A chromosome-level genome of Astyanax mexicanus surface fish for comparing population-specific genetic differences contributing to trait evolution

Wesley C. Warren, Tyler E. Boggs, Richard Borowsky, Brian M. Carlson, Estephany Ferrufino, Joshua B. Gross, La Deana Hillier, Zhilian Hu, Alex C. Keene, Alexander Kenzior, Johanna E. Kowalko, Chad Tomlinson, Milinn Kremitzki, Madeleine E. Lemieux, Tina Graves-Lindsay, Suzanne E. McGaugh, Jeffrey T. Miller, Mathilda T.M. Mommersteeg, Rachel L. Moran, Robert PeußEdward S. Rice, Misty R. Riddle, Itzel Sifuentes-Romero, Bethany A. Stanhope, Clifford J. Tabin, Sunishka Thakur, Yoshiyuki Yamamoto, Nicolas Rohner

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


Identifying the genetic factors that underlie complex traits is central to understanding the mechanistic underpinnings of evolution. Cave-dwelling Astyanax mexicanus populations are well adapted to subterranean life and many populations appear to have evolved troglomorphic traits independently, while the surface-dwelling populations can be used as a proxy for the ancestral form. Here we present a high-resolution, chromosome-level surface fish genome, enabling the first genome-wide comparison between surface fish and cavefish populations. Using this resource, we performed quantitative trait locus (QTL) mapping analyses and found new candidate genes for eye loss such as dusp26. We used CRISPR gene editing in A. mexicanus to confirm the essential role of a gene within an eye size QTL, rx3, in eye formation. We also generated the first genome-wide evaluation of deletion variability across cavefish populations to gain insight into this potential source of cave adaptation. The surface fish genome reference now provides a more complete resource for comparative, functional and genetic studies of drastic trait differences within a species.

Original languageEnglish (US)
Article number1447
JournalNature communications
Issue number1
StatePublished - Dec 1 2021

Bibliographical note

Funding Information:
The authors would like to thank Karin Zueckert-Gaudenz and Mihaela Sardiu for technical assistance and the Stowers aquatics group for fish care and help with shipments of fish between NYU and Stowers. A.K., S.E.M., and N.R. are supported by NIH 1R01GM127872-01. This work was also supported by NIH R24OD011198 to W.C.W., L.H., E.S.R., T.G.-L., and M.K., NSF EDGE Award 1923372 to N.R., J.E.K., and S.E.M., NSF DEB-1754231 to J.E.K. and A.K., and NSF IOS-1933428 to J.E.K., S.E.M., and N.R. Author N.R. is further supported by institutional funding, funding from the Edward Mallinckrodt Foundation, and NIH DP2AG071466. J.E.K. is further supported by NIH R15HD099022. J.B.G. is supported by NIDCR R01-DE025033 and NSF DEB-1457630. Some computation for this work was performed on the high-performance computing infrastructure provided by Research Computing Support Services and in part by the National Science Foundation under grant number CNS-1429294 at the University of Missouri, Columbia, MO, USA. The Minnesota Supercomputing Institute at the University of Minnesota provided resources that contributed to the research results reported within this paper.

Publisher Copyright:
© 2021, The Author(s).


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