Research in the Wise laboratory is focused on the high-throughput functional analysis of important agronomic genes in cereal crops. We use a variety of interdisciplinary approaches, including plant and microbial genetics, molecular biology, plant pathology, and bioinformatics & computational biology.
THE SYSTEMS WE WORK ON . . .
Plant diseases are among the greatest deterrents to crop production worldwide. Historically, cereal crops have laid the foundation for numerous classical genetic studies in host-pathogen interactions, resulting in many model biological systems. We have focused on the well-characterized, barley-powdery mildew pathosystem as our entry point to address fundamental questions regarding host resistance. In this system, resistance to the obligate biotroph, Blumeria graminis f. sp. hordei, is governed by gene-for-gene-specified interactions of barley Ml (Mildew resistance locus) genes and cognate powdery mildew avirulence (Avr) genes. (Wei et al. 1999; Halterman et al. 2001; Zhou et al. 2001; Wei et al. 2002; Halterman et al. 2003; Halterman and Wise 2004; Halterman and Wise 2006).
Bioinformatics and Agricultural Genomics:
In the area of plant-pathogen interactions, transcript profiling has provided unparalleled perception into the mechanisms underlying gene-for-gene resistance and basal defense, host vs. non-host resistance, or biotrophy vs. necrotrophy.
We are using Affymetrix GeneChip microarrays for large-scale genetical genomics and parallel expression profiling (Caldo et al. 2004; Eckardt 2004). The Barley1 GeneChip includes 22,792 probe sets derived from 350,000 high-quality ESTs from 84 cDNA libraries, in addition to 1,145 barley gene sequences from the NCBI non-redundant database (Close et al. 2004). Five of the 84 libraries were derived from resistant and susceptible interactions with Blumeria graminis (powdery mildew) and Fusarium graminearum (Fusarium head blight), obligate and facultative fungal pathogens, respectively (HarvEST Web). The Barley1 GeneChip has been validated by hybridization with labeled cRNA from contrasting developmental stage, tissues, genotype, abiotic and biotic stresses that reveal >21,500 probe sets corresponding to genes expressed above background in one or more conditions (Druka et al. 2006).
Dissection of coexpression networks in barley-powdery mildew interactions: a multi-dimensional approach to understanding parasitism by obligate biotrophs
Regulation of gene expression in barley-powdery mildew interactions influences the establishment of fungal biotrophy and the development of host resistance. To identify global expression responses to the powdery mildew fungus, Blumeria graminis f. sp. hordei, 468 Barley1 GeneChips were used to profile the expression of 21,439 genes in inoculated vs. non-inoculated seedlings at hours 0, 8, 16, 20, 24, and 32 for each of nine variants of genes in the Mla resistance signaling pathway, as well as programmed cell death mutants (NSF Plant Genome Award #0500461). We are analyzing these data to build coexpression networks containing genes involved in sugar transport, photosynthesis, WRKY signaling, secretion of PR proteins, signal peptide processing, and abiotic stress signaling. Single cell dsRNAi (TIGS), Virus Induced Gene Silencing (VIGS), transcript based cloning, and proteomics experiments are being used to dissect the various sub-networks and time-course interactions of disease defense pathways.
Regulatory networks in barley-Puccinia, barley-Blumeria, and Arabidopsis-Erysiphe interactions: a genetical genomics approach to understanding parasitism by obligate biotrophs
Pathogenesis of plants by fungal biotrophs is highly dependent on continuous derivation of nutrients from host cells. To identify the most significant host expression responses to biotrophic pathogen invasion, we are conducting genetical genomics (eQTL) experiments in barley to define the regulatory networks controlling reaction to Puccinia graminis TTKS, a stem rust isolate from East Africa that parasitizes both barley and wheat. Significantly, TTKS infects wheat carrying the Sr31 gene that has been utilized worldwide to confer resistance to stem rust. One-hundred seventy Affymetrix GeneChips are being used to profile the transcriptome of barley in inoculated vs. mock-inoculated leaves of a doubled haploid population that segregates for reaction to TTKS. Genome-wide regression scans are being done to detect significant cis- and trans-acting eQTLs. From these, we will identify trans-eQTL hotspots that pleiotropically regulate multiple genes that specifically respond to TTKS inoculation. Subsequently, we will locate the subset of eQTL that regulate the expression of disease defense genes currently being defined by barley-Blumeria graminis (see above) and Arabidopsis-Erysiphe orontii GeneChip experiments. This subset of loci will then be cross-referenced with the trans-eQTL hotspots. The intersections of these lists will represent candidates for the loci that orchestrate the dramatic transcriptome reprogramming in response to TTKS. The accuracy of the predictions derived from our multidimensional analyses will be testable upon completion of the QTL analysis of TTKS resistance in this population.
Part of this research is being done in collaboration with the USDA-ARS Cereal Disease Lab and the University of Minnesota.
