Deciphering the landscape of snoRNA-mediated RNA modifications with high-throughput sequencing approaches

Jedlinski, Dominik Jan. Deciphering the landscape of snoRNA-mediated RNA modifications with high-throughput sequencing approaches. 2016, Doctoral Thesis, University of Basel, Faculty of Science.


Official URL: http://edoc.unibas.ch/diss/DissB_12036

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Recent years have witnessed a burst of studies in the rapidly developing field of “epitranscriptomics”, which encompasses post-transcriptional changes of transcripts that have a functional relevance. Several new experimental approaches coupled with high-throughput-sequencing enabled the transcriptome-wide mapping of various RNA modifications, including those that are guided by the well-characterized small nucleolar RNAs (snoR-NAs). In the projects presented in this thesis, we have taken advantage of these new tools to comprehensively examine snoRNA functions in various cellular systems as well as in a health/disease context.
The first question that we set to answer is how complete is the catalog of human snoRNAs and snoRNA pro-cessing products, since it is known that a variety of small RNAs derive from other RNAs with well-known functions such as tRNAs and snoRNAs. To answer this question we sequenced long and short RNAs, RNA fragments ob-tained in photoreactive nucleotide-enhanced cross-linking and immunoprecipitation (PAR-CLIP) of core snoRNA-associated proteins and small RNAs that co-precipitate with the Argonaute 2 (Ago2) protein. A striking outcome of this study was that virtually all C/D box snoRNAs are specifically processed inside the regions of terminal com-plementarity, retaining in the mature form only 4-5 nucleotides upstream of the C box and 2-5 nucleotides down-stream of the D box. Further we found several new non-coding RNA targets that were repeatedly identified as bound by the core snoRNPs and that were validated as carrying 2’-O-methyl sites and/or pseudouridines. Analysis of the total and Ago2-associated populations of small RNAs in human cells revealed that despite their cellular abundance, snoRNA-derived small RNAs are not efficiently incorporated into the Ago2 protein. We therefore con-cluded that a miRNA-like function for these products in human is unlikely.
Identification of the targets for the many newly discovered regulatory RNAs remains a challenge. To address this problem, in a second project, we combined two powerful experimental high-throughput methods (CLIP-seq and RiboMeth-seq) with computational modelling to map 2’-O-methylation sites in human rRNA and to comprehen-sively associate C/D box guide snoRNAs with targets. We thereby determined that many “orphan” snoRNAs ap-pear to guide 2’-O-ribose methylation at sites that are targeted by other snoRNAs. Moreover, we found that snoRNAs can be reliably captured in interaction with many mRNAs, yet a subsequent 2’-O-methylation of these mRNAs cannot be detected. Our study provides a reliable approach to the comprehensive characterization of snoRNA-target interactions in species beyond those in which these interactions have been traditionally studied and contributes to the rapidly developing field of “epitranscriptomics”.
Finally, we applied the same approach to study a particular group of orphan snoRNAs that have been implicated in a rare neurodevelopmental disorder called Prader-Willi syndrome (PWS). PWS is characterized by excessive appe-tite, morbid obesity, mental and growth retardation, which are due to the loss of paternal expression of the ma-ternally imprinted SNORD116 C/D box snoRNAs. snoRNP-CLIPs in mouse and human cell lines as well as mouse primary neurons revealed that SNORD116 snoRNAs associate with snoRNP proteins, yet the RiboMeth-seq indi-cates that they do not have a primary snoRNP guide function. Nevertheless, the 2’-O-methylation landscape of wild-type mouse differs from that of a mouse model that does not express Snord116, and the identified candidate target sites are now subject to validation by mass spectrometry.
Advisors:Zavolan, Mihaela and Grosshans, Helge
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (Zavolan)
UniBasel Contributors:Zavolan, Mihaela
Item Type:Thesis
Thesis Subtype:Doctoral Thesis
Thesis no:12036
Thesis status:Complete
Number of Pages:1 Online-Ressource (viii, 90 Seiten)
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Last Modified:08 Feb 2020 14:35
Deposited On:03 Apr 2017 09:38

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