Complex Genetics of Interactions of Alcohol and CNS Function and Behavior

Genetic Dissection of Femoral and Tibial Microarchitecture

Our understanding of the genetic control of bone strength has relied mainly on estimates of bone mineral density. Here we have mapped genetic factors that influence femoral and tibial microarchitecture using high‐resolution x‐ray computed tomography (8‐μm isotropic voxels) across a family of 61 BXD strains of mice, roughly 10 isogenic cases per strain and balanced by sex. We computed heritabilities for 25 cortical and trabecular traits. Males and females have well‐matched heritabilities, ranging from 0.25 to 0.75. We mapped 16 genetic loci most of which were detected only in females. There is also a bias in favor of loci that control cortical rather than trabecular bone. To evaluate candidate genes, we combined well‐established gene ontologies with bone transcriptome data to compute bone‐enrichment scores for all protein‐coding genes. We aligned candidates with those of human genome‐wide association studies. A subset of 50 strong candidates fell into three categories: (1) experimentally validated genes already known to modulate bone function (Adamts4, Ddr2, Darc, Adam12, Fkbp10, E2f6, Adam17, Grem2, Ifi204); (2) candidates without any experimentally validated function in bone (eg, Greb1, Ifi202b), but linked to skeletal phenotypes in human cohorts; and (3) candidates that have high bone‐enrichment scores, but for which there is not yet any functional link to bone biology or skeletal system disease (including Ifi202b, Ly9, Ifi205, Mgmt, F2rl1, Iqgap2). Our results highlight contrasting genetic architecture between sexes and among major bone compartments. The alignment of murine and human data facilitates function analysis and should prove of value for preclinical testing of molecular control of bone structure. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

Cross-species molecular dissection across alcohol behavioral domains

This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 9-12, 2017. Psychiatric diseases, including alcohol-use disorders (AUDs), are influenced through complex interactions of genes, neurobiological pathways, and environmental influences. A better understanding of the common neurobiological mechanisms underlying an AUD necessitates an integrative approach, involving a systematic assessment of diverse species and phenotype measures. As part of the World Congress on Stress and Alcoholism, this symposium provided a detailed account of current strategies to identify mechanisms underlying the development and progression of AUDs. Dr. Sean Farris discussed the integration and organization of transcriptome and postmortem human brain data to identify brain regional- and cell type-specific differences related to excessive alcohol consumption that are conserved across species. Dr. Brien Riley presented the results of a genome-wide association study of DSM-IV alcohol dependence; although replication of genetic associations with alcohol phenotypes in humans remains challenging, model organism studies show that COL6A3, KLF12, and RYR3 affect behavioral responses to ethanol, and provide substantial evidence for their role in human alcohol-related traits. Dr. Rob Williams expanded upon the systematic characterization of extensive genetic-genomic resources for quantifying and clarifying phenotypes across species that are relevant to precision medicine in human disease. The symposium concluded with Dr. Robert Hitzemann's description of transcriptome studies in a mouse model selectively bred for high alcohol ("binge-like") consumption and a non-human primate model of long-term alcohol consumption. Together, the different components of this session provided an overview of systems-based approaches that are pioneering the experimental prioritization and validation of novel genes and gene networks linked with a range of behavioral phenotypes associated with stress and AUDs.

Introduction to sequencing the brain transcriptome

High-throughput next-generation sequencing is now entering its second decade. However, it was not until 2008 that the first report of sequencing the brain transcriptome appeared (Mortazavi, Williams, Mccue, Schaeffer, & Wold, 2008). These authors compared short-read RNA-Seq data for mouse whole brain with microarray results for the same sample and noted both the advantages and disadvantages of the RNA-Seq approach. While RNA-Seq provided exon level resolution, the majority of the reads were provided by a small proportion of highly expressed genes and the data analysis was exceedingly complex. Over the past 6 years, there have been substantial improvements in both RNA-Seq technology and data analysis. This volume contains 11 chapters that detail various aspects of sequencing the brain transcriptome. Some of the chapters are very methods driven, while others focus on the use of RNA-Seq to study such diverse areas as development, schizophrenia, and drug abuse. This chapter briefly reviews the transition from microarrays to RNA-Seq as the preferred method for analyzing the brain transcriptome. Compared with microarrays, RNA-Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, and can be used to extract genotype information, e.g., nonsynonymous coding single nucleotide polymorphisms. RNA-Seq embraces the complexity of the brain transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain-behavior-disease relationships is substantial.

