In silico mapping of complex disease-related traits in mice

What Have We Learned (or Expect to) From Analysis of Murine Genetic Models Related to Substance Use Disorders?

The tremendous public health problem created by substance use disorders (SUDs) presents a major opportunity for mouse genetics. Inbred mouse strains exhibit substantial and heritable differences in their responses to drugs of abuse (DOA) and in many of the behaviors associated with susceptibility to SUD. Therefore, genetic discoveries emerging from analysis of murine genetic models can provide critically needed insight into the neurobiological effects of DOA, and they can reveal how genetic factors affect susceptibility drug addiction. There are already indications, emerging from our prior analyses of murine genetic models of responses related to SUDs that mouse genetic models of SUD can provide actionable information, which can lead to new approaches for alleviating SUDs. Lastly, we consider the features of murine genetic models that enable causative genetic factors to be successfully identified; and the methodologies that facilitate genetic discovery.

The Effect of Population Structure on Murine Genome-Wide Association Studies

The ability to use genome-wide association studies (GWAS) for genetic discovery depends upon our ability to distinguish true causative from false positive association signals. Population structure (PS) has been shown to cause false positive signals in GWAS. PS correction is routinely used for analysis of human GWAS results, and it has been assumed that it also should be utilized for murine GWAS using inbred strains. Nevertheless, there are fundamental differences between murine and human GWAS, and the impact of PS on murine GWAS results has not been carefully investigated. To assess the impact of PS on murine GWAS, we examined 8223 datasets that characterized biomedical responses in panels of inbred mouse strains. Rather than treat PS as a confounding variable, we examined it as a response variable. Surprisingly, we found that PS had a minimal impact on datasets measuring responses in ≤20 strains; and had surprisingly little impact on most datasets characterizing 21 - 40 inbred strains. Moreover, we show that true positive association signals arising from haplotype blocks, SNPs or indels, which were experimentally demonstrated to be causative for trait differences, would be rejected if PS correction were applied to them. Our results indicate because of the special conditions created by GWAS (the use of inbred strains, small sample sizes) PS assessment results should be carefully evaluated in conjunction with other criteria, when murine GWAS results are evaluated.

In silico candidate variant and gene identification using inbred mouse strains

Mice are the most widely used animal model to study genotype to phenotype relationships. Inbred mice are genetically identical, which eliminates genetic heterogeneity and makes them particularly useful for genetic studies. Many different strains have been bred over decades and a vast amount of phenotypic data has been generated. In addition, recently whole genome sequencing-based genome-wide genotype data for many widely used inbred strains has been released. Here, we present an approach for in silico fine-mapping that uses genotypic data of 37 inbred mouse strains together with phenotypic data provided by the user to propose candidate variants and genes for the phenotype under study. Public genome-wide genotype data covering more than 74 million variant sites is queried efficiently in real-time to provide those variants that are compatible with the observed phenotype differences between strains. Variants can be filtered by molecular consequences and by corresponding molecular impact. Candidate gene lists can be generated from variant lists on the fly. Fine-mapping together with annotation or filtering of results is provided in a Bioconductor package called MouseFM. In order to characterize candidate variant lists under various settings, MouseFM was applied to two expression data sets across 20 inbred mouse strains, one from neutrophils and one from CD4⁺ T cells. Fine-mapping was assessed for about 10,000 genes, respectively, and identified candidate variants and haplotypes for many expression quantitative trait loci (eQTLs) reported previously based on these data. For albinism, MouseFM reports only one variant allele of moderate or high molecular impact that only albino mice share: a missense variant in the Tyr gene, reported previously to be causal for this phenotype. Performing in silico fine-mapping for interfrontal bone formation in mice using four strains with and five strains without interfrontal bone results in 12 genes. Of these, three are related to skull shaping abnormality. Finally performing fine-mapping for dystrophic cardiac calcification by comparing 9 strains showing the phenotype with eight strains lacking it, we identify only one moderate impact variant in the known causal gene Abcc6. In summary, this illustrates the benefit of using MouseFM for candidate variant and gene identification.

Substrains matter in phenotyping of C57BL/6 mice

The inbred mouse strain C57BL/6 has been widely used as a background strain for spontaneous and induced mutations. Developed in the 1930s, the C57BL/6 strain diverged into two major groups in the 1950s, namely, C57BL/6J and C57BL/6N, and more than 20 substrains have been established from them worldwide. We previously reported genetic differences among C57BL/6 substrains in 2009 and 2015. Since then, dozens of reports have been published on phenotypic differences in behavioral, neurological, cardiovascular, and metabolic traits. Substrains need to be chosen according to the purpose of the study because phenotypic differences might affect the experimental results. In this paper, we review recent reports of phenotypic and genetic differences among C57BL/6 substrains, focus our attention on the proper use of C57BL/6 and other inbred strains in the era of genome editing, and provide the life science research community wider knowledge about this subject.

