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An Evolutionary Approach to Long-Range Regulation

Posted on:2011-04-09Degree:Ph.DType:Thesis
University:McGill University (Canada)Candidate:Mongin, EmmanuelFull Text:PDF
GTID:2440390002467702Subject:Biology
Abstract/Summary:
Long-range regulatory regions play important functions in the regulation of transcription and are particularly involved in the precise spatio-temporal expression of target genes. Such regions have specific characteristics, among which is their ability to regulate many target genes that can be located up to 1Mb from the transcription start site. The prediction and functional characterization of such regions remains an open problem. Evolutionary approaches have been developed to detect regulatory regions that are under purifying selection. However, little has been done with regards to the impact of long-range regulation on genome evolution.;The results presented in this thesis contribute to different areas of research such as a better understanding of evolutionary dynamics related to evolutionary rearrangements and to a better in silico and in vivo characterization of cis-regulatory regions.;This thesis focuses on three different aspects of long-range regulation: (i) First we develop a method that predicts regions particularly prone to the fixation of evolutionary breakpoints. We discuss the results obtained in the context of long-range regulation and show that this type of regulation is a major factor shaping vertebrate genomes in evolution. (ii) The second project aims at predicting functional interactions between regulatory regions and target genes based on the observation of evolutionary rearrangements in various vertebrate species. We show how this approach produces a biologically meaningful prediction dataset that will be useful to researchers working on regulation. (iii) Third, we focus on the in vivo characterization of regulatory regions. We present a powerful and reliable enhancer detection pipeline composed of an in silico approach to predict putative enhancers and an in vivo method to functionally characterize the expression specificity of predicted regions in the developing medaka fish.
Keywords/Search Tags:Regions, Regulation, Long-range, Evolutionary, Approach
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