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| Status |
Public on Nov 06, 2015 |
| Title |
gDNA_CD8_H3K27ac_Control_rep7 |
| Sample type |
SRA |
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| Source name |
Genomic DNA, CD8 cells, H3K27ac ChIP, healthy control
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| Organism |
Homo sapiens |
| Characteristics |
tissue: blood
diagnosis: Healthy control
cell type: CD8 T cells
gender: Female
age: 54
antibody: H3K27ac
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
Peripheral blood mononuclear cells were extracted using Ficoll-Paque (GE Healthcare) gradient centrifugation. CD8+ T-cells and CD4+ T cells were purified by consecutive positive separation using microbeads (CD4+ #130-045-101; CD8+ #130-045-201) and AutoMACS technology (Miltenyi Biotec) according to the manufacturer's protocol. The purified cells were fixed in 1% formaldehyde and stored as cell pellets in a -80°C freezer. ChIP assays were performed using Auto Histone ChIP-seq kit (Diagenode) with minor modifications. Briefly, IP-Buffer (2 mM EDTA, 150 mM NaCl, 20 mM Tris-HCl, 1% Triton X-100) was used in exchange for kit Buffer H in IP reactions. DNA from 4-6 x 106 cells was fragmented with the Bioruptor sonicator (Diagenode) to fragments of 200-400 basepairs. Sheared chromatin from 1 million cells was immunoprecipitated with 2 μg of anti-H3K4me3 antibody (Millipore 07-473) or 2 μg of anti-H3K27Ac antibody (Abcam Ab4729) using the SX-8G IP-Star Automated System (Diagenode). ChIP-DNA was purified with MinElute PCR Purification Kit (Qiagen).
The purified ChIP and input DNAs were quantified by Qubit 2.0 Fluorometer (Life Technologies) prior to library preparation with the Ovation® Ultralow DR Multiplex System 1-96 kit (NuGeneration Limited) according to manufacturer’s instructions. The barcoded libraries were quantified by Qubit 2.0 Fluorometer and validated with Agilent 2200 TapeStation analysis (Agilent Technologies, Inc.). The ChIP-seq libraries were sequenced with HiSeq 2500 (Illumina) producing 50 bp paired-end reads. Phage PhiX sequencing library was included as 1% spike-in in the sequencing runs.
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| Library strategy |
ChIP-Seq |
| Library source |
genomic |
| Library selection |
ChIP |
| Instrument model |
Illumina HiSeq 2500 |
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| Data processing |
Read trimming and quality control. Raw reads were trimmed with Trim Galore! version 0.3.3 (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) using the paired-end mode and the Phred score threshold set to 30. The quality control with FastQC version 0.10.0 was performed before and after trimming.
Alignment. The trimmed paired-end reads were aligned to the human reference genome (hg19) with bowtie2 version 2.0.2 allowing clipping of read ends with the option --local.
Filtering of aligned reads. The SAMtools software suite (http://www.htslib.org/) was used to retain only properly paired alignments with mapping quality ≥ 30 and the duplicated reads were removed with MarkDuplicates from the Picard tools (http://broadinstitute.github.io/picard/).
Peak calling. Peaks were called with MACS2 (https://github.com/taoliu/MACS/). Both cell types (CD4+ and CD8+ T cells) and ChIP experiments (H3K4me3 and H3K27ac) have two input sample BAM files that were merged into single BAM files, which were used as controls in peak calling. The mappable genome size (-g 2627947484) for 50 bp reads was taken from [1]. Only the peaks with q-value <0.01 were considered to be significant. Peaks were filtered against the blacklisted regions given in wgEncodeDacMapabilityConsensusExcludable.bed.gz (available on the series record). 1. Derrien T, Estellé J, Marco Sola S, Knowles DG, Raineri E, Guigó R et al. Fast computation and applications of genome mappability. PLoS One, 2012;7:e30377.
Differential enrichment analysis. The analysis of differentially enriched peaks was performed with the R/Bioconductor package “DiffBind” [1]. Samples were read in in batch and then split by cell type and histone modification. The statistical methods for assessing the difference of the peak signals in GD and control samples were provided by the R/Bioconductor package “edgeR” [2]. Before the statistical test, the counts in the input sample were subtracted from counts in the ChIPed samples and the resulting library sizes were used for normalization. Peaks with a fold change difference of 1.5 and with the FDR adjusted p-value < 0.01 were considered for further analysis. 1. Ross-Innes CS, Stark R, Teschendorff AE, Holmes KA, Ali HR, Dunning MJ et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature, 2012;481:389-93. 2. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 2010;26:139-40.
Genome_build: hg19
Supplementary_files_format_and_content: The peak lists are in ENCODE narrowPeak format that is described on the UCSC Genome Browser help pages: http://genome-euro.ucsc.edu/FAQ/FAQformat.html
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| Submission date |
Aug 11, 2015 |
| Last update date |
May 15, 2019 |
| Contact name |
Pärt Peterson |
| E-mail(s) |
part.peterson@ut.ee
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| Phone |
+3727374202
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| Organization name |
University of Tartu
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| Department |
Department of Biomedicine
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| Lab |
Molecular Pathology Research Group
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| Street address |
Ravila 19
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| City |
Tartu |
| ZIP/Postal code |
50411 |
| Country |
Estonia |
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| Platform ID |
GPL16791 |
| Series (2) |
| GSE71952 |
Epigenetic profiling in CD4 and CD8 T cells from Graves’ disease patients reveals changes in genes associated with T cell receptor signaling [ChIP-seq] |
| GSE71957 |
Epigenetic profiling in CD4 and CD8 T cells from Graves disease patients reveals changes in genes associated with T cell receptor signaling |
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| Relations |
| BioSample |
SAMN03981541 |
| SRA |
SRX1142217 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM1847891_Sample25_CD8_H3K27ac.narrowPeak.gz |
497.7 Kb |
(ftp)(http) |
NARROWPEAK |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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