Tracking Five Millennia of Horse Management with Extensive Ancient Genome Time Series

Abstract

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 (R1-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.

We thank the reviewers for insightful comments and suggestions that helped improve the manuscript. We thank the staff of the Danish National High-Throughput DNA Sequencing Center for technical support; Rachel Ballantyne, Maude Barme, Lucie Cottier, Jean-Marc Fe´ molant, Ste´ phane Fre` re, Gae¨ tan Jouanin, Patrice Meniel, Nicolas Morand, Anaı¨s Ortiz, Ollivier Putelat, Vida Rajkovaca, Julie Rivie` re, Opale Robin, Noe´ mie Tomadini, Jean-Herve´ Yvinec, and the National Museum of Iceland for providing access to osteological material; Bazartseren Boldbat for his help and guidance; Laurent Frantz, Dan Bradley, and Greger Larson for critical reading of the manuscript; and Clio Der Sarkissian and Luca Ermini for preliminary analyses, technical support, and insightful discussion. B.B. was supported by the Taylor Family-Asia Foundation Endowed Chair in Ecology and Conservation Biology. M.L. was supported by a Marie-Curie Individual Fellowship (MSCA-IF-67852). L.L. was supported by the Estonian Research Council (PRG29). C.L. was supported by FCT (SFRH/ BPD/100511/2014). P.K., N.R., and O.M. were supported by the Ministry of Educations and Science of Russian Federation (33.1907, 2017/P4) and the Russian Scientific Foundation (18-18-00137). 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’attractivite´ , Universite´ 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 Economıa 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).