In development, heterogeneity helps give rise to the diverse cell types in the body. Our hypothesis is that this structural feature of cell populations arising in development may be co-opted by cancer to form persister cell states that resist therapy. Gene expression variability has previously been attributed to “noise,” or random variation. Yet, not all genes show variable expression, with many stably expressed across populations. We combine bioinformatic analysis of single cell expression datasets with targeted experimental cell biology to understand what gives rise to gene expression variation at the single cell level. We focus on mouse embryonic stem cells as a model system. Our current focus is on studying enhancers, non-coding RNAs, transcription factors, and how regulatory circuits are wired to give rise to heterogeneity. Other projects focus on variation in cancer cell states, particularly in melanoma.
