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ARS Home » Midwest Area » Columbia, Missouri » Plant Genetics Research » Research » Research Project #435034

Research Project: Soybean Seed Improvement Through Translational Genomics, Assessments of Elemental Carbon Metabolism, and Lipid Profiles

Location: Plant Genetics Research

Project Number: 5070-21000-043-000-D
Project Type: In-House Appropriated

Start Date: Jul 23, 2018
End Date: May 30, 2023

Objective 1: Develop novel analytical methods to understand the dynamics that underpin lipid metabolism to guide metabolic engineering efforts for lipid production in seeds. Objective 2: Assess central carbon metabolism in altered plant tissues and develop strategies that can be used to assess plant metabolic changes for improving agriculturally relevant seed composition traits or yield. Objective 3: 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 4: 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.

Goal 1.1: Quantify major acyl-Acyl Carrier Protein (ACP) species of fatty acid biosynthesis in soybeans. We will develop biochemical methods with mass spectrometry to rigorously quantify acyl-ACPs. Acyl ACPs connect central metabolism with lipid metabolism and will provide an indication of when acyl-ACP synthesis may be bottlenecking the production of lipids under different circumstances which will be further considered through isotopic labeling and measurement of labeled acyl-ACPs. Goal 1.2: Quantify labeling in phospholipid and neutral lipid pools. We will isotopically label seeds and investigate the labeling in phospholipid and neutral lipid intermediates that we hypothesize are most indicative of specific pathway use for lipid production and that can be informative to engineer increased lipid production in the future. The mass spectrometry methods will involve optimization with high resolution instruments. Goal 2: Analyze labeling in organic and amino acid pools in developing soybeans. We will build a platform to transiently label seeds with 13C over short durations (minutes to hours) to investigate the allocation of carbon during specific aspects of seed development. These stages of development contribute to the final composition and are therefore important in establishing the final composition. Methods to rigorously analyze important intermediates including amino acids and organic acids will include fragment evaluation with direct injection mass spectrometry and validation with standards prior to quantification of differences in seeds of different ages. Goal 3: Demonstrate that expression QTL genetic mapping is an effective approach to evaluate regulatory functions of genes in a co-expression network. A eQTL mapping analysis will be conducted with seed transcriptome sequencing and genome sequencing data of the wild and cultivated soybean genotypes to identify the trans-acting eQTL, reveal the relationship of candidate regulatory genes/alleles and their associated genes and 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. Goal 4: Establish that integration of structural and functional genomic analysis of genetic soybean diversity with QTL studies is an effective approach to discovering seed quality genes and alleles. Big data analysis methodologies and data mining strategies will be developed to integrate QTL mapping data, transcriptome and genome sequencing data, soybean seed gene regulatory networks with seed storage reserves and 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 validate regulatory function and provide insight into regulation of oil and/or protein production in seeds.