Bioinformatics toolbox for narrowing rodent quantitative trait loci

A genetic variant in IL-15Rα correlates with physical activity among European-American adults

BACKGROUND

Interleukin-15 (IL-15) is a myokine associated with muscle strength, possibly by attenuating protein breakdown. A variant in the alpha-receptor (IL-15Rα 1775 A>C, rs2228059) partially modulates the muscle strength and size response to resistance training. We examined if this polymorphism associated with habitual physical activity among European-American adults.

METHODS

Men (n = 240, 23.7 ± 0.3 year, body mass index [BMI] 25.3 ± 0.3 kg/m2 ) and women (n = 292, 23.2 ± 0.3 year, 24.0 ± 0.3 kg/m2 ) were genotyped. Physical activity phenotypes were derived from the Paffenbarger Physical Activity Questionnaire. Analysis of covariance (ancova) tested log-transformed differences between the IL-15Rα genotype and physical activity phenotypes by gender with age and BMI as covariates.

RESULTS

Men with the IL-15Rα 1775AA genotype spent more time in light intensity physical activity (39.4 ± 2.4 hr/week) than men with the CC genotype (28.6 ± 2.3 hr/week, (p = .009).

CONCLUSION

Further research is needed to confirm our finding and determine the possible mechanisms by which the IL-15Rα variant modulates light intensity physical activity.

Gene-by-Diet Interactions Affect Serum 1,25-Dihydroxyvitamin D Levels in Male BXD Recombinant Inbred Mice

1,25-Dihydroxyvitamin D (1,25[OH]2D) regulates calcium (Ca), phosphate, and bone metabolism. Serum 1,25(OH)2D levels are reduced by low vitamin D status and high fibroblast growth factor 23 (FGF23) levels and increased by low Ca intake and high PTH levels. Natural genetic variation controls serum 25-hydroxyvitamin D (25[OH]D) levels, but it is unclear how it controls serum 1,25(OH)2D or the response of serum 1,25(OH)2D levels to dietary Ca restriction (RCR). Male mice from 11 inbred lines and from 51 BXD recombinant inbred lines were fed diets with either 0.5% (basal) or 0.25% Ca from 4 to 12 weeks of age (n = 8 per line per diet). Significant variation among the lines was found in basal serum 1,25(OH)2D and in the RCR as well as basal serum 25(OH)D and FGF23 levels. 1,25(OH)2D was not correlated to 25(OH)D but was negatively correlated to FGF23 (r = -0.5). Narrow sense heritability of 1,25(OH)2D was 0.67 on the 0.5% Ca diet, 0.66 on the 0.25% Ca diet, and 0.59 for the RCR, indicating a strong genetic control of serum 1,25(OH)2D. Genetic mapping revealed many loci controlling 1,25(OH)2D (seven loci) and the RCR (three loci) as well as 25(OH)D (four loci) and FGF23 (two loci); a locus on chromosome 18 controlled both 1,25(OH)2D and FGF23. Candidate genes underlying loci include the following: Ets1 (1,25[OH]2D), Elac1 (FGF23 and 1,25[OH]2D), Tbc1d15 (RCR), Plekha8 and Lyplal1 (25[OH]D), and Trim35 (FGF23). This report is the first to reveal that serum 1,25(OH)2D levels are controlled by multiple genetic factors and that some of these genetic loci interact with the dietary environment.

Sports genetics moving forward: lessons learned from medical research

Sports genetics can take advantage of lessons learned from human disease genetics. By righting past mistakes and increasing scientific rigor, we can magnify the breadth and depth of knowledge in the field. We present an outline of challenges facing sports genetics in the light of experiences from medical research. Sports performance is complex, resulting from a combination of a wide variety of different traits and attributes. Improving sports genetics will foremost require analyses based on detailed phenotyping. To find widely valid, reproducible common variants associated with athletic phenotypes, study sample sizes must be dramatically increased. One paradox is that in order to confirm relevance, replications in specific populations must be undertaken. Family studies of athletes may facilitate the discovery of rare variants with large effects on athletic phenotypes. The complexity of the human genome, combined with the complexity of athletic phenotypes, will require additional metadata and biological validation to identify a comprehensive set of genes involved. Analysis of personal genetic and multiomic profiles contribute to our conceptualization of precision medicine; the same will be the case in precision sports science. In the refinement of sports genetics it is essential to evaluate similarities and differences between sexes and among ethnicities. Sports genetics to date have been hampered by small sample sizes and biased methodology, which can lead to erroneous associations and overestimation of effect sizes. Consequently, currently available genetic tests based on these inherently limited data cannot predict athletic performance with any accuracy.

Genetic regulation of bone strength: a review of animal model studies

Population- and family-based studies have established that fragility fracture risk is heritable; yet, the genome-wide association studies published to date have only accounted for a small fraction of the known variation for fracture risk of either the femur or the lumbar spine. Much work has been carried out using animal models toward finding genetic loci that are associated with bone strength. Studies using animal models overcome some of the issues associated with using patient data, but caution is needed when interpreting the results. In this review, we examine the types of tests that have been used for forward genetics mapping in animal models to identify loci and/or genes that regulate bone strength and discuss the limitations of these test methods. In addition, we present a summary of the quantitative trait loci that have been mapped for bone strength in mice, rats and chickens. The majority of these loci co-map with loci for bone size and/or geometry and thus likely dictate strength via modulating bone size. Differences in bone matrix composition have been demonstrated when comparing inbred strains of mice, and these matrix differences may be associated with differences in bone strength. However, additional work is needed to identify loci that act on bone strength at the materials level.

Using whole-genome sequences of the LG/J and SM/J inbred mouse strains to prioritize quantitative trait genes and nucleotides

Background

The laboratory mouse is the most commonly used model for studying variation in complex traits relevant to human disease. Here we present the whole-genome sequences of two inbred strains, LG/J and SM/J, which are frequently used to study variation in complex traits as diverse as aging, bone-growth, adiposity, maternal behavior, and methamphetamine sensitivity.

Results

We identified small nucleotide variants (SNVs) and structural variants (SVs) in the LG/J and SM/J strains relative to the reference genome and discovered novel variants in these two strains by comparing their sequences to other mouse genomes. We find that 39% of the LG/J and SM/J genomes are identical-by-descent (IBD). We characterized amino-acid changing mutations using three algorithms: LRT, PolyPhen-2 and SIFT. We also identified polymorphisms between LG/J and SM/J that fall in regulatory regions and highly informative transcription factor binding sites (TFBS). We intersected these functional predictions with quantitative trait loci (QTL) mapped in advanced intercrosses of these two strains. We find that QTL are both over-represented in non-IBD regions and highly enriched for variants predicted to have a functional impact. Variants in QTL associated with metabolic (231 QTL identified in an F₁₆ generation) and developmental (41 QTL identified in an F₃₄ generation) traits were interrogated and we highlight candidate quantitative trait genes (QTG) and nucleotides (QTN) in a QTL on chr13 associated with variation in basal glucose levels and in a QTL on chr6 associated with variation in tibia length.

