Detection, validation, and downstream analysis of allelic variation in gene expression

Rhes, a striatal enriched protein, regulates post-translational small-ubiquitin-like-modifier (SUMO) modification of nuclear proteins and alters gene expression

Rhes (Ras homolog enriched in the striatum), a multifunctional protein that regulates striatal functions associated with motor behaviors and neurological diseases, can shuttle from cell to cell via the formation of tunneling-like nanotubes (TNTs). However, the mechanisms by which Rhes mediates diverse functions remain unclear. Rhes is a small GTPase family member which contains a unique C-terminal Small Ubiquitin-like Modifier (SUMO) E3-like domain that promotes SUMO post-translational modification of proteins (SUMOylation) by promoting "cross-SUMOylation" of the SUMO enzyme SUMO E1 (Aos1/Uba2) and SUMO E2 ligase (Ubc-9). Nevertheless, the identity of the SUMO substrates of Rhes remains largely unknown. Here, by combining high throughput interactome and SUMO proteomics, we report that Rhes regulates the SUMOylation of nuclear proteins that are involved in the regulation of gene expression. Rhes increased the SUMOylation of histone deacetylase 1 (HDAC1) and histone 2B, while decreasing SUMOylation of heterogeneous nuclear ribonucleoprotein M (HNRNPM), protein polybromo-1 (PBRM1) and E3 SUMO-protein ligase (PIASy). We also found that Rhes itself is SUMOylated at 6 different lysine residues (K32, K110, K114, K120, K124, and K245). Furthermore, Rhes regulated the expression of genes involved in cellular morphogenesis and differentiation in the striatum, in a SUMO-dependent manner. Our findings thus provide evidence for a previously undescribed role for Rhes in regulating the SUMOylation of nuclear targets and in orchestrating striatal gene expression via SUMOylation.

Genetic architecture of protein expression and its regulation in the mouse brain

BACKGROUND

Natural variation in protein expression is common in all organisms and contributes to phenotypic differences among individuals. While variation in gene expression at the transcript level has been extensively investigated, the genetic mechanisms underlying variation in protein expression have lagged considerably behind. Here we investigate genetic architecture of protein expression by profiling a deep mouse brain proteome of two inbred strains, C57BL/6 J (B6) and DBA/2 J (D2), and their reciprocal F1 hybrids using two-dimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) technology.

RESULTS

By comparing protein expression levels in the four mouse strains, we observed 329 statistically significant differentially expressed proteins between the two parental strains and characterized the genetic basis of protein expression. We further applied a proteogenomic approach to detect variant peptides and define protein allele-specific expression (pASE), identifying 33 variant peptides with cis-effects and 17 variant peptides showing trans-effects. Comparison of regulation at transcript and protein levels show a significant divergence.

CONCLUSIONS

The results provide a comprehensive analysis of genetic architecture of protein expression and the contribution of cis- and trans-acting regulatory differences to protein expression.

Overexpression of an alternative allele of carboxyl/choline esterase 4 (CCE04) of Tetranychus urticae is associated with high levels of resistance to the keto-enol acaricide spirodiclofen

BACKGROUND

Spirodiclofen is an acaricide that targets lipid biosynthesis by inhibiting acetyl-coenzyme A carboxylase. Spirodiclofen resistance in spider mites has been previously documented and was associated with overexpression of CYP392E10, a cytochrome P450 mono-oxygenase that metabolizes spirodiclofen. However, additional mechanisms have been suggested in several studies and a carboxyl/choline esterase gene, CCE04, was shown to be overexpressed in two genetically different strains, SR-VP and SR-TK, both exhibiting high spirodiclofen resistance levels.

RESULTS

We identified two different CCE04 alleles in both resistant strains, CCE04^SR-VP and CCE04^London , with CCE04^SR-VP being highly overexpressed. Isoelectric focusing analysis confirmed the overexpression of a single esterase isozyme, while copy number and random fragment length polymorphism analysis revealed that CCE04^SR-VP overexpression was more likely due to selection for the CCE04^SR-VP allele rather than gene amplification. Both CCE04 alleles were functionally expressed using the Pichia expression system. Functional enzyme assays revealed only limited kinetic differences between CCE04 isoforms for model substrates. In addition, inhibition/competition experiments with spirodiclofen suggested a similar interaction with both enzymes, whereas its active metabolite, spirodiclofen enol, did not inhibit enzyme activity.

CONCLUSION

Our study suggests that selection with spirodiclofen results in enrichment of a specific allele of CCE04 (CCE04^SR-VP ) in two genetically independent strains, which is highly overexpressed. Based on kinetic enzyme data, however, quantitative rather than qualitative differences between CCE04^SR-VP and CCE04^London seem more likely to be involved in resistance. Our findings are discussed in the light of a possible spirodiclofen resistance mechanism, with sequestration of spirodiclofen by CCE04^SR-VP being a likely hypothesis. © 2019 Society of Chemical Industry.

RNA sequencing profiling of the retina in C57BL/6J and DBA/2J mice: Enhancing the retinal microarray data sets from GeneNetwork

Purpose

The goal of the present study is to provide an independent assessment of the retinal transcriptome signatures of C57BL/6J (B6) and DBA/2J (D2) mice, and to enhance existing microarray data sets for accurately defining the allelic differences in the BXD recombinant inbred strains.

Methods

Retinas from B6 and D2 mice (three of each) were used for the RNA sequencing (RNA-seq) analysis. Transcriptome features were examined for both strains. Differentially expressed genes between the two strains were identified, and bioinformatic analysis was performed to analyze the transcriptome differences between the B6 and D2 strains, including Gene Ontology (GO) analysis, Phenotype and Reactome enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The RNA-seq data were then directly compared with one of the microarray data sets (Department of Defense [DoD] Retina Normal Affy MoGene 2.0 ST RMA Gene Level Microarray Database) hosted on GeneNetwork.

Results

RNA-seq provided an in-depth analysis of the transcriptome of the B6 and D2 retinas with a total of more than 30,000,000 reads per sample. More than 70% of the reads were uniquely mapped, resulting in a total of 18,100 gene counts for all six samples. A total of 1,665 genes were differentially expressed, with 858 of these more highly expressed in the B6 retinas and 807 more highly expressed in the D2 retinas. Several molecular pathways were differentially active between the two strains, including the retinoic acid metabolic process, endoplasmic reticulum lumen, extracellular matrix (ECM) organization, and the PI3K-Akt signaling pathway. The most enriched KEGG pathways were the pentose and glucuronate interconversions pathway, the cytochrome P450 pathway, the protein digestion and absorption pathway, and the ECM-receptor interaction pathway. Each of these pathways had a more than fourfold enrichment. The DoD Normal Retina Microarray Database provided expression profiling for 26,191 annotated transcripts for B6 mouse, D2 mouse, and 53 BXD strains. A total of 13,793 genes in this microarray data set were comparable to the RNA-seq data set. For the B6 and D2 retinas, the RNA-seq data and the microarray data were highly correlated with each other (Pearson's r=0.780 for the B6 mice and 0.784 for D2 mice). These results suggest that the microarray data set can reliably detect differentially expressed genes between the B6 and D2 retinas, with an overall accuracy of 91.1%. Examples of true positive and false positive genes are provided.

