http://www.dspace.cam.ac.uk:80/handle/1810/221783 Fri, 24 May 2013 17:19:55 GMT 2013-05-24T17:19:55Z http://www.dspace.cam.ac.uk:80/handle/1810/244240 Title: Evolutionary analysis of animal microRNAs Authors: Guerra Martins dos Santos Assunção, José Afonso Abstract: In recent years, microRNAs (miRNAs) have been recognised as important genetic regulators of gene expression in Animals and Plants. They can potentially target a large fraction of the cellular transcriptome, having been shown to be important for diverse biological processes such as development, cell differentiation, proliferation and metabolism. The publication of the Human genome in 2001 marked the start of a great community effort to sequence a variety of other species. These data have great potential for comparative genomics, that can lead to better biological understanding. Some miRNA families are known to be highly conserved, across long evolutionary distances, many found in co-transcribed clusters across the genome. While these phenomena have been previously reported, a large-scale analysis of evolutionary patterns was still lacking. Furthermore, the rate at which new relevant data is being made available makes it challenging to keep up and many of the evolutionary studies performed before are now significantly out of date. This thesis describes a number of approaches taken to analyse miRNA datasets, harnessing the full potential of currently available data for comparative genomics. These were used, not only to revisit many of the notions in the field with a larger and updated dataset, but also to develop novel strategies that enable a coherent view of miRNA evolution at different evolutionary time-scales. A new tool, described within this thesis, was developed for large-scale, species independent miRNA mapping. An assessment of the evolution of the miRNA reper- toire across species was performed, together with detailed sequence conservation analysis and miRNA family clustering. Phylogenetic profile analysis uncovered in- teresting co-evolution between miRNAs and protein coding genes. The genomic organisation of miRNAs and their conservation across species was also studied, pro- viding detailed conserved synteny maps for miRNAs and proteins across more than 80 species. Finally, at the intra-specific level, I analysed the occurrence of single nucleotide polymorphisms affecting miRNA loci or their predicted target sites. All the tools built and integrated in this research were made available to the community and designed to be easily updated, making it easier to keep up with the data that is constantly being made available. Many aspects of miRNA biology are still being uncovered, and the ability to easily put these findings into an evolutionary context will potentially be useful for the community. Tue, 08 Jan 2013 00:00:00 GMT http://www.dspace.cam.ac.uk:80/handle/1810/244240 2013-01-08T00:00:00Z http://www.dspace.cam.ac.uk:80/handle/1810/236115 Title: A statistical model relating transcription factor concentrations to positional information in the early Drosophila embryo Authors: Ilsley, Garth Robert Abstract: The idea of morphogen gradients encoding positional information for a developing organism has long been discussed in the field of developmental biology, but only recently have quantitative models been proposed that relate measured transcription factor concentrations to enhancer activity. However, successful models are typically computationally time-consuming, thus limiting full exploration and interpretation of the data. This thesis addresses these problems using standard statistical techniques applied to a comprehensive data set with the even skipped (eve) locus as a test case. The first part of the thesis introduces the data set. This is the precellular Virtual Embryo from the Berkeley Drosophila Transcription Network project. It comprises expression measurements of almost 100 genes in more than 6,000 individual nuclei at six time points. Different modelling approaches are evaluated in the context of this data set leading to a justification of logistic regression and the methods used to prepare the data set for further analysis. The second part applies logistic regression to describe the response of the eve enhancers to known regulating transcription factors such as Hunchback. Predictions of behaviour under regulator perturbation are consistent with experimental results and the functional form is shown not to be arbitrarily flexible, both in terms of the regulators and regions of the embryo included. The third part uses the framework developed above to find minimal explanatory models in the context of statistical model selection. It is found that the best scoring models depend on well-known regulators. The model selection techniques are then extended by directing the process using previous biological observations to analyse the eve 2 and eve 3+7 enhancers. The results are consistent with published research, but suggest specific additional hypotheses for the enhancers’ regulation. Finally, the thesis concludes by proposing a general model of positional information and discussing the biological implications of the results. Overall, the results show how transcriptional control can be allocated to discrete enhancers and that characterising their activity in relatively simple terms is sufficient to explain their precise spatially-defined response to transcription factor concentrations. Mon, 11 Oct 2010 23:00:00 GMT http://www.dspace.cam.ac.uk:80/handle/1810/236115 2010-10-11T23:00:00Z