Strategies for mapping and cloning quantitative trait genes in rodents

Genetic architecture of quantitative traits in mice, flies, and humans

We compare and contrast the genetic architecture of quantitative phenotypes in two genetically well-characterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, with that found in our own species from recent successes in genome-wide association studies. We show that the current model of large numbers of loci, each of small effect, is true for all species examined, and that discrepancies can be largely explained by differences in the experimental designs used. We argue that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and we discuss the importance of epistasis, pleiotropy, and gene by environment interactions. Despite substantial advances in mapping quantitative trait loci, the identification of the quantitative trait genes and ultimately the sequence variants has proved more difficult, so that our information on the molecular basis of quantitative variation remains limited. Nevertheless, available data indicate that many variants lie outside genes, presumably in regulatory regions of the genome, where they act by altering gene expression. As yet there are very few instances where homologous quantitative trait loci, or quantitative trait genes, have been identified in multiple species, but the availability of high-resolution mapping data will soon make it possible to test the degree of overlap between species.

High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues

A proportion of the genetic variants underlying complex phenotypes do so through their effects on gene expression, so an important challenge in complex trait analysis is to discover the genetic basis for the variation in transcript abundance. So far, the potential of mapping both quantitative trait loci (QTLs) and expression quantitative trait loci (eQTLs) in rodents has been limited by the low mapping resolution inherent in crosses between inbred strains. We provide a megabase resolution map of thousands of eQTLs in hippocampus, lung, and liver samples from heterogeneous stock (HS) mice in which 843 QTLs have also been mapped at megabase resolution. We exploit dense mouse SNP data to show that artifacts due to allele-specific hybridization occur in approximately 30% of the cis-acting eQTLs and, by comparison with exon expression data, we show that alternative splicing of the 3' end of the genes accounts for <1% of cis-acting eQTLs. Approximately one third of cis-acting eQTLs and one half of trans-acting eQTLs are tissue specific. We have created an important systems biology resource for the genetic analysis of complex traits in a key model organism.

Thirty years of Mus spretus: a promising future

Extensive genetic polymorphisms in Mus spretus have ensured its widespread use in many areas of genetics. With the recent increase in the number of single nucleotide polymorphisms available for laboratory mouse strains, M. spretus is becoming less appealing, in particular for genetic mapping. Although M. spretus mice are aggressive and poor breeders, they have a bright future because they provide phenotypes unobserved in laboratory strains, and tools are available for modifying their genome and dissecting the genetic architecture of complex traits. Furthermore, they provide information on fundamental genetic questions, such as the details of evolution of genomes and speciation. Here, we examine the use of M. spretus from these perspectives. The impending completion of the M. spretus genome sequence will synergize these advantages.

Investigating the effect of genetic background on proteinuria and renal injury using two hypertensive strains

An earlier linkage analysis conducted on a population derived from the Dahl salt-sensitive hypertensive (S) and the spontaneously hypertensive rat (SHR) identified 10 genomic regions linked to several renal and/or cardiovascular traits. In particular, loci on rat chromosomes (RNO) 8 and 13 were linked to proteinuria, albuminuria, and renal damage. At both loci, the S allele was associated with increased proteinuria and renal damage. The current study aimed to confirm the linkage analysis and to evaluate the effect of genetic background on the ability of each locus (either RNO8 or RNO13) to exert a phenotypic difference when placed on a genetic background either susceptible (S rat) or resistant (SHR) to the development of renal disease. Congenic strains developed to transfer genomic segments from either RNO8 or RNO13 from the SHR onto the S genetic background [S.SHR(8) or S.SHR(13)] demonstrated significantly reduced proteinuria and improved renal function. Both congenic strains demonstrated significantly reduced glomerular and tubular injury, with renal interstitial fibrosis as the predominant pathological difference compared with the S. In contrast, transfer of RNO8 or RNO13 genomic regions from the S onto the resistant SHR genetic background [SHR.S(8) or SHR.S(13)] yielded no significant difference in proteinuria or glomerular, tubular, or interstitial injury compared with SHR. These findings demonstrate that genetic context plays a significant and important role in the phenotypic expression of genes influencing proteinuria on RNO8 and RNO13.

Genetic dissection of a major mouse obesity QTL (Carfhg2): integration of gene expression and causality modeling

HG.CAST-(D9Mit249-D9Mit133) (HG9) congenic mice are homozygous for CAST/EiJ chromosome (Chr) 9 alleles from approximately 9 to 84 Mbp on a C57BL6/J-hg/hg (HG) background. This region contains the carcass fat in high growth mice (Carfhg2) quantitative trait locus (QTL), and while its obesity-promoting effects have been confirmed in HG9 mice, its underlying genetic basis remains elusive. To refine the location of Carfhg2, we preformed a linkage analysis in two congenic F2 intercrosses and progeny-tested a recombinant F2 male. These analyses narrowed Carfhg2 to between 33.0 and 40.8 Mbp on Chr 9. To identify candidate genes we measured the expression of 44 transcripts surrounding the Carfhg2 peak in adipose, brain, liver, and muscle tissues from F2 mice using Biomark 48.48 Dynamic Arrays. In total, 68% (30 of the 44) of genes were regulated by a significant expression QTL (eQTL) in at least one tissue. To prioritize genes with eQTL we used Network Edge Orienting, a causality modeling tool. These analyses advance our goal of identifying the molecular basis of Carfhg2.

Expression quantitative trait loci mapping with multivariate sparse partial least squares regression

Expression quantitative trait loci (eQTL) mapping concerns finding genomic variation to elucidate variation of expression traits. This problem poses significant challenges due to high dimensionality of both the gene expression and the genomic marker data. We propose a multivariate response regression approach with simultaneous variable selection and dimension reduction for the eQTL mapping problem. Transcripts with similar expression are clustered into groups, and their expression profiles are viewed as a multivariate response. Then, we employ our recently developed sparse partial least-squares regression methodology to select markers associated with each cluster of genes. We demonstrate with extensive simulations that our eQTL mapping with multivariate response sparse partial least-squares regression (M-SPLS eQTL) method overcomes the issue of multiple transcript- or marker-specific analyses, thereby avoiding potential elevation of type I error. Additionally, joint analysis of multiple transcripts by multivariate response regression increases power for detecting weak linkages. We illustrate that M-SPLS eQTL compares competitively with other approaches and has a number of significant advantages, including the ability to handle highly correlated genotype data and computational efficiency. We provide an application of this methodology to a mouse data set concerning obesity and diabetes.

Genetic variation and population substructure in outbred CD-1 mice: implications for genome-wide association studies

Outbred laboratory mouse populations are widely used in biomedical research. Since little is known about the degree of genetic variation present in these populations, they are not widely used for genetic studies. Commercially available outbred CD-1 mice are drawn from an extremely large breeding population that has accumulated many recombination events, which is desirable for genome-wide association studies. We therefore examined the degree of genome-wide variation within CD-1 mice to investigate their suitability for genetic studies. The CD-1 mouse genome displays patterns of linkage disequilibrium and heterogeneity similar to wild-caught mice. Population substructure and phenotypic differences were observed among CD-1 mice obtained from different breeding facilities. Differences in genetic variation among CD-1 mice from distinct facilities were similar to genetic differences detected between closely related human populations, consistent with a founder effect. This first large-scale genetic analysis of the outbred CD-1 mouse strain provides important considerations for the design and analysis of genetic studies in CD-1 mice.

