 |
 |
GEO help: Mouse over screen elements for information. |
|
| Status |
Public on Nov 08, 2016 |
| Title |
SGE_018 |
| Sample type |
SRA |
| |
|
| Source name |
peripheral blood mononuclear cells
|
| Organism |
Macaca mulatta |
| Characteristics |
cell type: monocyte (CD3-/CD20-/HLADR+/CD14+)
subject_id: RPs7
sample date: 2013-05-09
study phase: phase 1
study group: RPs7
|
| Treatment protocol |
NA
|
| Growth protocol |
we drew 12-20 mL of blood from each female, purified the PBMC fraction using density gradient centrifugation, and performed fluorescent activated cell sortingto purify 5 PBMC populations. We sorted cell types as follows: classical monocytes (CD3-/CD20-/HLA-DR+/CD14+), natural killer cells (CD3-/CD20-/HLA-DR-/CD16+), B cells (CD3-/CD20+/HLA-DR+), helper T cells (CD3+/CD8-/CD4+), cytotoxic T cells (CD3+/CD8+/CD4-)
|
| Extracted molecule |
polyA RNA |
| Extraction protocol |
Purified cells were immediately pelleted, lysed, and frozen at -80°C until DNA and RNA extraction using the Qiagen AllPrep extraction kit.
Libraries were prepared according to NEB's instructions accompanying the NEBNext Ultra RNA Library Prep Kit. Briefly, we purified the poly-adenylated mRNA from 200 ng of total RNA using the NEBNext Poly(A) mRNA Magnetic Isolation Module. The mRNA was then reverse transcribed into cDNA, ligated to Illumina adapters, size-selected for a median size of ~350 bp, and amplified via PCR for 13 cycles. We tagged each sample with a unique molecular barcode and pooled 10-12 samples per Illumina HiSeq 2500 lane of single-end 100 bp sequencing.
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 2500 |
| |
|
| Data processing |
Following sequencing, we trimmed Illumina adapter sequence from the ends of the reads using Trim Galore! (v0.2.7), mapped trimmed reads to the rhesus macaque genome (MacaM v7; Zimin et al. PMID 25319552) using the STAR 2-pass method, and collated the number of reads that mapped uniquely to each annotated MacaM gene (v7.6.8) using HTSeq-count (v0.6.1) with the option “intersection-nonempty”.
We first filtered out genes that were very lowly or not detectably expressed in our samples by removing any gene with a median RPKM ≤ 2 in that cell type.
We normalized the resulting read count matrix using the function voom from the R package limma. We then modeled the normalized expression values as a function of the sample donor’s social group membership. Controlling for the identity of the group removes biological variation related to differences in group dynamics, and most technical batch effects related to sample collection and processing. The residuals of the model relating normalized expression to social group identity as our primary outcome measure in all subsequent analyses.
Genome_build: MacaM
Supplementary_files_format_and_content: [.txt] abundance measurements
|
| |
|
| Submission date |
Jun 13, 2016 |
| Last update date |
May 15, 2019 |
| Contact name |
Noah Snyder-Mackler |
| E-mail(s) |
nsnyderm@asu.edu
|
| Phone |
3025938430
|
| Organization name |
Arizona State University
|
| Lab |
Snyder-Mackler
|
| Street address |
427 East Tyler Mall
|
| City |
Tempe |
| State/province |
AZ |
| ZIP/Postal code |
85281 |
| Country |
USA |
| |
|
| Platform ID |
GPL19129 |
| Series (2) |
| GSE83302 |
Social status alters immune regulation and response to infection [cell_specific_RNAseq] |
| GSE83307 |
Social status alters immune regulation and response to infection |
|
| Relations |
| BioSample |
SAMN05237906 |
| SRA |
SRX1839526 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
|
|
|
|
 |
