Modeling of African population history using f-statistics is biased when applying all previously proposed SNP ascertainment schemes

Genomic exploration of the journey of Plasmodium vivax in Latin America

Plasmodium vivax is the predominant malaria parasite in Latin America. Its colonization history in the region is rich and complex, and is still highly debated, especially about its origin(s). Our study employed cutting-edge population genomic techniques to analyze whole genome variation from 620 P. vivax isolates, including 107 newly sequenced samples from West Africa, Middle East, and Latin America. This sampling represents nearly all potential source populations worldwide currently available. Analyses of the genetic structure, diversity, ancestry, coalescent-based inferences, including demographic scenario testing using Approximate Bayesian Computation, have revealed a more complex evolutionary history than previously envisioned. Indeed, our analyses suggest that the current American P. vivax populations predominantly stemmed from a now-extinct European lineage, with the potential contribution also from unsampled populations, most likely of West African origin. We also found evidence that P. vivax arrived in Latin America in multiple waves, initially during early European contact and later through post-colonial human migration waves in the late 19th-century. This study provides a fresh perspective on P. vivax's intricate evolutionary journey and brings insights into the possible contribution of West African P. vivax populations to the colonization history of Latin America.

An explanation for the sister repulsion phenomenon in Patterson's f-statistics

Patterson's f-statistics are among the most heavily utilized tools for analyzing genome-wide allele frequency data for demographic inference. Beyond studying admixture, f3- and f4-statistics are also used for clustering populations to identify groups with similar histories. However, previous studies have noted an unexpected behavior of f-statistics: multiple populations from a certain region systematically show higher genetic affinity to a more distant population than to their neighbors, a pattern that is mismatched with alternative measures of genetic similarity. We call this counter-intuitive pattern "sister repulsion". We first present a novel instance of sister repulsion, where genomes from Bronze Age East Anatolian sites show higher affinity toward Bronze Age Greece rather than each other. This is observed both using f3- and f4-statistics, contrasts with archaeological/historical expectation, and also contradicts genetic affinity patterns captured using principal components analysis or multidimensional scaling on genetic distances. We then propose a simple demographic model to explain this pattern, where sister populations receive gene flow from a genetically distant source. We calculate f3- and f4-statistics using simulated genetic data with varying population genetic parameters, confirming that low-level gene flow from an external source into populations from 1 region can create sister repulsion in f-statistics. Unidirectional gene flow between the studied regions (without an external source) can likewise create repulsion. Meanwhile, similar to our empirical observations, multidimensional scaling analyses of genetic distances still cluster sister populations together. Overall, our results highlight the impact of low-level admixture events when inferring demographic history using f-statistics.

9,000 years of genetic continuity in southernmost Africa demonstrated at Oakhurst rockshelter

Southern Africa has one of the longest records of fossil hominins and harbours the largest human genetic diversity in the world. Yet, despite its relevance for human origins and spread around the globe, the formation and processes of its gene pool in the past are still largely unknown. Here, we present a time transect of genome-wide sequences from nine individuals recovered from a single site in South Africa, Oakhurst Rockshelter. Spanning the whole Holocene, the ancient DNA of these individuals allows us to reconstruct the demographic trajectories of the indigenous San population and their ancestors during the last 10,000 years. We show that, in contrast to most regions around the world, the population history of southernmost Africa was not characterized by several waves of migration, replacement and admixture but by long-lasting genetic continuity from the early Holocene to the end of the Later Stone Age. Although the advent of pastoralism and farming substantially transformed the gene pool in most parts of southern Africa after 1,300 BP, we demonstrate using allele-frequency and identity-by-descent segment-based methods that the ‡Khomani San and Karretjiemense from South Africa still show direct signs of relatedness to the Oakhurst hunter-gatherers, a pattern obscured by recent, extensive non-Southern African admixture. Yet, some southern San in South Africa still preserve this ancient, Pleistocene-derived genetic signature, extending the period of genetic continuity until today.

Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA

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 pseudohaploidization. We observe that population differentiation is the primary factor driving qpAdm performance. Notably, while 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 among 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.

Hunter-gatherer genetics research: Importance and avenues

Major developments in the field of genetics in the past few decades have revolutionised notions of what it means to be human. Although currently only a few populations around the world practise a hunting and gathering lifestyle, this mode of subsistence has characterised members of our species since its very origins and allowed us to migrate across the planet. Therefore, the geographical distribution of hunter-gatherer populations, dependence on local ecosystems and connections to past populations and neighbouring groups have provided unique insights into our evolutionary origins. However, given the vulnerable status of hunter-gatherers worldwide, the development of the field of anthropological genetics requires that we reevaluate how we conduct research with these communities. Here, we review how the inclusion of hunter-gatherer populations in genetics studies has advanced our understanding of human origins, ancient population migrations and interactions as well as phenotypic adaptations and adaptability to different environments, and the important scientific and medical applications of these advancements. At the same time, we highlight the necessity to address yet unresolved questions and identify areas in which the field may benefit from improvements.

Testing Times: Challenges in Disentangling Admixture Histories in Recent and Complex Demographies

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.