The time-lag between demographic and genetic recovery has wide-ranging implications for conservation management of recently bottlenecked populations.

Using the examples of plague, smallpox, and HIV/AIDS, the present essay argues for the benefits of incorporating the evolutionary histories of pathogens, beyond visible epidemic spikes within human populations, into our understanding of what pandemics actually are as epidemiological phenomena. The pandemic arc - which takes the pathogen as the defining \"actor\" in a pandemic, from emergence to local proliferation to globalization - offers a framework capable of bringing together disparate aspects not only of the manifestations of disease but also of human involvement in the pandemic process. Pathogens may differ, but there are common patterns in disease emergence and proliferation that distinguish those diseases that become pandemic, dispersed through human communities regionally or globally. The same methods of genomic analysis that allow tracking the evolutionary development of a modern pathogen such as SARS-CoV-2 also allow us to trace pandemics into the past. Reconstruction of these pandemic arcs brings new elements of these stories into view, recovering the experiences of regions and populations hitherto overlooked by Eurocentric narratives. This expanded global history of infectious diseases, in turn, lays a groundwork for reconceiving what ambitions a truly global health might aim for.

Low genomic diversity is generally indicative of small population size and is considered detrimental by decreasing long-term adaptability.1,2,3,4,5,6 Moreover, small population size may promote gene flow with congeners and outbreeding depression.7,8,9,10,11,12,13 Here, we examine the connection between habitat availability, effective population size (Ne), and extinction by generating a 40× nuclear genome from the extinct blue antelope (Hippotragus leucophaeus). Historically endemic to the relatively small Cape Floristic Region in southernmost Africa,14,15 populations were thought to have expanded and contracted across glacial-interglacial cycles, tracking suitable habitat.16,17,18 However, we found long-term low Ne, unaffected by glacial cycles, suggesting persistence with low genomic diversity for many millennia prior to extinction in ∼AD 1800. A lack of inbreeding, alongside high levels of genetic purging, suggests adaptation to this long-term low Ne and that human impacts during the colonial era (e.g., hunting and landscape transformation), rather than longer-term ecological processes, were central to its extinction. Phylogenomic analyses uncovered gene flow between roan (H. equinus) and blue antelope, as well as between roan and sable antelope (H. niger), approximately at the time of divergence of blue and sable antelope (∼1.9 Ma). Finally, we identified the LYST and ASIP genes as candidates for the eponymous bluish pelt color of the blue antelope. Our results revise numerous aspects of our understanding of the interplay between genomic diversity and evolutionary history and provide the resources for uncovering the genetic basis of this extinct species\' unique traits.

Paleogenomics has expanded our knowledge of human evolutionary history. Since the 2020s, the study of ancient DNA has increased its focus on reconstructing the recent past. However, the accuracy of paleogenomic methods in answering questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation within the historical period remains an open question. We used two simulation approaches to evaluate the limitations and behavior of commonly used methods, qpAdm and the f3-statistic, on admixture inference. The first is based on branch-length data simulated from four simple demographic models of varying complexities and configurations. The second, an analysis of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudo-haploidization. We show that under conditions resembling historical populations, qpAdm can identify a small candidate set of true sources and populations closely related to them. However, in typical ancient DNA conditions, qpAdm is unable to further distinguish between them, limiting its utility for resolving fine-scaled hypotheses. Notably, we find that complex gene-flow histories generally lead to improvements in the performance of qpAdm and observe no bias in the estimation of admixture weights. We offer a heuristic for admixture inference that incorporates admixture weight estimate and P-values of qpAdm models, and f3-statistics to enhance the power to distinguish between multiple plausible candidates. Finally, we highlight the future potential of qpAdm through whole-genome branch-length f2-statistics, demonstrating the improved demographic inference that could be achieved with advancements in f-statistic estimations.

The analysis of ancient oral metagenomes from archaeological human and animal samples is largely confounded by contaminant DNA sequences from modern and environmental sources. Existing methods for Microbial Source Tracking (MST) estimate the proportions of environmental sources, but do not perform well on ancient metagenomes. We developed a novel method called decOM for Microbial Source Tracking and classification of ancient and modern metagenomic samples using k-mer matrices.
We analysed a collection of 360 ancient oral, modern oral, sediment/soil and skin metagenomes, using stratified five-fold cross-validation. decOM estimates the contributions of these source environments in ancient oral metagenomic samples with high accuracy, outperforming two state-of-the-art methods for source tracking, FEAST and mSourceTracker.
decOM is a high-accuracy microbial source tracking method, suitable for ancient oral metagenomic data sets. The decOM method is generic and could also be adapted for MST of other ancient and modern types of metagenomes. We anticipate that decOM will be a valuable tool for MST of ancient metagenomic studies. Video Abstract.