Genes, behavior and next-generation RNA sequencing

Advances in next-generation sequencing suggest that RNA-Seq is poised to supplant microarray-based approaches for transcriptome analysis. This article briefly reviews the use of microarrays in the brain-behavior context and then illustrates why RNA-Seq is a superior strategy. Compared with microarrays, RNA-Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, detects allele specific expression and can be used to extract genotype information, e.g. nonsynonymous coding single nucleotide polymorphisms. Examples of where RNA-Seq has been used to assess brain gene expression are provided. Despite the advantages of RNA-Seq, some disadvantages remain. These include the high cost of RNA-Seq and the computational complexities associated with data analysis. RNA-Seq embraces the complexity of the transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain-behavior relationship is substantial.

Integrative analysis of low- and high-resolution eQTL

The study of expression quantitative trait loci (eQTL) is a powerful way of detecting transcriptional regulators at a genomic scale and for elucidating how natural genetic variation impacts gene expression. Power and genetic resolution are heavily affected by the study population: whereas recombinant inbred (RI) strains yield greater statistical power with low genetic resolution, using diverse inbred or outbred strains improves genetic resolution at the cost of lower power. In order to overcome the limitations of both individual approaches, we combine data from RI strains with genetically more diverse strains and analyze hippocampus eQTL data obtained from mouse RI strains (BXD) and from a panel of diverse inbred strains (Mouse Diversity Panel, MDP). We perform a systematic analysis of the consistency of eQTL independently obtained from these two populations and demonstrate that a significant fraction of eQTL can be replicated. Based on existing knowledge from pathway databases we assess different approaches for using the high-resolution MDP data for fine mapping BXD eQTL. Finally, we apply this framework to an eQTL hotspot on chromosome 1 (Qrr1), which has been implicated in a range of neurological traits. Here we present the first systematic examination of the consistency between eQTL obtained independently from the BXD and MDP populations. Our analysis of fine-mapping approaches is based on 'real life' data as opposed to simulated data and it allows us to propose a strategy for using MDP data to fine map BXD eQTL. Application of this framework to Qrr1 reveals that this eQTL hotspot is not caused by just one (or few) 'master regulators', but actually by a set of polymorphic genes specific to the central nervous system.

Serious limitations of the QTL/microarray approach for QTL gene discovery

BACKGROUND

It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL). However, the effectiveness of this approach has not been assessed.

RESULTS

Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD) regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL) showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP).

CONCLUSIONS

The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes that were not tested. Together, our results explain the tendency to report QTL candidates as differentially expressed and indicate that the utility of the QTL/microarray as currently implemented is limited. Alternatives are proposed that make use of microarray data from multiple experiments to overcome the outlined limitations.

Dissection of a QTL hotspot on mouse distal chromosome 1 that modulates neurobehavioral phenotypes and gene expression

A remarkably diverse set of traits maps to a region on mouse distal chromosome 1 (Chr 1) that corresponds to human Chr 1q21-q23. This region is highly enriched in quantitative trait loci (QTLs) that control neural and behavioral phenotypes, including motor behavior, escape latency, emotionality, seizure susceptibility (Szs1), and responses to ethanol, caffeine, pentobarbital, and haloperidol. This region also controls the expression of a remarkably large number of genes, including genes that are associated with some of the classical traits that map to distal Chr 1 (e.g., seizure susceptibility). Here, we ask whether this QTL-rich region on Chr 1 (Qrr1) consists of a single master locus or a mixture of linked, but functionally unrelated, QTLs. To answer this question and to evaluate candidate genes, we generated and analyzed several gene expression, haplotype, and sequence datasets. We exploited six complementary mouse crosses, and combed through 18 expression datasets to determine class membership of genes modulated by Qrr1. Qrr1 can be broadly divided into a proximal part (Qrr1p) and a distal part (Qrr1d), each associated with the expression of distinct subsets of genes. Qrr1d controls RNA metabolism and protein synthesis, including the expression of approximately 20 aminoacyl-tRNA synthetases. Qrr1d contains a tRNA cluster, and this is a functionally pertinent candidate for the tRNA synthetases. Rgs7 and Fmn2 are other strong candidates in Qrr1d. FMN2 protein has pronounced expression in neurons, including in the dendrites, and deletion of Fmn2 had a strong effect on the expression of few genes modulated by Qrr1d. Our analysis revealed a highly complex gene expression regulatory interval in Qrr1, composed of multiple loci modulating the expression of functionally cognate sets of genes.

