QTL Associated with Joint/bone inflammation. On Chromosome 4 with a LOD score= 2.3, p-value =. From a(n) F2 of LEWxF344
Authors:
Wilder RL, Griffiths MM, Remmers EF, Cannon GW, Caspi RR, Kawahito Y, Gulko PS, Longman RE, Dracheva SV, Du Y, Sun SH, Wang J, Shepard JS, Joe B, Ge L, Chen S, Chang L, Hoffman J, Silver PB, Reese VR
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 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 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
Small intestine transcriptome changes in morphine treated mice. Eight-week-old, pathogen free, C57BL/6 male mice were used for this study (morphine n = 5, control n = 5). The animals were anesthetized using isoflurane (Pivetal®) and a 25mg slow-release morphine pellet or placebo pellet was implanted subcutaneously. Treatment lasted 16 hours. mRNA was purified from total RNA from using poly T-magnetic beads and strand specific library was constructed by using NEBNext Ultra RNA library prep kit. After quality control, the libraries were sequenced paired end by using Illumina sequencers (Illumina HiSeq 4000) for a read length of 150 base pairs. Clean reads were mapped to the mouse transcriptome using “STAR” software. The subsequent differential gene expression analysis was performed using DESeq2 R package (log2 (Fold change) > 1, P adj<0.05).
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 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 hypothalamus gene expression in females logFC
Description:
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 hypothalamus gene expression in females q-value
Description:
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 hypothalamus gene expression in males logFC
Description:
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 hypothalamus gene expression in males q-value
Description:
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 log2FC
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
Alcohol transcriptome changes in mice microglia total homogenate log2FC
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
Analysis using RNA-seq of FACS-purified oligodendrocytes revealed a large cohort of morphine-regulated genes. In addition, to investigate cell-type-specific opioid responses, we performed single-cell RNA sequencing (scRNA-seq) of the nucleus accumbens of mice following acute morphine treatment. Differential expression analysis uncovered unique morphine-dependent transcriptional responses by oligodendrocytes and astrocytes.
Authors:
Denis Avey, Sumithra Sankararaman, Aldrin K Y Yim, Ruteja Barve, Jeffrey Milbrandt, Robi D Mitra
DEG female mouse forebrain 3-tri morphine vs saline_pvalue
Description:
To examine forebrain transcriptomic changes that might elucidate mechanisms of withdrawal, delayed development, and any long-term behavior changes, we generated transcriptomic signatures following our “3-trimester” exposure model (3-Tri). In addition, we also examined transcriptomes from animals that received opioids only during the gestational period (PND1) or only during the last trimester from PND 1–14 (PND 14). We sought to determine whether transcriptomic signatures vary based on the window of exposure, perhaps contributing to the discrepancies in the literature regarding acute and long-term outcomes. Brains were dissected from PND 1 pups 6 h after discovery. Brains were dissected from post-natal exposure only (PND 14) or 3-trimester exposure (3-tri) 6 h after the last morphine or saline injection. The number of animals per group was similar (N = 5–7 animals, male and female C57Bl/6NTac mice), and the quality controls, library construction and sequence parameters were also identical across all groups. Libraries were sequenced on a NovaSeq 6000 at a depth of 30 million total reads/sample using paired-end sequencing of 150 base pairs (PE150), to a depth of 30 million total reads/sample. Reads were then mapped to the mouse reference genome (Mus Musculus, GRCm38/mm10) using HISAT2 (version 2.2.1), and duplicated fragments were removed using Picard MarkDuplicates. Differential expression analysis between two conditions (e.g., Morphine and Saline) was performed in R (version 4.1.1) with DESeq2 (v1.32.0) package. Genes were assigned by the authors as differentially expressed if the (adjusted) (nominal) p-value < 0.05. All genes/scores are presented here.
Authors:
Amelia D Dunn, Shivon A Robinson, Chiso Nwokafor, Molly Estill, Julia Ferrante, Li Shen, Crystal O Lemchi, Jordi Creus-Muncunill, Angie Ramirez, Juliet Mengaziol, Julia K Brynildsen, Mark Leggas, Jamie Horn, Michelle E Ehrlich, Julie A Blendy
DEG female mouse forebrain PND14 morphine vs saline_pvalue
Description:
To examine forebrain transcriptomic changes that might elucidate mechanisms of withdrawal, delayed development, and any long-term behavior changes, we generated transcriptomic signatures following our “3-trimester” exposure model (3-Tri). In addition, we also examined transcriptomes from animals that received opioids only during the gestational period (PND1) or only during the last trimester from PND 1–14 (PND 14). We sought to determine whether transcriptomic signatures vary based on the window of exposure, perhaps contributing to the discrepancies in the literature regarding acute and long-term outcomes. Brains were dissected from PND 1 pups 6 h after discovery. Brains were dissected from post-natal exposure only (PND 14) or 3-trimester exposure (3-tri) 6 h after the last morphine or saline injection. The number of animals per group was similar (N = 5–7 animals, male and female C57Bl/6NTac mice), and the quality controls, library construction and sequence parameters were also identical across all groups. Libraries were sequenced on a NovaSeq 6000 at a depth of 30 million total reads/sample using paired-end sequencing of 150 base pairs (PE150), to a depth of 30 million total reads/sample. Reads were then mapped to the mouse reference genome (Mus Musculus, GRCm38/mm10) using HISAT2 (version 2.2.1), and duplicated fragments were removed using Picard MarkDuplicates. Differential expression analysis between two conditions (e.g., Morphine and Saline) was performed in R (version 4.1.1) with DESeq2 (v1.32.0) package. Genes were assigned by the authors as differentially expressed if the (adjusted) (nominal) p-value < 0.05. All genes/scores are presented here.
Authors:
Amelia D Dunn, Shivon A Robinson, Chiso Nwokafor, Molly Estill, Julia Ferrante, Li Shen, Crystal O Lemchi, Jordi Creus-Muncunill, Angie Ramirez, Juliet Mengaziol, Julia K Brynildsen, Mark Leggas, Jamie Horn, Michelle E Ehrlich, Julie A Blendy
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
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 for alcohol preference locus on Chr19 at D19Mit46 (29.54 Mbp , Build 37)
Description:
alcohol preference locus spans 4.54 - 54.54 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 alcohol preference locus on Chr19 at D19Mit46 (29.54 Mbp , Build 37)
Description:
alcohol preference locus spans 4.54 - 54.54 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 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).
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