Abstract
The dramatic decline of reef-building corals calls for a better understanding of coral adaptation to ocean warming. Here, we characterize genetic diversity of the widespread genus Acropora by building a genomic database of 595 coral samples from different oceanic regions—from the Great Barrier Reef to the Persian Gulf. Through genome-environment associations, we find that different Acropora species show parallel evolutionary signals of heat-adaptation in the same genomic regions, pointing to genes associated with molecular heat shock responses and symbiosis. We then project the present and the predicted future distribution of heat-adapted genotypes across reefs worldwide. Reefs projected with low frequency of heat-adapted genotypes display higher rates of Acropora decline, indicating a potential genomic vulnerability to heat exposure. Our projections also suggest a transition where heat-adapted genotypes will spread at least until 2040. However, this transition will likely involve mass mortality of entire non-adapted populations and a consequent erosion of Acropora genetic diversity. This genetic diversity loss could hinder the capacity of Acropora to adapt to the more extreme heatwaves projected beyond 2040. Genomic vulnerability and genetic diversity loss estimates can be used to reassess which coral reefs are at risk and their conservation.
Data availability
Genomic data used in this study are publicly available in NCBI, for the full list of accession numbers and data links please see Supplementary Table 1. Processed data are available at Zenodo81 (https://doi.org/10.5281/zenodo.10838947). Supplementary Data 1 displays the list of the 85 genomic windows where genotype-environment associations were repeatedly found in different datasets.
Code availability
Code to reproduce the analysis is available at Zenodo81 (https://doi.org/10.5281/zenodo.10838947).
References
Souter, D. et al. Status of coral reefs of the world: 2020. (Australian government, United Nations Environment Program (UNEP), 2021).
Spalding, M., Ravilious, C. & Green, E. World atlas of coral reefs. (University of California Press, Berkeley, USA, 2001).
Dixon, G. B. et al. Genomic determinants of coral heat tolerance across latitudes. Science 348, 1460–1462 (2015).
Howells, E. J., Abrego, D., Meyer, E., Kirk, N. L. & Burt, J. A. Host adaptation and unexpected symbiont partners enable reef-building corals to tolerate extreme temperatures. Glob. Chang. Biol. 22, 2702–2714 (2016).
Selmoni, O. et al. Seascape genomics reveals candidate molecular targets of heat stress adaptation in three coral species. Mol. Ecol. 30, 1892–1906 (2021).
Thomas, L. et al. Spatially varying selection between habitats drives physiological shifts and local adaptation in a broadcast spawning coral on a remote atoll in Western Australia. Sci Adv 8, eabl9185 (2022).
Selmoni, O., Rochat, E., Lecellier, G., Berteaux-Lecellier, V. & Joost, S. Seascape genomics as a new tool to empower coral reef conservation strategies: An example on north-western Pacific Acropora digitifera. Evol. Appl. 13, 1923–1938 (2020).
Bay, R. A. & Palumbi, S. R. Multilocus adaptation associated with heat resistance in reef-building corals. Curr. Biol. 24, 2952–2956 (2014).
Fuller, Z. L. et al. Population genetics of the coral acropora millepora: Toward genomic prediction of bleaching. Science 369, eaba4674 (2020).
Cooke, I. et al. Genomic signatures in the coral holobiont reveal host adaptations driven by Holocene climate change and reef specific symbionts. Sci Adv 6, eabc6318 (2020).
Jin, Y. K. et al. Genetic markers for antioxidant capacity in a reef-building coral. Sci Adv 2, e1500842 (2016).
Selmoni, O., Bay, L. K., Exposito-Alonso, M. & Cleves, P. A. Finding genes and pathways that underlie coral adaptation. Trends Genet. 40, 213–227 (2024).
Skirving, W. et al. Coraltemp and the coral reef watch coral bleaching heat stress product suite version 3.1. Remote Sensing 12, 3856 (2020).
Riginos, C., Crandall, E. D., Liggins, L., Bongaerts, P. & Treml, E. A. Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies. Curr. Zool. 62, 581–601 (2016).
Rellstab, C., Dauphin, B. & Exposito-Alonso, M. Prospects and limitations of genomic offset in conservation management. Evol. Appl. 14, 1202–1212 (2021).
Rellstab, C., Gugerli, F., Eckert, A. J., Hancock, A. M. & Holderegger, R. A practical guide to environmental association analysis in landscape genomics. Mol. Ecol. 24, 4348–4370 (2015).
