Transcriptomics Analysis Methods: Microarray Data Processing, Analysis and Visualization Using the Affymetrix Genechip ® Vitis Vinifera Genome Array

The study of transcriptomics is a powerful method of studying the responses of organisms to their environment. The transcriptome consists of the entire set of transcripts that are expressed within a cell or organism at a particular developmental stage or under various environmental conditions. There are various technologies for assaying the transcriptome including hybridization-based microarrays and RNA sequencing. Microarrays have been used extensively to quantify the transcript abundance of grape cells, organs and tissues. Here we provide a practical guide on how to analyze microarray data using a study based on the Affymetrix GeneChip® Vitis vinifera genome array. Microarray studies have proven to be very powerful for the elucidation of molecular response networks and physiological processes. In this Chapter, we have outlined the steps required to process and analyze mRNA expression data. The first step is to check both microarray and data quality. The second step is to remove array and data outliers and reduce the variability of the data with cleansing and normalization techniques. The third step is to perform statistical tests to identify sets of transcripts differentially expressed among conditions under statistical significance. The fourth step is to evaluate these sets of significant transcripts using functional categorization and molecular maps. Such data sets can be compared or integrated with proteomic and metabolomic data sets using a systems biology approach to increase the robustness of the conclusions. From data analysis performed in these ways, hypotheses can be generated for further experimentation and validation, which denotes the fifth, and likely the most important, final step.

Peer reviewed