The human genome is thought to harbor 50,000 to 100,000 genes, of which about half have been sampled to date in the form of expressed sequence tags. An international consortium was organized to develop and map gene-based sequence tagged site markers on a set of two radiation hybrid panels and a yeast artificial chromosome library. More than 16,000 human genes have been mapped relative to a framework map that contains about 1000 polymorphic genetic markers. The gene map unifies the existing genetic and physical maps with the nucleotide and protein sequence databases in a fashion that should speed the discovery of genes underlying inherited human disease. The integrated resource is available through a site on the World Wide Web at http://www.ncbi.nlm.nih.gov/SCIENCE96/.

C57BL/6J (B6) and DBA/2J (D2) are two of the most commonly used inbred mouse strains in neuroscience research. However, the only currently available mouse genome is based entirely on the B6 strain sequence. Subsequently, oligonucleotide microarray probes are based solely on this B6 reference sequence, making their application for gene expression profiling comparisons across mouse strains dubious due to their allelic sequence differences, including single nucleotide polymorphisms (SNPs). The emergence of next-generation sequencing (NGS) and the RNA-Seq application provides a clear alternative to oligonucleotide arrays for detecting differential gene expression without the problems inherent to hybridization-based technologies. Using RNA-Seq, an average of 22 million short sequencing reads were generated per sample for 21 samples (10 B6 and 11 D2), and these reads were aligned to the mouse reference genome, allowing 16,183 Ensembl genes to be queried in striatum for both strains. To determine differential expression, ‘digital mRNA counting’ is applied based on reads that map to exons. The current study compares RNA-Seq (Illumina GA IIx) with two microarray platforms (Illumina MouseRef-8 v2.0 and Affymetrix MOE 430 2.0) to detect differential striatal gene expression between the B6 and D2 inbred mouse strains. We show that by using stringent data processing requirements differential expression as determined by RNA-Seq is concordant with both the Affymetrix and Illumina platforms in more instances than it is concordant with only a single platform, and that instances of discordance with respect to direction of fold change were rare. Finally, we show that additional information is gained from RNA-Seq compared to hybridization-based techniques as RNA-Seq detects more genes than either microarray platform. The majority of genes differentially expressed in RNA-Seq were only detected as present in RNA-Seq, which is important for studies with smaller effect sizes where the sensitivity of hybridization-based techniques could bias interpretation.

Physiological dependence and associated withdrawal episodes can constitute a powerful motivational force that perpetuates drug use and abuse. Using robust behavioral models of drug physiological dependence in mice, positional cloning, and sequence and expression analyses, we identified an addiction-relevant quantitative trait gene, Mpdz. Our findings provide a framework to define the protein interactions and neural circuit by which this gene's product (multiple PDZ domain protein) affects drug dependence, withdrawal and relapse.

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It is well established that chronic heavy alcohol drinking (CHD) results in significant organ damage, increased susceptibility to infections, and poor outcomes following injury. In contrast, chronic moderate drinking (CMD) has been associated with improved cardiovascular health and immunity. These differential outcomes have been linked to alterations in both innate and adaptive branches of the immune system; however, the mechanisms remain poorly understood. To address this question, we determined the impact of chronic drinking on the transcriptional and functional responses of peripheral blood mononuclear cells (PBMC) collected from male rhesus macaques classified as CMD or CHD after 12 months of voluntary ethanol self-administration. Our analysis suggests that chronic alcohol drinking, regardless of dose alters resting transcriptomes of PBMC, with the largest impact seen in innate immune cells. These transcriptional changes are partially explained by alterations in microRNA profiles. Additionally, chronic alcohol drinking is associated with a dose dependent heightened inflammatory profiled at resting and following LPS stimulation. Moreover, we observed a dose-dependent shift in the kinetics of transcriptional responses to LPS. These findings may explain the dichotomy in clinical and immunological outcomes observed with moderate versus heavy alcohol drinking.