Strain-dependent effects on lung structure, matrix remodeling, and Stat3/Smad2 signaling in C57BL/6N and C57BL/6J mice after neonatal hyperoxia

Bronchopulmonary dysplasia (BPD) is a chronic lung disease of preterm infants, characterized by lung growth arrest and matrix remodeling. Various animal models provide mechanistic insights in the pathogenesis of BPD. Since there is increasing evidence that genetic susceptibility modifies the response to lung injury, we investigated strain-dependent effects in hyperoxia (HYX)-induced lung injury of newborn mice. To this end, we exposed newborn C57BL/6N and C57BL/6J mice to 85% O₂ (HYX) or normoxia (NOX; 21% O₂) for 28 days, followed by lung excision for histological and molecular measurements. BL/6J-NOX mice exhibited a lower body and lung weight than BL/6N-NOX mice; hyperoxia reduced body weight in both strains and increased lung weight only in BL/6J-HYX mice. Quantitative histomorphometric analyses revealed reduced alveolar formation in lungs of both strains after HYX, but the effect was greater in BL/6J-HYX mice than BL/6N-HYX mice. Septal thickness was lower in BL/6J-NOX mice than BL/6N-NOX mice but increased in both strains after HYX. Elastic fiber density was significantly greater in BL/6J-HYX mice than BL/6N-HYX mice. Lungs of BL/6J-HYX mice were protected from changes in gene expression of fibrillin-1, fibrillin-2, fibulin-4, fibulin-5, and surfactant proteins seen in BL/6N-HYX mice. Finally, Stat3 was activated by HYX in both strains; in contrast, activation of Smad2 was markedly greater in lungs of BL/6N mice than BL/6J mice after HYX. In summary, we demonstrate strain-dependent differences in lung structure and matrix, alveolar epithelial cell markers, and Smad2 (transforming growth factor β) signaling in neonatal HYX-induced lung injury. Strain-dependent effects and genetic susceptibility need be taken into consideration for reproducibility and reliability of results in animal models.

Mouse genome-wide association and systems genetics identifies Lhfp as a regulator of bone mass

Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P = 3.1 x 10⁻¹²) BMD locus on Chromosome 3@52.5 Mbp that replicated in two separate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts. Furthermore, its expression was regulated by a local expression QTL (eQTL), which overlapped the BMD association. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp^-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp^-/- mice displayed increased osteogenic differentiation. Lhfp^-/- mice also had elevated BMD due to increased cortical bone mass. Lastly, we identified SNPs in human LHFP that were associated (P = 1.2 x 10⁻⁵) with heel BMD. In conclusion, we used GWAS and systems genetics to identify Lhfp as a regulator of osteoblast activity and bone mass.

Osteoporosis is a common, chronic disease characterized by low bone mineral density (BMD) that puts millions of Americans at high risk of fracture. Variation in BMD in the general population is, in large part, determined by genetic factors. To identify novel genes influencing BMD, we performed a genome-wide association study in a panel of inbred mouse strains. We identified a locus on Chromosome 3 strongly associated with BMD. Using a combination of systems genetics approaches, we connected the expression of the Lhfp gene with BMD-associated genetic variants and predicted it influenced BMD by altering the activity of bone-forming osteoblasts. Using mice deficient in Lhfp, we demonstrated that Lhfp negatively regulates bone formation and BMD. These data suggest that inhibiting Lhfp may represent a novel therapeutic strategy to increase BMD and decrease the risk of fracture.

A personalized, multiomics approach identifies genes involved in cardiac hypertrophy and heart failure

A traditional approach to investigate the genetic basis of complex diseases is to identify genes with a global change in expression between diseased and healthy individuals. However, population heterogeneity may undermine the effort to uncover genes with significant but individual contribution to the spectrum of disease phenotypes within a population. Here we investigate individual changes of gene expression when inducing hypertrophy and heart failure in 100 + strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). We find that genes whose expression fold-change correlates in a statistically significant way with the severity of the disease are either up or down-regulated across strains, and therefore missed by a traditional population-wide analysis of differential gene expression. Furthermore, those "fold-change" genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome. We validate our approach by showing that the knockdown of Hes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80-90% in neonatal rat ventricular myocytes. Our results demonstrate that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies.

Integration of genome-wide association and extant brain expression QTL identifies candidate genes influencing prepulse inhibition in inbred F1 mice

Genetic association mapping in structured populations of model organisms can offer a fruitful complement to human genetic studies by generating new biological hypotheses about complex traits. Here we investigated prepulse inhibition (PPI), a measure of sensorimotor gating that is disrupted in a number of psychiatric disorders. To identify genes that influence PPI, we constructed a panel of half-sibs by crossing 30 females from common inbred mouse strains with inbred C57BL/6J males to create male and female F1 offspring. We used publicly available single nucleotide polymorphism (SNP) genotype data from these inbred strains to perform a genome-wide association scan using a dense panel of over 150,000 SNPs in a combined sample of 604 mice representing 30 distinct F1 genotypes. We identified two independent PPI-associated loci on Chromosomes 2 and 7, each of which explained 12-14% of the variance in PPI. Searches of available databases did not identify any plausible causative coding polymorphisms within these loci. However, previously collected expression quantitative trait locus (eQTL) data from hippocampus and striatum indicated that the SNPs on Chromosomes 2 and 7 that showed the strongest association with PPI were also strongly associated with expression of several transcripts, some of which have been implicated in human psychiatric disorders. This integrative approach successfully identified a focused set of genes which can be prioritized for follow-up studies. More broadly, our results show that F1 crosses among common inbred strains can be used in combination with other informatics and expression datasets to identify candidate genes for complex behavioral traits.

