Weighted gene co-expression analysis for identification of key genes regulating heat stress in wheat

Abstract

Wheat is an important cereal crop, which holds the second rank globally in terms of production after maize. However, its productivity is highly sensitive to heat stress, which is one of the most serious threats due to global warming. Therefore, development of heat tolerance variety of wheat through molecular breeding approach is an urgent need of the hour for not only reducing productivity loss but also improving crop yield for feeding growing population. In this context, identification of heat-related genes is the first step for this molecular breeding. In this regard, several studies have been conducted in the past, but due to identification of large number of genes, it was found to be practically difficult to use these in molecular breeding programs. In order to address this issue, in this study, system biology approach has been followed to identify set of key genes related to heat stress in wheat which contributes significantly to regulating this entire process. Here, high-throughput RNAseq data were generated using control and treated samples of two contrasting wheat varieties, namely HD2967 (thermo-tolerant) and BT-Schomburgk (thermo-susceptible). Further, in order to identify important key genes, an advanced statistical framework called weighted gene co-expression network analysis (WGCNA) has been used. Moreover, functional annotation of these identified key genes has also been carried out, which confirms their association with the heat stress. These results will provide important lead to experimenters involved in the development of new heat-stress-tolerant wheat cultivars to mitigate effects of global warming.