Dataset features

Specifications


Application: Gene expression microarray analysis
Number of samples: 48
Release date: Apr 15 2016
Last update date: Aug 23 2018
Access: Public
Diseases: Substance-Related Disorders
Chemicals: Ethanol, Dopamine
Dataset link Chronic Intermittent Ethanol by vapor chamber gene expression time-course in central nucleus of amygdala [CEA]

Experimental Protocol


Adult male C57BL/6J mice (n=48) received either ethanol vapor exposure (CIE) in plexiglass inhalation chambers, or only air exposure in the inhalation chambers (Ctrl). Ethanol vapor concentrations were monitored daily and air flow was adjusted to maintain ethanol concentrations within a range (10-13 mg/l air). Before each chronic ethanol exposure cycle, intoxication was initiated in the CIE group by administration of ethanol (1.6 g/kg), and blood ethanol concentration was stabilized by injection of the alcohol dehydrogenase inhibitor pyrazole (1 mmol/kg). Both ethanol and pyrazole were administered intraperitoneally (i.p.) in a volume of 0.02 ml/g body weight. Ctrl mice were handled similarly, but administered saline and pyrazole (i.p.) prior to being placed in air only chambers. Mice spent 4 days in the inhalation chamber for 16hr/day. Following 4 days in the inhalation chamber mice underwent 7 days of complete abstinence from ethanol. At the end of the abstinence period, mice were returned to the inhalation chamber to begin the next cycle of CIE. This pattern of 4 days CIE (or air) exposure followed by 7 days abstinence was repeated for four complete cycles. Immediately following the last cycle of air or ethanol exposure as above, mice were removed from the inhalation chambers and euthanized at the appropriate time point by decapitation. Time points collected were 0, 8, and 72 hours (h) and 7 days (d), with n=6 for each treatment/time group. Gene expression was quantified with Affymetrix GeneChip Mouse Genome 430 2.0 arrays. Scanning data was stored in CEL file format using Affymetrix Expression Console software. Microarray data was analyzed using RMA normalization; ComBat to minimize batch effects; linear models for microarrays (LIMMA) to determine differences in gene expression between CIE and Ctrl groups; and Weighted Gene Correlated Network Analysis (WGCNA) to identify modules of co-expressed genes representing specific biological pathways. Modules were overlapped with genes differentially expressed between CIE and Ctrl mice at each time-point to identify modules regulated at specific times after CIE. Open source bioinformatics resources were further used to determine biological pathways represented by WGCNA modules.

Repositories


GEO

GSE72515

BioProject

PRJNA294197

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Contact


Michael Miles

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