Quantitative trait locus gene mapping: a new method for locating alcohol response genes

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.

Quantitative trait loci contributing to physiological and behavioural ethanol responses after acute and chronic treatment

The aim of the present study was the identification of gene loci that contribute to the development and manifestation of behaviours related to acute and chronic alcohol exposure, as well as to alcohol withdrawal. For this purpose, we performed a serial behavioural phenotyping of 534 animals from the second filial (F2) generation of a C57BL/6J and C3H/HeJ mice intercross in paradigms with relevance to alcohol dependence. First, ethanol-induced hypothermia was determined in ethanol-naive animals. The mice then received an ethanol solution for several weeks as their only fluid source. Ethanol tolerance, locomotor activity and anxiety-related behaviours were evaluated. The ethanol was next withdrawn and the withdrawal severity was assessed. The ethanol-experienced animals were finally analysed in a two-bottle choice paradigm to determine ethanol preference and stress-induced changes in ethanol preference. The genotypes of these mice were subsequently assessed by microsatellite marker mapping. We genotyped 264 markers with an average marker distance of 5.56 cM, which represents a high-density whole genome coverage. Quantitative trait loci (QTL) were subsequently identified using univariate analysis performed with the R/qtl tool, which is an extensible, interactive environment for mapping QTL in experimental crosses. We found QTL that have already been published, thus validating the serial phenotyping protocol, and identified several novel loci. Our analysis demonstrates that the various responses to ethanol are regulated by independent groups of genes.

Genome-wide association study of alcohol dependence implicates a region on chromosome 11

BACKGROUND

Alcohol dependence is a complex disease, and although linkage and candidate gene studies have identified several genes associated with the risk for alcoholism, these explain only a portion of the risk.

METHODS

We carried out a genome-wide association study (GWAS) on a case-control sample drawn from the families in the Collaborative Study on the Genetics of Alcoholism. The cases all met diagnostic criteria for alcohol dependence according to the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition; controls all consumed alcohol but were not dependent on alcohol or illicit drugs. To prioritize among the strongest candidates, we genotyped most of the top 199 single nucleotide polymorphisms (SNPs) (p < or = 2.1 x 10(-4)) in a sample of alcohol-dependent families and performed pedigree-based association analysis. We also examined whether the genes harboring the top SNPs were expressed in human brain or were differentially expressed in the presence of ethanol in lymphoblastoid cells.

RESULTS

Although no single SNP met genome-wide criteria for significance, there were several clusters of SNPs that provided mutual support. Combining evidence from the case-control study, the follow-up in families, and gene expression provided strongest support for the association of a cluster of genes on chromosome 11 (SLC22A18, PHLDA2, NAP1L4, SNORA54, CARS, and OSBPL5) with alcohol dependence. Several SNPs nominated as candidates in earlier GWAS studies replicated in ours, including CPE, DNASE2B, SLC10A2, ARL6IP5, ID4, GATA4, SYNE1, and ADCY3.

CONCLUSIONS

We have identified several promising associations that warrant further examination in independent samples.

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.

Mouse behavioural analysis in systems biology

Molecular techniques allowing in vivo modulation of gene expression have provided unique opportunities and challenges for behavioural studies aimed at understanding the function of particular genes or biological systems under physiological or pathological conditions. Although various animal models are available, the laboratory mouse (Mus musculus) has unique features and is therefore a preferred animal model. The mouse shares a remarkable genetic resemblance and aspects of behaviour with humans. In this review, first we describe common mouse models for behavioural analyses. As both genetic and environmental factors influence behavioural performance and need to be carefully evaluated in behavioural experiments, considerations for designing and interpretations of these experiments are subsequently discussed. Finally, common behavioural tests used to assess brain function are reviewed, and it is illustrated how behavioural tests are used to increase our understanding of the role of histaminergic neurotransmission in brain function.