Centre National de la Recherche Scientifique, Université Grenoble-Alpes, Grenoble INP, TIMC UMR 5525, 38000 Grenoble, France.
DIADE, Université de Montpellier, Institut de Recherche pour le Développement, French Agricultural Research Centre for International Development (CIRAD), Montpellier, France.
Mol Biol Evol. 2023 Jun 1;40(6). doi: 10.1093/molbev/msad140.
Genomic offset statistics predict the maladaptation of populations to rapid habitat alteration based on association of genotypes with environmental variation. Despite substantial evidence for empirical validity, genomic offset statistics have well-identified limitations, and lack a theory that would facilitate interpretations of predicted values. Here, we clarified the theoretical relationships between genomic offset statistics and unobserved fitness traits controlled by environmentally selected loci and proposed a geometric measure to predict fitness after rapid change in local environment. The predictions of our theory were verified in computer simulations and in empirical data on African pearl millet (Cenchrus americanus) obtained from a common garden experiment. Our results proposed a unified perspective on genomic offset statistics and provided a theoretical foundation necessary when considering their potential application in conservation management in the face of environmental change.
基因组偏移统计基于基因型与环境变化的关联,预测种群对快速生境改变的适应不良。尽管有大量经验有效性的证据,但基因组偏移统计存在明显的局限性,并且缺乏有助于解释预测值的理论。在这里,我们澄清了基因组偏移统计与由环境选择位点控制的未观察到的适应性状之间的理论关系,并提出了一种几何度量来预测局部环境快速变化后的适应度。我们的理论预测在计算机模拟和来自共同花园实验的非洲珍珠粟(Cenchrus americanus)的经验数据中得到了验证。我们的研究结果提出了一个关于基因组偏移统计的统一观点,并为在面对环境变化时考虑其在保护管理中的潜在应用提供了必要的理论基础。