Mayank Musaddi received his Master of Science – Dual Degree in Computational Natural Sciences (CND). His research work was supervised by Dr. Nita Parekh. Here’s a summary of his research work on Multi-stress rice transcriptome analysis using network-based approach:

Rice is a fascinating and complex organism. Consumed by more than half of the world’s population, it is important to have a comprehensive understanding of the organism to advance crop engineering and breeding strategies. Abiotic stresses like drought, high temperature, salinity and flood have affected its growth and productivity. Furthermore, global climate change has added to the severity of these stresses, suggesting the need for varieties with improved stress tolerance for sustainable crop production. Improving stress tolerance requires an in-depth understanding of the biological processes, transcriptional pathways and hormone signaling involved in stress response. With the surge in omics data, it has paved the way for deciphering the biological information underlying complex traits. However, dealing with such large datasets calls for the development of powerful bioinformatics methods for a thorough transcriptome analysis. A popular approach is the construction and analysis of co-expression networks representing transcriptionally coordinated genes that are often part of the same biological process. Using prior knowledge and data integration further enhances the elucidation of gene regulatory relationships in this network. With this objective we have developed a Network based Rice Expression Analysis Server (NetREx), that hosts ranked co-expression networks of Oryza sativa (rice) using publicly available mRNA-seq data. It provides a range of interactable data viewers and modules for comparative analysis of query genes across for four abiotic (drought, flood, cold and osmosis) and two hormonal treatment (abscisic and jasmonic acid) conditions, both for root and shoot tissues. Subnetworks of user-defined genes can be queried in preconstructed tissue-specific networks, allowing users to view the fold-change, module memberships, gene annotations and analysis of their neighborhood genes and associated pathways. It also supports querying rice orthologous from other plants, namely, Arabidopsis, wheat, maize, barley, and sorghum. Here we demonstrate that NetREx can be used to identify novel candidate genes and tissue-specific interactions under stress conditions and can aid in the analysis and understanding of complex phenotypes linked to stress response in rice. Available at: https://bioinf.iiit.ac.in/netrex/. In this work we carried out comparative analysis of differentially expressed genes and transcription factors and metabolic processes based on their WGCNA module membership across different stress and hormone conditions in root tissue in a time-specific manner. We observed that osmotic stress resulted in very early response with number of co-expressed modules differentially activated/repressed by 1hr time-point. Some of these responses were observed in drought condition at a later time-point. So, a detailed analysis of the transcriptome in response to osmotic stress was carried out. Analysis of the early response modules revealed various signaling pathways and metabolic processes affected within 3hr time-point. Events like MAPK cascade, chromatin reorganisation, JA signalling pathway and lipid metabolism are activated within one hour, while ROS scavenging activity and oxidation reduction processes are initiated after 6hr time-point. This is followed by the activity of kinases and leucine rich repeats in the activation of required proteins and signal transmission. Networks of genes involved in these processes are discussed.

May 2023