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Sample GSM4648373

Query DataSets for GSM4648373

Status

Public on Sep 08, 2020

Title

RNA-Rat-71

Sample type

SRA

Source name

Liver

Organism

Rattus norvegicus

Characteristics

strain: F344
Sex: Male
tissue: Liver
cell line: --
preservation: frozen
chemical treatment: vehicle control

Extracted molecule

total RNA

Extraction protocol

FFPE and cell samples that underwent TempO-sequencing were lysed using BioSpyder 2X lysis buffer
FFPE lysates were first deparaffinized by an overlay of mineral oil and heated to 95°C for 5 min. RNA, cellular lysate, and deparaffinized FFPE lysates were then treated with Protease K followed by annealing of a pair of detector oligos 25 nt adjacent to the target RNA. Excess oligos were digested with nuclease while those bound adjacent to the target were ligated (Yeakley et al. 2017) and amplified. Each sample was assigned a specific barcode pair that hybridized with the universal detector oligos allowing for sample identification following sequencing and library generation for the s1500+ rat and mouse transcriptome assays. The s1500+ rat measures 2603 genes (2636 probes) and the s1500+ mouse measures 2756 genes (3045 probes) targeting a subset of protein-coding genes considered representative of the entire transcriptome. Sample amplicons were pooled and purified using a PCR clean-up kit (Clontech, Mountain View, California). Libraries were sequenced using a NextSeq 550 sequencing platform by BioSpyder

Library strategy

OTHER

Library source

transcriptomic

Library selection

other

Instrument model

NextSeq 550

Description

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

Data processing

Library strategy: TempO-sequencing
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