Comparative study highlights how gene flow shapes adaptive genomic architecture

Adaptation to environmental conditions, and the mechanisms underlying these adaptations, can vary greatly among species. This variation can be attributed to a variety of factors including the strength of evolutionary processes like selection, gene flow, time since divergence, and/or genetic drift, as well as the interactions between these processes. A number of simulation and theoretical studies have helped elucidate the role of these processes on the genomic basis of adaptation (Schaal et al., 2022; Yeaman et al., 2016). However, complementary empirical studies to test these theoretical expectations for within-species adaptation have been limited due to the challenging nature of evaluating these processes in a comparative framework. To do this effectively, it is necessary to have systems where the range of environmental variation is similar between species, but where one or more of these evolutionary processes vary. In a From the Cover article in this issue of Molecular Ecology, Shi et al. (2022) provide an excellent example of a freshwater system where rates of gene flow differ between populations of six riverine species due to variation in spawning strategies (i.e., broadcast spawners = high gene flow, nest spawners = low gene flow), but all experience the same variation in environmental conditions across their distributions. The authors take a multivariate approach to evaluate the genomic basis of adaptation by using a combination of differentiation-based and genotype-environment association (GEA) methods. By comparing the amount of gene flow between species and the resulting genomic basis of local adaptation, they are able to infer how genomic architecture may be shaped by rates of gene flow. Their results identify a general pattern of increased genomic clustering in species with increasing levels of gene flow. However, two of six species did not follow this pattern, which could be due to additional factors not assessed. Additionally, they provide convincing evidence that the underlying evolutionary mechanisms that formed genomic clusters within each species vary. These deviations from a general pattern highlight how difficult evaluating these processes in natural populations are, particularly because species-specific responses can vary dramatically. Taken together, their comparative framework for assessing the genomic architecture of adaptation is unique, sheds important light on how evolutionary processes can impact adaptation, and provides robust empirical support of foundational theoretical and simulation studies.

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