Ethanol Induced Ataxia Chr#17 rs3672987(33247165) with right flanking marker rs4136382(3388912) and left marker rs3715723(58810428). This was mapped in 300 + (b6x129)F2 mice.
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
The GEO2R tool was used to analyze microarray data from mice either mock-infected or infected with SARS-CoV1. The Gene sets used in the analysis were from GSE59185. GEO2R was used with default parameters. Genes with an adjusted p-value of <0.05 and a log fold change <-1.0 are included in this set. EntrezGene identifiers or sequence identifiers were converted to MGI identifiers. Genes that could not be converted were omitted. If a gene was represented more than once, the largest fold-change was chosen.
Authors:
Jose A Regla-Nava, Jose L Nieto-Torres, Jose M Jimenez-Guardeño, Raul Fernandez-Delgado, Craig Fett, Carlos Castaño-RodrÃguez, Stanley Perlman, Luis Enjuanes, Marta L DeDiego
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
Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. Although prescribed for dyslipidemia and type-II diabetes, PPAR agonists also possess anti-addictive characteristics. PPAR agonists decrease ethanol consumption and reduce withdrawal severity and susceptibility to stress-induced relapse in rodents. However, the cellular and molecular mechanisms facilitating these properties have yet to be investigated. We tested three PPAR agonists in a continuous access two-bottle choice (2BC) drinking paradigm and found that tesaglitazar (PPARα/γ; 1.5 mg/kg) and fenofibrate (PPARα; 150 mg/kg) decreased ethanol consumption in male C57BL/6J mice while bezafibrate (PPARα/γ/β; 75 mg/kg) did not. We hypothesized that changes in brain gene expression following fenofibrate and tesaglitazar treatment lead to reduced ethanol drinking. We studied unbiased genomic profiles in areas of the brain known to be important for ethanol dependence, the prefrontal cortex (PFC) and amygdala, and also profiled gene expression in liver. Genomic profiles from the non-effective bezafibrate treatment were used to filter out genes not associated with ethanol consumption. Because PPAR agonists are anti-inflammatory, they would be expected to target microglia and astrocytes. Surprisingly, PPAR agonists produced a strong neuronal signature in mouse brain, and fenofibrate and tesaglitazar (but not bezafibrate) targeted a subset of GABAergic interneurons in the amygdala. Weighted gene co-expression network analysis (WGCNA) revealed co-expression of treatment-significant genes. Functional annotation of these gene networks suggested that PPAR agonists might act via neuropeptide and dopaminergic signaling pathways in the amygdala. Our results reveal gene targets through which PPAR agonists can affect alcohol consumption behavior.
Authors:
Laura B Ferguson, Dana Most, Yuri A Blednov, R Adron Harris
Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. Although prescribed for dyslipidemia and type-II diabetes, PPAR agonists also possess anti-addictive characteristics. PPAR agonists decrease ethanol consumption and reduce withdrawal severity and susceptibility to stress-induced relapse in rodents. However, the cellular and molecular mechanisms facilitating these properties have yet to be investigated. We tested three PPAR agonists in a continuous access two-bottle choice (2BC) drinking paradigm and found that tesaglitazar (PPARα/γ; 1.5 mg/kg) and fenofibrate (PPARα; 150 mg/kg) decreased ethanol consumption in male C57BL/6J mice while bezafibrate (PPARα/γ/β; 75 mg/kg) did not. We hypothesized that changes in brain gene expression following fenofibrate and tesaglitazar treatment lead to reduced ethanol drinking. We studied unbiased genomic profiles in areas of the brain known to be important for ethanol dependence, the prefrontal cortex (PFC) and amygdala, and also profiled gene expression in liver. Genomic profiles from the non-effective bezafibrate treatment were used to filter out genes not associated with ethanol consumption. Because PPAR agonists are anti-inflammatory, they would be expected to target microglia and astrocytes. Surprisingly, PPAR agonists produced a strong neuronal signature in mouse brain, and fenofibrate and tesaglitazar (but not bezafibrate) targeted a subset of GABAergic interneurons in the amygdala. Weighted gene co-expression network analysis (WGCNA) revealed co-expression of treatment-significant genes. Functional annotation of these gene networks suggested that PPAR agonists might act via neuropeptide and dopaminergic signaling pathways in the amygdala. Our results reveal gene targets through which PPAR agonists can affect alcohol consumption behavior.
