Genetic analysis reveals three novel QTLs underpinning a butterfly egg-induced hypersensitive response-like cell death in Brassica rapa

Abstract

Abstract Background Cabbage white butterflies (Pieris spp.) can be severe pests of Brassica crops such as Chinese cabbage, Pak choi (Brassica rapa) or cabbages (B. oleracea). Eggs of Pieris spp. can induce a hypersensitive response-like (HR-like) cell death which reduces egg survival in the wild black mustard (B. nigra). Unravelling the genetic basis of this egg-killing trait in Brassica crops could improve crop resistance to herbivory, reducing major crop losses and pesticides use. Here we investigated the genetic architecture of a HR-like cell death induced by P. brassicae eggs in B. rapa. Results A germplasm screening of 56 B. rapa accessions, representing the genetic and geographical diversity of a B. rapa core collection, showed phenotypic variation for cell death. An image-based phenotyping protocol was developed to accurately measure size of HR-like cell death and was then used to identify two accessions that consistently showed weak (R-o-18) or strong cell death response (L58). Screening of 160 RILs derived from these two accessions resulted in three novel QTLs for Pieris brassicae-induced cell death on chromosomes A02 (Pbc1), A03 (Pbc2), and A06 (Pbc3). The three QTLs Pbc1–3 contain cell surface receptors, intracellular receptors and other genes involved in plant immunity processes, such as ROS accumulation and cell death formation. Synteny analysis with A. thaliana suggested that Pbc1 and Pbc2 are novel QTLs associated with this trait, while Pbc3 also contains an ortholog of LecRK-I.1, a gene of A. thaliana previously associated with cell death induced by a P. brassicae egg extract. Conclusions This study provides the first genomic regions associated with the Pieris egg-induced HR-like cell death in a Brassica crop species. It is a step closer towards unravelling the genetic basis of an egg-killing crop resistance trait, paving the way for breeders to further fine-map and validate candidate genes.