The Drug Related Gene Database (DRG), funded by National Institute of Drug Abuse (NIDA) ARRA Supplement #HHSN27120080035C, was created to facilitate discovery and use of resources relevant to drug abuse research.  The database and associated tools were specifically created for providing data that is contained in tables, figures and supplementary materials from published papers in a way that facilitates search across the results of these studies.  These data are extracted from published journal articles that directly test hypotheses relevant to the neuroscience of addiction and addictive behavior.  The current database mainly focuses on gene expression data and exposes data from investigations using DNA microarrays, polymerase chain reaction, immunohistochemistry and in-situ hybridizations. Data types include the effects of a particular drug, strain, or knock out on a particular gene, in a particular anatomical region. Once loaded, these data are available for query through the NIF interface.  During this process, the content is standardized using a generic high level description of a relevant study and terms are mapped to ontologies available through the NIF project (NIFSTD) to enhance semantic search of such data. 

Table of Contents:

Publications whose tables are available through DRG

Instructions for authors - submit your data to the DRG

Step by step example of a submission: 

Click here to find step by step instructions using a specific example from Grice et al. (2007) Transcriptional profiling of C57 and DBA strains of mice in the absence and presence of morphine.   BMC Genomics. Mar 16;8:76.  These sample data are included in the Excel template provided in the instructions to authors on the 3rd tab (worksheet) or you may download them directly

Resources for Submission Testers:

Click here for some resources identified for submission testers that may be good to add to the DRG. For your convenience, data has already been extracted.

Database issues below:

Articles requiring a subscription to access:

Table 2. Brain CYP2D protein immunocytochemical staining in saline- and chronic nicotine-treated monkeys

Table 4. Genes groups differentially expressed between smokers and nonsmokers (P < 0.05)

Table 6. QRT-PCR confirmation of microarray gene expression changes

Supplemental Table 2. Probe sets on the Affymetrix U95Av2 chips for genes expressed in the NMDA postsynaptic density

Supplemental Table 3.  All genes differentially expressed between smokers and nonsmokers (p<0.05)

Supplemental Table 4. All genes differentially expressed by the interaction of schizophrenia x smoking

Table 2. Results DNA microarrays: chronic morphine treatment vs. saline treatment (control)

Table 3. Results DNA-microarrays: naloxone precipitated morphine withdrawal vs. saline treatment (control)

Table 1. Summary of brain areas expressing NuIP protein and Nurr1.

Table 1. Mean number of Fos positive cells and associated statistics after saline, 15 or 30 mg/kg cocaine

Table 2. The difference in cocaine-induced Fos between adolescents and adults after correcting for locomotor activity

Table 3. Mean number of Fos positive cells and associated statistics after saline, 2, or 4 mg/kg methamphetamine

Table 4. The difference in methamphetamine-induced Fos between adolescents and adults after correcting for locomotor activity

Fig. 3. Striatal c-fos induction in E22 fetuses: prenatal ethanol and cocaine treatments.

Table 1. Fos expression in neonatal rats at 0, 3, and 24 h after C-section

Table 2. Caspase-3 expression in neonatal rats at 0, 3, and 24 h after C-section

Fig. 6. Striatal caspase-3 induction in E22 fetuses: prenatal ethanol and cocaine treatments.

Table 2. Hypothalamic genes with highest fold regulation by morphine

Table 3. Pituitary genes with highest fold regulation by morphine

Table 4. Genes involved in the food intake pathway as elucidated by microarray analysis

Table 5. Real-time RT-PCR results compared with microarray data (expressed as percent of control)

Table 2. Overview of mating-induced Fos and Meth-induced pERK expression in brain areas where sex and drugs activate non-overlapping neural populations

Table 3. Overview of mating-induced Fos and Meth-induced pERK expression in brain areas where neural activation was induced only by mating

Fig. 2. Sex-induced Fos and Meth-induced pERK expression in Nac, BLA and ACA neurons 10 min following administration of 4mg/kg Meth.

Fig. 4, Sex-induced Fos and Meth-induced pERK expression in NAc, BLA, and ACA neurons 15 min following administration of 4 mg/kg Meth.

Table 1. Apoptosis-related genes affected in the frontal and occipital regions of the fetal mouse cerebral wall by chronic cocaine exposure

Publications without direct link to tables:

                TABLE IV. Partial list of cocaine-regulated genes in the rat caudate putamen

Table 2. Brain CYP2D protein immunocytochemical staining in saline- and chronic nicotine-treated monkeys

Table 1: Genes significantly changed after cocaine CPP treatment in the hippocampus

Table 2: Reverse transcriptase--polymerase chain reaction confirmation for selected genes changed after cocaine CPP treatment in the hippocampus and cortex

Table 3 - Differentially expressed genes common to both the NA and PFC.

Table 4 - Comparison of gene expression of selected genes using microarray and RT-PCR.

Table 5 - Differentially expressed genes in the PFC in major functional groups.

Table 6 - Genes differentially expressed in the alcoholic NA in major functional groups.

