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| Status |
Public on Apr 14, 2010 |
| Title |
Lefterova_mac_PPARg |
| Sample type |
SRA |
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| Source name |
primary macrophage
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| Organism |
Mus musculus |
| Characteristics |
strain: C57BL/6
cell type: thioglycollate-elicited peritoneal macrophages
chip antibody: PPARgamma
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| Treatment protocol |
ChIP was performed as described using cross-linked 3T3-L1 nuclear lysates or macrophage whole-cell lysates. The following antibodies were used: anti-PPAR (sc-7196, Santa Cruz or 81b8, Cell Signaling Technologies), anti-RXR (sc-774, Santa Cruz), anti-H3K9Ace (ab4441, Abcam), anti-H3K9Me2 (ab1220, Abcam), anti-H3K27Me3 (07-449, Millipore), anti-PU.1 (sc-352x, Santa Cruz), anti-C/EBP (sc-61, Santa Cruz), and anti-C/EBP (sc-150x, Santa Cruz). For the ChIP-chip experiments, the anti-H3K9Ace (06-942, Upstate) and anti-histone 3(H3) (ab1791) antibodies were used.
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| Growth protocol |
Macrophages were obtained from male C57Bl6 mice (Jackson Laboratory) via peritoneal lavage 3 days post intraperitoneal injection with 1 ml of sterile 3% thioglycollate. Cells were harvested after 24 h of adherence purification in culture. 3T3-L1 preadipocytes were obtained from American Type Culture Collection and differentiated to adipocytes according to standard protocol. All cells were cultured in high-glucose DMEM supplemented with 10% fetal bovine serum and 100 U/ml penicillin and 100 μg/ml streptomycin.
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
ChIP samples were amplified using the ChIP-Seq Sample Prep Kit (Illumina) according to manufacturer's instructions. For macrophages, cells from at least 4 animals were pooled per sequencing run to minimize the effects of biological variability. Two sequencing runs were performed for the macrophage PPAR ChIP and the data were concatenated; one sequencing run was performed for all other transcription factors and histone modifications. Sequence reads of 36 bp were obtained using the Solexa Analysis Pipeline, and mapped to the mouse genome (mm8) using ELAND allowing up to two mismatches. Only reads with a unique best match were included in further analysis.
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| Library strategy |
ChIP-Seq |
| Library source |
genomic |
| Library selection |
ChIP |
| Instrument model |
Illumina Genome Analyzer II |
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| Description |
Chromatin IP against PPARgamma
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| Data processing |
ChIP-seq peak calling. All transcription factor binding data were analyzed with GLITR using default parameters and an iteration number of 100. GLITR first filtered each data set such that each start coordinate was represented once. Then a Pseudo-ChIP data set that had the same number of tags as each filtered data set was generated. Pseudo-ChIP sequence tags were sampled from the input sequence tag data available at http://web.me.com/kaestnerlab1/GLITR/ and the remaining input sequence tags in this set were used as background for the GLITR sampling procedure. The following statistical cut-offs were used to generate the lists of high confidence binding intervals for transcription factors: False Discovery Rate (FDR) > 0.5% except for PU.1 (FDR > 0.1%); fold change over input>5; number of reads at the peak summit > 9. These criteria and filtering out of regions enriched in inputs were applied to minimize nonspecific effects from PCR bias or local chromatin structure. H3K9Ace enrichment was analyzed using Significance Tester for Accumulation of Reads (STAR, manuscript in preparation). Briefly, an algorithm was developed to determine regions with a locally significant accumulation of reads, while controlling for false positives. For each sample, a set of permutation controls was generated by randomizing the reads via a uniform distribution across the genome. For an error rate of alpha, a cutoff for peak height was chosen that gives a proportion of the (average) signal over the permuted controls to the signal in the ChIP sample of no more than alpha. This gives a cutoff for significant peak height that controls the proportion of false positives in the set of all calls, otherwise known as the FDR. Prior to the comparison with the permutation controls, regions previously identified as common input bias were filtered out. Calls were made using a window of length 500 bp with a displacement of 50 bp as appropriate for histone modifications and FDR < 5%.
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| Submission date |
Apr 12, 2010 |
| Last update date |
May 15, 2019 |
| Contact name |
Mitchell A. Lazar |
| E-mail(s) |
lazar@mail.med.upenn.edu
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| Organization name |
University of Pennsylvania
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| Department |
Institute for Diabetes, Obesity, and Metabolism
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| Lab |
Mitchell A. Lazar
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| Street address |
700 CRB, 415 Curie Blvd.
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| City |
philadelphia |
| State/province |
PA |
| ZIP/Postal code |
19104 |
| Country |
USA |
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| Platform ID |
GPL9250 |
| Series (1) |
| GSE21314 |
Cell-Specific Determinants of PPARg Function in Adipocytes and Macrophages |
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| Relations |
| SRA |
SRX019134 |
| BioSample |
SAMN00011220 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM532739_ALL_GLITR_output_Mac_PPARg_Lefterova.txt.gz |
245.9 Kb |
(ftp)(http) |
TXT |
| GSM532739_Mac_PPARg_peaks.txt.gz |
32.7 Kb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Processed data provided as supplementary file |
| Raw data are available in SRA |
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