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United States Department of Agriculture

Agricultural Research Service


Location: Corn Insects and Crop Genetics Research

2008 Annual Report

1a.Objectives (from AD-416)
Obj. 1: Apply functional genomics tools and resources available to barley, rice, and the model dicot Arabidopsis thaliana, to accelerate comparative analysis of cereal disease defense pathways and associate newly discovered genes with biological function.

Obj. 2: Characterize diversity of global gene expression in cereal crops as a baseline to determine effects of transgene insertion and assess risk of developing improved crop products by bioengineering or marker-assisted breeding approaches.

1b.Approach (from AD-416)
Obj. 1: Utilize allelic variability inherent to barley Mla, Rar1, and Rom1 as a switch to discover new pathways involved in both Rar1-dependent and Rar1-independent plant disease resistance. High-throughput barley dsRNAi and Arabidopsis T-DNA reverse genetic systems will be used to functionally validate candidate genes in resistance pathways of both monocot and dicot plants.

Obj. 2: Determine the global transcript profiles of a diverse set of barley germplasm and specific sets of transgenic lines and their progenitors. Integrative computational approaches will be used to establish whether or not differences in gene expression can be used as a predictor for genetic anomalies associated with transgenic crops.

3.Progress Report
Obj. 1a. Comparative analysis of global gene expression in Rar1-dependent and Rar1-independent disease response pathways.

Barley has a complex interaction with powdery mildew [Blumeria graminis f. sp. hordei (Bgh)] that begins with early recognition of the pathogen. During Bgh invasion of the epidermis, the fate of cells is decided by the presence of resistance (R) genes that can halt the pathogen’s growth. Host transcriptome profiling throughout a time-course was used to dissect barley-Bgh interactions; 144 replicated interactions were used to interrogate plants containing allelic variants and mutants of Mla, Rar1, and Rom1, which is a restorer of Rar1-independent, Mla12-specified resistance. Our data show that Bgh resistance involves dynamic reprogramming of the host transcriptome. More than 5,000 genes are differentially expressed in resistant versus susceptible reactions governed by natural allelic variants of Mla. In experiments using null mutations of Mla, early signaling effects are compromised. Together, our results show that Mla acts at a high level in disease defense and point to an essential early regulatory role.

Obj. 1b. Integrated reverse genetic analysis to establish gene function.

Using high-throughput RNA interference (RNAi) assays, we have screened 20 WRKY transcription factors, 7 sugar transporters, 4 receptor kinases, 3 shikimate pathway genes, and 24 others. All candidate genes were selected based on bioinformatic analyses of GeneChip experiments described in Obj. 1. Notably, four novel HvWRKY transcription factors were implicated in barley-Bgh interactions. These data demonstrate that a complex network of HvWRKY transcription factors regulate the defense transcriptome during Bgh invasion.

Obj. 1c. Integrate expression profiling, phenotypic and pathway data into BarleyBase/PLEXdb, a MIAME-compliant, database for cereal GeneChips.

New functionality has been added to PLEXdb. Model Genome Interrogator (MGI) and Microarray Platform Translator (MPT) provide unique meta-analysis capabilities that support investigations utilizing gene expression data. MGI ( maps gene sequences onto model genomes (Rice and Arabidopsis) in batches and displays predicted and annotated gene structures, which allows the user to retrieve all types of desired sequences. Microarray Platform Translator is a new web service for within- or cross-species mapping of microarray elements and GenBank sequences.

Obj. 2a. Analysis of pathogen-responsive promoters.

Rice meta-promoter sequences orthologous to promoters of barley genes known to be involved in disease defense were extracted and analyzed for conserved elements. Numerous elements were found, and several were shown to be conserved for 15 million years in both the rice and barley lineages, suggesting functional importance. In one case, we extended our biochemical knowledge of a primary target gene, Bdl1, which encodes a negative regulator of disease defense.

This progress report relates to National Program #302, Component 1 because this research will lead to more complete understanding of the structure and function of genes responsible for the health of crops.

1. Transcript-based Cloning of RRP46, a Negative Regulator of Ribosomal RNA Processing and R-gene-independent Cell Death in Barley – Powdery Mildew Interactions.

Programmed cell death (PCD) plays pivotal roles in plant development and defense. Powdery mildew (Bgh) challenged barley and its fast-neutron-derived “Bgh-induced tip cell death1” mutant, bcd1, were compared using the 22K Barley1 GeneChip. Contrasts were made to identify genes associated with the cell death phenotype as opposed to R-gene mediated resistance. Functional analysis of RRP46 (Ribosomal RNA-processing protein 46), demonstrated that RRP46 was responsible for bcd1-mediated tip cell death. These findings suggest that the Bcd1-encoded RRP46 mediates metabolism involved in cell death progression as a result of signaling during the barley-powdery mildew interaction, but is independent of gene-for-gene resistance. This accomplishment addresses National Program #302, Component 1, Problem Statement 1B: Applying Genomics to Crop Improvement.

2. New Bioinformatic Tools Accelerate Genome Assembly.

The genome of an organism contains all of the hereditary information encoded in the DNA. Transposable elements (TEs) are mobile segments of DNA that produce the repetitive segments and are found throughout the genome. New bioinformatic software, designated TEnest, was developed that will accelerate the assembly of the genome. Using this new software enables researchers to identify repeat insertions in the genome and calculate their ages since integration into the DNA, and model their evolution. TEnest is available for use both as a web server on the Resource for Plant Comparative Genomics,, and as a standalone downloadable version available from To date, the tool has been applied to four agriculturally important grains including maize, barley, wheat, and rice. Bioinformatic tools such as TEnest dramatically increase the speed and efficiency with which genomes are assembled and provide insight into the evolutionary history of the plant through time. Understanding the genome of agricultural crops may allow scientists to develop crops capable of growing in arid conditions and resistant to pests. This accomplishment addresses National Program #302, Conponent 1, Problem Statement 1B: Applying Genomics to Crop Improvement.

5.Significant Activities that Support Special Target Populations

6.Technology Transfer

Number of Non-Peer Reviewed Presentations and Proceedings1

Review Publications
Kronmiller, B.A., Wise, R.P. 2007. TEnest: Automated Chronological Annotation and Visualization of Nested Plant Transposable Elements. Plant Physiology. 146(1):45-59.

Druka, A., Potokina, E., Luo, Z., Bonar, N., Druka, I., Zhang, L., Marshall, D.F., Steffenson, B.J., Close, T.J., Wise, R.P., Kleinhofs, A., Williams, R.W., Kearsey, M.J., Waugh, R. 2008. Exploiting Regulatory Variation to Identify Genes Underlying Quantitative Resistance to the Wheat Stem Rust Pathogen Puccinia graminis f. sp. tritici in Barley. Theoretical and Applied Genetics. 117(2):261-272. Available:

Hu, P., Wise, R.P. 2008. Diversification of Lrk/Tak Kinase Gene Clusters is Associated with Subfunctionalization and Cultivar-specific Transcript Accumulation in Barley. Functional and Integrative Genomics. 8:199-209. Available:

Potokina, E., Druka, A., Luo, Z.W., Wise, R.P., Waugh, R., Kearsey, M.J. 2008. Gene Expression Quantitative Trait Locus Analysis of 16,000 Barley Genes Reveals a Complex Pattern of Genome-wide Transcriptional Regulation. Plant Journal. 53(1):90-101.

Wise, R.P., Moscou, M.M., Whitham, S.A., Bogdanove, A.J. 2007. Transcript Profiling in Host-pathogen Interactions. Annual Review of Phytopathology. 45:329-369.

Last Modified: 4/19/2014
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