Conclusions

We show how integrating genomic sequence with QTL reduces the QTL search space and helps researchers prioritize candidate genes and nucleotides for experimental follow-up. Additionally, given the LG/J and SM/J phylogenetic context among inbred strains, these data contribute important information to the genomic landscape of the laboratory mouse.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1592-3) contains supplementary material, which is available to authorized users.

Differential skeletal muscle proteome of high- and low-active mice

Physical inactivity contributes to cardiovascular disease, type II diabetes, obesity, and some types of cancer. While the literature is clear that there is genetic regulation of physical activity with existing gene knockout data suggesting that skeletal muscle mechanisms contribute to the regulation of activity, actual differences in end-protein expression between high- and low-active mice have not been investigated. This study used two-dimensional differential gel electrophoresis coupled with mass spectrometry to evaluate the proteomic differences between high-active (C57L/J) and low-active (C3H/HeJ) mice in the soleus and extensor digitorum longus (EDL). Furthermore, vivo-morpholinos were used to transiently knockdown candidate proteins to confirm their involvement in physical activity regulation. Proteins with higher expression patterns generally fell into the calcium-regulating and Krebs (TCA) cycle pathways in the high-active mice (e.g., annexin A6, P = 0.0031; calsequestrin 1; P = 0.000025), while the overexpressed proteins in the low-active mice generally fell into cytoskeletal structure- and electron transport chain-related pathways (e.g., ATPase, P = 0.031; NADH dehydrogenase, P = 0.027). Transient knockdown of annexin A6 and calsequestrin 1 protein of high-active mice with vivo-morpholinos resulted in decreased physical activity levels (P = 0.001). These data suggest that high- and low-active mice have unique protein expression patterns and that each pattern contributes to the peripheral capability to be either high- or low-active, suggesting that different specific mechanisms regulate activity leading to the high- or low-activity status of the animal.

Differential gene expression in high- and low-active inbred mice

Numerous candidate genes have been suggested in the recent literature with proposed roles in regulation of voluntary physical activity, with little evidence of these genes' functional roles. This study compared the haplotype structure and expression profile in skeletal muscle and brain of inherently high- (C57L/J) and low- (C3H/HeJ) active mice. Expression of nine candidate genes [Actn2, Actn3, Casq1, Drd2, Lepr, Mc4r, Mstn, Papss2, and Glut4 (a.k.a. Slc2a4)] was evaluated via RT-qPCR. SNPs were observed in regions of Actn2, Casq1, Drd2, Lepr, and Papss2; however, no SNPs were located in coding sequences or associated with any known regulatory sequences. In mice exposed to a running wheel, Casq1 (P = 0.0003) and Mstn (P = 0.002) transcript levels in the soleus were higher in the low-active mice. However, when these genes were evaluated in naïve animals, differential expression was not observed, demonstrating a training effect. Among naïve mice, no genes in either tissue exhibited differential expression between strains. Considering that no obvious SNP mechanisms were determined or differential expression was observed, our results indicate that genomic structural variation or gene expression data alone is not adequate to establish any of these genes' candidacy or causality in relation to regulation of physical activity.

Recalculation of 23 mouse HDL QTL datasets improves accuracy and allows for better candidate gene analysis

In the past 15 years, the quantitative trait locus (QTL) mapping approach has been applied to crosses between different inbred mouse strains to identify genetic loci associated with plasma HDL cholesterol levels. Although successful, a disadvantage of this method is low mapping resolution, as often several hundred candidate genes fall within the confidence interval for each locus. Methods have been developed to narrow these loci by combining the data from the different crosses, but they rely on the accurate mapping of the QTL and the treatment of the data in a consistent manner. We collected 23 raw datasets used for the mapping of previously published HDL QTL and reanalyzed the data from each cross using a consistent method and the latest mouse genetic map. By utilizing this approach, we identified novel QTL and QTL that were mapped to the wrong part of chromosomes. Our new HDL QTL map allows for reliable combining of QTL data and candidate gene analysis, which we demonstrate by identifying Grin3a and Etv6, as candidate genes for QTL on chromosomes 4 and 6, respectively. In addition, we were able to narrow a QTL on Chr 19 to five candidates.

A major X-linked locus affects kidney function in mice

Chronic kidney disease is a common disease with increasing prevalence in the western population. One common reason for chronic kidney failure is diabetic nephropathy. Diabetic nephropathy and hyperglycemia are characteristics of the mouse inbred strain KK/HlJ, which is predominantly used as a model for metabolic syndrome due to its inherited glucose intolerance and insulin resistance. We used KK/HlJ, an albuminuria-sensitive strain, and C57BL/6J, an albuminuria-resistant strain, to perform a quantitative trait locus (QTL) cross to identify the genetic basis for chronic kidney failure. Albumin-creatinine ratio (ACR) was measured in 130 F2 male offspring. One significant QTL was identified on chromosome (Chr) X and four suggestive QTL were found on Chrs 6, 7, 12, and 13. Narrowing of the QTL region was focused on the X-linked QTL and performed by incorporating genotype and expression analyses for genes located in the region. From the 485 genes identified in the X-linked QTL region, a few candidate genes were identified using a combination of bioinformatic evidence based on genomic comparison of the parental strains and known function in urine homeostasis. Finally, this study demonstrates the significance of the X chromosome in the genetic determination of albuminuria.

Spontaneous trigeminal allodynia in rats: a model of primary headache

Animal models are essential for studying the pathophysiology of headache disorders and as a screening tool for new therapies. Most animal models modify a normal animal in an attempt to mimic migraine symptoms. They require manipulation to activate the trigeminal nerve or dural nociceptors. At best, they are models of secondary headache. No existing model can address the fundamental question: How is a primary headache spontaneously initiated? In the process of obtaining baseline periorbital von Frey thresholds in a wild-type Sprague-Dawley rat, we discovered a rat with spontaneous episodic trigeminal allodynia (manifested by episodically changing periorbital pain threshold). Subsequent mating showed that the trait is inherited. Animals with spontaneous trigeminal allodynia allow us to study the pathophysiology of primary recurrent headache disorders. To validate this as a model for migraine, we tested the effects of clinically proven acute and preventive migraine treatments on spontaneous changes in rat periorbital sensitivity. Sumatriptan, ketorolac, and dihydroergotamine temporarily reversed the low periorbital pain thresholds. Thirty days of chronic valproic acid treatment prevented spontaneous changes in trigeminal allodynia. After discontinuation, the rats returned to their baseline of spontaneous episodic threshold changes. We also tested the effects of known chemical human migraine triggers. On days when the rats did not have allodynia and showed normal periorbital von Frey thresholds, glycerol trinitrate and calcitonin gene related peptide induced significant decreases in the periorbital pain threshold. This model can be used as a predictive model for drug development and for studies of putative biomarkers for headache diagnosis and treatment.

