|
| Status |
Public on Sep 03, 2019 |
| Title |
monkeyPFC-ethanol-24 |
| Sample type |
RNA |
| |
|
| Source name |
Brodmann brain areas 24, 25, and 32, ethanol drinker
|
| Organism |
Macaca mulatta |
| Characteristics |
Sex: male
age: adult
tissue: brain, Brodmann areas 24, 25, 32 pooled
treatment: ethanol consuming
|
| Treatment protocol |
Macaques individually housed at the Oregon National Primate Research Center were induced to drink ethanol by schedule-induced polydipsia per previously published methods (Grant et al. 2008, Helms, Park, and Grant 2014), and were then allowed 22 hours per day of ad libitum access to water and 4% (w/v) ethanol in water for a period of one year. Control animals were given daily maltose dextran solution (calorically matched to an ethanol drinker) and had access to water during all portions of the experiment.
|
| Growth protocol |
n/a
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Brain samples were homogenized with a tissue homogenizer. RNA was extracted from brain tissue using either RNeasy Mini Kit (Qiagen, Valencia, CA; cohorts 4 & 5) or All Prep DNA/RNA/miRNA Universal Kit (Qiagen; cohorts 7a & 7b) following the manufacturer’s protocol.
|
| Label |
biotin
|
| Label protocol |
Biotinylated cRNA samples were prepared according to Affymetrix protocols.
|
| |
|
| Hybridization protocol |
Following fragmentation, cRNA samples were hybridized for 16 hr to GeneChip Rhesus Macaque Genome arrays by procedures outlined by Affymetrix.
|
| Scan protocol |
Arrays were washed, stained with streptavidin-phycoerythrin and scanned using the Affymetrix GeneChip Scanner 3000.
|
| Description |
Coh7a_EtOH_33
Gene expression data from male Rhesus macaque prefrontal cortex tissue, ethanol consuming animal x 1 year.
|
| Data processing |
Raw microarray expression data from monkeys underwent background correction and quantile normalization in a single group by the Robust Multi-array Average (RMA) method within the affy package for R (Gautier et al. 2004). RMA data was examined for batch effects by principal component analysis. Batch effects were evident for two factors with similar patterns of segregation: microarray processing batch and MATRR cohort. To remove batch effects, RMA data was adjusted using the ComBat method in R (Johnson, Li, and Rabinovic 2007), with microarray processing batch as the batch factor. Principal component analysis confirmed that ComBat removed the batch effects. Network analysis with WGCNA and bioinformatics analysis were used to identify modules of co-expressed genes representing specific biological pathways.
|
| |
|
| Submission date |
Jul 19, 2019 |
| Last update date |
Sep 03, 2019 |
| Contact name |
Michael Miles |
| E-mail(s) |
Michael.Miles@vcuhealth.org
|
| Organization name |
Virginia Commonwealth Univ.
|
| Department |
Pharmacology and Toxicology
|
| Lab |
Miles
|
| Street address |
PO Box 980613
|
| City |
Richmond |
| State/province |
VA |
| ZIP/Postal code |
23298 |
| Country |
USA |
| |
|
| Platform ID |
GPL3535 |
| Series (1) |
| GSE134546 |
Cross-species co-analysis of prefrontal cortex chronic ethanol transcriptome responses in mice and monkeys |
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