The retrieval of ancient DNA from osteological material provides direct evidence of human genetic diversity in the past. Ancient DNA samples are often used to investigate whether there was population continuity in the settlement history of an area. Methods based on the serial coalescent algorithm have been developed to test whether the population continuity hypothesis can be statistically rejected by analysing DNA samples from the same region but of different ages. Rejection of this hypothesis is indicative of a large genetic shift, possibly due to immigration occurring between two sampling times. However, this approach is only able to reject a model of full continuity model (a total absence of genetic input from outside), but admixture between local and immigrant populations may lead to partial continuity. We have recently developed a method to test for population continuity that explicitly considers the spatial and temporal dynamics of populations. Here, we extended this approach to estimate the proportion of genetic continuity between two populations, using ancient genetic samples. We applied our original approach to the question of the Neolithic transition in Central Europe. Our results confirmed the rejection of full continuity, but our approach represents an important step forward by estimating the relative contribution of immigrant farmers and of local hunter‐gatherers to the final Central European Neolithic genetic pool. Furthermore, we show that a substantial proportion of genes brought by the farmers in this region were assimilated from other hunter‐gatherer populations along the way from Anatolia, which was not detectable by previous continuity tests. Our approach is also able to jointly estimate demographic parameters, as we show here by finding both low density and low migration rate for pre‐Neolithic hunter‐gatherers. It provides a useful tool for the analysis of the numerous ancient DNA data sets that are currently being produced for many different species.

BackgroundRecent advances in sequencing technologies have allowed for the retrieval of ancient DNA data (aDNA) from skeletal remains, providing direct genetic snapshots from diverse periods of human prehistory. Comparing samples taken in the same region but at different times, hereafter called “serial samples”, may indicate whether there is continuity in the peopling history of that area or whether an immigration of a genetically different population has occurred between the two sampling times. However, the exploration of genetic relationships between serial samples generally ignores their geographical locations and the spatiotemporal dynamics of populations. Here, we present a new coalescent-based, spatially explicit modelling approach to investigate population continuity using aDNA, which includes two fundamental elements neglected in previous methods: population structure and migration. The approach also considers the extensive temporal and geographical variance that is commonly found in aDNA population samples.ResultsWe first showed that our spatially explicit approach is more conservative than the previous (panmictic) approach and should be preferred to test for population continuity, especially when small and isolated populations are considered. We then applied our method to two mitochondrial datasets from Germany and France, both including modern and ancient lineages dating from the early Neolithic. The results clearly reject population continuity for the maternal line over the last 7500 years for the German dataset but not for the French dataset, suggesting regional heterogeneity in post-Neolithic migratory processes.ConclusionsHere, we demonstrate the benefits of using a spatially explicit method when investigating population continuity with aDNA. It constitutes an improvement over panmictic methods by considering the spatiotemporal dynamics of genetic lineages and the precise location of ancient samples. The method can be used to investigate population continuity between any pair of serial samples (ancient-ancient or ancient-modern) and to investigate more complex evolutionary scenarios. Although we based our study on mitochondrial DNA sequences, diploid molecular markers of different types (DNA, SNP, STR) can also be simulated with our approach. It thus constitutes a promising tool for the analysis of the numerous aDNA datasets being produced, including genome wide data, in humans but also in many other species.Electronic supplementary materialThe online version of this article (10.1186/s12863-017-0575-6) contains supplementary material, which is available to authorized users.

The Bronze Age is a complex period of social, cultural and economic changes. Recent paleogenomic studies have documented a large and rapid genetic change in early Bronze Age populations from Central Europe. However, the detailed demographic and genetic processes involved in this change are still debated. Here we have used spatially explicit simulations of genomic components to better characterize the demographic and migratory conditions that may have led to this change. We investigated various scenarios representing the expansion of pastoralists from the Pontic steppe, potentially linked to the Yamnaya cultural complex, and their interactions with local populations in Central Europe, considering various eco-evolutionary factors, such as population admixture, competition and long-distance dispersal. Our results do not support direct competition but rather the cohabitation of pastoralists and farmers in Central Europe, with limited gene flow between populations. They also suggest occasional long-distance migrations accompanying the expansion of pastoralists and a demographic decline in both populations following their initial contact. These results link recent archaeological and paleogenomic observations and move further the debate of genomic changes during the early Bronze Age.

