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GEO help: Mouse over screen elements for information. |
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| Status |
Public on Dec 10, 2010 |
| Title |
RAR_Day2_ChIP-seq |
| Sample type |
SRA |
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| Source name |
Day2 pre-RA, ChIP-seq
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| Organism |
Mus musculus |
| Characteristics |
cell-line: HBG3
cell-stage: Day2
chip-antibody: RAR sc-773
fraction: IP
agent: none (pre-RA)
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| Treatment protocol |
Ectopic exposure to retinoic acid
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| Growth protocol |
ES cells were grown on ES Medium (DMEM, 15% FBS, Non-essential amino acids, Glutamine, Pen/Strept, 2-mercaptoethanol and LIF) on feeder cells for amplification or on Gelatin for differentiation and experiments. Motor neuron differentiation was done as described (Wichterle & Peljto, Curr Protoc Stem Cell Biol, 2009). Briefly, ES cells were tripsinized and allowed to form aggregates in ANDFK medium (Advanced DMEM/F12, Neurobasal Medium, Knockout-SR, of Pen/Strep, L-Glutamine, and 2-mercaptoethanol. Day 0 is the day of tripsinization. At Day 2, RA is added.
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
ChIP protocols were adapted from http://jura.wi.mit.edu/young_public/hESregulation/ChIP.html. Briefly, approximately 3x10e7 cells taken from each developmental time point were cross-linked using formaldehyde and snap-frozen with liquid nitrogen. Cells were thawed on ice, resuspended in 5ml lysis buffer 1 (50 mM Hepes-KOH, pH 7.5, 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% NP-40, 0.25% Triton X-100) and mixed on a rotating platform at 4°C for 5 minutes. Samples were spun down for 3 minutes at 3000rpm, resuspended in 5ml lysis buffer 2 (10 mM Tris-HCl, pH 8.0, 200 mM NaCl, 1 mM EDTA, 0.5 mM EGTA), and mixed on a rotating platform for 5 minutes at room temperature. Samples were spun down once more, resuspended in lysis buffer 3 (10 mM Tris-HCl, pH 8.0, 100 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 0.1% Na-Deoxycholate, 0.5% N-lauroylsarcosine) and sonicated using a Misonix 3000 model sonicator to sheer cross-linked DNA to an average fragment size of approximately 500bp. Triton X-100 was then added to the lysate after sonication to final concentrations of 1% and the lysate spun down to pellet cell debris. The resulting whole-cell extract supernatant was incubated on a rotating mixer overnight at 4°C with 100 µL of Dynal Protein G magnetic beads that had been preincubated the previous 24 hours with 10 µg of the appropriate antibody in a PBS/BSA solution. After approximately 16 hours of bead-lysate incubation, beads were collected with a Dynal magnet. ChIP samples probing for transcription factor binding were washed with the following regimen, mixing on a rotating mixer at 4°C for 5 minutes per buffer: low-salt buffer (20 mM Tris at pH 8.1, 150 mM NaCl, 2 mM EDTA, 1% Triton X-100, 0.1% SDS), high-salt buffer (20 mM Tris at pH 8.1, 500 mM NaCl, 2 mM EDTA, 1% Triton X-100, 0.1% SDS), LiCl buffer (10 mM Tris at pH 8.1, 250 mM LiCl, 1 mM EDTA, 1% deoxycholate, 1% NP-40), and TE containing 50 mM NaCl. ChIP samples probing for histone and chromatin marks were washed 4 times with RIPA buffer (50 mM Hepes-KOH, pH 7.6, 500 mM LiCl, 1 mM EDTA, 1% NP-40, 0.7% Na-Deoxycholate) and then once with TE containing 50 mM NaCl, again mixing on a rotating mixer at 4°C for 5 minutes per buffer. After the final bead wash, samples were spun down to collect and discard excess wash solution, and bound antibody-protein-DNA fragment complexes were eluted from the beads by incubation in elution buffer at 65°C with occasional vortexing. Cross-links were reversed by overnight incubation at 65°C. Samples were digested with RNase A and Proteinase K to remove proteins and contaminating nucleic acids, and the DNA fragments precipitated with cold EtOH. Resulting purified DNA fragments were processed according to a modified version of the Illumina/Solexa sequencing protocol (Illumina, http://www.illumina.com/pages.ilmn?ID=252). Descriptions of these protocol modifications and data handling have been previously published (Guenther, et al. Genes Dev 2008).
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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 RAR
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| Data processing |
Alignment: Sequence reads were aligned to the mouse genome (version mm8) using Bowtie (Langmead et al Genome Biology 2009) version 0.9.9.2 with options -k 2 --best. Only uniquely mapping reads were analyzed further. Multiple hits aligning to the same nucleotide position are discarded above the level expected at a 10^-7 probability from a per-base Poisson model of the uniquely mappable portion of the mouse genome. In practice, this caps the number of hits that start at the same nucleotide to 3 in the RAR ChIP-seq experiments.
