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Status |
Public on Mar 31, 2021 |
Title |
iBMDM-Reg1WT-3h-rep1 |
Sample type |
SRA |
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Source name |
iBMDM cell line
|
Organism |
Mus musculus |
Characteristics |
cell line: iBMDM genotype: WT
|
Treatment protocol |
For structure probing, cells were treated with NAI-N3 or DMSO at 37°C for 5min and quenched by adding 500 µl Trizol. For RNA seq, cells were treated with 100 ng/ml LPS for 0 h or 3 h before RNA isolation. For uvCLAP, cells were maintained in media supplied with 50 µM biotin overnight and treated with 100 ng/mL LPS for 3 h.
|
Growth protocol |
HEK293T cells, iBMDM and Raw264.7 cells were cultured were maintained in DMEM (Gibco) medium with high glucose, supplemented with 10% FBS and 1% Penicillin-Streptomycin at 37°C with 5% CO2.
|
Extracted molecule |
polyA RNA |
Extraction protocol |
For smartSHAPE and RNA-Seq, RNAs were isolated with Trizol reagents. For smartSHAPE, cells were treated with NAI-N3 or DMSO and RNAs were isolated with Trizol followed by rRNA removal. RNAs were reverse transcribed with random primers, and RNase I digestion was performed at 37 °C for 30 min. Enrichment was performed using MyOne C1 beads. After elution, cDNAs were ligated with biotinylated 3’ adaptor using CircLigase and immobilized with MyOne C1 beads. Second strand synthesis and 5’ligation was performed on the beads. smartSHAPE libraries were generated by amplification of ligation products. RNA seq libraries of Reg1 KO and WT iBMDMs were generated with KAPA RNA Hyper Prep kit. uvCLAP libraries were generated as published protocol (PMID: 29559621).
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Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
cDNA |
Instrument model |
HiSeq X Ten |
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Description |
RNA_Seq_ReadCount_3h.csv.gz
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Data processing |
Calculate smartSHAPE score from smartSHAPE sequencing data: 1) The 3’ adaptor is removed with Cutadapt 2) Duplicated reads were collapsed with custom script; 3) The first 10nt were removed using trimmomatic 4) Clean reads were mapped to human rRNA with Bowtie2 5) Un-mapped reads were mapped to the human (hg38) or mouse (mm10) genome using STAR 6) Sam files were convert into .tab files using icSHAPE-pipe sam2tab; 7) The smartSHAPE score was calculated using icSHAPE-pipe calcSHAPENoCont For uvCLAP data: Raw reads were trimmed by Cutadapt and collapsed to remove duplicated reads. The clean reads were mapped to mouse rRNA by Bowtie2, and the remaining un-mapped reads were re-mapped to mouse genome (mm10) by STAR. Peaks were called out by Piranha with Reg1 group as response sample and GFP group as covariate sample. The bin size was set to 50 with -z 50. For RNA-Seq data: Raw reads were trimmed by Cutadapt. The trimmed reads were mapped to mouse rRNA by bowtie2, and the remaining un-mapped reads were re-mapped to mouse genome (mm10) by STAR. We set parameter --quantMode TranscriptomeSAM GeneCounts to generate the read count file. The RNA-Seq differentail expression analysis is carried by DESeq2. Genome_build: hg38 and mm10 Supplementary_files_format_and_content: .shape format: tab-seperated file, each row represent a transcript. The meaning of each column: transcript_id, length, a star symbol, reactivity score for each base
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Submission date |
Aug 10, 2020 |
Last update date |
Mar 31, 2021 |
Contact name |
Meiling Piao |
E-mail(s) |
pml16@mails.tsinghua.edu.cn
|
Organization name |
Tsinghua University
|
Department |
Life Science
|
Street address |
Shuangqing Road 30
|
City |
Beijing |
ZIP/Postal code |
100084 |
Country |
China |
|
|
Platform ID |
GPL21273 |
Series (1) |
GSE155961 |
smartSHAPE: a low-input method for transcriptome-wide RNA structure probing uncovers RNA structure landscape in mouse colonic macrophages |
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Relations |
BioSample |
SAMN15773567 |
SRA |
SRX8915542 |