Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

ChIP profiling by array of histone modifications in normal human islets

ABSTRACT: This experiment used ChIP-seq technology to create a genome-wide profile of histone marks in normal human pancreatic islets. In the current work we analyzed two histone marks associated with gene expression (H3K4me3, H3K4me1) and marks associated with gene repression(H3K27me3). Each mark was anayzed using samples obtained from four donors (n=4). Chromatin Immunoprecipitations (ChIPs) for histone marks were performed using specific anti-histone antibodies. Enrichment of each sample was calulated with respect to its individual input using qPCR. Samples were sequenced with Solexa and sequenced DNA from both Input (n=4) and ChIP (n = 4) samples were aligned to the NCBI Genome Build 36.1 Ð Hg18 to determine regions that were enriched for binding by modified histones. Chromatin modifications were related to gene expression levels.

ORGANISM(S): Homo sapiens

SUBMITTER: John Le Lay

PROVIDER: E-MTAB-191 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Genome-wide analysis of histone modifications in human pancreatic islets.

Bhandare Reena R Schug Jonathan J Le Lay John J Fox Alan A Smirnova Olga O Liu Chengyang C Naji Ali A Kaestner Klaus H KH

Genome research 20100224 4

The global diabetes epidemic poses a major challenge. Epigenetic events contribute to the etiology of diabetes; however, the lack of epigenomic analysis has limited the elucidation of the mechanistic basis for this link. To determine the epigenetic architecture of human pancreatic islets we mapped the genome-wide locations of four histone marks: three associated with gene activation-H3K4me1, H3K4me2, and H3K4me3-and one associated with gene repression, H3K27me3. Interestingly, the promoters of t ...[more]

PMID: 20181961

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Project description:This track displays a chromatin state segmentation for each of nine human cell types (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=GM12878,H1-hESC,HepG2,HUVEC,HMEC,HSMM,K562,NHEK,NHLF). A common set of states across the cell types were learned by computationally integrating ChIP-seq data for nine factors plus input (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=CTCF,H3K4me1,H3K4me2,H3K4me3,H3K27ac,H3K9ac,H3K36me3,H4K20me1,H3K27me3,Input) using a Hidden Markov Model (HMM). In total, fifteen states were used to segment the genome, and these states were then grouped and colored to highlight predicted functional elements. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf ChIP-seq data from the Broad Histone (http://hgwdev.cse.ucsc.edu/cgi-bin/hgTrackUi?db=hg18&g=wgEncodeBroadChipSeq) track was used to generate this track. Data for nine factors plus input (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=CTCF,H3K4me1,H3K4me2,H3K4me3,H3K27ac,H3K9ac,H3K36me3,H4K20me1,H3K27me3,Input) and nine cell types (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=GM12878,H1-hESC,HepG2,HUVEC,HMEC,HSMM,K562,NHEK,NHLF) was binarized separately at a 200 base pair resolution based on a Poisson background model. The chromatin states were learned from this binarized data using a multivariate Hidden Markov Model (HMM) that explicitly models the combinatorial patterns of observed modifications (Ernst and Kellis, 2010). To learn a common set of states across the nine cell types, first the genomes were concatenated across the cell types. For each of the nine cell types, each 200 base pair interval was then assigned to its most likely state under the model. Detailed information about the model parameters and state enrichments can be found in (Ernst et al, accepted). This is release 1 (Jun 2011) of this track, and it is based on the NCBI36/hg18 release of the Broad Histone (http://hgwdev.cse.ucsc.edu/cgi-bin/hgTrackUi?db=hg18&g=wgEncodeBroadChipSeq) track. This track has also been lifted over to GRCh37/hg19 (http://hgwdev.cse.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=wgEncodeBroadHmm). It is anticipated that the HMM methods will be run on the newer GRCh37/hg19 Broad Histone (http://hgwdev.cse.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=wgEncodeBroadHistone) data and will replace the lifted version.

Dataset Information

ChIP profiling by array of histone modifications in normal human islets

Publications

Genome-wide analysis of histone modifications in human pancreatic islets.

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