Floral signals evolve in a predictable way under artificial and pollinator selection in Brassica rapa

You find here the R scripts and data necessary to reproduce the results published in "Floral signals evolve in a predictable way under artificial and pollinator selection in Brassica rapa" by Zu et al. 2020 BMC Evolutionary Biology. The whole analysis is in the script "G-analysis.R". The associated data is loaded from the ".Rdata" and ".txt" files associated. The scripts "randG...R" are required to generate bootstrap replicates of G-matrix estimates. This is best done on an HPC cluster. To avoid having to run those randomizations, we provide the summary data we have generated from randomizations to run the full analysis. In Zu et al., we used data from an artificial selection and a pollinator (bumblebee, hoverfly) evolution experiment with fast cycling Brassica rapa plants to predict evolutionary changes of 12 floral volatiles and 4 morphological floral traits in response to selection. Using the observed selection gradients and the genetic variance-covariance matrix (G-matrix) of the traits, we showed that the observed responses of most floral traits including volatiles were predicted in the right direction in both artificial- and bumblebee-selection experiment. Genetic covariance had a mix of constraining and facilitating effects on evolutionary responses. We further revealed that G-matrices also evolved in the selection processes. We are depositing here the raw phenotypic data used to estimate the G-matrices in the artificial selection experiment along with the R scripts used to run the analyses. The phenotypic data of the pollinator experimental evolution experiment have been published elsewehere (Gervasi & Schiestl, 2017, Nature Communications 8:14691; doi:10.1038/ncomms14691)