Genetic analysis of albuminuria in collaborative cross and multiple mouse intercross populations

Albuminuria is an important marker of nephropathy that increases the risk of progressive renal and chronic cardiovascular diseases. The genetic basis of kidney disease is well-established in humans and rodent models, but the causal genes remain to be identified. We applied several genetic strategies to map and refine genetic loci affecting albuminuria in mice and translated the findings to human kidney disease. First, we measured albuminuria in mice from 33 inbred strains, used the data for haplotype association mapping (HAM), and detected 10 genomic regions associated with albuminuria. Second, we performed eight F(2) intercrosses between genetically diverse strains to identify six loci underlying albuminuria, each of which was concordant to kidney disease loci in humans. Third, we used the Oak Ridge National Laboratory incipient Collaborative Cross subpopulation to detect an additional novel quantitative trait loci (QTL) underlying albuminuria. We also performed a ninth intercross, between genetically similar strains, that substantially narrowed an albuminuria QTL on Chromosome 17 to a region containing four known genes. Finally, we measured renal gene expression in inbred mice to detect pathways highly correlated with albuminuria. Expression analysis also identified Glcci1, a gene known to affect podocyte structure and function in zebrafish, as a strong candidate gene for the albuminuria QTL on Chromosome 6. Overall, these findings greatly enhance our understanding of the genetic basis of albuminuria in mice and may guide future studies into the genetic basis of kidney disease in humans.

Genetic regulation of life span, metabolism, and body weight in Pohn, a new wild-derived mouse strain

Quantitative trait loci (QTL) of longevity identified in human and mouse are significantly colocalized, suggesting that common mechanisms are involved. However, the limited number of strains that have been used in mouse longevity studies undermines the ability to identify longevity genes. We crossed C57BL/6J mice with a new wild-derived strain, Pohn, and identified two life span QTL-Ls1 and Ls2. Interestingly, homologous human longevity QTL colocalize with Ls1. We also defined new QTL for metabolic heat production and body weight. Both phenotypes are significantly correlated with life span. We found that large clone ratio, an in vitro indicator for cellular senescence, is not correlated with life span, suggesting that cell senescence and intrinsic aging are not always associated. Overall, by using Pohn mice, we identified new QTL for longevity-related traits, thus facilitating the exploration of the genetic regulation of aging.

Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross

A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification.

Genetic basis of atherosclerosis: insights from mice and humans

Atherosclerosis is a complex and heritable disease involving multiple cell types and the interactions of many different molecular pathways. The genetic and molecular mechanisms of atherosclerosis have, in part, been elucidated by mouse models; at least 100 different genes have been shown to influence atherosclerosis in mice. Importantly, unbiased genome-wide association studies have recently identified a number of novel loci robustly associated with atherosclerotic coronary artery disease. Here, we review the genetic data elucidated from mouse models of atherosclerosis, as well as significant associations for human coronary artery disease. Furthermore, we discuss in greater detail some of these novel human coronary artery disease loci. The combination of mouse and human genetics has the potential to identify and validate novel genes that influence atherosclerosis, some of which may be candidates for new therapeutic approaches.

Genome-wide association for methamphetamine sensitivity in an advanced intercross mouse line

Sensitivity to the locomotor stimulant effects of methamphetamine (MA) is a heritable trait that utilizes neurocircuitry also associated with the rewarding effects of drugs. We used the power of a C57BL/6J × DBA/2J F(2) intercross (n = 676) and the precision of a C57BL/6J × DBA/2J F(8) advanced intercross line (Aap: B6, D2-G8; or F(8) AIL; n = 552) to identify and narrow quantitative trait loci (QTLs) associated with sensitivity to the locomotor stimulant effects of MA. We used the program QTLRel to simultaneously map QTL in the F(2) and F(8) AIL mice. We identified six genome-wide significant QTLs associated with locomotor activity at baseline and seven genome-wide significant QTLs associated with MA-induced locomotor activation. The average per cent decrease in QTL width between the F(2) and the integrated analysis was 65%. Additionally, these QTLs showed a distinct temporal specificity within each session that allowed us to further refine their locations, and identify one QTL with a 1.8-LOD support interval of 1.47 Mb. Next, we utilized publicly available bioinformatics resources to exploit strain-specific sequence data and strain- and region-specific expression data to identify candidate genes. These results illustrate the power of AILs in conjunction with sequence and gene expression data to investigate the genetic underpinnings of behavioral and other traits.

Forward genetic approaches to understanding complex behaviors

Assigning function to genes has long been a focus of biomedical research.Even with complete knowledge of the genomic sequences of humans, mice and other experimental organisms, there is still much to be learned about gene function and control. Ablation or overexpression of single genes using knockout or transgenic technologies has provided functional annotation for many genes, but these technologies do not capture the extensive genetic variation present in existing experimental mouse populations. Researchers have only recently begun to truly appreciate naturally occurring genetic variation resulting from single nucleotide substitutions,insertions, deletions, copy number variation, epigenetic changes (DNA methylation,histone modifications, etc.) and gene expression differences and how this variation contributes to complex phenotypes. In this chapter, we will discuss the benefits and limitations of different forward genetic approaches that capture the genetic variation present in inbred mouse strains and present the utility of these approaches for mapping QTL that influence complex behavioral phenotypes.

Vesico-ureteric reflux: using mouse models to understand a common congenital urinary tract defect

Vesico-ureteric reflux (VUR) is a common congenital urinary tract defect in which urine flows retrogradely from the bladder to the kidneys because of an abnormally formed uretero-vesical junction. It is associated with recurrent urinary tract infections, renal hypo/dysplasia, reflux nephropathy, hypertension, and end-stage renal disease. In humans, VUR is genetically and phenotypically heterogeneous, encompassing diverse renal and urinary tract phenotypes. To understand the significance of these phenotypes, we and others have used the mouse as a model organism and this has led to the identification of new candidate genes. Through careful phenotypic analysis of these models, a new understanding of the genetics and biology of VUR is now underway.

Cross-species behavioural genetics: A starting point for unravelling the neurobiology of human psychiatric disorders

Identifying the genetic and neurobiological mechanisms underlying certain behavioural traits is an important strategy to understand the aetiology of various psychiatric disorders and to find potential new treatment possibilities. It has proven a great challenge to develop paradigms that allow translational research for behavioural phenotypes that are relevant for disorders across the psychiatric spectrum. Recently, there has been increasing attention for studies that implement rodent behavioural paradigms in the home cage to assess the association between genetic backgrounds and behavioural traits. The application of interspecies genetics to unravel these traits has revealed novel insights in the genetic mechanisms that are encoding phenotypes relevant to biological processes underlying psychiatric disorders. By means of two examples, namely the stress-induced hyperthermia paradigm and the home cage environment, this review aims to show that by using individual genetic variations with phenotypes obtained from mice and across categories of neuropsychiatric disorders, novel insights in the neurobiological trajectory of psychiatric disorders can be obtained.

