In order for cells and tissues to properly develop, to respond to changes in the environment and to maintain homeostasis, gene expression needs to be precisely regulated. A major part of this regulation occurs post-transcriptionally, where many RNA-binding proteins and small regulatory RNAs control messenger RNAs by binding at specific sites. This project investigates how individual factors that control gene expression interact with each other with synergistic or antagonistic effects. The understanding of how gene expression is regulated in an organism is key to developing a means of engineering the organism potentially impacting food supply, health and environmental sustainability. The project supports an intensive summer laboratory program for upper-level students and provide valuable experience and mentoring in experimental research, scientific reasoning, hypothesis building and communication. Undergraduates participate in longer, year-round projects that allow in-depth exposure to laboratory science and involvement in extended scientific projects. The project also fosters development of future researchers. The goal is to significantly contribute to preparing minority, low-income and disadvantaged students for professional research careers in academia and industry.
Gene expression and organismal development fundamentally depend on post-transcriptional regulatory processes, where a large set of RNA-binding proteins (RBPs) and small regulatory RNAs (ex., microRNAs) control messenger RNAs (mRNAs) by binding at specific sites. While individual molecular functions of RBPs have been traditionally studied, current evidence supports a model of combinatorial post-transcriptional regulation by factors at the 3? UTR which is a regulatory hub where multiple RBPs interact to produce a combinatorially large set of expression outcomes. However, there is a significant knowledge gap in understanding the principles of these interactions. It is essential to identify and characterize such RBP-RBP interactions on mRNAs transcriptome-wide, and such approaches are currently lacking. This project addresses this critical need by developing and applying a robust and quantitative detection platform and data analysis framework to detect sites of combinatorial control of gene expression by RBPs. In this project the focus is on applying the platform to interactions between a key RNA binding protein, PUM, and the microRNA machinery. This approach combines massively parallel reporter systems with precise RBP level manipulation and statistical modeling.
This project is supported by the Systems and Synthetic Biology and Genetic Mechanisms Clusters of the Division of Molecular and Cellular Biosciences in the Biological Sciences Directorate.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