Conclusions

Retinal transcriptome features of B6 and D2 mouse strains provide a useful reference for a better understanding of the mouse retina. Generally, the microarray database presented on GeneNetwork shows good agreement with the RNA-seq data, but we note that any allelic difference between B6 and D2 mice should be verified with the latter.

Quantification of allelic differential expression using a simple Fluorescence primer PCR-RFLP-based method

Allelic differential expression (ADE) is common in diploid organisms, and is often the key reason for specific phenotype variations. Thus, ADE detection is important for identification of major genes and causal mutations. To date, sensitive and simple methods to detect ADE are still lacking. In this study, we have developed an accurate, simple, and sensitive method, named fluorescence primer PCR-RFLP quantitative method (fPCR-RFLP), for ADE analysis. This method involves two rounds of PCR amplification using a pair of primers, one of which is double-labeled with an overhang 6-FAM. The two alleles are then separated by RFLP and quantified by fluorescence density. fPCR-RFLP could precisely distinguish ADE cross a range of 1- to 32-fold differences. Using this method, we verified PLAG1 and KIT, two candidate genes related to growth rate and immune response traits of pigs, to be ADE both at different developmental stages and in different tissues. Our data demonstrates that fPCR-RFLP is an accurate and sensitive method for detecting ADE on both DNA and RNA level. Therefore, this powerful tool provides a way to analyze mutations that cause ADE.

Exploring the involvement of Tac2 in the mouse hippocampal stress response through gene networking

Tachykinin 2 (Tac2) is expressed in a number of areas throughout the brain, including the hippocampus. However, knowledge about its function has been only well explored in the hypothalamus in the context of reproductive health. In this study, we identified and validated increased hippocampal Tac2 mRNA expression in response to chronic mild stress in mice. Expression quantitative trait locus (eQTL) analysis showed Tac2 is cis-regulated in the hippocampus. Using a systems genetics approach, we constructed a Tac2 co-expression network to better understand the relationship between Tac2 and the hippocampal stress response. Our network identified 69 total genes associated with Tac2, several of which encode major neuropeptides involved in hippocampal stress signaling as well as critical genes for producing neural plasticity, indicating that Tac2 is involved in these processes. Pathway analysis for the member of Tac2 gene network revealed a strong connection between Tac2 and neuroactive ligand-receptor interaction, calcium signaling pathway, as well as cardiac muscle contraction. In addition, we also identified 46 stress-related phenotypes, specifically fear conditioning response, that were significantly correlated with Tac2 expression. Our results provide evidence for Tac2 as a strong candidate gene who likely plays a role in hippocampal stress processing and neural plasticity.

Ethanol's Effect on Coq7 Expression in the Hippocampus of Mice

Coenzyme Q (CoQ) is a well-studied molecule, present in every cell membrane in the body, best known for its roles as a mitochondrial electron transporter and a potent membrane anti-oxidant. Much of the previous work was done in vitro in yeast and more recent work has suggested that CoQ may have additional roles prompting calls for a re-assessment of its role using in vivo systems in mammals. Here we investigated the putative role of Coenzyme Q in ethanol-induced effects in vivo using BXD RI mice. We examined hippocampal expression of Coq7 in saline controls and after an acute ethanol treatment, noting enriched biologic processes and pathways following ethanol administration. We also identified 45 ethanol-related phenotypes that were significantly correlated with Coq7 expression, including six phenotypes related to conditioned taste aversion and ethanol preference. This analysis highlights the need for further investigation of Coq7 and related genes in vivo as well as previously unrecognized roles that it may play in the hippocampus.

Profiling DNA methylation differences between inbred mouse strains on the Illumina Human Infinium MethylationEPIC microarray

The Illumina Infinium MethylationEPIC provides an efficient platform for profiling DNA methylation in humans at over 850,000 CpGs. Model organisms such as mice do not currently benefit from an equivalent array. Here we used this array to measure DNA methylation in mice. We defined probes targeting conserved regions and performed differential methylation analysis and compared between the array-based assay and affinity-based DNA sequencing of methyl-CpGs (MBD-seq) and reduced representation bisulfite sequencing. Mouse samples consisted of 11 liver DNA from two strains, C57BL/6J (B6) and DBA/2J (D2), that varied widely in age. Linear regression was applied to detect differential methylation. In total, 13,665 probes (1.6% of total probes) aligned to conserved CpGs. Beta-values (β-value) for these probes showed a distribution similar to that in humans. Overall, there was high concordance in methylation signal between the EPIC array and MBD-seq (Pearson correlation r = 0.70, p-value < 0.0001). However, the EPIC probes had higher quantitative sensitivity at CpGs that are hypo- (β-value < 0.3) or hypermethylated (β-value > 0.7). In terms of differential methylation, no EPIC probe detected a significant difference between age groups at a Benjamini-Hochberg threshold of 10%, and the MBD-seq performed better at detecting age-dependent change in methylation. However, the top most significant probe for age (cg13269407; uncorrected p-value = 1.8 x 10-5) is part of the clock CpGs used to estimate the human epigenetic age. For strain, 219 EPIC probes detected significant differential methylation (FDR cutoff 10%) with ~80% CpGs associated with higher methylation in D2. This higher methylation profile in D2 compared to B6 was also replicated by the MBD-seq data. To summarize, we found only a small subset of EPIC probes that target conserved sites. However, for this small subset the array provides a reliable assay of DNA methylation and can be effectively used to measure differential methylation in mice.

Post-genomic behavioral genetics: From revolution to routine

What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www.

RESEARCH

va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

The effect of alcohol on the differential expression of cluster of differentiation 14 gene, associated pathways, and genetic network

Alcohol consumption affects human health in part by compromising the immune system. In this study, we examined the expression of the Cd14 (cluster of differentiation 14) gene, which is involved in the immune system through a proinflammatory cascade. Expression was evaluated in BXD mice treated with saline or acute 1.8 g/kg i.p. ethanol (12.5% v/v). Hippocampal gene expression data were generated to examine differential expression and to perform systems genetics analyses. The Cd14 gene expression showed significant changes among the BXD strains after ethanol treatment, and eQTL mapping revealed that Cd14 is a cis-regulated gene. We also identified eighteen ethanol-related phenotypes correlated with Cd14 expression related to either ethanol responses or ethanol consumption. Pathway analysis was performed to identify possible biological pathways involved in the response to ethanol and Cd14. We also constructed a genetic network for Cd14 using the top 20 correlated genes and present several genes possibly involved in Cd14 and ethanol responses based on differential gene expression. In conclusion, we found Cd14, along with several other genes and pathways, to be involved in ethanol responses in the hippocampus, such as increased susceptibility to lipopolysaccharides and neuroinflammation.