Glucuronic acid epimerase is associated with plasma triglyceride and high-density lipoprotein cholesterol levels in Turks

We narrowed chromosome 15q21-23 linkage to plasma high-density lipoprotein cholesterol (HDL-C) levels in Turkish families by fine mapping, then focused on glucuronic acid epimerase (GLCE), a heparan sulfate proteoglycan (HSPG) biosynthesis enzyme. HSPGs participate in lipid metabolism along with apolipoprotein (apo) E. Of 31 SNPs in the GLCE locus, nine analyzed by haplotype were associated with HDL-C and triglyceride levels (permuted p = 0.006 and 0.013, respectively) in families. Of five tagging GLCE SNPs in two cohorts of unrelated subjects, three (rs16952868, rs11631403, and rs3865014) were associated with triglyceride and HDL-C levels in males (nonpermuted p < 0.05). The association was stronger in APOE 2/3 subjects (apoE2 has reduced binding to HSPGs) and reached multiple-testing significance (p < 0.05) in both males and females (n= 2612). Similar results were obtained in the second cohort (n= 1164). Interestingly, at the GLCE locus, bounded by recombination hotspots, Turks had a minor allele frequency of SNPs resembling Chinese more than European ancestry; adjoining regions resembled the European pattern. Studies of glce(+/-) apoe(-/-) mice fed a chow or high-fat diet supported a role for GLCE in lipid metabolism. Thus, SNPs in GLCE are associated with triglyceride and HDL-C levels in Turks, and mouse studies support a role for glce in lipid metabolism.

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a "toolbox" of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits.

Combining genome-wide data from humans and animal models of dyslipidemia and atherosclerosis

PURPOSE OF REVIEW

Comparative genomics allows researchers to combine genome-wide association data from humans with studies in animal models in order to assist in the identification of the genes and the genetic variants that modify susceptibility to dyslipidemia and atherosclerosis.

RECENT FINDINGS

Association and linkage studies in human and rodent species have been successful in identifying genetic loci associated with complex traits, but have been less robust in identifying and validating the responsible gene and/or genetic variants. Recent technological advancements have assisted in the development of comparative genomic approaches, which rely on the combination of human and rodent datasets and bioinformatics tools, followed by the narrowing of concordant loci and improved identification of candidate genes and genetic variants. Additionally, candidate genes and genetic variants identified by these methods have been further validated and functionally investigated in animal models, a process that is not feasible in humans.

SUMMARY

Comparative genomic approaches have led to the identification and validation of several new genes, including a few not previously implicated, as modifiers of plasma lipid levels and atherosclerosis, yielding new insights into the biological mechanisms of these complex traits.

The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol

Genome-wide association (GWA) studies represent a powerful strategy for identifying susceptibility genes for complex diseases in human populations but results must be confirmed and replicated. Because of the close homology between mouse and human genomes, the mouse can be used to add evidence to genes suggested by human studies. We used the mouse quantitative trait loci (QTL) map to interpret results from a GWA study for genes associated with plasma HDL cholesterol levels. We first positioned single nucleotide polymorphisms (SNPs) from a human GWA study on the genomic map for mouse HDL QTL. We then used mouse bioinformatics, sequencing, and expression studies to add evidence for one well-known HDL gene (Abca1) and three newly identified genes (Galnt2, Wwox, and Cdh13), thus supporting the results of the human study. For GWA peaks that occur in human haplotype blocks with multiple genes, we examined the homologous regions in the mouse to prioritize the genes using expression, sequencing, and bioinformatics from the mouse model, showing that some genes were unlikely candidates and adding evidence for candidate genes Mvk and Mmab in one haplotype block and Fads1 and Fads2 in the second haplotype block. Our study highlights the value of mouse genetics for evaluating genes found in human GWA studies.

Current understanding of the genetic basis for physical activity

Although it is well known that physical activity prevents and ameliorates a large number of conditions and chronic diseases, it is also incontrovertible that physical inactivity is becoming more prevalent. This paradox has led some to suggest that genetic/biological factors influence activity levels as opposed to the classical notion that voluntary activity is solely regulated by environmental factors. There is a plethora of recent data showing that there is considerable genetic influence on activity levels in both humans and animals and emerging evidence suggesting potential genomic locations for those genetic factors. Several independent lines of evidence suggest that dopamine receptor 1 (Drd1) and nescient helix loop helix (Nhlh2) are excellent candidate genes for the regulation of physical activity, with several other potential candidate genes only partially supported. This foundation provides the basis for continuing work to identify additional candidate genes, to identify other genetic factors that are involved in the regulation of physical activity, and to investigate the mechanisms by which these genes and genetic factors regulate activity.

Cancer evolution and individual susceptibility

Cancer susceptibility is due to interactions between inherited genetic factors and exposure to environmental carcinogens. The genetic component is constituted mainly by weakly acting low-penetrance genetic variants that interact among themselves, as well as with the environment. These low susceptibility genes can be categorized into two main groups: one includes those that control intrinsic tumor cell activities (i.e. apoptosis, proliferation or DNA repair), and the other contains those that modulate the function of extrinsic tumor cell compartments (i.e. stroma, angiogenesis, or endocrine and immune systems). Genome-Wide Association Studies (GWAS) of human populations have identified numerous genetic loci linked with cancer risk and behavior, but nevertheless the major component of cancer heritability remains to be explained. One reason may be that GWAS cannot readily capture gene-gene or gene-environment interactions. Mouse model approaches offer an alternative or complementary strategy, because of our ability to control both the genetic and environmental components of risk. Recently developed genetic tools, including high-throughput technologies such as SNP, CGH and gene expression microarrays, have led to more powerful strategies for refining quantitative trait loci (QTL) and identifying the critical genes. In particular, the cross-species approaches will help to refine locations of QTLs, and reveal their genetic and environmental interactions. The identification of human tumor susceptibility genes and discovery of their roles in carcinogenesis will ultimately be important for the development of methods for prediction of risk, diagnosis, prevention and therapy for human cancers.

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.

Fluoride's effects on the formation of teeth and bones, and the influence of genetics

Fluorides are present in the environment. Excessive systemic exposure to fluorides can lead to disturbances of bone homeostasis (skeletal fluorosis) and enamel development (dental/enamel fluorosis). The severity of dental fluorosis is also dependent upon fluoride dose and the timing and duration of fluoride exposure. Fluoride's actions on bone cells predominate as anabolic effects both in vitro and in vivo. More recently, fluoride has been shown to induce osteoclastogenesis in mice. Fluorides appear to mediate their actions through the MAPK signaling pathway and can lead to changes in gene expression, cell stress, and cell death. Different strains of inbred mice demonstrate differential physiological responses to ingested fluoride. Genetic studies in mice are capable of identifying and characterizing fluoride-responsive genetic variations. Ultimately, this can lead to the identification of at-risk human populations who are susceptible to the unwanted or potentially adverse effects of fluoride action and to the elucidation of fundamental mechanisms by which fluoride affects biomineralization.

