NETWORK ANALYSIS OF SORGHUM GRAIN DEVELOPMENT TO CLARIFY THE BIOSYNTHESIS OF STARCH, PROTEIN, AND OIL

The goal of this project is to elucidate the physiological and regulatory mechanisms underlying the production of starch, protein, and oil in sorghum grain to assist breeders. Three specific aims are revised as below:Aim 1. Characterization of endosperm and embryo structure and physiochemical properties in the sorghum grain quality mapping population. Six MAGIC parental lines with different grain quality features and two bi-parental recombinant inbred lines (RILs) will be selected for the metabolism analysis and SEM visualization. The plants will be planted at the research farm of Texas Tech University during the summer of 2023. GC-MS and SEM grain structure imaging will be performed at five developmental stages.Aim 2. Reveal the dynamic transcriptome landscapes of sorghum endosperm and embryo development.Matching RNA-seq data will be generated using the same tissue at the five development stages from Aim 1. By comparing the transcriptome profiles of seed development in the eight lines with their grain chemical composition, we will be able to answer the questions: 1) How do the transcriptome profiles differ among the genotypes during grain development? 2) How many genes are specifically involved in seed development in this population?Aim 3. Identify conserved genes controlling grain quality in thePoaceaeusing reverse genetics.The functions of sorghum orthologs of 30 maize and rice grain quality genes will be validated using EMS mutants as the backbones of the network analysis in Aim 4.Aim 4. Identify potential grain quality breeding targets by comparing gene networks resulting in high or low production of starch and protein.Networks of starch, protein and oil biosynthesis will be built and compared among different genotypes using the metabolism and transcriptome data. The key question to answer is which genes are primarily responsible for tradeoffs between carbon allocation pathways influencing starch, protein, and oil content in mature grain. A selection of 20 genes will be validated from the network using the mutant population