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| Status |
Public on Sep 30, 2023 |
| Title |
rna-seq_skm-gn_male_reference_3_vial_80000885540 |
| Sample type |
SRA |
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| Source name |
RNA-Seq of Rat Male Gastrocnemius Powder Reference
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| Organism |
Rattus norvegicus |
| Characteristics |
tissue: Gastrocnemius Powder
treatment: Reference
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| Extracted molecule |
total RNA |
| Extraction protocol |
RNA sequencing (RNA-Seq) was performed at Stanford University and the Icahn School of Medicine at Mount Sinai. Rat tissues (30 mg for white adipose, 15 mg for brown adipose, 10 mg for other solid tissues, and 0.47 ml blood) were disrupted in Agencourt RNAdvance tissue lysis buffer (Beckman Coulter, Brea, CA) using a tissue ruptor (Omni International, Kennesaw, GA, # 19-040E). Total RNA was extracted in a BiomekFx automation workstation according to the manufacturer's instructions for tissue-specific extraction. Total RNA from blood collected in PAXgene tubes (BD Biosciences, Franklin Lakes, NJ, # 762165) was extracted using the Agencourt RNAdvance blood specific kit (Beckman Coulter). Two tissue-specific consortium reference standards were included to monitor the sample processing QC. The RNA was quantified by NanoDrop (ThermoFisher Scientific, # ND-ONE-W) and Qubit assay (ThermoFisher Scientific), and the quality was determined by either Bioanalyzer or Fragment Analyzer analysis.
Universal Plus mRNA-Seq kit from NuGEN/Tecan (# 9133) were used for generation of RNA- Seq libraries derived from poly(A)-selected RNA according to the manufacturer's instructions. Universal Plus mRNA-Seq libraries contain dual (i7 and i5) 8 bp barcodes and an 8 bp unique molecular identifier (UMI), which enable deep multiplexing of NGS sequencing samples and accurate quantification of PCR duplication levels. Approximately 500ng of total RNA were used to generate the libraries. The Universal Plus mRNA-Seq workflow consists of poly(A) RNA selection, RNA fragmentation and double-stranded cDNA generation using a mix-ture of random and oligo(dT) priming, end repair to generate blunt ends, adaptor ligation, strand selection, AnyDeplete workflow to remove unwanted ribosomal and globin transcripts, and PCR amplification to enrich final library species. All library preparations were performed using a 13 Biomek i7 laboratory automation system (Beckman Coulter). Tissue-specific reference standards provided by the consortium were included with all RNA isolations to QC the RNA.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
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| Description |
motrpac_pass1b-06_t55-gastrocnemius_transcript-rna-seq_rsem-genes-count.txt
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| Data processing |
Pooled libraries were sequenced on an Illumina NovaSeq 6000 platform (Illumina, San Diego, CA, USA) to a target depth of 35 million read pairs (70 million paired-end reads) per sample using a paired-end 100 base pair run configuration
In order to capture the 8-base UMIs, libraries were sequenced using 16 cycles for the i7 index read and 8 cycles for the i5 index read
Reads were demultiplexed with bcl2fastq2 (v2.20.0) using options --use-bases-mask Y*,I8Y*,I*,Y* --mask-short-adapter-reads 0 --minimum-trimmed-read-length 0 (Illumina, San Diego, CA, USA), and UMIs in the index FASTQ files were attached to the read FASTQ files
Adapters were trimmed with cutadapt (v1.18), and trimmed reads shorter than 20 base pairs were removed
FastQC (v0.11.8) was used to generate pre-alignment QC metrics
STAR (v2.7.0d) was used to index and align reads to release 96 of the Ensembl Rattus norvegicus (rn6) genome and gene annotation
Default parameters were used for STAR's genomeGenerate run mode; in STAR's alignReads run mode, SAM attributes were specified as NH HI AS NM MD nM, and reads were removed if they did not contain high-confidence collapsed splice junctions (--outFilterType BySJout)
RSEM (v1.3.1) was used to quantify transcriptome-coordinate-sorted alignments using a forward probability of 0.5 to indicate a non-strand-specific protocol
Bowtie 2 (v2.3.4.3) was used to index and align reads to globin, rRNA, and phix sequences in order to quantify the percent of reads that mapped to these contaminants and spike-ins
UCSC's gtfToGenePred was used to convert the rn6 gene annotation (GTF) to a refFlat file in order to run Picard CollectRnaSeqMetrics (v2.18.16) with options MINIMUM_LENGTH=50 and RRNA_FRAGMENT_PERCENTAGE=0.3
UMIs were used to accurately quantify PCR duplicates with NuGEN's nodup.py script (https://github.com/tecangenomics/nudup)
QC metrics from every stage of the quantification pipeline were compiled, in part with multiQC (v1.6)
The openWDL-based implementation of the RNA-Seq pipeline on Google Cloud Platform is available at https://github.com/MoTrPAC/motrpac-rna-seq-pipeline.
Assembly: rn6
Supplementary files format and content: Consolidated raw read count matrix for genes (RSEM program) of all samples run per tissue/phase.
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| Submission date |
Sep 05, 2023 |
| Last update date |
Sep 30, 2023 |
| Contact name |
Euan Ashley |
| Organization name |
Stanford University
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| Street address |
870 Quarry Road
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| City |
Stanford |
| State/province |
CA |
| ZIP/Postal code |
94305 |
| Country |
USA |
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| Platform ID |
GPL25947 |
| Series (2) |
| GSE242354 |
MoTrPAC- Endurance Exercise Training Study In 6 Months Old Rats [RNA-seq] |
| GSE242358 |
MoTrPAC: Endurance Exercise Training Study In 6 Months Old Rats |
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| Relations |
| BioSample |
SAMN36363919 |
| SRA |
SRX20997506 |
| 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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