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Status |
Public on Jul 07, 2024 |
Title |
Gastric adenocarcinoma cells - AGS NAT10 KO-1 IP |
Sample type |
SRA |
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Source name |
AGS
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Organism |
Homo sapiens |
Characteristics |
cell type: Gastric adenocarcinoma cells cell line: AGS genotype: NAT10 knockout rip antibody: ac4C antibody (Abcam)
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Extracted molecule |
total RNA |
Extraction protocol |
Total RNA was extracted from NAT10 knockout or control AGS cells using Trizol reagent, then digested with DNase I and fragmented into 100~200 nt nucleotides by RNA fragmentation reagent (Ambion). After saving 50ng fragmented RNA as input, the rest (150 μg) was used for RNA immunoprecipitation with ac4C antibody (Abcam). ac4C RNAs were immunoprecipitated with Dynabeads Protein G (Invitrogen), and purified with HiPure cell miRNA (Magen). Ribosomal RNA was removed from input RNA and ac4C-enriched RNA samples. RNA sequencing libraries for input RNA (RNA-seq) and ac4C-enriched RNA (acRIP-seq) were simultaneously constructed with the EpiTM mini longRNA-seq kit (Epibiotek), and then sequenced on the Illumina NovaSeq 6000 with two independent biological replicates. RNA libraries were prepared for sequencing using standard Illumina6000 protocols acRIP-seq
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Library strategy |
RIP-Seq |
Library source |
transcriptomic |
Library selection |
other |
Instrument model |
Illumina NovaSeq 6000 |
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Description |
KO-1_peak.txt
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Data processing |
Cutadapt (v2.5 ) was used to trim adapters and filter for sequences Hisat2 aligner (v2.1.0) was used to align the reads to the reference genome under parameters: “--rna-strandness RF”. ExomePeak R package (v2.13.2) was used to identify ac4C peaks under parameters: “PEAK_CUTOFF_PVALUE=0.05,PEAK_CUTOFF_FDR=NA,FRAGMENT_LENGTH=200”. Identified ac4C peaks which p value <0.05 were chosen for the de novo motif analysis using homer (v4.10.4) under parameters:”-len 12 -rna”. Genome_build: GRCh38 Supplementary_files_format_and_content: The peak files are the results of ac4C peaks.
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Submission date |
Jul 20, 2021 |
Last update date |
Jul 07, 2024 |
Contact name |
Min Deng |
E-mail(s) |
mindeng@gzhmu.edu.cn
|
Phone |
13924307478
|
Organization name |
Affiliated Cancer Hospital & Institute of Guangzhou Medical University
|
Street address |
Affiliated Cancer Hospital & Institute of Guangzhou Medical University, NO.78, Hengzhigang Road.
|
City |
GUANGZHOU |
State/province |
GUANGDONG |
ZIP/Postal code |
510095 |
Country |
China |
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|
Platform ID |
GPL24676 |
Series (1) |
GSE180494 |
ac4C RIP-seq analysis of AGS cells upon NAT10 knockout. |
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Relations |
BioSample |
SAMN20330994 |
SRA |
SRX11509051 |