Discovery of ZIP transporters that participate in cadmium damage to testis and kidney

It has been known for decades that cadmium (Cd) must enter the cell to cause damage, but there was no mechanism to explain genetic differences in response to Cd toxicity until 2005. Starting with the mouse Cdm locus associated with differences in Cd-induced testicular necrosis between inbred strains, a 24.6-centiMorgan region on chromosome 3 was reduced ultimately to 880 kb; in this segment is the Slc39a8 gene encoding the ZIP8 Zn(2+)/HCO(3)(-) symporter. In endothelial cells of the testis vasculature, Cd-sensitive mice exhibit high ZIP8 expression, Cd-resistant mice exhibit very low expression. A 168.7-kb bacterial artificial chromosome (BAC) from a 129S6 (Cd-sensitive) BAC library containing the Slc39a8 gene was inserted into the Cd-resistant C57BL/6J genome: Cd treatment produced testicular necrosis in BAC-transgenic BTZIP8-3 mice but not in non-transgenic littermates, thereby proving that the Slc39a8 gene is indeed the Cdm locus. Cd-induced renal failure also occurred in these BTZIP8-3 mice. Immunohistochemistry showed highly expressed ZIP8 protein in the renal proximal tubular epithelial apical surface, suggesting that ZIP8 participates in Cd-induced renal failure. Slc39a14, most closely evolutionarily related to Slc39a8, encodes differentially-spliced products ZIP14A and ZIP14B that display properties similar to ZIP8. ZIP8 in alveolar cells brings environmental Cd into the organism and ZIP14 in intestinal enterocytes carries Cd into the organism and into the hepatocyte. We believe these two transporters function endogenously as Zn(2+)/HCO(3)(-) symporters important in combating inflammation and carrying out other physiological functions; Cd is able to displace the endogenous cation, enter the cell, and produce tissue damage and disease.

An E3 ubiquitin ligase, Really Interesting New Gene (RING) Finger 41, is a candidate gene for anxiety-like behavior and beta-carboline-induced seizures

BACKGROUND

Identification of the genes underlying psychiatric illness remains a thorny problem. Previously, Quantitative Trait Loci (QTL) for anxiety-like behaviors and beta-carboline-induced seizure vulnerability have been mapped to the distal portion of mouse chromosome 10, with crosses of A/J and C57BL6 mice.

METHODS

An interval specific congenic strain for this chromosomal 10 region facilitated the genetic dissection of novelty-induced exploratory behaviors.

RESULTS

By microarray studies, an unsuspected E3 ubiquitin ligase, Really Interesting New Gene (RING) Finger 41 (Rnf41) was differentially expressed in the region of interest, being upregulated in the hippocampi of B6 compared with A/J as well as congenic A.B6(chr10) versus A/J. By quantitative real-time polymerase chain reaction (qRT-PCR), Rnf41 expression levels were significantly increased 1.5- and 1.3-fold in the hippocampi of C57BL6/J and A.B6(chr10) mice compared with A/J mice, respectively. Protein levels of Rnf41 were increased in hippocampi of B6 mice compared with A/J mice across postnatal development with a 5.5-fold difference at P56. Yeast two-hybrid studies searching for Rnf41 binding partners in fetal hippocampus identified several potential targets. An interaction between Rnf41 and NogoA was validated by glutathionine-S-transferase-Rnf41 pulldown experiments. Re-analysis of a microarray database of human postmortem prefrontal cortex (Brodmann's Area 46/10) found that RNF41 messenger RNA expression levels were reduced significantly in patients with major depression and bipolar disorder compared with unaffected control subjects and confirmed by qRT-PCR.

CONCLUSIONS

Overall, Rnf41 is nominated as a candidate gene for anxiety-like behaviors, depression, and vulnerability to seizures. The RNF41 and its binding partners suggest molecular pathways underlying behavior, highlighting a potential role for the ubiquitin proteasome system in psychiatric illness.

Inheritance patterns of progressive hearing loss in laboratory strains of mice

Positional cloning of mouse deafness mutations uncovered a plethora of proteins that have important functions in the peripheral auditory system in particular in the cochlear organ of Corti and stria vascularis. Most of these mutant variants follow a monogenic form of inheritance and are rare, highly penetrant, and deleterious alleles. Inbred and heterogenous strains of mice, in contrast, present with non-syndromic hearing impairment due to the effects of multiple genes and hypomorphic and less penetrant alleles that are often transmitted in a non-Mendelian manner. Here we review hearing loss inheritance patterns as they were discovered in different strains of mice and discuss the relevance of candidate genes to late-onset progressive hearing impairment in mouse and human.

HECTD2 is associated with susceptibility to mouse and human prion disease

Prion diseases are fatal transmissible neurodegenerative disorders, which include Scrapie, Bovine Spongiform Encephalopathy (BSE), Creutzfeldt-Jakob Disease (CJD), and kuru. They are characterised by a prolonged clinically silent incubation period, variation in which is determined by many factors, including genetic background. We have used a heterogeneous stock of mice to identify Hectd2, an E3 ubiquitin ligase, as a quantitative trait gene for prion disease incubation time in mice. Further, we report an association between HECTD2 haplotypes and susceptibility to the acquired human prion diseases, vCJD and kuru. We report a genotype-associated differential expression of Hectd2 mRNA in mouse brains and human lymphocytes and a significant up-regulation of transcript in mice at the terminal stage of prion disease. Although the substrate of HECTD2 is unknown, these data highlight the importance of proteosome-directed protein degradation in neurodegeneration. This is the first demonstration of a mouse quantitative trait gene that also influences susceptibility to human prion diseases. Characterisation of such genes is key to understanding human risk and the molecular basis of incubation periods.

PECAM-independent thioglycollate peritonitis is associated with a locus on murine chromosome 2

Background

Previous studies have demonstrated that knockout or inhibition of Platelet/Endothelial Cell Adhesion Molecule (PECAM, CD31) in a number of murine strains results in impaired inflammatory responses, but that no such phenotype is seen in the C57BL/6 (B6) murine background.

Methodology/Principal Findings

We have undertaken a quantitative trait locus (QTL) mapping effort between FVB/n (FVB) and B6 mice deficient for PECAM to identify the gene or genes responsible for this unique feature of B6 mice. We have identified a locus on murine chromosome 2 at approximately 35.8 Mb that is strongly associated (LOD score = 9.0) with inflammatory responses in the absence of PECAM.

Conclusions/Significance

These data potentiate further study of the diapedesis machinery, as well as potential identification of new components of this machinery. As such, this study is an important step to better understanding the processes of inflammation.