Differential peptidomics assessment of strain and age differences in mice in response to acute cocaine administration

Neurochemical differences in the hypothalamic-pituitary axis between individuals and between ages may contribute to differential susceptibility to cocaine abuse. This study measured peptide levels in the pituitary gland (Pit) and lateral hypothalamus (LH) in adolescent (age 30 days) and adult (age 65 days) mice from four standard inbred strains, FVB/NJ, DBA/2J, C57BL/6J, and BALB/cByJ, which have previously been characterized for acute locomotor responses to cocaine. Individual peptide profiles were analyzed using mass spectrometric profiling and principal component analysis. Sequences of assigned peptides were verified by tandem mass spectrometry. Principal component analysis classified all strains according to their distinct peptide profiles in Pit samples from adolescent mice, but not adults. Select pro-opiomelanocortin-derived peptides were significantly higher in adolescent BALB/cByJ and DBA/2J mice than in FVB/NJ or C57BL/6J mice. A subset of peptides in the LH, but not in the Pit, was altered by cocaine in adolescents. A 15 mg/kg dose of cocaine induced greater peptide alterations than a 30 mg/kg dose, particularly in FVB/NJ animals, with larger differences in adolescents than adults. Neuropeptides in the LH affected by acute cocaine administration included pro-opiomelanocortin-, myelin basic protein-, and glutamate transporter-derived peptides. The observed peptide differences could contribute to differential behavioral sensitivity to cocaine among strains and ages. Peptides were measured using mass spectrometry (MALDI-TOF) in individual lateral hypothalamus and pituitary samples from four strains and two ages of inbred mice in response to acute cocaine administration. Principal component analyses (PCA) classified the strains according to their peptide profiles from adolescent mice, and a subset of peptides in the lateral hypothalamus was altered by cocaine in adolescents.

Genetic diversity and association mapping of iron and zinc concentrations in chickpea (Cicer arietinum L.)

Chickpea (Cicer arietinum L.) is the world's second most important pulse crop after common bean. Chickpea has historically been an important daily staple in the diet of millions of people, especially in the developing countries. Current chickpea breeding programs have mainly been directed toward high yield, biotic and abiotic stress resilience that has increased global production, but less attention has been directed toward improving micronutrient concentrations in seeds. In an effort to develop micronutrient-dense chickpea lines, a study to examine the variability and to identify SNP alleles associated with seed iron and zinc concentrations was conducted using 94 diverse accessions of chickpea. The results indicated that there is substantial variability present in chickpea germplasm for seed iron and zinc concentrations. In the current set of germplasm, zinc is negatively correlated with grain yield across all locations and years; whereas the negative correlation between iron and grain yield was only significant at the Elrose locality. Eight SNP loci associated with iron and (or) zinc concentrations in chickpea seeds were identified. One SNP located on chromosome 1 (chr1) is associated with both iron and zinc concentrations. On chr4, three SNPs associated with zinc concentration and two SNPs for iron concentration were identified. Two additional SNP loci, one on chr6 and the other on chr7, were also found to be associated with iron and zinc concentrations, respectively. The results show potential opportunity for molecular breeding for improvement of seed iron and zinc concentrations in chickpea.

Heritability of periodontal bone loss in mice

BACKGROUND

Periodontitis is an inflammatory disease of the periodontal tissues that compromises tooth support and can lead to tooth loss. Although bacterial biofilm is central in disease pathogenesis, the host response plays an important role in the progression and severity of periodontitis. Indeed, clinical genetic studies indicate that periodontitis is 50% heritable. In this study, we hypothesized that lipopolysaccharide (LPS) injections lead to a strain-dependent periodontal bone loss pattern.

MATERIAL AND METHODS

We utilized five inbred mouse strains that derive the recombinant strains of the hybrid mouse diversity panel. Mice received Porphyromonas gingivalis-LPS injections for 6 wk.

RESULTS AND CONCLUSION

Micro-computed tomography analysis demonstrated a statistically significant strain-dependent bone loss. The most susceptible strain, C57BL/6J, had a fivefold higher LPS-induced bone loss compared to the most resistant strain, A/J. More importantly, periodontal bone loss revealed 49% heritability, which closely mimics periodontitis heritability for patients. To evaluate further the functional differences that underlie periodontal bone loss, osteoclast numbers of C57BL/6J and A/J mice were measured in vivo and in vitro. In vitro analysis of osteoclastogenic potential showed a higher number of osteoclasts in C57BL/6J compared to A/J mice. In vivo LPS injections statistically significantly increased osteoclast numbers in both groups. Importantly, the number of osteoclasts was higher in C57BL/6J vs. A/J mice. These data support a significant role of the genetic framework in LPS-induced periodontal bone loss and the feasibility of utilizing the hybrid mouse diversity panel to determine the genetic factors that affect periodontal bone loss. Expanding these studies will contribute in predicting patients genetically predisposed to periodontitis and in identifying the biological basis of disease susceptibility.

