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| Status |
Public on Nov 08, 2012 |
| Title |
ChiP-Seq REST APL blast |
| Sample type |
SRA |
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| Source name |
APL bone marrow blasts
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| Organism |
Homo sapiens |
| Characteristics |
disease state: Primary diagnosis
Sex: m
age: 45
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
ChIP-seq: Cells were fixed for 10 min in culture media containing 1% formaldehyde and were processed for ChIP as previously described (Dietrich et al, PLOS Genetics 2012). Briefly, formaldehyde fixed chromatin was sonicated in IP buffer (IP buffer =2 volume SDS Buffer : 1 volume Triton Dilution Buffer; SDS Buffer- 100mM NaCl 50mM Tris-Cl, pH8.1, 5mM EDTA, pH 8.0, 0.2% NaN3, 2% SDS; Triton Dilution Buffer- 100mM Tris-Cl, pH 8.6, 100mM NaCl, 5mM EDTA, pH 8.0, 0.2% NaN3, 5.0% Triton X-100) using Branson Sonifier (4 cycles of 30 sec each at 20% amplitude). 15ug DNA (sonicated chromatin) was used for each ChIP in IP buffer. Antibodies used: Rabbit IgG (DAKO), rabbit anti-REST (Millipore, 07-579), anti-SUZ12 (Rabbit monoclonal, Cell signaling). Samples were incubated with antibodies overnight at 40C and immunocomplexes were precipitated with protein A-sepharose beads with 3 hr rotation at 40C. After subsequent washes the samples were decrosslinked overnight at 650C (shaking) in 1%SDS, 0.1M NaHCO3. Finally, ChIP DNA was purified using Qiagen PCR purification kit. The ChIPs were validated at REST and Polycomb target genes by qPCR. ChIP DNA from three parallel ChIPs were pooled and 10 ng was used for making ChIP-seq libraries. The libraries were prepared using “ChIP seq DNA sample preparation kit” from Illumina following manufacturer’s instructions. Individual samples were run in a single lane on HiSeq2000 (Illumina). Basecalls were performed using on-instrument real time analysis (RTA). Mapping was performed with bowtie allowing for <=2 mismatches and only including reads that were mapped to a single position to hg18. The number of reads in 100 bp sections of the genome were counted genome-wide. A normal distribution was fitted to the counts, and the distribution with the least root-mean-square deviation was used as model for the background in the datasets. Thresholds were set so that windows that scored positive had p-values < 0.001 compared to the background distribution. A ChIP-sequenced IgG-control was used as a negative control and handled in the same way. Only windows scoring positive for REST or Suz12, but not IgG, were included for downstream analysis. Also windows where the positive signal (normalized to dataset size) did not exceed the negative signal (normalized to dataset size) at least threefold were omitted from downstream analysis. Datasets were analyzed this way four times in 25 bp shifts, thereby reducing the number of regions that scored negative due to a division of the reads into neighboring sections. Overlapping positive windows and positive windows within 100bp for REST and 500bp for Suz12 of each other were merged. The position of the border was refined by shifting the window in one bp steps until the window scored positive (without scoring positive in the negative control sample) starting at a distance of one window-size from the regions border. Genomic positions were transferred to hg19 using the UCSC liftover tool (http://genome.ucsc.edu/cgi-bin/hgLiftOver).
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| Library strategy |
ChIP-Seq |
| Library source |
genomic |
| Library selection |
ChIP |
| Instrument model |
Illumina HiSeq 2000 |
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| Data processing |
Basecalls were performed using on-instrument real time analysis (RTA) on an Illumina HiScan-SQ
Off-Line Basecaller (OLB) was used for bcl to qseq conversion
Illumina paired-end adapter sequences were removed using Cutadapt version 0.9.3
Reads were mapped using Bismark version 0.5
Methylation calls from Bismark were extracted with a modified methylation_extractor script which removed 3’-MspI-sites
The extracted methylation data was further analyzed in R/Bioconductor with the BiSeq package
Genome_build: hg19 for human samples and mm9 for mouse samples
Supplementary_files_format_and_content: Extracted CpG methylation call files were generated using R/Bioconductor with help of the BiSeq package. Each processed file contains a column for chromosome, position and extracted methylation data for the respective sample. For each CpG position observed the number of methylated / unmethylated reads is listed.
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| Submission date |
Nov 05, 2012 |
| Last update date |
May 15, 2019 |
| Contact name |
Christian Rohde |
| E-mail(s) |
christian.rohde@uni-heidelberg.de
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| Organization name |
Heidelberg University
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| Lab |
Molecular Hematology and Oncology
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| Street address |
Im Neuenheimer Feld 410
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| City |
Heidelberg |
| ZIP/Postal code |
69120 |
| Country |
Germany |
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| Platform ID |
GPL11154 |
| Series (2) |
| GSE42044 |
DNA methylation changes are a late event in Acute Promyelocytic Leukemia and coincide with loss of transcription factor binding (sequencing) |
| GSE42119 |
DNA methylation changes are a late event in Acute Promyelocytic Leukemia and coincide with loss of transcription factor binding |
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| Relations |
| SRA |
SRX203058 |
| BioSample |
SAMN01801805 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM1031241_ChiP-Seq_REST_APL_patient.peaks.txt.gz |
37.8 Kb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Processed data provided as supplementary file |
| Raw data are available in SRA |
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