|
| Status |
Public on Mar 31, 2022 |
| Title |
cKO2-Treg cells (RNA-seq) |
| Sample type |
SRA |
| |
|
| Source name |
CD4+CD25+YFP+ Treg cells
|
| Organism |
Mus musculus |
| Characteristics |
strain: C57BL/6
age: post natal 7-week- old
tissue: Mus spleen and lymph node
cell type: isolated CD4+CD25+YFP+ Treg cells from Foxp3cre/+ TKTfl/fl female mouse by flow cytometery
genotype: Treg specific TKT knockout
|
| Treatment protocol |
no treatment
|
| Growth protocol |
All mice were maintained in the animal facility of Shanghai Jiao Tong University School of Medicine under specific pathogen-free conditions
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was isolated from Tregs by Trizol, then used for RNA sequencing analysis by the Illumina HiSeq X Ten platform
RNA libraries were prepared for sequencing using standard Illumina protocols
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
HiSeq X Ten |
| |
|
| Data processing |
The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq X ten platform and 125 bp/150 bp paired-end reads were generated.
Reference genome and gene model annotation files were downloaded from genome website directly. Index of the reference genome was built using Hisat2 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. We selected Hisat2 as the mapping tool for that Hisat2 can generate a database of splice junctions based on the gene model annotation file and thus a better mapping result than other non-splice mapping tools.
featureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene. And then FPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene. FPKM, expected number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced, considers the effect of sequencing depth and gene length for the reads count at the same time, and is currently the most commonly used method for estimating gene expression levels.
Differential expression analysis of two conditions/groups (two biological replicates per condition) was performed using the DESeq2 R package (1.16.1). DESeq2 provide statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate . Genes with an adjusted P-value
Genome_build: mm10
Supplementary_files_format_and_content: Matrix table with raw gene counts for every gene and every sample
|
| |
|
| Submission date |
Apr 08, 2021 |
| Last update date |
Mar 31, 2022 |
| Contact name |
Qi Liu |
| E-mail(s) |
liuqi0325@sjtu.edu.cn
|
| Phone |
13262626838
|
| Organization name |
Shanghai Jiao Tong University School of Medicine
|
| Street address |
280 S. Chongqing Road
|
| City |
shang hai |
| ZIP/Postal code |
200025 |
| Country |
China |
| |
|
| Platform ID |
GPL21273 |
| Series (2) |
| GSE171675 |
Control of regulatory T cell function by the non-oxidative pentose phosphate pathway [RNA-Seq] |
| GSE172048 |
Control of regulatory T cell function by the non-oxidative pentose phosphate pathway |
|
| Relations |
| BioSample |
SAMN18672094 |
| SRA |
SRX10549791 |