Effects of pharmacological stressors on c-fos and CRF mRNA in mouse brain: relationship to alcohol seeking

A marked heterogeneity exists among stressors in their ability to reinstate alcohol seeking in rats. We have reported that the pharmacological stressor yohimbine, an alpha-2 adrenoceptor antagonist, potently reinstated alcohol seeking, but FG-7142, a benzodiazepine inverse agonist was ineffective. In rats, we determined that yohimbine elicits patterns of brain expression of the mRNAs for c-fos, a marker of neuronal activation, and corticotropin-releasing factor (CRF) a stress-related peptide, distinct from that produced by FG-7142. The purpose of the present experiment is to determine if these differential effects of yohimbine and FG-7142 on regional c-fos and CRF mRNA expression generalize to another animal commonly used in alcohol research, the C57 BL/6J mouse. In comparing the results of the present study to those of our previous one, we found a number of commonalities in the patterns of activation elicited by yohimbine and FG-7142 between the two species, and some notable differences. As we found in the rat, yohimbine selectively increased c-fos mRNA in the mouse NACs, BLA and CeA. Yohimbine increased CRF mRNA only in the mouse PVN, but was without effect on CRF mRNA in extrahypothalamic sites, the BNST and CeA. This differs from what we saw in the rat, where yohimbine increased CRF mRNA in these extrahypothalamic regions, but not the PVN. The selective induction of c-fos in the NACs, BLA and CeA of mice and rats by yohimbine offers further support for the idea that activation of these structures participates in reinstatement induced by such stressors.

Identification of Quantitative Trait Loci and candidate genes influencing ethanol sensitivity in honey bees

Invertebrate models have greatly furthered our understanding of ethanol sensitivity and alcohol addiction. The honey bee (Apis mellifera), a widely used behavioral model, is valuable for comparative studies. A quantitative trait locus (QTL) mapping experiment was designed to identify QTL and genes influencing ethanol vapor sensitivity. A backcross mating between ethanol-sensitive and resistant lines resulted in worker offspring that were tested for sensitivity to the sedative effects of alcohol. A linkage map was constructed with over 500 amplified fragment length polymorphism (AFLP) and sequence-tagged site (STS) markers. Four QTL were identified from three linkage groups with log of odds ratio (LOD) scores of 2.28, 2.26, 2.23, and 2.02. DNA from markers within and near QTL were cloned and sequenced, and this data was utilized to integrate our map with the physical honey bee genome. Many candidate genes were identified that influence synaptic transmission, neuronal growth, and detoxification. Others affect lipid synthesis, apoptosis, alcohol metabolism, cAMP signaling, and electron transport. These results are relevant because they present the first search for QTL that affect resistance to acute ethanol exposure in an invertebrate, could be useful for comparative genomic purposes, and lend credence to the use of honey bees as biomedical models of alcohol metabolism and sensitivity.

Exploiting regulatory variation to identify genes underlying quantitative resistance to the wheat stem rust pathogen Puccinia graminis f. sp. tritici in barley

