Transcriptional regulatory information, represented by patterns of protein binding sites on DNA, comprises a key portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remains a major challenge. Minor changes in protein binding sites can have profound effects on gene expression, and such changes have been shown to underlie key aspects of disease and evolution. Thus, a key goal in contemporary genomics is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences however distinct enhancers differ in many features, including transcription factor activity, spacing and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis-regulatory elements. We have pursued a unique "bottom up" approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study is concentrated on a set of proteins known as short-range repressors such as Giant, Kruppel, Knirps and Snail, which play central roles in development.We have generated a large quantitative data set using fluorescent Confocal Laser Scanning Microscopy (CLSM) to determine the inputs (Giant, Kruppel and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. In this study (Chapter 2) we present a semi-automatic algorithm to process the image stacks from CLSM to correlate the protein levels of the short-range repressors with lacZ mRNA produced by reporter genes using images of Drosophila blastoderm embryos. We show that signals derived from CLSM are proportional to actual mRNA levels. Our analysis reveals that a suggested parabolic form of the background fluorescence in confocal images of early Drosophila embryos is evident most prominently in flattened specimens, with intact embryos exhibiting a more linear background. The data extraction described in this paper is primarily conceived for analysis of synthetic reporter genes, but the techniques are generalizable for quantitative analysis of other engineered or endogenous genes in embryos.Using fractional occupancy based modeling on this data set (Chapter 3) we identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters are used to build and test the model. We uncovered previously unknown features that allow correct predictions of regulation by short-range repressors on synthetic and endogenous elements. These features include a nonmonotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor-repressor cooperativity, and similarity in repression of disparate activators. This work provides essential quantitative elements of a transcriptional grammar that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification of cis-regulatory elements and the prediction of the quantitative output from novel regulatory elements.
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