Location: Plant Physiology and Genetics Research
Project Number: 2020-21410-008-000-D
Project Type: In-House Appropriated
Start Date: Jun 16, 2023
End Date: Jun 15, 2028
With increasing global climate change challenges, there is an increasing demand for new clean bioenergy resources such as developing new crops, and genetically improving current crops to increase their tolerance to environmental changes and to sustain the agricultural sectors in semi-arid regions. The overall goal of this research project is to investigate genetic variations in bioenergy and industrial crops such as camelina, guayule, sorghum, and soybean to identify candidate genes controlling abiotic stress tolerance traits and identify new germplasm that can be used to develop superior cultivars with high yield and stable productivity to meet those challenges. The specific objectives of the project are: Objective 1: Conduct research to identify alleles, candidate genes, and molecular markers for drought and/or heat tolerance of oilseed and biomass crops in semi-arid field conditions and determine association of abiotic stress tolerance with agronomic performance and biofuel traits such as biomass yield and conversion. Sub-objective 1.A: Identify alleles/genes and associated molecular markers controlling oil content and composition, and related abiotic stress tolerance traits in camelina. Sub-objective 1.B: Identify alleles/genes and associated molecular markers conditioning seed quality and composition and related stress tolerance traits in soybean. Sub-objective 1.C: Identify alleles/genes and associated molecular markers conditioning biofuel production, biomass yield, and traits related to abiotic stress tolerance in bioenergy sorghum. Sub-objective 1.D: Screen USDA guayule germplasm collection to discover biofuel-related traits, determine their variation in pyrolysis production, and associations with abiotic stress tolerance. Objective 2: Conduct research to determine and effectively utilize bioinformatics and other genomic processing pipelines, such as transcriptomics and metabolomics, to enhance genetic improvement and trait enhancement of food, industrial, and biofuel crops. Sub-objective 2.A: Characterize the genetic mechanisms governing wax content and composition in soybean growing under abiotic stress conditions. Sub-objective 2.B: Explore guayule resin pathway(s) and related candidate genes using multi-omics approaches.
This project establishes a sustainable agricultural system for semi-arid regions using new and established crops for biofuel and industrial purposes. The approaches will explore genetic variation in bioenergy and industrial crops to discover abiotic stress tolerance traits and identify genes/alleles controlling those traits. Objective 1 will focus on identifying candidate genes for abiotic stress tolerance using developed populations (camelina) and diversity panels (soybean and sorghum) planted under stress/non-stress conditions. Oil content and composition, biofuel and related abiotic stress tolerance traits will be collected using traditional and high throughput phenotyping platforms and analyzed using MIXED model. G×E interaction analyses will be conducted across irrigation levels for recorded traits. In Camelina, Quantitative Trait Loci (QTL) associated with recorded traits and stability parameters will be conducted. Candidate genes under QTL interval will be identified using SNP position on the camelina reference genome. GWAS analyses will be conducted for soybean and sorghum diversity panels. Candidate genes from multiple GWAS analyses will be identified from genomic intervals in the soybean and sorghum reference genome assemblies. Guayule will be planted under stress/non-stress conditions and traits related to abiotic stress tolerance will be collected. Rubber and resin, pyrolysis and biofuel related traits will be determined. Objective 2 will focus on identifying candidate genes using multi-omics approaches, such as transcriptomics and metabolomics, to characterize genetic mechanisms governing wax content in soybean and resin in guayule. For transcriptome analyses, RNA will be harvested from soybean and guayule plants planted under stress/non-stress conditions and cDNA libraries will be sequenced. Following the structured pipeline, the paired-end clean reads will be aligned and mapped. Genes, with an adjusted p value, will be declared as differentially expressed. The Kyoto Encyclopedia of Genes and Genomes (KEGG) will be used to annotate genes to biological/metabolic pathway. For metabolomic approach, tissues from guayule will be harvested and resins will be extracted, purified and analyzed using liquid chromatography–mass spectrometry. Raw data will be processed to identify unknow compounds, search chemical databases for putative candidates, and annotate spectra with predicted fragmentation. Principal component analysis will be used to identify abundant metabolites and putative biomarkers responsible for differences among resin content in guayule genotypes and irrigation treatments. To interpret the metabolite’s function, pathway enrichments for detected metabolites will be calculated using KEGG database.