Booker, T. R., Yeaman, S. & Whitlock, M. C. Using genome scans to identify genes used repeatedly for adaptation. Evolution 77, 801–811 (2023).
Whiting, J. R. et al. The genetic architecture of repeated local adaptation to climate in distantly related plants. Nat. Ecol. Evol. 8, 1933–1947 (2024).
Torquato, F. et al. Population genetic structure of a major reef-building coral species Acropora downingi in northeastern Arabian Peninsula. Coral Reefs 41, 743–752 (2022).
Shinzato, C., Mungpakdee, S., Arakaki, N. & Satoh, N. Genome-wide SNP analysis explains coral diversity and recovery in the Ryukyu Archipelago. Sci. Rep. 5, 18211 (2015).
Drury, C. & Lirman, D. Genotype by environment interactions in coral bleaching. Proc. Biol. Sci. 288, 20210177 (2021).
Matz, M. V., Treml, E. A., Aglyamova, G. V. & Bay, L. K. Potential and limits for rapid genetic adaptation to warming in a Great Barrier Reef coral. PLoS Genet. 14, e1007220 (2018).
Sedlazeck, F. J., Rescheneder, P. & von Haeseler, A. NextGenMap: fast and accurate read mapping in highly polymorphic genomes. Bioinformatics 29, 2790–2791 (2013).
Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: Analysis of next generation sequencing data. BMC Bioinformatics 15, 356 (2014). 2014 15:11–13.
Exposito-Alonso, M. et al. Genetic diversity loss in the anthropocene. Science 377, 1431–1435 (2022).
García-Urueña, R., Kitchen, S. A. & Schizas, N. V. Fine scale population structure of Acropora palmata and acropora cervicornis in the colombian caribbean. PeerJ 10, e13854 (2022).
van der Ven, R. M., Ratsimbazafy, H. A. & Kochzius, M. Large-scale biogeographic patterns are reflected in the genetic structure of a broadcast spawning stony coral. Coral Reefs 41, 611–624 (2022).
Caye, K., Jumentier, B., Lepeule, J. & François, O. LFMM 2: Fast and accurate inference of gene-environment associations in genome-wide studies. Mol. Biol. Evol. 36, 852–860 (2019).
Selmoni, O., Lecellier, G., Berteaux-Lecellier, V. & Joost, S. The reef environment centralized information system (RECIFS): An integrated geo-environmental database for coral reef research and conservation. Glob. Ecol. Biogeogr. 32, 622–632 (2023).
Liu, G., Strong, A. E. & Skirving, W. Remote sensing of sea surface temperatures during 2002 Barrier Reef coral bleaching. Eos Trans. Amer. Geophys. Union 84, 137–141 (2003).
Selmoni, O., Vajana, E., Guillaume, A., Rochat, E. & Joost, S. Sampling strategy optimization to increase statistical power in landscape genomics: A simulation-based approach. Mol. Ecol. Resour. 20, 154–169 (2020).
Simillion, C., Liechti, R., Lischer, H. E. L., Ioannidis, V. & Bruggmann, R. Avoiding the pitfalls of gene set enrichment analysis with SetRank. BMC Bioinformatics 18, 151 (2017).
Dixon, G., Abbott, E. & Matz, M. Meta-analysis of the coral environmental stress response: Acropora corals show opposing responses depending on stress intensity. Mol. Ecol. 29, 2855–2870 (2020).
Rosenzweig, R., Nillegoda, N. B., Mayer, M. P. & Bukau, B. The Hsp70 chaperone network. Nat. Rev. Mol. Cell Biol. 20, 665–680 (2019).
Louis, Y. D. et al. Local acclimatisation-driven differential gene and protein expression patterns of Hsp70 in Acropora muricata: Implications for coral tolerance to bleaching. Mol. Ecol. 29, 4382–4394 (2020).
van Oppen, M. J. H. & Lough, J. M. Synthesis: Coral bleaching — Patterns, processes, causes and consequences. in coral bleaching: Patterns, processes, causes and consequences (eds. van Oppen, M. J. H. & Lough, J. M.) 175–176 (Springer berlin heidelberg, berlin, heidelberg, 2009).
Matthews, J. L. et al. Optimal nutrient exchange and immune responses operate in partner specificity in the cnidarian-dinoflagellate symbiosis. Proc. Natl. Acad. Sci. USA. 114, 13194–13199 (2017).
Matthews, J. L. et al. Partner switching and metabolic flux in a model cnidarian–dinoflagellate symbiosis. Proceedings of the Royal Society B: Biological Sciences 285, 20182336 (2018).
