Computational protocol: Transcriptome dynamic of Arabidopsis roots infected with Phytophthora parasitica identifies VQ29, a gene induced during the penetration and involved in the restriction of infection

Similar protocols

Protocol publication

[…] Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) experiments were performed with 5 μl of a 1:50 dilution of first-strand cDNA and SYBR Green, according to the manufacturer’s instructions (Eurogentec SA, Seraing, Belgium). Gene-specific oligonucleotides () were designed with Primer3 software (http://frodo.wi.mit.edu), and their specificity was checked by analyzing dissociation curves after each run. Genes encoding a mitochondrial NADH-ubiquinone oxidoreductase subunit (AT5G11770) and a mitochondrial inner membrane translocase (AT5G62050) were selected as constitutive internal controls []. For microarray validation, RNA was isolated from non-inoculated roots (NI), and from roots 2.5 hours after inoculation (hai), 6 hai, 10.5 hai and 30 hai with P. parasitica. Two biological replicates of the entire experiment were performed, each as a technical triplicate. For each time point, six results were analyzed. Gene expression was quantified and normalized with respect to constitutively expressed internal controls [].For VQ29 and hormonal pathway expression analysis for mutant validation, RNA was isolated from non-inoculated roots (NI), and from roots 6 hours after inoculation. Three biological replicates of each time points were performed, each as a technical triplicate. Analysis was performed as above. [...] In two independent experiments, roots from the ecotype N60000 were inoculated with water or with P. parasitica to establish a compatible interaction. Total RNA was extracted as described above, and cDNA synthesis, sample labeling, hybridization procedures and data acquisition were performed at the NASC microarray platform []. The dataset is available from the GEO database at the NCBI under accession number GPL198. The transcriptome statistical analysis was performed as previously described []. After quality control with the Bioconductor package “simpleaffy” (Crisipn Miller), the cel-files were quantile-normalized with the “gcrma” package of Bioconductor []. Then, a quality control filter was performed. If the log2 ratios for the two time series differed by more than 75% of the mean of the two log2 ratios, the gene concerned was removed from subsequent analyses. Each of the remaining genes was tested for significant up- or downregulation by ANOVA analysis of variance and p-value correction by false discovery rate (FDR) []. Genes with adjusted p-value <0.05 and an absolute fold-change of 2 or more were considered to be differentially expressed. For clustering, the data were first mean-centered and log-2-transformed with Epclust (http://www.bioinf.ebc.ee/EP/EP/EPCLUST, []. Hierarchical clustering (Pierson correlations, mean linkage) and k-mean clustering (default parameters) were performed with Genesis software (http://genome.tugraz.at/genesisclient/genesisclient_description.shtml). For all cluster analyses, we used Virtual plant 1.3 programs to assess the overrepresentation of terms from the MIPS Functional Catalogue Database (FunCatDB, http://virtualplant.bio.nyu.edu/cgi-bin/vpweb/ [,]. Finally, we used the GENEVESTIGATOR online platform for the global analysis of publicly available expression data for Arabidopsis exposed to biotic stresses, PAMP and hormone treatments []. We selected as candidate genes, from the genes displaying a modulation of expression in our array analysis, those not deregulated in response to all biotic stresses, PAMP and hormone treatments. […]

Pipeline specifications

Software tools Primer3, Simpleaffy, GC–RMA, VirtualPlant, Genevestigator
Databases FunCat
Applications Gene expression microarray analysis, qPCR, Transcription analysis
Organisms Arabidopsis thaliana, Phytophthora parasitica
Diseases Infection