Even after their discovery more than 60 years ago, little is known about how messenger RNAs (mRNAs) are packaged inside the cells. To ensure efficient and accurate delivery of the intended message to its proper destination, it is important to package the informational molecule in a way that protects it from premature degradation but also proper decoding at the destination. However, very little is known about the this fundamentally important step of mRNA packaging inside eukaryotic cells. To this end, we developed a novel approach, RIPPLiT (RNA ImmunoPrecipitation and Proximity Ligation in Tandem), to capture the 3D architecture of the ribonucleoprotein particles (RNPs) of interest transcriptome-wide. To begin with, we applied RIPPLiT to the exon-junction complex (EJC), a set of proteins stably bound to a spliced RNA. EJCs have been shown to interact with other proteins like SR- and SR-like to form megadalton sized complexes and help protect large regions of mRNAs. Thus, we hypothesized that these RNPs would provide an ideal system to elucidate the higher order organization of mRNPs.
Preliminary analysis of data obtained from RIPPLiT consisted of “chimeric reads”, reads with multiple RNA fragments ligated together, which could not be analyzed with any of the existing bioinformatics tools. Thus, we developed a new bioinformatics suite, ChimeraTie, to map, analyze and visualize chimeric reads. Performing polymer analysis on chimeric reads obtained for hundreds of mRNAs, we were able to predict that mRNPs are linearly and densely packed into flexible rod-like structures before they undergo translation.
In this thesis, along with the detailed biological conclusion, I have also provided a step-wise manual to perform RIPPLiT experiment and analyze the ensuing data using ChimeraTie.
| Identifer | oai:union.ndltd.org:umassmed.edu/oai:escholarship.umassmed.edu:gsbs_diss-2002 |
| Date | 30 July 2018 |
| Creators | Metkar, Mihir |
| Publisher | eScholarship@UMassChan |
| Source Sets | University of Massachusetts Medical School |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Morningside Graduate School of Biomedical Sciences Dissertations and Theses |
| Rights | Licensed under a Creative Commons license, http://creativecommons.org/licenses/by-nc/4.0/ |
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