QTL for alcohol consumption on Chr1 at D1Mit167 (21.28 Mbp , Build 37)
Description:
alcohol consumption spans 0.00 - 46.28 Mbp (NCBI Build 37) on Chr1. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
Authors:
Vadasz C, Saito M, Gyetvai B, Mikics E, Vadasz C 2nd
QTL for alcohol preference locus on Chr1 at D1Mit295 (22.09 Mbp , Build 37)
Description:
alcohol preference locus spans 0.00 - 47.09 Mbp (NCBI Build 37) on Chr1. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for alcohol preference locus on Chr1 at D1Mit165 (22.12 Mbp , Build 37)
Description:
alcohol preference locus spans 0.00 - 47.12 Mbp (NCBI Build 37) on Chr1. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for METH responses for home cage activity on Chr1 at D1Mit1 (22.85 Mbp , Build 37)
Description:
METH responses for home cage activity spans 0.00 - 47.85 Mbp (NCBI Build 37) on Chr1. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for morphine antinociception on Chr1 at D1Mit67 (22.97 Mbp , Build 37)
Description:
morphine antinociception spans 0.00 - 47.97 Mbp (NCBI Build 37) on Chr1. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
Authors:
Bergeson SE, Helms ML, O\'Toole LA, Jarvis MW, Hain HS, Mogil JS, Belknap JK
In 3-month-old C57BL/6J mice, 2229 genes (1980 up-regulated vs. 449 down-regulated) were differentially expressed 1 hour after fear conditioning when compared with the age-matched control group in the hippocampus. False Discovery rate (FDR) < 5%, fold change log2 ≥ 1.
Authors:
Peleg S, Sananbenesi F, Zovoilis A, Burkhardt S, Bahari-Javan S, Agis-Balboa RC, Cota P, Wittnam JL, Gogol-Doering A, Opitz L, Salinas-Riester G, Dettenhofer M, Kang H, Farinelli L, Chen W, Fischer A
In 3-month-old C57BL/6 mice, 1539 differentially expressed genes (1362 up-regulated vs. 177 down-regulated) were specific for associative learning (learning-regulated genes)in the hippocampus using fear conditioning. False Discovery rate (FDR) < 5%, fold change log2 ≥ 1
Authors:
Peleg S, Sananbenesi F, Zovoilis A, Burkhardt S, Bahari-Javan S, Agis-Balboa RC, Cota P, Wittnam JL, Gogol-Doering A, Opitz L, Salinas-Riester G, Dettenhofer M, Kang H, Farinelli L, Chen W, Fischer A
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
The current study used two inbred mouse strains, C57BL/6 J and A/J, to investigate the genetics of behavioral responses to fentanyl. Mice were tested for conditioned place preference and fentanyl-induced locomotor activity. C57BL/6J mice formed a conditioned place preference to fentanyl injections and fentanyl increased their activity. Neither effect was noted in A/J mice. We conducted RNA-sequencing on the nucleus accumbens of mice used for fentanyl-induced locomotor activity. Surprisingly, we noted few differentially expressed genes using treatment as the main factor. However many genes differed between strains.
Authors:
Samuel J Harp, Mariangela Martini, Will Rosenow, Larry D Mesner, Hugh Johnson, Charles R Farber, Emilie F Rissman
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