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ARS Home » Midwest Area » Columbia, Missouri » Plant Genetics Research » Research » Research Project #424655

Research Project: Genetics and Genomics of Complex Traits in Grain Crops

Location: Plant Genetics Research

2015 Annual Report


Objectives
Objective 1: Create novel genetic resources for complex trait dissection in diverse maize germplasm. • Sub-objective 1.1: Create, genotype, and phenotype doubled haploid (DH) lines from a synthetic population containing diverse germplasm, including teosinte alleles. • Sub-objective 1.2: Create, genotype and phenotype novel quantitative trait loci (QTL) populations derived from a (teosinte x B73) x B73 population. Objective 2: Characterize the genetic basis of important agronomic traits (heterosis, drought tolerance, yield components, DIMBOA synthesis, and kernel composition) in maize. • Sub-objective 2.1: Determine the genetic basis of heterosis and its relationship to recombination and the Hill-Robertson effect. • Sub-objective 2.2: Fine-map the regulatory site for the major QTL of DIMBOA synthesis for chromosome 4 from CI31A. • Sub-objective 2.3: Fine map the genes responsible for a KRN QTL on chromosome 2 in a teosinte x maize population. • Sub-objective 2.4: Determine the genetic basis of kernel composition in maize x teosinte introgression libraries, and compare the QTL and effects to those observed in maize. Objective 3: Determine molecular and biochemical mechanisms of drought tolerance in maize and model species. • Sub-objective 3.1: Determine the expression patterns of transcription factor (TF) genes in the drought response of maize. • Sub-objective 3.2: To fully characterize the molecular genetic basis of the conserved interplay between reactive oxygen species (ROS) and amino acid metabolism, linked through gamma-glutamyl amino acids (GGAA) metabolism and transport, and the role of GGAA metabolism in dehydration tolerance. Objective 4: Identify and curate key datasets that will serve to benchmark genomic discovery tools for key agronomic traits, especially response to biotic and abiotic environmental stressors. • Sub-objective 4.1: Bring into The Maize Genome Database (MaizeGDB) the phenotypic data generated by critically important research endeavors including the Maize Diversity Project. • Sub-objective 4.2: Curate maize metabolism and pathways data for release as a BioCyc database and as GO annotation files. Objective 5: Characterize the relationship between root biology and drought tolerance in wheat and related species. • Sub-objective 5.1: Elucidate the physiological basis of root growth responses in wheat (hard and soft red winter) and the “wheat model” Brachypodium distachyon, to imposed water deficits.


Approach
Create and fully describe double haploid lines and QTL populations for complex trait dissection. Map and characterize yield QTLs to interrogate the genetic basis of heterosis in maize. Use QTL fine mapping protocols to define the genetic regulation of DIMBOA synthesis in maize. Develop targeted metabolomic profiles to define the role of nitrogen metabolism in establishing dehydration tolerance in the C4 grasses, including maize. Combine field experiments and transgenic maize lines to determine the role of selected transcription factors in the response of roots to water deficits and their possible role in drought tolerance. Use modern curation tools to improve the phenotype to gene utility of the MaizeGDB and improve linkages to other community database efforts.


