Research Project: Genetics of Disease Resistance and Food Quality Traits in Corn

Location: Plant Science Research

2022 Annual Report

Objectives
1. Identify genes and mechanisms underlying defense response and quantitative disease resistance to foliar fungal pathogens and ear stalk rots in maize. [NP301, C1, PS1A] 1.A. Validate and fine-map QTL alleles underlying multiple disease resistance in maize. 1.B. Test the effects of candidate SLB resistance genes using transgenic and mutant analysis. 1.C. Assess the resistance of diverse lines to Anthracnose stalk rot. 1.D. Validate the roles of genes associated with variation in the maize hypersensitive response (HR). 1.E. Validate the effects of candidate QTL identified in genome-wide association studies of Fusarium ear rot. 2. Test new methods of genomics-assisted breeding for quantitative disease resistance in maize to improve productivity and food safety. Conduct genomic selection for resistance to Fusarium ear rot. [NP301, C1, PS1A] 3. Evaluate diverse maize germplasm for potential in specialty food products by conducting agronomic and disease evaluations. [NP301, C1, PS1B] 3.A. Evaluate open-pollinated varieties for food quality and agronomic production characteristics. 3.B. Develop populations with lower grain protein content for use in metabolic disorder diets. 4. Manage and coordinate the Southeastern component of a multi-year, multi-site, cooperative program of maize genetic resource evaluation, genetic enhancement, inbred line development, and information sharing which will broaden the genetic base for U.S. maize. [NP301, C1, PS1A, PS1B] 5. Evaluate temperate, subtropical, and tropical maize genetic resources for adaptation, yield, resistance to ear, stalk, and foliar diseases, tolerance to environmental extremes, and selected value-added, product quality traits. Record and disseminate evaluation data via the GEM database, GEM website, GRIN-Global, and other data sources. [NP301, C2, PS2A] 6. Breed and release maize populations and inbred lines with primarily 50% unadapted/50% temperate pedigrees which contribute to U.S. maize more diverse genetic resistance to diseases, tolerance to environmental extremes, higher yield, unique product qualities, other valuable new traits, or which enable maize trait analysis and allelic diversity research. [NP301, C1, PS1B] 6.A. Evaluate additional nursery rows of breeding crosses for grain yield. 6.B. Evaluate additional field trial plots for disease resistance. 6.C. Evaluate new breeding populations for tolerance to environmental extremes, and selected value-added, product quality traits. This research will be implemented by increasing the number of nursery rows and field trial plots focused on improving yield; disease resistance; value-added, product quality traits; and related breeding values of maize populations and inbred lines in the southeastern United States.

Approach
We selected 37 near-isogenic lines carrying the 30 most effective multiple disease resistance genes based on previous evaluations. We will produce F2:3 mapping populations of about 100 lines each and rate their disease reactions in replicated field trials. SNP markers will be used to test the effect of each QTL in mostly homogeneous genetic backgrounds. We previously identified 16 candidate genes for southern leaf blight resistance based on detailed genome-wide association analysis. To functionally characterize these genes, we will first identify and assess lines in which a Mu transposon has inserted into the candidate gene. Also, we will over-express or silence the gene of interest using transgenesis and evaluate the resulting disease phenotypes. We also identified 6 candidate genes associated with modulation of the maize hypersensitive response. We will test if these candidate genes can suppress hypersensitive response using transient expression assays in Nicotiana benthamiana, test if their proteins interact physically with the hypersensitive response trigger protein Rp1-D21 using co-immunoprecipitation assays, and also attempt to identify UnifomMu insertional mutants in these candidate genes and determine whether mutation of these genes affects the hypersensitive response. We will assess resistance to Anthracnose stalk rot in 30 diverse maize inbred lines grown in replicated field trials under artificial inoculation. We will test the effects of candidate QTL identified in previous genome-wide association studies of Fusarium ear rot in three new biparental cross families. The new lines will be genotyped at SNP markers previously associations with ear rot resistance and grown in replicated field trials under artificial inoculation with Fusarium. Statistical tests of association between SNP genotypes and ear rot resistance in these new populations will be used to independently evaluate their effects. We will test the effectiveness of genomic selection in a genetically broad-based population. S1 lines from this population were densely genotyped and evaluated across multiple environments to create a training model for genomic selection. Four cycles of genomic recurrent selection will be conducted among individual plants in this population. One cycle of phenotypic selection among replicated S1 lines will be conducted in parallel in the same time frame. Lines resulting from both procedures will be tested in common field trials to compare the effectiveness of genomic and phenotypic selection in this population. Field evaluations and traditional breeding approaches will be applied to corn populations derived from heirloom populations to find the best sources of agronomic and food quality performance and to initiate within-population selection for improvements in these traits. Traditional breeding methods will also be implemented in crosses between corn lines with lower protein content to attempt to obtain varieties with lower protein content to serve as alternative foods for patients with metabolic disorders.