In-silico QTL mapping of postpubertal mammary ductal development in the mouse uncovers potential human breast cancer risk loci

Genetic background plays a dominant role in mammary gland development and breast cancer (BrCa). Despite this, the role of genetics is only partially understood. This study used strain-dependent variation in an inbred mouse mapping panel, to identify quantitative trait loci (QTL) underlying structural variation in mammary ductal development, and determined if these QTL correlated with genomic intervals conferring BrCa susceptibility in humans. For about half of the traits, developmental variation among the complete set of strains in this study was greater (P < 0.05) than that of previously studied strains, or strains in current common use for mammary gland biology. Correlations were also detected with previously reported variation in mammary tumor latency and metastasis. In-silico genome-wide association identified 20 mammary development QTL (Mdq). Of these, five were syntenic with previously reported human BrCa loci. The most significant (P = 1 × 10(-11)) association of the study was on MMU6 and contained the genes Plxna4, Plxna4os1, and Chchd3. On MMU5, a QTL was detected (P = 8 × 10(-7)) that was syntenic to a human BrCa locus on h12q24.5 containing the genes Tbx3 and Tbx5. Intersection of linked SNP (r(2) > 0.8) with genomic and epigenomic features, and intersection of candidate genes with gene expression and survival data from human BrCa highlighted several for further study. These results support the conclusion that mammary tumorigenesis and normal ductal development are influenced by common genetic factors and that further studies of genetically diverse mice can improve our understanding of BrCa in humans.

Development of SNP markers for C57BL/6N-derived mouse inbred strains

C57BL/6N inbred mice are used as the genetic background for producing knockout mice in large-scale projects worldwide; however, the genetic divergence among C57BL/6N-derived substrains has not been verified. Here, we identified novel single nucleotide polymorphisms (SNPs) specific to the C57BL/6NJ strain and selected useful SNPs for the genetic monitoring of C57BL/6N-derived substrains. Informative SNPs were selected from the public SNP database at the Wellcome Trust Sanger Institute by comparing sequence data from C57BL/6NJ and C57BL/6J mice. A total of 1,361 candidate SNPs from the SNP database could distinguish the C57BL/6NJ strain from 12 other inbred strains. We confirmed 277 C57BL/6NJ-specific SNPs including 10 nonsynonymous SNPs by direct sequencing, and selected 100 useful SNPs that cover all of the chromosomes except Y. Genotyping of 11 C57BL/6N-derived substrains at these 100 SNP loci demonstrated genetic differences among the substrains. This information will be useful for accurate genetic monitoring of mouse strains with a C57BL/6N-derived background.

Limitation of number of strains and persistence of false positive loci in QTL mapping using recombinant inbred strains

While the identification of causal genes of quantitative trait loci (QTL) remains a difficult problem in the post-genome era, the number of QTL continues to accumulate, mainly identified using the recombinant inbred (RI) strains. Over the last decade, hundreds of publications have reported nearly a thousand QTL identified from RI strains. We hypothesized that the inaccuracy of most of these QTL makes it difficult to identify causal genes. Using data from RI strains derived from C57BL/6J (B6) X DBA/2J (D2), we tested the possibility of detection of reliable QTL with different numbers of strains in the same trait in five different traits. Our results indicated that studies using RI strains of less than 30 in general have a higher probability of failing to detect reliable QTL. Errors in many studies could include false positive loci, switches between QTL with small and major effects, and missing the real major loci. The similar data was obtained from a RI strain population derived from a different pair of parents and a RI strain population of rat. Thus, thousands of reported QTL from studies of RI strains may need to be double-checked for accuracy before proceeding to causal gene identification.

An integrated genomics approach to identify genetic regions associated with neonatal growth trait in mice

Neonatal growth during the early post-partum period is closely associated with lactation performance. Neonatal growth reflects milk output and is a complex variable trait among inbred mouse strains, but few studies have compared this trait systematically across more than a few strains. In the present study, 11 inbred strains of mice were measured for a neonatal growth phenotype during the first eight days of lactation. Significant differences in neonatal growth trait were observed with QSi5 (3.71±0.05 g) and DBA/1J (2.67±0.06 g) strains defining the two extremes of the phenotype. In silico association analysis was performed for trait variability using the high density SNP information on inbred strains of mice. We found strong evidence to refine a previously identified large neonatal growth QTL on mouse chromosome 9, Neogq1. When an integrated strategy that combined fine mapping and analysis of mammary transcriptome expression profiles of lactating mice with divergent phenotypes was applied, we identified neogenin (Neo1), a gene important for mammary gland morphogenesis, as a likely quantitative trait gene (QTG) underlying the Neogq1 QTL in mice.

