QTL spans- 118.3-168.3 Mbp (NCBI Build 37) on Chr3. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org). Ethanol consumption in mice was analyzed in selectively breed mice derived from an F2 population of intercrossed (C57BL/6J x DBA/2J)F1 mice. Whereas C57BL/6J are high consumers of alcohol and DBA/2J are low consumers. The concentration of ethanol used was 10%. With low preference mice and high preference mice mated for a maximum of 4 generations. In generation 4 of the Low selected line a significant QTL was observed and associated with D3Mit17. Authors suggest Adh1 may be a candidate gene.
Ethanol Induced Hypothermia Chr# 3 rs3710548 (145932289) with right flanking marker rs3719390 (85222358) and left marker rs30801216 (156802752). This was mapped in 300 + (b6x129)F2 mice.
Genes that are differentially expressed in response to over expressing MECP2 (causes anxiety phenotype) in the amygdala. Statistics reported as fold change.
Authors:
Samaco RC, Mandel-Brehm C, McGraw CM, Shaw CA, McGill BE, Zoghbi HY
Genes that have enhancers which have changes in chromatin structure to state 4 or 5 in response to cocaine in adult (8-10 week) male C57BL/6J mice. 5hmC levels were measured via 5hmC-seq. Data taken from Supplementary Table 3. Values presented are "1" for presence. Data available at GEO with accession number GSE63749.
Authors:
Jian Feng, Ningyi Shao, Keith E Szulwach, Vincent Vialou, Jimmy Huynh, Chun Zhong, Thuc Le, Deveroux Ferguson, Michael E Cahill, Yujing Li, Ja Wook Koo, Efrain Ribeiro, Benoit Labonte, Benjamin M Laitman, David Estey, Victoria Stockman, Pamela Kennedy, Thomas Couroussé, Isaac Mensah, Gustavo Turecki, Kym F Faull, Guo-li Ming, Hongjun Song, Guoping Fan, Patrizia Casaccia, Li Shen, Peng Jin, Eric J Nestler
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous set of behavioral signs and symptoms. There are no laboratory tests that provide direct objective evidence for diagnosis. Microarray and RNA-Seq technologies enable genome-wide transcriptome profiling at low costs and provide an opportunity to identify bio- markers to facilitate diagnosis, prognosis, and treatment of patients. However, access to brain tissue in living patients is not possible. Blood contains cellular and extracellular RNAs that provide disease-relevant information for some brain diseases. We hypothesized that blood gene expression profiles can be used to diagnose AUD. We profiled brain (prefrontal cortex, amygdala, and hypothalamus) and blood gene expression levels in C57BL/6J mice using RNA-seq one week after chronic intermittent ethanol (CIE) exposure, a mouse model of alcohol dependence. We found a high degree of preservation (rho range: [0.50, 0.67]) between blood and brain transcript levels. There was small overlap between blood and brain DEGs, and considerable overlap of gene networks perturbed after CIE related to cell- cell signaling (e.g., GABA and glutamate receptor signaling), immune responses (e.g., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic regression, random forest, and partial least squares discriminant analysis), which were highly accurate at predicting alcohol dependence status (maximum AUC: 90.1%). These results suggest that gene expression profiles from peripheral blood samples contain a bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
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