RNA‐seq was used to investigate the pathology of oxycodone abuse. In order to uncover the potential epitranscriptomic role of m6A methylation in oxycodone abuse, three different doses of saline or oxycodone (1.5, 3.0, and 6.0mg/kg) were administered intraperitoneally (i.p., 0.1mL/10g) to a group of mice for 9 days. Subsequently, after 4 days of oxycodone withdrawal and 1hr after open field testing, striatum samples from the experimental mice were collected for RNA‐sequencing (RNA‐seq) to detect m6A methylation‐associated enzymes and then examine m6A‐related epigenetic alterations. Total RNA was extracted from the striatum (n=3 C57BL/6J mice in each group), and the quantification of lncRNA, ncRNA, and mRNA followed. Quality‐checked libraries were sequenced on the DNBseq platform using MGISEQ‐2000 with 100PE sequencing. Library construction, lncRNA‐seq, ncRNA‐seq, and RNA‐seq, as well as data collection and mapping were outsourced to HuaDa Gene Biotechnology (Shenzhen, China). From supplementary table 1. Please note that the upregulated genes reported in the Results section correspond to negative fold change values in the table, and downregulated correspond to positive fold change values - this may or may not be an error in reporting by the authors.
RNA‐seq was used to investigate the pathology of oxycodone abuse. In order to uncover the potential epitranscriptomic role of m6A methylation in oxycodone abuse, three different doses of saline or oxycodone (1.5, 3.0, and 6.0mg/kg) were administered intraperitoneally (i.p., 0.1mL/10g) to a group of mice for 9 days. Subsequently, after 4 days of oxycodone withdrawal and 1hr after open field testing, striatum samples from the experimental mice were collected for RNA‐sequencing (RNA‐seq) to detect m6A methylation‐associated enzymes and then examine m6A‐related epigenetic alterations. Total RNA was extracted from the striatum (n=3 C57BL/6J mice in each group), and the quantification of lncRNA, ncRNA, and mRNA followed. Quality‐checked libraries were sequenced on the DNBseq platform using MGISEQ‐2000 with 100PE sequencing. Library construction, lncRNA‐seq, ncRNA‐seq, and RNA‐seq, as well as data collection and mapping were outsourced to HuaDa Gene Biotechnology (Shenzhen, China). From supplementary table 1. Please note that the upregulated genes reported in the Results section correspond to negative fold change values in the table, and downregulated correspond to positive fold change values - this may or may not be an error in reporting by the authors.
RNA‐seq was used to investigate the pathology of oxycodone abuse. In order to uncover the potential epitranscriptomic role of m6A methylation in oxycodone abuse, three different doses of saline or oxycodone (1.5, 3.0, and 6.0mg/kg) were administered intraperitoneally (i.p., 0.1mL/10g) to a group of mice for 9 days. Subsequently, after 4 days of oxycodone withdrawal and 1hr after open field testing, striatum samples from the experimental mice were collected for RNA‐sequencing (RNA‐seq) to detect m6A methylation‐associated enzymes and then examine m6A‐related epigenetic alterations. Total RNA was extracted from the striatum (n=3 C57BL/6J mice in each group), and the quantification of lncRNA, ncRNA, and mRNA followed. Quality‐checked libraries were sequenced on the DNBseq platform using MGISEQ‐2000 with 100PE sequencing. Library construction, lncRNA‐seq, ncRNA‐seq, and RNA‐seq, as well as data collection and mapping were outsourced to HuaDa Gene Biotechnology (Shenzhen, China). From supplementary table 1. Please note that the upregulated genes reported in the Results section correspond to negative fold change values in the table, and downregulated correspond to positive fold change values - this may or may not be an error in reporting by the authors.
