Enhancers and silencers are non-coding DNA sequences that regulate the activity of nearby genes. Enhancers increase gene expression by recruiting transcriptional activators, while silencers reduce expression by recruiting repressors. Both types of elements are typically cell-type specific and play central roles in establishing the gene expression programs that define different tissues and developmental states. Genetic variants within these elements can disrupt normal gene regulation and contribute to human disease.
This track collection displays candidate enhancers and silencers predicted by TREDNet, a two-phase deep learning model trained on chromatin accessibility (DNase-seq) and histone modification (H3K27ac and H3K27me3 ChIP-seq) data from 97 ENCODE biosamples spanning a wide range of cell types, cell lines, and tissues. Each region is colored by the type of sample in which it is predominantly active.
See the individual subtrack pages for details on the enhancer and silencer predictions:
Each item represents a merged genomic window where one or more of the 97 biosamples were predicted to harbor a candidate regulatory element. Items are colored by the dominant sample category contributing to that region:
Tissue – region active predominantly in primary tissue samples (Uberon ontology)
Cell type – region active predominantly in primary cell type samples (Cell Ontology)
Cell line – region active predominantly in cell line samples (EFO ontology)
Mixed – region active across multiple sample categories without a dominant type
Mousing over a region shows the names of all contributing samples (up to 10), or a count summary when more than 10 samples share the region. The full comma-separated sample list is always available in the item detail view.
Data for this track collection can be explored interactively in table format with the Table Browser or the Data Integrator. See the individual subtrack pages for download instructions and links to the source data.
Huang D, Ovcharenko I. The contribution of silencer variants to human diseases. Genome Biol. 2024 Jul 8;25(1):184. PMID: 38978133; PMC: PMC11232194