A statistical model for reference-free inference of archaic local ancestry

Statistical analyses of genomic data from diverse human populations have demonstrated that archaic hominins, such as Neanderthals and Denisovans, interbred or admixed with the ancestors of present-day humans. Central to these analyses are methods for inferring archaic ancestry along the genomes of present-day individuals (archaic local ancestry). Methods for archaic local ancestry inference rely on the availability of reference genomes from the ancestral archaic populations for accurate inference. However, several instances of archaic admixture lack reference archaic genomes, making it difficult to characterize these events. We present a statistical method that combines diverse population genetic summary statistics to infer archaic local ancestry without access to an archaic reference genome. We validate the accuracy and robustness of our method in simulations. When applied to genomes of European individuals, our method recovers segments that are substantially enriched for Neanderthal ancestry, even though our method did not have access to any Neanderthal reference genomes. Author summary Recent analyses of modern human genomes have shown that archaic hominins like Neanderthals and Denisovans contribute a few percentage of ancestry to many populations. These analyses rely on having accurate reference genomes from these archaic populations. Due to the difficulty in sequencing these genomes, we lack a complete collection of reference genomes with which to identify archaic ancestry. Here, we develop a method that identifies segments of archaic ancestry in modern human genomes without the need for archaic reference genomes. We systematically evaluate the accuracy and robustness of our method and apply it to modern European genomes to uncover signals of introgression which we confirm to be from a population related to Neanderthals.