Analyses of differentially expressed genes after exposure to acute stress, acute ethanol, or a combination of both in mice

Alcohol abuse is a complex disorder, which is confounded by other factors, including stress. In the present study, we examined gene expression in the hippocampus of BXD recombinant inbred mice after exposure to ethanol (NOE), stress (RSS), and the combination of both (RSE). Mice were given an intraperitoneal (i.p.) injection of 1.8 g/kg ethanol or saline, and subsets of both groups were exposed to acute restraint stress for 15 min or controls. Gene expression in the hippocampus was examined using microarray analysis. Genes that were significantly (p < 0.05, q < 0.1) differentially expressed were further evaluated. Bioinformatic analyses were predominantly performed using tools available at GeneNetwork.org, and included gene ontology, presence of cis-regulation or polymorphisms, phenotype correlations, and principal component analyses. Comparisons of differential gene expression between groups showed little overlap. Gene Ontology demonstrated distinct biological processes in each group with the combined exposure (RSE) being unique from either the ethanol (NOE) or stress (RSS) group, suggesting that the interaction between these variables is mediated through diverse molecular pathways. This supports the hypothesis that exposure to stress alters ethanol-induced gene expression changes and that exposure to alcohol alters stress-induced gene expression changes. Behavior was profiled in all groups following treatment, and many of the differentially expressed genes are correlated with behavioral variation within experimental groups. Interestingly, in each group several genes were correlated with the same phenotype, suggesting that these genes are the potential origins of significant genetic networks. The distinct sets of differentially expressed genes within each group provide the basis for identifying molecular networks that may aid in understanding the complex interactions between stress and ethanol, and potentially provide relevant therapeutic targets. Using Ptp4a1, a candidate gene underlying the quantitative trait locus for several of these phenotypes, and network analyses, we show that a large group of differentially expressed genes in the NOE group are highly interrelated, some of which have previously been linked to alcohol addiction or alcohol-related phenotypes.

Genetic divergence in the transcriptional engram of chronic alcohol abuse: A laser-capture RNA-seq study of the mouse mesocorticolimbic system

Genetic factors that influence the transition from initial drinking to dependence remain enigmatic. Recent studies have leveraged chronic intermittent ethanol (CIE) paradigms to measure changes in brain gene expression in a single strain at 0, 8, 72 h, and even 7 days following CIE. We extend these findings using LCM RNA-seq to profile expression in 11 brain regions in two inbred strains - C57BL/6J (B6) and DBA/2J (D2) - 72 h following multiple cycles of ethanol self-administration and CIE. Linear models identified differential expression based on treatment, region, strain, or interactions with treatment. Nearly 40% of genes showed a robust effect (FDR < 0.01) of region, and hippocampus CA1, cortex, bed nucleus stria terminalis, and nucleus accumbens core had the highest number of differentially expressed genes after treatment. Another 8% of differentially expressed genes demonstrated a robust effect of strain. As expected, based on similar studies in B6, treatment had a much smaller impact on expression; only 72 genes (p < 0.01) are modulated by treatment (independent of region or strain). Strikingly, many more genes (415) show a strain-specific and largely opposite response to treatment and are enriched in processes related to RNA metabolism, transcription factor activity, and mitochondrial function. Over 3 times as many changes in gene expression were detected in D2 compared to B6, and weighted gene co-expression network analysis (WGCNA) module comparison identified more modules enriched for treatment effects in D2. Substantial strain differences exist in the temporal pattern of transcriptional neuroadaptation to CIE, and these may drive individual differences in risk of addiction following excessive alcohol consumption.

GeneNetwork: A Toolbox for Systems Genetics

The goal of systems genetics is to understand the impact of genetic variation across all levels of biological organization, from mRNAs, proteins, and metabolites, to higher-order physiological and behavioral traits. This approach requires the accumulation and integration of many types of data, and also requires the use of many types of statistical tools to extract relevant patterns of covariation and causal relations as a function of genetics, environment, stage, and treatment. In this protocol we explain how to use the GeneNetwork web service, a powerful and free online resource for systems genetics. We provide workflows and methods to navigate massive multiscalar data sets and we explain how to use an extensive systems genetics toolkit for analysis and synthesis. Finally, we provide two detailed case studies that take advantage of human and mouse cohorts to evaluate linkage between gene variants, addiction, and aging.

RasGRP1 promotes amphetamine-induced motor behavior through a Rhes interaction network ("Rhesactome") in the striatum

The striatum of the brain coordinates motor function. Dopamine-related drugs may be therapeutic to patients with striatal neurodegeneration, such as Huntington's disease (HD) and Parkinson's disease (PD), but these drugs have unwanted side effects. In addition to stimulating the release of norepinephrine, amphetamines, which are used for narcolepsy and attention-deficit/hyperactivity disorder (ADHD), trigger dopamine release in the striatum. The guanosine triphosphatase Ras homolog enriched in the striatum (Rhes) inhibits dopaminergic signaling in the striatum, is implicated in HD and L-dopa-induced dyskinesia, and has a role in striatal motor control. We found that the guanine nucleotide exchange factor RasGRP1 inhibited Rhes-mediated control of striatal motor activity in mice. RasGRP1 stabilized Rhes, increasing its synaptic accumulation in the striatum. Whereas partially Rhes-deficient (Rhes+/-) mice had an enhanced locomotor response to amphetamine, this phenotype was attenuated by coincident depletion of RasGRP1. By proteomic analysis of striatal lysates from Rhes-heterozygous mice with wild-type or partial or complete knockout of Rasgrp1, we identified a diverse set of Rhes-interacting proteins, the "Rhesactome," and determined that RasGRP1 affected the composition of the amphetamine-induced Rhesactome, which included PDE2A (phosphodiesterase 2A; a protein associated with major depressive disorder), LRRC7 (leucine-rich repeat-containing 7; a protein associated with bipolar disorder and ADHD), and DLG2 (discs large homolog 2; a protein associated with chronic pain). Thus, this Rhes network provides insight into striatal effects of amphetamine and may aid the development of strategies to treat various neurological and psychological disorders associated with the striatal dysfunction.

The Genetic Architecture of Murine Glutathione Transferases

Glutathione S-transferase (GST) genes play a protective role against oxidative stress and may influence disease risk and drug pharmacokinetics. In this study, massive multiscalar trait profiling across a large population of mice derived from a cross between C57BL/6J (B6) and DBA2/J (D2)—the BXD family—was combined with linkage and bioinformatic analyses to characterize mechanisms controlling GST expression and to identify downstream consequences of this variation. Similar to humans, mice show a wide range in expression of GST family members. Variation in the expression of Gsta4, Gstt2, Gstz1, Gsto1, and Mgst3 is modulated by local expression QTLs (eQTLs) in several tissues. Higher expression of Gsto1 in brain and liver of BXD strains is strongly associated (P < 0.01) with inheritance of the B6 parental allele whereas higher expression of Gsta4 and Mgst3 in brain and liver, and Gstt2 and Gstz1 in brain is strongly associated with inheritance of the D2 parental allele. Allele-specific assays confirmed that expression of Gsto1, Gsta4, and Mgst3 are modulated by sequence variants within or near each gene locus. We exploited this endogenous variation to identify coexpression networks and downstream targets in mouse and human. Through a combined systems genetics approach, we provide new insight into the biological role of naturally occurring variants in GST genes.