Identification of genetic determinants of IGF-1 levels and longevity among mouse inbred strains

The IGF-1 signaling pathway plays an important role in regulating longevity. To identify the genetic loci and genes that regulate plasma IGF-1 levels, we intercrossed MRL/MpJ and SM/J, inbred mouse strains that differ in IGF-1 levels. Quantitative trait loci (QTL) analysis of IGF-1 levels of these F2 mice detected four QTL on chromosomes (Chrs) 9 (48 Mb), 10 (86 Mb), 15 (18 Mb), and 17 (85 Mb). Haplotype association mapping of IGF-1 levels in 28 domesticated inbred strains identified three suggestive loci in females on Chrs 2 (13 Mb), 10 (88 Mb), and 17 (28 Mb) and in four males on Chrs 1 (159 Mb), 3 (52 and 58 Mb), and 16 (74 Mb). Except for the QTL on Chr 9 and 16, all loci co-localized with IGF-1 QTL previously identified in other mouse crosses. The most significant locus was the QTL on Chr 10, which contains the Igf1 gene and which had a LOD score of 31.8. Haplotype analysis among 28 domesticated inbred strains revealed a major QTL on Chr 10 overlapping with the QTL identified in the F2 mice. This locus showed three major haplotypes; strains with haplotype 1 had significantly lower plasma IGF-1 and extended longevity (P < 0.05) than strains with haplotype 2 or 3. Bioinformatic analysis, combined with sequencing and expression studies, showed that Igf1 is the most likely QTL gene, but that other genes may also play a role in this strong QTL.

A wild derived quantitative trait locus on mouse chromosome 2 prevents obesity

Background

The genetic architecture of multifactorial traits such as obesity has been poorly understood. Quantitative trait locus (QTL) analysis is widely used to localize loci affecting multifactorial traits on chromosomal regions. However, large confidence intervals and small phenotypic effects of identified QTLs and closely linked loci are impeding the identification of causative genes that underlie the QTLs. Here we developed five subcongenic mouse strains with overlapping and non-overlapping wild-derived genomic regions from an F2 intercross of a previously developed congenic strain, B6.Cg-Pbwg1, and its genetic background strain, C57BL/6J (B6). The subcongenic strains developed were phenotyped on low-fat standard chow and a high-fat diet to fine-map a previously identified obesity QTL. Microarray analysis was performed with Affymetrix GeneChips to search for candidate genes of the QTL.

Results

The obesity QTL was physically mapped to an 8.8-Mb region of mouse chromosome 2. The wild-derived allele significantly decreased white fat pad weight, body weight and serum levels of glucose and triglyceride. It was also resistant to the high-fat diet. Among 29 genes residing within the 8.8-Mb region, Gpd2, Upp2, Acvr1c, March7 and Rbms1 showed great differential expression in livers and/or gonadal fat pads between B6.Cg-Pbwg1 and B6 mice.

Conclusions

The wild-derived QTL allele prevented obesity in both mice fed a low-fat standard diet and mice fed a high-fat diet. This finding will pave the way for identification of causative genes for obesity. A further understanding of this unique QTL effect at genetic and molecular levels may lead to the discovery of new biological and pathologic pathways associated with obesity.

Quantitative trait loci for electrocardiographic parameters and arrhythmia in the mouse

Cardiac arrhythmias associated with sudden death are influenced by multiple biological pathways and are modulated by numerous genetic and environmental factors. Elevated heart rate and prolonged ECG indices of conduction and repolarization have been associated with risk of sudden death. Insight into the genetic underpinnings of these parameters thus provides an important means to the dissection of the genetic components modulating risk of sudden cardiac death. In this study we mapped quantitative trait loci (QTL) modulating heart rate, ECG indices of conduction and repolarization, and susceptibility to arrhythmia, in a conduction disease-sensitized F(2) mouse population. Heart rate, P-duration, PR-, QRS- and QT-interval were measured at baseline (n=502) and after flecainide administration (n=370) in mutant F(2) progeny (F(2)-MUT) resulting from the FVB/NJ-Scn5a1798(insD/+) X 129P2-Scn5a1798(insD/+) mouse cross. Episodes of sinus arrhythmia and ventricular tachyarrhythmia occurring post-flecainide were treated as binary traits. F(2)-MUT mice were genotyped using a genome-wide 768 single nucleotide polymorphism (SNP) panel. Interval mapping uncovered multiple QTL for ECG parameters and arrhythmia. A sex-interacting scan identified QTL displaying sex-dependency, and a two-dimensional QTL scan unmasked locus-locus (epistasis) interactions influencing ECG traits. A number of QTL coincided at specific chromosomal locations, suggesting pleiotropic effects at these loci. Through transcript profiling in myocardium from the parental mouse strains we identified genes co-localizing at the identified QTL that constitute highly relevant candidates for the observed effects. The detection of QTL influencing ECG indices and arrhythmia is an essential step towards identifying genetic networks for sudden, arrhythmic, cardiac death.

Mouse BMD quantitative trait loci show improved concordance with human genome-wide association loci when recalculated on a new, common mouse genetic map

Bone mineral density (BMD) is a heritable trait, and in mice, over 100 quantitative trait loci (QTLs) have been reported, but candidate genes have been identified for only a small percentage. Persistent errors in the mouse genetic map have negatively affected QTL localization, spurring the development of a new, corrected map. In this study, QTLs for BMD were remapped in 11 archival mouse data sets using this new genetic map. Since these QTLs all were mapped in a comparable way, direct comparisons of QTLs for concordance would be valid. We then compared human genome-wide association study (GWAS) BMD loci with the mouse QTLs. We found that 26 of the 28 human GWAS loci examined were located within the confidence interval of a mouse QTL. Furthermore, 14 of the GWAS loci mapped to within 3 cM of a mouse QTL peak. Lastly, we demonstrated that these newly remapped mouse QTLs can substantiate a candidate gene for a human GWAS locus, for which the peak single-nucleotide polymorphism (SNP) fell in an intergenic region. Specifically, we suggest that MEF2C (human chromosome 5, mouse chromosome 13) should be considered a candidate gene for the genetic regulation of BMD. In conclusion, use of the new mouse genetic map has improved the localization of mouse BMD QTLs, and these remapped QTLs show high concordance with human GWAS loci. We believe that this is an opportune time for a renewed effort by the genetics community to identify the causal variants regulating BMD using a synergistic mouse-human approach.

Untangling HDL quantitative trait loci on mouse chromosome 5 and identifying Scarb1 and Acads as the underlying genes

Two high-density lipoprotein cholesterol quantitative trait loci (QTL), Hdlq1 at 125 Mb and Hdlq8 at 113 Mb, were previously identified on mouse distal chromosome 5. Our objective was to identify the underlying genes. We first used bioinformatics to narrow the Hdlq1 locus to 56 genes. The most likely candidate, Scarb1 (scavenger receptor B1), was supported by gene expression data consistent with knockout and transgenic mouse models. Then we confirmed Hdlq8 as an independent QTL by detecting it in an intercross between NZB and NZW (LOD = 12.7), two mouse strains that have identical genotypes for Scarb1. Haplotyping narrowed this QTL to 9 genes; the most likely candidate was Acads (acyl-coenzymeA dehydrogenase, short chain). Sequencing showed that Acads had an amino acid polymorphism, Gly94Asp, in a conserved region; Western blotting showed that protein levels were significantly different between parental strains. A previously known spontaneous deletion causes loss of ACADS activity in BALB/cBy mice. We showed that HDL levels were significantly elevated in BALB/cBy compared with BALB/c mice and that this HDL difference cosegregated with the Acads mutation. We confirmed that Hdlq1 and Hdlq8 are independent QTL on mouse chromosome 5 and demonstrated that Scarb1 and Acads are the underlying genes.