Authors:
Laura B Ferguson, Dana Most, Yuri A Blednov, R Adron Harris
Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. Although prescribed for dyslipidemia and type-II diabetes, PPAR agonists also possess anti-addictive characteristics. PPAR agonists decrease ethanol consumption and reduce withdrawal severity and susceptibility to stress-induced relapse in rodents. However, the cellular and molecular mechanisms facilitating these properties have yet to be investigated. We tested three PPAR agonists in a continuous access two-bottle choice (2BC) drinking paradigm and found that tesaglitazar (PPARα/γ; 1.5 mg/kg) and fenofibrate (PPARα; 150 mg/kg) decreased ethanol consumption in male C57BL/6J mice while bezafibrate (PPARα/γ/β; 75 mg/kg) did not. We hypothesized that changes in brain gene expression following fenofibrate and tesaglitazar treatment lead to reduced ethanol drinking. We studied unbiased genomic profiles in areas of the brain known to be important for ethanol dependence, the prefrontal cortex (PFC) and amygdala, and also profiled gene expression in liver. Genomic profiles from the non-effective bezafibrate treatment were used to filter out genes not associated with ethanol consumption. Because PPAR agonists are anti-inflammatory, they would be expected to target microglia and astrocytes. Surprisingly, PPAR agonists produced a strong neuronal signature in mouse brain, and fenofibrate and tesaglitazar (but not bezafibrate) targeted a subset of GABAergic interneurons in the amygdala. Weighted gene co-expression network analysis (WGCNA) revealed co-expression of treatment-significant genes. Functional annotation of these gene networks suggested that PPAR agonists might act via neuropeptide and dopaminergic signaling pathways in the amygdala. Our results reveal gene targets through which PPAR agonists can affect alcohol consumption behavior.
Authors:
Laura B Ferguson, Dana Most, Yuri A Blednov, R Adron Harris
Authors develop a brain reward circuit-wide atlas of opioid-induced transcriptional regulation by combining RNA sequencing (RNA-seq) and heroin self-administration in male mice modeling multiple OUD-relevant conditions: acute heroin exposure, chronic heroin intake, context-induced drug-seeking following abstinence, and relapse. Bioinformatics analysis of this rich dataset identified numerous patterns of transcriptional regulation, with both region-specific and pan-circuit biological domains affected by heroin. Integration of RNA-seq data. This design enabled investigation of the transcriptomic landscape in multiple conditions that model distinct aspects of the OUD syndrome: first-ever heroin exposure (SH), ongoing/early withdrawal from heroin intake (H24), context-induced heroin-seeking following protracted abstinence (HS), and a combination of drug-induced and context-induced heroin-seeking representative of a relapse-like episode (HH). with OUD-relevant behavioral outcomes uncovered region-specific molecular changes and biological processes that predispose to OUD vulnerability.
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "cytoplasm", which is defined as "All of the contents of a cell excluding the plasma membrane and nucleus, but including other subcellular structures." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "biological_process", which is defined as "Any process specifically pertinent to the functioning of integrated living units: cells, tissues, organs, and organisms. A process is a collection of molecular events with a defined beginning and end." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "metabolic process", which is defined as "The chemical reactions and pathways, including anabolism and catabolism, by which living organisms transform chemical substances. Metabolic processes typically transform small molecules, but also include macromolecular processes such as DNA repair and replication, and protein synthesis and degradation." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "cell", which is defined as "The basic structural and functional unit of all organisms. Includes the plasma membrane and any external encapsulating structures such as the cell wall and cell envelope." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "intracellular", which is defined as "The living contents of a cell; the matter contained within (but not including) the plasma membrane, usually taken to exclude large vacuoles and masses of secretory or ingested material. In eukaryotes it includes the nucleus and cytoplasm." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "intracellular part", which is defined as "Any constituent part of the living contents of a cell; the matter contained within (but not including) the plasma membrane, usually taken to exclude large vacuoles and masses of secretory or ingested material. In eukaryotes it includes the nucleus and cytoplasm." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "peptide metabolic process", which is defined as "The chemical reactions and pathways involving peptides, compounds of two or more amino acids where the alpha carboxyl group of one is bound to the alpha amino group of another." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "organonitrogen compound metabolic process", which is defined as "The chemical reactions and pathways involving organonitrogen compound." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "organonitrogen compound biosynthetic process", which is defined as "The chemical reactions and pathways resulting in the formation of organonitrogen compound." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "biosynthetic process", which is defined as "The chemical reactions and pathways resulting in the formation of substances; typically the energy-requiring part of metabolism in which simpler substances are transformed into more complex ones." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "macromolecule biosynthetic process", which is defined as "The chemical reactions and pathways resulting in the formation of a macromolecule, any molecule of high relative molecular mass, the structure of which essentially comprises the multiple repetition of units derived, actually or conceptually, from molecules of low relative molecular mass." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
GeneWeaver