Genetic expression analysis of E2F-associated phosphoprotein in stress responses in the mouse

Dysfunction of the monoaminergic system is critical in stress and anxiety disorders, but the role of each family member in the development of stress-related psychopathologies is not sufficiently understood. Eapp has been reported to be a transcriptional repressor of monoamine oxidase B (Maob) and down-regulates Maob via the Maob core promoter. In the present study, we more specifically examine the role of Eapp in stress responses by testing the hypothesis that Eapp may be involved in the occurrence and development of stress responses. Western blotting, qPCR and immunohistochemistry were used to investigate the expression variation of Eapp in hypothalamus tissue after exposure to stress. The expression of Eapp is controlled by a cis-acting quantitative trait locus (cis-eQTL). Two genes Sphk2 and Nosip, had trans-eQTLs that mapped to the location of Eapp and altered expression of these two genes was shown following siRNA knockdown of Eapp. Additionally, Mmp9, Npy, Npy5r and Maob were shown to have different expression levels in the Eapp knock-down experiments. Our data provide strong evidence that the cis-modulated gene, Eapp, is associated with stress responses, and that validated downstream targets and members of Eapp gene network may also be involved in the development of stress.

A novel heat shock protein alpha 8 (Hspa8) molecular network mediating responses to stress- and ethanol-related behaviors

Genetic differences mediate individual differences in susceptibility and responses to stress and ethanol, although, the specific molecular pathways that control these responses are not fully understood. Heat shock protein alpha 8 (Hspa8) is a molecular chaperone and member of the heat shock protein family that plays an integral role in the stress response and that has been implicated as an ethanol-responsive gene. Therefore, we assessed its role in mediating responses to stress and ethanol across varying genetic backgrounds. The hippocampus is an important mediator of these responses, and thus, was examined in the BXD family of mice in this study. We conducted bioinformatic analyses to dissect genetic factors modulating Hspa8 expression, identify downstream targets of Hspa8, and examined its role. Hspa8 is trans-regulated by a gene or genes on chromosome 14 and is part of a molecular network that regulates stress- and ethanol-related behaviors. To determine additional components of this network, we identified direct or indirect targets of Hspa8 and show that these genes, as predicted, participate in processes such as protein folding and organic substance metabolic processes. Two phenotypes that map to the Hspa8 locus are anxiety-related and numerous other anxiety- and/or ethanol-related behaviors significantly correlate with Hspa8 expression. To more directly assay this relationship, we examined differences in gene expression following exposure to stress or alcohol and showed treatment-related differential expression of Hspa8 and a subset of the members of its network. Our findings suggest that Hspa8 plays a vital role in genetic differences in responses to stress and ethanol and their interactions.

Equalizer reduces SNP bias in Affymetrix microarrays

BACKGROUND

Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans.

RESULTS

By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings.

CONCLUSIONS

The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.

Identification of candidate genes that underlie the QTL on chromosome 1 that mediates genetic differences in stress-ethanol interactions

Alcoholism, stress, and anxiety are strongly interacting heritable, polygenetic traits. In a previous study, we identified a quantitative trait locus (QTL) on murine chromosome (Chr) 1 between 23.0 and 31.5 Mb that modulates genetic differences in the effects of ethanol on anxiety-related phenotypes. The goal of the present study was to extend the analysis of this locus with a focus on identifying candidate genes using newly available data and tools. Anxiety-like behavior was evaluated with an elevated zero maze following saline or ethanol injections (1.8 g/kg) in C57BL/6J, DBA2J, and 72 BXD strains. We detected significant effects of strain and treatment and their interaction on anxiety-related behaviors, although surprisingly, sex was not a significant factor. The Chr1 QTL is specific to the ethanol-treated cohort. Candidate genes in this locus were evaluated using now standard bioinformatic criteria. Collagen 19a1 (Col19a1) and family sequence 135a (Fam135a) met most criteria but have lower expression levels and lacked biological verification and, therefore, were considered less likely candidates. In contrast, two other genes, the prenylated protein tyrosine phosphate family member Ptp4a1 (protein tyrosine phosphate 4a1) and the zinc finger protein Phf3 (plant homeoDomain finger protein 3) met each of our bioinformatic criteria and are thus strong candidates. These findings are also of translational relevance because both Ptp4a1 and Phf3 have been nominated as candidates genes for alcohol dependence in a human genome-wide association study. Our findings support the hypothesis that variants in one or both of these genes modulate heritable differences in the effects of ethanol on anxiety-related behaviors.

Integrative genomics and transcriptomics analysis of human embryonic and induced pluripotent stem cells

Background

Human genomic variations, including single nucleotide polymorphisms (SNPs) and copy number variations (CNVs), are associated with several phenotypic traits varying from mild features to hereditary diseases. Several genome-wide studies have reported genomic variants that correlate with gene expression levels in various tissue and cell types.

Results

We studied human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) measuring the SNPs and CNVs with Affymetrix SNP 6 microarrays and expression values with Affymetrix Exon microarrays. We computed the linear relationships between SNPs and expression levels of exons, transcripts and genes, and the associations between gene CNVs and gene expression levels. Further, for a few of the resulted genes, the expression value was associated with both CNVs and SNPs. Our results revealed altogether 217 genes and 584 SNPs whose genomic alterations affect the transcriptome in the same cells. We analyzed the enriched pathways and gene ontologies within these groups of genes, and found out that the terms related to alternative splicing and development were enriched.

Conclusions

Our results revealed that in the human pluripotent stem cells, the expression values of several genes, transcripts and exons were affected due to the genomic variation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-014-0032-2) contains supplementary material, which is available to authorized users.

Genetic dissection of the Drosophila melanogaster female head transcriptome reveals widespread allelic heterogeneity

Modern genetic mapping is plagued by the “missing heritability” problem, which refers to the discordance between the estimated heritabilities of quantitative traits and the variance accounted for by mapped causative variants. One major potential explanation for the missing heritability is allelic heterogeneity, in which there are multiple causative variants at each causative gene with only a fraction having been identified. The majority of genome-wide association studies (GWAS) implicitly assume that a single SNP can explain all the variance for a causative locus. However, if allelic heterogeneity is prevalent, a substantial amount of genetic variance will remain unexplained. In this paper, we take a haplotype-based mapping approach and quantify the number of alleles segregating at each locus using a large set of 7922 eQTL contributing to regulatory variation in the Drosophila melanogaster female head. Not only does this study provide a comprehensive eQTL map for a major community genetic resource, the Drosophila Synthetic Population Resource, but it also provides a direct test of the allelic heterogeneity hypothesis. We find that 95% of cis-eQTLs and 78% of trans-eQTLs are due to multiple alleles, demonstrating that allelic heterogeneity is widespread in Drosophila eQTL. Allelic heterogeneity likely contributes significantly to the missing heritability problem common in GWAS studies.