Combining QTL data for HDL cholesterol levels from two different species leads to smaller confidence intervals

Quantitative trait locus (QTL) analysis detects regions of a genome that are linked to a complex trait. Once a QTL is detected, the region is narrowed by positional cloning in the hope of determining the underlying candidate gene-methods used include creating congenic strains, comparative genomics and gene expression analysis. Combined cross analysis may also be used for species such as the mouse, if the QTL is detected in multiple crosses. This process involves the recoding of QTL data on a per-chromosome basis, with the genotype recoded on the basis of high- and low-allele status. The data are then combined and analyzed; a successful analysis results in a narrowed and more significant QTL. Using parallel methods, we show that it is possible to narrow a QTL by combining data from two different species, the rat and the mouse. We combined standardized high-density lipoprotein phenotype values and genotype data for the rat and mouse using information from one rat cross and two mouse crosses. We successfully combined data within homologous regions from rat Chr 6 onto mouse Chr 12, and from rat Chr 10 onto mouse Chr 11. The combinations and analyses resulted in QTL with smaller confidence intervals and increased logarithm of the odds ratio scores. The numbers of candidate genes encompassed by the QTL on mouse Chr 11 and 12 were reduced from 1343 to 761 genes and from 613 to 304 genes, respectively. This is the first time that QTL data from different species were successfully combined; this method promises to be a useful tool for narrowing QTL intervals.

The C3H/HeJ inbred mouse is a model of vesico-ureteric reflux with a susceptibility locus on chromosome 12

Vesico-ureteric reflux is the most common congenital anomaly of the urinary tract, characterized by a defective uretero-vesical junction with retrograde urine flow from the bladder toward the kidneys. Because there is strong evidence for a genetic basis for some cases of vesico-ureteric reflux, we screened 11 inbred mouse strains for reflux and kidney size and identified one strain, C3H/HeJ, that has a 100 percent incidence of vesico-ureteric reflux with otherwise normal kidneys at birth. These mice are predisposed to reflux as a result of a defective uretero-vesical junction characterized by a short intravesical ureter. This defect results from a delay in urinary tract development initially manifested by a ureteric bud arising from a more caudal location along the mesonephric duct. In contrast, C57BL/6J mice (resistant to reflux at birth) have long intravesical ureters, normally positioned ureteric buds, and no delay in urinary tract development. Genome-wide and additional fine mapping of backcross mice, derived from C3H/HeJ and C57BL/6J crosses, identified a significant reflux susceptibility locus, Vurm1, on chromosome 12 (peak logarithm of the odds=7.39). The C3H/HeJ mouse is a model of vesico-ureteric reflux without renal malformation, and further characterization of this model will allow for the identification of a pathway important for urinary tract development, a finding that will serve as a model for the human disorder.

Congenic and bioinformatics analyses resolved a major-effect Fob3b QTL on mouse Chr 15 into two closely linked loci

We previously identified a Chr 15 quantitative trait locus (QTL) Fob3b in lines of mice selected for high (Fat line) and low (Lean line) body fat content that represent a unique model of polygenic obesity. Here we genetically dissected the Fob3b interval by analyzing the phenotypes of eight overlapping congenic lines and four F(2) congenic intercrosses and prioritized candidates by bioinformatics approaches. Analyses revealed that the Fob3b QTL consists of at least two separate linked QTLs Fob3b1 and Fob3b2. They exhibit additive inheritance and are linked in coupling with alleles originating from the Lean line, decreasing obesity-related traits. In further analyses, we focused on Fob3b1 because it had a larger effect on obesity-related traits than Fob3b2, e.g., the difference between homozygotes for adiposity index (ADI) percentage was 1.22 and 0.77% for Fob3b1 and Fob3b2, respectively. A set of bioinformatics tools was used to narrow down positional candidates from 85 to 4 high-priority Fob3b1 candidates. A previous single Fob3b QTL was therefore resolved into another two closely linked QTLs, confirming the fractal nature of QTLs mapped at low resolution. The interval of the original Fob3b QTL was narrowed from 22.39 to 4.98 Mbp for Fob3b1 and to 7.68 Mbp for Fob3b2, which excluded the previously assigned candidate squalene epoxidase (Sqle) as the causal gene because it maps proximal to refined Fob3b1 and Fob3b2 intervals. A high-resolution map along with prioritization of Fob3b1 candidates by bioinformatics represents an important step forward to final identification of the Chr 15 obesity QTL.

High-throughput behavioral phenotyping in the expanded panel of BXD recombinant inbred strains

Genetic reference populations, particularly the BXD recombinant inbred (BXD RI) strains derived from C57BL/6J and DBA/2J mice, are a valuable resource for the discovery of the bio-molecular substrates and genetic drivers responsible for trait variation and covariation. This approach can be profitably applied in the analysis of susceptibility and mechanisms of drug and alcohol use disorders for which many predisposing behaviors may predict the occurrence and manifestation of increased preference for these substances. Many of these traits are modeled by common mouse behavioral assays, facilitating the detection of patterns and sources of genetic coregulation of predisposing phenotypes and substance consumption. Members of the Tennessee Mouse Genome Consortium (TMGC) have obtained phenotype data from over 250 measures related to multiple behavioral assays across several batteries: response to, and withdrawal from cocaine, 3,4-methylenedioxymethamphetamine; "ecstasy" (MDMA), morphine and alcohol; novelty seeking; behavioral despair and related neurological phenomena; pain sensitivity; stress sensitivity; anxiety; hyperactivity and sleep/wake cycles. All traits have been measured in both sexes in approximately 70 strains of the recently expanded panel of BXD RI strains. Sex differences and heritability estimates were obtained for each trait, and a comparison of early (N = 32) and recent (N = 37) BXD RI lines was performed. Primary data are publicly available for heritability, sex difference and genetic analyses using the MouseTrack database, and are also available in GeneNetwork.org for quantitative trait locus (QTL) detection and genetic analysis of gene expression. Together with the results of related studies, these data form a public resource for integrative systems genetic analysis of neurobehavioral traits.

Thermoregulation in mice exhibits genetic variability early in senescence

Aging leads to a loss of thermoregulation that can be readily monitored in laboratory mice. However, it is unclear from previous studies-we provide a tabular summary of 15 articles-whether significant loss occurs by midlife ( approximately 15 months of age). In this study, we examined 34 females from 22 LSXSS strains starting at 4 and 8 months of age (17 mice per age group). We used transponders inserted just under the loose skin of the pelt and calibrated against rectal body temperature to measure temperatures quickly without restraint. We found that the mean body temperatures measured 5 months later (9 and 13 months of age) had dropped significantly below normal in both groups: 0.6 masculineC lower in the younger cohort and 1.0 masculineC lower in the older cohort. These drops were not associated with weight loss or signs of pathology. Notably, the loss of thermoregulation between 8 and 13 months of age also exhibited genetic variation that was highly significant (P = 0.004). Such variation is potentially a powerful tool for determining the cause of thermoregulatory loss with age and whether this loss predicts senescence changes later in life, including the force of mortality.

