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Transcriptional factors (TFs) and many of their target genes are involved in gene regulation at the level of transcription. To decipher gene regulatory networks (GRNs) we require a comprehensive and accurate knowledge of transcriptional regulatory elements. TRED (http://rulai.cshl.edu/TRED) was designed as a resource for gene regulation and function studies. It collects mammalian cis- and trans-regulatory elements together with experimental evidence. All the regulatory elements were mapped on to the assembled genomes. In this new release, we included a total of 36 TF families involved in cancer. Accordingly, the number of target promoters and genes for TF families has increased dramatically. There are 11,660 target genes (7479 in human, 2691 in mouse and 1490 in rat) and 14,908 target promoters (10,225 in human, 2985 in mouse and 1698 in rat). Additionally, we constructed GRNs for each TF family by connecting the TF-target gene pairs. Such interaction data between TFs and their target genes will assist detailed functional studies and help to obtain a panoramic view of the GRNs for cancer research.

In order to understand gene regulation, accurate and comprehensive knowledge of transcriptional regulatory elements is essential. Here, we report our efforts in building a mammalian Transcriptional Regulatory Element Database (TRED) with associated data analysis functions. It collects cis- and trans-regulatory elements and is dedicated to easy data access and analysis for both single-gene-based and genome-scale studies. Distinguishing features of TRED include: (i) relatively complete genome-wide promoter annotation for human, mouse and rat; (ii) availability of gene transcriptional regulation information including transcription factor binding sites and experimental evidence; (iii) data accuracy is ensured by hand curation; (iv) efficient user interface for easy and flexible data retrieval; and (v) implementation of on-the-fly sequence analysis tools. TRED can provide good training datasets for further genome-wide cis-regulatory element prediction and annotation, assist detailed functional studies and facilitate the decipher of gene regulatory networks (http://rulai.cshl.edu/TRED).