For traits with complex genetic inheritance it has generally proven very difficult to identify the majority of the specific causative variants involved. A range of hypotheses have been put forward to explain this so-called “missing heritability”. One idea—allelic heterogeneity, where genes each harbor multiple different causative variants—has received little attention, because it is difficult to detect with most genetic mapping designs. Here we make use of a panel of Drosophila melanogaster lines derived from multiple founders, allowing us to directly test for the presence of multiple alleles at a large set of genetic loci influencing gene expression. We find that the vast majority of loci harbor more than two functional alleles, demonstrating extensive allelic heterogeneity at the level of gene expression and suggesting that such heterogeneity is an important factor determining the genetic basis of complex trait variation in general.

Functionally enigmatic genes: a case study of the brain ignorome

What proportion of genes with intense and selective expression in specific tissues, cells, or systems are still almost completely uncharacterized with respect to biological function? In what ways do these functionally enigmatic genes differ from well-studied genes? To address these two questions, we devised a computational approach that defines so-called ignoromes. As proof of principle, we extracted and analyzed a large subset of genes with intense and selective expression in brain. We find that publications associated with this set are highly skewed--the top 5% of genes absorb 70% of the relevant literature. In contrast, approximately 20% of genes have essentially no neuroscience literature. Analysis of the ignorome over the past decade demonstrates that it is stubbornly persistent, and the rapid expansion of the neuroscience literature has not had the expected effect on numbers of these genes. Surprisingly, ignorome genes do not differ from well-studied genes in terms of connectivity in coexpression networks. Nor do they differ with respect to numbers of orthologs, paralogs, or protein domains. The major distinguishing characteristic between these sets of genes is date of discovery, early discovery being associated with greater research momentum--a genomic bandwagon effect. Finally we ask to what extent massive genomic, imaging, and phenotype data sets can be used to provide high-throughput functional annotation for an entire ignorome. In a majority of cases we have been able to extract and add significant information for these neglected genes. In several cases--ELMOD1, TMEM88B, and DZANK1--we have exploited sequence polymorphisms, large phenome data sets, and reverse genetic methods to evaluate the function of ignorome genes.

Genetics of gene expression in CNS

Transcriptome studies have revealed a surprisingly high level of variation among individuals in expression of key genes in the CNS under both normal and experimental conditions. Ten-fold variation is common, yet the specific causes and consequences of this variation are largely unknown. By combining classic gene mapping methods-family linkage studies and genomewide association-with high-throughput genomics, it is now possible to define quantitative trait loci (QTLs), single-gene variants, and even single SNPs and indels that control gene expression in different brain regions and cells. This review considers some of the major technical and conceptual challenges in analyzing variation in expression in the CNS with a focus on mRNAs, rather than noncoding RNAs or proteins. At one level of analysis, this work has been highly successful, and we finally have techniques that can be used to track down small numbers of loci that control expression in the CNS. But at a higher level of analysis, we still do not understand the genetic architecture of gene expression in brain, the consequences of expression QTLs on protein levels or on cell function, or the combined impact of expression differences on behavior and disease risk. These important gaps are likely to be bridged over the next several decades using (1) much larger sample sizes, (2) more powerful RNA sequencing and proteomic methods, and (3) novel statistical and computational models to predict genome-to-phenome relations.

The genetics of gene expression in complex mouse crosses as a tool to study the molecular underpinnings of behavior traits

Complex Mus musculus crosses provide increased resolution to examine the relationships between gene expression and behavior. While the advantages are clear, there are numerous analytical and technological concerns that arise from the increased genetic complexity that must be considered. Each of these issues is discussed, providing an initial framework for complex cross study design and planning.

SOcK, MiSTs, MASK and STicKs: the GCKIII (germinal centre kinase III) kinases and their heterologous protein-protein interactions

The GCKIII (germinal centre kinase III) subfamily of the mammalian Ste20 (sterile 20)-like group of serine/threonine protein kinases comprises SOK1 (Ste20-like/oxidant-stress-response kinase 1), MST3 (mammalian Ste20-like kinase 3) and MST4. Initially, GCKIIIs were considered in the contexts of the regulation of mitogen-activated protein kinase cascades and apoptosis. More recently, their participation in multiprotein heterocomplexes has become apparent. In the present review, we discuss the structure and phosphorylation of GCKIIIs and then focus on their interactions with other proteins. GCKIIIs possess a highly-conserved, structured catalytic domain at the N-terminus and a less-well conserved C-terminal regulatory domain. GCKIIIs are activated by tonic autophosphorylation of a T-loop threonine residue and their phosphorylation is regulated primarily through protein serine/threonine phosphatases [especially PP2A (protein phosphatase 2A)]. The GCKIII regulatory domains are highly disorganized, but can interact with more structured proteins, particularly the CCM3 (cerebral cavernous malformation 3)/PDCD10 (programmed cell death 10) protein. We explore the role(s) of GCKIIIs (and CCM3/PDCD10) in STRIPAK (striatin-interacting phosphatase and kinase) complexes and their association with the cis-Golgi protein GOLGA2 (golgin A2; GM130). Recently, an interaction of GCKIIIs with MO25 has been identified. This exhibits similarities to the STRADα (STE20-related kinase adaptor α)-MO25 interaction (as in the LKB1-STRADα-MO25 heterotrimer) and, at least for MST3, the interaction may be enhanced by cis-autophosphorylation of its regulatory domain. In these various heterocomplexes, GCKIIIs associate with the Golgi apparatus, the centrosome and the nucleus, as well as with focal adhesions and cell junctions, and are probably involved in cell migration, polarity and proliferation. Finally, we consider the association of GCKIIIs with a number of human diseases, particularly cerebral cavernous malformations.

Expression, covariation, and genetic regulation of miRNA Biogenesis genes in brain supports their role in addiction, psychiatric disorders, and disease

The role of miRNA and miRNA biogenesis genes in the adult brain is just beginning to be explored. In this study we have performed a comprehensive analysis of the expression, genetic regulation, and co-expression of major components of the miRNA biogenesis pathway using human and mouse data sets and resources available on the GeneNetwork web site (genenetwork.org). We found a wide range of variation in expression in both species for key components of the pathway—Drosha, Pasha, and Dicer. Across species, tissues, and expression platforms all three genes are generally well-correlated. No single genetic locus exerts a strong and consistent influence on the expression of these key genes across murine brain regions. However, in mouse striatum, many members of the miRNA pathway are correlated—including Dicer, Drosha, Pasha, Ars2 (Srrt), Eif2c1 (Ago1), Eif2c2 (Ago2), Zcchc11, and Snip1. The expression of these genes may be partly influenced by a locus on Chromosome 9 (105.67–106.32 Mb). We explored ~1500 brain phenotypes available for the C57BL/6J × DBA/2J (BXD) genetic mouse population in order to identify miRNA biogenesis genes correlated with traits related to addiction and psychiatric disorders. We found a significant association between expression of Dicer and Drosha in several brain regions and the response to many drugs of abuse, including ethanol, cocaine, and methamphetamine. Expression of Dicer, Drosha, and Pasha in most of the brain regions explored is strongly correlated with the expression of key members of the dopamine system. Drosha, Pasha, and Dicer expression is also correlated with the expression of behavioral traits measuring depression and sensorimotor gating, impulsivity, and anxiety, respectively. Our study provides a global survey of the expression and regulation of key miRNA biogenesis genes in brain and provides preliminary support for the involvement of these genes and their product miRNAs in addiction and psychiatric disease processes.

