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Computational genomics of regulatory elements and regulatory territories

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Title: Computational genomics of regulatory elements and regulatory territories
Authors: Tan, Ge
Item Type: Thesis or dissertation
Abstract: Whole genome comparison of metazoan genomes reveals extremely high level of noncoding conservation over tens to hundreds of base pairs across distant species. These sequences are termed as conserved noncoding elements (CNEs). Arrays of conserved noncoding elements that span the loci of developmental regulatory genes and their span defines regulatory genomic blocks (GRBs). CNEs are currently known to be involved in transcriptional regulation and development as long-range enhancers. However, no molecular mechanism can yet explain their exceptional degree of conservation. As a first step towards the genome-wide study of these elements, I developed two R/Bioconductor packages CNEr and TFBSTools, to detect and analyse regulatory elements. Next, I designed a novel CNE detection pipeline for duplicated regions in the ameiotic Adineta vaga genome. Identification of CNEs in this genome suggests that the principal function of CNEs is regulation of developmental gene expression rather than copy number sensing. In addition, I performed a de novo genome annotation of European common carp Cyprinus carpio. This genome stands as an ideal candidate for comparative study of zebrafish genome. Its analysis revealed a wealth of previously undetected fish regulatory elements and their unexpectedly high level of conservation between the two genomes. Finally, I presented a computational method for the identification of GRB boundaries and prediction of the corresponding target genes under long-range regulation. The predicted target genes are implicated in developmental, transcriptional regulation and axon guidance. The disruption of regulation of these target genes is likely to cause complex diseases, including cancer. The GRB boundaries and predicted target genes are valuable resource for investigating developmental regulation and interpreting genome-wide association studies.
Content Version: Open Access
Issue Date: Nov-2017
Date Awarded: May-2018
URI: http://hdl.handle.net/10044/1/59758
DOI: https://doi.org/10.25560/59758
Supervisor: Lenhard, Boris
Department: Institute of Clinical Sciences
Publisher: Imperial College London
Qualification Level: Doctoral
Qualification Name: Doctor of Philosophy (PhD)
Appears in Collections:Department of Clinical Sciences PhD Theses

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