A quantitative trait locus on chromosome 4 affects cycling of hematopoietic stem and progenitor cells through regulation of TGF-beta 2 responsiveness

The hematopoietic stem and progenitor cell (HSPC) compartment is subject to extensive quantitative genetic variation. We have previously shown that TGF-beta2 at low concentrations enhances flt3 ligand-induced growth of HSPCs, while it is potently antiproliferative at higher concentrations. This in vitro enhancing effect was subject to quantitative genetic variation, for which a quantitative trait locus (QTL) was tentatively mapped to chromosome 4 (chr.4). Tgfb2(+/-) mice have a smaller and more slowly cycling HSPC compartment, which has a decreased serial repopulation capacity, and are less susceptible to the lethal effect of high doses of 5-fluorouracil. To unequivocally demonstrate that these phenotypes can be attributed to the enhancing effect of TGF-beta2 on HSPC proliferation observed in vitro and are therefore subject to mouse strain-dependent variation as well, we generated congenic mice where the telomeric region of chr.4 was introgressed from DBA/2 into C57BL/6 mice. In these mice, the enhancing effect of TGF-beta2 on flt3 signaling, but not the generic antiproliferative effect of high concentrations of TGF-beta2, was abrogated, confirming the location of this QTL, which we named tb2r1, on chr.4. These mice shared a smaller and more slowly cycling HSPC compartment and increased 5-fluorouracil resistance but not a decreased serial repopulation capacity with Tgfb2(+/-) mice. The concordance of phenotypes between Tgfb2(+/-) and congenic mice indicates that HSPC frequency and cycling are regulated by tb2r1, while an additional QTL in the telomeric region of chr.4 may regulate the serial repopulation capacity of hematopoietic stem cells.

A systematic strategy for the discovery of candidate genes responsible for phenotypic variation

It is increasingly common to combine genome-wide expression data with quantitative trait mapping data to aid in the search for sequence polymorphisms responsible for phenotypic variation. By joining these complex but different data types at the level of the biological pathway, we can take advantage of existing biological knowledge to systematically identify possible mechanisms of genotype-phenotype interaction. With the development of web services and workflows, this process can be made rapid and systematic. Our methodology was applied to a use case of resistance to African trypanosomiasis in mice. Workflows developed in this investigation, including a guide to loading and executing them with example data, are available at http://www.myexperiment.org/users/43/workflows .

Computing genetic imprinting expressed by haplotypes

Different expression of maternally and paternally inherited alleles at certain genes is called genetic imprinting. Despite its great importance in trait formation, development, and evolution, it remains unclear how genetic imprinting operates in a complex network of interactive genes located throughout the genome. Genetic mapping has proven to be a powerful tool that can estimate the distribution and effects of imprinted genes. While traditional mapping models attempt to detect imprinted quantitative trait loci based on a linkage map constructed from molecular markers, we have developed a statistical model for estimating the imprinting effects of haplotypes composed of multiple sequenced single-nucleotide polymorphisms. The new model provides a characterization of the difference in the effect of maternally and paternally derived haplotypes, which can be used as a tool for genetic association studies at the candidate gene or genome-wide level. The model was used to map imprinted haplotype effects on body mass index in a random sample from a natural human population, leading to the detection of significant imprinted effects at the haplotype level. The new model will be useful for characterizing the genetic architecture of complex quantitative traits at the nucleotide level.

A resource for the simultaneous high-resolution mapping of multiple quantitative trait loci in rats: the NIH heterogeneous stock

The laboratory rat (Rattus norvegicus) is a key tool for the study of medicine and pharmacology for human health. A large database of phenotypes for integrated fields such as cardiovascular, neuroscience, and exercise physiology exists in the literature. However, the molecular characterization of the genetic loci that give rise to variation in these traits has proven to be difficult. Here we show how one obstacle to progress, the fine-mapping of quantitative trait loci (QTL), can be overcome by using an outbred population of rats. By use of a genetically heterogeneous stock of rats, we map a locus contributing to variation in a fear-related measure (two-way active avoidance in the shuttle box) to a region on chromosome 5 containing nine genes. By establishing a protocol measuring multiple phenotypes including immunology, neuroinflammation, and hematology, as well as cardiovascular, metabolic, and behavioral traits, we establish the rat HS as a new resource for the fine-mapping of QTLs contributing to variation in complex traits of biomedical relevance.

An integrative genetics approach to identify candidate genes regulating BMD: combining linkage, gene expression, and association

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J x C3H/HeJ (BXH) F(2) mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F(2) mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification.

Applying mouse complex-trait resources to behavioural genetics

Studies of the genetic basis of behaviour in mice are at a turning point. Soon, new resources will enable the behavioural function of all genes to be tested and the networks of genes, messenger RNAs and proteins involved in a particular behaviour to be identified. Using these resources, scientists will be able to analyse mouse behaviour at an unprecedented level of detail. Interpreting the new data, however, will require a shift in focus from gene-based approaches to network-based approaches.

Genetic analysis of the psychostimulant effects of nicotine in chromosome substitution strains and F2 crosses derived from A/J and C57BL/6J progenitors

Previous research utilizing the AcB/BcA recombinant congenic strains (RCS) of mice mapped provisional quantitative trait loci (QTLs) for the psychostimulant effects of nicotine to multiple regions on chromosomes 7, 11, 12, 14, 16, and 17. The current study was designed to confirm these QTLs in an A/J (A) x C57Bl/6J (B6) F2 cross and a panel of B6.A chromosome substitution strains (CSS). The panel of B6.A CSS consists of 21 strains, each carrying a different A/J chromosome on a B6 background. The A x B6 F2, CSS, A, and B6 mice were tested for sensitivity to the effects of nicotine on locomotor activity using a computerized open-field apparatus. In A x B6 F2 mice two QTLs were identified which confirm those previously observed in the AcB/BcA RCS. Significant differences in the expression of nicotine-induced activity were associated with loci on chromosome 11 (D11Mit62) and chromosome 16 (D16Mit131) in the A x B6 F2. At the chromosome 11 QTL, an A allele was associated with lower nicotine-induced activity scores relative to the B6. In contrast, the A allele was associated with greater relative nicotine activity values for the chromosome 16 QTL. A survey of the CSS panel confirmed the presence of QTLs for nicotine activation on chromosomes 2, 14, 16, and 17 previously identified in the AcB/BcA RCS. In the informative CSS strains, A alleles were consistently associated with greater nicotine-induced activity scores compared to the B6. The results of the present study are the first to validate QTLs for sensitivity to the effects of nicotine across multiple strains of mice. QTLs on chromosomes 2, 11, 14, 16, and 17 were confirmed in CSS and/or F2 mice. Significantly, the identification of a QTL on chromosome 16 has now been replicated in three crosses derived from the A and B6 progenitors.

