A gene-regulatory network model for density-dependent and sex-biased dispersal evolution during range expansions
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Abstract
Dispersal is key to understanding ecological and evolutionary dynamics. Dispersal may itself evolve and exhibit phenotypic plasticity. Specifically, organisms may modulate their dispersal rates in response to the density of their conspecifics (density-dependent dispersal) and their own sex (sex-biased dispersal). While optimal dispersal plastic responses have been derived from first principles, the genetic and molecular basis of dispersal plasticity has not been modelled. An understanding of the genetic architecture of dispersal plasticity is especially relevant for understanding dispersal evolution during rapidly changing spatial ecological conditions such as range expansions. In this context, we develop an individual-based metapopulation model of the evolution of density-dependent and sex-biased dispersal during range expansions. We represent the dispersal trait as a gene-regulatory network (GRN), which can take population density and an individual's sex as an input and analyse emergent context- and condition-dependent dispersal responses. We compare dispersal evolution and ecological dynamics in this GRN model to a standard reaction norm (RN) approach under equilibrium metapopulation conditions and during range expansions. We find that under equilibrium metapopulation conditions, the GRN model produces emergent density-dependent and sex-biased dispersal plastic response shapes that match the theoretical expectation of the RN model. However, during range expansion, when mutation effects are large enough, the GRN model leads to faster range expansion because GRNs can maintain higher adaptive potential. Our results imply that, in order to understand eco-evolutionary dynamics in contemporary time, the genetic architecture of traits must be taken into account.
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Natural populations rarely experience a uniform environment. Local density, resource availability, and mating opportunities often vary considerably across a population range. Theory has shown that such heterogeneity favours the evolution of density-dependent dispersal in the form of dispersal reaction norms. These models typically assume a simple genetic basis, with dispersal reaction norms encoded by a single Mendelian locus. Yet, dispersal plasticity is presumably controlled by more complex genetic architectures. Early work by Ezoe and Iwasa (1997) illustrated how evolved neural networks could generate dispersal reaction norms very similar to those predicted by Mendelian genetics.In their manuscript, Deshpande and Fronhofer (2023) build on this work by examining how different genetic architectures influence the evolution of …Natural populations rarely experience a uniform environment. Local density, resource availability, and mating opportunities often vary considerably across a population range. Theory has shown that such heterogeneity favours the evolution of density-dependent dispersal in the form of dispersal reaction norms. These models typically assume a simple genetic basis, with dispersal reaction norms encoded by a single Mendelian locus. Yet, dispersal plasticity is presumably controlled by more complex genetic architectures. Early work by Ezoe and Iwasa (1997) illustrated how evolved neural networks could generate dispersal reaction norms very similar to those predicted by Mendelian genetics.In their manuscript, Deshpande and Fronhofer (2023) build on this work by examining how different genetic architectures influence the evolution of dispersal plasticity and its ecological consequences. They compare dispersal plasticity encoded either by a classical reaction norm controlled by a single Mendelian locus or by a gene-regulatory network following the Wagner model, where several interacting regulatory genes respond to local density cues and the individual's sex to determine dispersal probability.Under stable conditions, both architectures successfully reproduce classical patterns of density- and sex-dependent dispersal. However, a clear difference emerges once populations expand into new, empty territories. Evolved gene-regulatory networks harbour substantially more cryptic genetic variation, which is revealed under these changing conditions. Previously hidden variation becomes exposed to selection at the expanding front, where low-density conditions create novel selective pressures. As a result, dispersal increases significantly, accelerating range expansions compared to the simpler, single-locus architectures.These findings highlight how the genetic architecture of ecologically relevant traits, such as dispersal, not only shapes range dynamics but can also influence how populations respond to the demographic and environmental shifts encountered during expansion. By demonstrating that gene-regulatory networks facilitate faster range expansions due to their ability to store and later reveal cryptic genetic variation, Deshpande and Fronhofer take a useful step toward integrating genetic complexity into eco-evolutionary models.ReferencesEzoe, H. and Iwasa, Y. (1997), Evolution of condition-dependent dispersal: A genetic-algorithm search for the ESS reaction norm. Popul Ecol, 39: 127-137. https://doi.org/10.1007/BF02765258Jhelam N. Deshpande, Emanuel A. Fronhofer (2023) A gene-regulatory network model for density-dependent and sex-biased dispersal evolution during range expansions. bioRxiv, ver.4 peer-reviewed and recommended by PCI Evol Biol -
