Abstract
BackgroundTranscription regulatory networks are composed of protein-DNA interactions between transcription factors and their target genes. A long-term goal in genome biology is to map protein-DNA interaction networks of all regulatory regions in a genome of interest. Both transcription factor -and gene-centered methods can be used to systematically identify such interactions. We use high-throughput yeast one-hybrid assays as a gene-centered method to identify protein-DNA interactions between regulatory sequences (e.g. gene promoters) and transcription factors in the nematode Caenorhabditis elegans. We have already mapped several hundred protein-DNA interactions and analyzed the transcriptional consequences of some by examining differential gene expression of targets in the presence or absence of an upstream regulator. The rapidly increasing amount of protein-DNA interaction data at a genome scale requires a database that facilitates efficient data storage, retrieval and integration.DescriptionHere, we report the implementation of a C. elegans differential gene expression database (EDGEdb). This database enables the storage and retrieval of protein-DNA interactions and other data that relate to differential gene expression. Specifically, EDGEdb contains: i) sequence information of regulatory elements, including gene promoters, ii) sequence information of all 934 predicted transcription factors, their DNA binding domains, and, where available, their dimerization partners and consensus DNA binding sites, iii) protein-DNA interactions between regulatory elements and transcription factors, and iv) expression patterns conferred by regulatory elements, and how such patterns are affected by interacting transcription factors.ConclusionEDGEdb provides a protein-DNA -and protein-protein interaction resource for C. elegans transcription factors and a framework for similar databases for other organisms. The database is available at .
Highlights
Transcription regulatory networks are composed of protein-DNA interactions between transcription factors and their target genes
Two complementary strategies are currently being used to identify protein-DNA interactions: transcription factors (TFs)-centered approaches, where the DNA sequences that interact with a TF or set of TFs of interest are identified; and genecentered methods that identify the TFs that interact with a regulatory DNA sequence or set of DNA sequences of interest[2]
We have identified 605 protein-DNA interactions between 115 gene promoters and 176 TFs [3,5,6,7]
Summary
Transcription regulatory networks are composed of protein-DNA interactions between transcription factors and their target genes. A long-term goal in genome biology is to map protein-DNA interaction networks of all regulatory regions in a genome of interest Both transcription factor -and gene-centered methods can be used to systematically identify such interactions. We use high-throughput yeast one-hybrid assays as a gene-centered method to identify protein-DNA interactions between regulatory sequences (e.g. gene promoters) and transcription factors in the nematode Caenorhabditis elegans. Differential gene expression is governed, at least in part, by protein-DNA interactions between transcription factors (TFs) and their target genes Together, such proteinDNA interactions can be modeled into transcription regulatory networks that describe the logic underlying the development, function, and pathology of a system of interest [1,2]. We developed a high-throughput yeast one-hybrid system for the gene-centered mapping of protein-DNA interactions between gene promoters or small cis-regulatory elements and TFs in the nematode Caenorhabditis elegans [3,4]. We aim to generate a protein-DNA interaction map between all regulatory DNA elements and TFs in the C. elegans genome [2]
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