Candidate gene identification for maize gibberella ear rot disease resistance using genomic and transcriptomic approaches.
Kebede, A., Johnston, A., Schneiderman, D., Bosnich, W., Reid, L.M., Harris, L.J. Candidate gene identification for maize gibberella ear rot disease resistance using genomic and transcriptomic approaches. 5th International Conference on Quantitative Genetics, Madison, Wisconsin, June 12-17, 2016.
To improve breeding efficiency for Gibberella ear rot (GER) resistance and gain a deeper understanding of the host-pathogen interaction at the molecular level, advances in next generation sequencing technologies such as Genotyping-by-Sequencing (GBS) and RNA-seq offer powerful tools. Using GBS and a bi-parental recombinant inbred line population, we mapped GER disease resistance quantitative trait loci (QTLs) and significantly improved the accuracy and precision of identified chromosomal regions. Notably, the QTL regions were flanked by a much narrower marker-to-marker distance which could in turn significantly reduce unwanted linkage drag when performing marker-assisted selections. To further characterize the trait, the transcriptional changes observed in maize kernel tissues during the early stages of GER infection were studied in the same inbred lines using RNA-seq. By comparing QTL regions with gene expression data, we identified genes involved in modulation of the plant hormone jasmonic acid, signaling for cell wall modification, cell detoxification, biosynthesis of pathogenesis related proteins and phytoalexin as candidate resistance genes. We used droplet digital PCR to validate gene expression profiles in a broader range of treatments. To conclude, whole genome gene expression profiling using RNA-seq is an invaluable tool to understand and characterize disease resistance through identification of genes which have the potential to serve in marker assisted selection and/or genome editing and rapid deployment of resistant genotypes, especially when gene expression profiling information is coupled with QTL mapping.