Progress Report
We evaluated nearly 3000 Doubled Haploids (DH) created from the Zea Synthetic for uniformity and self-pollinated the lines to increase seed stocks for future trials and deposition in the Maize Genetics Stock Center. We evaluated 2000 DH lines in a three location trial (MO, NC, NY) in summer 2015 for agronomic and fitness related traits. The 2000 DH lines have been submitted for genotyping-by-sequencing, and the first 20 96-well plates of genotypic data have been received. Because the Zea Synthetic is a randomly mated population containing alleles from diverse maize inbreds and teosinte, this set of DH lines is a unique resource for systematically evaluating the phenotypic effects of severe inbreeding on alleles from temperate and tropical maize alleles, as well as teosinte, the progenitor of maize. In addition we evaluated 2000 selfed families from the Teosinte Synthetic for second year in summer 2015, collecting data for agronomic traits such as flowering time and plant and ear height. Ears will be harvested in the fall for collection of ear and kernel data. All leaf samples have been collected for DNA extraction in the winter of 2015/16. The purpose of this trial is to search for epistatic interactions (gene x gene interactions) among the regions of the teosinte genome that contribute to phenotypic variation in the population. The kernel row number fine mapping project has been completed and the results were included in a manuscript submitted in FY14. The kernel composition fine mapping project (1.4) has been delayed by crop failure in Puerto Rico because of high insect pressure, and our inability to plant our genetics nursery in Columbia, MO in 2015 due to extremely wet weather. Initial crosses have been made for a small number of near isogenic lines (NILs), but the self-generation to make F2s has not been completed. This research will continue, but will be behind schedule by one year. We have extended our analysis of the transcription factor expression data from the lab-based studies to greenhouse and field samples and we have developed the artificial mico-ribonucleaic acid (miRNA) constructs to perform our selective drought functional assays using a knock-down or knock-out strategy. We are also constructing artificial miRNAs under the control of a chemically inducible promoter to control timing of expression. We have completed our analysis of native miRNA responses to drought in maize roots and have established the gene targets that are controlled by each one. Our research has led to the identification of a drought-induced target mimic that may protect the maize seedling from miRNAs that alter phosphate uptake mechanisms. We have demonstrated the movement of nitrogen from old to young leaves during dehydration using N15 labeling. We have completed our non-targeted metabolite profiles for both roots and shoots of our dehydration sensitive model species, Sporobolus pyramidalis, to complement our data for Sporobolus stapfianus and maize. We have maximized the likelihood that we can isolate the appropriate and desired Sporobolus sequences for cloning by enhancing our coverage for draft full genome sequence for both Sporobolus species. The specific genes we need to control and regulate the biosynthesis and catabolism of the gamma-glutamyl amino acids (GGAAs) in both S. stapfianus and maize have been targeted but unfortunately each gene is a member of a very large family of genes, which complicates the analysis. We are currently trying to determine which specific member of each gene family to target for our transgenic studies. The PCR cloning of these genes is underway. New phenotype data for public germplasm has been integrated into MaizeGDB, using the workflow developed last year and is accessible at MaizeGDB from an interface listed on the Diversity page (see accomplishment). This year, the phenotype data covered ~3000 US elite inbreds, in addition to the ~5000 recombinant inbreds from diverse mapping populations (Nested Association Map or NAM; Intermated B73 x Mo17 or IBM) developed from elite inbreds. Much of the effort required germplasm record maintenance at MaizeGDB to include all synonyms used in the literature, and links to public resources where the germplasm is freely available. These resources include the USDA-ARS National Genetic Resources Program (GRIN)/North Central Plant Introduction Station, Ames, IA; the USDA-ARS Maize Genetics Cooperation Stock Center, Urbana, IL; and the International Maize and Wheat Improvement Center (CIMMYT), Mexico. Maintaining germplasm names, synonyms and links facilitates development of MaizeGDB tools that link phenotype data to the extensive genotyping available for over 14,000 maize inbred lines. All data has been published in peer reviewed publications, and much of it is from USDA-ARS researchers on this project, Raleigh NC, Ithaca, NY, and their collaborators. New phenotype evaluations added this year include disease and insect responses, root anatomy and growth, shoot apical meristem size, whole plant architecture, and starch quality properties. This integration used the workflow/pipeline developed during the first year of this project, and international annotation standards, including Plant Ontology, Trait Ontology, and Gene Ontology. We continue to work with developers of all ontologies to ensure granularity appropriate to maize, and with the MaizeGDB team towards enhanced data access that leverages the hierarchy of the ontology dictionaries, in addition to using them as controlled machine readable vocabularies. Related to this work, we will provide an updated Plant Ontology annotation to the group, now part of a Planteome project (www.planteome.org). The major update comes from the Gene Expression Atlas at MaizeGDB, soon to be updated with an RNA-seq dataset that is not only of higher quality than the earlier microarray data, but includes several new root tissues. Metabolism annotation of CornCyc for experimentally verified maize genes encoding enzymes in photosynthesis, carbohydrate metabolism, and response to diseases and pests. This is a collaboration with PMN (Plant Metabolic Networks, Stanford CA), who maintain the software with the MaizeGDB team in Ames, IA and the MetaCyc database team at SRI, Menlo Park, CA. In addition, Gene Ontology (GO) annotation has been expanded to include genes with phenotypes, regardless of roles in metabolism. This involves collaboration with the Ames MaizeGDB team. This expansion meets a recommendation of the MaizeGDB working group, namely that we annotate experimentally confirmed function of genes other than those encoding enzymes. In addition, the GO annotation activity is synergistic with an NSF-funded Phenotype RCN (Research Coordination Networks) project, where MaizeGDB has been a collaborator for many years. Arrangements have been made with the Gene Ontology Consortium (GOC) to receive our annotation files, being readied for submission to the GOC late summer 2015. Objective 5 Experiments have been initiated and we anticipate a rapid advancement to the completion of milestones for this objective.