PLEXdb (BarleyBase) Expression profiling database
BarleyBase is an on-line relational database for raw and normalized expression data for cereal GeneChips (Shen et al. 2005). BarleyBase utilizes a MIAME-compliant data submission process as well as the developing plant and trait ontology (www.plantontology.org) terms for barley and other cereals so that experiments can accurately describe development stages and plant tissue types. These terms allow cross-species comparisons based upon common identifiers, facilitating interoperability between existing plant databases. Interconnecting links with PlantGDB, GrainGenes, and Gramene, (e.g., http://www.plexdb.org/modules/PD_probeset/annotation.php?genechip=Barley1) allow BarleyBase users to perform gene predictions using the 21,439 non-redundant Barley1 gene sequences, or cross-species comparisons with rice and wheat at the genome level, respectively. Recently, BarleyBase has evolved into PLEXdb (NSF Award #0543441), to make available all the expression analysis tools developed for Barley1, as well as relevant genomic database links, applicable to any new plant array. These include rice, wheat, maize, and sugarcane as well as dicots, such as Medicago, tomato, soybean, grape, and Arabidopsis. BarleyBase/PLEXdb currently houses 4,083 GeneChip hybridizations from 101 experiments in barley, wheat, rice, maize, Arabidopsis, soybean, and grape GeneChips. Notably, over 900 Barley1 hybridizations have been uploaded from investigators in the US, Europe, and Australia, representing 15 tissues from seed to seed in development, interactions with Fusarium graminearum (head blight), Blumeria graminis (powdery mildew), and Puccinia graminis (stem rust), as well as other abiotic and biotic stresses. Since its inception in October, 2003, BarleyBase has been accessed by academic, government, and corporate users from over 60 countries in Europe, North America, and the Pacific Rim; 468 registered users in 35 countries have batch downloaded complete experiment data over 4,000 times for analysis.
Nuclear—cytoplasmic interactions: Fertility restoration in cms-T maize by post-transcriptional, mitochondrial gene regulation (USDA-NRI 2002-35301-12064)
Cytoplasmic male sterility (CMS) is invaluable in the breeding of hybrid seed. CMS systems are found in 150 plant species and are often attributed to chimeric open-reading frames in the mitochondrial genome. These open-reading frames encode unique proteins that can interfere with mitochondrial function and pollen development and also can confer disease sensitivity. Nuclear restorer (Rf) genes suppress CMS-associated male sterility. In many instances, this suppression is concurrent with Rf-gene-dependent mitochondrial RNA processing (Wise et al. 1996; Dill et al. 1997; Wise et al. 1999). To characterize these mechanisms, we are investigating the T-cytoplasm maize restorers that mediate the processing of T-urf13 mitochondrial transcripts and the concurrent reduction of the mitochondrial URF13 protein. Nuclear-directed modification of T-urf13 transcripts is mediated by one of three (Rf1, Rf8, or Rf*) genes, which in combination with the Rf2a gene, suppress the male-sterile phenotype. These nuclear-cytoplasmic interactions share common features among many plants, such as sorghum, rice, wheat, sunflower, oilseed rape, petunia, and common bean. Investigation of these interactions will therefore contribute to the understanding of mitochondrial RNA processing and fertility restoration in crop plants. In many of these economically important plants, CMS is the only efficient way to produce hybrid seed.
To facilitate a candidate approach towards identification of the rf1 gene, three B73 BAC libraries were used to create a physical map of 794 clones from the centromeric region of chromosome 3 anchored to the rf1 locus. A minimum-tiling path of 19 contiguous BACs covering 1.5 megabases were shotgun sequenced, assembled and finished to completion for annotation and display in the GBrowse viewer. In 2006, we developed the bioinformatic software, TE nest, to perform automated annotation of complex repeated regions of the maize genome. This is especially important as the $30 million maize sequencing project was started this year. Seventy percent of the maize genome consists of transposable elements (TEs). Of these, 95% are LTR retrotransposons, which greatly hinder sequence assemblies. A majority of TEs occur in clusters of nested repeats, where a TE inserts within the sequence of an existing element, creating short segments of different types. Mapping of maize TEs is therefore difficult as the resulting fragments are not easily identified, necessitating an accurate nested TE identification tool for complete annotation of the genome. With use of a maize canonical TE database, TE nest identifies and maps repeat incorporations into the original genome sequence while providing chronology of insertion events in Mya based on LTR base pair substitution rate. An insertion graph is produced to give an accurate visual representation of TE integration history showing timeline, location and types of each TE identified, thus creating a framework from which evolutionary comparisons can be made among various regions of the maize genome. We have used TE nest to analyze all 165 finished maize BACs from GenBank along with in-house generated 1.5 Mb rf1-spanning sequence in the centromeric region of chr3, constructed from 19 contiguous BACs.