UW DNase DGF Track Settings
 
ENCODE Univ. Washington Digital DNase Genomic Footprinting   (All Regulation tracks)

Maximum display mode:       Reset to defaults   
Select views (Help):
Hotspots ▾       Peaks ▾       Signal ▾       Raw Signal ▾      
Select subtracks by cell line:
  Cell Line GM06990  HepG2  K562  SK-N-SH RA  Th1 
List subtracks: only selected/visible    all    ()
  Cell Line↓1 views↓2   Track Name↓3    Restricted Until↓4
 
hide
 Configure
 GM06990  Hotspots  ENCODE UW Digital Genomic Footprinting - Hotspots (in GM06990 cells)    Schema   2010-10-14 
 
hide
 Configure
 GM06990  Peaks  ENCODE UW Digital Genomic Footprinting - Peaks (FDR 0.5%) (in GM06990 cells)    Schema   2010-10-14 
 
hide
 Configure
 GM06990  Raw Signal  ENCODE UW Digital Genomic Footprinting - Raw Signal (in GM06990 cells)    Schema   2010-10-14 
 
hide
 Configure
 GM06990  Signal  ENCODE UW Digital Genomic Footprinting - Per-base Signal (in GM06990 cells)    Schema   2010-10-14 
 
hide
 Configure
 HepG2  Hotspots  ENCODE UW Digital Genomic Footprinting - Hotspots (in HepG2 cells)    Schema   2010-07-02 
 
hide
 Configure
 HepG2  Peaks  ENCODE UW Digital Genomic Footprinting - Peaks (FDR 0.5%) (in HepG2 cells)    Schema   2010-07-02 
 
hide
 Configure
 HepG2  Raw Signal  ENCODE UW Digital Genomic Footprinting - Raw Signal (in HepG2 cells)    Schema   2010-07-02 
 
hide
 Configure
 HepG2  Signal  ENCODE UW Digital Genomic Footprinting - Per-base Signal (in HepG2 cells)    Schema   2010-07-02 
 
hide
 Configure
 K562  Hotspots  ENCODE UW Digital Genomic Footprinting - Hotspots (in K562 cells)    Schema   2010-10-13 
 
hide
 Configure
 K562  Peaks  ENCODE UW Digital Genomic Footprinting - Peaks (FDR 0.5%) (in K562 cells)    Schema   2010-10-13 
 
hide
 Configure
 K562  Raw Signal  ENCODE UW Digital Genomic Footprinting - Raw Signal (in K562 cells)    Schema   2010-10-13 
 
hide
 Configure
 K562  Signal  ENCODE UW Digital Genomic Footprinting - Per-base Signal (in K562 cells)    Schema   2010-10-13 
 
hide
 Configure
 SK-N-SH RA  Hotspots  ENCODE UW Digital Genomic Footprinting - Hotspots (in SK-N-SH_RA cells)    Schema   2010-07-02 
 
hide
 Configure
 SK-N-SH RA  Peaks  ENCODE UW Digital Genomic Footprinting - Peaks (FDR 0.5%) (in SK-N-SH_RA cells)    Schema   2010-07-02 
 
hide
 Configure
 SK-N-SH RA  Raw Signal  ENCODE UW Digital Genomic Footprinting - Raw Signal (in SK-N-SH_RA cells)    Schema   2010-07-02 
 
hide
 Configure
 SK-N-SH RA  Signal  ENCODE UW Digital Genomic Footprinting - Per-base Signal (SK-N-SH_RA cells)    Schema   2010-07-02 
 
hide
 Configure
 Th1  Hotspots  ENCODE UW Digital Genomic Footprinting - Hotspots (in Th1 cells)    Schema   2010-07-05 
 
hide
 Configure
 Th1  Peaks  ENCODE UW Digital Genomic Footprinting - Peaks (FDR 0.5%) (in Th1 cells)    Schema   2010-07-05 
 
hide
 Configure
 Th1  Raw Signal  ENCODE UW Digital Genomic Footprinting - Raw Signal (in Th1 cells)    Schema   2010-07-05 
 
hide
 Configure
 Th1  Signal  ENCODE UW Digital Genomic Footprinting - Per-base Signal (in Th1 cells)    Schema   2010-07-05 
     Restriction Policy
Downloads

Description

This track, produced as part of the ENCODE Project, contains deep sequencing DNase data that will be used to identify sites where regulatory factors bind to the genome (footprints).

