The African Turquoise Killifish Genome Provides Insights into Evolution and Genetic Architecture of Lifespan

Dario Riccardo Valenzano*, Bérénice A. Benayoun, Param Priya Singh, Elisa Zhang, Paul D. Etter, Chi Kuo Hu, Mathieu Clément-Ziza, David Willemsen, Rongfeng Cui, Itamar Harel, Ben E. MacHado, Muh Ching Yee, Sabrina C. Sharp, Carlos D. Bustamante, Andreas Beyer, Eric A. Johnson, Anne Brunet

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

142 Scopus citations

Abstract

Summary Lifespan is a remarkably diverse trait ranging from a few days to several hundred years in nature, but the mechanisms underlying the evolution of lifespan differences remain elusive. Here we de novo assemble a reference genome for the naturally short-lived African turquoise killifish, providing a unique resource for comparative and experimental genomics. The identification of genes under positive selection in this fish reveals potential candidates to explain its compressed lifespan. Several aging genes are under positive selection in this short-lived fish and long-lived species, raising the intriguing possibility that the same gene could underlie evolution of both compressed and extended lifespans. Comparative genomics and linkage analysis identify candidate genes associated with lifespan differences between various turquoise killifish strains. Remarkably, these genes are clustered on the sex chromosome, suggesting that short lifespan might have co-evolved with sex determination. Our study provides insights into the evolutionary forces that shape lifespan in nature.

Original languageAmerican English
Pages (from-to)1539-1554
Number of pages16
JournalCell
Volume163
Issue number6
DOIs
StatePublished - 3 Dec 2015
Externally publishedYes

Bibliographical note

Funding Information:
We thank Robert Piskol, Duygu Ucar, Erik Lenhert, Joanna Kelley, and Julian Catchen for their help with genome analysis. We thank Jonathan Pritchard and Yang Li for helping with evolutionary analyses, statistics, and the manuscript. We thank Dmitri Petrov and David Enard for their help with the evolutionary analysis. We thank Art Owen for his help with statistics. We thank David Kingsley, Felicity Jones, and Frank Chan for helping with QTL analysis and the manuscript. We thank members of the Brunet lab for help on the manuscript. We thank Aaron Daugherty, Ben Dulken, Katja Hebestreit, Andrew McKay, and Robin Yeo for helping with independent code verification. We thank Aimee Kao for helpful discussion about GRN. This work was supported by NIH DP1AG044848 (A. Brunet), the Glenn Laboratories for the Biology of Aging (A. Brunet.), the Max Planck Society and the Max Planck Institute for Biology of Ageing (D.R.V., D.W. and R.C.), the Dean’s fellowship at Stanford and NIH K99AG049934 (B.A.B.), the Stanford Center for Computational Evolutionary and Human Genomics fellowship (P.P.S.), the Life Sciences Research Foundation fellowship (C.K.H.), the Damon Runyon, Rothschild, and HFSP fellowships (I.H.), and the German Federal Ministry of Education and Research (A. Beyer., M.C.Z., Grant: Sybacol).

Publisher Copyright:
© 2015 Elsevier Inc.

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