Location: Corn Insects and Crop Genetics Research2021 Annual Report
Objective 1. Discover diverse fungal disease resistance mechanisms in cereal (barley and maize) crops. Sub-Objective 1A. Use expression quantitative trait locus (eQTL) analysis in combination with genome-wide promoter-motif enrichment strategies to discover master regulators of immunity. Sub-Objective 1B: Identify host targets of pathogen effectors by next generation yeast-two-hybrid interaction screens. Sub-Objective 1C: Identify and characterize the genetic and molecular pathological modes of action for isolate-specific and non-specific Quantitative Disease Resistance (QDR) mechanisms that protect corn plants against northern leaf blight. Objective 2: Generate novel sets of disease defense alleles for mechanistic dissection and application to crop protection. Sub-Objective 2A: Functional confirmation via integrated reverse genetic analysis. Sub-Objective 2B: Evaluate yield and northern leaf blight resistance properties of QDR alleles in hybrid genetic contexts.
Large-scale sequencing of plant and pathogen genomes has provided unprecedented access to the genes and gene networks that underlie diverse outcomes in host-pathogen interactions. Determination of regulatory focal points critical to these interactions will provide the molecular foundation necessary to dissect important disease resistance pathways. This knowledge can be used to guide modern plant breeding efforts in response to pathogens that present diverse challenges to the host.
Fungal pathogens are the greatest threats to cereal grain production worldwide. ARS scientists in Ames, Iowa, use plant-pathogen interactions of barley and corn to identify both host disease defense components and pathogen signaling molecules that suppress them. By understanding how plants and pathogens influence each other during complex interactions, geneticists and breeders can tip the scales in favor of the crop plants to promote more stable and more efficient production. Significant new insights into disease resistance signaling were obtained in FY2021. To create a foundation for Objective 1, Sub-Objective 1B, novel computational resources were developed for genome-wide analysis of protein-protein interactions among the barley host and its powdery mildew pathogen. These interactions regulate a wide range of biological processes, most significantly resistance to yield and quality reducing diseases. Extra help was obtained from graduate students at Iowa State University and extramural funding was obtained from Fulbright - Minciencias 2015 & Schlumberger Faculty for the Future fellowships, USDA-NIFA-ELI Postdoctoral Fellowship, Oak Ridge Institute for Science and Education (ORISE), National Science Foundation - Plant Genome Research Program, and USDA-National Institute of Food and Agriculture. Over the years, many techniques have been used to investigate protein-protein interactions. Among these, yeast two-hybrid (Y2H) has been integrated with next generation sequencing (NGS) to perform these investigations on a genome-wide scale. The fusion of these two methods has been termed next-generation-interaction screening, abbreviated as Y2H-NGIS. However, the diverse data sets resulting from this technology have presented many challenges to analysis. To advance Objective 1, Sub-Objective 1B, new computational resources were developed to identify high-confidence interacting proteins, and also to provide practical help to the non-specialist in computerized methodology. Two novel software programs were established, NGPINT (A Next-generation protein-protein interaction software) and Y2H-SCORES, which can be utilized for model and non-model organisms. They also demonstrated how the system works experimentally, by validating novel interactions between, MLA6, a barley powdery mildew resistance protein, and fourteen cellular targets, including proteins involved in signaling, transcriptional regulation, and intracellular trafficking. Since the barley MLA immune receptor is an ancestral gene for resistance to many important cereal diseases, results from these investigations can be applied to other host-pathogen interactions as well, including Ug99 stem rust, stripe rust, victoria blight, and rice blast. NGPINT and Y2H-SCORES software are published in Briefings in Bioinformatics and PLoS Computational Biology and are available at GitHub repositories https://github.com/Wiselab2/NGPINT and https://github.com/Wiselab2/Y2H-SCORES/tree/master/Software, respectively. Application of NGPINT and Y2H SCORES will enable scientists to model cellular behavior via relevant biological networks. This will promote new investigations from lab to fields, critical to breeders and growers that use stress resistance to produce better crops. In contrast to barley, whose disease defense relies heavily on classical disease resistance genes that initiate signaling cascades resulting in qualitative resistance, maize relies more on quantitative disease resistance (QDR) mechanisms. This is consequential to breeding because it dictates the types of approaches that should be used to prevent and mitigate disease outbreaks. For Objective 1, Sub-Objective 1C, no additional northern corn leaf blight studies were conducted in 2020. Efforts were impacted by the pandemic in 2020 and the unexpected passing of an SY in 2021. Collaborative efforts with Iowa State University scientists were continued to conduct transcriptomic and proteomic evaluations of experimental maize genotypes produced from introgression breeding. These include genetic mapping of metabolite quantitative trait loci (mQTL) and protein quantitative trait loci (pQTL). This research will help identify and better understand the mechanisms of infection by northern corn leaf blight and resistance in maize.