Progress Report
ARS scientists at Raleigh, North Carolina, assessed F2:3 Populations mapping populations to validate and fine-map genes underlying multiple disease resistance in maize. We assessed maize plants carrying transposal element insertions in candidate SLB resistance genes. We validated the roles of several genes associated with variation in the maize hypersensitive response (related to disease resistance). We evaluated lines selected from populations developed by genomic selection or by phenotypic selection for resistance to Fusarium ear rot in a maize population. We selected for superior productivity, disease resistance, and ear quality within 12 heirloom populations. We evaluated diverse inbred lines and hybrids in the field for grain protein content, and a subset of those for specific amino acid contents. We coordinated 6000 yield plots from Raleigh, North Carolina, with about 1000 planted in North Carolina and the rest planted by five cooperators at various locations throughout the Southeast and Midwest. The results of second year trials will determine which entries are recommended to the Germplasm Enhancement of Maize project cooperators. Disease evaluation continues in 2022 for resistance to aflatoxin accumulation, with trials conducted by collaborators in Mississippi, Texas, and Georgia. Over 150 new breeding crosses were observed for agronomic traits of interest.

Accomplishments
1. The Germplasm Enhancement of Maize (GEM) project is a cooperative effort of public and private sector maize breeders to enhance the genetic diversity of the U.S. maize crop. The GEM project selects lines with high yield potential from crosses between elite temperate lines and exotic parents. The GEM program has released hundreds of useful breeding lines based on traditional phenotypic selection. Developing genomic prediction models for the GEM program may contribute to increases in the rate of genetic gain. ARS scientists at Raleigh, North Carolina used genotypic information and yield trial data on GEM hybrids to create genomic prediction models for this program. We demonstrated that the accuracy of genomic prediction models was at least as good as phenotypic selection for yield and grain moisture. The genomic prediction models have the advantage that they can be applied to new GEM lines before expensive and time-consuming hybrid production and yield trial. Genomic prediction models should help the GEM program more effectively deliver on its mission to broaden the genetic base of United States germplasm in the future.

Review Publications
Diepenbrock, C.H., Ilut, D.C., Magallanes-Lundback, M., Kandianis, C.B., Lipka, A.E., Bradbury, P., Holland, J.B., Hamilton, J.P., Wooldridge, E., Vaillancourt, B., Góngora-Castillo, E., Wallace, J.G., Cepela, J., Mateos-Hernandez, M., Owens, B.F., Tiede, T., Buckler IV, E.S., Rocheford, T., Buell, C., Gore, M.A., Dellapenna, D. 2021. Eleven biosynthetic genes explain the majority of natural variation in carotenoid levels in maize grain. The Plant Cell. 33(4):882–900. https://doi.org/10.1093/plcell/koab032.
Rogers, A.R., Dunne, J.C., Romay, M.C., Bohn, M., Buckler IV, E.S., Ciampitti, I.C., Edwards, J.W., Ertl, D., Flint Garcia, S.A., Gore, M.A., Graham, C., Hirsch, C.N., Hood, E.C., Hooker, D., Knoll, J.E., Lee, E.C., Lorenz, A., Lynch, J.P., Mckay, J., Moose, S.P., Murray, S.C., Nelson, R., Rocheford, T., Schnable, J.C., Schnable, P.S., Sekhon, R., Singh, M., Smith, M., Springer, N., Thelen, K., Thomison, P., Thompson, A., Tuinstra, M., Wallace, J., Wisser, R., Xu, W., Gilmour, A., Kaeppler, S.M., Deleon, N., Holland, J.B. 2021. The importance of dominance and genotype-by-environment interactions on grain yield variation in a large-scale public cooperative maize experiment. Genes, Genomes, Genetics. 11(2):jkaa050. https://doi.org/10.1093/g3journal/jkaa050.
Balint Kurti, P.J., Kim, S. 2022. Close encounters in the corn field. Molecular Plant. 15:802-804. https://doi.org/10.1016/j.molp.2022.02.008.
Ge, C., Wang, Y., Lu, S., Zhao, X., Hou, B., Balint Kurti, P.J., Wang, G. 2021. Multi-omics analyses reveal the regulatory network and the function of ZmUGTs in maize defense response. Frontiers in Plant Science. 12:738261. https://doi.org/10.3389/fpls.2021.738261.
Martins, L., Balint Kurti, P.J., Reberg-Horton, C. 2022. Genome-wide association study for morphological traits and resistance to Peryonella pinodes in the USDA pea single-plant plus collection. Genes, Genomes, and Genomics. 12(9):jkac168. https://doi.org/10.1093/g3journal/jkac168.
Samayoa, L., Olukolu, B.A., Yang, C.J., Chen, Q., Stetter, M.G., York, A.M., Sanchez-Gonzalez, J., Glaubitz, J.C., Bradbury, P., Cinta Romay, M., Sun, Q., Yang, J., Ross-Ibarra, J., Buckler IV, E.S., Doebley, J.F., Holland, J.B. 2021. Domestication reshaped the genetic basis of inbreeding depression in a maize landrace compared to its wild relative, teosinte. PLoS Genetics. 2:1009797. https://doi.org/10.6084/m9.figshare.14750790.
Butoto, E., Brewer, J.C., Holland, J.B. 2022. Empirical comparison of genomic and phenotypic selection for resistance to Fusarium ear rot and fumonisin contamination in maize. Theoretical and Applied Genetics. https://doi.org/10.1007/s00122-022-04150-8.
Lauer, E., Holland, J.B., Isik, F. 2021. Genomic prediction ability affected by the degree of genetic relationship with the training population in Pinus taeda. G3, Genes/Genomes/Genetics. 12:2. https://doi.org/10.1093/g3journal/jkab405.
Rogers, A., Holland, J.B. 2021. Environment-specific genomic prediction ability in maize using environmental covariates depends on environmental similarity to training data. G3, Genes/Genomes/Genetics. https://doi.org/10.1093/g3journal/jkab440.