Host susceptibility to malaria in human and mice: compatible approaches to identify potential resistant genes

There is growing evidence for human genetic factors controlling the outcome of malaria infection, while molecular basis of this genetic control is still poorly understood. Case-control and family-based studies have been carried out to identify genes underlying host susceptibility to malarial infection. Parasitemia and mild malaria have been genetically linked to human chromosomes 5q31-q33 and 6p21.3, and several immune genes located within those regions have been associated with malaria-related phenotypes. Association and linkage studies of resistance to malaria are not easy to carry out in human populations, because of the difficulty in surveying a significant number of families. Murine models have proven to be an excellent genetic tool for studying host response to malaria; their use allowed mapping 14 resistance loci, eight of them controlling parasitic levels and six controlling cerebral malaria. Once quantitative trait loci or genes have been identified, the human ortholog may then be identified. Comparative mapping studies showed that a couple of human and mouse might share similar genetically controlled mechanisms of resistance. In this way, char8, which controls parasitemia, was mapped on chromosome 11; char8 corresponds to human chromosome 5q31-q33 and contains immune genes, such as Il3, Il4, Il5, Il12b, Il13, Irf1, and Csf2. Nevertheless, part of the genetic factors controlling malaria traits might differ in both hosts because of specific host-pathogen interactions. Finally, novel genetic tools including animal models were recently developed and will offer new opportunities for identifying genetic factors underlying host phenotypic response to malaria, which will help in better therapeutic strategies including vaccine and drug development.

Marker panels for genealogy-based mapping, breed demographics, and inference-of-ancestry in the dog

Short tandem repeat polymorphisms (STRPs) are robust and informative markers for a range of genetic applications. STRPs are advantageous in experimental designs that derive power from sampling many individuals rather than many loci (e.g., pedigree-based studies, fine-scale mapping, and conservation genetics). STRPs have proven useful for vetting samples prior to costly high-density SNP analysis. Here we present validated STRPs (n = 1,012) spanning the canine genome (2.1 +/-1.4 Mb; 2.1 +/-2.1 cM). Standardized design, pre-multiplexing, M13-based dye-labeling, and selection for loci amenable to semi-automated allele-scoring minimize cost and facilitate efficient genotyping. The markers are leveraged from the canine linkage map, and thus are backed by genetic data useful for parametric multipoint analysis and assessment of empiric coverage. We demonstrate several applications with different marker subsets. The complete set provides a genome scan for linkage at ∼5 cM resolution. A subset of the markers measures molecular diversity between domestic and wild canid populations. Another subset reflects ancestry within breeds, uncovering hidden stratification and flagging genetic outliers prior to SNP genotyping. Thus, the markers described here add flexibility and cost effectiveness to several genetic applications in the dog that complement genome-wide SNP genotyping studies. Supplemental material is available for this article. Go to the publisher's online edition of Animal Biotechnology.

Genome-wide association studies in mice

Genome-wide association studies (GWASs) have transformed the field of human genetics and have led to the discovery of hundreds of genes that are implicated in human disease. The technological advances that drove this revolution are now poised to transform genetic studies in model organisms, including mice. However, the design of GWASs in mouse strains is fundamentally different from the design of human GWASs, creating new challenges and opportunities. This Review gives an overview of the novel study designs for mouse GWASs, which dramatically improve both the statistical power and resolution compared to classical gene-mapping approaches.

Identification of exercise capacity QTL using association mapping in inbred mice

There are large interindividual differences in exercise capacity. It is well established that there is a genetic basis for these differences. However, the genetic factors underlying this variation are undefined. Therefore, the purpose of this study was to identify novel putative quantitative trait loci (QTL) for exercise capacity by measuring exercise capacity in inbred mice and performing genome-wide association mapping. Exercise capacity, defined as run time and work, was assessed in male mice (n = 6) from 34 strains of classical and wild-derived inbred mice performing a graded treadmill test. Genome-wide association mapping was performed with an efficient mixed-model association (EMMA) algorithm to identify QTL. Exercise capacity was significantly different across strains. Run time varied by 2.7-fold between the highest running strain (C58/J) and the lowest running strain (A/J). These same strains showed a 16.5-fold difference in work. Significant associations were identified for exercise time on chromosomes 1, 2, 7, 11, and 13. The QTL interval on chromosome 2 (~168 Mb) contains one gene, Nfatc2, and overlaps with a suggestive QTL for training responsiveness in humans. These results provide phenotype data on the widest range of inbred strains tested thus far and indicate that genetic background significantly influences exercise capacity. Furthermore, the novel QTLs identified in the current study provide new targets for investigating the underlying mechanisms for variation in exercise capacity.

Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits

We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5% of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches.

In silico QTL mapping of maternal nurturing ability with the mouse diversity panel

Significant variation exists for maternal nurturing ability in inbred mice. Although classical mapping approaches have identified quantitative trait loci (QTL) that may account for this variation, the underlying genes are unknown. In this study, lactation performance data among the mouse diversity panel were used to map genomic regions associated with this variation. Females from each of 32 inbred strains (n = 8-19 dams/strain) were studied during the first 8 days of lactation by allowing them to raise weight- and size-normalized cross-foster litters (10 pups/litter). Average daily weight gain (ADG) of litters served as the primary indicator of milk production. The number of pups successfully reared to 8 days (PNUM8) also served as a related indicator of maternal performance. Initial haplotype association analysis using a Bonferroni-corrected, genome-wide threshold revealed 10 and 15 associations encompassing 11 and 13 genes for ADG and PNUM8, respectively. The most significant of these associated haplotype blocks were found on MMU 8, 11, and 19 and contained the genes Nr3c2, Egfr, Sec61g, and Gnaq. Lastly, two haplotype blocks on MMU9 were detected in association with PNUM8. These overlapped with the previously described maternal performance QTL, Neogq1. These results suggest that the application of in silico QTL mapping is a useful tool in discovering the presence of novel candidate genes involved in determining lactation capacity in mice.

