Co-transcriptional processing of nascent pre-mRNA is a central mechanism for gene regulation in eukaryotes and requires temporal coordination between transcription initiation, elongation, splicing and cleavage. Each of these processes is carried out by megadalton macromolecular complexes acting at a single genetic locus, and kinetic competition between these processes has been proposed to determine RNA fate. Genome-wide studies across organisms indicate heterogeneous distributions of both RNA polymerase and nascent RNA along the gene, suggesting that kinetic checkpoints exist throughout the gene, including at promoter-proximal sites, translation start sites, intron-exon boundaries, and at the 3' end of genes. However, population studies reflect the balance of kinetic rates and are unable to resolve the multiple competing processes occurring at a single gene. Moreover, genome-wide measurements lack the time-resolution which might provide mechanistic clues about the underlying enzymatic processes. The hypothesis of kinetic competition is that a fast process will out-compete a process which may in fact be more energetically preferred. For example, kinetic competition during the transcription cycle has been shown to influence splice site selection during alternative splicing, recruitment of factors which release promoter proximal pausing, and even RNAi-mediated genome defense. However, since these processes occur within the dynamic milieu of the nucleus, the stochastic interactions between macromolecules may result in a range of possible outcomes for the nascent RNA. Stochastic RNA synthesis - transcriptional 'noise' - has been directly visualized in multiple organisms, but stochastic RNA processing has never been directly observed, and the potential consequences for gene regulation are largely unexplored. Alternatively, regulatory checkpoints have been proposed which safeguard against such stochastic RNA processing events, providing a level of quality control. For example, the model of exon definition requires that splicing of the terminal intron relies on synergy between 3' end formation, nascent RNA cleavage, and intron excision. Similarly, multiple studies indicate an increased density of nascent RNA present at the 3' end of genes or in the chromatin-bound fraction, suggesting that nascent RNA is retained at the site of transcription to ensure correct processing. In both the competition model and the checkpoint model, kinetics play a prominent role, but in the latter case the cell has developed additional safeguard mechanisms. In FY13, we used an in vivo single-molecule RNA imaging approach to directly measure kinetic coupling between transcription and splicing of a human B-globin reporter gene. The approach is based on simultaneous dual-color imaging of both the intron and exon of the same pre-mRNA using both PP7 and MS2 stem loops. We found that kinetic competition results in multiple competing pathways for pre-mRNA splicing. Splicing of the terminal intron occurs stochastically both co- and post-transcriptionally, indicating there is not a strict quality control checkpoint to ensure pre-mRNA splicing before transcript release. Post-release splicing occurs from freely diffusing transcripts in the nucleus and is an order of magnitude faster than co-transcriptional splicing. A single missense mutation (Ser34Phe) in the zinc finger domain of the conserved splicing factor U2AF1 which is recurrent in multiple cancers changes the balance, making all splicing post-release. This same effect can also be observed on the endogenous, un-modified fragile X mental retardation mRNA (FXR1). Our results show that kinetic competition governs the stochastic balance between multiple competing pathways for RNA synthesis and processing and that this balance is perturbed by oncogenic mutations.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Investigator-Initiated Intramural Research Projects (ZIA)
Project #
1ZIABC011383-06
Application #
9343898
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
6
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Basic Sciences
Department
Type
DUNS #
City
State
Country
Zip Code
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