Variable bone fragility associated with an Amish COL1A2 variant and a knock-in mouse model

Osteogenesis imperfecta (OI) is a heritable form of bone fragility typically associated with a dominant COL1A1 or COL1A2 mutation. Variable phenotype for OI patients with identical collagen mutations is well established, but phenotype variability is described using the qualitative Sillence classification. Patterning a new OI mouse model on a specific collagen mutation therefore has been hindered by the absence of an appropriate kindred with extensive quantitative phenotype data. We benefited from the large sibships of the Old Order Amish (OOA) to define a wide range of OI phenotypes in 64 individuals with the identical COL1A2 mutation. Stratification of carrier spine (L1-4) areal bone mineral density (aBMD) Z-scores demonstrated that 73% had moderate to severe disease (less than -2), 23% had mild disease (-1 to -2), and 4% were in the unaffected range (greater than -1). A line of knock-in mice was patterned on the OOA mutation. Bone phenotype was evaluated in four F(1) lines of knock-in mice that each shared approximately 50% of their genetic background. Consistent with the human pedigree, these mice had reduced body mass, aBMD, and bone strength. Whole-bone fracture susceptibility was influenced by individual genomic factors that were reflected in size, shape, and possibly bone metabolic regulation. The results indicate that the G610C OI (Amish) knock-in mouse is a novel translational model to identify modifying genes that influence phenotype and for testing potential therapies for OI.

An experimental assessment of in silico haplotype association mapping in laboratory mice

Background

To assess the utility of haplotype association mapping (HAM) as a quantitative trait locus (QTL) discovery tool, we conducted HAM analyses for red blood cell count (RBC) and high density lipoprotein cholesterol (HDL) in mice. We then experimentally tested each HAM QTL using published crosses or new F2 intercrosses guided by the haplotype at the HAM peaks.

Results

The HAM for RBC, using 33 classic inbred lines, revealed 8 QTLs; 2 of these were true positives as shown by published crosses. A HAM-guided (C57BL/6J × CBA/J)F2 intercross we carried out verified 2 more as true positives and 4 as false positives. The HAM for HDL, using 81 strains including recombinant inbred lines and chromosome substitution strains, detected 46 QTLs. Of these, 36 were true positives as shown by published crosses. A HAM-guided (C57BL/6J × A/J)F2 intercross that we carried out verified 2 more as true positives and 8 as false positives. By testing each HAM QTL for RBC and HDL, we demonstrated that 78% of the 54 HAM peaks were true positives and 22% were false positives. Interestingly, all false positives were in significant allelic association with one or more real QTL.

Conclusion

Because type I errors (false positives) can be detected experimentally, we conclude that HAM is useful for QTL detection and narrowing. We advocate the powerful and economical combined approach demonstrated here: the use of HAM for QTL discovery, followed by mitigation of the false positive problem by testing the HAM-predicted QTLs with small HAM-guided experimental crosses.

A verification of previously identified QTLs for cocaine-induced activation using a panel of B6.A chromosome substitution strains (CSS) and A/J x C57Bl/6J F2 mice

BACKGROUND

The objective of this study was to confirm provisional quantitative trait loci (QTL) for cocaine-induced locomotor activation, on chromosomes 1, 5, 6, 9, 12, 15, 16, 17, and 18, previously identified in the AXB/BXA recombinant inbred (RI) and AcB/BcA recombinant congenic (RC) strains of mice derived from A/J (A) and C57BL/6J (B6) progenitors. This was accomplished through a genetic analysis of cocaine-induced activity in an AxB6 F2 cross and a phenotypic survey across a panel of B6.A chromosome substitution strains (CSS) mice. Mice were tested for cocaine-induced activity, following administration of saline and cocaine (20 mg/kg), utilizing an open-field procedure.

RESULTS

Among AxB6 F2 mice, differences in cocaine-induced activity were associated with loci on chromosome 1 (D1Mit305), 5 (D5Mit409), 16 (D16Mit131), and 18 (D18Mit189). A survey of the CSS panel confirmed cocaine QTLs on chromosomes 5 and 15, previously identified in RI or RC strains. Overall, the regions on chromosomes 5 and 18 represent verification of QTL previously identified in both the RC and RI strains. Additionally, the B6 allele for these QTL was consistently associated with greater relative cocaine activation.

CONCLUSIONS

Collectively, chromosome 5 and 18 QTL have now been replicated in multiple independent crosses derived from the A/J and C57BL/6J progenitors. The use of an in silico analysis highlighted potential candidate genes on chromosomes 5 and 18. The present results complement the targeted gene approach currently prevalent in the study of cocaine and provide a broader empirically based focus for subsequent candidate gene studies.

Genetic region characterization (Gene RECQuest) - software to assist in identification and selection of candidate genes from genomic regions

BACKGROUND

The availability of research platforms like the web tools of the National Center for Biotechnology Information (NCBI) has transformed the time-consuming task of identifying candidate genes from genetic studies to an interactive process where data from a variety of sources are obtained to select likely genes for follow-up. This process presents its own set of challenges, as the genetic researcher has to interact with several tools in a time-intensive, manual, and cumbersome manner. We developed a method and implemented an effective software system to address these challenges by multidisciplinary efforts of professional software developers with domain experts. The method presented in this paper, Gene RECQuest, simplifies the interaction with existing research platforms through the use of advanced integration technologies.

FINDINGS

Gene RECQuest is a web-based application that assists in the identification of candidate genes from linkage and association studies using information from Online Mendelian Inheritance in Man (OMIM) and PubMed. To illustrate the utility of Gene RECQuest we used it to identify genes physically located within a linkage region as potential candidate genes for a quantitative trait locus (QTL) for very low density lipoprotein (VLDL) response on chromosome 18.

CONCLUSION

Gene RECQuest provides a tool which enables researchers to easily identify and organize literature supporting their own expertise and make informed decisions. It is important to note that Gene RECQuest is a data acquisition and organization software, and not a data analysis method.

