Average rotarod training latency Chr# 5 rs13478110 (9741228) with right flanking marker rs13478092(3595407) and left marker rs3718776 (150393227). 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
Differential gene expression in nucleus accumbens somatostatin interneurons_cocaine_mice_pvalue
Description:
To characterize transcriptional alterations that cocaine induces in these cells, we perform cell type-specific RNA-sequencing on FACS-isolated nuclei of somatostatin interneurons and identified 1100 DETs enriched for processes related to neural plasticity. To profile the entire (non poly-A selected) transcriptome of NAc somatostatin interneurons, we generated a transgenic reporter line (SST-TLG498 mice) to label the nuclei of these cells with a modified form of EGFP that is retained in the nuclear membrane (EGFP-F)22, enabling their isolation from NAc dissections using FACS. We succeeded in FACS-isolating nuclei suitable for RNA-sequencing from individual SST-TLG498 mice. We proceeded with differential expression analysis of the RNA-sequencing data to identify differentially expressed transcripts (DETs) in NAc somatostatin interneurons in response to repeated cocaine exposure: 778 transcripts were upregulated by cocaine and 322 were downregulated.
Authors:
Efrain A Ribeiro, Marine Salery, Joseph R Scarpa, Erin S Calipari, Peter J Hamilton, Stacy M Ku, Hope Kronman, Immanuel Purushothaman, Barbara Juarez, Mitra Heshmati, Marie Doyle, Casey Lardner, Dominicka Burek, Ana Strat, Stephen Pirpinias, Ezekiell Mouzon, Ming-Hu Han, Rachael L Neve, Rosemary C Bagot, Andrew Kasarskis, Ja Wook Koo, Eric J Nestler
Genes identified as expressed higher (up) in the AJ strain than in the NOD strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed higher (up) in the AJ strain than in the NOD strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed higher (up) in the AJ strain than in the NZO strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed higher (up) in the AJ strain than in the S129 strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed higher (up) in the AJ strain than in the NZO strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed higher (up) in the AJ strain than in the S129 strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed lower (down) in the AJ strain than in the CAST strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed lower (down) in the AJ strain than in the CAST strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Acute and chronic alcohol exposure was analyzed in 534 (C57BL/6J x C3H/HeJ)F2 mice. Behavioral testing was done using 5 traits, acute drug effect, forced ethanol drinking, withdrawal studies ethanol preference and stress induced ethanol drinking. The following QTL were found in a genome wide scan: Following the QTL is the Chromosome , cM location, and LOD score, Eih1 (Chr 1, 85 cM, LOD 6.6), Eih2 (Chr 7, 10 cM, LOD 3.6), Ceih1 (Chr 3, 55 cM, LOD 4.1), Ceih2 (Chr 6, 24.7 cM, LOD 4.1), Ceih3 (Chr 13, 39 cM, LOD 4.1), Eia1(Chr 1, 65 cM, LOD 10.3 and 10.4), Eiwa1 (Chr 7, 50 cM, LOD 4.4), Eiwa2(Chr 11, 43.1 cM, LOD 4.1),Aldd1(Chr 5, 42 cM, LOD 13.2), Aldd2(Chr 12, 18 cM, LOD 5.3),Eiwax1(Chr 1, 79 cM, LOD 6.5), Eiwax2(Chr 5, 59 cM, LOD 15.0), Eiwax3(Chr 12, 21 cM, LOD 3.6), Methp1(Chr 16, 31.4 cM, LOD 4.3), Mec1(Chr 16, 19.4 cM, LOD 5.1), Epbs1(Chr 16, 33 cM, LOD 4.1), Ecbs1(Chr 16, 29.4 cM, LOD 4.8), Mec2(Chr 1, 109 cM, LOD 3.9), Mec3(Chr 2, 109 cM, LOD 4.3), Mec4(Chr 5, 29 cM, LOD 3.9), Mec5(Chr 10, 2 cM, LOD 5.0), Mec6(Chr 15, 49 cM, LOD 5.2, 95% CI 6.7–56.7).
