How organisms adapt to their environment is not only a central topic of evolutionary biology but also a pressing question in the light of recent global change. Unravelling the genetic basis of these local adaptations can help to predict the response of a population to an increase in temperature or the more frequent occurrence of droughts. A popular approach to study the genes that drive local adaptation is the analysis of genotype-environment associations (GEA), testing the correlation of genomic features (typically single-nucleotide polymorphisms, SNPs) and environmental conditions. In this issue of Molecular Ecology Resources, Booker et al. (Molecular Ecology Resources, 2023) present a new approach to GEA, introducing genomic window analysis. They combine the information of neighbouring SNPs instead of analysing each SNP independently, therefore gaining power for detecting genomic signals of environmental adaptation. Using simulations of local adaptation to a heterogeneous environment as well as previously published real data from a natural population of lodgepole pine, they prove the superiority of their method over several established GEA approaches, especially in the case of small sample sizes. Leveraging the information present in closely linked genomic sites, Booker et al. (Molecular Ecology Resources, 2023) take genotype-environment association studies to the next level.
Keywords: adaptation; ecological genetics; genomics; landscape genetics.
© 2023 The Authors. Molecular Ecology Resources published by John Wiley & Sons Ltd.