Genomic forecasting links climate-associated variation to spring phenology in the European wild apple, a crop wild relative of the cultivated apple
Year: 2026
Type: preprint
Abstract: Background Climate-associated genomic variation is often used as a proxy for adaptive potential, yet whether it reflects adaptation with phenotypic consequences, rather than demography alone, is rarely tested in long-lived species. Genomic offsets forecast climate maladaptation from genotype–environment models but are seldom validated against phenotypes. We combined whole-genome resequencing, SNP and transposable element insertion polymorphism (TIP) variation, landscape genomics, genome-wide association, genomic offset, and common-garden phenotyping in the European wild apple ( Malus sylvestris Mill.), a crop wild relative with a complex demographic history, to test this. Results Of 148 resequenced accessions (135 wild, 13 cultivated), 89 wild individuals formed the core dataset. Population structure was associated with Last Glacial Maximum precipitation rather than contemporary climate, and genetic diversity increased from west to east. Genome–environment associations across 9.75 million SNPs identified climate-associated loci enriched in photoperiod-related flowering-time genes, with limited overlap with phenotype-associated loci. SNP-based genomic offset was associated with bud-break timing in the Saclay common garden (marginal R 2 = 0.31), with higher offsets corresponding to earlier bud break, but not with growth or ecophysiological traits. This association depended on Austrian and Romanian populations and was clearest in non-admixed wild individuals. Offsets based on TIPs or glacial climate did not predict measured phenotypes. Conclusions Climate association, phenotypic relevance, and predictive power of genomic variation are separable. In a long-lived tree, genomic offset predicted spring phenology, a key adaptive trait, but this signal varied across provenances and ancestries and was absent for transposable elements. Genomic offsets can therefore forecast potential phenological maladaptation, provided they are validated against phenotypes such as bud break.
Authors: Maxime Criado, Aurélie Mesnil, Somia Saidi, Anthony Venon, Komlan Avia, Johann Confais, Anamaria Roman, Tudor-Mihai Ursu, Dana Șuteu, Alexis Rodriguez, Thomas Kirisits, Mathieu Brisson, Frédérique Didelot, Arnaud Lemarquand, Stéphane Bazot, Gaëlle Vincent, Yann Bourgeois, Olivier François, Élodie Marchadier, Amandine Cornille
Institutions: Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Génétique Quantitative et Évolution Le Moulon, New York University Abu Dhabi, Santé de la Vigne et Qualité du Vin, Université de Strasbourg, National Institute of Research and Development for Biological Sciences, Unité Expérimentale de Recherches Intégrées en arboriculture fruitière - Gotheron, Institute of Forest Ecology of the Slovak Academy of Sciences, Unité Expérimentale Horticole, Ecologie, Société, Evolution, Institut de Recherche pour le Développement, Institut polytechnique de Grenoble, Translational Innovation in Medicine and Complexity, Université Grenoble Alpes
Language: English
Subfield: Genetics
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
Funders: New York University Abu Dhabi, Equipex, Institut Français de Bioinformatique, Agence Nationale de la Recherche, BNP Paribas Cardif, Conseil Régional, Île-de-France, Centre National de la Recherche Scientifique, Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii, Tamkeen, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Fondation BNP Paribas
OpenAlex ID: W7225018348