Location: Plant Genetics Research
2023 Annual Report
Objectives
Objective 1: Conduct research to determine the impacts of genetic or environmental changes on central metabolism and flux in soybean to enhance productivity and seed composition traits.
Sub-objective 1A: Identify genotypes and phenotypes for further characterization.
Goal 1A: Identification of homozygous lines genetically altered to produce more protein and oil.
Sub-objective 1B: Use metabolite levels and isotope tracers to assess changes in carbon allocation that impact composition.
Goal 1B: In-depth analysis of molecular phenotype of altered seeds.
Objective 2: Develop and deploy novel analytical methods or tools to evaluate integration of various seed metabolism and turnover processes to produce desirable soybean seed composition and determine effects on the dynamics of seed metabolism.
Sub-objective 2A: Develop analytical tools to assess biosynthetic and turnover events in metabolism.
Goal 2A: Establish a method to quantify short chain acyl-CoAs.
Sub-objective 2B: Quantify intermediates of central and lipid metabolism that contribute changes in composition.
Goal 2B: Quantify lipid dynamics in seeds.
Objective 3: Conduct research to develop methods for identification and characterization of novel genetic variation for seed composition traits in soybeans using sequencing and/or genome editing to validate the genes and/or associated biological networks, and work with breeders to determine phenotypic variation and usefulness for improving soybean seed traits and climate resilience.
Sub-objective 3A: Identify genes, gene variants and networks important to soybean seed quality, yield, and resilience to climate change.
Goal 3A: Identify putative causative genes, alleles and associated regulatory gene network underlying QTLs important to soybean seed quality, yield, and resilience to climate change.
Sub-objective 3B: Validate and characterize the discovered genes, gene variants and networks to develop new strategies for biotechnologists and breeders to effectively improve soybean seed traits and climate resilience.
Goal 3B: Developing a manageable number of validated genes, gene variants and networks for effectively improving soybean seed quality and climate resilience.
Approach
Goal 1A: Identification of homozygous lines genetically altered to produce more protein and oil.
Soybeans will be modified through transgenic approaches to enhance seed value by augmenting metabolic pathways to alter composition in protein, oil, and carbohydrate. Transformed soybeans containing genes to reduce lipid turnover and to reduce carbohydrate biosynthesis will be self-pollinated, screened, and tested for oil and protein levels, seed size, pod and node number to choose transgenic events for further evaluation.
Goal 1.B: In-depth analysis of molecular phenotype of altered seeds.
Lipid, protein, and carbohydrate production will be quantified including new methods to assess synthesis of carbohydrate polymers involving development of combined mass spectrometry and UV-visible light spectrophotometer-based assays. Central intermediates, proteins, and lipids in combination with their isotopologues from isotope-labeling experiments will be quantified to derive metabolic flux information.
Goal 2.A: Establish a method to quantify short chain acyl-CoAs.
A method to extract and quantify short chain acyl-CoAs will be established through development of extraction and purification methods along with detection and quantification using liquid chromatography mass spectrometry. Odd chain length standards will be used with multiple types of column chromatography and injected into samples to assess extraction efficiency, serve as controls, and internal standards.
Goal 2.B: Quantify lipid dynamics in seeds.
Methods with isotopes including 13C, 18O, or 2H will be tested to develop a quantitative assay to assess the rate of fatty acid and lipid biosynthesis and turnover in filling seeds. To assess the rate of fatty acid biosynthesis, isotopically labeled acyl-acyl carrier proteins (i.e., acyl-ACPs) will be quantified by liquid chromatography mass spectrometry, and acyl-CoAs quantified to assess fatty acid and lipid synthesis and turnover.
Goal 3.A: Discover a suite of putative causative genes, alleles and associated regulatory gene network underlying QTLs important to soybean seed quality, yield, and resilience to climate change.
A bioinformatic pipeline will be developed to analyze the large soybean structural and functional genomic, genotyping and phenotyping, and other biological datasets. Integrative and data-driven strategies will be developed to mine -omics data for predicting and cross-validating causative genes, alleles and associated regulatory gene networks underlying QTLs important to soybean seed quality, yield and resilience to climate changes.
Goal 3.B: Validate two genes underlying two major QTLs for soybean oil, their gene variants and networks to effectively improve soybean seed quality and climate resilience.
Two major QTLs for seed oil and protein will be selected. Soybean plants over-expressing and containing altered gene functions will be generated and characterized to validate the underlying genes, alleles and gene regulatory networks and to comprehend resilience to environmental stresses. Transcriptomic and metabolomic changes will be investigated to illustrate their molecular mode of action.
Progress Report
This is a new project, therefore, there is no progress to report for FY2023.
Accomplishments
