DNA methylation predicts age and provides insight into exceptional longevity of bats

Exceptionally long-lived species, including many bats, rarely show overt signs of aging, making it difficult to determine why species differ in lifespan. Here, we use DNA methylation (DNAm) profiles from 712 known-age bats, representing 26 species, to identify epigenetic changes associated with age and longevity. We demonstrate that DNAm accurately predicts chronological age. Across species, longevity is negatively associated with the rate of DNAm change at age-associated sites. Furthermore, analysis of several bat genomes reveals that hypermethylated age- and longevity-associated sites are disproportionately located in promoter regions of key transcription factors (TF) and enriched for histone and chromatin features associated with transcriptional regulation. Predicted TF binding site motifs and enrichment analyses indicate that age-related methylation change is influenced by developmental processes, while longevity-related DNAm change is associated with innate immunity or tumorigenesis genes, suggesting that bat longevity results from augmented immune response and cancer suppression.

Citation

Wilkinson , G S , Adams , D M , Haghani , A , Lu , A T , Zoller , J , Breeze , C E , Arnold , B D , Ball , H C , Carter , G G , Cooper , L N , Dechmann , D K N , Devanna , P , Fasel , N J , Galazyuk , A V , Günther , L , Hurme , E , Jones , G , Knörnschild , M , Lattenkamp , E Z , Li , C Z , Mayer , F , Reinhardt , J A , Medellin , R A , Nagy , M , Pope , B , Power , M L , Ransome , R D , Teeling , E C , Vernes , S C , Zamora-Mejías , D , Zhang , J , Faure , P A , Greville , L J & Horvath , S 2021 , ' DNA methylation predicts age and provides insight into exceptional longevity of bats ' , Nature Communications , vol. 12 , 1615 . https://doi.org/10.1038/s41467-021-21900-2

Publication

Nature Communications

Status

Peer reviewed

DOI

https://doi.org/10.1038/s41467-021-21900-2

ISSN

2041-1723

Type

Journal article

Rights

Copyright © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Description

This work was supported by a Paul G. Allen Frontiers Group grant to S.H., the University of Maryland, College of Computer, Mathematical and Natural Sciences to G.S.W., an Irish Research Council Consolidator Laureate Award to E.C.T., a UKRI Future Leaders Fellowship (MR/T021985/1) to S.C.V. and a Discovery Grant from the Natural Sciences and Engineering Research Council (NSERC) of Canada to P.A.F. S.C.V. and P.D. were supported by a Max Planck Research Group awarded to S.C.V. by the Max Planck Gesellschaft, and S.C.V. and E.Z.L. were supported by a Human Frontiers Science Program Grant (RGP0058/2016) awarded to S.C.V. L.J.G. was supported by an NSERC PGS-D scholarship.

Collections

University of St Andrews Research

URI

http://hdl.handle.net/10023/21641