The control of gene expression is highly combinatorial: most transcription factors (TFs) regulate the expression of multiple genes, and most genes are themselves regulated by multiple TFs. Interactions between TFs and their target genes can be visualized in transcription regulatory networks. Such networks allow insights into higher order regulation of gene expression, for example by the identification and characterization of network <
sym08>hubs<
sym09> and network motifs. Here, we present a transcription regulatory network of the C. elegans digestive tract. To identify TF-target gene interactions in a high-throughput manner, we developed a Gateway-compatible yeast one-hybrid (Y1H) system. This Y1H system can be used to identify TFs that can bind to a gene promoter. Our Y1H system is compatible with ORFeome (for TF-encoding ORFs) and Promoterome (for target gene promoters) resources, and allows the identification of TF-target gene interactions from a <
sym08>gene centered<
sym09> perspective. Thus, this system provides information that is distinct from, but complementary to data obtained from <
sym08>TF centered<
sym09> chromatin-immunoprecipitation-based methods. We used our Y1H system to identify TF-promoter interactions for 180 genes involved in development of the worm digestive tract. We identified >300 TF-DNA interactions and visualized these into a transcription regulatory network. The resulting network is highly connected and contains several TF and promoter <
sym08>hubs<
sym09> (e.g. TFs that bind to many genes and vice versa). We characterized several TF hubs in more detail. For instance, we inspected the collection of DNA fragments they can interact with to predict consensus TF binding sites. We also identified several other network motifs, including feed forward loops, regulator chains and single- and multi-input motifs. We have begun to experimentally test several hypotheses derived from this network. Taken together, the Y1H system provides a powerful tool for the high-throughput mapping of transcription regulatory networks in metazoan systems.