QTL for METH responses for body temperature on Chr19 at Gnblps1 (0.00 Mbp , Build 37)
Description:
METH responses for body temperature spans 0.00 - 25.00 Mbp (NCBI Build 37) on Chr19. 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 body temperature on Chr19 at Lybp2 (2.15 Mbp , Build 37)
Description:
METH responses for body temperature spans 0.00 - 27.15 Mbp (NCBI Build 37) on Chr19. 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 body temperature on Chr19 at Pomc-2 (14.21 Mbp , Build 37)
Description:
METH responses for body temperature spans 0.00 - 39.21 Mbp (NCBI Build 37) on Chr19. 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 body temperature on Chr19 at Lpc1 (23.27 Mbp , Build 37)
Description:
METH responses for body temperature spans 0.00 - 48.27 Mbp (NCBI Build 37) on Chr19. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL associated with bone response to mechanical loading 12. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (3645155)
QTL associated with fluctuating asymmetry QTL 10. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (20420342)
Authors:
Zhang S, Lou Y, Amstein TM, Anyango M, Mohibullah N, Osoti A, Stancliffe D, King R, Iraqi F, Gershenfeld HK
QTL associated with induction of brown adipocytes 4. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (26402805)
QTL associated with macrophage-associated risk inflammatory factor 3. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (20636654)
QTL associated with nerve sheath tumor resistance QTL 1. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (5321112)
Authors:
Walrath JC, Fox K, Truffer E, Gregory Alvord W, Quiones OA, Reilly KM
QTL associated with pulmonary adenoma susceptibility 3. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (20420342)
QTL associated with postnatal body weight growth 20. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (5011610)
QTL associated with tibia bone quality traits 7. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (15599162)
Authors:
Jiao Y, Chiu H, Fan Z, Jiao F, Eckstein EC, Beamer WG, Gu W
QTL associated with thymic lymphoma resistance 1. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (26884543)
Authors:
Santos J, Gonzlez-Snchez L, Villa-Morales M, Ors I, Lpez-Nieva P, Vaquero C, Gonzlez-Gugel E, Fernndez-Navarro P, Roncero AM, Guenet JL, Montagutelli X, Fernndez-Piqueras J
Here, female High Drinking in the Dark (HDID) mice were stereotaxically injected with 0.5uL rAAV2/5-CMV-Cre-GFP and 0.5uL rAAV2-hSyn-DIO-hM3Dq-mCherry bilaterally into the NAc. A Drinking in the Dark (DID) experiment lasting 6 weeks was carried out with 2 fluid groups (water or ethanol) and 2 treatment groups (VEH/VEH/VEH or VEH/CNO/VEH). Mice were serially treated with vehicle prior to DID during week 1 to establish baseline drinking, CNO (1mg/kg) during weeks 2-5 to measure the effects of chronic treatment, and then mice were treated with vehicle again during week 6 to determine if there were any lasting effects of chronic CNO treatment. This gene set comprises 2,377 genes that were differentially expressed in the nucleus accumbens of ethanol drinking HDID mice treated with CNO as compared to the water drinking and vehicle treated control group.
Authors:
Darya Y. Pozhidayeva, Sean P. Farris, Calla M. Goeke, Evan J. Firsick, Kayla G. Townsley, Marina Guizzetti, and Angela R. Ozburn
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
Alcohol transcriptome changes in mice microglia p-value
Description:
Microglia are fundamentally important immune cells within the central nervous system (CNS) that respond to environmental challenges to maintain normal physiological processes. Alterations in steady-state cellular function and over-activation of microglia can facilitate the initiation and progression of neuropathological conditions such as Alzheimer’s disease, Multiple Sclerosis, and Major Depressive Disorder. Alcohol consumption disrupts signaling pathways including both innate and adaptive immune responses that are necessary for CNS homeostasis. Coordinate expression of these genes is not ascertained from an admixture of CNS cell-types, underscoring the importance of examining isolated cellular populations to reveal systematic gene expression changes arising from mature microglia. Unbiased RNA-Seq profiling was used to identify gene expression changes in isolated prefrontal cortical microglia in response to recurring bouts of voluntary alcohol drinking behavior. The voluntary ethanol paradigm utilizes long-term consumption ethanol that results in escalated alcohol intake and altered cortical plasticity that is seen in humans. Gene coexpression analysis identified a coordinately regulated group of genes, unique to microglia, that collectively are associated with alcohol consumption. Genes within this group are involved in toll-like receptor signaling and transforming growth factor beta signaling. Network connectivity of this group identified Siglech as a putative hub gene and highlighted the potential importance of proteases in the microglial response to chronic ethanol. In conclusion, we identified a distinctive microglial gene expression signature for neuroimmune responses related to alcohol consumption that provides valuable insight into microglia-specific changes underlying the development of substance abuse, and possibly other CNS disorders.
Authors:
Gizelle M McCarthy, Sean P Farris, Yuri A Blednov, R Adron Harris, R Dayne Mayfield
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