Genetic architecture of complex traits: large phenotypic effects and pervasive epistasis

The genetic architecture of complex traits underlying physiology and disease in most organisms remains elusive. We still know little about the number of genes that underlie these traits, the magnitude of their effects, or the extent to which they interact. Chromosome substitution strains (CSSs) enable statistically powerful studies based on testing engineered inbred strains that have single, unique, and nonoverlapping genetic differences, thereby providing measures of phenotypic effects that are attributable to individual chromosomes. Here, we report a study of phenotypic effects and gene interactions for 90 blood, bone, and metabolic traits in a mouse CSS panel and 54 traits in a rat CSS panel. Two key observations emerge about the genetic architecture of these traits. First, the traits tend to be highly polygenic: across the genome, many individual chromosome substitutions each had significant phenotypic effects and, within each of the chromosomes studied, multiple distinct loci were found. Second, strong epistasis was found among the individual chromosomes. Specifically, individual chromosome substitutions often conferred surprisingly large effects (often a substantial fraction of the entire phenotypic difference between the parental strains), with the result that the sum of these individual effects often dramatically exceeded the difference between the parental strains. We suggest that strong, pervasive epistasis may reflect the presence of several phenotypically-buffered physiological states. These results have implications for identification of complex trait genes, developmental and physiological studies of phenotypic variation, and opportunities to engineer phenotypic outcomes in complex biological systems.

Molecular analyses and identification of promising candidate genes for loci on mouse chromosome 1 affecting alcohol physical dependence and associated withdrawal

We recently mapped quantitative trait loci (QTLs) with large effects on predisposition to physical dependence and associated withdrawal severity following chronic and acute alcohol exposure (Alcdp1/Alcw1) to a 1.1-Mb interval of mouse chromosome 1 syntenic with human chromosome 1q23.2-23.3. Here, we provide a detailed analysis of the genes within this interval and show that it contains 40 coding genes, 17 of which show validated genotype-dependent transcript expression and/or non-synonymous coding sequence variation that may underlie the influence of Alcdp1/Alcw1 on ethanol dependence and associated withdrawal. These high priority candidates are involved in diverse cellular functions including intracellular trafficking, oxidative homeostasis, mitochondrial respiration, and extracellular matrix dynamics, and indicate both established and novel aspects of the neurobiological response to ethanol. This work represents a substantial advancement toward identification of the gene(s) that underlies the phenotypic effects of Alcdp1/Alcw1. Additionally, a multitude of QTLs for a variety of complex traits, including diverse behavioral responses to ethanol, have been mapped in the vicinity of Alcdp1/Alcw1, and as many as four QTLs on human chromosome 1q have been implicated in human mapping studies for alcoholism and associated endophenotypes. Thus, our results will be primary to further efforts to identify genes involved in a wide variety of behavioral responses to alcohol and may directly facilitate progress in human alcoholism genetics.

Searching for genes underlying behavior: lessons from circadian rhythms

The success of forward genetic (from phenotype to gene) approaches to uncover genes that drive the molecular mechanism of circadian clocks and control circadian behavior has been unprecedented. Links among genes, cells, neural circuits, and circadian behavior have been uncovered in the Drosophila and mammalian systems, demonstrating the feasibility of finding single genes that have major effects on behavior. Why was this approach so successful in the elucidation of circadian rhythms? This article explores the answers to this question and describes how the methods used successfully for identifying the molecular basis of circadian rhythms can be applied to other behaviors such as anxiety, addiction, and learning and memory.

A systems-based framework for understanding complex metabolic and cardiovascular disorders

Common forms of metabolic and cardiovascular diseases involve the interplay of numerous genes as well as important environmental factors. Traditional biochemical and genetic approaches generally attempt to dissect these diseases one gene at a time, for example, by analysis of Mendelian forms or genetically engineered experimental organisms. But, it is also important to understand how the genes interact with each other and the environment, and how these interactions change in disease states. Technological advances, such as the development of expression arrays that allow quantification of all transcript levels in a cell or tissue, have made it feasible to globally monitor molecular phenotypes that underlie disease states. By applying statistical methods, relationships between DNA variation, gene expression patterns, and diseases can be modeled.

Review. Neurogenetic studies of alcohol addiction

Neurogenetic studies of alcohol dependence have relied substantially on genetic animal models, particularly rodents. Studies of inbred strains, selectively bred lines and mutants bearing genes whose function has been targeted for over or under expression are reviewed. Studies focused on gene expression changes are the most recent contributors to this literature, and some genetic effects may work through epigenetic mechanisms. In a few instances, interesting parallels have been revealed between genetic risk in humans and studies in non-human animal models. Future approaches are likely to be increasingly complex.

Genetic determinants in hepatic fibrosis: from experimental models to fibrogenic gene signatures in humans

Hepatic fibrosis, or scarring of the liver, is a nonspecific reaction to chronic liver injury. Hepatic fibrosis is commonly caused by exogenous factors such as viral hepatitis or alcohol abuse, but recent studies also indicate a genetic predisposition. Although some patients who have chronic liver diseases show only minor morphologic and functional alterations of the liver and are characterized by slow progression of disease with mild clinical symptoms, others develop pronounced hepatic fibrosis rapidly, culminating in cirrhosis, liver failure, or hepatocellular carcinoma, respectively. These well known differences in progression of hepatic fibrosis persist when controlling for age (at infection), gender, and exogenous factors in multivariate analysis, indicating that genetic factors might play important roles in the modulation of hepatic fibrosis and contribute to the variability in fibrosis progression. This review summarizes genetic determinants in hepatic fibrosis.

An association analysis of murine anxiety genes in humans implicates novel candidate genes for anxiety disorders

BACKGROUND

Human anxiety disorders are complex diseases with largely unknown etiology. We have taken a cross-species approach to identify genes that regulate anxiety-like behavior with inbred mouse strains that differ in their innate anxiety levels as a model. We previously identified 17 genes with expression levels that correlate with anxiety behavior across the studied strains. In the present study, we tested their 13 known human homologues as candidate genes for human anxiety disorders with a genetic association study.

METHODS

We describe an anxiety disorder study sample derived from a Finnish population-based cohort and consisting of 321 patients and 653 carefully matched control subjects, all interviewed to obtain DSM-IV diagnoses. We genotyped altogether 208 single nucleotide polymorphisms (SNPs) (all non-synonymous SNPs, SNPs that alter potential microRNA binding sites, and gap-filling SNPs selected on the basis of HapMap information) from the investigated anxiety candidate genes.

RESULTS

Specific alleles and haplotypes of six of the examined genes revealed some evidence for association (p < or = .01). The most significant evidence for association with different anxiety disorder subtypes were: p = .0009 with ALAD (delta-aminolevulinate dehydratase) in social phobia, p = .009 with DYNLL2 (dynein light chain 2) in generalized anxiety disorder, and p = .004 with PSAP (prosaposin) in panic disorder.

CONCLUSIONS

Our findings suggest that variants in these genes might predispose to specific human anxiety disorders. These results illustrate the potential utility of cross-species approaches in identification of candidate genes for psychiatric disorders.

