RNA structures in non-coding RNA : from the SARS-CoV-2 genome to S. cerevisiae introns
Abstract/Contents
- Abstract
- Structured RNAs play critical roles across the domains of life, whether facilitating viral packaging and replication or regulating complex eukaryotic RNA processing pathways like pre-mRNA splicing. Understanding RNA in the context of its folding can give us a better picture for the mechanism and regulation of these processes, and moreover, this understanding could inform attempts to intervene in these pathways. In the first section of this dissertation, I will discuss the capabilities of computational RNA structure prediction and RNA structure determination. I will highlight our efforts towards evaluating de novo computational prediction methods for RNA tertiary structures, along with our work on building RNA structures in cryo-EM density maps for large RNA or RNA-protein complexes. Then I will focus on our application of de novo RNA structure modeling in making predictions for secondary and tertiary structures in the SARS-CoV-2 RNA genome, providing candidate target regions for diagnostics and anti-viral therapeutic development. In the second section of the dissertation, I will focus on our characterization of the RNA structure landscape in S. cerevisiae pre-mRNA through biochemical experiments and computational prediction. We identify intron secondary structures through transcriptome-wide dimethyl sulfate (DMS) probing experiments, enriching for low-abundance pre-mRNA through splicing inhibition. These data reveal structures bridging splice sites present across yeast introns, along with previously uncharacterized long stems that distinguish pre-mRNA from spliced mRNA. With high-throughput structure-function experiments, we measure the effects of modulating a set of candidate intron structures, finding that some structured elements can increase spliced mRNA levels despite being distal from canonical splice sites, while other structures can increase intron retention. To more deeply interrogate these functional intron structures, we explore the potential protein-binding partners and tertiary structure for a candidate functional structured domain. Our transcriptome-wide inference of intron RNA structures suggests new ideas and model systems for understanding how pre-mRNA folding promotes splicing efficiency and regulation of gene expression. This approach provides a blueprint for computational, structural, and functional experiments that can help dissect the role that RNA structure plays in various biological processes.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Rangan, Ramya |
|---|---|
| Degree supervisor | Das, Rhiju |
| Thesis advisor | Das, Rhiju |
| Thesis advisor | Manuel Ares, Jr |
| Thesis advisor | Puglisi, Joseph D |
| Degree committee member | Manuel Ares, Jr |
| Degree committee member | Puglisi, Joseph D |
| Associated with | Stanford University, School of Humanities and Sciences |
| Associated with | Stanford University, Biophysics Program |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Ramya Rangan. |
|---|---|
| Note | Submitted to the Biophysics Program. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/bc953ry5802 |
Access conditions
- Copyright
- © 2023 by Ramya Rangan
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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