1. Novel disease resistance in barley. Fungal pathogens are among the greatest threats to cereal grain production worldwide. ARS scientists in Ames, Iowa, and funded by the National Science Foundation-Plant Genome Research Program, used genomic methods to identify a novel variant of SGT1, a protein vital for all life, in barley. This variant contains a unique mutation in the structural region that helps to stabilize other disease resistance proteins. In nature, mutations to SGT1 are usually lethal, but this research deomnstrates for the first time a unique modificaiton that delineates the requirement for some disease resistances, while unaffecting others as well as normal cell processes. This discovery can be used to predict regions by which pathogen effectors and host proteins interact with SGT1, facilitating precise editing of effector imcompatible, disease resistance crops. LOG NO. 377317.
2. Maize silk expression atlas. Each year, growers across the globe collectively produce approximately one million corn kernels per human on the planet. These corn kernels are produced through cross-pollination, which occurs when pollen from the male parent comes in contact with the silks from the female parent. Yet the biological complexities of silk form and function are not yet well understood. ARS scientists in Ames, Iowa, and collaborators at Iowa State University developed a comprehensive catalgue of how genes are turned on and off in corn silks. This "corn expression atlas" provides the data to understand how silks function in diverse environments utilized in maize production. This research demonstrates for the first time the wide diversity of genes expressed during maize silk growth and function, including important roles in development, metabolism, physiology and abiotic- and biotic-defense. These results are expected to be widely used in agricultural research focusing on both stress response and plant reproductive biology. LOG NO. 365258.
Chapman, A.V., Hunt, M., Surana, P., Velasquez-Zapata, V., Xu, W., Fuerst, G.S., Wise, R.P. 2020. Disruption of barley immunity to powdery mildew by an in-frame Lys-Leu deletion in the essential protein SGT1. Genetics. 217(2). https://doi.org/10.1093/genetics/iyaa026.
Banerjee, S., Velasquez-Zapata, V., Fuerst, G.S., Elmore, J.M., Wise, R.P. 2020. NGPINT: a next-generation protein-protein interaction software. Briefings in Bioinformatics. 22(4). https://doi.org/10.1093/bib/bbaa351.
Velasquez-Zapata, V., Elmore, M.J., Banerjee, S., Dorman, K., Wise, R.P. 2021. Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor. PLoS Computational Biology. 17(4). Article e1008890. https://doi.org/10.1371/journal.pcbi.1008890.
Banerjee, S., Bhandary, P., Woodhouse, M.H., Sen, T.Z., Wise, R.P., Andorf, C.M. 2021. FINDER: an automated software package to annotate eukaryotic genes from RNA-Seq data and associated protein sequences. BMC Bioinformatics. 22. Article 205. https://doi.org/10.1186/s12859-021-04120-9.
McNinch, C., Chen, K., Dennison, T.S., Lopez, M.D., Yandeau-Nelson, M.D., Lauter, N.C. 2020. A multigenotype maize silk expression atlas reveals how exposure-related stresses are mitigated following emergence from husk leaves. The Plant Genome. 13(3). Article e20040. https://doi.org/10.1002/tpg2.20040.