Bohyeon Yu, PhD

Postdoc

Aaron Diaz, University of California, San Francisco

Pronouns: he/him

My research career began with developing a stochastic model for accurate detection of somatic single nucleotide variants (SNVs) and analyzing the mutational signatures of triple-negative breast cancer (TNBC). Since then, I have mainly focused on cancer transcriptomics. To understand the functional roles of the 3’ untranslated region (3’ UTR), I developed a regression-based program, GETUTR, and assessed the dynamics of 3’ UTR in a cell-type-specific context. I further extended my research goal to reconstruct transcriptome maps with large-scale unstranded RNA-seq data accurately and devised the machine learning-based transcriptome assembly pipeline, CAFE. In this study, I reconstructed high-confident cancer transcriptome maps and annotated cancer-related novel lncRNAs. Applying CAFE pipeline to esophageal squamous cell carcinoma (ESCC), I identified a novel ESCC-driving long noncoding RNA (lncRNA) that regulates both canonical and noncanonical Wnt pathways to promote ESCC by interacting with EZH2.
I am currently working on extending my previous work to the single-cell level. My most recent work involves building comprehensive cancer and immune transcriptome maps and applying them to single-cell RNA-seq analysis to explore non-coding regions that have not been studied. Specifically, I hope to identify and characterize tumor immune microenvironment (TIME)-associated lncRNAs in diverse cancers and investigate the distribution and the interaction of sense and antisense gene pairs at the single-cell resolution.