The worldwide expansion of modern humans (Homo sapiens) from Africa started before the extinction of Neanderthals (Homo neanderthalensis). Both species coexisted and interbred, as revealed by the sequencing of Neanderthal genomes, leading to ~2% Neanderthal DNA in modern Eurasians, with slightly higher introgression in East Asians than in Europeans. These distinct levels of ancestry have been argued to result from selection processes. However, recent theoretical simulations have shown that range expansions could be another explanation. This hypothesis would lead to the generation of spatial gradients of introgression, increasing with the distance from the source of the expansion, i.e., Africa for modern humans. Here, we investigate the presence of Neanderthal introgression gradients after past human expansions by analysing an extended palaeogenomic dataset of Eurasian populations. Our results show that the Out-of-Africa expansion of modern humans into Eurasia resulted in spatial gradients of Neanderthal ancestry that persisted through time. Moreover, while keeping the same gradient orientation, the expansion of early Neolithic farmers into western Eurasia contributed decisively to reducing the average level of Neandertal genomic introgression in European compared to Asian populations. This is because Neolithic farmers carried less Neanderthal DNA than preceding Palaeolithic hunter-gatherers. This study shows that inferences about past population dynamics within our species can be made from the spatiotemporal variation in archaic introgression.

The aim of the study is to investigate mitochondrial diversity in Neolithic Greece and its relation to hunter-gatherers and farmers who populated the Danubian Neolithic expansion axis. We sequenced 42 mitochondrial palaeogenomes from Greece and analysed them together with European set of 328 mtDNA sequences dating from the Early to the Final Neolithic and 319 modern sequences. To test for population continuity through time in Greece, we use an original structured population continuity test that simulates DNA from different periods by explicitly considering the spatial and temporal dynamics of populations. We explore specific scenarios of the mode and tempo of the European Neolithic expansion along the Danubian axis applying spatially explicit simulations coupled with Approximate Bayesian Computation. We observe a striking genetic homogeneity for the maternal line throughout the Neolithic in Greece whereas population continuity is rejected between the Neolithic and present-day Greeks. Along the Danubian expansion axis, our best-fitting scenario supports a substantial decrease in mobility and an increasing local hunter-gatherer contribution to the gene-pool of farmers following the initial rapid Neolithic expansion. Οur original simulation approach models key demographic parameters rather than inferring them from fragmentary data leading to a better understanding of this important process in European prehistory.

International audienceThe onset and conservation of genetic polymorphism is a major question in evolutionary ecology. The influence of temporal fluctuations in the environment was invoked by early theorists such as J.B.S. Haldane and S. Jayakar in a controversial article published in, 1963, but their frequently cited model has almost never been used with empirical evidence. In this paper,we present a simulation model inspired by the biology of common gorse (Ulex europaeus), a species which shows polymorphism of flowering phenology: long flowering plants produce flowers from winter to spring and short flowering plants only flower in the spring. The early fruits of the former run the risk of frost, but largely escape seed predation, while those of the latter escape the risk of frost but are subject to a strong risk of seed predation. These two selection pressures vary unpredictably from year to year, making this flowering phenotype a good candidate to test Haldane and Jayakar’s model. Assuming that both flowering types are determined by a single major locus, we devise a simulation model firstly in a diploid form, and secondly by taking intoaccount the hexaploid characteristic of gorse. Our results show that the combination of the two selective pressures acting on gorse flowering phenology can lead to fitness values meeting the Haldane and Jayakar’s conditions on geometric and arithmetic means, and to long term maintenance of polymorphism. In addition, the values of the parameters allowing polymorphism persistence and the relative proportions obtained are in agreement with values observed in natural populations. We also show that hexaploidy strongly increases the range of parameters in which polymorphism is self sustaining. These results are discussed in the context of climatic change, where increases of both mean temperature and its variance are predicted

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