We previously mapped mRNA transcript abundance traits (expression-QTL or eQTL) using the Barley1 Affymetrix array and 'whole plant' tissue from 139 progeny of the Steptoe x Morex (St/Mx) reference barley mapping population. Of the 22,840 probesets (genes) on the array, 15,987 reported transcript abundance signals that were suitable for eQTL analysis, and this revealed a genome-wide distribution of 23,738 significant eQTLs. Here we have explored the potential of using these mRNA abundance eQTL traits as surrogates for the identification of candidate genes underlying the interaction between barley and the wheat stem rust fungus Puccinia graminis f. sp. tritici. We re-analysed quantitative 'resistance phenotype' data collected on this population in 1990/1991 and identified six loci associated with barley's reaction to stem rust. One of these coincided with the major stem rust resistance locus Rpg1, that we had previously positionally cloned using this population. Correlation analysis between phenotype values for rust infection and mRNA abundance values reported by the 22,840 GeneChip probe sets placed Rpg1, which is on the Barley1 GeneChip, in the top five candidate genes for the major QTL on chromosome 7H corresponding to the location of Rpg1. A second co-located with the rpg4/Rpg5 stem rust resistance locus that has been mapped in a different population and the remaining four were novel. Correlation analyses identified candidate genes for the rpg4/Rpg5 locus on chromosome 5H. By combining our data with additional published mRNA profiling data sets, we identify a putative sensory transduction histidine kinase as a strong candidate for a novel resistance locus on chromosome 2H and compile candidate gene lists for the other three loci.

Genetic determinants of emotionality and stress response in AcB/BcA recombinant congenic mice and in silico evidence of convergence with cardiovascular candidate genes

Genomic loci bearing stress-related phenotypes were dissected in recombinant congenic strains (RCS) of mice with C57BL/6J (B6) and A/J progenitors. Adult male mice from 14 A/J and 22 B6 background lines were evaluated for emotional reactivity in open-field (OF) and elevated plus-maze tests. Core temperature was monitored by radio telemetry during immobilization and on standard as well as salt-enriched diets. In addition, urinary electrolytes were measured. Genome-wide linkage analysis of the parameters revealed over 20 significant quantitative trait loci (QTL). The highest logarithm of odds (LOD) scores were within the previously-reported OF emotionality locus on Chr 1 (LOD = 4.6), in the dopa decarboxylase region on Chr 11 for the plus-maze (LOD = 4.7), and within a novel region of calmodulin 1 on Chr 12 for Ca++ excretion after a 24-h salt load (LOD = 4.6). RCS stress QTL overlapped with several candidate loci for cardiovascular (CV) disease. In silico evidence of functional polymorphisms by comparative sequence analysis of progenitor strains assisted to ascertain this convergence. The anxious BcA70 strain showed down regulation of Atp1a2 gene expression in the heart (P < 0.001) and brain (P < 0.05) compared with its parental B6 strain, compatible with the enhanced emotionality described in knock out animals for this gene, also involved in the salt-sensitive component of hypertension. Functional polymorphisms in regulatory elements of candidate genes of the CV/inflammatory/immune systems support the hypothesis of genetically-altered environmental susceptibility in CV disease development.

Heterogeneous Effects of Alcohol on Dopamine Release in the Striatum: A PET Study

BACKGROUND

A dopaminergic response to alcohol in humans has not been demonstrated consistently with positron emission tomography (PET). We hypothesized that the effect of alcohol on striatal dopamine (DA) release may be anatomically heterogeneous between subjects. Our approach was to identify voxels that exhibited alcohol-induced DA responses within the striatum, and to determine the relationships between DA responses and alcohol-related behavior.

METHODS

A novel method was developed to examine the anatomic extent and magnitude of striatal DA responses to alcohol across subjects. Thirteen healthy control subjects underwent 2 PET scans with [11C]raclopride (1 at baseline, 1 with an i.v. alcohol infusion to a target breath alcohol concentration of either 60 or 80 mg%). Parametric images of striatal binding potential (BP) were used to create maps of change in BP (deltaBP, an index of changes in DA levels). The anatomic extent and magnitude of DA responses were determined with voxel extraction methods. Subjective responses ("High," "Intoxication") to the alcohol infusion and behavioral data from the 90-day time-line follow back were assessed for relationships with DA responses to alcohol.

RESULTS

A voxel-wise t-test between baseline and alcohol BP images did not show any differences in D2/D3 receptor availability between the conditions. Data from the striatal deltaBP maps nevertheless showed that the anatomic extent and magnitude of alcohol-induced DA release in the striatum are correlated with subjective responses to alcohol.

CONCLUSIONS

The heterogeneity of dopaminergic responses to alcohol across subjects may be a reason for the lack of reports demonstrating DA involvement in alcohol-related behaviors. By allowing for different spatial patterns of DA release within each subject's striata, we showed correlations between alcohol-induced DA release in the striata and behavioral outcomes related to alcohol.