Peaks: Binding event detection is carried out using a customized methodology named SEEDS (Sequencing Experiment Event Detection Statistics) that uses statistical significance testing to find regions producing an over-abundance of sequenced reads in the signal experiments compared with the control. The algorithm is run twice across the data. The first pass estimates a scaling factor for control sequencing read depth and a model of the distribution of sequencing read alignment hits around binding events. The second pass applies these parameters to predict a final set of significant events. Before the first pass, the scaling factor is initialized to be the ratio of total hit counts between the signal and control channels. The binding distribution model is initialized to be an empirical distribution estimated around predicted binding events in Oct4 ChIP-seq data (Marson, et al. Cell 2008). All alignment hits are extended in both 3’ and 5’ directions, mirroring the observed distribution of hits around binding events. The extension magnitudes are set equal to the positions where the binding model distribution intersects a uniform distribution over the same area. Control channel hit counts are scaled using the signal-control scaling factor. A sliding window of bin width 50bp and offset 25bp is run over the genome. Overlapping extended hit counts are calculated for both the signal and (scaled) control channels. The background distribution of ChIP-seq hits is modeled as a non-homogenous Poisson process with parameters estimated from the scaled control hit counts. Specifically, the Poisson parameter is chosen as the maximum mean overlapping hit count in 50bp windows of those observed from i) the entire genome, ii) a 5Kbp window centered on the current location, and iii) a 10Kbp window centered on the current location. The use of this dynamic background model is motivated by the desire to correct local ChIP-seq enrichment biases that appear in the signal and control channels, and is similar to the model employed by MACS (Zhang, et al. Genome Biol 2008). A given bin is denoted as potentially enriched if the overlapping hit count exceeds that expected from the background model at a p-value of 10^-9. P-values for each potentially enriched bin’s over-representation in the signal channel over the control are calculated using the binomial distribution CDF (see Rozowsky, et al. Nature Biotech 2009). Neighboring regions in the set of potentially enriched regions are merged, and the maximal p-value observed for the constituent bins is attached to the resulting merged region. The p-values are corrected for multiple hypothesis testing using Benjamini & Hochberg’s method, and all regions with corrected p-values above 0.001 are discarded. False-discovery rates are estimated by repeating the event discovery procedures after swapping the scaled control channel and the signal channel. After the first pass, the scaling factor is estimated by carrying out linear regression on the hit counts observed in 10,000 bp windows that are devoid of potentially significant events in both the signal and control channels. The binding model is estimated from enriched regions with p-values < 10^-7 and signal/control hit count enrichment greater than 10. These regions are aligned around the 'peak' location, defined as the position of maximum probability when scanning the current binding model over the region's hit landscape.
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| Submission date |
Dec 10, 2009 |
| Last update date |
May 15, 2019 |
| Contact name |
Shaun Mahony |
| E-mail(s) |
mahony@psu.edu
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| Phone |
814-865-3008
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| Organization name |
Penn State University
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| Department |
Biochemistry & Molecular Biology
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| Lab |
Shaun Mahony
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| Street address |
404 South Frear Bldg
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| City |
University Park |
| State/province |
PA |
| ZIP/Postal code |
16802 |
| Country |
USA |
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| Platform ID |
GPL9250 |
| Series (2) |
| GSE19409 |
Ligand-dependent dynamics of retinoic acid receptor binding during early neurogenesis |
| GSE19450 |
Rapid and synchronous clearance of PcG histone modifications from Hox genes anticipates motor neuron differentiation |
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| Relations |
| SRA |
SRX018669 |
| BioSample |
SAMN00010815 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM482749_ES-MN_D2_RAR_1.bowtie.align.txt.gz |
152.4 Mb |
(ftp)(http) |
TXT |
| GSM482749_ES-MN_D2_RAR_2.bowtie.align.txt.gz |
135.6 Mb |
(ftp)(http) |
TXT |
| GSM482749_ES-MN_D2_RAR_3.bowtie.align.txt.gz |
141.7 Mb |
(ftp)(http) |
TXT |
| GSM482749_ES-MN_D2_RAR_4.bowtie.align.txt.gz |
135.9 Mb |
(ftp)(http) |
TXT |
| GSM482749_ES-MN_D2_RAR_5.bowtie.align.txt.gz |
132.6 Mb |
(ftp)(http) |
TXT |
| GSM482749_ES-MN_D2_RAR_6.bowtie.align.txt.gz |
145.9 Mb |
(ftp)(http) |
TXT |
| GSM482749_RARd2_vs_WCE.peaks.txt.gz |
54.5 Kb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Processed data provided as supplementary file |
| Raw data are available in SRA |
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