Systematic Analysis of Drosophila transcription factor binding specificities

描述（由申请人提供）：生物体基因组的完整注释需要系统地识别顺式调控序列和结合它们的反式作用因子。对于所有生物体来说，实现这一目标的一个重要障碍是具有良好特征的dna结合特异性的转录因子（tf）数量有限。我们开发了一种细菌单杂交系统，提供了一种快速的方法来表征tf的dna结合特异性。利用该技术，我们确定了所有预测序列特异性转录因子的特异性为15%（108/~750）。该特异性目录包括代表12种不同类型的dna结合结构域和所有84个独立同源结构域家族成员的蛋白质。为了补充这个数据集，我们开发了计算工具来绘制TF结合位点频率的基因组分布，并使用这些信息来识别数据集中任何TF组合的推定顺式调控模块（crm）。基于web的界面允许用户在流行的Gbrowse界面中对crm进行全基因组搜索，或显示tf或tf组合的结合位点频率。

DESCRIPTION (provided by applicant): The full annotation of an organism's genome requires the systematic identification of cis-regulatory sequences and the trans-acting factors that bind them. For all organisms, a significant remaining impediment to this goal is the limited number of transcription factors (TFs) with well-characterized DNA-binding specificities. We have developed a bacterial one-hybrid system that provides a rapid method to characterize the DNA-binding specificities of TFs. Using this technology, we have determined the specificity of 15% (108/~750) of all of the predicted sequence-specific transcription factors in Drosophila melanogaster. This catalog of specificities includes proteins representing 12 different types of DNA-binding domains and all 84 independent homeodomain family members. To complement this dataset we have developed computational tools that map the genomic distribution of TF binding site frequencies and use this information to identify putative cis-regulatory modules (CRMs) for any combination of TFs in our dataset. A web-based interface allows users to perform genome-wide searches for CRMs or to display binding site frequencies for TFs or combinations of TFs as tracks within the popular Gbrowse interface. We now propose to characterize the DNA-binding specificity of all remaining D. melanogaster TFs, including all monomeric and homo-oligomeric TFs as well as all functional heterodimeric combinations from the basic leucine zipper and basic helix-loop-helix families. We will also refine our computational tools to improve their ability to distinguish CRMs within the genome and we will integrate other data sources (e.g. ChIP-chip datasets) to enhance the ability to predict CRMs. This effort will culminate in the development of web-accessible database and search tools that will allow the scientific community to computationally identify putative CRMs that are regulated by any combination of factors of interest. An outgrowth of our analysis will be genome-wide annotations of CRMs for subsets of factors that function in known transcriptional regulatory networks. To date, a complete description of TF specificities has not been obtained in any organism. Combined with improved computational tools and the extensive and growing body of experimental studies on D. melanogaster transcription, a catalog of TF specificities will allow the systematic annotation of CRMs throughout its genome. Once developed, these databases and tools should be directly applicable to the annotation of CRMs in other organisms, including humans. PUBLIC HEALTH RELEVANCE: Although the genome project has extensively mapped which DNA sequences in humans and other organisms encode genes, mapping the regulatory regions that turn genes on and off has proven to be much more difficult. We will use newly developed experimental and computational tools to systematically map these control elements in an entire genome. This new genome "map" will help researchers understand how these elements function in normal cells and how mutations in these elements can lead to disease.