Tracking five millennia of horse management with extensive ancient genome time series

Horse domestication revolutionized warfare and accelerated travel, trade, and the geographic expansion of languages. Here, we present the largest DNA time series for a non-human organism to date, including genome-scale data from 149 ancient animals and 129 ancient genomes (≥1-fold coverage), 87 of which are new. This extensive dataset allows us to assess the modern legacy of past equestrian civilizations. We find that two extinct horse lineages existed during early domestication, one at the far western (Iberia) and the other at the far eastern range (Siberia) of Eurasia. None of these contributed significantly to modern diversity. We show that the influence of Persian-related horse lineages increased following the Islamic conquests in Europe and Asia. Multiple alleles associated with elite-racing, including at the MSTN "speed gene," only rose in popularity within the last millennium. Finally, the development of modern breeding impacted genetic diversity more dramatically than the previous millennia of human management.T.M.-B. was supported by the BFU2017-86471-P (MINECO/FEDER, UE), the U01 MH106874 grant, Howard Hughes International Early Career, Obra Social “La Caixa,” and Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya. V.P. was supported by Russian Science Foundation (16-18-10265). This research received support from the SYNTHESYS Project (http://www.synthesys.info/), which is financed by European Community Research Infrastructure Action under the Seventh Framework “Capacities” Programme. This work was supported by the Danish National Research Foundation (DNRF94), the Initiative d’Excellence Chaires d’attractivité, Université de Toulouse (OURASI), the International Highly Cited Research Group Program (HCRC#15-101), Deanship of Scientific Research, King Saud University, the Villum Fonden miGENEPI research project, the Swiss National Science Foundation (CR13I1_140638), the Research Council of Norway (project 230821/F20); the investigation grant HAR2016-77600-P, Ministerio de Economía y Competitividad, Spain, and the National Science Foundation (ANS-1417036). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement 681605)