Coexpression Network Construction and Visualization from Transcriptomes Underlying ER Stress Responses

Abstract

Dynamic gene expression changes are primary cellular reactions in response to most stresses and developmental cues in all organisms, including plants. With the ever-decreasing cost and increasing access, high-throughput transcriptome analyses have become a significant research tool to understand a wide spectrum of complex gene regulatory mechanisms. However, it is still challenging to understand the complete picture of gene responses because of the interactive and dynamic nature of gene expression in biological networks. Coexpression network analyses followed by network mapping are being increasingly applied to overcome this challenge. In this chapter, we will introduce detailed instructions for performing a weighted coexpression network analysis (WGCNA) and network visualization using a transcriptome dataset obtained during recovery from endoplasmic reticulum (ER) stress in Arabidopsis thaliana. The streamlined workflow described here allows biologists to identify and visualize coexpression interactions among genes, accessing a comprehensive landscape of dynamic gene expression changes for further downstream analyses using their datasets.