TIGP (BIO)—Advancing Accurate Prediction of Gene Expression and Biological Networks in Ever-Changing Environments

Abstract

Biological functions shape the overall structure of biological networks, including gene regulatory and signaling systems. Gene duplication and subsequent mutations introduce evolutionary diversity into these networks, enabling plants to adapt to extreme environments and environmental changes over time. By leveraging extensive multi-OMICs datasets, we can explore the complexity, specificity, and divergence of biological networks across various species. In our lab, we focus on understanding the evolutionary conservation and divergence of biological systems. Using quantitative OMICs methodologies, we work with two model species, Marchantia polymorpha and Arabidopsis thaliana, to explore different biological networks involved in plant responses to abiotic stress. Our goal is to uncover how these networks adapt and evolve in response to genetic and environmental changes, and to use this knowledge to predict plant stress responses. One of our key areas of interest is heat stress (HS), which is not only one of the most significant stressors for terrestrial life but also a major limitation on plant growth and crop productivity. By gaining a deeper and more systematic understanding of the mechanisms that govern HS signaling and response networks, we hope to develop new strategies to mitigate the effects of heat stress on plants. During my talk, I will discuss ongoing projects that integrate multi-OMIC techniques and advanced analysis to unravel the complexities of HS responses in land plants. Additionally, I will highlight how predictive modeling is being incorporated into multi-OMICs analysis to identify critical genes or features within these stress responses.

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