Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcriptome changes triggered by Hyaloperonospora parasitica arabidopsis Noco2 in WT and wrky72 mutants at 96 hpt

ABSTRACT: Functional characterization of AtWRKY72 using Arabidopsis T-DNA insertion lines showed that this gene is important for basal defense to root-knot nematode (RKN) and Hyaloperonospora parasitica arabidopsis (Hpa), but not several tested R gene-mediated defenses.To profile transcriptional reprogramming associated with AtWRKY72-dependent basal defense we used Affymetrix ATH1 GeneChips representing ~24,000 Arabidopsis genes. Three independent biological replicates were performed with Col-0, wrky72-1 and wrky72-2 plants at 96 hpt with HpaNoco2 or mock treatment. Using a false discovery rate of less than 0.05 we identified for each of these three lines genes that showed significant transcriptional changes in response to HpaNoco2 compared to the mock-treated controls. Identification of downstream targets of WRKY72 in Arabidopsis by this microarray suggests that WRKY72 uses a unique signaling pathway that involves AP2/ERF TFs independent of the ethylene signaling pathway. We intended to identify Arabidopsis genes that are regulated in WRKY72-dependent manner in response to Hyaloperonospora parasitica arabidopsis (Hpa) at 96 hpt. For this, we used Col-0 and two wrky72 mutant lines and compared the differentially expressed genes with the hypothesis ‘genes that are specifically regulated in Col-0 but not in wrky72 mutants are WRKY72-dependent genes’.

ORGANISM(S): Arabidopsis thaliana

SUBMITTER: Kishor Bhattarai

PROVIDER: E-GEOD-18329 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

WRKY72-type transcription factors contribute to basal immunity in tomato and Arabidopsis as well as gene-for-gene resistance mediated by the tomato R gene Mi-1.

Bhattarai Kishor K KK Atamian Hagop S HS Kaloshian Isgouhi I Eulgem Thomas T

The Plant journal : for cell and molecular biology 20100419 2

WRKY transcription factors play a central role in transcriptional reprogramming associated with plant immune responses. However, due to functional redundancy, typically the contribution of individual members of this family to immunity is only subtle. Using microarray analysis, we found that the paralogous tomato WRKY genes SlWRKY72a and b are transcriptionally up-regulated during disease resistance mediated by the R gene Mi-1. Virus-induced gene silencing of these two genes in tomato resulted in ...[more]

PMID: 20409007

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Project description:Plants have evolved strong innate immunity mechanisms, but successful pathogens evade or suppress plant immunity via effectors delivered into the plant cell. Hyaloperonospora arabidopsidis (Hpa) causes downy mildew on Arabidopsis thaliana, and a genome sequence is available for isolate Emoy2. Here, we exploit the availability of genome sequences for Hpa and Arabidopsis to measure gene-expression changes in both Hpa and Arabidopsis simultaneously during infection. Using a high-throughput cDNA tag sequencing method, we reveal expression patterns of Hpa predicted effectors and Arabidopsis genes in compatible and incompatible interactions, and promoter elements associated with Hpa genes expressed during infection. By resequencing Hpa isolate Waco9, we found it evades Arabidopsis resistance gene RPP1 through deletion of the cognate recognized effector ATR1. Arabidopsis salicylic acid (SA)-responsive genes including PR1 were activated not only at early time points in the incompatible interaction but also at late time points in the compatible interaction. By histochemical analysis, we found that Hpa suppresses SA-inducible PR1 expression, specifically in the haustoriated cells into which host-translocated effectors are delivered, but not in non-haustoriated adjacent cells. Finally, we found a highly-expressed Hpa effector candidate that suppresses responsiveness to SA. As this approach can be easily applied to host-pathogen interactions for which both host and pathogen genome sequences are available, this work opens the door towards transcriptome studies in infection biology that should help unravel pathogen infection strategies and the mechanisms by which host defense responses are overcome. Three weeks old Arabidopsis (Col-0) plants were inoculated with either the avirulent isolate Emoy2 (incompatible interaction) or the virulent isolate Waco9 (compatible interaction) of Hpa, and infected plants were harvested at 1, 3 and 5 days post-inoculation (dpi) for total RNA extraction. mRNA profiles were generated by deep sequencing on Illumina GAIIx using EXPRSS tag-seq protocol. Each biological replicate set of samples were sequenced as one batch (biorep1, biorep2 and biorep3 in filenames) and each batch was sequenced in 4 individual Illumina flowcell lanes (lane1 to lane4 in filenames). Four sequecing lanes of each three biological repliates resulted in 12 sequencing libraries. Emoy2 1, 3 and 5 dpi samples and Waco9 1 dpi samples were made two different codes (lib1 and lib2 in filenames) to generate higher depth of sequencing data. Each biological replicate set of samples were sequenced as one batch and each batch was sequenced in 4 individual Illumina flowcell lanes. Four sequecing lanes of each three biological repliates resulted in 12 sequencing libraries. 'The unassigned read_*' samples are for 'nobarcode_biorep[x]_lanne[x].fq' file containing sequences unassigned to any barcode from respective bioreplicate sequencing lanes.

Project description:Changes in gene expression form a crucial part of the plant response to pathogen infection. Whole-leaf expression profiling has played a valuable role in identifying genes and processes that contribute to the interactions between the model plant Arabidopsis thaliana and a diverse range of pathogens. However, for highly localised infections, such as downy mildew caused by the biotrophic oomycete pathogen Hyaloperonospora arabidopsidis (Hpa), whole-leaf profiling may fail to capture the complete Arabidopsis response. Highly localised expression changes may be diluted by the comparative abundance of non-responding leaf cells or the Hpa oomycete evading detection by cells. Furthermore, local and systemic Hpa responses of a differing nature may become convoluted. To address this we applied the technique of Fluorescence Activated Cell Sorting (FACS), typically used for analyzing plant abiotic responses, to the study of plant-pathogen interactions. Using the promoter of Downy Mildew Resistant 6 (DMR6) linked to GFP as a fluorescent marker of pathogen-contacting cells, we isolated Hpa-proximal and Hpa-distal cells from infected leaf samples using FACS, and measured global gene expression. The whole experiment was carried out in triplicate, with two time points (5 and 7 days post-inoculation) and three cell types (pathogen-proximal, pathogen-distal and uninfected control), totalling 18 microarrays. Transgenic Arabidopsis thaliana Col-0 with the transgene pDMR6:GFP was used for all experiments. Seedling populations were inoculated with 30,000-60,000 spores/ml of Hyaloperonospora arabidopsis strain Noks1 at 7 days old, and overground tissue sampled at 5 and 7 days post-inoculation. Protoplasts were generated from these samples according to Grønlund et al. 2012 JOVE, and sorted by fluorescence activated cell sorting into a GFP-positive (pathogen-proximal) and GFP-negative (pathogen-distal) population. As a control, uninfected seedlings were also sampled at 12 and 14 days old (equivalent age of 5 and 7 days post-inoculation), protoplasts generated and sorted to yield a GFP-negative population of uninfected control cells. Gene expression was analysed using NimbleGen 12 x 135K microarrays, designed for the TAIR10 genome. Data was normalised using the Robust Multichip Averaging algorithm.

Dataset Information

Transcriptome changes triggered by Hyaloperonospora parasitica arabidopsis Noco2 in WT and wrky72 mutants at 96 hpt

Publications

WRKY72-type transcription factors contribute to basal immunity in tomato and Arabidopsis as well as gene-for-gene resistance mediated by the tomato R gene Mi-1.

Similar Datasets

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