Haplotype Association Mapping Identifies a Candidate Gene Region in Mice Infected With Staphylococcus aureus

Exposure to Staphylococcus aureus has a variety of outcomes, from asymptomatic colonization to fatal infection. Strong evidence suggests that host genetics play an important role in susceptibility, but the specific host genetic factors involved are not known. The availability of genome-wide single nucleotide polymorphism (SNP) data for inbred Mus musculus strains means that haplotype association mapping can be used to identify candidate susceptibility genes. We applied haplotype association mapping to Perlegen SNP data and kidney bacterial counts from Staphylococcus aureus-infected mice from 13 inbred strains and detected an associated block on chromosome 7. Strong experimental evidence supports the result: a separate study demonstrated the presence of a susceptibility locus on chromosome 7 using consomic mice. The associated block contains no genes, but lies within the gene cluster of the 26-member extended kallikrein gene family, whose members have well-recognized roles in the generation of antimicrobial peptides and the regulation of inflammation. Efficient mixed-model association (EMMA) testing of all SNPs with two alleles and located within the gene cluster boundaries finds two significant associations: one of the three polymorphisms defining the associated block and one in the gene closest to the block, Klk1b11. In addition, we find that 7 of the 26 kallikrein genes are differentially expressed between susceptible and resistant mice, including the Klk1b11 gene. These genes represent a promising set of candidate genes influencing susceptibility to Staphylococcus aureus.

Genetically determined P2X7 receptor pore formation regulates variability in chronic pain sensitivity

Chronic pain is highly variable between individuals, as is the response to analgesics. Although much of the variability in chronic pain and analgesic response is heritable, an understanding of the genetic determinants underlying this variability is rudimentary. Here we show that variation within the coding sequence of the gene encoding the P2X7 receptor (P2X7R) affects chronic pain sensitivity in both mice and humans. P2X7Rs, which are members of the family of ionotropic ATP-gated receptors, have two distinct modes of function: they can function through their intrinsic cationic channel or by forming nonselective pores that are permeable to molecules with a mass of up to 900 Da. Using genome-wide linkage analyses, we discovered an association between nerve-injury-induced pain behavior (mechanical allodynia) and the P451L mutation of the mouse P2rx7 gene, such that mice in which P2X7Rs have impaired pore formation as a result of this mutation showed less allodynia than mice with the pore-forming P2rx7 allele. Administration of a peptide corresponding to the P2X7R C-terminal domain, which blocked pore formation but not cation channel activity, selectively reduced nerve injury and inflammatory allodynia only in mice with the pore-forming P2rx7 allele. Moreover, in two independent human chronic pain cohorts, a cohort with pain after mastectomy and a cohort with osteoarthritis, we observed a genetic association between lower pain intensity and the hypofunctional His270 (rs7958311) allele of P2RX7. Our findings suggest that selectively targeting P2X7R pore formation may be a new strategy for individualizing the treatment of chronic pain.

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.

The Zebrafish Neurophenome Database (ZND): a dynamic open-access resource for zebrafish neurophenotypic data

Zebrafish (Danio rerio) are widely used in neuroscience research, where their utility as a model organism is rapidly expanding. Low cost, ease of experimental manipulations, and sufficient behavioral complexity make zebrafish a valuable tool for high-throughput studies in biomedicine. To complement the available repositories for zebrafish genetic information, there is a growing need for the collection of zebrafish neurobehavioral and neurological phenotypes. For this, we are establishing the Zebrafish Neurophenome Database (ZND; www.tulane.edu/∼znpindex/search ) as a new dynamic online open-access data repository for behavioral and related physiological data. ZND, currently focusing on adult zebrafish, combines zebrafish neurophenotypic data with a simple, easily searchable user interface, which allow scientists to view and compare results obtained by other laboratories using various treatments in different testing paradigms. As a developing community effort, ZND is expected to foster innovative research using zebrafish by federating the growing body of zebrafish neurophenotypic data.

Quantitative trait Loci association mapping by imputation of strain origins in multifounder crosses

Although mapping quantitative traits in inbred strains is simpler than mapping the analogous traits in humans, classical inbred crosses suffer from reduced genetic diversity compared to experimental designs involving outbred animal populations. Multiple crosses, for example the Complex Trait Consortium's eight-way cross, circumvent these difficulties. However, complex mating schemes and systematic inbreeding raise substantial computational difficulties. Here we present a method for locally imputing the strain origins of each genotyped animal along its genome. Imputed origins then serve as mean effects in a multivariate Gaussian model for testing association between trait levels and local genomic variation. Imputation is a combinatorial process that assigns the maternal and paternal strain origin of each animal on the basis of observed genotypes and prior pedigree information. Without smoothing, imputation is likely to be ill-defined or jump erratically from one strain to another as an animal's genome is traversed. In practice, one expects to see long stretches where strain origins are invariant. Smoothing can be achieved by penalizing strain changes from one marker to the next. A dynamic programming algorithm then solves the strain imputation process in one quick pass through the genome of an animal. Imputation accuracy exceeds 99% in practical examples and leads to high-resolution mapping in simulated and real data. The previous fastest quantitative trait loci (QTL) mapping software for dense genome scans reduced compute times to hours. Our implementation further reduces compute times from hours to minutes with no loss in statistical power. Indeed, power is enhanced for full pedigree data.