Complex genetics of obesity in mouse models

Traits related to energy balance and obesity are exceptionally complex, with varying contributions of genetic susceptibility and interacting environmental factors. The use of mouse models has been a powerful driving force in understanding the genetic architecture of polygenic traits such as obesity. However, the use of mouse models for analysis of complex traits is at an important crossroad. Genome-wide association studies in humans are now leading to direct identification of obesity genes. In this review, we focus on three areas representing the current and future roles of mouse models regarding genetics of complex obesity. First, we summarize increasingly powerful ways to harness the strength of mouse models for discovery of genes affecting polygenic obesity. Second, we examine the status of using a systems biology approach to dissect the genetic architecture of obesity. And third, we explore the effects of recent findings indicating increasing levels of complexity in the nature of variation underlying, and the heritability of, complex traits such as obesity.

Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci

Dissecting the genes involved in complex traits can be confounded by multiple factors, including extensive epistatic interactions among genes, the involvement of epigenetic regulators, and the variable expressivity of traits. Although quantitative trait locus (QTL) analysis has been a powerful tool for localizing the chromosomal regions underlying complex traits, systematically identifying the causal genes remains challenging. Here, through its application to plasma levels of high-density lipoprotein cholesterol (HDL) in mice, we demonstrate a strategy for narrowing QTL that utilizes comparative genomics and bioinformatics techniques. We show how QTL detected in multiple crosses are subjected to both combined cross analysis and haplotype block analysis; how QTL from one species are mapped to the concordant regions in another species; and how genomewide scans associating haplotype groups with their phenotypes can be used to prioritize the narrowed regions. Then we illustrate how these individual methods for narrowing QTL can be systematically integrated for mouse chromosomes 12 and 15, resulting in a significantly reduced number of candidate genes, often from hundreds to <10. Finally, we give an example of how additional bioinformatics resources can be combined with experiments to determine the most likely quantitative trait genes.

The alpha 3 subunit gene of the nicotinic acetylcholine receptor is a candidate gene for ethanol stimulation

Alcohol and nicotine are coabused, and preclinical and clinical data suggest that common genes may influence responses to both drugs. A gene in a region of mouse chromosome 9 that includes a cluster of three nicotinic acetylcholine receptor (nAChR) subunit genes influences the locomotor stimulant response to ethanol. The current studies first used congenic mice to confirm the influential gene on chromosome 9. Congenic F(2) mice were then used to more finely map the location. Gene expression of the three subunit genes was quantified in strains of mice that differ in response to ethanol. Finally, the locomotor response to ethanol was examined in mice heterozygous for a null mutation of the alpha 3 nAChR subunit gene (Chrna3). Congenic data indicate that a gene on chromosome 9, within a 46 cM region that contains the cluster of nAChR subunit genes, accounts for 41% of the genetic variation in the stimulant response to ethanol. Greater expression of Chrna3 was found in whole brain and dissected brain regions relevant to locomotor behavior in mice that were less sensitive to ethanol-induced stimulation compared to mice that were robustly stimulated; the other two nAChR subunit genes in the gene cluster (alpha 5 and beta 4) were not differentially expressed. Locomotor stimulation was not expressed on the genetic background of Chrna3 heterozygous (+/-) and wild-type (+/+) mice; +/- mice were more sensitive than +/+ mice to the locomotor depressant effects of ethanol. Chrna3 is a candidate gene for the acute locomotor stimulant response to ethanol that deserves further examination.

Using gene expression databases for classical trait QTL candidate gene discovery in the BXD recombinant inbred genetic reference population: mouse forebrain weight

Background

Successful strategies for QTL gene identification benefit from combined experimental and bioinformatic approaches. Unique design aspects of the BXD recombinant inbred line mapping panel allow use of archived gene microarray expression data to filter likely from unlikely candidates. This prompted us to propose a simple five-filter protocol for candidate nomination. To filter more likely from less likely candidates, we required candidate genes near to the QTL to have mRNA abundance that correlated with the phenotype among the BXD lines as well as differed between the parental lines C57BL/6J and DBA/2J. We also required verification of mRNA abundance by an independent method, and finally we required either differences in protein levels or confirmed DNA sequence differences.

Results

QTL mapping of mouse forebrain weight in 34 BXD RI lines found significant association on chromosomes 1 and 11, with each C57BL/6J allele increasing weight by more than half a standard deviation. The intersection of gene lists that were within ± 10 Mb of the strongest associated location, that had forebrain mRNA abundance correlated with forebrain weight among the BXD, and that had forebrain mRNA abundance differing between C57BL/6J and DBA/2J, produced two candidates, Tnni1 (troponin 1) and Asb3 (ankyrin repeat and SOCS box-containing protein 3). Quantitative RT-PCR confirmed the direction of an increased expression in C57BL/6J genotype over the DBA/2J genotype for both genes, a difference that translated to a 2-fold difference in Asb3 protein. Although Tnni1 protein differences could not be confirmed, a 273 bp indel polymorphism was discovered 1 Kb upstream of the transcription start site.

Conclusion

Delivery of well supported candidate genes following a single quantitative trait locus mapping experiment is difficult. However, by combining available gene expression data with QTL mapping, we illustrated a five-filter protocol that nominated Asb3 and Tnni1 as candidates affecting increased mouse forebrain weight. We recommend our approach when (1) investigators are working with phenotypic differences between C57BL/6J and DBA/2J, and (2) gene expression data are available on that relate to the phenotype of interest. Under these circumstances, measurement of the phenotype in the BXD lines will likely also deliver excellent candidate genes.

Mixed effects models for quantitative trait loci mapping with inbred strains

Fixed effects models have dominated the statistical analysis of genetic crosses between inbred strains. In spite of their popularity, the traditional models ignore polygenic background and must be tailored to each specific cross. We reexamine the role of random effect models in gene mapping with inbred strains. The biggest difficulty in implementing random effect models is the lack of a coherent way of calculating trait covariances between relatives. The standard model for outbred populations is based on premises of genetic equilibrium that simply do not apply to crosses between inbred strains since every animal in a strain is genetically identical and completely homozygous. We fill this theoretical gap by introducing novel combinatorial entities called strain coefficients. With an appropriate theory, it is possible to reformulate QTL mapping and QTL association analysis as an application of mixed models involving both fixed and random effects. After developing this theory, our first example compares the mixed effects model to a standard fixed effects model using simulated advanced intercross line (AIL) data. Our second example deals with hormone data. Here multivariate traits and parameter identifiability questions arise. Our final example involves random mating among eight strains and vividly demonstrates the versatility of our models.

Multigenic control of tuberculosis resistance: analysis of a QTL on mouse chromosome 7 and its synergism with sst1

Tuberculosis remains a significant global health problem: one-third of the human population is infected with Mycobacterium tuberculosis (MTB) and 10% of those are at lifetime risk of developing tuberculosis. In the majority of individuals infected, genetic determinants of susceptibility remain largely unknown due to complex multigenic control and the influence of genes--environment interactions. Genetic variation of host resistance to MTB in animal models reflects heterogeneity among humans. Stepwise dissection of these interactions will permit the deciphering of MTB's complex virulence strategy. Previously, we have characterized a mouse supersusceptibility locus (sst1) controlling antituberculosis immunity. In this study, eight host resistance quantitative trait loci (QTLs) were mapped that counter-balance the devastating effect of sst1, among which a QTL on chromosome 7 (Chr7) was most prominent. The Chr7 and sst1 loci independently control distinct resistance mechanisms to MTB, but their effects apparently converge on macrophages in remarkable synergy. Combining these resistance alleles on a C3HeB/FeJ-susceptible background reduced the lung pathology and improved survival after MTB challenge accounting for half of the difference between susceptible and resistant parental strains. These data reveal novel gene interactions controlling MTB resistance and will enable the identification of resistance gene(s) encoded within Chr7 locus.