Effects of the Ras homolog Rhes on Akt/protein kinase B and glycogen synthase kinase 3 phosphorylation in striatum

G protein-coupled receptors (GPCR) signal not only through heterotrimeric G proteins, but also through alternate pathways. Thus, dopamine D2 receptors in the striatum signal through Gαi/o and also by promoting formation of a multi-protein complex containing β-arrestin2, protein phosphatase 2A (PP2A), and Akt in order to dephosphorylate Akt. Lithium, on the other hand, disrupts this complex to increase Akt phosphorylation. Rhes is a striatally enriched GTP-binding protein that has been shown to inhibit dopamine receptor-mediated behavior and signaling through heterotrimeric G proteins. Therefore, our objective was to test whether Rhes similarly affects signaling through the Akt/GSK3 pathway in the striatum. Rhes(-/-) mice showed basally increased Akt and GSK3β phosphorylation relative to rhes(+/+) mice that was not further enhanced by lithium treatment. Furthermore, they responded to the D1/D2 agonist apomorphine with increased Akt and GSK3 phosphorylation. Co-immunoprecipitation experiments revealed that apomorphine treatment recruits PP 2A-C to Akt in both rhes(+/+) and rhes(-/-) mice. Lithium did not disrupt their interaction in rhes(-/-) mice as there was little basal interaction. Rhes co-immunoprecipitated with β-arrestins, suggesting that it is integral to the multi-protein complex. Thus, Rhes is necessary for Akt dephosphorylation by the striatal multi-protein complex, and in its absence, a lithium-treated phenotype results.

Genetic control of a central pattern generator: rhythmic oromotor movement in mice is controlled by a major locus near Atp1a2

Fluid licking in mice is a rhythmic behavior that is controlled by a central pattern generator (CPG) located in a complex of brainstem nuclei. C57BL/6J (B6) and DBA/2J (D2) strains differ significantly in water-restricted licking, with a highly heritable difference in rates (h(2)≥0.62) and a corresponding 20% difference in interlick interval (mean ± SEM = 116.3±1 vs 95.4±1.1 ms). We systematically quantified motor output in these strains, their F(1) hybrids, and a set of 64 BXD progeny strains. The mean primary interlick interval (MPI) varied continuously among progeny strains. We detected a significant quantitative trait locus (QTL) for a CPG controlling lick rate on Chr 1 (Lick1), and a suggestive locus on Chr 10 (Lick10). Linkage was verified by testing of B6.D2-1D congenic stock in which a segment of Chr 1 of the D2 strain was introgressed onto the B6 parent. The Lick1 interval on distal Chr 1 contains several strong candidate genes. One of these is a sodium/potassium pump subunit (Atp1a2) with widespread expression in astrocytes, as well as in a restricted population of neurons. Both this subunit and the entire Na(+)/K(+)-ATPase molecule have been implicated in rhythmogenesis for respiration and locomotion. Sequence variants in or near Apt1a2 strongly modulate expression of the cognate mRNA in multiple brain regions. This gene region has recently been sequenced exhaustively and we have cataloged over 300 non-coding and synonymous mutations segregating among BXD strains, one or more of which is likely to contribute to differences in central pattern generator tempo.

'maskBAD'--a package to detect and remove Affymetrix probes with binding affinity differences

BACKGROUND

Hybridization differences caused by target sequence differences can be a confounding factor in analyzing gene expression on microarrays, lead to false positives and reduce power to detect real expression differences. We prepared an R Bioconductor compatible package to detect, characterize and remove such probes in Affymetrix 3'IVT and exon-based arrays on the basis of correlation of signal intensities from probes within probe sets.

RESULTS

Using completely mouse genomes we determined type 1 (false negatives) and type 2 (false positives) errors with high accuracy and we show that our method routinely outperforms previous methods. When detecting 76.2% of known SNP/indels in mouse expression data, we obtain at most 5.5% false positives. At the same level of false positives, best previous method detected 72.6%. We also show that probes with differing binding affinity both hinder differential expression detection and introduce artifacts in cancer-healthy tissue comparison.

CONCLUSIONS

Detection and removal of such probes should be a routine step in Affymetrix data preprocessing. We prepared a user friendly R package, compatible with Bioconductor, that allows the filtering and improving of data from Affymetrix microarrays experiments.

Complex control of GABA(A) receptor subunit mRNA expression: variation, covariation, and genetic regulation

GABA type-A receptors are essential for fast inhibitory neurotransmission and are critical in brain function. Surprisingly, expression of receptor subunits is highly variable among individuals, but the cause and impact of this fluctuation remains unknown. We have studied sources of variation for all 19 receptor subunits using massive expression data sets collected across multiple brain regions and platforms in mice and humans. Expression of Gabra1, Gabra2, Gabrb2, Gabrb3, and Gabrg2 is highly variable and heritable among the large cohort of BXD strains derived from crosses of fully sequenced parents—C57BL/6J and DBA/2J. Genetic control of these subunits is complex and highly dependent on tissue and mRNA region. Remarkably, this high variation is generally not linked to phenotypic differences. The single exception is Gabrb3, a locus that is linked to anxiety. We identified upstream genetic loci that influence subunit expression, including three unlinked regions of chromosome 5 that modulate the expression of nine subunits in hippocampus, and that are also associated with multiple phenotypes. Candidate genes within these loci include, Naaa, Nos1, and Zkscan1. We confirmed a high level of coexpression for subunits comprising the major channel—Gabra1, Gabrb2, and Gabrg2—and identified conserved members of this expression network in mice and humans. Gucy1a3, Gucy1b3, and Lis1 are novel and conserved associates of multiple subunits that are involved in inhibitory signaling. Finally, proximal and distal regions of the 3′ UTRs of single subunits have remarkably independent expression patterns in both species. However, corresponding regions of different subunits often show congruent genetic control and coexpression (proximal-to-proximal or distal-to-distal), even in the absence of sequence homology. Our findings identify novel sources of variation that modulate subunit expression and highlight the extraordinary capacity of biological networks to buffer 4–100 fold differences in mRNA levels.

