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| Status |
Public on Oct 28, 2024 |
| Title |
HepG2 cells, wild type, ONT DRS |
| Sample type |
SRA |
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| Source name |
HepG2
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| Organism |
Homo sapiens |
| Characteristics |
cell line: HepG2
genotype: WT
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| Extracted molecule |
polyA RNA |
| Extraction protocol |
Total RNAs were extracted from HepG2 cells using the standard TRIzol (Invitrogen) protocol. Briefly, cells were homogenized in 1 ml of TRIzol reagent and incubated at 4°C for 10 minutes. Next, the total RNA precipitates were collected as pellets after appropriate centrifugation. RNA pellets were then washed with 75% ethanol and resuspended in RNase-free water for further use. To purify poly-adenylated RNAs, the kit NEBNext® Poly(A) mRNA Magnetic Isolation Module (NEB #E7490S/L) was used. All steps were performed according to the manufacturer’s instructions to isolate intact poly(A)+ RNAs with Oligo dT Beads d(T)25. Last, concentrations and purity were measured by the NanoDrop ND1000 Spectrophotometer and the Qubit Fluorometer to ensure the quality of harvested RNAs.
500 ng of poly(A)+ RNAs from HepG2 samples were used to perform Direct RNA sequencing on the PromethION sequencers (Oxford Nanopore Technologies Ltd., ONT). All RNA libraries were prepared using the RNA-SQK002 Kit and sequenced on R9.4.1 flowcells, following the guidelines provided by ONT.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
PromethION |
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| Description |
pred.tsv contains site-level m6A prediction results in transcript-based coordination. Transcript: name of transcript, TranscriptStart: position of predicted site, Motif: 5-mer RNA motif of predicted site, Coverage: number of aligned reads, Probability: m6A modification probability, Ratio, m6A modification ratio.
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| Data processing |
Raw FAST5 files containing current intensity data were basecalled by Guppy basecalling software version 5.0.11 to generate FASTQ files of basecalled sequences. Reads scoring higher than a threshold of 7 in quality were used for alignment. Sequence alignment was performed against synthetic IVT sequences or GRCh38 reference transcriptome (cDNA and ncRNA) retrieved from the Ensembl project by Minimap2, and sorted BAM files and index files were prepared with Samtools. Preprocessed data containing m6A predictions were generated using our m6A detection tool m6ATM (https://github.com/poigit/m6ATM)
Assembly: hg38
Supplementary files format and content: bedGraph file including modification ratio information for m6A peaks
Supplementary files format and content: tab-delimited text file including Transcript, TranscriptStart, Motif, Coverage, Probability, Ratio information for predicted sites in each Sample
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| Submission date |
Apr 25, 2024 |
| Last update date |
Oct 28, 2024 |
| Contact name |
Boyi Yu |
| E-mail(s) |
[email protected]
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| Organization name |
RCAST
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| Street address |
4-6-1 Komaba, Meguro-ku
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| City |
Tokyo |
| ZIP/Postal code |
153-8904 |
| Country |
Japan |
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| Platform ID |
GPL26167 |
| Series (1) |
| GSE265867 |
m6ATM: a deep learning framework for demystifying m6A epitranscriptome via Nanopore long read RNA-seq data [HepG2 ] |
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| Relations |
| BioSample |
SAMN41085807 |
| SRA |
SRX24373538 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM8230314_HepG2_WT.bedGraph.gz |
101.6 Kb |
(ftp)(http) |
BEDGRAPH |
| GSM8230314_HepG2_WT_pred.tsv.gz |
4.3 Mb |
(ftp)(http) |
TSV |
SRA Run Selector |
| Raw data are available in SRA |
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