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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

2016 Annual Report

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. Objective 6: Develop and improve sources of resistance in maize to corn rootworm larval feeding. Objective 7: Characterize Western corn rootworm colonies with resistance to Bacillus thuringiensis (Bt) toxins to facilitate better resistance management decisions.

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 have completed all phenotypic and genotypic activities for the Zea Synthetic doubled haploid (DH) population comprised of nearly 2000 DH lines ahead of schedule. Genetic analysis is ongoing including genome wide association mapping (GWAS) of all traits and the analysis of haplotypes that have been selected during DH development. We have completed multiple rounds of seed increase, but continue to attempt increases of problematic lines for the public release that is scheduled for FY17. We have also completed all phenotypic and genotypic activities for the 2000 selfed families of the Teosinte Synthetic population ahead of schedule. Likewise, genetic analysis is underway including GWAS for all the traits that were evaluated, and a genome-wide scan for significant two-locus epistatic interactions. The fine mapping projects involving heterosis and 2- ß-D-glucopyranosyloxy-4-hydroxy-7-methoxy-1,4-benzoxazin-3-one DIMBOA (1.1 and 1.2) have been discontinued with the retirement of the senior researcher on the project plan in 2014. 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 at least one year. We began a replicated long-term selection program based on the open-pollenated variety of maize called Shoepeg. Seed for the initial population was increased in the greenhouse in winter 2015 and spring 2016. The population was planted summer 2016 and selections are being conducted for tall and short plants. We have begun setting up an area of one lab where we will focus on long-term selection and experimental evolution in the green algae chlamydomonas, to parallel our selection work with maize. Results observed in algae will directly translate to and direct the methods we use for studying maize. We initiated work to develop two Epistasis Mapping Populations (EMPs). These are being developed in the summer of 2016 via diallel crosses of 20 selected near isogenic lines that were previously developed. We are continuing development of a B73 x B97 population of near isogenic lines. The lines are planted in the nursery for self-pollinating in summer 2016. We developed a pipeline to evaluate Medical Subject Headings (MeSH terms) that can be used for enrichment analysis in maize. This method is similar to gene ontology (GO) evaluation, but it can provide an independent confirmation of Gene Ontology (GO) results or additional biological hypotheses. We refined this method by studying data from chickens, and then we applied it to several maize datasets to learn about the biology of domestication and recent artificial selection for the improvement of important agronomic traits. We are in the process of developing, in collaboration with scientists in Germany, a method to test which quantitative traits have been selected over the course of the past several generations. Inputs for this method are a modern genotyped and phenotyped population, coupled with an estimate of allele frequencies from past generations. We have extended our analysis of the transcription factor expression data to begin to determine the downstream gene targets for each transcription factor regulated by water deficit treatments. We have completed a transcriptome study that will form the basis of our network analysis to determine the gene expression “hub” position that each transcription factor occupies. We completed construction of artificial micro-ribonucleic acids (miRNAs) under the control of a chemically inducible promoter to control timing of expression and once funds are available transformations will be started to produce transgenic maize. We are also developing an in vivo assessment of the constructs using transient assays in a model species. We have completed a detailed comparison of nitrogen remobilization during dehydration stress, comparing plants with added nitrogen and low nitrogen inputs using N15 labeled ammonium nitrate. Analysis of the data will be completed in FY16. We have also assessed nitrogen remobilization from mature leaves using N15 labeled glutamate directly applied to the leaves. We have completed our analysis of root metabolomes for both Sporobolus stapfianus and Sporobolus pyramidalis in order to compare the response of roots to dehydration in a tolerant (stapfianus) with a sensitive (pyramidalis) grass species. We are close to completing the genomes of both grass models which will serve not only as a genomic resource but also to ensure that we can target the specific member of the gene family that controls and regulates the biosynthesis and catabolism of our target metabolites, gamma-glutamyl amino acids (GGAAs), in S. stapfianus and by extension maize. Gene isolation for transgenic analyses is underway. We have developed a soil-plate based system for quantifying wheat seedling root length in under water stress conditions and established analysis protocols to allow for accurate screening of the genetic diversity for water deficit responses of roots of various wheat genotypes. We have utilized this controlled system to conduct water stress root length experiments to assess wheat genotypes that we obtained from the ARS Pullman, WA lab. Contrasting genotypes that differ in their root growth responses are currently under assessment. We have developed a method for extraction and quantification of Abscisic Acid (ABA) and Giberellic Acid (GA) hormones from wheat roots by liquid chromatography-mass spectroscopy (LC-MS) and have collected tissues for hormone extractions from seminal roots of several wheat varieties under water stress. The first analyses of these extracts are underway.

