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MIT OpenCourseWare http://ocw.mit.edu 6.047 / 6.878 Computational Biology: Genomes, Networks, EvolutionFall 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.Genome wide st udy of gene regulation 6.047/6.878 Lecture 20 Lectured by P. Kheradpour, 11/13/08 Table of contents Genome wide study of gene regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Gene expression patterns (motivation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Transcription factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Experimental discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Computational discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Discovered motifs have functional enrichments . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 microRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 The biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Computational miRNA dis covery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 12 Drosophila genomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Validation of the predicted miRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Additional signatures of mature miRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Prediction of binding sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Experimental approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Computational approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Phylogenetic footprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Comparison with experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Network level examination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Gene expression patterns (motivation) Given the complex spatial and temporal regulation of gene expression [7], exemplified by recent studies on the mouse [21], and on Drosophil a heart de velopment [30], there is great impetus to identify the targets of regulatory factors in order to understand how such re gulation is achieved. Many connections in these regulatory networks are conserved all the way up to mammmals, and so we can conceivably use evolutionary information in order to probe the regulator y networks of humans. We will focus here on regulation of transcription – as achieved by transcription factors (TFs) – and also regulation of translation by microRNAs (miRNAs). Transcription factors TFs re gulate the expression of target genes by binding to DNA, in regions that may or may not be proximal to the gene that is being regulated. Binding is specific for a particular target sequence, or motif , although there is most probably also non-specific binding that enables the TFs to bind to other regions of DNA in order to rapidly locate their target s equences [10]. Each motif can be v ie wed as a position weight matrix (PWM), which shows the relative specificity for each base at every position in the motif. T he effect of TF binding may be to activate or to repress gene expression. 1We will now examine some of the approaches that have been used to discover motifs. Experimental discovery Several revolutionary exp e rimental methods have enabled motif discovery to be carried out in a brute force, de novo fashion, without need for knowledge of promoter regions. The Systematic Evolution of Ligands by Ex ponential Enrichment (SELEX) protocol [32] involves taking a pool of RNA or DNA fragments (the library) and adding the protei n of interest. T he members of …


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