Regulatory architecture of disease resistance in maize revealed by multi-omic systems genetics

Abstract

AbstractComplex traits such as disease resistance have been traditionally studied using quantitative genetics. Here, we use systems genetics to integrate disease severity and multi-omic quantitate trait loci (QTL) to uncover biological networks underlying interaction with northern leaf blight (NLB), a yield-limiting disease of corn. Specifically, we integrated transcriptome, (phospho)proteome, and metabolome measurements to map molecular QTL and build predictive regulatory networks following NLB infection. These inferred networks identified a critical signaling module that was genetically validated comprised of a kinase termedNLBSUSCEPTIBLEKINASE 1, a bHLH transcription factor, and the lignin biosynthesis enzyme BROWN MIDRIB 2. Our results demonstrate the feasibility of high-throughput mapping of genetic determinants of gene- product levels and demonstrates the power of systems genetics to identify upstream regulatory genes that confer resistance to NLB that can inform future strategies for crop protection.