RNA sequencing for the study of splicing
type: CreativeWork
description: Amongst the many processes that shape the final set of RNA molecules present in eukaryote cells, splicing emerges as the most prominent mechanism for message diversification. In recent years, applications of high throughput sequencing to RNA, known as RNA sequencing, have opened new avenues for the study of transcriptome composition, and have enabled further characterisation of such mechanism. In this thesis, I focus on the application of this technology to the study of human transcript diversity and its potential impact on the protein repertoire. In the first results chapter, I explore the extent of transcriptome diversity by asking whether there is a preference for the production of specific alternative transcripts within each given gene. I show that while many alternative transcripts can be detected, the expression of most protein coding genes tends to be dominated by one single transcript (major transcript). Such findings are validated in the second chapter, and are further used to explore changes in splicing patterns in a disease context. By analysing healthy and tumor samples from kidney cancer patients, I show that most of the detected splicing alterations do not lead to big changes in the relative abundance of major transcripts, at least in a recurrent manner. In addition, I introduce a framework to visualise the most extreme changes in splicing and to evaluate their potential functional impact. In the third chapter, I investigate the role of spliceosome assembly dynamics on the regulation of splice site choice. I show that depletion of PRPF8, a core spliceosomal component, leads to the preferential retention of a subset of introns with weaker splice sites, and also introduces alterations in the rate of co-transcriptional splicing. Finally, in the last chapter, I explore the validation of changes in alternative transcript abundance at the protein level, through the integration of results derived from RNA sequencing datasets with those obtained from proteomic…
abstract: Amongst the many processes that shape the final set of RNA molecules present in eukaryote cells, splicing emerges as the most prominent mechanism for message diversification. In recent years, applications of high throughput sequencing to RNA, known as RNA sequencing, have opened new avenues for the study of transcriptome composition, and have enabled further characterisation of such mechanism. In this thesis, I focus on the application of this technology to the study of human transcript diversity and its potential impact on the protein repertoire. In the first results chapter, I explore the extent of transcriptome diversity by asking whether there is a preference for the production of specific alternative transcripts within each given gene. I show that while many alternative transcripts can be detected, the expression of most protein coding genes tends to be dominated by one single transcript (major transcript). Such findings are validated in the second chapter, and are further used to explore changes in splicing patterns in a disease context. By analysing healthy and tumor samples from kidney cancer patients, I show that most of the detected splicing alterations do not lead to big changes in the relative abundance of major transcripts, at least in a recurrent manner. In addition, I introduce a framework to visualise the most extreme changes in splicing and to evaluate their potential functional impact. In the third chapter, I investigate the role of spliceosome assembly dynamics on the regulation of splice site choice. I show that depletion of PRPF8, a core spliceosomal component, leads to the preferential retention of a subset of introns with weaker splice sites, and also introduces alterations in the rate of co-transcriptional splicing. Finally, in the last chapter, I explore the validation of changes in alternative transcript abundance at the protein level, through the integration of results derived from RNA sequencing datasets with those obtained from proteomic…
author: Gonzàlez-Porta, Mar
language: en
keywords: RNAseq, RNA sequencing, Transcriptomics, Splicing, Human
license: https://www.repository.cam.ac.uk/bitstreams/0eb1ab8f-c9de-43f0-84e1-2d007408d98c/download
date published: 2014-10-07
date modified: 2026-07-24T01:33:33Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.15986