RNA‐seq was used to investigate the pathology of oxycodone abuse. In order to uncover the potential epitranscriptomic role of m6A methylation in oxycodone abuse, three different doses of saline or oxycodone (1.5, 3.0, and 6.0mg/kg) were administered intraperitoneally (i.p., 0.1mL/10g) to a group of mice for 9 days. Subsequently, after 4 days of oxycodone withdrawal and 1hr after open field testing, striatum samples from the experimental mice were collected for RNA‐sequencing (RNA‐seq) to detect m6A methylation‐associated enzymes and then examine m6A‐related epigenetic alterations. Total RNA was extracted from the striatum (n=3 C57BL/6J mice in each group), and the quantification of lncRNA, ncRNA, and mRNA followed. Quality‐checked libraries were sequenced on the DNBseq platform using MGISEQ‐2000 with 100PE sequencing. Library construction, lncRNA‐seq, ncRNA‐seq, and RNA‐seq, as well as data collection and mapping were outsourced to HuaDa Gene Biotechnology (Shenzhen, China). From supplementary table 1. Please note that the upregulated genes reported in the Results section correspond to negative fold change values in the table, and downregulated correspond to positive fold change values - this may or may not be an error in reporting by the authors.
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "RNA N6-methyladenosine methyltransferase complex", which is defined as "An mRNA methyltransferase complex that catalyzes the post-transcriptional methylation of adenosine to form N6-methyladenosine (m6A). In budding yeast, the MIS complex consists of Mum2p, Ime4p and Slz1p. In vertebrates, the complex consists of METTL3, METTL14 and WTAP." 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 "RNA N6-methyladenosine methyltransferase complex", which is defined as "A RNA methyltransferase complex that catalyzes the post-transcriptional methylation of adenosine to form N6-methyladenosine (m6A). In budding yeast, the MIS complex consists of Mum2p, Ime4p and Slz1p. In vertebrates, the complex consists of METTL3, METTL14 and associated components WTAP, ZC3H13, VIRMA, CBLL1/HAKAI and in some cases of RBM15 (RBM15 or RBM15B)." 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. 0.2.12.
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 "RNA N6-methyladenosine methyltransferase complex", which is defined as "A RNA methyltransferase complex that catalyzes the post-transcriptional methylation of adenosine to form N6-methyladenosine (m6A). In budding yeast, the MIS complex consists of Mum2p, Ime4p and Slz1p. In vertebrates, the complex consists of METTL3, METTL14 and associated components WTAP, ZC3H13, VIRMA, CBLL1/HAKAI and in some cases of RBM15 (RBM15 or RBM15B)." 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. 0.2.12.
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
Postmortem human brain tissue from the putamen region of a total of 48 individuals with Alcohol Use Disorder (AUD) and 51 control individuals were taken and RNA extracted from frozen tissue. Sequencing was carried out using the NovaSeq 6000 (Illumina) platform, and gene expression analysis was carried out with respect to AUD and control samples. Gene symbols from Entrez ids are used and Logbase2 FC as provided by the authors are annotated.
Authors:
Lea Zillich, Eric Poisel, Josef Frank, Jerome C Foo, Marion M Friske, Fabian Streit, Lea Sirignano, Stefanie Heilmann-Heimbach, André Heimbach, Per Hoffmann, Franziska Degenhardt, Anita C Hansson, Georgy Bakalkin, Markus M Nöthen, Marcella Rietschel, Rainer Spanagel, Stephanie H Witt
Transcriptional alterations in dorsolateral prefrontal cortex and nucleus accumbens implicate neuroinflammation and synaptic remodeling in opioid use disorder. Transcriptomic profile of 20 control subjects and 20 OUD subjects in brain region DLPFC and NAC. Analyzed using GEO2R (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE174409) separately for each brain region, comparing OUD and control samples.
Authors:
Xiangning Xue, Wei Zong, Jill R Glausier, Sam-Moon Kim, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Marianne L Seney, Ryan W Logan
Transcriptional alterations in dorsolateral prefrontal cortex and nucleus accumbens implicate neuroinflammation and synaptic remodeling in opioid use disorder. Transcriptomic profile of 20 control subjects and 20 OUD subjects in brain region DLPFC and NAC. Analyzed using GEO2R (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE174409) separately for each brain region, comparing OUD and control samples.
Authors:
Xiangning Xue, Wei Zong, Jill R Glausier, Sam-Moon Kim, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Marianne L Seney, Ryan W Logan
Postmortem tissue samples of the dorsolateral prefrontal cortex (DLPFC) from 153 deceased individuals (Mage = 35.4; 62% male; 77% European ancestry). Study groups included 72 brain samples from individuals who died of acute opioid intoxication, 53 psychiatric controls, and 28 normal controls. Whole transcriptome RNA-sequencing was used to generate exon counts, and differential expression was tested using limma-voom. Analyses were adjusted for relevant sociodemographic characteristics, technical covariates, and cryptic relatedness using quality surrogate variables. Weighted correlation network analysis and gene set enrichment analyses also were conducted.
