Moos, Katharina (2023). A Dynamic Model of mRNA Metabolism. PhD thesis, Universität zu Köln.
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Abstract
RNA is one of the key components in the central dogma of biology. The protein-coding mRNAs are synthesised in the nucleus, processed to form the mature mRNA molecule, exported to the cytosol where they are translated into the functional protein, and eventually degraded. Gene expression can be regulated by adjusting, for example, mRNA synthesis or degradation rates. These mRNA metabolic rates are measured with RNA metabolic labelling experiments: Newly synthesised RNAs are tagged with modified nucleosides and can thereby be distinguished from pre-existing RNA transcripts. Yet, the analysis of metabolic labelling data is statistically challenging. The tagging of newly synthesised RNA transcripts is incomplete as only a fraction of the native nucleosides is replaced by the modified nucleoside. Also, to our knowledge, no currently available analysis tool provides a framework to investigate mRNA export. To address these challenges, I developed a dynamic model of mRNA metabolism. The model distinguishes between the nuclear and cytosolic compartment (two-compartment model) and thereby allows to analyse nuclear export in addition to cytosolic degradation. The data pre-processing steps are specifically tailored to metabolic labelling data and include the estimation of RNA labelling efficiencies in a time-dependent manner. We performed a metabolic labelling experiment on HeLa-S3 cells combined with cellular fractionation to measure nuclear and cytosolic RNA separately. We then applied my model to estimate nuclear and cytosolic RNA half lives. We find that nuclear half lives are much higher than cytosolic half lives, which leads to the conclusion that mRNA export is slower than mRNA degradation. Consequently, mRNA transcripts spend most of their lifetime in the nucleus and are more abundant in the nucleus than in the cytosol. We discover a group of outstanding genes, called ‘Supernova’ genes, which show an exceptionally fast mRNA export, arguing for a novel and distinct export mechanism.
Item Type: | Thesis (PhD thesis) | ||||||||||||
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URN: | urn:nbn:de:hbz:38-649288 | ||||||||||||
Date: | 1 March 2023 | ||||||||||||
Language: | English | ||||||||||||
Faculty: | Faculty of Mathematics and Natural Sciences | ||||||||||||
Divisions: | Faculty of Medicine > Medizinische Statistik und Bioinformatik | ||||||||||||
Subjects: | Natural sciences and mathematics Mathematics |
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Date of oral exam: | 27 April 2022 | ||||||||||||
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Refereed: | Yes | ||||||||||||
URI: | http://kups.ub.uni-koeln.de/id/eprint/64928 |
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