Moises A. Bernal ^1,2, Celia Schunter^1,3, Robert Lehmann¹, Damien J. Lightfoot¹, Birdie J. M. Allan^4,5, Heather D. Veilleux^5,6, Jodie L. Rummer⁵, Philip L. Munday⁵, Timothy Ravasi⁷

1. Division of Biological and Environmental Sciences & Engineering, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Kingdom of Saudi Arabia
2. Department of Biological Sciences, College of Science and Mathematics, Auburn University, Auburn, AL 36849, USA
3. Swire Institute of Marine Science, School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
4. Department of Marine Science, University of Otago, Dunedin 9054, New Zealand
5. Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland 4811, Australia
6. Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2R3, Canada
7. Marine Climate Change Unit, Okinawa Institute of Science and Technology Graduate University, 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan

Science Advances 2020, 6(12), eaay3423. doi: DOI: 10.1126/sciadv.aay342

The marine heatwave of 2016 was one of the longest and hottest thermal anomalies recorded on the Great Barrier Reef, influencing multiple species of marine ectotherms, including coral reef fishes. There is a gap in our understanding of what the physiological consequences of heatwaves in wild fish populations are. Thus, in this study, we used liver transcriptomes to understand the molecular response of five species to the 2016 heatwave conditions. Gene expression was species specific, yet we detected overlap in functional responses associated with thermal stress previously reported in experimental setups. The molecular response was also influenced by the duration of exposure to elevated temperatures. This study highlights the importance of considering the effects of extreme warming events when evaluating the consequences of climate change on fish communities.

• OrthologAlignment.fa: Multiple Sequence Alignment of orthologous gene sequences
• OrthologAlignment.raxml: Phylogeny obtained from the alignment using RAxML Next Generation, model LG+G4, ml search over 50 random and 50 parsimony-based starting trees, with bootstrap support.