New tools for characterizing early brown stem rot disease resistance signaling in soybean

Authors: McCabe, Chantal; Graham, Michelle

Submitted to: The Plant Genome
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/26/2020
Publication Date: 9/14/2020
Citation: McCabe, C.E., Graham, M.A. 2020. New tools for characterizing early brown stem rot disease resistance signaling in soybean. The Plant Genome. 13(3). Article e20037. https://doi.org/10.1002/tpg2.20037.
DOI: https://doi.org/10.1002/tpg2.20037

Interpretive Summary: Brown stem rot (BSR) reduces soybean yield by up to 38%. The causal agent of BSR is Phialophora gregata, a slow growing necrotrophic fungus whose life-cycle includes inactive and active disease causing phases, each lasting several weeks. BSR leaf symptoms are often misdiagnosed as other soybean diseases or nutrient stress, making BSR resistance especially difficult to phenotype and utilize in breeding programs. To shed light on the genes and networks contributing to resistance, we conducted whole genome expression analyses of infected and mock-infected leaf, stem, and root tissues of a BSR resistant genotype at 12, 24 and 36 hours. By using multiple tissues and time points, we could see that leaves, stems and roots use the same defense pathways. Gene networks associated with defense, photosynthesis, nutrient homeostasis, DNA replication and growth are the hallmarks of BSR resistance. While P. gregata is a slow growing pathogen, our results demonstrate that pathogen recognition by the plant occurs hours after infection. By exploiting the genes and networks described here we will be able to develop novel diagnostic tools to facilitate breeding and screening for BSR resistance.

Technical Abstract: Brown stem rot (BSR) is caused by the fungus Phialophora gregata and reduces soybean yield by up to 38%. Identifying this disease is difficult as BSR foliar symptoms are often misdiagnosed as other soybean diseases or nutrient stress. These difficulties slow down efforts towards screening and breeding for BSR resistance. To characterize genes and networks contributing to resistance, we conducted RNA-seq of infected and mock-infected leaf, stem, and root tissues of a resistant genotype at 12, 24 and 36 hours after infection. The analyses determined that leaves, stems and roots use the same defense pathways, but the timing of their defense responses differ. While P. gregata is a slow growing pathogen, our results demonstrate that the plant recognizes the pathogen just occurs hours after infection. By exploiting the genes and networks identified we will be able to develop novel diagnostic tools to facilitate breeding and screening for BSR resistance.