Genomic signatures of climate-driven (mal)adaptation in an iconic conifer, the English yew ( Taxus baccata L.)

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Abstract
The risk of climate maladaptation is increasing for numerous species, including trees. Developing robust methods to assess population maladaptation remains a critical challenge. Genomic offset approaches aim to predict climate maladaptation by characterising the genomic changes required for populations to maintain their fitness under changing climates. In this study, we assessed the risk of climate maladaptation in European populations of English yew ( Taxus baccata ), a long-lived tree with a patchy distribution across Europe, the Atlas Mountains, and the Near East, where many populations are small or threatened. We found evidence suggesting local climate adaptation by analysing 8,616 SNPs in 475 trees from 29 European T. baccata populations, with climate explaining 18.1% of genetic variance and 100 unlinked climate-associated loci identified via genotype-environment association (GEA). Then, we evaluated the deviation of populations from the overall gene-climate association to assess variability in local adaptation or different adaptation trajectories across populations and found the highest deviations in low latitude populations. Moreover, we predicted genomic offsets and successfully validated these predictions using fitness proxies assessed in plants from 26 populations grown in a comparative experiment. Finally, we integrated information from current local adaptation, genomic offset, historical genetic differentiation and effective migration rates to show that Mediterranean and high-elevation T. baccata populations face higher vulnerability to climate change than low-elevation Atlantic and continental populations. Our study demonstrates the practical use of the genomic offset framework in conservation genetics, offers insights for its further development, and highlights the need for a population-centred approach that incorporates additional statistics and data sources to credibly assess climate vulnerability in wild plant populations.
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Funding Information
  • H2020 GENTREE (676876)
  • H2020 FORGENIUS (862221)
  • TAXUS (CGL2007-63107/BOS)
  • ADAPCON (CGL2011‐30182‐C02‐02)
  • READAPT (PID2020-112738GB-I00)
  • Taxol-GR (MIS5004922)
  • Slovenian Research Agency (P4-0107)
  • MedForAct (GA 101107604)

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