Modelling multilocus selection in an individual‐based, spatially‐explicit landscape genetics framework

Abstract

We implemented multilocus selection in a spatially‐explicit, individual‐based framework that enables multivariate environmental gradients to drive selection in many loci as a new module for the landscape genetics programs, CDPOP and CDMetaPOP. Our module simulates multilocus selection using a linear additive model, providing a flexible platform to evaluate a wide range of genotype‐environment associations. Importantly, the module allows simulation of selection in any number of loci under the influence of any number of environmental variables. We validated the module with individual‐based selection simulations under Wright‐Fisher assumptions. We then evaluated results for simulations under a simple landscape selection model. Next, we simulated individual‐based multilocus selection across a complex selection landscape with three loci linked to three different environmental variables. Finally, we demonstrated how the program can be used to simulate multilocus selection under varying selection strengths across different levels of gene flow in a landscape genetics framework. This new module provides a valuable addition to the study of landscape genetics, allowing for explicit evaluation of the contributions and interactions between gene flow and selection‐driven processes across complex, multivariate environmental and landscape conditions.

Genome sequencing and population genomics modeling provide insights into the local adaptation of weeping forsythia

“…Importantly, however, our results strongly suggest that the adaptive differentiation of genes related to multiple metabolic pathways occurred in the genome of natural plant populations under multiple abiotic selection pressures. Our study gives us substantial insight into the genetic basis of the local adaptation of F. suspensa, which should form the foundation for more thorough confirmatory work in common garden experiments 9 and simulation modeling 50 .…”

Morphological Differences in Pinus strobiformis Across Latitudinal and Elevational Gradients

“…Given the difficulty of reliably isolating drivers and apportioning explanatory variance among them with either observational or common garden experiments on longlived tree species, we also recommend the use of simulation modeling (e.g., Landguth and Cushman, 2010;Landguth et al, 2017). Specifically, employing an individual-based, spatially explicit eco-evolutionary model (e.g., Landguth et al, 2020) to simulate the interactions of different degrees of gene flow, drift, environmental selection and phenotypic plasticity provides a unique means to explore the potential interactions of these factors and quantify the patterns of genomic and phenotypic variation that can be expected under these interactions (e.g., Cushman, 2015;Cushman and Landguth, 2016).…”

MetaPopGen 2.0: A multilocus genetic simulator to model populations of large size

“…Memory needs and computation time increase with the number of loci simulated, because the numbers of possible unique gametes and genotypes increase geometrically with the number of loci and alleles per locus (Box 2), and increasing the number of classes entails a parallel increase in computation time. The comparison of computation times between MetaPopGen 2.0 and Nemo 2.2.0 suggests that, in order to simulate adaptive dynamics in small populations with more than a few loci, individual‐based simulators like Aladyn (Schiffers & Travis, 2014), Nemo and quantiNemo (Guillaume & Rougemont, 2006; Neuenschwander et al., 2008, 2019) or CDPOP and CDMetaPOP (Landguth et al., 2017, 2020; Landguth & Cushman, 2010) are still the best option. However, numerous species show phenotypic traits under the control of a few loci only (Courtier‐Orgogozo et al., 2020) and some of these traits are related to fitness and local adaptation.…”