Location: Plant Physiology and Genetics Research
2023 Annual Report
Objectives
The objectives of the plan concentrate on utilizing advanced phenomic and genomic approaches to genetically improve cotton, oilseed crops, bioenergy and industrial crops and expand their use for food, feed, fuel, and fiber production for United States agricultural sectors and global use. To reach that goal our specific objectives are:
Objective 1: Use existing and newly developed field-based phenotyping methods to evaluate cotton, oilseeds, and other industrial and biofuel crops, and utilize the results to enable effective use of high-throughput phenotyping (HTP) methodology for crop genetic improvement and management.
Sub-objective 1A: Field-based evaluation of cotton using high-throughput phenotyping and conventional methods for germplasm improvement and crop management.
Sub-objective 1B: Field-based phenotypic evaluations for biofuel crop camelina using high-throughput and traditional phenotyping technologies for traits related to drought stress.
Sub-objective 1C: Use high-throughput and traditional phenotyping strategies to identify soybean germplasm with abiotic stress tolerance traits.
Sub-objective 1D: Phenotypic characterization of USDA guayule collection under abiotic stress conditions and Arizona growing conditions using traditional and high-throughput phenotyping technologies.
Objective 2: Utilize various new and conventional genetic approaches to identify genes and associated molecular markers conditioning abiotic stress tolerance in arid environments, and determine relationships with important agronomic traits.
Sub-objective 2A: Identify molecular markers associated with genes involved in temporal patterns with abiotic stress tolerance and agronomic traits in cotton using high-throughput phenotyping.
Sub-objective 2B: Identifying alleles/genes and associated molecular markers conditioning yield and abiotic stress tolerance and related traits in bioenergy crop, camelina.
Sub-objective 2C: Identify genes/alleles and associated molecular markers conditioning yield and abiotic stress tolerance in soybean.
Approach
The objectives of the plan will be carried out using various high through-put phenotyping (HTP) approaches used to identify and improve cotton, camelina, soybean and guayule crops with increased tolerance to abiotic stress and stable productivity. For each crop, a genetic population/diversity panel will be planted under well-watered (WW) and water-limited treatments, based on agronomic recommendations of each crop, in replicated design over several years. The HTP data will be collected on a weekly basis throughout the growing season using HTP platforms that use electronic sensors to measure crop height, canopy multi-spectral reflectances and canopy temperature. In addition to HTP measurements, morphological, physiological and agronomic traits including plant height, lodging score, and flowering date will be collected during the growing season. At physiological maturities, plots will be harvested and seed/lint yield will be determined. Oil and leaf wax contents and compositions will be quantified using standard gas chromatography analysis. For guayule, rubber and resin will be determined using an Ion chromatography system. Traits will be analyzed using MIXED model in statistical analysis software (SAS) software, where water treatments, different environments and accessions will be considered as fixed effects and replicates will be the random effect. Differences among lines within each water treatment will be determined with a Bonferroni adjustment for multiplicity test. G×E interaction analysis will be conducted for recorded traits where water treatments, replicates, environments, and accessions will be considered as random effects.
Quantitative trait loci (QTL)/alleles/genes associated with complex traits like heat and drought stress tolerances will also be identified. Cotton recombinant inbred line (RIL) population and camelina and soybean diversity panels will be genotyped using Genotyping-by-Sequencing technology. Genome-Wide Association Studies (GWAS) and QTL analyses will be used to identify molecular markers that are associated with and controlling the dynamic changes in plant growth under stress conditions, crop productivity traits and stability and oil and wax content and quality (Objective 1). Best linear unbiased predictors (BLUPs) of each phenotypic trait will be determined using mixed model of SAS software. GWAS analyses will be conducted using the trait analysis by association, evolution and linkage (TASSEL) package. To find the best model that is able to detect the associations between phenotypic traits and single nucleotide polymorphism (SNP) markers, and reduce the number of false-positive associations, the Mixed Linear Models (MLM) approach of TASSEL will be used. Candidate genes from multiple GWAS analyses will be identified from genomic intervals in the reference genome assemblies. In cotton, QTL analyses will be conducted using the inclusive composite interval mapping (ICIM) program.
Progress Report
This is the final report for the project 2020-21410-007-000D, entitled, “Enhancing Abiotic Stress Tolerance of Cotton, Oilseeds, and Other Industrial and Biofuel Crops Using High Throughput Phenotyping and Other Genetic Approaches” which expired in June 2023. Related research is continuing under a new project 2020-21410-008-000D. For a description of the new objectives and progress of current research, please see the annual report for the new project. Substantial results have been achieved over the five years of this project.