Experimental models for anxiolytic drug discovery in the era of omes and omics

INTRODUCTION

Animal behavioral models have become an indispensable tool for studying anxiety disorders and testing anxiety-modulating drugs. However, significant methodological and conceptual challenges affect the translational validity and accurate behavioral dissection in such models. They are also often limited to individual behavioral domains and fail to target the disorder's real clinical picture (its spectrum or overlap with other disorders), which hinder screening and development of novel anxiolytic drugs.

AREAS COVERED

In this article, the authors discuss and emphasize the importance of high-throughput multi-domain neurophenotyping based on the latest developments in video-tracking and bioinformatics. Additionally, the authors also explain how bioinformatics can provide new insight into the neural substrates of brain disorders and its benefit for drug discovery.

EXPERT OPINION

The throughput and utility of animal models of anxiety and other brain disorders can be markedly increased by a number of ways: i) analyzing systems of several domains and their interplay in a wider spectrum of model species; ii) using a larger number of end points generated by video-tracking tools; iii) correlating behavioral data with genomic, proteomic and other physiologically relevant markers using online databases and iv) creating molecular network-based models of anxiety to identify new targets for drug design and discovery. Experimental models utilizing bioinformatics tools and online databases will not only improve our understanding of both gene-behavior interactions and complex trait interconnectivity but also highlight new targets for novel anxiolytic drugs.

Mutations in the glycoprotein of vesicular stomatitis virus affect cytopathogenicity: potential for oncolytic virotherapy

Vesicular stomatitis virus (VSV) has been widely used to characterize cellular processes, viral resistance, and cytopathogenicity. Recently, VSV has also been used for oncolytic virotherapy due to its capacity to selectively lyse tumor cells. Mutants of the matrix (M) protein of VSV have generally been preferred to the wild-type virus for oncolysis because of their ability to induce type I interferon (IFN) despite causing weaker cytopathic effects. However, due to the large variability of tumor types, it is quite clear that various approaches and combinations of multiple oncolytic viruses will be needed to effectively treat most cancers. With this in mind, our work focused on characterizing the cytopathogenic profiles of four replicative envelope glycoprotein (G) VSV mutants. In contrast to the prototypic M mutant, VSV G mutants are as efficient as wild-type virus at inhibiting cellular transcription and host protein translation. Despite being highly cytopathic, the mutant G(6R) triggers type I interferon secretion as efficiently as the M mutant. Importantly, most VSV G mutants are more effective at killing B16 and MC57 tumor cells in vitro than the M mutant or wild-type virus through apoptosis induction. Taken together, our results demonstrate that VSV G mutants retain the high cytopathogenicity of wild-type VSV, with G(6R) inducing type I IFN secretion at levels similar to that of the M mutant. VSV G protein mutants could therefore prove to be highly valuable for the development of novel oncolytic virotherapy strategies that are both safe and efficient for the treatment of various types of cancer.

Gene networks associated with conditional fear in mice identified using a systems genetics approach

Background

Our understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution.

Results

A total of 27 behavioral quantitative trait loci were mapped with a false discovery rate of 5%. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and also genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. In addition, we surveyed the architecture of brain transcript regulation and demonstrated preservation of gene co-expression modules in hippocampus and striatum, while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance were strongly associated with fear phenotypes.

Conclusion

Application of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior.

Positional cloning of a quantitative trait locus contributing to pain sensitivity: possible mediation by Tyrp1

To identify novel pain-relevant genes, a set of 35 recombinant congenic strains derived from the sensitive C57BL/6 and resistant A/J strains were tested for their sensitivity to noxious heat on the radiant heat paw-withdrawal test. Nine strains were found to display differential sensitivity, and the two most extreme responders were used to generate independent secondary crosses for quantitative trait locus (QTL) mapping. From these genetic analyses, a QTL, which we call Tpnr5, was mapped to a 14-Mb interval of mouse chromosome 4 containing 39 genes. In addition to the paw-withdrawal test phenotype, Tpnr5 may be relevant to mechanical and inflammatory nociception. A series of strategies - including in silico analyses, reverse transcriptase polymerase chain reaction (RT-PCR) in multiple tissues and exonic DNA sequencing - were used to generate a list of six prioritized candidate genes. One of these, tyrosinase-related protein 1 (Tyrp1), displayed enriched expression in the dorsal root ganglia, an inactivating (C110Y) mutation in the resistant A/J strain, and a null mutant found to be more resistant to thermal nociception compared to its wild-type counterpart. Although other genes cannot be definitively ruled out, existing data are supportive of the candidacy of Tyrp1 as representing the Tpnr5 QTL. Tyrosinase-related protein 1 is the rate-limiting enzyme in the production of eumelanin, and possible relationships between eumelanin-expressing cells and thermal nociception are discussed. The positional cloning of Tpnr5 is also considered in light of the heuristic value but continuing challenges of QTL mapping in the mouse.