Hillyer, K. E., Dias, D., Lutz, A., Roessner, U. & Davy, S. K. 13C metabolomics reveals widespread change in carbon fate during coral bleaching. Metabolomics 14, 12 (2017).
Hillyer, K. E. et al. Metabolite profiling of symbiont and host during thermal stress and bleaching in the coral Acropora aspera. Coral Reefs 36, 105–118 (2017).
González-Pech, R. A. et al. Physiological factors facilitating the persistence of Pocillopora aliciae and Plesiastrea versipora in temperate reefs of south-eastern australia under ocean warming. Coral Reefs 41, 1239–1253 (2022).
Rädecker, N. et al. Heat stress destabilizes symbiotic nutrient cycling in corals. Proc. Natl. Acad. Sci. USA. 118, e2022653118 (2021).
Breiman, L. Random Forests. Mach. Learn. 45, 5–32 (2001).
Pinsky, M. L., Clark, R. D. & Bos, J. T. Coral Reef Population Genomics in an Age of Global Change. Annu. Rev. Genet. 57, 87–115 (2023).
Loya, Y. et al. Coral bleaching: the winners and the losers. Ecol. Lett. 4, 122–131 (2001).
van Woesik, R., Sakai, K., Ganase, A. & Loya, Y. Revisiting the winners and the losers a decade after coral bleaching. Mar. Ecol. Prog. Ser. 434, 67–76 (2011).
McClanahan, T. R. et al. Highly variable taxa-specific coral bleaching responses to thermal stresses. Mar. Ecol. Prog. Ser. 648, 135–151 (2020).
McClanahan, T. R. et al. Large geographic variability in the resistance of corals to thermal stress. Glob. Ecol. Biogeogr. 29, 2229–2247 (2020).
González-Rivero, M. et al. The catlin seaview survey – kilometre-scale seascape assessment, and monitoring of coral reef ecosystems. Aquat. Conserv. 24, 184–198 (2014).
Nakagawa, S., Johnson, P. C. D. & Schielzeth, H. The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded. J. R. Soc. Interface 14, 20170213 (2017).
Renema, W. et al. Are coral reefs victims of their own past success?. Sci Adv 2, e1500850 (2016).
Mellin, C. et al. Cumulative risk of future bleaching for the world’s coral reefs. Sci Adv 10, eadn9660 (2024).
Williams, D., Nedimyer, K., Bright, A. & Ladd, M. Genotypic inventory and impact of the 2023 marine heatwave on Acropora palmata (elkhorn coral) populations in the Upper Florida Keys, USA: 2020-2023 (National Oceanic and Atmospheric Administration, USA, 2024) https://doi.org/10.25923/37C0-X182.
Logan, C. A., Dunne, J. P., Ryan, J. S., Baskett, M. L. & Donner, S. D. Quantifying global potential for coral evolutionary response to climate change. Nat. Clim. Chang. 11, 537–542 (2021).
Fagan, W. F. & Holmes, E. E. Quantifying the extinction vortex. Ecol. Lett. 9, 51–60 (2006).
Andrello, M. et al. A global map of human pressures on tropical coral reefs. Conserv. Lett. 15, https://doi.org/10.1111/conl.12858 (2022).
Claar, D. C. et al. Dynamic symbioses reveal pathways to coral survival through prolonged heatwaves. Nat. Commun. 11, 6097 (2020).
UNEP-WCMC & IUCN. The World Database on Protected Areas (WDPA). (2020).
Beyer, H. L. et al. Risk-sensitive planning for conserving coral reefs under rapid climate change. Conserv. Lett. 11, e12587 (2018).
Drury, C. et al. Genomic patterns in Acropora cervicornis show extensive population structure and variable genetic diversity. Ecol. Evol. 7, 6188–6200 (2017).
Leinonen, R., Sugawara, H., Shumway, M. & Collaboration, I. N. S. D. The sequence read archive. Nucleic Acids Res. 39, D19–D21 (2010).
Andrews, S. FASTQC: A quality control tool for high throughput sequence data. (2010).
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
McKenna, A. et al. The genome analysis toolkit: A mapreduce framework for analyzing next-generation dna sequencing data. Genome Res. 20, 1297–1303 (2010).
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378–400 (2017).
Goudet, J. HIERFSTAT, a package for R to compute and test hierarchical F-statistics. Mol. Ecol. Notes 5, 184–186 (2005).
Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nat. Commun. 10, 1–5 (2019).
Liu, G. et al. Reef-Scale Thermal stress monitoring of coral ecosystems: New 5-km global products from noaa coral reef watch. Remote Sensing 6, 11579–11606 (2014).
Frichot, E. & François, O. L. E. A. An R package for landscape and ecological association studies. Methods Ecol. Evol. 6, 925–929 (2015).
Storey, J. D. The positive false discovery rate: A bayesian interpretation and the q-Value. Ann. Stat. 31, 2013–2035 (2003).
Camacho, C. et al. BLAST+: architecture and applications. BMC Bioinformatics 10, 421 (2009).
Bateman, A. et al. UniProt: A hub for protein information. Nucleic Acids Res. 43, D204–D212 (2015).
Spalding, M. D. et al. Marine ecoregions of the world: A bioregionalization of coastal and shelf areas. Bioscience 57, 573–583 (2007).
Barton, K. MuMIn: Multi-model inference. (2009).
Mann, H. B. & Whitney, D. R. On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50–60 (1947).
Unep-Wcmc, WorldFish Centre, World resources institute & the nature conservancy. Global distribution of warm-water coral reefs, compiled from multiple sources including the millennium coral reef mapping project. (UN environment world conservation monitoring centre, cambridge (UK), 2021).
Provoost, P., Bosch, S. & appletans, W. Robis: R client to access data from the OBIS API. (Ocean biogeographic information system. Intergovernmental oceanographic commission of UNESCO, 2017).
Hadfield, J. D. MCMC Methods for multi-response generalized linear mixed models: The MCMCglmm R Package. J. Stat. Softw. 33, 1–22 (2010).
Pinheiro, J., bates, D., Debroy, S. & Sarkar, D. Nlme: Nonlinear mixed-effects models. (2013).
Selmoni, O., Cleves, P. & Exposito-Alonso, M. Scripts and data from ‘global coral genomic vulnerability explains recent reef losses’. https://doi.org/10.5281/zenodo.10838947 (2024).
NOAA national centers for environmental information. ETOPO 2022 15 arc-second global relief Model. https://doi.org/10.25921/fd45-gt74 (2022).
Unep-Wcmc, WorldFish-Center, Wri & Tnc. Global distribution of warm-water coral reefs, compiled from multiple sources including the millennium coral reef mapping project. Version 4.1. http://data.unep-wcmc.org/datasets/1 (2021).
Acknowledgements
We are grateful to the openness of many researchers who make genomic data publicly available, making this research possible: Cooke et al., Drury et al., Fulle et al., Matz et al., Selmoni et al., Shinzato et al., and Torquato et al. We also thank the Catlin Seaview Survey project for collecting and giving access to the field survey data for the Acropora GBR case study, the Coral Reef Watch for giving access to the degree heating week data, the United Nations Environment Programme World Conservation Monitoring Centre for giving access to the worldwide distribution of coral reefs data, and Dixon et al. for sharing the Acropora gene expression data. We thank Rachael Bay and Stephane Joost for early discussions of coral datasets, and thank the MoiLab and Cleves lab for comments and discussions. M.E.-A. is supported by the Office of the Director of the National Institutes of Health’s Early Investigator Award (1DP5OD029506-01), the Carnegie Institution for Science, the Howard Hughes Medical Institute, and the University of California, Berkeley. Computational analyses were done on the High-Performance Computing clusters Memex, Calc, and MoiNode supported by the Carnegie Institution for Science. P.A.C. is supported by an NSF-EDGE grant (2128073), Pew Biomedical and Marine Fellowship (00036631), Revive and Restore, the Carnegie Institution for Science, and Moore Foundation grant (12187). We also thank a Carnegie Venture Grant (P.A.C. and M.E.-A.) for support.
Author information
Authors and Affiliations
Contributions
O.S., P.A.C., and M.E.-A. conceived and led the project. O.S. conducted research, O.S., P.A.C., and M.E.-A. interpreted the results and wrote the manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. A peer review file is available.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Description of Additional Supplementary Information
Supplementary Data 1
Transparent Peer Review file
Rights and permissions
Open Access 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.
Reprints and permissions
About this article
Cite this article
Selmoni, O., Cleves, P.A. & Exposito-Alonso, M. Global coral genomic vulnerability explains recent reef losses.
Nat Commun (2025). https://doi.org/10.1038/s41467-025-67616-5
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41467-025-67616-5
Source: Ecology - nature.com