Objective 1 focused on exploring the phenotypic diversity in cotton, soybean, camelina and guayule. For Sub-objective 1A, substantial progress was made on field-based evaluation of cotton using traditional and high-throughput phenotyping methods. Cotton germplasms adapted to multiple locations were selected from populations developed by ARS researchers in College Station, Texas, and Florence, South Carolina, and tested at each location for four years. These lines were evaluated at Maricopa, Arizona, College Station, Texas, and Florence, South Carolina, locations before final selection and release of multi-location adapted germplasm. Five cotton germplasm lines that have potential to be used as a valuable source of climate resilient cotton were released to improve cultivars for sustainable fiber quality.
Sub-objective 1B focused on characterization of camelina spring diversity panel. The panel, consisting of 250 accessions, was planted under field conditions at Maricopa, Arizona, over two years in well-irrigated and reduced-irrigation trials. High throughput phenotyping (HTP) data were collected throughout the growing season. In addition to HTP measurements, traditional morphological and physiological traits, including flowering time and plant height, were collected. After harvesting, seed yield, seed weight, oil content and fatty acid were estimated. Statistical analyses over environments and years indicated that genotypes responded differently to drought stress. For example, there were significant variations among genotypes for normalized difference vegetation index (NDVI), an indicator of stress-induced chlorophyll degradation. Significant effects of genotype were observed in other HTP-related traits. Physiological traits such as seed yield, plant height, flowering time, fatty acids profiles and oil and protein contents were significantly affected by genotypes, environments, but no Genotype x Environment (GxE) interaction was observed affecting those traits.
Sub-objective 1C focused on screening and identifying drought tolerant soybean germplasm under semi-arid conditions. To achieve that goal, 200 maturity group 4 soybean genotypes and drought-tolerant checks were planted in Arizona, Arkansas, and Missouri, under well-irrigated and reduced-irrigation field conditions in replicated trials over two years. The HTP data were collected throughout the growing season. In addition to HTP measurements, drought tolerance-related traits, such as canopy wilting (CW), carbon isotope discrimination (C13), and leaf wax content and compositions, were collected. Data showed high phenotypic variation among soybean genotypes for studied traits. For each trait, certain genotypes showed stable changes when grown under reduced-irrigated compared to well-irrigated conditions. Significant correlation coefficients were observed between HTP-related traits and drought related traits, for example, canopy temperature positively correlated with canopy wilting and carbon isotope discrimination traits, indicating that HTP related traits could be used as a direct indictor for stress tolerance in soybean. Statistical analyses over years indicated significant effects for genotypes, environments, and GxE interactions.
Sub-objective 1D focused on understanding the phenotypic variation in traits related to guayule rubber and resin production, a potential new crop for arid-lands and low input regions in the southwestern United States. The USDA guayule collection, including improved breeding germplasm and wild accessions collected from deserts in northern Mexico and southern Texas, were grown in replicated field trials at Maricopa, Arizona, under two irrigation regimes (well-irrigated vs. reduced-irrigation). Plant biomass, resin and rubber content, and production traits were evaluated. Results showed that the guayule collection has wide phenotypic variation in biomass, resin and rubber traits, with differential responses to irrigation treatments among accessions. Results indicated that typically water-stressed conditions increase resin and rubber accumulations, while well-watered conditions increased biomass. Significant correlations between biomass-related and morphological traits and resin and rubber production could indicate the possibility of selection for multiple traits together. This study lays the foundation for guayule breeding efforts. Parental candidates can be selected for abilities to grow under different agricultural systems, with the intent of extending guayule production into different geographical zones and to meet different end-user demands and goals.
The data collected from Objective 1 allowed conducting Objective 2 to identify genes and associated molecular markers associated with abiotic stress tolerance in arid environments. To support Sub-objective 2B and develop genomic tools and information for underpinning those traits, the spring camelina panel was genotyped using genome-by-sequencing (GBS). The camelina panel showed a high level of genetic diversity that could serve as a basis for developing new camelina cultivars with desirable characteristics such as high yield potential, high oil production and tolerance to abiotic stress. Genome-Wide Association Studies (GWAS) analyses were used to associate phenotypic and genotypic data and identify candidate genes controlling the studied traits. GWAS analyses identified 57 Single nucleotide polymorphisms (SNPs) significantly associated with fatty acids, oil content, and protein content. Of the 57 identified SNPs, six SNPs shared associations between different traits, indicating putative genes related to fatty acid biosynthesis and transfer. The leaf cuticle contains a waxy protective layer that has low permeability to water, which directly affects the rate of leaf water loss and thus the susceptibility of plants to drought stress. The GWAS revealed 42 SNP markers that were significantly associated with 15 leaf wax traits, including major wax components such as total primary alcohols, total alkanes, and total wax esters as well as their constituents. These SNP markers are co-localized in genes related to wax biosynthesis. These loci could potentially serve as candidates for the genetic control of intracellular wax transport that could be manipulated to facilitate leaf wax accumulation in camelina. These results and the associated molecular markers will benefit plant breeders and can be used as powerful tools in marker-assisted selection programs to breed improved Camelina sativa cultivars with superior biotic/abiotic tolerance. Salinized soil is one of the abiotic stresses that affect camelina seed germination and thus yield. GWAS analyses identified 19 SNPs that were significantly associated with camelina seed germination rate and seedling dry weight for accessions grown under salt stress. These associated SNP molecular markers are located on the putative candidate genes controlling plant root development and related to salt stress resistance. These identified candidate genes and associated markers could provide a foundation for future molecular breeding efforts aiming to improve salt tolerance in camelina.