Sequential elimination of major-effect contributors identifies additional quantitative trait loci conditioning high-temperature growth in yeast

Several quantitative trait loci (QTL) mapping strategies can successfully identify major-effect loci, but often have poor success detecting loci with minor effects, potentially due to the confounding effects of major loci, epistasis, and limited sample sizes. To overcome such difficulties, we used a targeted backcross mapping strategy that genetically eliminated the effect of a previously identified major QTL underlying high-temperature growth (Htg) in yeast. This strategy facilitated the mapping of three novel QTL contributing to Htg of a clinically derived yeast strain. One QTL, which is linked to the previously identified major-effect QTL, was dissected, and NCS2 was identified as the causative gene. The interaction of the NCS2 QTL with the first major-effect QTL was background dependent, revealing a complex QTL architecture spanning these two linked loci. Such complex architecture suggests that more genes than can be predicted are likely to contribute to quantitative traits. The targeted backcrossing approach overcomes the difficulties posed by sample size, genetic linkage, and epistatic effects and facilitates identification of additional alleles with smaller contributions to complex traits.

High-resolution mapping of gene expression using association in an outbred mouse stock

Quantitative trait locus (QTL) analysis is a powerful tool for mapping genes for complex traits in mice, but its utility is limited by poor resolution. A promising mapping approach is association analysis in outbred stocks or different inbred strains. As a proof of concept for the association approach, we applied whole-genome association analysis to hepatic gene expression traits in an outbred mouse population, the MF1 stock, and replicated expression QTL (eQTL) identified in previous studies of F2 intercross mice. We found that the mapping resolution of these eQTL was significantly greater in the outbred population. Through an example, we also showed how this precise mapping can be used to resolve previously identified loci (in intercross studies), which affect many different transcript levels (known as eQTL “hotspots”), into distinct regions. Our results also highlight the importance of correcting for population structure in whole-genome association studies in the outbred stock.

In rodents, as in humans, traits such as obesity or diabetes are under the influence of many genes spread throughout the genome. Using linkage analysis, the locations of the major contributing genes can be mapped only to very large regions of chromosomes, usually encompassing hundreds of genes. This has made it difficult to identify the underlying genes and mutations. Another approach, analogous to genome-wide association in human populations, is to use association analyses among outbred stocks of mice. In this proof-of-principle article, we make use of common variations that locally perturb gene expression to demonstrate the greatly improved mapping resolution of association in mice. Our results indicate that association analyses in mice are a powerful approach to the dissection of complex traits and their underlying molecular networks.

Trait correlated expression combined with expression QTL analysis reveals biological pathways and candidate genes affecting water holding capacity of muscle

Background

Leakage of water and ions and soluble proteins from muscle cells occurs during prolonged exercise due to ischemia causing muscle damage. Also post mortem anoxia during conversion of muscle to meat is marked by loss of water and soluble components from the muscle cell. There is considerable variation in the water holding capacity of meat affecting economy of meat production. Water holding capacity depends on numerous genetic and environmental factors relevant to structural and biochemical muscle fibre properties a well as ante and post slaughter metabolic processes.

Results

Expression microarray analysis of M. longissimus dorsi RNAs of 74 F2 animals of a resource population showed 1,279 transcripts with trait correlated expression to water holding capacity. Negatively correlated transcripts were enriched in functional categories and pathways like extracellular matrix receptor interaction and calcium signalling. Transcripts with positive correlation dominantly represented biochemical processes including oxidative phosphorylation, mitochondrial pathways, as well as transporter activity. A linkage analysis of abundance of trait correlated transcripts revealed 897 expression QTL (eQTL) with 104 eQTL coinciding with QTL regions for water holding capacity; 96 transcripts had trans acting and 8 had cis acting regulation.

Conclusion

The complex relationships between biological processes taking place in live skeletal muscle and meat quality are driven on the one hand by the energy reserves and their utilisation in the muscle and on the other hand by the muscle structure itself and calcium signalling. Holistic expression profiling was integrated with QTL analysis for the trait of interest and for gene expression levels for creation of a priority list of genes out of the orchestra of genes of biological networks relevant to the liability to develop elevated drip loss.

Systematic analysis of emotionality in consomic mouse strains established from C57BL/6J and wild-derived MSM/Ms

Consomic strains have recently attracted attention as an advantageous method to screen for genes related to developmental, physiological, and behavioral phenotypes. Recently, a new set of consomic strains was established from the Japanese wild-derived mouse strain MSM/Ms and C57BL/6JJcl. By analyzing the entire consomic panel, we were able to identify a number of chromosomes associated with anxiety-like behaviors in the open-field (OF) test, a light-dark box and an elevated plus maze. Detailed observation of the OF behavior allowed us to identify chromosomes associated with those ethological traits, such as stretch attend, rearing, and jumping. Repeated OF test trials have different meanings for animals, and we found that some chromosomes responded to only the first or second trial, while others were consistent across both trials. By examining both male and female mice, sex-dependent effects were found in several measurements. Principal component analysis of anxiety-like behaviors extracted five factors: 'general locomotor activity', 'thigmotaxis', 'risk assessment', 'open-arm exploration' and 'autonomic emotionality'. We mapped chromosomes associated with these five factors of emotionality.

Positional cloning of "Lisch-Like", a candidate modifier of susceptibility to type 2 diabetes in mice

In 404 Lep^ob/ob F2 progeny of a C57BL/6J (B6) x DBA/2J (DBA) intercross, we mapped a DBA-related quantitative trait locus (QTL) to distal Chr1 at 169.6 Mb, centered about D1Mit110, for diabetes-related phenotypes that included blood glucose, HbA1c, and pancreatic islet histology. The interval was refined to 1.8 Mb in a series of B6.DBA congenic/subcongenic lines also segregating for Lep^ob. The phenotypes of B6.DBA congenic mice include reduced β-cell replication rates accompanied by reduced β-cell mass, reduced insulin/glucose ratio in blood, reduced glucose tolerance, and persistent mild hypoinsulinemic hyperglycemia. Nucleotide sequence and expression analysis of 14 genes in this interval identified a predicted gene that we have designated “Lisch-like” (Ll) as the most likely candidate. The gene spans 62.7 kb on Chr1qH2.3, encoding a 10-exon, 646–amino acid polypeptide, homologous to Lsr on Chr7qB1 and to Ildr1 on Chr16qB3. The largest isoform of Ll is predicted to be a transmembrane molecule with an immunoglobulin-like extracellular domain and a serine/threonine-rich intracellular domain that contains a 14-3-3 binding domain. Morpholino knockdown of the zebrafish paralog of Ll resulted in a generalized delay in endodermal development in the gut region and dispersion of insulin-positive cells. Mice segregating for an ENU-induced null allele of Ll have phenotypes comparable to the B.D congenic lines. The human ortholog, C1orf32, is in the middle of a 30-Mb region of Chr1q23-25 that has been repeatedly associated with type 2 diabetes.