Authors:
Drews E, Rcz I, Lacava AD, Barth A, Bilkei-Gorz A, Wienker TF, Zimmer A
QTL for Voluntary Ethanol Consumption on LS x SS RI lines spans 43765164-93765164 .This interval was obtained by using an arbitrary interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org). Chr 15 D15Mit3 39 cM VEC (females) 0.02
534 differentially expressed genes in the prefrontal cortex of adult male C57BL/6J mice within 7 d of withdrawal from chronic cocaine. Gene expression was evaluated using RNA-seq, and validation of DEGs was performed using RT-qPCR. Data taken from Supplemental Table S4. Values presented are log2 fold change. Data can be accessed from GEO with accession # GSE89572.
Authors:
Mingzhen Li, Peng Xu, Yanhua Xu, Huajing Teng, Weiping Tian, Quansheng Du, Mei Zhao
Drug NaĂŻve DO mice were tested for open field, light dark, hole board, novelty place preference before collecting the striatum. RNA-Seq data was analyzed with WGCNA using a soft thresholding power of 3 selected using the WGCNA scale-free topology R2 threshold of 0.9, signed network with a minimum module size of 30, correlation type is bicor, used numeric labels.
Drug NaĂŻve DO mice were tested for open field, light dark, hole board, novelty place preference before collecting the striatum. RNA-Seq data was analyzed with paraclique using a bicor was used with a correlation coefficient threshold of |0.5| (unsigned), minimum seed clique size of 5, minimum finished paraclique size of 10, proportional glom factor of 0.2 for paraclique construction.
Microglia depletion and alcohol gene expression logFC
Description:
Alcohol abuse induces changes in microglia morphology and immune function, but whether microglia initiate or simply amplify the harmful effects of alcohol exposure is still a matter of debate. Here, we determine microglia function in acute and voluntary drinking behaviors using a colony-stimulating factor 1 receptor inhibitor (PLX5622). We show that microglia depletion does not alter the sedative or hypnotic effects of acute intoxication. Microglia depletion also does not change the escalation or maintenance of chronic voluntary alcohol consumption. Transcriptomic analysis revealed that although many immune genes have been implicated in alcohol abuse, down regulation of microglia genes does not necessitate changes in alcohol intake. Instead, microglia depletion and chronic alcohol result in compensatory upregulation of alcohol-responsive, reactive astrocyte genes, indicating astrocytes may play a role in regulation of these alcohol behaviors. Taken together, our behavioral and transcriptional data indicate that microglia are not theprimary effector cell responsible for regulation of acute and voluntary alcohol behaviors. Because microglia depletion did not regulate acute or voluntary alcohol behaviors, we hypothesized that these doses were insufficient to activate microglia and recruit them to an effector phenotype. Therefore, we used a model of repeated immune activation using polyinosinic:polycytidylic acid
We investigated the role of microglia in a mouse model of alcohol dependence using a colony stimulating factor 1 receptor inhibitor (PLX5622) to deplete microglia and a chronic intermittent ethanol vapor two-bottle choice drinking procedure. Additionally, we examined anxiety-like behavior during withdrawal. We then analyzed synaptic neuroadaptations in the central nucleus of the amygdala (CeA) and gene expression changes in the medial prefrontal cortex (mPFC) and CeA from the same animals used for behavioral studies.
In the present study Aaq1, a previously mapped QTL on mouse Chromosome 15 linked to alcohol acceptance, is confirmed using a (C57BL/6J x DBA/2J)F2 population. Aaq1 mapped to 15 cM (D15Mit60)- 48 cM (D15Mit34) on mouse Chromosome 15 with a peak LOD score of 3.8 at approximately 30 cM. C57BL/6J-derived alleles confer increased alcohol acceptance in a dominant fashion at Aaq1. A potential candidate gene for Aaq1 is the peripheral benzodiazepine receptor gene, Bzrp.
Authors:
McClearn GE, Tarantino LM, Rodriguez LA, Jones BC, Blizard DA, Plomin R
QTL associated with Avp transcript abundance QTL 3. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (85473357)
QTL associated with body growth late QTL 10. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (81241701)
Authors:
Cheverud JM, Routman EJ, Duarte FA, van Swinderen B, Cothran K, Perel C
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