Visualising ribosome profiling and using it for reading frame detection and exploration of eukaryotic translation initiation

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dc.check.chapterOfThesisChapters of thesis - 4,5
dc.check.date10000-01-01
dc.check.embargoformatBoth hard copy thesis and e-thesisen
dc.check.infoPlease note that Chapter 4 (pp.63-75) and Chapter 5 (pp.91-254) are unavailable due to a restriction requested by the author.en
dc.check.opt-outNot applicableen
dc.check.reasonThis thesis is due for publication or the author is actively seeking to publish this materialen
dc.contributor.advisorAtkins, John F.en
dc.contributor.advisorBaranov, Pavel V.en
dc.contributor.authorMannion Michel, Audrey
dc.contributor.funderIrish Research Council for Science Engineering and Technologyen
dc.date.accessioned2014-06-13T10:20:30Z
dc.date.issued2013
dc.date.submitted2014
dc.description.abstractRibosome profiling (ribo-seq) is a recently developed technique that provides genomewide information on protein synthesis (GWIPS) in vivo. The high resolution of ribo-seq is one of the exciting properties of this technique. In Chapter 2, I present a computational method that utilises the sub-codon precision and triplet periodicity of ribosome profiling data to detect transitions in the translated reading frame. Application of this method to ribosome profiling data generated for human HeLa cells allowed us to detect several human genes where the same genomic segment is translated in more than one reading frame. Since the initial publication of the ribosome profiling technique in 2009, there has been a proliferation of studies that have used the technique to explore various questions with respect to translation. A review of the many uses and adaptations of the technique is provided in Chapter 1. Indeed, owing to the increasing popularity of the technique and the growing number of published ribosome profiling datasets, we have developed GWIPS-viz (http://gwips.ucc.ie), a ribo-seq dedicated genome browser. Details on the development of the browser and its usage are provided in Chapter 3. One of the surprising findings of ribosome profiling of initiating ribosomes carried out in 3 independent studies, was the widespread use of non-AUG codons as translation initiation start sites in mammals. Although initiation at non-AUG codons in mammals has been documented for some time, the extent of non-AUG initiation reported by these ribo-seq studies was unexpected. In Chapter 4, I present an approach for estimating the strength of initiating codons based on the leaky scanning model of translation initiation. Application of this approach to ribo-seq data illustrates that initiation at non-AUG codons is inefficient compared to initiation at AUG codons. In addition, our approach provides a probability of initiation score for each start site that allows its strength of initiation to be evaluated.en
dc.description.sponsorshipIrish Research Council for Science Engineering and Technology (EMBARK Initiative)en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Version
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMannion Michel, A. 2013. Visualising ribosome profiling and using it for reading frame detection and exploration of eukaryotic translation initiation. PhD Thesis, University College Cork.en
dc.identifier.endpage254
dc.identifier.urihttps://hdl.handle.net/10468/1575
dc.language.isoenen
dc.publisherUniversity College Corken
dc.relation.urihttp://gwips.ucc.ie
dc.rights© 2013, Audrey Mannion Michelen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectRibosome profilingen
dc.subjectDual codingen
dc.subjectTranslation initiationen
dc.subjectRibosome profiling visualisationen
dc.subjectGWIPS-vizen
dc.subjectGenome-wide information on protein synthesis (GWIPS)en
dc.thesis.opt-outfalse
dc.titleVisualising ribosome profiling and using it for reading frame detection and exploration of eukaryotic translation initiationen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD (Science)en
ucc.workflow.supervisorj.atkins@ucc.ie
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