Linking genomic offset statistics to the shape of selection gradients

Genomic offset metrics are increasingly used to predict population maladaptation under changing climates, based on the assumption of a negative statistical relationship between offset measures and local relative fitness. Recent theoretical advances have confirmed this relationship by relating genomic offset to phenotypic trait distances along selection gradients. However, these metrics typically rely on the assumption that stabilizing selection, which maintains local adaptive optima, operates on fitness-related traits through Gaussian-shaped selection gradients. In this study, we extend the theory to accommodate more diverse forms of selection gradients and introduce more general genomic offset measures that preserve the fitness-offset relationship. We validate this generalization through simulations and demonstrate the utility of these new measures in predicting relative fitness in common garden experiments involving three plant species: pearl millet, a vital staple cereal grown in ari..., The ⍺-GO statistics and their relationship with the geometric GO were first tested using simulations. Spatially explicit individual-based simulations were performed using SLiM 3.7 (Haller and Messer 2019), as described for the highly polygenic scenario in Gain and colleagues (2023). Briefly, each individual genome contained both neutral and adaptive mutations, the latter ones being under local stabilizing selection from a 2D environment (12x12 grid) with two orthogonal environmental gradients, (x1, x2). Two traits, (z1, z2), controlled by 120 adaptive mutations with additive effects, were matched to each causal environmental variable by local stabilizing selection. The probability of survival of an individual genome in the next generation was calculated as the product of density regulation and fitness. The density of individuals was regulated by spatial competition depending on the number of individuals within a circle with radius S = 0.8 (Haller and Messer 2019). Individual fitness was..., , # GENERAL INFORMATION

This README.txt file was updated on May 12th 2025 by Thibaut Capblancq

### Paper associated with this archive

This repository contains the data necessary to reproduce the results of the article \"Linking genomic offset statistics to the shape of selection gradients\", written by Thibaut Capblancq, Aurlien Tauzin, Yves Vigouroux, Philippe Cubry and Olivier Franois and published in 2025 in the journal*The American Naturalist* for a special feature on Genomic Forecasting.

### Originators

Thibaut CAPBLANCQ (1), Aurélien TAUZIN (1), Yves VIGOUROUX (2), Philippe CUBRY (2) and Olivier FRANÇOIS (1)

(1) *TIMC, Centre National de la Recherche Scientifique, Université Grenoble-Alpes, Grenoble INP, Grenoble, France*

(2) *DIADE, Université de Montpellier, Institut de Recherche pour le Développement, Montpellier, France*

### Contact information

Capblancq Thibaut: [[e-mail]](mailto:[e-mail])

Olivier FRANÇOIS:...,