Alexandre Rego, Julian Baur, Camille Girard-Tercieux, Maria de la Paz Celorio-Mancera, Rike Stelkens, David Berger
{"title":"Strong Selection, but low repeatability: Temperature-specific effects on genomic predictions of adaptation","authors":"Alexandre Rego, Julian Baur, Camille Girard-Tercieux, Maria de la Paz Celorio-Mancera, Rike Stelkens, David Berger","doi":"10.1101/2024.09.12.612579","DOIUrl":null,"url":null,"abstract":"Evolution should be more predictable when natural selection is strong and favors the same outcome. Climate warming is increasing temperatures beyond the optima of many ectotherms, which, due to the inherent non-linear relationship between temperature and the rate of cellular processes, is predicted to impose stronger selection compared to corresponding shifts toward cold temperatures. This suggests that adaptation to climate warming should be relatively predictable. Here, we tested this hypothesis from the level of single-nucleotide polymorphisms to life-history traits, by conducting an evolve-and-resequence experiment on three genetic backgrounds of the seed beetle, Callosobruchus maculatus. Indeed, phenotypic evolution was faster and more repeatable at hot, relative to cold, temperature. However, at the genomic level, adaptation to heat was less repeatable than to cold, especially when comparing responses between backgrounds. As a result, genomic predictions of phenotypic (mal)adaptation in populations exposed to hot temperature were highly accurate within, but inaccurate between, genetic backgrounds. These results seem best explained by an increased importance of epistasis during adaptation to heat and imply that the same biophysical mechanisms that increase the repeatability of phenotypic evolution by exerting strong selection at hot temperature, reduce repeatability at the genome level. Thus, predictions of adaptation in key phenotypes from genomic data may become increasingly difficult as climates warm.","PeriodicalId":501183,"journal":{"name":"bioRxiv - Evolutionary Biology","volume":"37 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv - Evolutionary Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.12.612579","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Evolution should be more predictable when natural selection is strong and favors the same outcome. Climate warming is increasing temperatures beyond the optima of many ectotherms, which, due to the inherent non-linear relationship between temperature and the rate of cellular processes, is predicted to impose stronger selection compared to corresponding shifts toward cold temperatures. This suggests that adaptation to climate warming should be relatively predictable. Here, we tested this hypothesis from the level of single-nucleotide polymorphisms to life-history traits, by conducting an evolve-and-resequence experiment on three genetic backgrounds of the seed beetle, Callosobruchus maculatus. Indeed, phenotypic evolution was faster and more repeatable at hot, relative to cold, temperature. However, at the genomic level, adaptation to heat was less repeatable than to cold, especially when comparing responses between backgrounds. As a result, genomic predictions of phenotypic (mal)adaptation in populations exposed to hot temperature were highly accurate within, but inaccurate between, genetic backgrounds. These results seem best explained by an increased importance of epistasis during adaptation to heat and imply that the same biophysical mechanisms that increase the repeatability of phenotypic evolution by exerting strong selection at hot temperature, reduce repeatability at the genome level. Thus, predictions of adaptation in key phenotypes from genomic data may become increasingly difficult as climates warm.