Timed floral transition is one plant defense against stress conditions, and impacts seed yield in camelina and other crops. Using GWAS analyses, a total of 20 significant trait-associated SNPs were found to be colocalized within/or near a variety of transcription factors or protein families containing specific functional domains. These transcription factors interact with key regulatory genes in biological pathways to cooperatively regulate floral transition. In addition, the predictive ability to use the current set of molecular markers was estimated for future genomic selection for early flowering. The GWAS results lay the foundation for future molecular breeding efforts to develop early flowering camelina varieties with desirable characteristics such as high seed yield, high oil production and abiotic stress tolerance suitable for sustainable agricultural systems.
Sub-objective 2C supported developing genomic tools and elucidating genomic regions expected to control traits related to drought stress tolerance in soybean. GWAS identified candidate genes may be directly or indirectly associated with transpiration or water conservation. The confirmed genomic regions may be an important resource for pyramiding favorable alleles and as candidates for genomic selection aimed at enhancing soybean drought tolerance. Improving WUE for soybean through selection for the carbon isotope C13 may increase drought tolerance. GWAS identified 71 candidate genes had annotations associated with transpiration or water conservation and transport, root development, root hair elongation, and stomatal complex morphogenesis. These genomic regions associated with trait plasticity will be a useful resource for implementing genomic selection for improving drought tolerance in soybean. GWAS assays conducted on soybeans grown under drought stress condition indicated that 19, 16, and 55 SNPs were respectively significantly associated with leaf wax accumulation, NDVI, and canopy temperature. The putative trait-associated SNPs will be used to explore the candidate genes/molecular mechanisms underlying wax and secondary metabolite biosynthesis, plant growth, and development in relation to drought stress toward developing molecular makers to be used in breeding programs.
Accomplishments
1. Identification of genomic regions associated with carbon isotope discrimination in soybean. Improvements in water use efficiency (WUE) in soybean through selection for carbon discrimination ratio appears possible due to the positive association between C13 ratio and WUE. This can be used to improve soybean resiliency to drought. ARS researchers in Maricopa, Arizona, Stoneville, Mississippi, and Columbia, Missouri, in collaboration with researchers from the University of Arkansas and University of Missouri, designed a multi-state trial to assay a soybean diversity panel under irrigated and rain-fed conditions to identify genomic regions associated with the stability of C13. Genome-wide association mapping approach identified SNP located within genes that have biological annotations associated with drought stress tolerance, such as transpiration rates, water transport, root development, root hair elongation, and stomatal complex morphogenesis. Those genomic regions and candidate genes may provide the basis for genomic selection and rapid improvement of drought.
2. Characterization of genetic diversity in a USDA collection of Brassica juncea. The success of plant biofuels relies on finding inexpensive feedstocks that can be cultivated economically in diverse geographical regions and agricultural production systems. ARS scientists in Maricopa, Arizona, explored the genetic diversity of a USDA collection of Brassica juncea, a promising biodiesel crop. Population structure analyses, based on 99 thousand identified SNPs, revealed five distinct subpopulations. Variation in genetic diversity indexes indicate that directed selection and geographical adaptation may have affected the formation and differentiation within B. juncea natural populations. The genotyped panel coupled with identified SNP markers is a great resource for allele/gene identification using genome-wide association analysis studies and marker-assisted selection approaches. This information provides a tool to enhance genetic gain in Brassica juncea breeding programs for biofuel and other economically related traits.
Review Publications
Kim, J.Y., Abdel-Haleem, H.A., Luo, Z., Szczepanek, A.E. 2022. Open-source electronics for plant phenotyping and irrigation in controlled environment. Smart Agricultural Technology. 3. Article 100093. https://doi.org/10.1016/j.atech.2022.100093.
Abdel-Haleem, H.A., Luo, Z., Szczepanek, A.E. 2022. Genetic diversity and population structure of the USDA collection of Brassica juncea L. Industrial Crops and Products. 187(Part A). Article 115379. https://doi.org/10.1016/j.indcrop.2022.115379.
Chamarthi, S., Kaler, A., Abdel-Haleem, H.A., Fritschi, F., Gillman, J.D., Ray, J.D., Smith, J.R., Purcell, L. 2022. Identification of genomic regions associated with the plasticity of carbon 13 ratio in soybean. The Plant Genome. 16(1). Article e20284. https://doi.org/10.1002/tpg2.20284.
