Supplemental Material for Keep et al., 2020
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Figure S1: Histograms of Minor Allele Frequencies of all SNP markers per population and averaged over populations.
Figure S2: Scatter plot of Pearson correlation between allele frequencies of pairs of SNP markers from a same scaffold and genomic distance between SNP markers in base pairs.
Figure S3: Q-Q plots of p-values from GWAS for all available traits accounting for neither structure nor kinship, only for structure, only for kinship or for both kinship and structure.
Figure S4: Pairwise phenotypic Euclidian distances plotted against pairwise Euclidian genetic distances for all available traits. Genetic Euclidian distances were calculated based on the 100 most significantly associated SNP markers to the trait as given by the GWAS.
Table S1: Genebank accessions from the natural diversity of perennial ryegrass used in the study.
Table S2: List of perennial ryegrass cultivars used in the study and their origin.
Table S3: Hi-Plex genotyping description.
Table S4: Alternative allele frequencies of 189,781 SNP markers for the natural populations and cultivars used in this study. SNP markers are referred to as follows: scaffold number (from reference genome of Byrne et al. 2015)_scaffold reference_SNP position in scaffold. The SNP from the Hi-Plex are indicated by “monsterplex” at the end of the SNP marker names.
Table S5: Seasonal climatic conditions at the three experimental gardens over the duration of the experiments.
Table S6: Adjusted means per population for all the phenotypic traits used in this study.
Table S7: Phenotypic variables description and associated results from GWAS and genomic prediction analysis.
Table S8: Pearson correlation coefficients between the phenotypic variables.
Table S9: SNP markers significantly associated with each trait (q-value<10%). For each trait, the following information is indicated: P-values, false discovery rates, SNP marker effects and variance explained by SNP markers from both a linear model which did not account for kinship (trait-SNP linear regression model) and a linear model which accounted for kinship (GWAS model).
Table S10: Number of SNP jointly associated (GWAS with q-value<10%) to phenotypic trait pairs.File S1: Detailed description of the phenotypic variables.