Data from: What affects the predictability of evolutionary constraints using a G-matrix? The relative effects of modular pleiotropy and mutational correlation
Chebib, Jobran, University of Zurich
Guillaume, Frédéric, University of Zurich
Published Jul 25, 2017 on Dryad.
Cite this dataset
Chebib, Jobran; Guillaume, Frédéric (2017). Data from: What affects the predictability of evolutionary constraints using a G-matrix? The relative effects of modular pleiotropy and mutational correlation [Dataset]. Dryad. https://doi.org/10.5061/dryad.3qs54
Phenotypic traits do not always respond to selection independently from each other and often show correlated responses to selection. The structure of a genotype-phenotype map (GP map) determines trait covariation, which involves variation in the degree and strength of the pleiotropic effects of the underlying genes. It is still unclear, and debated, how much of that structure can be deduced from variational properties of quantitative traits that are inferred from their genetic (co)variance matrix (G-matrix). Here we aim to clarify how the extent of pleiotropy and the correlation among the pleiotropic effects of mutations differentially affect the structure of a G-matrix and our ability to detect genetic constraints from its eigen decomposition. We show that the eigenvectors of a G-matrix can be predictive of evolutionary constraints when they map to underlying pleiotropic modules with correlated mutational effects. Without mutational correlation, evolutionary constraints caused by the fitness costs associated with increased pleiotropy are harder to infer from evolutionary metrics based on a G-matrix's geometric properties because uncorrelated pleiotropic effects do not affect traits' genetic correlations. Correlational selection induces much weaker modular partitioning of traits' genetic correlations in absence then in presence of underlying modular pleiotropy.
Init files for running with Nemo v2.3.4 (with variable modularity). For 10,000 generations of stabilizing selection to reach mutation-selection balance. G-matrix eigen decomposition and evolutionary metric analyses performed on 10,000th generation for each simulation averaged over 50 replicates.
Init files for running with Nemo v2.3.4 (with variable modularity). For 2,000 generations of directional selection performed on 10,000th generation of Stabilizing Selection population simulation output. Number of generations to a fitness cut-off for each simulation averaged over 50 replicates.