Effects of atherogenic diet on hepatic gene expression across mouse strains

Diets high in fat and cholesterol are associated with increased obesity and metabolic disease in mice and humans. To study the molecular basis of the metabolic response to dietary fat, 10 inbred strains of mice were fed atherogenic high-fat and control low-fat diets. Liver gene expression and whole animal phenotypes were measured and analyzed in both sexes. The effects of diet, strain, and sex on gene expression were determined irrespective of complex processes, such as feedback mechanisms, that could have mediated the genomic responses. Global gene expression analyses demonstrated that animals of the same strain and sex have similar transcriptional profiles on a low-fat diet, but strains may show considerable variability in response to high-fat diet. Functional profiling indicated that high-fat feeding induced genes in the immune response, indicating liver damage, and repressed cholesterol biosynthesis. The physiological significance of the transcriptional changes was confirmed by a correlation analysis of transcript levels with whole animal phenotypes. The results found here were used to confirm a previously identified quantitative trait locus on chromosome 17 identified in males fed a high-fat diet in two crosses, PERA x DBA/2 and PERA x I/Ln. The gene expression data and phenotype data have been made publicly available as an online tool for exploring the effects of atherogenic diet in inbred mouse strains (http://cgd-array.jax.org/DietStrainSurvey).

Genetic analysis of blood pressure in 8 mouse intercross populations

The genetic basis of hypertension is well established, yet very few genes that cause common forms of hypertension are known. Quantitative trait locus (QTL) analyses in rodent models can guide the search for human hypertension genes, but the excellent genetic resources for mice have been underused in this regard. To address this issue, we surveyed blood pressure variation in mice from 37 inbred strains and generated 2577 mice in 8 intercross populations to perform QTL analyses of blood pressure. We identified 14 blood pressure QTL in these populations, including > or =7 regions of the mouse genome not linked previously to blood pressure. Many QTL were detected in multiple crosses, either within our study or in studies published previously, which facilitates the use of bioinformatics methods to narrow the QTL and focus the search for candidate genes. The regions of the human genome that correspond to all but 1 of the 14 blood pressure QTL in mice are linked to blood pressure in humans, suggesting that these regions contain causal genes with a conserved role in blood pressure control. These results greatly expand our knowledge of the genomic regions underlying blood pressure regulation in mice and support future studies to identify the causal genes within these QTL intervals.

Replication and narrowing of gene expression quantitative trait loci using inbred mice

Gene expression quantitative trait locus (eQTL) mapping has become a powerful tool in systems biology. While many authors have made important discoveries using this approach, one persistent challenge in eQTL studies is the selection of loci and genes that should receive further biological investigation. In this study we compared eQTL generated from gene expression profiling in the livers of two panels of mouse strains: 41 BXD recombinant inbred and 36 Mouse Diversity Panel (MDP) strains. Cis-eQTL, loci in which the transcript and its maximum QTL are colocated, have been shown to be more reproducible than trans-eQTL, which are not colocated with the transcript. We observed that between 9.9 and 12.1% of cis-eQTL and between 2.0 and 12.6% of trans-eQTL replicated between the two panels depending on the degree of statistical stringency. Notably, a significant eQTL hotspot on distal chromosome 12 observed in the BXD panel was reproduced in the MDP. Furthermore, the shorter linkage disequilibrium in the MDP strains allowed us to considerably narrow the locus and limit the number of candidate genes to a cluster of Serpin genes, which code for extracellular proteases. We conclude that this strategy has some utility in increasing confidence and resolution in eQTL mapping studies; however, due to the high false-positive rate in the MDP, eQTL mapping in inbred strains is best carried out in combination with an eQTL linkage study.

Gene expression profiling as a tool for positional cloning of genes-shortcut or the longest way round

The identification of quantitative trait loci, QTL, in arthritis animal models is a straight forward process. However, to identify the underlying genes is a great challenge. One strategy frequently used, is to combine QTL analysis with genomic/proteomic screens. This has resulted in a number of publications where carefully performed genomic analyses present likely candidate genes for their respective QTL s. However, seldom the findings are reconnected to the QTL controlled phenotypes. In this review, we use our own data as an illustrative example that "very likely candidate genes" identified by genomic/proteomics is not necessarily the same as true QTL underlying genes.

Four additional mouse crosses improve the lipid QTL landscape and identify Lipg as a QTL gene

To identify genes controlling plasma HDL and triglyceride levels, quantitative trait locus (QTL) analysis was performed in one backcross, (NZO/H1Lt x NON/LtJ) x NON/LtJ, and three intercrosses, C57BL/6J x DBA/2J, C57BL/6J x C3H/HeJ, and NZB/B1NJ x NZW/LacJ. HDL concentrations were affected by 25 QTL distributed on most chromosomes (Chrs); those on Chrs 1, 8, 12, and 16 were newly identified, and the remainder were replications of previously identified QTL. Triglyceride concentrations were controlled by nine loci; those on Chrs 1, 2, 3, 7, 16, and 18 were newly identified QTL, and the remainder were replications. Combining mouse crosses with haplotype analysis for the HDL QTL on Chr 18 reduced the list of candidates to six genes. Further expression analysis, sequencing, and quantitative complementation testing of these six genes identified Lipg as the HDL QTL gene on distal Chr 18. The data from these crosses further increase the ability to perform haplotype analyses that can lead to the identification of causal lipid genes.

A major QTL for acute ethanol sensitivity in the alcohol tolerant and non-tolerant selected rat lines

The Alcohol Tolerant and Alcohol Non-Tolerant rats (AT, ANT) were selectively bred for ethanol-induced ataxia as measured on the inclined plane. Here we report on a quantitative trait locus (QTL) study in an F(2) intercross population derived from inbred AT and ANT (IAT, IANT) and a follow-up study of congenics that were bred to examine one of the mapped QTLs. Over 1200 F(2) offspring were tested for inclined plane sensitivity, acute tolerance on the inclined plane, duration of the loss of righting reflex (LORR) and blood ethanol at regain of the righting reflex (BECRR). F(2) rats that were in the upper and lower 20% for inclined plane sensitivity were genotyped with 78 SSLP markers. Significant QTLs for inclined plane sensitivity were mapped on chromosomes 8 and 20; suggestive QTLs were mapped on chromosomes 1, 2 and 3. Highly significant QTLs for LORR duration (LOD = 12.4) and BECRR (LOD = 5.7) were mapped to the same locus on chromosome 1. Breeding and testing of reciprocal congenic lines confirmed the chromosome 1 LORR/BECRR QTL. A series of recombinant congenic sub-lines were bred to fine-map this QTL. Current results have narrowed the QTL to an interval of between 5 and 20 Mb. We expect to be able to narrow the interval to less than 5 Mb with additional genotyping and continued breeding of recombinant sub-congenic lines.

The future of mouse QTL mapping to diagnose disease in mice in the age of whole-genome association studies

Genome-wide association analysis is emerging as a powerful tool to define novel genes and molecular pathways involved in susceptibility to human complex disorders. However, in spite of recent successes, this approach is not without its limitations, the most notable of which is inconsistent phenotype penetrance due to varied environmental exposures. Mouse models do, however, circumvent some of these drawbacks by allowing for a much higher degree of control over genetic variation and environmental exposure, and although their application to human complex genetics is not always straightforward, they do serve as a powerful means of complementing observations in human populations. Mouse quantitative trait locus mapping has proven a successful, yet technically demanding method for defining trait susceptibility. In this review, we focus upon recent advances that are both reducing the technical burden traditionally associated with quantitative trait locus mapping, and enhancing the applicability of these approaches to human disease.