Generative models have shown breakthroughs in a wide spectrum of domains due to recent advancements in machine learning algorithms and increased computational power. Despite these impressive achievements, the ability of generative models to create realistic synthetic data is still under-exploited in genetics and absent from population genetics. Yet a known limitation in the field is the reduced access to many genetic databases due to concerns about violations of individual privacy, although they would provide a rich resource for data mining and integration towards advancing genetic studies. In this study, we demonstrated that deep generative adversarial networks (GANs) and restricted Boltzmann machines (RBMs) can be trained to learn the complex distributions of real genomic datasets and generate novel high-quality artificial genomes (AGs) with none to little privacy loss. We show that our generated AGs replicate characteristics of the source dataset such as allele frequencies, linkage disequilibrium, pairwise haplotype distances and population structure. Moreover, they can also inherit complex features such as signals of selection. To illustrate the promising outcomes of our method, we showed that imputation quality for low frequency alleles can be improved by data augmentation to reference panels with AGs and that the RBM latent space provides a relevant encoding of the data, hence allowing further exploration of the reference dataset and features for solving supervised tasks. Generative models and AGs have the potential to become valuable assets in genetic studies by providing a rich yet compact representation of existing genomes and high-quality, easy-access and anonymous alternatives for private databases.

The recently enriched genomic history of Indigenous groups in the Americas is still meager concerning continental Central America. Here, we report ten pre-Hispanic (plus two early colonial) genomes and 84 genome-wide profiles from seven groups presently living in Panama. Our analyses reveal that pre-Hispanic demographic events contributed to the extensive genetic structure currently seen in the area, which is also characterized by a distinctive Isthmo-Colombian Indigenous component. This component drives these populations on a specific variability axis and derives from the local admixture of different ancestries of northern North American origin(s). Two of these ancestries were differentially associated to Pleistocene Indigenous groups that also moved into South America, leaving heterogenous genetic footprints. An additional Pleistocene ancestry was brought by a still unsampled population of the Isthmus (UPopI) that remained restricted to the Isthmian area, expanded locally during the early Holocene, and left genomic traces up to the present day.

A general imbalance in the proportion of disembarked males and females in the Americas has been documented during the Trans-Atlantic Slave Trade and the Colonial Era and, although less prominent, more recently. This imbalance may have left a signature on the genomes of modern-day populations characterised by high levels of admixture. The analysis of the uniparental systems and the evaluation of continental proportion ratio of autosomal and X chromosomes revealed a general sex imbalance towards males for European and females for African and Indigenous American ancestries. However, the consistency and degree of this imbalance are variable, suggesting that other factors, such as cultural and social practices, may have played a role in shaping it. Moreover, very few investigations have evaluated the sex imbalance using haplotype data, containing more critical information than genotypes. Here, we analysed genome-wide data for more than 5000 admixed American individuals to assess the presence, direction and magnitude of sex-biased admixture in the Americas. For this purpose, we applied two haplotype-based approaches, ELAI and NNLS, and we compared them with a genotype-based method, ADMIXTURE. In doing so, besides a general agreement between methods, we unravelled that the post-colonial admixture dynamics show higher complexity than previously described.

American populations are one of the most interesting examples of recently admixed groups, where ancestral components from three major continental human groups (Africans, Eurasians and Native Americans) have admixed within the last 15 generations. Recently, several genetic surveys focusing on thousands of individuals shed light on the geography, chronology and relevance of these events. However, even though gene flow could drive adaptive evolution, it is unclear whether and how natural selection acted on the resulting genetic variation in the Americas. In this study, we analysed the patterns of local ancestry of genomic fragments in genome-wide data for ~ 6000 admixed individuals from 10 American countries. In doing so, we identified regions characterized by a divergent ancestry profile (DAP), in which a significant over or under ancestral representation is evident. Our results highlighted a series of genomic regions with DAPs associated with immune system response and relevant medical traits, with the longest DAP region encompassing the human leukocyte antigen locus. Furthermore, we found that DAP regions are enriched in genes linked to cancer-related traits and autoimmune diseases. Then, analysing the biological impact of these regions, we showed that natural selection could have acted preferentially towards variants located in coding and non-coding transcripts and characterized by a high deleteriousness score. Taken together, our analyses suggest that shared patterns of post admixture adaptation occurred at a continental scale in the Americas, affecting more often functional and impactful genomic variants.