A single molecule toolbox for quantitative analysis of transcriptional dynamics in yeast
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Genes relay their information via an intermediary molecule known as messenger RNA (mRNA). These molecules have complex lifecycles, involving the coordination of many processing events and regulatory steps. Ensemble biochemical approaches have been key in understanding much about these events, however, the use of single molecule imaging techniques has provided a more comprehensive view by allowing us to observe dynamic events as they happen. We have focused on developing single molecule imaging tools for the quantitative analysis of transcription in yeast. First, we use single molecule FISH as a method for transcriptional profiling, keeping the gene length constant and directly comparing transcriptional activity across different promoters known to act through different regulatory mechanisms. We also adapt the experimental protocol, performing single molecule FISH for the first time in S. pombe. Our results confirm that it is the promoter sequence that governs a particular mode of expression. Next, we describe a method using PP7 and MS2 RNA-tags to visualize single RNA transcripts in two colors. Previous applications of live cell imaging of RNA have yielded important insights into transcription, mRNA export and localization, however in vivo RNA-labeling methodologies have been generally limited to the tagging of a single gene and have never been utilized to quantify single transcripts over time in yeast. We show that two identical alleles are expressed independently, with uncorrelated steady-state fluctuations that provide the first measurement of intrinsic noise in mRNA expression over time. We also engineer a two color intramolecular construct as a direct and novel read-out for measuring RNA polymerase II kinetics at a single yeast gene, revealing a surprisingly high degree of cell-to-cell variability in elongation rates. Overall, our observations describe a population of identical cells that is simultaneously inherently variable in terms of gene expression. While these tools have been developed for studying transcription, they will be useful in studying the kinetics of other mRNA-specific processes.
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