Type 2 diabetes (T2D) accounts for over 90% of instances of diabetes and is a leading cause of medical morbidity and mortality. Twin studies indicate a strong polygenic contribution to susceptibility within the context of obesity. Although approximately ten genes making important contributions to individual risk have been identified, it is clear that others remain to be identified. In this study, we intercrossed obese, diabetes-resistant and diabetes-prone mouse strains to implicate a genetic interval on mouse Chr1 associated with reduced β-cell numbers and elevated blood glucose. We narrowed the region using molecular genetics and computational approaches to identify a novel gene we designated “Lisch-like” (Ll). The orthologous human genetic interval has been repeatedly implicated in T2D. Mice with an induced mutation that reduces Ll expression are impaired in both β-cell development and glucose metabolism, and reduced expression of the homologous gene in zebrafish disrupts islet development. Ll is expressed in organs implicated in the pathophysiology of T2D (hypothalamus, islets, liver, and skeletal muscle) and is predicted to encode a transmembrane protein that could mediate cholesterol transport and/or convey signals related to cell division. Either mechanism could mediate effects on β-cell mass that would predispose to T2D.

Differential sensitivity of mouse strains to an N-alkylated imino sugar: glycosphingolipid metabolism and acrosome formation

This review deals with the pharmacological properties of an alkylated monosaccharide mimetic, N-butyldeoxynojirimycin (NB-DNJ). This compound is of pharmacogenetic interest because one of its biological effects in mice - impairment of spermatogenesis, leading to male infertility - depends greatly on the genetic background of the animal. In susceptible mice, administration of NB-DNJ perturbs the formation of an organelle, the acrosome, in early post-meiotic male germ cells. In all recipient mice, irrespective of reproductive phenotype, NB-DNJ has a similar biochemical effect: inhibition of the glucosylceramidase beta-glucosidase 2 and subsequent elevation of glucosylceramide, a glycosphingolipid. The questions that we now need to address are: how can glucosylceramide specifically affect early acrosome formation, and why is this contingent on genetic factors? Here we discuss relevant aspects of reproductive biology, the metabolism and cell biology of sphingolipids, and complex trait analysis; we also present a speculative model that takes our observations into account.

Distribution and functional impact of DNA copy number variation in the rat

The abundance and dynamics of copy number variants (CNVs) in mammalian genomes poses new challenges in the identification of their impact on natural and disease phenotypes. We used computational and experimental methods to catalog CNVs in rat and found that they share important functional characteristics with those in human. In addition, 113 one-to-one orthologous genes overlap CNVs in both human and rat, 80 of which are implicated in human disease. CNVs are nonrandomly distributed throughout the genome. Chromosome 18 is a cold spot for CNVs as well as evolutionary rearrangements and segmental duplications, suggesting stringent selective mechanisms underlying CNV genesis or maintenance. By exploiting gene expression data available for rat recombinant inbred lines, we established the functional relationship of CNVs underlying 22 expression quantitative trait loci. These characteristics make the rat an excellent model for studying phenotypic effects of structural variation in relation to human complex traits and disease.

New therapeutic targets in immune disorders: ItpkB, Orai1 and UNC93B

BACKGROUND

Sequencing of the murine and human genomes has enabled large-scale functional genomics approaches to target identification. This holds the promise of drastically accelerating target discovery. Moreover, by providing an initial validation coincident with target identification, cell based cDNA or small interfering RNA (siRNA) screens and in particular genome-wide in vivo approaches, including forward or reverse genetics and analyses of natural gene polymorphisms, can move the relatively late step of target validation to the beginning of the process, reducing the risk of pursuing targets with little in vivo relevance.

OBJECTIVE

We critically discuss the value of combining functional genomics with traditional approaches for accelerating target identification and validation.

METHODS

We evaluate the potentials of inositol (1,4,5)trisphosphate 3-kinase B (ItpkB), Orai1 and UNC93B, three particularly interesting proteins that were recently identified through functional genomics, as targets in immune disorders.

RESULTS/CONCLUSION

Combining functional genomics with traditional approaches can accelerate target discovery and validation, but requires a follow-up platform that integrates and analyzes all relevant data for assessment of the clinical potential of the growing number of novel targets.

Candidate genes for obesity revealed from a C57BL/6J x 129S1/SvImJ intercross

OBJECTIVE

To identify the genes controlling body fat, we carried out a quantitative trait locus (QTL) analysis using C57BL/6J (B6) and 129S1/SvImJ (129) mice, which differ in obesity susceptibility after consuming an atherogenic diet.

METHODS

Mice were fed chow until 8 weeks and an atherogenic diet from 8 to 16 weeks; body fatness was measured by X-ray absorptiometry in 528 (B6 x 129) F(2) at 8 and 16 weeks. A high-density genome scan was performed using 508 polymorphic markers. After identifying the genetic loci, we narrowed the QTL using comparative genomics and bioinformatics.

RESULTS

The percentage of body fat was significantly linked to loci on chromosomes (Chr) 1 (22, 68 and 173 Mb), 4 (74 Mb), 5 (73 Mb), 7 (88 Mb), 8 (43 and 80 Mb), 9 (55 Mb), 11 (115 Mb) and 12 (32 Mb); three suggestive loci on Chrs 6 (76 Mb), 9 (30 Mb) and 16 (26 Mb) and two pairs of interacting loci (Chr 2 at 99.8 Mb with Chr 7; Chr 1 at 68 Mb with Chr 11). Comparative genomics narrowed the QTL intervals by 20-57% depending on the chromosome; in most cases, haplotype analysis further narrowed them by about 90%.

CONCLUSIONS

Our analysis identified 15 QTL for percentage of body fat. We narrowed the QTL using comparative genomics and haplotype analysis and suggest several candidate genes: Apcs on Chr 1, Ppargc1a on Chr 5, Ucp1 on Chr 8, Angptl6 on Chr 9 and Lpin1 on Chr 12.