BackgroundThe current study focused on the extent genetic diversity within a species (Mus musculus) affects gene co-expression network structure. To examine this issue, we have created a new mouse resource, a heterogeneous stock (HS) formed from the same eight inbred strains that have been used to create the collaborative cross (CC). The eight inbred strains capture > 90% of the genetic diversity available within the species. For contrast with the HS-CC, a C57BL/6J (B6) × DBA/2J (D2) F2 intercross and the HS4, derived from crossing the B6, D2, BALB/cJ and LP/J strains, were used. Brain (striatum) gene expression data were obtained using the Illumina Mouse WG 6.1 array, and the data sets were interrogated using a weighted gene co-expression network analysis (WGCNA).ResultsGenes reliably detected as expressed were similar in all three data sets as was the variability of expression. As measured by the WGCNA, the modular structure of the transcriptome networks was also preserved both on the basis of module assignment and from the perspective of the topological overlap maps. Details of the HS-CC gene modules are provided; essentially identical results were obtained for the HS4 and F2 modules. Gene ontology annotation of the modules revealed a significant overrepresentation in some modules for neuronal processes, e.g., central nervous system development. Integration with known protein-protein interactions data indicated significant enrichment among co-expressed genes. We also noted significant overlap with markers of central nervous system cell types (neurons, oligodendrocytes and astrocytes). Using the Allen Brain Atlas, we found evidence of spatial co-localization within the striatum for several modules. Finally, for some modules it was possible to detect an enrichment of transcription binding sites. The binding site for Wt1, which is associated with neurodegeneration, was the most significantly overrepresented.ConclusionsDespite the marked differences in genetic diversity, the transcriptome structure was remarkably similar for the F2, HS4 and HS-CC. These data suggest that it should be possible to integrate network data from simple and complex crosses. A careful examination of the HS-CC transcriptome revealed the expected structure for striatal gene expression. Importantly, we demonstrate the integration of anatomical and network expression data.

Previous studies on changes in murine brain gene expression associated with the selection for ethanol preference have used F2 intercross or heterogeneous stock (HS) founders, derived from standard laboratory strains. However, these populations represent only a small proportion of the genetic variance available in Mus musculus. To investigate a wider range of genetic diversity, we selected mice for ethanol preference using an HS derived from the eight strains of the collaborative cross. These HS mice were selectively bred (four generations) for high and low ethanol preference. The nucleus accumbens shell of naive S4 mice was interrogated using RNA sequencing (RNA-Seq). Gene networks were constructed using the weighted gene coexpression network analysis assessing both coexpression and cosplicing. Selection targeted one of the network coexpression modules (greenyellow) that was significantly enriched in genes associated with receptor signaling activity including Chrna7, Grin2a, Htr2a and Oprd1. Connectivity in the module as measured by changes in the hub nodes was significantly reduced in the low preference line. Of particular interest was the observation that selection had marked effects on a large number of cell adhesion molecules, including cadherins and protocadherins. In addition, the coexpression data showed that selection had marked effects on long non-coding RNA hub nodes. Analysis of the cosplicing network data showed a significant effect of selection on a large cluster of Ras GTPase-binding genes including Cdkl5, Cyfip1, Ndrg1, Sod1 and Stxbp5. These data in part support the earlier observation that preference is linked to Ras/Mapk pathways.

Methamphetamine (MA) and neurotransmitter precursors and metabolites such as tyramine, octopamine, and β-phenethylamine stimulate the G protein-coupled trace amine-associated receptor 1 (TAAR1). TAAR1 has been implicated in human conditions including obesity, schizophrenia, depression, fibromyalgia, migraine, and addiction. Additionally TAAR1 is expressed on lymphocytes and astrocytes involved in inflammation and response to infection. In brain, TAAR1 stimulation reduces synaptic dopamine availability and alters glutamatergic function. TAAR1 is also expressed at low levels in heart, and may regulate cardiovascular tone. Taar1 knockout mice orally self-administer more MA than wild type and are insensitive to its aversive effects. DBA/2J (D2) mice express a non-synonymous single nucleotide polymorphism (SNP) in Taar1 that does not respond to MA, and D2 mice are predisposed to high MA intake, compared to C57BL/6 (B6) mice. Here we demonstrate that endogenous agonists stimulate the recombinant B6 mouse TAAR1, but do not activate the D2 mouse receptor. Progeny of the B6XD2 (BxD) family of recombinant inbred (RI) strains have been used to characterize the genetic etiology of diseases, but contrary to expectations, BXDs derived 30–40 years ago express only the functional B6 Taar1 allele whereas some more recently derived BXD RI strains express the D2 allele. Data indicate that the D2 mutation arose subsequent to derivation of the original RIs. Finally, we demonstrate that SNPs in human TAAR1 alter its function, resulting in expressed, but functional, sub-functional and non-functional receptors. Our findings are important for identifying a predisposition to human diseases, as well as for developing personalized treatment options.