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ARS Home » Midwest Area » Columbia, Missouri » Plant Genetics Research » Research » Research Project #434365

Research Project: Soybean Seed Quality Improvement through Translational Genomics

Location: Plant Genetics Research

Project Number: 5070-21000-042-00-D
Project Type: In-House Appropriated

Start Date: Mar 12, 2018
End Date: Mar 11, 2023

Objective:
Objective 1: Develop and make available new approaches to evaluate gene functions in gene networks and verify these tools by examining previously identified gene networks in soybean. Objective 2: Discover, characterize, and make available genes for industry-relevant protein and oil traits from new and existing genetic populations created through various methods, such as fast neutrons, conventional crossing, reverse genetics (TILLING), or mining exotic diversity contained in the USDA National Plant Germplasm System.

Approach:
We will apply a genome-wide reverse engineering approach to reconstruct a gene regulatory network in soybean using in-house generated and public available transcriptome sequencing data. An eQTL mapping analysis will conducted with seed transcriptome sequencing and genome sequencing data of the wild and cultivated soybean genotypes to identify the trans-acting eQTL and reveal the relationship of candidate regulatory genes/alleles and their associated genes. The reconstructed gene regulatory network, regulatory relationships generated from eQTL analysis and the co-expression gene network that we previously modeled will be compared to evaluate each regulatory relationship (edge) to generate a consensus soybean seed gene regulatory network. A set of CRISPR/Cas9 genome editing vectors for a regulatory gene (hub) will be constructed to alter its regulatory function in “transgenic” soybean for validation of its regulatory functions in the network. In addition, a set of big data analysis methodologies and data mining strategies will be developed to integrate the large amount of publically available and in-house generated QTL mapping data, transcriptome and genome sequencing data, soybean seed gene regulatory networks predicted above and seed storage reserve related metabolic pathways to identify putative genes/alleles that cause the variation in oil and/or protein content in soybean. We will sequence transcriptomes of soybean seeds containing different alleles of a putative gene to determine their transcriptome response to the allelic variation for validating its regulatory function and providing an insight into its underlying mode of action in regulating oil and/or protein production in seeds.