As the collapse of the Western Roman Empire accelerated during the 4th and 5th centuries, arriving \"barbarian\" groups began to establish new communities in the border provinces of the declining (and eventually former) empire. This was a time of significant cultural and political change throughout not only these border regions but Europe as a whole.1,2 To better understand post-Roman community formation in one of these key frontier zones after the collapse of the Hunnic movement, we generated new paleogenomic data for a set of 38 burials from a time series of three 5th century cemeteries3,4,5 at Lake Balaton, Hungary. We utilized a comprehensive sampling approach to characterize these cemeteries along with data from 38 additional burials from a previously published mid-6th century site6 and analyzed them alongside data from over 550 penecontemporaneous individuals.7,8,9,10,11,12,13,14,15,16,17,18,19 The range of genetic diversity in all four of these local burial communities is extensive and wider ranging than penecontemporaneous Europeans sequenced to date. Despite many commonalities in burial customs and demography, we find that there were substantial differences in genetic ancestry between the sites. We detect evidence of northern European gene flow into the Lake Balaton region. Additionally, we observe a statistically significant association between dress artifacts and genetic ancestry among 5th century genetically female burials. Our analysis shows that the formation of early Medieval communities was a multifarious process even at a local level, consisting of genetically heterogeneous groups.

The analysis of past epidemics and pandemics, either spontaneous or of human origin, may revise the physical history of microbiota and create a temporal context in our understanding regarding pathogen attributes like virulence, evolution, transmission and disease dynamics. The data of high-tech scientific methods seem reliable, but their interpretation may still be biased when tackling events of the distant past. Such endeavors should be adjusted to other cognitive resources including historical accounts reporting the events of interest and references in alien medical cultures and terminologies; the latter may contextualize them differently from current practices. Thus \'historical microbiology\' emerges. Validating such resources requires utmost care, as these may be susceptible to different biases regarding the interpretation of facts and phenomena; biases partly due to methodological limitations.
Bacteria and viruses have always impacted humankind. They do this directly by causing illness or indirectly by destroying crops and threatening livestock. We can learn a lot by studying disease events of the past – for example, we can see how bacteria and viruses have changed over time and predict how they might change in the future. This knowledge could be important to understanding present disease events and predicting future ones. In this review, we propose the concept of \'historical microbiology’, which encourages collaboration between scientists, doctors, historians and linguists to provide historical, linguistic and cultural context to our scientific understanding of diseases of the past.

The results of studies in Quaternary geology, archeology, paleoanthropology and human genetics demonstrate that the ancestors of Native Americans arrived in mid-latitude North America mainly along the Pacific Northwest Coast, but had previously inhabited the Arctic and during the last glacial maximum were in a refugium in Beringia, a land bridge connecting Eurasia and North America. The gene pool of Native Americans is represented by unique haplogroups of mitochondrial DNA and the Y chromosome, the evolutionary age of which ranges from 13 to 22 thousand years. The results of a paleogenomic analysis also show that during the last glacial maximum Beringia was populated by human groups that had arisen as a result of interaction between the most ancient Upper Paleolithic populations of Northern Eurasia and newcomer groups from East Asia. Approximately 20 thousand years ago the Beringian populations began to form, and the duration of their existence in relative isolation is estimated at about 5 thousand years. Thus, the adaptation of the Beringians to the Arctic conditions could have taken several millennia. The adaptation of Amerindian ancestors to high latitudes and cold climates is supported by genomic data showing that adaptive genetic variants in Native Americans are associated with various metabolic pathways: melanin production processes in the skin, hair and eyes, the functioning of the cardiovascular system, energy metabolism and immune response characteristics. Meanwhile, the analysis of the existing hypotheses about the selection of some genetic variants in the Beringian ancestors of the Amerindians in connection with adaptation to the Arctic conditions (for example, in the FADS, ACTN3, EDAR genes) shows the ambiguity of the testing results, which may be due to the loss of some traces of the \"Beringian\" adaptation in the gene pools of modern Native Americans. The most optimal strategy for further research seems to be the search for adaptive variant.
Результаты исследований в области четвертичной геологии, археологии, палеоантропологии и генетики человека показывают, что предки американских индейцев прибыли в средние широты Северной Америки главным образом по тихоокеанскому побережью. Но до этого они населяли Арктику и во время последнего ледникового максимума укрывались в рефугиуме на территории Берингии, соединявшей Евразию и Северную Америку. Генофонд американских индейцев представлен уникальными гаплогруппами митохондриальной ДНК и Y-хромосомы, эволюционный возраст которых составляет от 13 до 22 тыс. лет. Результаты анализа палеогеномных данных также свидетельствуют о том, что во время последнего ледникового максимума на территории Берингии сохранялись группы населения, возникшие в результате взаимодействия древнейшего верхнепалеолитического населения Северной Евразии и пришлых групп населения из Восточной Азии. Примерно 20 тыс. лет назад началось формирование популяций Берингии, а время их существования в относительной изоляции оценивается примерно в 5 тыс. лет. Таким образом, период адаптации берингийцев к условиям Арктики мог занять несколько тысячелетий. Адаптация предков америндов к высоким широтам и холодному климату подтверждается геномными данными, показавшими, что адаптивные генетические варианты у американских индейцев ассоциируются с различными метаболическими пу- тями: процессами продукции меланина в коже, волосах и глазах, функционированием сердечно-сосудистой системы, энергетическим обменом и особенностями иммунного ответа. Между тем анализ существующих гипотез об отборе некоторых генетических вариантов у берингийских предков америндов в связи с адаптацией к условиям Арктики (например, в генах FADS, ACTN3, EDAR) демонстрирует неоднозначность результа- тов проверки, что может быть связано с утратой некоторых следов «берингийской» адаптации в генофондах современных американских индейцев. Наиболее оптимальной стратегией дальнейших исследований представляется поиск адаптивных вариантов с помощью анализа палеогеномных данных с территории Берингии, однако таких генетических данных пока очень мало.