Bioinformatics Pipeline

By Kranthi Varala, Mary Williams, and Amy Marshall-Colon


The activation of transcription via signal transduction pathways is one of the most sophisticated molecular mechanisms plants have that allows them to cope with and adapt to stressful environments. Scores of signal transduction pathways can be initiated depending on the combination of stresses experienced by the plant. Directly or indirectly, plant transcription factors (TFs) sense and respond to external signals such as light and temperature, as well as endogenous signals such as hormones. Moreover, TFs regulate other TFs, resulting in complex regulatory networks controlling thousands of genes in response to the various environmental signals. It is difficult to conceptualize genome-wide transcriptional regulation and even more challenging to organize, analyze, and visualize data at this scale. Network analysis of gene expression data is a popular way for plant scientists to deal with “-omic” scale data. However, the tools and techniques needed for such an analysis are not commonly taught alongside other plant biology curricula. Here, we present a flexible learning module that provides students with training in the construction and analysis of a co-expression network in the context of transcriptional regulation by TFs.

This module can be taught as a traditional lecture or as a hands-on module for small lecture or laboratory courses. The first part of the lesson provides background and theory for the analysis, and the second part provides two step-by-step tutorials for hands-on exploration of the tools used for transcriptional analysis.

Like all Teaching Tools, this article has undergone rigorous peer review, and includes a set of PowerPoint slides for use in teaching, a review article suitable for undergraduates, a teaching guide with questions to prompt students to synthesize the information presented, and a short, 24-slide abridged slide set.

Read about the authors of this Teaching Tool and their perspectives about this exciting topic.

Posted October 2018.