Research

Non-coding RNA (ncRNA) Biology

A small fraction of the human genome actually encodes proteins (< 2%), yet the majority of it is transcribed into RNA. Once labeled as “junk DNA”, this vast, largely uncharted landscape of non-coding RNAs (ncRNAs) can function as scaffolds, decoys, guides, and catalysts that can orchestrate cellular behavior. Our lab is fascinated by this frontier. Understanding non-coding RNA biology and functional mechanisms holds huge promise for unlocking the complexities of human biology while also inspiring us to engineer the next generation of precision RNA biomedicines.

Proximity Labeling Platforms

Understanding RNA function requires capturing its highly dynamic interactions within the native cellular environment. We develop and deploy advanced proximity labeling techniques to capture RNA-protein, RNA-DNA, and RNA-RNA interactions with high spatial and temporal resolution. By mapping these microenvironments we seek to uncover the hidden regulatory roles and mechanisms of non-coding transcripts.

Functional ncRNA Discovery

In our lab, we want to understand which ncRNAs are important, and which parts of them are responsible for their activity. We develop and leverage CRISPR-based functional genomics platform to systematically decode these complex molecules. Using scalable perturbation strategies and advanced screening methodologies to disrupt specific genetic elements, we can map these cause-and-effect relationships across the transcriptome. This data allows us to identify which ncRNAs are essential drivers of cellular physiology and pinpoint novel mechanisms and promising therapeutic targets.

RNA Bioengineering

Inspired by the functional potential of non-coding RNAs, our lab is pioneering the design of synthetic RNA biomedicines. These represent a largely unexplored class of bioactive chemical matter, possessing unique capabilities to control gene expression and augment cellular behavior. Engineering this activity remains a grand challenge, and so we are establishing new directed evolution and synthetic biology platforms to select transcripts with novel bioactivities as well as build generative AI models for designing synthetic RNA biologics from the ground up.