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Sample GSM4648279

Query DataSets for GSM4648279

Status

Public on Sep 08, 2020

Title

1-8A_L2.D708

Sample type

SRA

Source name

Liver

Organism

Mus musculus

Characteristics

strain: B6C3F1
Sex: Male
tissue: Liver
cell line: --
preservation: frozen
chemical treatment: Vehicle control (water)

Extracted molecule

total RNA

Extraction protocol

For frozen tissue samples, total RNA was extracted and purified using homogenization in RNAzol® RT (Molecular Research Center, Cincinnati, OH) and elution with RNeasy MinElute columns (Qiagen GmbH, Hilden, Germany) (Lake et al. 2016). The RNA quality of each sample was evaluated by Agilent 2100 Bioanalyzer and quantitated via Nanodrop and/or Qubit fluorometer (ThermoFisher Scientific, Waltham, MA). For FFPE samples that underwent RNA-sequencing, blocks were first sectioned into two 10-μm thick curls per sample using a Leica RM 2155 microtome (Leica Biosystems, Buffalo Grove, IL). RNA was then extracted following deparaffinization, proteinase K digestion (56°C for 15 min), heating (80°C for 15 min), DNAse treatment, RNeasy MinElute spin column (Qiagen GmbH, Hilden, Germany) clean up, and elution in 20-30 μl nuclease free water according to Qiagen AllPrep ® DNA/RNA FFPE kit protocols. RNA quality and concentration were quantified as for frozen samples.
For RNA-sequencing, 100 ng of total RNA was converted into cDNA libraries using the Illumina TruSeq Stranded Total RNA, as previously described (Wehmas et al. 2017 ). Ribosomal RNA was removed from samples through sequence-specific rRNA depletion using biotinylated probes and strepavadin bead immobilization (Ribo-Zero Gold Library Prep Kit, #RS-122-2303, Illumina, San Diego, CA). Samples were fragmented by heating with divalent cations. FFPE samples were subjected to reduced fragmentation/heating times to enable consistent library size distributions with frozen (FR). This process was quantified by Agilent Bioanalyzer (DNA 1000 kit #5067-1504) and qPCR (KAPA Library Quant Kit #KK4824, KAPA Biosystems, Wilmington, MA) followed by library normalization and sequencing. Samples were labeled with a barcode, mixed together in a sequencing pool, and run at eight per sequencing lane. Sequencing was performed at Expression Analysis (EA) (EA Genomic Services, Q2 Solutions – a Quintiles Quest Joint Venture, Durham, NC) using the Illumina HiSeq platform with 2x50bp-paired end reads

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2500

Description

Raw files were unavailable at the time of submission due to the COVID-19 epidemic

Data processing

After sequencing, basecall files were converted into FASTQ output files using CASAVA (1.8.2). RNA-sequencing FASTQ data were demultiplexed, and sequencing adapters and other low-quality bases were removed from the ends of reads during clipping and trimming using the fastq-mcf3 tool (available at https://github.com/ExpressionAnalysis/ea-utils/blob/wiki/FastqMcf.md). Trimming included removal of Illumina adapters, homopolymers at read ends and nucleotides with quality scores (Phred Q-scores) <7. Any read with one base >95% frequency, homopolymers ≥ 4 within a read, and an average Q-score below 25, or length < 25 bases were also filtered by fastq-mcf3 tool.
Total RNA-seq reads from Studies 1 and 2 were aligned to External RNA Controls Consortium (ERCC) spike-ins to assess the success of library construction and sequencing. A subset of the reads (~1 million) was aligned to other added control sequences (PhiX and other Illumina controls used during library preparation), residual sequences (globin and rRNA), and poly-A/T sequences that persisted after clipping. Reads were also aligned to a sampling of intergenic regions to assess the level of DNA contamination.
Subsequent data analysis was carried out using Partek Flow NGS® v 6.17.1128 (Partek Inc., St. Louis, MO). Total RNA-seq reads were aligned using STAR v2.5.3a and counts matrices were generated using the Expectation-Maximization algorithm (Xing et al. 2006) implemented in Partek Flow. For mouse samples, clipped FASTQ files were aligned to the Mus musculus reference genome (GRCm38/mm10) and quantified to the transcriptome (RefSeq transcript 81-2017-05-02). A 0.0001 offset was added to gene features with zero counts. Gene features with geometric mean of ≤ 1 count across all samples were filtered prior to counts per million normalization (CPM). Filtered, normalized gene counts were then analyzed for differential gene expression using Partek Gene Specific Analysis™ algorithm (GSA). Significance was defined as false discovery rate (FDR)-adjusted p-value of <0.05 and absolute fold change count ≥ 2.
For TempO-sequencing data, reads from FASTQ files involving rat were directly aligned to the Rattus norvegicus reference genome (rn6) using STAR v2.5.3a and quantified to rn6 - Ensembl Transcripts release 90 transcriptome annotation model. Reads from FASTQ files involving the AML12 cells were aligned to the Mus musculus reference genome (GRCm38/mm10) and quantified to the RefSeq transcript 81-2017-05-02 annotation model. Counts matrices were generated using the Expectation-Maximization algorithm (Xing et al. 2006) implemented in Partek Flow. One FR rat lung sample (RNA-Rat-54) was removed from subsequent analyses due to low read counts. Differentially expressed genes were identified using Partek Gene Specific Analysis™ algorithm (GSA). Significance was defined as false discovery rate (FDR)-adjusted p-value of <0.05 and absolute fold change count ≥ 2.
Genome_build: Rattus norvegicus rn6
Genome_build: Mus musculus mm10
Supplementary_files_format_and_content: raw and normalized gene counts

Submission date

Jul 01, 2020

Last update date

Sep 08, 2020

Contact name

Susan Hester

E-mail(s)

hester.susan@epa.gov

Phone

919-541-1320

Organization name

US EPA