Unknown,Transcriptomics,Genomics,Proteomics

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High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells (Dnase-seq)

ABSTRACT: Using DNaseI hypersensitivity (HS) assays (Dnase-seq), high resolution DNaseI digestion profiles were generated genome-wide in diverse human cell types. We showed that within general regions of DNaseI HS that are known to identify locations of gene regulatory elements, DNaseI digestion patterns allowed us to identify locations of individual transcription factor binding sites that protected against the bound DNA against digestion. To measure the accuracy of these footprints, we also generated ChIP-seq data for the CTCF DNA binding factor in the same cell growths. We found that DNaseI footprints containing the CTCF canonical binding motif show significant ChIP-seq signal while CTCF binding motifs not in footprints show almost no signal providing one measure of valdation of the DNaseI footprints. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Six cell lines representing cervica carcinoma, chronic myeloid leukemia, human embryonic stem cells, lymphoblastoid cells, human epidermal keratinocytes and umbilical vein endothelial cells were analyzed using Dnase-seq.

ORGANISM(S): Homo sapiens

SUBMITTER: Terry Furey

PROVIDER: E-GEOD-25344 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells.

Boyle Alan P AP Song Lingyun L Lee Bum-Kyu BK London Darin D Keefe Damian D Birney Ewan E Iyer Vishwanath R VR Crawford Gregory E GE Furey Terrence S TS

Genome research 20101124 3

Regulation of gene transcription in diverse cell types is determined largely by varied sets of cis-elements where transcription factors bind. Here we demonstrate that data from a single high-throughput DNase I hypersensitivity assay can delineate hundreds of thousands of base-pair resolution in vivo footprints in human cells that precisely mark individual transcription factor-DNA interactions. These annotations provide a unique resource for the investigation of cis-regulatory elements. We find t ...[more]

PMID: 21106903

Publication: 1/2

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Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Yijun Ruan mailto:ruanyj@gis.a-star.edu.sg). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). 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 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. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf 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 GRCh37/hg19 human genome using Bowtie 0.12.5 (Eland was used to map to NCBI36/hg18); 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 1.0% (FDR 0.01) 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 1.0% (FDR 0.01) 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.

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). 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 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. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf 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 GRCh37/hg19 human genome using Bowtie 0.12.5 (Eland was used to map to NCBI36/hg18); 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 1.0% (FDR 0.01) 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 1.0% (FDR 0.01) 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.

Dataset Information

High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells (Dnase-seq)

Publications

High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells.

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