Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.677721
Title: Transcriptional co-regulation of microRNAs and protein-coding genes
Author: Webber, Aaron
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2013
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Abstract:
This thesis was presented by Aaron Webber on the 4th December 2013 for the degree of Doctor of Philosophy from the University of Manchester. The title of this thesis is ‘Transcriptional co-regulation of microRNAs and protein-coding genes’. The thesis relates to gene expression regulation within humans and closely related primate species. We have investigated the binding site distributions from publically available ChIP-seq data of 117 transcription regulatory factors (TRFs) within the human genome. These were mapped to cis-regulatory regions of two major classes of genes,  20,000 genes encoding proteins and  1500 genes encoding microRNAs. MicroRNAs are short 20 - 24 nt noncoding RNAs which bind complementary regions within target mRNAs to repress translation. The complete collection of ChIP-seq binding site data is related to genomic associations between protein-coding and microRNA genes, and to the expression patterns and functions of both gene types across human tissues. We show that microRNA genes are associated with highly regulated protein-coding gene regions, and show rigorously that transcriptional regulation is greater than expected, given properties of these protein-coding genes. We find enrichment in developmental proteins among protein-coding genes hosting microRNA sequences. Novel subclasses of microRNAs are identified that lie outside of protein-coding genes yet may still be expressed from a shared promoter region with their protein-coding neighbours. We show that such microRNAs are more likely to form regulatory feedback loops with the transcriptional regulators lying in the upstream protein-coding promoter region. We show that when a microRNA and a TRF regulate one another, the TRF is more likely to sometimes function as a repressor. As in many studies, the data show that microRNAs lying downstream of particular TRFs target significantly many genes in common with these TRFs. We then demonstrate that the prevalence of such TRF/microRNA regulatory partnerships relates directly to the variation in mRNA expression across human tissues, with the least variable mRNAs having the most significant enrichment in such partnerships. This result is connected to theory describing the buffering of gene expression variation by microRNAs. Taken together, our study has demonstrated significant novel linkages between the transcriptional TRF and post-transcriptional microRNA-mediated regulatory layers. We finally consider transcriptional regulators alone, by mapping these to genes clustered on the basis of their expression patterns through time, within the context of CD4+ T cells from African green monkeys and Rhesus macaques infected with Simian immunodeficiency virus (SIV). African green monkeys maintain a functioning immune system despite never clearing the virus, while in rhesus macaques, the immune system becomes chronically stimulated leading to pathogenesis. Gene expression clusters were identified characterizing the natural and pathogenic host systems. We map transcriptional regulators to these expression clusters and demonstrate significant yet unexpected co-binding by two heterodimers (STAT1:STAT2 and BATF:IRF4) over key viral response genes. From 34 structural families of TRFs, we demonstrate that bZIPs, STATs and IRFs are the most frequently perturbed upon SIV infection. Our work therefore contributes to the characterization of both natural and pathogenic SIV infections, with longer term implications for HIV therapeutics.
Supervisor: Robertson, David ; Griffiths-Jones, Samuel Sponsor: Biotechnology and Biological Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.677721  DOI: Not available
Keywords: MicroRNA ; Transcription factor ; Regulatory network
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