Development of Bioinformatic Methods to Detect Functional RNA-Ligand Interactions In-Cellulo – UROP Spring Symposium 2025

Development of Bioinformatic Methods to Detect Functional RNA-Ligand Interactions In-Cellulo

Ayush Reddy

Research Mentor(s): Brandon Klein
Mentor Department: Medicinal Chemistry
Authors: Ayush Reddy, Brandon Klein, Amanda Garner
Session: Session 4 (1:00pm – 1:50pm)
Presentation Type: Poster 42

Abstract

RNA, more specifically 3′ UTRs, are un-translated regions on the 3′ end of the gene (after the translated region) that have broad functions in the regulation of mRNAs. RNA structures in the 3′ UTR are regulatory hubs, contributing to protein expression, RNA localization, and transcript degradation. The complexity of the machinery in the 3′ UTR poses a significant challenge to investigators wanting to leverage engineered RNA for synthetic biology and therapeutic applications. To facilitate these applications, we have created a chemical probing assay that allows us to interact with RNA structures transcriptome-wide using bio-active chemical probes. Untargeted transcriptome-wide probing approaches suffer from signal-to-noise problems. Large amounts of data are generated in these experiments, creating a feature selection problem for researchers. Feature selection problems plague RNA structure research because not all RNA structures are functional, making it difficult to identify those with bio-active functions. To address this problem, we are benchmarking ways of analyzing our data with direct statistical analysis and orthogonal approaches. This work focuses on comparing the direct techniques, DiffBind–a region-level differential binding analysis designed for proteins, with differential expression–a gene-level analysis. These techniques analyze fragments of RNAs that we enrich in our biochemical assay. Our research is primarily investigative as we are attempting to determine RNAs with specific structures that interact with our chemical probes. We are addressing issues with this approach and developing solutions through fine-tuning our methods and experiments. Overall, we are working towards automating a pipeline of data processing tasks to determine areas of interest in the human genome that are enriched by our chemical probes. This will help researchers narrow down what genes are worth looking into, and their potential functions. This is a crucial preliminary step required for researching and developing treatments related to targeting and manipulating gene expression.

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