A greenhouse‐based high‐throughput phenotyping platform for identification and genetic dissection of resistance to Aphanomyces root rot in field pea

Abstract

Abstract Aphanomyces root rot (ARR) is a devastating disease in field pea (Pisum sativum L.) that can cause up to 100% crop failure. Assessment of ARR resistance can be a rigorous, costly, time‐demanding activity that is relatively low‐throughput and prone to human errors. These limits the ability to effectively and efficiently phenotype the disease symptoms arising from ARR infection which remains a perennial bottleneck to the successful evaluation and incorporation of disease resistance into new cultivars. In this study, we developed a greenhouse‐based high‐throughput phenotyping (HTP) platform that moves along the rails above the greenhouse benches and captures the visual symptoms caused by Aphanomyces euteiches in field pea. We pilot tested this platform alongside with conventional visual scoring in five experimental trials under greenhouse conditions, assaying over 12,600 single plants of advanced breeding lines developed by the North Dakota State University Pulse Breeding Program. Precision estimated through broad‐sense heritability (H2) was consistently higher for RGB‐derived indices (H2, Exg = 0.86) than the conventional visual scores (H2, disease severity index = 0.59). Prediction of disease severity using a random forest modeling of RGB‐derived indices achieved 0.69 accuracy on the test sets, with inaccurate classification partly attributed to the presence of tolerant lines (displaying root rot but no foliar symptoms) and within‐line genetic heterogeneity. We genetically dissected variation for ARR resistance from the population using RGB‐derived indices and visual scores through genome‐wide association mapping and identified a total of 260 associated single nucleotide polymorphism (SNP). The number of associated SNP for RGB‐derived indices was consistently higher than the number of associated SNP identified using visual scores, with the most significant SNP explaining about 5%–9% of variance per index. We identified previously mapped genes known to be involved in the biological pathways that trigger immunity against ARR and a few novel QTLs with small‐effect sizes that may be worthy of validation in the future. The newly identified QTLs and underlying genes, along with genotypes with promising resistance identified in this study, can be useful for improving a long‐term and durable resistance to ARR.