My research is focused on two different areas of gene regulation within the context of developmental biology. One area concerns the molecular mechanisms and functions of non-coding RNAs. Long non-coding RNAs (lncRNAs) are the most ubiquitous of non-coding RNAs, with tens of thousands annotated in the human genome. Yet, they are also the most poorly understood non-coding RNA, as only a small fraction of annotated lncRNAs have been characterized at a mechanistic level. Therefore, it is important to obtain a basic understanding of how these RNAs work, how they are regulated, and what broad biological functions they have. We focus on studying these questions in the model organism Drosophila because the mechanisms and regulation thus far discovered in flies are highly similar to humans. The rich genetics of Drosophila enable functional experiments that would not be possible in mammals. This award will support our efforts to discover new principles of lncRNA regulation and flush out necessary detailed information about previous discoveries. The second area concerns the interplay between gene regulatory programs and extrinsic inputs such as cell metabolism, cell morphogenesis, and physically-based processes. We combine mathematical modeling and quantitative experiments in Drosophila to define the links between these extrinsic inputs and gene regulation. We generate substantial technical advances in quantitative approaches including (1) new high dimensional biological datasets across spatial (cellular to organism) and temporal scales, (2) new conceptual models of diverse developmental processes, and (3) mathematical models that describe developmental emergence. Future directions include understanding whether redundant gene activation is a common feature of life because it affords greater flexibility to regulatory programs to faithfully couple with cellular energy metabolism. Another direction concerns the inherent stochasticity in biochemical reactions and how that affects the fidelity of cell differentiation and patterning. Another future direction is to adapt our proven approaches to explore how mechanical forces experienced by cells within tissues cause changes in their gene expression programs. Understanding the biophysical nature of tissues will have great benefit for tissue engineering.
|Effective start/end date||4/1/21 → 3/31/26|
- National Institute of General Medical Sciences (5R35GM118144-08)
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