Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites.

The human genome contains ∼2000 transcriptional regulatory proteins, including ∼1600 DNA-binding transcription factors (TFs) recognizing characteristic sequence motifs to exert regulatory effects on gene expression. The binding specificities of these factors have been profiled both in vitro, using techniques such as HT-SELEX, and in vivo, using techniques including ChIP-seq. We previously developed Factorbook, a TF-centric database of annotations, motifs, and integrative analyses based on ChIP-seq data from Phase II of the ENCODE Project.

Annotation of chromatin states in 66 complete mouse epigenomes during development.

The morphologically and functionally distinct cell types of a multicellular organism are maintained by their unique epigenomes and gene expression programs. Phase III of the ENCODE Project profiled 66 mouse epigenomes across twelve tissues at daily intervals from embryonic day 11.5 to birth.

Expanded encyclopaedias of DNA elements in the human and mouse genomes.

The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development.

A curated benchmark of enhancer-gene interactions for evaluating enhancer-target gene prediction methods.

Background: Many genome-wide collections of candidate cis-regulatory elements (cCREs) have been defined using genomic and epigenomic data, but it remains a major challenge to connect these elements to their target genes.

Results: To facilitate the development of computational methods for predicting target genes, we develop a Benchmark of candidate Enhancer-Gene Interactions (BENGI) by integrating the recently developed Registry of cCREs with experimentally derived genomic interactions. We use BENGI to test several published computational methods for linking enhancers with genes, including signal correlation and the TargetFinder and PEP supervised learning methods.