Dig Bijay holds a B.S. in Biochemistry, Molecular Biology, and Bioinformatics from Towson University. His research journey began in Dr. Gerald Wilson’s lab at the University of Maryland, Baltimore, where he studied RNA stability and its role in breast cancer. This experience ignited his interest in gene expression and disease. He earned his Ph.D. in Molecular Biology and Genetics at Cornell University with Dr. John Lis, developing nascent RNA sequencing methods and applying them to examine transcriptional dynamics and gene regulation under proteotoxic stress. His thesis work showed that transcription during heat stress is primarily regulated at the level of paused RNA polymerase II and its release, revealing a more focused role for transcription factor HSF1 than previously understood. He also found that proteotoxic stress leaves a transcriptional memory in enhancers, which can be exploited during tumorigenesis.
Dig Bijay joined Dr. Phillip Sharp’s laboratory at the Koch Institute for Integrative Cancer Research at MIT for his postdoctoral training. There, he focused on non-coding regulatory elements and their roles in immune dysfunction and disease. He developed a single-cell nascent RNA sequencing technology that captures active transcription with single-nucleotide resolution, revealing coordinated transcription across the genome between enhancers and their gene targets. In a collaboration spanning three institutions, he discovered that mutant p53—the most frequently mutated gene in cancer—gains a novel function by co-opting enhancers of immunosuppressive chemokines, thereby promoting immune evasion in pancreatic cancer.
Dig Bijay’s training in biochemistry, genomics, and immunology inspires his research on transcription dysregulation in diseases. His lab focuses on identifying and targeting disease-driving enhancers, especially those that regulate cytokines/chemokines in the tumor microenvironment and harbor genetic risk variants associated with autoimmune disorders. By developing and applying genome-wide assays and combining them with AI and machine learning approaches, his lab aims to understand how non-coding DNA sequences control gene expression, ultimately leading to new therapeutic strategies for immune dysfunction diseases.
