Statistical analysis of phenotypic data and marker-trait association
All statistical analyses were conducted on R v4.0.1 (R Core Team 2021). Scoring of HR-like cell death in severity categories were analysed with a non-parametric method (Kruskal-Wallis test) on HR scores (0, 1, 2, 3, and 4) and different accessions were included as categorical fixed factors. Differences in mean HR severity were tested using Kruskal-Wallis test, followed by Wilcoxon Rank Sum test with Benjamini-Hochberg correction. Chi-square tests were used to test the goodness of fit of the segregation of phenotypic data and KASP markers data. Marker-trait association was analyzed with the R/qtl package (Broman et al., 2003) using the scanone function for binary data (presence/absence of HR).

Results

Natural variation in egg-induced HR between B. nigra accessions
To study natural variation in egg-induced HR-like under controlled conditions, we collected seeds from a local B. nigra population that previously showed variation in HR-like cell death in field conditions (Fatouros et al., 2014; Griese et al., 2017). Induction of HR-like cell death was tested using treatment with an egg wash, which we previously showed to mimic Pieris eggs (Caarls et al., 2023). Overall, we observed variation between plants of each accession in occurrence and severity of the HR-like cell death (Fig. 1). In addition, we found significant differences between accessions for the severity of the HR-like cell death response (Kruskall-Wallis test, p< 0.05). In some accessions, for example SF48-O1, almost all plants showed an HR (score 2-4) and for some, e.g., DG1, only 1 out of 7 plants responded with an HR to the wash. The variation in egg-induced HR within and between accessions suggests the existence of genetic variation within the population that could be used for genetic mapping.