Dogs were the first domestic animal, but little is known about their population history and to what extent it was linked to humans. We sequenced 27 ancient dog genomes and found that all dogs share a common ancestry distinct from present-day wolves, with limited gene flow from wolves since domestication but substantial dog-to-wolf gene flow. By 11,000 years ago, at least five major ancestry lineages had diversified, demonstrating a deep genetic history of dogs during the Paleolithic. Coanalysis with human genomes reveals aspects of dog population history that mirror humans, including Levant-related ancestry in Africa and early agricultural Europe. Other aspects differ, including the impacts of steppe pastoralist expansions in West and East Eurasia and a near-complete turnover of Neolithic European dog ancestry.

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Natural and human-driven selection of a single noncoding body size variant in ancient and modern canids Highlights d An ancestral variant on IGF1 locus regulates body size in ancient and modern dogs d Variant alleles are associated with body size in dogs, wolves, and coyotes d The large body size-associated allele arose more than 53,000 years ago in wolves

Summary The evolution of the genera Bos and Bison , and the nature of gene flow between wild and domestic species, is poorly understood, with genomic data of wild species being limited. We generated two genomes from the likely extinct kouprey ( Bos sauveli ) and analyzed them alongside other Bos and Bison genomes. We found that B. sauveli possessed genomic signatures characteristic of an independent species closely related to Bos javanicus and Bos gaurus . We found evidence for extensive incomplete lineage sorting across the three species, consistent with a polytomic diversification of the major ancestry in the group, potentially followed by secondary gene flow. Finally, we detected significant gene flow from an unsampled Asian Bos -like source into East Asian zebu cattle, demonstrating both that the full genomic diversity and evolutionary history of the Bos complex has yet to be elucidated and that museum specimens and ancient DNA are valuable resources to do so.

Identification of specific species in metagenomic samples is critical for several key applications, yet many tools available require large computational power and are often prone to false positive identifications. Here we describe High-AccuracY and Scalable Taxonomic Assignment of MetagenomiC data (HAYSTAC), which can estimate the probability that a specific taxon is present in a metagenome. HAYSTAC provides a user-friendly tool to construct databases, based on publicly available genomes, that are used for competitive reads mapping. It then uses a novel Bayesian framework to infer the abundance and statistical support for each species identification and provide per-read species classification. Unlike other methods, HAYSTAC is specifically designed to efficiently handle both ancient and modern DNA data, as well as incomplete reference databases, making it possible to run highly accurate hypothesis-driven analyses (i.e., assessing the presence of a specific species) on variably sized reference databases while dramatically improving processing speeds. We tested the performance and accuracy of HAYSTAC using simulated Illumina libraries, both with and without ancient DNA damage, and compared the results to other currently available methods (i.e., Kraken2/Bracken, KrakenUniq, MALT/HOPS, and Sigma). HAYSTAC identified fewer false positives than both Kraken2/Bracken, KrakenUniq and MALT in all simulations, and fewer than Sigma in simulations of ancient data. It uses less memory than Kraken2/Bracken, KrakenUniq as well as MALT both during database construction and sample analysis. Lastly, we used HAYSTAC to search for specific pathogens in two published ancient metagenomic datasets, demonstrating how it can be applied to empirical datasets. HAYSTAC is available from https://github.com/antonisdim/HAYSTAC.