ENCODE Regulation TF rPeak Clusters Track Settings

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Transcription Factor Representative Peak (rPeak) Clusters (912 factors in 1152 biosamples) from ENCODE 4

Track collection: Integrated Regulation from ENCODE

Description

These tracks contain information relevant to the regulation of transcription from the ENCODE Project.

The TF rPeak Clusters track shows genomic regions bound by DNA-associated proteins involved in transcriptional regulation from ENCODE 4.
The Transcription track shows transcription levels assayed by sequencing of polyadenylated RNA from a variety of cell types.
The Layered H3K4Me1 and Layered H3K27Ac tracks show where modification of histone proteins is suggestive of enhancer and, to a lesser extent, other regulatory activity. These histone modifications, particularly H3K4Me1, are quite broad. The actual enhancers are typically just a small portion of the area marked by these histone modifications.
The Layered H3K4Me3 track shows a histone mark associated with promoters.
The DNase I Hypersensitivity tracks indicate where chromatin is hypersensitive to cutting by the DNase enzyme, which has been assayed in a large number of cell types. Regulatory regions, in general, tend to be DNase-sensitive, and promoters are particularly DNase-sensitive.
The Txn Factor ChIP tracks show DNA regions where transcription factors, proteins responsible for modulating gene transcription, bind as assayed by chromatin immunoprecipitation with antibodies specific to the transcription factor followed by sequencing of the precipitated DNA (ChIP-seq).

These tracks complement each other and together can shed much light on regulatory DNA. The histone marks are informative at a high level, but they have a resolution of just ~200 bases and do not provide much in the way of functional detail. The DNase hypersensitivity assay is higher in resolution at the DNA level and can be done on a large number of cell types since it's just a single assay. At the functional level, DNase hypersensitivity suggests that a region is very likely to be regulatory in nature, but provides little information beyond that. The transcription factor ChIP assay has a high resolution at the DNA level and, due to the very specific nature of the transcription factors, is often informative with respect to functional detail. However, since each transcription factor must be assayed separately, the information is only available for a limited number of transcription factors on a limited number of cell lines. Though each assay has its strengths and weaknesses, the fact that all of these assays are relatively independent of each other gives increased confidence when multiple tracks are suggesting a regulatory function for a region.

For additional information, please click on the hyperlinks for the individual tracks above. Also note that additional histone marks and transcription information is available in other ENCODE tracks. This integrative supertrack just shows a selection of the most informative data of most general interest.

To view the full description, click here.

All tracks in this collection (10)

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Filter by Name of transcription factor (select multiple items - help)

Match if all one or more match

Shade of lowest-scoring items: Label: Name of transcription factor

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Data last updated at UCSC: 2024-07-23 11:17:48

Description

This track displays regulatory regions in the human genome identified using ENCODE data, specifically spanning ENCODE phases 2 through 4. It highlights genomic regions bound by DNA-associated proteins involved in transcriptional regulation, such as RNA polymerase, transcription factors (TFs), and chromatin remodeling proteins. Sequence-specific TFs bind directly to short DNA motifs via their DNA-binding domains, while other DNA-associated proteins interact with DNA indirectly through protein-protein interactions with sequence-specific TFs. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a high-throughput method for mapping genome-wide protein-DNA interactions. Regions of high ChIP signal, commonly referred to as ChIP-seq peaks, indicate protein binding sites. For each DNA -associated protein, all ENCODE ChIP-seq peaks across biosamples were integrated to generate a set of representative peaks (rPeaks). This track displays these rPeaks alongside detected DNA motif sites.

Display Conventions and Configuration

Each rPeak is represented as a gray box, with the shade of gray corresponding to the maximum ChIP-seq signal observed across contributing biosamples. The HGNC gene name of the associated protein is displayed to the left of the box. If the rPeak overlaps a cognate TF motif site in the collection built previously (PMID: 37104580 DOI: 10.1126/science.abn7930), the motif site is highlighted in green.

Clicking on an rPeak provides detailed information about the biosamples where the rPeak was detected, including the count of biosamples with contributing ChIP-seq peaks and the total number of biosamples assayed for the protein. Links to relevant ENCODE ChIP-seq experiments and overlapping ENCODE candidate cis-regulatory elements (cCREs) are also provided.

By default, rPeaks for all 912 DNA-associated proteins with ENCODE ChIP-seq data are displayed. Users can customize the display by selecting specific DNA-associated proteins in the track settings.

Methods

2,509 ENCODE ChIP-seq experiments were integrated from 912 DNA-associated proteins across 1,152 unique biosamples to produce representative peaks (rPeaks) for each protein. The processing steps were as follows:

ChIP-seq peaks for each protein were downloaded from the ENCODE Portal, generated using the ENCODE Transcription Factor ChIP-seq Processing Pipeline.
Using bedtools merge, ChIP-seq peaks were clustered from the protein’s experiments across all biosamples.
In each cluster, the peak with the highest ChIP signal (normalized by sequencing depth) was selected as the rPeak.
All ChIP-seq peaks overlapping this rPeak by at least one nucleotide were marked as represented and removed from subsequent clustering rounds.
Steps 2-4 were repeated until a final list of non-overlapping rPeaks was generated, representing all ChIP-seq peaks for the protein.

Data Access

The raw data for the ENCODE TF rPeak track will soon be available.

The raw data can be explored interactively with the Table Browser, for download, intersection or correlations with other tracks. To join this track with others based on the chromosome positions, use the Data Integrator.

Regarding access to this data track in the Genome Browser, for automated download and analysis, the genome annotation is stored in a bigBed file that can be downloaded from our download server. The file for this track is called TFrPeakClusters.bb. Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain only features within a given range, e.g. bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/ENCODE4/TFrPeakClusters.bb -chrom=chr21 -start=0 -end=100000000 stdout

For automated access, this track like all others, is also available via our API. However, for bulk processing in pipelines, downloading the data and/or using bigBed files as described above is usually faster.

Credits

This track was made possible thanks to the efforts of the ENCODE Consortium, ENCODE ChIP-seq production laboratories, and the ENCODE Data Coordination Center for generating and processing the ChIP-seq datasets. The ENCODE accession numbers for the constituent datasets are accessible from the peak details page. Special thanks to Drs. Mingshi Gao, Greg Andrews, Jill Moore, and Zhiping Weng at UMass Chan Medical School, who were members of the ENCODE Data Analysis Center, for developing this track, including providing the rPeak and motif datasets and associated metadata and building the track. We also extend our gratitude to Max Haeussler and Jonathan Casper from the UCSC Genome Browser Project Team for their assistance in developing this track. For updates on the track, please contact the Weng lab.