Accomplishments
1. Comprehensive public maize phenotype datasets. Public data generated by USDA-ARS researchers in Columbia, MO and other ARS and university locations has been available in many different formats and on-line locations. This makes it difficult for researchers to access all the data for the large statistical analyses required to associate naturally occurring genomic variations with favorable agronomic traits and phenotypes. To address this problem, comprehensive public maize phenotype evaluation data are now readily accessible in a single format at the Maize Genetics and Genomics Database (MaizeGDB) Diversity page. In addition, the data are annotated using international standards designed to promote easy data exchange among different databases for maize, other crop plants and model plant species. Each data point at MaizeGDB has links to source publications, environments, summaries of methods used to measure phenotypes, and germplasm sources. Germplasm source links include the USDA-ARS in Urbana, IL, the USDA-ARS in Ames, IA, and the International Maize and Wheat Improvement Center, in Mexico. These database entries and tools improve the ability of maize geneticists and breeders to pursue maize improvement to meet food security needs.

2. Genetic control of the drought response of maize roots. Drought threatens food security and contributes to the growing problem of malnutrition and hunger. Understanding how plants respond to soil water deficits at the genetic and genomic level is critical to develop drought tolerant crops. ARS scientists in Columbia, MO are studying the drought-induced response of molecules called miRNAs that inhibit the expression of protein-coding genes. ARS scientists identified more than 40 miRNAs in the growth zone of the maize primary root that significantly respond to water deficits. Among the water deficit responsive miRNAs was a family known to inhibit phosphate uptake by the plant. This would suggest that during drought, maize productivity could be impaired due to an inability to extract phosphate, an essential nutrient, from the soil for growth. It was also discovered that during drought, maize root tips also accumulate an RNA molecule that may protect the ability of the critical root areas to access soil phosphate during a drought. Understanding how these genetic control elements function to control the damaging effects of water deficit on root function will enable the development of novel breeding strategies to improve the drought tolerance of corn and other grain crops.


Review Publications
Venkatesh, T.V., Harrigan, G.G., Perez, T., Flint-Garcia, S.A. 2015. Compositional assessments of key maize populations: B73 hybrids of the nested association mapping founder lines and diverse landrace inbred lines. Journal of Agricultural and Food Chemistry. 63:5282-5295.
Teixeira, J.E., Weldekidan, T., de Leon, N., Flint Garcia, S.A., Holland, J.B., Lauter, N.C., Murray, S.C., Xu, W., Hessel, D., Kleintop, A.E., Hawk, J., Hallauer, A.R., Wisser, R. 2015. Hallauer’s Tusón: a decade of selection for tropical-to-temperate phenological adaptation in maize. Heredity. 114:229-240.
Hirsch, C.N., Flint Garcia, S.A., Beissinger, T.M., Eichten, S.R., Deshpande, S., Barry, K., Mcmullen, M.D., Holland, J.B., Buckler IV, E.S., Springer, N., Buell, R.C., de Leon, N., Kaeppler, S.M. 2014. Insights into the effects of long-term artificial selection on seed size in maize. Genetics. 198(1):409-421.
Xiao, L., Yang, G., Zhang, L., Yang, X., Zhao, S., Ji, Z., Zhou, Q., Hu, M., Oliver, M.J., He, Y., et.al 2015. The resurrection genome of Boea hygrometrica: A blueprint for survival of dehydration. Proceedings of the National Academy of Sciences. 112(18):5833-5837.