Genomic forecasting for climate‐resilient fruit trees
Year: 2026
Type: article
Abstract: Fruit trees - long-lived perennial crops cultivated for their edible fruits or nuts and frequently propagated clonally - are increasingly exposed to climate extremes that threaten their productivity and survival. Yet their capacity to adapt to rapid environmental change remains poorly understood. We argue that fruit trees and their wild relatives are powerful but underused systems for advancing genomic forecasting in perennials, with a focus on genomic offset analyses. Genomic offset estimates the mismatch between current genomic variation and that predicted to be optimal under future climates, offering a promising framework to anticipate maladaptation and guide conservation, breeding, and management strategies. Although its application is expanding rapidly in annual crops and forest trees, its interpretation and predictive value remain actively debated and require stronger empirical validation. Fruit trees are particularly well suited to address these challenges as they combine distinctive biology - including long generation times, clonal propagation and intensive management practices - with expanding genomic resources and common garden networks. Using emblematic Mediterranean and temperate species, we outline a roadmap that combines genomic offset with common-garden networks, high-resolution climate data, and trait-based fitness proxies. Together, these resources position fruit trees as an powerful model to evaluate and refine genomic forecasting into a practical tool for biodiversity-informed breeding and conservation under global change, and better understand plant adaptation and maladaptation processes.
Source: New Phytologist
DOI: 10.1111/nph.71352
Authors: Maxime Criado, Mathieu Brisson, Karine Alix, Yann X.C. 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, Institut de Recherche pour le Développement, Institut polytechnique de Grenoble, Translational Innovation in Medicine and Complexity, Université Grenoble Alpes, New York University Abu Dhabi
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $5,790
Funders: New York University Abu Dhabi, York University, Agence Nationale de la Recherche, BNP Paribas Cardif, Centre National de la Recherche Scientifique, AgroParisTech, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Tamkeen, Université de Versailles Saint-Quentin-en-Yvelines, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Directorate for Biological Sciences, Fondation BNP Paribas
OpenAlex ID: W7166827563
