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Promoters located at the 5 prime ends of genes play a critical role in regulating transcription initiation. The basal transcriptional machinery of RNA polymerase II assembles at the core promoter, which is a minimum stretch of DNA sequence from up stream 35 to down stream 35 bp of the transcription start site (TSS), that is sufficient to direct the transcription initiation. The proximal promoter region (from up stream 500 to down stream 250 nt of TSS) contains the cis-regulatory elements of most of the TFs. Enhancers and silencers are located several kbp upstream of the TSS. Extensive molecular research has provided a wealth of such information about experimentally characterized proximal promoter sequences, TFs and their binding sites. This information is dispersed throughout various databases, such as GenBank, PubMed, TRANSFAC and DBTSS. The integration of such essential information with the human and rodent genome sequences is one of the major challenges of the post-genome era. Novel high-throughput technologies, such as ChIP-chip (Chromatin-immunoprecipitation followed by microarray analysis), are facilitating the genome-wide identification of the epigenetic mechanisms and protein?DNA interactions that effect gene expression. In recent years, ChIP-chip assays have been successfully used by us and others to find the target genes of transcription factors in mammalian systems. A large-scale effort to map the sequence information on the micro-arrays to the corresponding gene promoters and integration of the ChIP-chip experimental results into a database would significantly help the future studies in modeling mammalian transcriptional regulatory networks. Similar promoter databases, such as EPD, DBTSS and TRED, are available to the research community for quite some time. However, these databases have their own limitations. For example, EPD and DBTSS contain only the annotation of transcription start sites. Although TRED contains more than 50K promoters and seems more comprehensive, it has many putative promoters obtained by computational prediction. Computational programs, such as FirstEF, can predict CpG-related promoters and first exons with high accuracy but perform rather poorly in predicting Non-CpG-related first exons and promoters. In view of these shortcomings, we have essentially considered experimentally supported data from GenBank and other primary data sources in building MPromDb. Here, we present a database of mammalian promoters that are experimentally supported along with experimentally known TF binding sites and ChIP-chip data. The data was obtained by computational pipeline followed by manual curation for high quality. The overall goal of MPromDb is to integrate the ChIP-chip experimental results obtained in our laboratories and others and serve as a portal for promoter analysis of ChIP-chip experimental data. |
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