Global transcriptome and metabolome analyses reveal a key role for jasmonate and lignin biosynthetic pathways in soybean resistance to Sclerotinia sclerotiorum
A. RANJAN (1), D. Smith (1), M. Kabbage (2) (1) University of Wisconsin Madison, U.S.A.; (2) University of Wisconsin, U.S.A.

Sclerotinia sclerotiorum, a necrotrophic fungal pathogen with a broad host range, causes a devastating disease on soybean called Sclerotinia stem rot (SSR) can lead to losses as high as 50-60%. Resistance mechanisms against SSR are poorly understood. We used a dual approach utilizing RNA sequencing and metabolomics to decipher the molecular mechanisms governing resistance to S. sclerotiorum in soybean. Transcripts and metabolites of two isogenic breeding lines of soybean; susceptible (91-44) and partially resistant (91-145) were analyzed in a time course experiment. The RNA sequencing data analysis indicated that after 24 h, 48 h and 96 h of infection, there were 272 (145 up and 127 down), 178 (74 up and 104 down), and 114 (48 up and 66 down) differentially regulated genes (> two-fold change and FDR < 0.05) respectively, in the partially resistant line compared to the susceptible line. Under the non-infected condition, there were 351 (167 up and 184 down) differentially regulated genes in the partially resistant line compared to the susceptible line, which might explain preformed immunity in the partially resistant line. Overall, transcript analysis identified a number of transcription factors (WRKY, DREBa, BZIP), stress and disease responsive genes, and lignin catabolic genes that may be involved in resistance mechanisms against S. sclerotiorum. Results from metabolomics and phytohormone estimation studies also indicated a role for secondary metabolites like the lignin pathway intermediates, antimicrobial compounds and jasmonate for resistance, and corroborated our transcriptomic data. This study provides an important step towards understanding resistance responses of soybean to S. sclerotiorum and identified novel mechanisms and targets. 

Abstract Number: P18-689
Session Type: Poster