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Status |
Public on Jul 30, 2020 |
Title |
sup_plus_2 |
Sample type |
SRA |
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Source name |
CD8+ T cells
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Organism |
Mus musculus |
Characteristics |
strain: C57BL/6 cell type: CD8+ T cells medium: B16F10 supernatants + methionine
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Treatment protocol |
CD8+ T cells were cultured with fresh medium without methionine (fresh-), fresh medium with methionine (fresh+), B16F10 supernatants (Sup-), and B16F10 supernatants with methionine supplementation (Sup+) for 36h.
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Growth protocol |
CD8+ T cells were first activated with anti-CD3/CD28 for 2 days, and then cultured with media for 36h.
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Extracted molecule |
total RNA |
Extraction protocol |
RNA was isolated from these cells using Direct-zolTM RNA miniprep Plus kit (ZOMO research, Irvine, CA, USA).
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Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
cDNA |
Instrument model |
Illumina HiSeq 4000 |
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Description |
Sample_119007 processed data file: depth_normalized_counts.txt processed data file: phenotype_repFpkms.txt
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Data processing |
Sequencing was performed by the UM DNA Sequencing Core, using the Illumina Hi-Seq 4000 platform, single end, 50 cycles, stranded mRNA prep. We checked the quality of the raw reads data for each sample using FastQC (version 0.11.3) to identify features of the data that may indicate quality problems (e.g. low quality scores, over-represented sequences, inappropriate GC content). We used the Tuxedo Suite software package for alignment, differential expression analysis, and post-analysis diagnostics. Briefly, we aligned reads to the reference mRNA transcriptome (mm10) using TopHat (version 2.0.13) and Bowtie2 (version 2.2.1.). We used default parameter settings for alignment, with the exception of: “--b2-very-sensitive” telling the software to spend extra time searching for valid alignments. We used FastQC for a second round of quality control (post-alignment), to ensure that only high quality data would be input to expression quantitation and differential expression analysis. We used Cufflinks/CuffDiff (version 2.2.1) for expression quantitation, normalization, and differential expression analysis, using mm10.fa as the reference genome sequence. For this analysis, we used parameter settings: “--multi-read-correct” to adjust expression calculations for reads that map in more than one locus, as well as “--compatible-hits-norm” and “--upper-quartile–norm” for normalization of expression values. We generated diagnostic plots using the CummeRbund R package. Genome_build: mRNA transcriptome (mm10/GRCm38) Supplementary_files_format_and_content: depth_normalized_counts.txt Supplementary_files_format_and_content: phenotype_repFpkms.txt
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Submission date |
May 19, 2020 |
Last update date |
Jul 30, 2020 |
Contact name |
Yingjie Bian |
E-mail(s) |
[email protected]
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Organization name |
University of Michigan
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Department |
Surgery
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Street address |
109 Zina Pitcher Pl
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City |
Ann Arbor |
State/province |
MI |
ZIP/Postal code |
48109 |
Country |
USA |
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Platform ID |
GPL21103 |
Series (2) |
GSE150886 |
RNA-seq in mouse CD8+ T cells cultured with medium with or without methionine |
GSE150887 |
Cancer SLC43A2 alters T cell methionine metabolism and histone methylation |
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Relations |
BioSample |
SAMN14977478 |
SRA |
SRX8365664 |
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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