Abstract
Genomic studies of species threatened by extinction are providing crucial information about evolutionary mechanisms and genetic consequences of population declines and bottlenecks. However, to understand how species avoid the extinction vortex, insights can be drawn by studying species that thrive despite past declines. Here, we studied the population genomics of the muskox (Ovibos moschatus), an Ice Age relict that was at the brink of extinction for thousands of years at the end of the Pleistocene yet appears to be thriving today. We analysed 108 whole genomes, including present-day individuals representing the current native range of both muskox subspecies, the white-faced and the barren-ground muskox (O. moschatus wardi and O. moschatus moschatus) and a ~21,000-year-old ancient individual from Siberia. We found that the muskox' demographic history was profoundly shaped by past climate changes and post-glacial re-colonizations. In particular, the white-faced muskox has the lowest genome-wide heterozygosity recorded in an ungulate. Yet, there is no evidence of inbreeding depression in native muskox populations. We hypothesize that this can be explained by the effect of long-term gradual population declines that allowed for purging of strongly deleterious mutations. This study provides insights into how species with a history of population bottlenecks, small population sizes and low genetic diversity survive against all odds.
Originalsprog | Engelsk |
---|---|
Tidsskrift | Molecular Ecology |
Vol/bind | 33 |
Udgave nummer | 2 |
Antal sider | 25 |
ISSN | 0962-1083 |
DOI | |
Status | Udgivet - 2024 |
Bibliografisk note
Funding Information:This study was supported by a DFF grant no. 8021‐00344B awarded to H.R.S. Additional funding was provided by a Carlsberg Foundation Young Researcher Fellowship grant (CF20‐0539) awarded to I.M. E.L., L.D. and A.G. acknowledge funding from the Bolin Centre for Climate Research, Research Area 8. The authors acknowledge the support of local communities and organizations that P.J.C.G. received in the process of collecting samples for this study. The authors also acknowledge support from the Science for Life Laboratory, the National Genomics Infrastructure and UPPMAX (project numbers: b2015028, SNIC2019/8‐330, SNIC2020/5‐3, SNIC2021/22‐951, SNIC2021/23‐432, SNIC2022/5‐27) for providing assistance in massive parallel sequencing and computational infrastructure. E.L. acknowledges the National Bioinformatics Infrastructure Sweden at SciLifeLab for bioinformatics advice in the scope of the Swedish Bioinformatics Advisory Programme. The authors acknowledge the helpful discussion with J. Víctor Moreno‐Mayar regarding direct ancestry testing. L.D., F.D., and A.G. acknowledge logistical field work support from the Swedish Polar Research Secretariat during the Ryder19 expedition. Sergey Vartanyan was supported by the Russian Science Foundation (Project No. 22‐27‐00082). In addition, the authors acknowledge the use of computing resources at the core facility for biocomputing at the Department of Biology, University of Copenhagen. Finally, the authors thank the reviewers for insightful comments that helped to improve the manuscript.
Publisher Copyright:
© 2023 John Wiley & Sons Ltd.