Table II. Genes with Altered Expression in Subjects With a History of Alcohol Abuse/Dependence

Table 4. Genes groups differentially expressed between smokers and nonsmokers (P < 0.05)

Table 6. QRT-PCR confirmation of microarray gene expression changes

Supplemental Table 2. Probe sets on the Affymetrix U95Av2 chips for genes expressed in the NMDA postsynaptic density

Supplemental Table 3.  All genes differentially expressed between smokers and nonsmokers (p<0.05)

Supplemental Table 4. All genes differentially expressed by the interaction of schizophrenia x smoking

Table 2. Myelin-Related Expression Data

Table 3. Genes That Meet the Criteria for Differential Expression on the cDNA (GS-1, GS-2) Array

Table 4. Genes That Meet the Criteria for Differential Expression on the Oligonucleotide (A-1, A-2) Arrays

Table 4 - Differential expression values for genes involved in global processes

Table 5 - Differential expression values for genes involved in specific signaling processes

Additional data file 2 - List of probe-sets of genes differentially expressed among the four inbred strains of mice.

Additional data file 3 - Detailed description of Gene Ontology analysis presented in Table 1 and Table 2.

Table 2. Results DNA microarrays: chronic morphine treatment vs. saline treatment (control)

Table 3. Results DNA-microarrays: naloxone precipitated morphine withdrawal vs. saline treatment (control)

TABLE 1 - Relative lntensity of c-fos mRNA signals in rat brain 1 hr after naloxone-precipitated morphine withdrawal

Table 1. Summary of brain areas expressing NuIP protein and Nurr1.

Table 3. Genes expressed at significantly (P < /= 0.01) higher levels in hippocampus of iP than iNP rats

Table 4. Genes expressed at significantly (P < /= 0.01) lower levels in the hippocampus of iP than iNP rats

Table 1. Mean number of Fos positive cells and associated statistics after saline, 15 or 30 mg/kg cocaine

Table 2. The difference in cocaine-induced Fos between adolescents and adults after correcting for locomotor activity

Table 3. Mean number of Fos positive cells and associated statistics after saline, 2, or 4 mg/kg methamphetamine

Table 4. The difference in methamphetamine-induced Fos between adolescents and adults after correcting for locomotor activity

Fig. 3. Striatal c-fos induction in E22 fetuses: prenatal ethanol and cocaine treatments.

Table 1. Fos expression in neonatal rats at 0, 3, and 24 h after C-section

Table 2. Caspase-3 expression in neonatal rats at 0, 3, and 24 h after C-section

Fig. 6. Striatal caspase-3 induction in E22 fetuses: prenatal ethanol and cocaine treatments.

Table 2. Hypothalamic genes with highest fold regulation by morphine

Table 3. Pituitary genes with highest fold regulation by morphine

Table 4. Genes involved in the food intake pathway as elucidated by microarray analysis

Table 5. Real-time RT-PCR results compared with microarray data (expressed as percent of control)

Table 2. Mu opioid receptor-dependent genes regulated by chronic morphine in the lateral hypothalamus (LH)

Table 3. qPCR analysis of chronic morphine treatments for selected LH genes

Table 2. Overview of mating-induced Fos and Meth-induced pERK expression in brain areas where sex and drugs activate non-overlapping neural populations

Table 3. Overview of mating-induced Fos and Meth-induced pERK expression in brain areas where neural activation was induced only by mating

Fig. 2. Sex-induced Fos and Meth-induced pERK expression in Nac, BLA and ACA neurons 10 min following administration of 4mg/kg Meth.

Fig. 4, Sex-induced Fos and Meth-induced pERK expression in NAc, BLA, and ACA neurons 15 min following administration of 4 mg/kg Meth.

Table 1. Apoptosis-related genes affected in the frontal and occipital regions of the fetal mouse cerebral wall by chronic cocaine exposure

Publications without direct link to methods (treatment):
Stability of Probe IDs:

Microarray manufacturers were individually questioned about the stability of their probe ids - if they change over time.  For your information, below we have their individual replies:

Illumina:  "The probes ID is an unique internal Illumina reference and can change between chip versions."

and
"Just to clarify, "PROBE_ID" is a unique probe identifier in the Illumina manufacturing database that distinguishes a probe across all products and all species. This should be consistent from chip to chip and if you see the same probe on different versions of a manifest, the probe sequence would be the same."

techsupport@illumina.com

NimbleGen:

"Probe IDs are linked to the design name. If the name is the same, then so are the probe IDs."

and

"The PROBE_IDs within an NDF file are fixed and do not change. So long as the design name (or better yet, the DESIGN_ID) is the same then the PROBE_ID should be stable provided the end user didn't manually edit anything."

"It is worth pointing out that there is no guarantee that PROBE_ID will be unique within a design file. It is always best to HASH on the union of CONTAINER|GENE_EXPR_OPTION, SEQ_ID, and PROBE_ID if you want to insure uniqueness."

biochemts.us@roche.com

Affymetrix:
"The probe ids do not change over time."

"The sequences that they interrogate may change over time because more genes get discovered, and others may change depending on the validation by the scientific community.
The changes for the sequences will be reflected in the annotation updates.
The annotation updates are released three times yearly in mid-March, July and November for all arrays. If there is an update in the genome assembly build for a given organism, that update usually is reflected in the following annotation."

"Annotation updates incorporate current releases from GenBank, RefSeq, Ensembl, UniGene, Entrez Gene, UniProt and UCSC, as well as sequences from other organism-specific databases. The sources for each annotation update since release 20 are documented and available on the NetAffx Support Materials Page."
support@affymetrix.com