1. Root metabolic responses in contrasting C4 grass species that vary in dehydration tolerance. Drought threatens food security and contributes to the growing problem of malnutrition and hunger. Because of their role in supplying water and minerals to the plant, roots are at the center of the response to water deficit and the signals they generate are critical to the overall plant’s response to a dehydration event. ARS scientists in Columbia, Missouri are studying the dehydration-induced metabolic responses of root tips in two forage grass species that differ in their ability to survive dehydration. ARS scientists have determined that roots of the tolerant species are pre-programmed metabolically for a dehydration event and respond less to a drought than do the roots of the sensitive species. The tolerant roots also appear to send a metabolic signal to the shoot to prepare the plant for reduced water availability, a signal that is not produced by the sensitive plant. Understanding how these metabolic responses function to control the damaging effects of water deficit on root function and limit shoot growth will enable the development of novel breeding strategies to improve the drought tolerance of economically important grass crops such as corn, rice, and wheat.

2. A computational pipeline enabling the use of Medical Subject Headings (MeSH terms) for biological interpretations in maize. MeSH terms, which are assigned to published manuscripts at the National Library of Medicine and can be publicly accessed via PubMed, contain valuable information regarding the biological function of genes or sets of genes. ARS scientists in Columbia, Missouri have developed a pipeline that can be easily applied to maize data for the end goal of generating or confirming biological hypotheses. Researchers anywhere can input a list of genes and the output will be a list of terms relating these genes to one another. If the input genes are all related to the same trait, MeSH analysis can identify this trait as a target of interest. The pipeline allows researchers and breeders to understand how domestication of maize influenced agronomic traits and with thus enhance our capabilities to more rapidly improve maize as a crop.

Review Publications
Liu, Z., Cook, J., Melia-Hancock, S., Guill, K.E., Bottoms, C., Garcia, A., Ott, O., Nelson, R., Recker, J., Balint-Kurti, P.J., Larsson, S., Lepak, N.K., Buckler, E.S., Trimble, L., Tracy, W., McMullen, M.D., Flint-Garcia, S.A. 2016. Expanding maize genetic resources with predomestication alleles: maize-teosinte introgression populations. The Plant Genome. 9(1). doi:10.3835/plantgenome2015.07.0053.
Lennon, J., Krakowsky, M.D., Goodman, M., Flint Garcia, S.A., Balint Kurti, P.J. 2016. Identification of alleles conferring resistance to gray leaf spot in maize derived from its wild progenitor species teosinte (Zea mays ssp. parviglumis). Crop Science. 56:209-218.
Oliver, M.J. 2014. Why we need GMO crops in agriculture. Missouri Medicine. 111.6:493-507.
Mahmoud, M.A., Sharp, R.E., Oliver, M.J., Finke, D.L., Ellersieck, M.R., Hibbard, B.E. 2016. The effect of western corn rootworm (Coleoptera: Chrysomelidae) and water deficit on maize performance under controlled conditions. Journal of Economic Entomology. 109:864-898.
Beissinger, T.M., Wang, L., Crosby, K., Durvasula, A., Hufford, M.B., Ross-Ibarra, J. 2016. Recent demography drives changes in linked selection across the maize genome. Nature Plants. doi:10.1038/nplants.2016.84.
Venkatesh, T.V., Chassy, A., Fiehn, O., Flint Garcia, S.A., Zeng, Q., Skogerson, K., Harrigan, G.G. 2016. Metabolomic assessment of key maize resources: GC-MS and NMR profiling of grain from B73 hybrids of the nested association mapping (NAM) founders and of geographically diverse landraces. Journal of Agricultural and Food Chemistry. 64(10):2162-2172. doi: 10.1021/acs.jafc.5b04901.