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Temperature-specific repeatability of evolution and its implications for genomic predictions of adaptation to warming

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DataONE2025-03-20 更新2025-04-26 收录
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Climate warming is threatening biodiversity by increasing temperatures beyond the optima of many ectotherms. Due to the inherent non-linear relationship between temperature and the rate of cellular processes, such shifts towards hot temperature are predicted to impose stronger selection compared to corresponding shifts toward cold temperature. This suggests that when adaptation to warming occurs, it should be relatively rapid and predictable. Here, we tested this hypothesis from the level of single-nucleotide polymorphisms to life-history traits in the beetle Callosobruchus maculatus. We conducted an evolve-and-resequence experiment on three genetic backgrounds of the beetle reared at hot or cold temperatures. Indeed, we find that phenotypic evolution was faster and more repeatable at hot temperatures. However, at the genomic level, adaptation to heat was less repeatable when compared across genetic backgrounds. As a result, genomic predictions of phenotypic adaptation in populations ex..., , , # Temperature-specific repeatability of evolution and its implications for genomic predictions of adaptation to warming --- This dataset consists of phenotypic data from an experiment used to quantify the predictability of evolution in the seed beetle *Callosobruchus maculatus* under different thermal regimes. Three main `R` scripts were used to run the analyses. ## Dataset Version and Release History * Current Version: * Number: 1.0.0 * Date: 2024-9-23 * Persistent identifier: DOI: * Summary of changes: n/a ## Description of the Data and file structure **Phenotypic data:** The raw population-mean phenotypic data for 7 life-history traits (amongst other traits not used in the analysis) are in the text file titled `TotalScaled_newerr.txt`. Each row is a population, designated by its geographic origin (`pop`), replicate number (`rep`), and thermal regime (`selection`). The relevant columns for the analysis are lifetime reproductive success (`LRS`: total offspring produced), ...,
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2025-03-21
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