Statistical Analysis and Biological Implication of Powdery-Mildew-Responsive Transcriptional Profiling in the Two Vitis Species


Yan He

Date of Graduation

Summer 2006


Master of Science in Plant Science (Agriculture)


School of Agriculture

Committee Chair

Wenping Qiu


To analyze the global framework of host gene expression during the early infection stage of the powdery mildew fungus, we performed large-scale mRNA expression profiling using Affymetrix GeneChip. Spores of the powdery mildew fungus were inoculated onto the leaves of disease-susceptible Vitis vinifera ‘Cabernet sauvignon’ (Cabernet) and disease-resistant Vitis aestivalis ‘Norton’ (Norton). Fungal spores- and mock-inoculated leaf samples were collected at 0, 4, 8, 12, 24, and 48 hours post inoculation to investigate gene expression changes before and after fungal spore penetration. Two types of t-test statistical methods were employed to identify genes with significantly differential expression in incompatible and compatible grapevine-fungus interactions across six time points after pathogen challenge. Unexpectedly, the response intensity of transcriptional profiling in the compatible interaction was significantly more pronounced that in the incompatible interaction. A total of 410 transcripts were found by Bayesian t-test to be differentially expressed (278 up-regulated and 132 down-regulated) under the compatible interaction, but only 46 genes (42 up-regulated and 4 down-regulated) under incompatible interaction. Further analysis demonstrated that there is a constitutively high level of the expression of powdery mildew-responsive genes in Norton than in Cabernet, which is proposed to be a possible mechanism underlying Norton’s superior tolerance to pathogens. In addition, the approach of genome walking was successfully applied to isolate unknown flanking sequence from grapevine, which will be useful for further cloning promoter elements.


GeneChip, incompatible interaction, compatible interaction, powdery mildew-responsive genes, transcriptional profiling

Subject Categories

Fruit Science | Genomics


© Yan He