A sensitized mutagenesis screen identifies Gli3 as a modifier of Sox10 neurocristopathy

Haploinsufficiency for the transcription factor SOX10 is associated with the pigmentary deficiencies of Waardenburg syndrome (WS) and is modeled in Sox10 haploinsufficient mice (Sox10(LacZ/+)). As genetic background affects WS severity in both humans and mice, we established an N-ethyl-N-nitrosourea (ENU) mutagenesis screen to identify modifiers that increase the phenotypic severity of Sox10(LacZ/+) mice. Analysis of 230 pedigrees identified three modifiers, named modifier of Sox10 neurocristopathies (Mos1, Mos2 and Mos3). Linkage analysis confirmed their locations on mouse chromosomes 13, 4 and 3, respectively, within regions distinct from previously identified WS loci. Positional candidate analysis of Mos1 identified a truncation mutation in a hedgehog(HH)-signaling mediator, GLI-Kruppel family member 3 (Gli3). Complementation tests using a second allele of Gli3 (Gli3(Xt-J)) confirmed that a null mutation of Gli3 causes the increased hypopigmentation in Sox10(LacZ/+);Gli3(Mos1/)(+) double heterozygotes. Early melanoblast markers (Mitf, Sox10, Dct, and Si) are reduced in Gli3(Mos1/)(Mos1) embryos, indicating that loss of GLI3 signaling disrupts melanoblast specification. In contrast, mice expressing only the GLI3 repressor have normal melanoblast specification, indicating that the full-length GLI3 activator is not required for specification of neural crest to the melanocyte lineage. This study demonstrates the feasibility of sensitized screens to identify disease modifier loci and implicates GLI3 and other HH signaling components as modifiers of human neurocristopathies.

From mutations to MAGIC: resources for gene discovery, validation and delivery in crop plants

The dissection of gene-trait associations and its translation into practice through plant breeding is a central aspect of modern plant biology. The identification of genes underlying simply inherited traits has been very successful. However, the identification of gene-trait associations for complex (multi-genic) traits in crop plants with large, often polyploid genomes has been limited by the absence of appropriate genetic resources that allow quantitative trait loci (QTL) and causal genes to be identified and localised. There has also been a tendency for genetic resources to be developed in germplasm not directly relevant to the breeding community limiting effective implementation. In this review, we discuss approaches to mapping genes and the development of Multi-parent Advanced Generation Inter-cross (MAGIC) populations derived from breeder-relevant germplasm as a platform for a new generation of gene-trait analysis in crop species.

Primer: strategies for identifying genes involved in renal disease

The globally increasing number of patients with end-stage renal disease urges the identification of molecular pathways involved in renal pathophysiology, to serve as targets for intervention. Moreover, the identification of genetic risk factors or protective genes can aid tailored therapy. Tools that can be used to identify genes involved in renal disease include gene expression arrays, linkage analysis and association studies. Arrays are a powerful and widely used approach to the analysis of gene transcription and protein expression, whereas linkage analysis and association studies link disease susceptibility to particular genetic regions. Animal models are available to pinpoint the disease-associated genes. Candidate genes so far identified in renal disease include those encoding the podocyte proteins nephrin and podocin, the transcription factor WT1, the calcium channel TRPC6 and the enzyme phospholipase C-epsilon-1 (in congenital nephrotic syndrome and focal segmental glomerulosclerosis), and carnosinase (in diabetic nephropathy). In addition, linkage studies have identified chromosomal regions implicated in systemic lupus erythematosus, diabetic nephropathy and familial IgA nephropathy. Future studies will elucidate the emerging role of epigenetic regulation of gene expression in renal disease.

Candidate genes for plasma triglyceride, FFA, and glucose revealed from an intercross between inbred mouse strains NZB/B1NJ and NZW/LacJ

To identify the genes controlling plasma concentrations of triglycerides (TGs), FFAs, and glucose, we carried out a quantitative trait loci (QTL) analysis of the closely related mouse strains New Zealand Black (NZB/B1NJ) and New Zealand White (NZW/LacJ), which share 63% of their genomes. The NZB x NZW F(2) progeny were genotyped and phenotyped to detect QTL, and then comparative genomics, bioinformatics, and sequencing were used to narrow the QTL and reduce the number of candidate genes. Triglyceride concentrations were linked to loci on chromosomes (Chr) 4, 7, 8, 10, and 18. FFA concentrations were affected by a significant locus on Chr 4, a suggestive locus on Chr 16, and two interacting loci on Chr 2 and 15. Plasma glucose concentrations were affected by QTL on Chr 2, 4, 7, 8, 10, 15, 17, and 18. Comparative genomics narrowed the QTL by 31% to 86%; haplotype analysis was usually able to further narrow it by 80%. We suggest several candidate genes: Gba2 on Chr 4, Irs2 on Chr 8, and Ppargc1b on Chr 18 for TG; A2bp1 on Chr 16 for FFA; and G6pc2 on Chr 2 and Timp3 on Chr 10 for glucose.

Genetic dissection of quantitative trait locus for ethanol sensitivity in long- and short-sleep mice

Interval-specific congenic strains (ISCS) allow fine mapping of a quantitative trait locus (QTL), narrowing its confidence interval by an order of magnitude or more. In earlier work, we mapped four QTL specifying differential ethanol sensitivity, assessed by loss of righting reflex because of ethanol (LORE), in the inbred long-sleep (ILS) and inbred short-sleep (ISS) strains, accounting for approximately 50% of the genetic variance for this trait. Subsequently, we generated reciprocal congenic strains in which each full QTL interval from ILS was bred onto the ISS background and vice versa. An earlier paper reported construction and results of the ISCS on the ISS background; here, we describe this process and report results on the ILS background. We developed multiple ISCS for each Lore QTL in which the QTL interval was broken into a number of smaller intervals. For each of the four QTL regions (chromosomes 1, 2, 11 and 15), we were successful in reducing the intervals significantly. Multiple, positive strains were overlapped to generate a single, reduced interval. Subsequently, this reduced region was overlaid on previous reductions from the ISS background congenics, resulting in substantial reductions in all QTL regions by approximately 75% from the initial mapping study. Genes with sequence or expression polymorphisms in the reduced intervals are potential candidates; evidence for these is presented. Genetic background effects can be important in detection of single QTL; combining this information with the generation of congenics on both backgrounds, as described here, is a powerful approach for fine mapping QTL.

Fine mapping of mouse QTLs for fatness using SNP data

Quantitative trait loci (QTLs), as determined in crossbred studies, are a valuable resource to identify genes responsible for the corresponding phenotypic variances. Due to their broad chromosomal extension of some dozens of megabases, further steps are necessary to bring the number of candidate genes that underlie the detected effects to a reasonable order of magnitude. We use a set of 13,370 SNPs to identify informative haplotype blocks in 22 mouse QTLs for fatness. About half of the genes in a typical QTL overlap with haplotype blocks, which are different for the two base mouse lines, and which, thus, qualify for further analysis. For these genes we collect four more pieces of evidence for association with fat accumulation, namely (1) homology to genes identified in a Caenorhabditis elegans knock-out experiment as fat decreasing or fat increasing, (2) the overexpression of the genes in mouse fat, liver, muscle, or hypothalamus tissues, (3) the occurrence of a gene in several independently found QTLs, and (4) the information provided by gene ontology, to achieve a ranked list of 131 candidate genes. Ten genes fulfill three or four of the above sketched criteria and are discussed briefly, 121 further genes fulfilling two criteria are provided as on-line material. Viewing the genomic region of fatness-related QTLs under several different aspects is appropriate to assess the many thousands of genes that reside in such QTLs and to produce lists of more robust candidate genes.