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ARS Home » Midwest Area » Ames, Iowa » Corn Insects and Crop Genetics Research » Research » Publications at this Location » Publication #342939
Title: Leveraging RNA-Seq to characterize resistance to brown stem rot and the Rbs3 locus in soybean

Author
item McCabe, Chantal
item CIANZIO, SILVIA - Iowa State University
item O`Rourke, Jamie
item Graham, Michelle

Submitted to: Molecular Plant-Microbe Interactions
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/27/2018
Publication Date: 8/20/2018
Citation: McCabe, C.E., Cianzio, S.R., O'Rourke, J.A., Graham, M.A. 2018. Leveraging RNA-Seq to characterize resistance to brown stem rot and the Rbs3 locus in soybean. Molecular Plant-Microbe Interactions. 31(10):1083-1094. https://doi.org/10.1094/MPMI-01-18-0009-R.
DOI: https://doi.org/10.1094/MPMI-01-18-0009-R

Interpretive Summary: Breeding for resistance to diseases and pests is important for protecting crop yields. Crop damage from diseases and pests results in a loss of over $60 billion in the United States each year. Brown stem rot (BSR), caused by the soybean fungus Phialophora gregata, can cause yield losses up to 38%. While BSR is agronomically important, there are many difficulties identifying the disease including misdiagnosis with similar diseases and the need for multiple destructive screening methods 5 to 6 weeks after infection. Genetic screening, facilitated by molecular markers, would be faster and more accurate than current screening methods. Using high throughput sequencing, we have identified the genes and gene networks important in P. gregata resistance. Further, we have developed useful molecular markers that can be used by breeders to identify new resistance traits and develop soybean lines with improved resistance.

Technical Abstract: Breeding for pathogen resistance is important to improve and protect soybean yields. Brown stem rot (BSR), caused by the fungus Phialophora gregata, reduces yield by 38%. Three dominant BSR resistance loci have been identified: Rbs1, Rbs2, and Rbs3, however the gene networks regulating defense responses remain unknown. Further, identifying resistant germplasm by genotyping or phenotyping remains difficult due to complexities of soybean/P. gregata interactions. We conducted RNA-Seq of P. gregata infected and mock infected leaf, stem, and root tissues of both a resistant (PI 437970, Rbs3) and a susceptible (Corsoy 79) soybean genotype. Our bioinformatic analyses allowed us to identify genes differentially expressed in response to infection (treatment) and between genotypes (resistant or susceptible). This allowed us to characterize the gene networks contributing to defense and to leverage historical Rbs mapping data to characterize the Rbs3 locus itself. Our results indicate there is little overlap in differential gene expression between genotypes or tissues when infected by P. gregata. Defense, DNA replication, and iron homeostasis are the hallmarks of P. gregata resistance. The Rbs3 locus corresponds to 12 receptor-like proteins (RLPs), seven of which are expressed at higher levels in resistant roots. Clusters of RLPs are also associated with Rbs1 and Rbs2. The RLPs have signatures of disease resistance genes including clustering, evidence of recombination, and conserved resistance motifs. Finally, the RNA-Seq data was used to generate novel SNPs within the Rbs3 locus that will be used to improve phenotyping and breeding efficiency.