Meta-analysis of transcripts associated with race-specific resistance to stripe rust in wheat demonstrates common induction of blue copper-binding protein, heat-stress transcription factor, pathogen-induced WIR1A protein, and ent-kaurene synthase transcripts
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Resistance to stripe rust in wheat is a preferred method of disease prevention. Race-specific all-stage resistance usually provides complete protection; thus an understanding of the molecular control of race-specific resistance is important. To build on previous studies of race-specific resistance controlled by the Yr5 gene, this study reports the construction and use of a custom oligonucleotide microarray to perform a meta-analysis of the transcriptional response involved in race-specific resistance conferred by Yr1, Yr5, Yr7, Yr8, Yr9, Yr10, Yr15, and Yr17. By profiling the response of eight resistance genes in a common background, we identified 28 transcripts significantly involved in the resistance phenotype across all genotypes. The most significant of these were annotated as blue copper-binding protein, heat-stress transcription factor, pathogen-induced WIR1A protein, and ent-kaurene synthase transcripts. Unique transcripts significant in each genotype were also identified, which highlighted some transcriptional events specific to certain genotypes. The approach was effective in narrowing down the list of candidate genes in comparison to studying individual genotypes. Annotation revealed key gene expression events involved in race-specific resistance. The results confirm the activity of known R-gene-mediated pathway race-specific resistance, including an oxidative burst that likely contributes to a hypersensitive response, as well as pathogenesis-related protein expression and activity of the phenylpropanoid pathway. However, several identified transcripts remained unknown and may prove interesting candidates for further characterization.
KeywordsWheat Stripe rust Microarray Gene expression Resistance
This research was supported in part by the US Department of Agriculture, Agricultural Research Service (project no. 5348-22000-014-00D), USDA-ARS Postdoctoral Program, and Washington Wheat Commission (project no. 13C-3061-3923). PPNS no. XXXX, Department of Plant Pathology, College of Agricultural, Human, and Natural Resources Research Center, project numbers WNP00823. The authors acknowledge Lisa Orfe and Dr. Douglas Call for printing the microarrays.
- Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc B 57:289–300Google Scholar
- Buckley M (2002) The spot user’s guide. CSIRO Mathematical and Information Sciences. http://www.cmis.csiro.au/IAP/Spot/spotmanual.htm
- Chen X (2005) Epidemiology and control of stripe rust (Puccinia striiformis f. sp. tritici) on wheat. Can J Plant Pathol 27:314–337Google Scholar
- Gentleman R, Carey V, Bates D, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn TWH, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini A, Sawitzki G, Smith C, Smyth G, Tierney L, Yang J, Zhang J (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5:R80CrossRefPubMedGoogle Scholar
- Narusaka Y, Narusaka M, Seki M, Umezawa T, Ishida J, Nakajima M, Enju A, Shinozaki K (2004) Crosstalk in the responses to abiotic and biotic stresses in Arabidopsis: analysis of gene expression in cytochrome P450 gene superfamily by cDNA microarray. Plant Mol Biol 55:327–342CrossRefPubMedGoogle Scholar
- R Development Core Team (2006) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Wellings C, Singh R, McIntosh R, Pretorius Z (2004) The development and application of near isogenic lines for the wheat stripe (yellow) rust pathosystem. In 11th International Cereal Rusts and Powdery Mildew Conference. John Innes Centre, Norwich, p 39Google Scholar