Genomic forecasting links climate-associated variation to spring phenology in the European wild apple, a crop wild relative of the cultivated apple

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 R2 = 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

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-10-31
DOI
https://doi.org/10.64898/2026.10.29.761786
Primary Topic
Genetic diversity and population structure
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Genomic forecasting links climate-associated variation to spring phenology in the European wild apple, a crop wild relative of the cultivated apple

Yann Bourgeois, Tudor‐Mihai Ursu, Frédérique Didelot, Stéphane Bazot et al.
bioRxiv (Cold Spring Harbor Laboratory)
Genetic diversity and population structure
preprint

Genomic forecasting links climate-associated variation to spring phenology in the European wild apple, a crop wild relative of the cultivated apple

Yann Bourgeois, Tudor‐Mihai Ursu, Frédérique Didelot, Stéphane Bazot, Amandine Cornille, Dana Şuteu, Aurélie Mesnil, Komlan Avia, Somia Saidi, Anthony Venon, Johann Confais, Marni Brisson, Anamaria Roman, Arnaud Lemarquand, Thomas Kirisits, Olivier François, Elodie Marchadier, Maxime Criado, Alexis Rodriguez, Gaelle Vincent
preprint en

Abstract

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 R2 = 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.

bioRxiv (Cold Spring Harbor Laboratory)
Institut polytechnique de Grenoble (FR), New York University Abu Dhabi (AE), Centre National de la Recherche Scientifique (FR), AgroParisTech (FR), Université Paris-Saclay (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Ecologie, Société, Evolution (FR), Génétique Quantitative et Évolution Le Moulon (FR), National Institute of Research and Development for Biological Sciences (RO), Santé de la Vigne et Qualité du Vin (FR), Translational Innovation in Medicine and Complexity (FR), Institut de Recherche pour le Développement (FR), Unité Expérimentale de Recherches Intégrées en arboriculture fruitière - Gotheron (FR), Unité Expérimentale Horticole (FR), Université de Strasbourg (FR), Université Grenoble Alpes (FR), BOKU University (AT)
Genetic diversity and population structure
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon