Fig. 1

Population structure of the pea association mapping collection based on Discriminant Analysis of Principal Components (DAPC) analysis. a Number of clusters vs BIC values. The x-axis shows the potential numbers of clusters representing the population structure. The y-axis represents the BIC value associated with each number of clusters. b Number of principal components (PCs) vs a-score criterion. The x-axis shows the potential numbers of PCs which is used in the principal component analysis (PCA) step of DAPC. The y-axis gives the a-score criterion associated with each number of PCs. The optimal number of PCs, represented by a red bar, was obtained after 100 permutations. c Scatterplot showing the distribution of the association mapping collection along the first two principal components of the DAPC. Accessions are represented by dots and genetic clusters as inertia ellipses coded from 1 to 7. The bottom right inset shows eigenvalues of the six principal components in relative magnitude, ordered from 1 to 6 from the left to the right. d Scatterplot showing the correspondence between the classification of accessions for their cultivation status and the 7 clusters identified with DAPC; unknown accessions are shown by black dots