Description
This collection of tracks offers an integrated view of genomic annotations and experimental
data from all phases of the
ENCODE Project,
with a focus on transcriptional regulation. It includes averaged and representative signals
from assays that measure chromatin accessibility (DNase-seq and ATAC-seq), transcription
factor (TF) binding (ChIP-seq for individual TFs), histone modifications (ChIP-seq for
H3K4me3 and H3K27ac), CTCF binding, and transcription (RNA-seq).
Tracks labeled (Layered) show organ-averaged signals as a transparent
overlay of multiple organs within a single track. Tracks labeled (Indiv.)
show signals from individual experiments in specific biosamples.
- The H3K27ac (Layered) track displays enrichment levels of a histone modification associated with
active enhancers and promoters, averaged across 19 organs.
- The DNase (Layered) track displays regions of chromatin that are hypersensitive
to DNase I digestion, indicating open and potentially regulatory chromatin. Signal is averaged
across biosamples from the same organ for 26 organs.
- The ATAC (Layered) track displays regions of open chromatin identified by
ATAC-seq, which uses Tn5 transposase insertion to assay accessibility. Signal is averaged
across 12 organs.
- The H3K4me3 (Layered) track displays enrichment levels of a histone modification associated with
active or poised promoters, averaged across 20 organs.
- The CTCF (Layered) track displays genomic regions bound by CTCF, a multifunctional DNA-binding protein involved in chromatin organization and gene regulation. Signal
is averaged across 16 organs.
- The Transcription (Layered) track displays transcription levels measured by
strand-specific total RNA-seq across a large number of biosamples, shown separately for
the two genomic strands.
- The TF ChIP-seq (Indiv.), DNase/ATAC/Histone/CTCF (Indiv.), and
RNA-seq (Indiv.) tracks display signals from individual experiments in specific
biosamples.
These tracks complement one another and collectively provide a resource for
interpreting regulatory DNA. Histone marks are broadly informative but have limited resolution
(~200 bp) and relatively low functional specificity. DNase-seq assays offer higher resolution
and scalability across many cell types, and they reliably indicate regulatory potential, though
they lack detailed functional context. ATAC-seq serves a similar role to DNase-seq, with
comparable resolution and limitations. Transcription factor ChIP-seq has high positional
resolution and, due to the specificity of TFs, often provides more direct functional insight.
However, because each TF must be assayed individually, the data are limited in biosample
coverage. Despite the individual strengths and limitations of these assays, their independence
from one another increases confidence when multiple assays suggest a regulatory function for
the same genomic region.
For additional information, click on the hyperlinks for the individual tracks above.
Additional histone marks and transcription data are available in other ENCODE tracks. This
integrative supertrack presents a curated selection of the most informative and broadly
relevant datasets. Further functional annotations of individual regulatory elements are
available at SCREEN.
For annotations of individual regulatory elements, see the related
ENCODE cCREs track.
Display Conventions
By default, the DNase (Layered), ATAC (Layered),
H3K4me3 (Layered), H3K27ac (Layered), CTCF (Layered), and
Transcription (Layered) tracks use a transparent overlay to visualize signals from
multiple organs or tissues within a single track. For each organ or tissue, signal values from
all associated experiments are averaged. Each organ or tissue is assigned a distinct color,
selected to be light and saturated to maintain clarity when overlaid. Initially, each layered
track displays an overlay of representative organs: blood, brain, kidney, liver, and
muscle (the H3K27ac and ATAC tracks have no muscle data). Clicking on the track opens a details page where you can view and select organs or
tissues.
The TF ChIP-seq (Indiv.), DNase/ATAC/Histone/CTCF (Indiv.), and
RNA-seq (Indiv.) tracks are hidden by default. Clicking on any of these tracks opens
a details page where you can select specific biosample-level experiments to display.
Data Access
The ENCODE 4 Regulation data on the UCSC Genome Browser can be explored interactively with the
Table Browser or the
Data Integrator.
For automated download and analysis, the track data files can be downloaded from
our download server or queried using the
REST API.
Individual regions or the whole genome annotation can be accessed as text using
our utilities bigWigToWig and bigBedToBed. Instructions for
downloading source code and binaries can be found
here.
The original data files are also available from the
ENCODE portal.
Credits
Data were generated by the ENCODE Consortium. The data were further processed for visualization
through a collaborative effort between the
Weng lab and the
Moore lab
at UMass Chan Medical School (funded by NIH grant HG012343). Integration and visualization
were developed by Drs. Mingshi Gao, Jill Moore, and Zhiping Weng at UMass Chan
Medical School, who were part of the ENCODE Data Analysis Center.
Data Use Policy
Users may freely download, analyze, and publish results based on any ENCODE data without
restrictions.
Researchers using unpublished ENCODE data are encouraged to contact the data producers to
discuss possible coordinated publications; however, this is optional.
Users of ENCODE datasets are requested to cite the ENCODE Consortium and ENCODE
production laboratory(s) that generated the datasets used, as described in
Citing
ENCODE.
References
ENCODE Project Consortium, Moore JE, Purcaro MJ, Pratt HE, Epstein CB, Shoresh N, Adrian J,
Kawli T, Davis CA, Dobin A et al.
Expanded encyclopaedias of DNA elements in the human and mouse genomes.
Nature. 2020 Jul;583(7818):699-710.
PMID: 32728249; PMC: PMC7410828
Moore JE, Pratt HE, Fan K, Phalke N, Fisher J, Elhajjajy SI, Andrews G, Gao M, Shedd N,
Fu Y et al.
An Expanded Registry of Candidate cis-Regulatory Elements for Studying Transcriptional
Regulation.
Nature. 2026 January 7.
PMID: 39763870; PMC: PMC11703161