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GEO help: Mouse over screen elements for information. |
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| Status |
Public on Jan 06, 2014 |
| Title |
Mettl14 knockdown 3 |
| Sample type |
SRA |
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| Source name |
Mettl14 knockdown
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| Organism |
Mus musculus |
| Characteristics |
treatment: Mettl14 knockdown
antibody: none
cell line: J1
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| Treatment protocol |
Lentiviral constructs including shRNA were purchased from Sigma. To produce lentivirus, lentiviral constructs and packaging constructs were transfected into 293ft cells by calcium phosphate reagent (Clontech). About 36 hours after transfection, viral supernatants were collected and supplemented with 6 μg/μl polybrene (Millipore). ES cells were incubated with virus-containing medium for 12 h. 3 days after infection, 2 μg/ml puromycin (Sigma) were added to medium for stable cell lines selection.
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| Growth protocol |
Mouse ES cells were maintained on feeder layers of irradiated mouse embryonic fibroblasts (MEFs) in DMEM (Invitrogen) supplemented with 15% fetal bovine serum (FBS, Hyclone), 2 mM L-glutamine, 0.1 mM non-essential amino acids (Gibco), 0.1 mM β-mercaptoethanol (Sigma) and 500 units/ml leukemia inhibiting factor (LIF, Chemicon).
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| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was extracted using Trizol reagent (Invitrogen). RNA was treated with RNAse free DNAse I (Roche) to deplete DNA contamination. PolyA RNA was purified using GenEluteª mRNA Miniprep Kit (Sigma Aldrich) per manufacturer's instruction. PolyA RNA was fragmented using RNA fragmentation kit (Ambion). Two _g fragmented RNA was saved as input. Two hundred _g fragmented RNA was incubated with 3 _g anti-m6A antibody (Synaptic Systems) in RIP buffer (150mM NaCl, 10mM Tris, 0.1% NP40) for 2 hrs at 4 oC, followed by the addition of washed protein A/G magnetic beads (Millipore) and incubation at 4 oC for additional 2 hrs. Beads were washed 6 times in RIP buffer and incubated with 50 _l IP buffer containing 0.5mg/mL to elute RNA. IP'ed RNA was extracted with phenol/chloroform.
The Scriptseq v.2 RNA-seq Library Preparation method was performed on 40 ng of RNA for each sample. We followed the protocol given in the Scriptseq v.2 RNA-seq Library Preparation manual (Epicentre, an Illumina company), except DNA Clean & Concentratorª-5 - PCR/DNA clean columns (Zymo Research) were used to isolate the cDNA prior to PCR step. 15 cycles of PCR were performed on the cDNA and the resulting DNA products were purified on 2% E-Gel¨ EX Agarose Gels (Invitrogen). The products were visualized using a blue light transluminator and selected regions of the gel were excised corresponding to 200-400 bp products. The gel slices were dissolved in agarose dissolving buffer and the DNA was isolated on DNA Clean & Concentratorª-5 - PCR/DNA clean columns. The isolated DNA products were then analyzed and quantitated on an Agilent Bioanalyzer 2100. Samples were pooled and loaded into one lane of a HiSeq2000 v3 flowcell (Illumina) and sequenced for 100 bases with separate 7 base indexing read.
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| Library strategy |
OTHER |
| Library source |
transcriptomic |
| Library selection |
other |
| Instrument model |
Illumina HiSeq 2000 |
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| Data processing |
The Genome Analyzer Pipeline Software (currently Casava v1.8.2) is used to perform the early data analysis of a sequencing run, which does the image analysis, base calling, and alignment.
Reads containing non-determinant nucleotides (`N') were filtered out using fastx_clipper from FASTX-Toolkit (0.0.13). Bases lower than a defined Phred quality threshold (default: 20) at the 3' end were trimmed off from each read using cutadapt (1.1). Next, known Illumina primers and adaptor sequences were clipped off from each read by cutadapt. Finally, filtered reads were aligned against a custom contaminant list using Bowtie (0.12.7) to further filter contaminant (aligned) reads mapped to mitochondria genome, ribosomal, actin RNA or phi X genome.
Alignment to the mouse genome build mm10 was performed using TopHat (v2.0.6) with the following options: --max-multihits 1 (obtain uniquely mapped reads); --b2-very-sensitive (maximize alignment sensitive); --GTF provided with RefSeq gene annotation downloaded from UCSC Genome Browser for mm10 (May 13, 2012) to improve detection of splicing junctions.
To account for PCR artefacts, only reads aligned to the distinct genome coordinates were retained. This post-alignment filtering was achieved using samtools rmdup from Samtools (0.1.18) and MarkDuplicates from Picard (1.74). As a result, the final processed alignments in each library comprises of distinct reads each mapped to a unique location in the mm10 reference genome.
To identify strand-specific reads-enriched regions or peaks in m6A-IP relative to the control library, we applied MACS to reads on “+” and “-” strands separately (Zhang et al., 2008). MACS was run with default options except for --nomodel, --shiftsize=25, and --gsize ‘mm’ to turn off fragment size estimation (only applicable to double-stranded DNA), to make window size as 25 bp (which was chosen empirically to obtain peaks of median size around 200 nt), and to base peak calling on mouse reference genome size, respectively. The strand-specific peaks from MACS were then pooled for each library. The pooled peaks from m6A-IP libraries were subject to a stringent cutoff requiring each peak to have false discover rate (FDR estimated by MACS) < 0.1.
The fold-enrichment calculated from MACS for each filtered peaks were scaled by the corresponding fold-change of ActB gene (in terms of RPKM) to control for differential base-line expression between IP libraries.
Finally, we compared peaks from wildtype (control) with peaks from knockdown (treatment) to obtain "treatmentOnly", "controlOnly", "common" peaks. The "common" peaks are the peaks overlapped between control and knockdown peaks. For the common peaks, we compared their scaled fold-enrichments computed above to obtain "fold_enrichment_scaled_diff", which is the fold-change of treatment over control. Thus, negative (positive) fold_enrichment_scaled_diff indicates the common peak has higher (lower) enrichment in control than in treatment.
Genome_build: mm10
Supplementary_files_format_and_content: Tab-delimited file containing the peaks statistics as described above and the genes overlapped by the peaks
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| Submission date |
May 13, 2013 |
| Last update date |
May 15, 2019 |
| Contact name |
Yue Li |
| E-mail(s) |
gorillayue@gmail.com
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| Organization name |
Massachusetts Institute of Technology
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| Street address |
32 Vassar Street, 32-D528
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| City |
Cambridge |
| State/province |
Massachusetts |
| ZIP/Postal code |
02139 |
| Country |
USA |
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| Platform ID |
GPL13112 |
| Series (2) |
| GSE46878 |
RNA methylation destabilizes developmental regulators in murine embryonic stem cells (m6A) |
| GSE46880 |
RNA methylation destabilizes developmental regulators in murine embryonic stem cells |
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| Relations |
| BioSample |
SAMN02142708 |
| SRA |
SRX277436 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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