Rhes: a GTP-binding protein integral to striatal physiology and pathology

Rhes, the Ras Homolog Enriched in Striatum, is a GTP-binding protein whose gene was discovered during a screen for mRNAs preferentially expressed in rodent striatum. This 266 amino acid protein is intermediate in size between small Ras-like GTP-binding proteins and α-subunits of heterotrimeric G proteins. It is most closely related to another Ras-like GTP-binding protein termed Dexras1 or AGS1. Although subsequent studies have shown that the rhes gene is expressed in other brain areas in addition to striatum, the striatal expression level is relatively high, and Rhes protein is likely to play a vital role in striatal physiology and pathology. Indeed, it has recently been shown to interact with the Huntingtin protein and play a pivotal role in the selective vulnerability of striatum in Huntington's disease (HD). Not surprisingly, Rhes can interact with multiple proteins to affect striatal physiology at multiple levels. Functional studies have indicated that Rhes plays a role in signaling by striatal G protein-coupled receptors (GPCR), although the details of the mechanism remain to be determined. Rhes has been shown to bind to both α- and β-subunits of heterotrimeric G proteins and to affect signaling by both Gi/o- and Gs/olf-coupled receptors. In this context, Rhes can be classified as a member of the family of accessory proteins to GPCR signaling. With documented effects in dopamine- and opioid-mediated behaviors, an interaction with thyroid hormone systems and a role in HD pathology, Rhes is emerging as an important protein in striatal physiology and pathology.

Genome-wide association for fear conditioning in an advanced intercross mouse line

Fear conditioning (FC) may provide a useful model for some components of post-traumatic stress disorder (PTSD). We used a C57BL/6J × DBA/2J F(2) intercross (n = 620) and a C57BL/6J × DBA/2J F(8) advanced intercross line (n = 567) to fine-map quantitative trait loci (QTL) associated with FC. We conducted an integrated genome-wide association analysis in QTLRel and identified five highly significant QTL affecting freezing to context as well as four highly significant QTL associated with freezing to cue. The average percent decrease in QTL width between the F(2) and the integrated analysis was 59.2%. Next, we exploited bioinformatic sequence and expression data to identify candidate genes based on the existence of non-synonymous coding polymorphisms and/or expression QTLs. We identified numerous candidate genes that have been previously implicated in either fear learning in animal models (Bcl2, Btg2, Dbi, Gabr1b, Lypd1, Pam and Rgs14) or PTSD in humans (Gabra2, Oprm1 and Trkb); other identified genes may represent novel findings. The integration of F(2) and AIL data maintains the advantages of studying FC in model organisms while significantly improving resolution over previous approaches.

A promoter polymorphism in the Per3 gene is associated with alcohol and stress response

The period homolog genes Per1, Per2 and Per3 are important components of the circadian clock system. In addition to their role in maintaining circadian rhythm, these genes have been linked to mood disorders, stress response and vulnerability to addiction and alcoholism. In this study, we combined high-resolution sequence analysis and quantitative trait locus (QTL) mapping of gene expression and behavioral traits to identify Per3 as a compelling candidate for the interaction between circadian rhythm, alcohol and stress response. In the BXD family of mouse strains, sequence variants in Per3 have marked effects on steady-state mRNA and protein levels. As a result, the transcript maps as a cis-acting expression QTL (eQTL). We found that an insertion/deletion (indel) variant in a putative stress response element in the promoter region of Per3 causes local control of transcript abundance. This indel results in differences in protein binding affinities between the two alleles through the Nrf2 transcriptional activator. Variation in Per3 is also associated with downstream differences in the expression of genes involved in circadian rhythm, alcohol, stress response and schizophrenia. We found that the Per3 locus is linked to stress/anxiety traits, and that the basal expression of Per3 is also correlated with several anxiety and addiction-related phenotypes. Treatment with alcohol results in increased expression of Per3 in the hippocampus, and this effect interacts with acute restraint stress. Our data provide strong evidence that variation in the Per3 transcript is causally associated with and also responsive to stress and alcohol.

Expression QTL mapping in regulatory and helper T cells from the BXD family of strains reveals novel cell-specific genes, gene-gene interactions and candidate genes for auto-immune disease

BACKGROUND

Regulatory T cells (Tregs) play an essential role in the control of the immune response. Treg cells represent important targets for therapeutic interventions of the immune system. Therefore, it will be very important to understand in more detail which genes are specifically activated in Treg cells versus T helper (Th) cells, and which gene regulatory circuits may be involved in specifying and maintaining Treg cell homeostasis.

RESULTS

We isolated Treg and Th cells from a genetically diverse family of 31 BXD type recombinant inbred strains and the fully inbred parental strains of this family--C57BL/6J and DBA/2J. Subsequently genome-wide gene expression studies were performed from the isolated Treg and Th cells. A comparative analysis of the transcriptomes of these cell populations allowed us to identify many novel differentially expressed genes. Analysis of cis- and trans-expression Quantitative Trait Loci (eQTLs) highlighted common and unique regulatory mechanisms that are active in the two cell types. Trans-eQTL regions were found for the Treg functional genes Nrp1, Stat3 and Ikzf4. Analyses of the respective QTL intervals suggested several candidate genes that may be involved in regulating these genes in Treg cells. Similarly, possible candidate genes were found which may regulate the expression of F2rl1, Ctla4, Klrb1f. In addition, we identified a focused group of candidate genes that may be important for the maintenance of self-tolerance and the prevention of allergy.

CONCLUSIONS

Variation of expression across the strains allowed us to find many novel gene-interaction networks in both T cell subsets. In addition, these two data sets enabled us to identify many differentially expressed genes and to nominate candidate genes that may have important functions for the maintenance of self-tolerance and the prevention of allergy.

Next-generation DNA sequencing-based assay for measuring allelic expression imbalance (AEI) of candidate neuropsychiatric disorder genes in human brain

BACKGROUND

Common genetic variants that regulate gene expression are widely suspected to contribute to the etiology and phenotypic variability of complex diseases. Although high-throughput, microarray-based assays have been developed to measure differences in mRNA expression among independent samples, these assays often lack the sensitivity to detect rare mRNAs and the reproducibility to quantify small changes in mRNA expression. By contrast, PCR-based allelic expression imbalance (AEI) assays, which use a "marker" single nucleotide polymorphism (mSNP) in the mRNA to distinguish expression from pairs of genetic alleles in individual samples, have high sensitivity and accuracy, allowing differences in mRNA expression greater than 1.2-fold to be quantified with high reproducibility. In this paper, we describe the use of an efficient PCR/next-generation DNA sequencing-based assay to analyze allele-specific differences in mRNA expression for candidate neuropsychiatric disorder genes in human brain.

RESULTS

Using our assay, we successfully analyzed AEI for 70 candidate neuropsychiatric disorder genes in 52 independent human brain samples. Among these genes, 62/70 (89%) showed AEI ratios greater than 1 ± 0.2 in at least one sample and 8/70 (11%) showed no AEI. Arranging log2AEI ratios in increasing order from negative-to-positive values revealed highly reproducible distributions of log2AEI ratios that are distinct for each gene/marker SNP combination. Mathematical modeling suggests that these log2AEI distributions can provide important clues concerning the number, location and contributions of cis-acting regulatory variants to mRNA expression.

