Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.772084
Title: Regulation of gene expression in human brain using transcriptome sequencing
Author: Guelfi, Manuel Sebastian
ISNI:       0000 0004 7661 1158
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
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Abstract:
Characterising the molecular mechanisms underlying disease risk variants identified in genome-wide association studies (GWAS) is of major interest. Expression Quantitative Trait Loci (eQTL) mapping studies provide a genome-wide characterisation of the impact of common genetic variation on gene expression and splicing and therefore have the potential to achieve this. In this thesis, I investigated the effect of common genetic variants in human brain through eQTL analysis. As part of the UK Brain Expression Consortium project, the analyses in this PhD thesis were performed on whole transcriptome RNA sequencing data from neuropathologically normal human post-mortem brain. I conducted eQTL analyses on putamen and substantia nigra using different types of quantification in order to interrogate regulation at different stages of RNA processing. This analysis pointed to splicing as an important process for the pathogenesis of Parkison's Disease. Thus, I identify not only disease-relevant regulatory loci but also the types of analyses yielding the most disease-specific information. Due to the limitations of current gene annotation and the complex transcriptomic landscape in human brain, I investigated transcription and splicing in the hippocampus using annotation-agnostic methods. This not only revealed the existence of widespread gene misannotation in the human brain, but also revealed the limitation of current quantification methods to capture transcriptome complexity in brain. Therefore, a reference-free eQTL analysis was performed and by testing for eQTL-GWAS co-localisation I found that incomplete annotation of the brain transcriptome limits the interpretation of risk loci for neurological disorders. I anticipate that analyses of this kind will have an increasing impact on our understanding of a range of disorders, but are likely to have most impact on neurological and neuropsychiatric disorders because of the high transcriptome complexity of human brain tissue.
Supervisor: Ryten, M. ; Weale, M. ; Hardy, J. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.772084  DOI: Not available
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