Footprinting is a technique used to define the DNA sequences that interact with and bind specific DNA-binding proteins, such as transcription factors, zinc-finger proteins, hormone-receptor complexes, and other chromatin-modulating factors like CTCF. The technique depends upon the strength and tight nature of protein-DNA interactions. In their native chromatin state, DNA sequences that interact directly with DNA-binding proteins are relatively protected from DNA degrading endonucleases, while the exposed/unbound portions are readily degraded by such endonucleases. A massively parallel next-generation sequencing technique to define the DNase hypersensitive sites in the genome was adopted. Sequencing these next-generation-sequencing DNase samples to significantly higher depths of 300-fold or greater produces a base-pair level resolution of the DNase susceptibility maps of the native chromatin state. These base-pair resolution maps represent and are dependent upon the nature and the specificity of interaction of the DNA with the regulatory/modulatory proteins binding at specific loci in the genome; thus they represent the native chromatin state of the genome under investigation. The deep sequencing approach has been used to define the footprint landscape of the genome by identifying DNA motifs that interact with known or novel DNA binding proteins.

Display Conventions and Configuration

This track is a multi-view composite track that contains multiple data types (views). For each view, there are multiple subtracks that display individually on the browser. Instructions for configuring multi-view tracks are here.

For each cell type, this track contains the following views:

HotSpots
DNaseI hypersensitive zones identified using the HotSpot algorithm.
Peaks
DNaseI hypersensitive sites (DHSs) identified as signal peaks within FDR 0.5% hypersensitive zones.
Signal
The density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome).
Raw Signal
Density graph (wiggle) of signal enrichment based on aligned read density.

DNaseI sensitivity is shown as the absolute density of in vivo cleavage sites across the genome mapped using the Digital DNaseI methodology (see below). Data have been normalized to 25 million reads per cell type.

Methods

Cells were grown according to the approved ENCODE cell culture protocols. Digital DNaseI was performed by DNaseI digestion of intact nuclei, followed by isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (27 bp reads). High-quality reads were mapped to the genome; only unique mappings were kept. DNaseI sensitivity is directly reflected in raw tag density (Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI hypersensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). False discovery rate thresholds of 0.5% (FDR 0.005) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36-mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within 0.5% (FDR 0.005) hypersensitive zones using a peak-finding algorithm. Only DNase Solexa libraries from unique cell types producing the highest quality data, as defined by Percent Tags in Hotspots (PTIH ~40%) were designated for deep sequencing to a depth of over 200 million tags.

Verification

Results were validated by conventional DNaseI hypersensitivity assays using end-labeling/Southern blotting methods.

Release Notes

This is the initial release of this track.

Credits

These data were generated by the UW ENCODE group.

Contact: Richard Sandstrom

References

Sabo PJ, Kuehn MS, Thurman R, Johnson BE, Johnson EM, Cao H, Yu M, Rosenzweig E, Goldy J, Haydock A et al. Genome-scale mapping of DNase I sensitivity in vivo using tiling DNA microarrays Nat Methods. 2006 Jul;3(7):511-8.

Sabo PJ, Hawrylycz M, Wallace JC, Humbert R, Yu M, Shafer A, Kawamoto J, Hall R, Mack J, Dorschner M et al. Discovery of functional noncoding elements by digital analysis of chromatin structure. Proc Natl Acad Sci U S A. 2004 Nov 30;101(48):16837-42.

Data Release Policy

Data users may freely use ENCODE data, but may not, without prior consent, submit publications that use an unpublished ENCODE dataset until nine months following the release of the dataset. This date is listed in the Restricted Until column, above. The full data release policy for ENCODE is available here.