Authors:
David W Sosnowski, Andrew E Jaffe, Ran Tao, Amy Deep-Soboslay, Chang Shu, Sarven Sabunciyan, Joel E Kleinman, Thomas M Hyde, Brion S Maher
Opioid controls_human_ dorsolateral prefrontal cortex and nucleus accumbens_coefficient
Description:
RNA sequencing on the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc) from unaffected comparison subjects (n = 20) and subjects diagnosed with opioid use disorder OUD (n = 20). Transcriptomic analyses identified differentially expressed transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric orderlap.transcriptional differences by brain region in unaffected comparison subjects, finding unique transcriptional profiles in the DLPFC and NAc
Authors:
Marianne L Seney, Sam-Moon Kim, Jill R Glausier, Mariah A Hildebrand, Xiangning Xue, Wei Zong, Jiebiao Wang, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Zachary Freyberg, Ryan W Logan
Opioid controls_human_ dorsolateral prefrontal cortex and nucleus accumbens_qvalue
Description:
RNA sequencing on the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc) from unaffected comparison subjects (n = 20) and subjects diagnosed with opioid use disorder OUD (n = 20). Transcriptomic analyses identified differentially expressed transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric orderlap.transcriptional differences by brain region in unaffected comparison subjects, finding unique transcriptional profiles in the DLPFC and NAc
Authors:
Marianne L Seney, Sam-Moon Kim, Jill R Glausier, Mariah A Hildebrand, Xiangning Xue, Wei Zong, Jiebiao Wang, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Zachary Freyberg, Ryan W Logan
Opioid use disorder_human_dorsolateral prefrontal cortex_coefficient
Description:
RNA sequencing on the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc) from unaffected comparison subjects (n = 20) and subjects diagnosed with opioid use disorder OUD (n = 20). Transcriptomic analyses identified differentially expressed transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric orderlap.transcriptional differences by brain region in unaffected comparison subjects, finding unique transcriptional profiles in the DLPFC and NAc
Authors:
Marianne L Seney, Sam-Moon Kim, Jill R Glausier, Mariah A Hildebrand, Xiangning Xue, Wei Zong, Jiebiao Wang, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Zachary Freyberg, Ryan W Logan
Opioid use disorder_human_nucleus accumbens_coefficient
Description:
RNA sequencing on the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc) from unaffected comparison subjects (n = 20) and subjects diagnosed with opioid use disorder OUD (n = 20). Transcriptomic analyses identified differentially expressed transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric orderlap.transcriptional differences by brain region in unaffected comparison subjects, finding unique transcriptional profiles in the DLPFC and NAc
Authors:
Marianne L Seney, Sam-Moon Kim, Jill R Glausier, Mariah A Hildebrand, Xiangning Xue, Wei Zong, Jiebiao Wang, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Zachary Freyberg, Ryan W Logan
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Corradin et al. 2022_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Corradin et al. 2022_qvalue
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Sosnowski et al 2022_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Sosnowski et al 2022_qvalue
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Striatum Gene Expression Correlates for C1VCOUNT15 measured in BXD RI Males obtained using GeneNetwork Striatum M430V2 (Apr05) RMA. The C1VCOUNT15 measures Open Field rears 0-15 min post cocaine under the domain Cocaine. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
Whole Brain Gene Expression Correlates for LD_LIGHT_DIST measured in BXD RI Males obtained using INIA Brain mRNA M430 (Jun06) RMA. The LD_LIGHT_DIST measures Light-Dark Box Total distance traveled in light compartment under the domain Basal Behavior. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
Cerebellum Gene Expression Correlates for LD_LIGHT_DIST measured in BXD RI Males obtained using SJUT Cerebellum mRNA M430 (Mar05) RMA. The LD_LIGHT_DIST measures Light-Dark Box Total distance traveled in light compartment under the domain Basal Behavior. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
Cerebellum Gene Expression Correlates for OF_DIST_10_15 measured in BXD RI Males obtained using SJUT Cerebellum mRNA M430 (Mar05) RMA. The OF_DIST_10_15 measures Open Field - Total distance traveled 10-15 minutes under the domain Basal Behavior. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
GeneWeaver