Transcription is the first step in the central dogma of molecular biology, when genetic information encoded on DNA is made into RNA. How this fundamental process occurs in eukaryotes is well characterized in vitro, but surprisingly poorly understood at the cellular level. This is in part because conventional live cell imaging approaches fail to capture with sufficient quantitative detail the intricate, weak and transient molecular interactions that regulate eukaryotic transcription process in vivo. To surmount these limitations, we propose novel quantitative imaging methods that enable probing eukaryotic transcription with high spatial and temporal resolution, with single molecule sensitivity directly n live mammalian cells. We investigate how spatiotemporal organization and dynamics of RNA Polymerase II (Pol II), the molecular enzyme responsible for the transcription of all protein encoding genes, regulate gene expression in individual living cells. We examine how foci of clustered Pol II, hypothesized to be foyer of eukaryotic transcriptional activity, dynamically correlate with nascent messenger RNA output at an active gene locus in the living cell. We envision determining quantitatively with single molecule sensitivity, the mechanisms by which key steps in eukaryotic transcription are dynamically regulated through the recruitment of individual molecular partners in living cells.
Improved understanding of eukaryotic transcription processes in the cellular context will have broad implications for human health: the regulation of transcription is primordial for cellular homeostasis, and aberrant cellular regulation of transcription has been linked to many maladies including cancer and developmental disabilities.
|Cho, Won-Ki; Jayanth, Namrata; Mullen, Susan et al. (2016) Super-resolution imaging of fluorescently labeled, endogenous RNA Polymerase II in living cells with CRISPR/Cas9-mediated gene editing. Sci Rep 6:35949|
|Cho, Won-Ki; Jayanth, Namrata; English, Brian P et al. (2016) RNA Polymerase II cluster dynamics predict mRNA output in living cells. Elife 5:|