Dr. Fernando Correr (Plant Sciences and Plant Pathology Dept., MSU) 

04/21/2022  3:10pm

Abstract:

Characterization of gene function helps us understand the traits that have driven species evolution and accelerate breeding efforts. Gene functions are studied en masse through transcriptome analyses, in which the assessment of gene expression profiles is a powerful tool to decipher gene regulatory networks. Many plant species share a complication in examining gene function—the number of genes is very large due to one or more duplications of plant genomes. In this presentation, I will show the application of methods for working with these large plant genomes using transcriptomics First, I will share research using a weighted gene co-expression network analysis (WGCNA) to identify important genes in Camelina sativa seed development. The main aim of this research is to find network components associated with larger seeds in this oilseed crop. Secondly, the allelic origin of the transcript also causes variation in expression, and multiple doses of the alleles in polyploid organisms expands this complexity. To better understand this phenomenon, I will present results of a hierarchical Beta-Binomial model to evaluate allele-specific expression in the species of Saccharum (sugarcane).