CONCLUSIONS

We have developed a highly sensitive and reproducible method for quantifying AEI of mRNA expressed in human brain. Importantly, this assay allowed quantification of differential mRNA expression for many candidate disease genes entirely missed in previously published microarray-based studies of mRNA expression in human brain. Given the ability of next-generation sequencing technology to generate large numbers of independent sequencing reads, our method should be suitable for analyzing from 100- to 200-candidate genes in 100 samples in a single experiment. We believe that this is the appropriate scale for investigating variation in mRNA expression for defined sets candidate disorder genes, allowing, for example, comprehensive coverage of genes that function within biological pathways implicated in specific disorders. The combination of AEI measurements and mathematical modeling described in this study can assist in identifying SNPs that correlate with mRNA expression. Alleles of these SNPs (individually or as sets) that accurately predict high- or low-mRNA expression should be useful as markers in genetic association studies aimed at linking candidate genes to specific neuropsychiatric disorders.

Genetic dissection of the Gpnmb network in the eye

PURPOSE

To use a systematic genetics approach to investigate the regulation of Gpnmb, a gene that contributes to pigmentary dispersion syndrome (PDS) and pigmentary glaucoma (PG) in the DBA/2J (D2) mouse.

METHODS

Global patterns of gene expression were studied in whole eyes of a large family of BXD mouse strains (n = 67) generated by crossing the PDS- and PG-prone parent (DBA/2J) with a resistant strain (C57BL/6J). Quantitative trait locus (eQTL) mapping methods and gene set analysis were used to evaluate Gpnmb coexpression networks in wild-type and mutant cohorts.

RESULTS

The level of Gpnmb expression was associated with a highly significant cis-eQTL at the location of the gene itself. This autocontrol of Gpnmb is likely to be a direct consequence of the known premature stop codon in exon 4. Both gene ontology and coexpression network analyses demonstrated that the mutation in Gpnmb radically modified the set of genes with which Gpnmb expression is correlated. The covariates of wild-type Gpnmb are involved in biological processes including melanin synthesis and cell migration, whereas the covariates of mutant Gpnmb are involved in the biological processes of posttranslational modification, stress activation, and sensory processing.

CONCLUSIONS

These results demonstrated that a systematic genetics approach provides a powerful tool for constructing coexpression networks that define the biological process categories within which similarly regulated genes function. The authors showed that the R150X mutation in Gpnmb dramatically modified its list of genetic covariates, which may explain the associated ocular pathology.

Genetic dissection of behavioral flexibility: reversal learning in mice

BACKGROUND

Behavioral inflexibility is a feature of schizophrenia, attention-deficit/hyperactivity disorder, and behavior addictions that likely results from heritable deficits in the inhibitory control over behavior. Here, we investigate the genetic basis of individual differences in flexibility, measured using an operant reversal learning task.

METHODS

We quantified discrimination acquisition and subsequent reversal learning in a cohort of 51 BXD strains of mice (2-5 mice/strain, n = 176) for which we have matched data on sequence, gene expression in key central nervous system regions, and neuroreceptor levels.

RESULTS

Strain variation in trials to criterion on acquisition and reversal was high, with moderate heritability (∼.3). Acquisition and reversal learning phenotypes did not covary at the strain level, suggesting that these traits are effectively under independent genetic control. Reversal performance did covary with dopamine D2 receptor levels in the ventral midbrain, consistent with a similar observed relationship between impulsivity and D2 receptors in humans. Reversal, but not acquisition, is linked to a locus on mouse chromosome 10 with a peak likelihood ratio statistic at 86.2 megabase (p < .05 genome-wide). Variance in messenger RNA levels of select transcripts expressed in neocortex, hippocampus, and striatum correlated with the reversal learning phenotype, including Syn3, Nt5dc3, and Hcfc2.

CONCLUSIONS

This work demonstrates the clear trait independence between, and genetic control of, discrimination acquisition and reversal and illustrates how globally coherent data sets for a single panel of highly related strains can be interrogated and integrated to uncover genetic sources and molecular and neuropharmacological candidates of complex behavioral traits relevant to human psychopathology.

Genetic modulation of horizontal cell number in the mouse retina

Neuronal populations display conspicuous variability in their size among individuals, but the genetic sources of this variation are largely undefined. We demonstrate a large and highly heritable variation in neuron number within the mouse retina, affecting a critical population of interneurons, the horizontal cells. Variation in the size of this population maps to the distal end of chromosome (Chr) 13, a region homologous to human Chr 5q11.1-11.2. This region contains two genes known to modulate retinal cell number. Using conditional knock-out mice, we demonstrate that one of these genes, the LIM homeodomain gene Islet-1 (Isl1), plays a role in regulating horizontal cell number. Genetic differences in Isl1 expression are high during the period of horizontal cell production, and cis-regulation of Isl1 expression within the retina is demonstrated directly. We identify a single nucleotide polymorphism in the 5' UTR of Isl1 that creates an E-box sequence as a candidate causal variant contributing to this variation in horizontal cell number.

Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility

BACKGROUND

Germline polymorphisms can influence gene expression networks in normal mammalian tissues and can affect disease susceptibility. We and others have shown that analysis of this genetic architecture can identify single genes and whole pathways that influence complex traits, including inflammation and cancer susceptibility. Whether germline variants affect gene expression in tumors that have undergone somatic alterations, and the extent to which these variants influence tumor progression, is unknown.

RESULTS

Using an integrated linkage and genomic analysis of a mouse model of skin cancer that produces both benign tumors and malignant carcinomas, we document major changes in germline control of gene expression during skin tumor development resulting from cell selection, somatic genetic events, and changes in the tumor microenvironment. The number of significant expression quantitative trait loci (eQTL) is progressively reduced in benign and malignant skin tumors when compared to normal skin. However, novel tumor-specific eQTL are detected for several genes associated with tumor susceptibility, including IL18 (Il18), Granzyme E (Gzme), Sprouty homolog 2 (Spry2), and Mitogen-activated protein kinase kinase 4 (Map2k4).

CONCLUSIONS

We conclude that the genetic architecture is substantially altered in tumors, and that eQTL analysis of tumors can identify host factors that influence the tumor microenvironment, mitogen-activated protein (MAP) kinase signaling, and cancer susceptibility.

Toxicogenetics: population-based testing of drug and chemical safety in mouse models

The rapid decline in the cost of dense genotyping is paving the way for new DNA sequence-based laboratory tests to move quickly into clinical practice, and to ultimately help realize the promise of 'personalized' therapies. These advances are based on the growing appreciation of genetics as an important dimension in science and the practice of investigative pharmacology and toxicology. On the clinical side, both the regulators and the pharmaceutical industry hope that the early identification of individuals prone to adverse drug effects will keep advantageous medicines on the market for the benefit of the vast majority of prospective patients. On the environmental health protection side, there is a clear need for better science to define the range and causes of susceptibility to adverse effects of chemicals in the population, so that the appropriate regulatory limits are established. In both cases, most of the research effort is focused on genome-wide association studies in humans where de novo genotyping of each subject is required. At the same time, the power of population-based preclinical safety testing in rodent models (e.g., mouse) remains to be fully exploited. Here, we highlight the approaches available to utilize the knowledge of DNA sequence and genetic diversity of the mouse as a species in mechanistic toxicology research. We posit that appropriate genetically defined mouse models may be combined with the limited data from human studies to not only discover the genetic determinants of susceptibility, but to also understand the molecular underpinnings of toxicity.