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Title: Transcriptional brain networks and their key regulators across the human lifespan
Author: Wehrspaun, Claudia Constanze
ISNI:       0000 0004 5369 4675
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
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The human brain’s transcriptome undergoes substantial changes over the lifespan and shows characteristic patterns that reflect anatomical regions and cellular compositions. In this thesis, I applied combinations of network algorithms and tools from computational biology to analyse transcriptional networks and their key regulators in the human brain across space (brain regions) and time (the human life course). First, I identified an age-dependent transcriptional network enriched for microglial markers. The microglia network recapitulated haematopoietic master regulators that are crucial for early microglia development using data from the ageing human brain only. In the second project, I demonstrated that gene clusters linked to neurogenesis during fetal life show moderate to strong preservation in the human adult brain. In addition to temporal development, I analysed transcriptional network dynamics across the spatial axis and detected a network of ion channel/transporter genes that express their longest 3’ untranslated regions (3’UTRs) exclusively in the brain. Enrichment for predicted miRNA response elements that are often shared among the ion channel/transporter genes, along with increased co-expression of this gene set, indicated that the extended 3’UTRs could serve as a hub for an endogenous competitive RNA network. I extended the analysis to differentiate between brain regions and additional regulatory RNA elements, namely long noncoding (lnc) RNAs. I found that genes in the hypothalamus express a region-specific network to which are also associated co-expressed lncRNAs. Finally, I added global metrics to the analysis of local networks. The dynamics of global network metrics indicated strong coordination of expression across the lifespan compared to similar variance within age groups. This work shows that the transcriptome of human post-mortem brains at least partially preserves the network structure of cell types and functionally related genes, and how it may be dissected using suitable combinations of bioinformatic algorithms.
Supervisor: Ponting, Chris P. Sponsor: Wellcome Trust
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Life Sciences ; Bioinformatics (life sciences) ; Genetics (life sciences) ; Neuroscience ; transcriptional network ; ageing ; gene expression