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| Status |
Public on Mar 08, 2017 |
| Title |
JDK275-J |
| Sample type |
SRA |
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| Source name |
HepG2_ACFtreatment_5µM_2
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| Organism |
Homo sapiens |
| Characteristics |
cell line: HepG2
treatment: 5 µM ACF
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| Treatment protocol |
Cells were cultured to near confluency in TC flasks, the medium was changed and fresch medium with ACF or vehicle(DMSO) was added. After 24 hours cells were collected for transcriptome anlysis, stored in Trizol and subsequently the RNA extracted.
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| Growth protocol |
HepG2 human hepatoblastoma cells (HB-8065) were obtained from ATCC (Rockville, MD, USA). Cells were grown in Williams Medium E (WEM, Invitrogen) supplemented with 10% fetal calf serum (FCS), 2 mM L-glutamine, 20 mU/mL insulin, 50 nM dexamethasone, 100 U/mL penicillin, 100 μg/mL streptomycin, 2.5 μg fungizone, 50 μg/mL gentamycin and 100 μg/mL vancomycin (=WEM-C). Sorafenib (Bayer HealthCare, Leverkusen, Germany) was dissolved in 100% dimethylsulfoxid (DMSO) (Acros Organics, New Jersey, USA). The HepG2S1 cell line was developed over a period of several months by exposing the HepG2 cells to increasing doses of Sorafenib.
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| Extracted molecule |
total RNA |
| Extraction protocol |
Rneasy kit (Qiagen)
RNA concentration and purity were determined spectrophotometrically using the Nanodrop ND-1000 (Nanodrop Technologies) and RNA integrity was assessed using a Bioanalyzer 2100 (Agilent). Per sample, an amount of 1ug total RNA was used as input. Using the Illumina TruSeq® Stranded mRNA Sample Prep Kit (protocol version 15031047 Rev.E) poly-A containing mRNA molecules were purified from the total RNA input using poly-T oligo-attached magnetic beads. In a reverse transcription reaction using random primers, RNA was converted into first strand cDNA and subsequently converted into double-stranded cDNA in a second strand cDNA synthesis reaction using the provided Second Strand Marking Master Mix. The cDNA fragments were extended with a single ‘A’ base to the 3’ ends of the blunt-ended cDNA fragments after which multiple indexing adapters were ligated introducing different barcodes for each sample. Finally an enrichment PCR of 10 cycles was carried out to enrich those DNA fragments that have adapter molecules on both ends and to amplify the amount of DNA in the library. Libraries were equimolarly pooled and sequenced using high 75 cycles NextSeq v2 kits on part of an Illumina NextSeq500 flow-cell.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NextSeq 500 |
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| Description |
HepG2S1, Sorafenib resistant cell line derived from HepG2 (ATCC) see GSE62813 and PMID:23111106
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| Data processing |
Read Preprocessing: Low quality ends and adapter sequences were trimmed off from the Illumina reads with FastX 0.0.14 and Cutadapt 1.7.1. Using FastX 0.0.14 and ShortRead 1.24.0, we filtered subsequently small reads (length < 35 bp), polyA-reads (more than 90% of the bases equal A), ambiguous reads (containing N) and low quality reads (more than 50% of the bases < Q25). With Bowtie2 v2.2.4 we identified and removed reads that mapped to the spiked-in PhiX. The number of processed reads per sample then varied between 13,831,499 and 19,366,753.
Alignment: Processed reads were aligned with STAR v2.4.1d to the reference genome of Homo sapiens (GRCh37.73), as downloaded from the Genome Reference Consortium. Default STAR parameter settings were used, except for ‘outSAMprimaryFlag=OneBestScore’, ‘twopassMode=Basic’, ‘alignIntronMin=50’, ‘alignIntronMax=500000’, ‘outSAMtype=BAM’, SortedByCoordinate. Using Samtools 1.1, reads with a mapping quality smaller than 20 were removed from the alignments.
Counting: Transcript coordinates were extracted from the GRC reference annotation with Gffread from the Cufflinks v2.1.1 suite and merged to gene coordinates with mergeBed from the Bedtools v2.17.0 toolkit. GC content and gene length were derived from the gene coordinates. The numbers of aligned reads per gene were summarized using featureCounts 1.4.6 with parameters ‘Q=0’, ‘s=2’, ’t=exon’ and ‘g=gene_id’. We removed 45,839 genes for which all samples had less than 1 count-per-million. As such, we continued with raw counts for 17,313 genes. Raw counts were further corrected within samples for GC-content and between samples using full quantile-normalization, as implemented in the EDASeq package from Bioconductor.
Identifying differential gene expression: With the EdgeR 3.8.6 package, a negative binomial generalized linear model (GLM) was fitted against the normalized counts. We did not use the normalized counts directly, but worked with offsets. Differential expression was tested for with a GLM likelihood ratio test, also implemented in the EdgeR package. The resulting p-values were corrected for multiple testing with Benjamini-Hochberg to control the false discovery rate.
Genome_build: GRCh37
Supplementary_files_format_and_content: One tab-delimited text file with raw read counts per gene and per sample. Gene IDs are Ensembl IDs.
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| Submission date |
Jun 01, 2016 |
| Last update date |
May 15, 2019 |
| Contact name |
Rekin's Janky |
| E-mail(s) |
Nucleomics.Bioinformatics@vib.be
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| Organization name |
VIB
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| Department |
Nucleomics Core
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| Street address |
Herestraat 49 Box 816
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| City |
Leuven |
| ZIP/Postal code |
B-3000 |
| Country |
Belgium |
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| Platform ID |
GPL18573 |
| Series (2) |
| GSE82110 |
Acriflavine inhibits the epithelial-to-mesenchymal transition in vitro in liver and pancreatic cancer cells (part of study on HepG2) |
| GSE82299 |
Acriflavine inhibits the epithelial-to-mesenchymal transition in vitro in liver and pancreatic cancer cells |
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| Relations |
| BioSample |
SAMN05194401 |
| SRA |
SRX1813355 |
| 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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