The Supramap project: linking pathogen genomes with geography to fight emergent infectious diseases

Novel pathogens have the potential to become critical issues of national security, public health and economic welfare. As demonstrated by the response to Severe Acute Respiratory Syndrome (SARS) and influenza, genomic sequencing has become an important method for diagnosing agents of infectious disease. Despite the value of genomic sequences in characterizing novel pathogens, raw data on their own do not provide the information needed by public health officials and researchers. One must integrate knowledge of the genomes of pathogens with host biology and geography to understand the etiology of epidemics. To these ends, we have created an application called Supramap (http://supramap.osu.edu) to put information on the spread of pathogens and key mutations across time, space and various hosts into a geographic information system (GIS). To build this application, we created a web service for integrated sequence alignment and phylogenetic analysis as well as methods to describe the tree, mutations, and host shifts in Keyhole Markup Language (KML). We apply the application to 239 sequences of the polymerase basic 2 (PB2) gene of recent isolates of avian influenza (H5N1). We map a mutation, glutamic acid to lysine at position 627 in the PB2 protein (E627K), in H5N1 influenza that allows for increased replication of the virus in mammals. We use a statistical test to support the hypothesis of a correlation of E627K mutations with avian-mammalian host shifts but reject the hypothesis that lineages with E627K are moving westward. Data, instructions for use, and visualizations are included as supplemental materials at: http://supramap.osu.edu/sm/supramap/publications. © The Willi Hennig Society 2010.

Animal models of eating disorder traits

Eating disorders, such as anorexia and bulimia nervosa, are psychiatric disorders that are likely determined by a complex interaction between genetic variations, developmental processes, and certain life events. Cross-species analysis of traits related to eating disorders may provide a way to functionally and systematically study neurobiological mechanisms underlying these disorders. Interspecies trait genetics may offer opportunities to identify common neurobiological mechanisms underlying eating disorder characteristics relevant to the initiation, progression, and/or maintenance of the disease, such as cognitive rigidity, increased anxiety levels, and behavioral hyperactivity. These can subsequently be tested directly by studying allelic variation in mice and human subjects and by applying methods that can modify gene expression levels in rodent models. Increasing our knowledge about these traits and their underlying neurobiological mechanisms will be relevant to develop new therapies for patients within the heterogeneous eating disorder populations. Novel mouse genetic and phenotyping tools offer a way to study these neurobehavioral traits under controlled environmental and genetic background conditions.

In silico QTL mapping of basal liver iron levels in inbred mouse strains

Both iron deficiency and iron excess are detrimental in many organisms, and previous studies in both mice and humans suggest that genetic variation may influence iron status in mammals. However, these genetic factors are not well defined. To address this issue, we measured basal liver iron levels in 18 inbred strains of mice of both sexes on a defined iron diet and found ∼4-fold variation in liver iron in males (lowest 153 μg/g, highest 661 μg/g) and ∼3-fold variation in females (lowest 222 μg/g, highest 658 μg/g). We carried out a genome-wide association mapping to identify haplotypes underlying differences in liver iron and three other related traits (copper and zinc liver levels, and plasma diferric transferrin levels) in a subset of 14 inbred strains for which genotype information was available. We identified two putative quantitative trait loci (QTL) that contain genes with a known role in iron metabolism: Eif2ak1 and Igf2r. We also identified four putative QTL that reside in previously identified iron-related QTL and 22 novel putative QTL. The most promising putative QTL include a 0.22 Mb region on Chromosome 7 and a 0.32 Mb region on Chromosome 11 that both contain only one candidate gene, Adam12 and Gria1, respectively. Identified putative QTL are good candidates for further refinement and subsequent functional studies.

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.

Genetics of osteoporosis

Osteoporosis is a common disease with a strong genetic component characterized by reduced bone mass, defects in the microarchitecture of bone tissue, and an increased risk of fragility fractures. Twin and family studies have shown high heritability of bone mineral density (BMD) and other determinants of fracture risk such as ultrasound properties of bone, skeletal geometry, and bone turnover. Osteoporotic fractures also have a heritable component, but this reduces with age as environmental factors such as risk of falling come into play. Susceptibility to osteoporosis is governed by many different genetic variants and their interaction with environmental factors such as diet and exercise. Notable successes in identification of genes that regulate BMD have come from the study of rare Mendelian bone diseases characterized by major abnormalities of bone mass where variants of large effect size are operative. Genome-wide association studies have also identified common genetic variants of small effect size that contribute to regulation of BMD and fracture risk in the general population. In many cases, the loci and genes identified by these studies had not previously been suspected to play a role in bone metabolism. Although there has been extensive progress in identifying the genes and loci that contribute to the regulation of BMD and fracture over the past 15 yr, most of the genetic variants that regulate these phenotypes remain to be discovered.

Mapping quantitative traits and strategies to find quantitative trait genes

In 1999 a meeting took place at the Jackson Laboratory, a large mouse research centre in Bar Harbor, Maine, to consider the value of systematically collecting phenotypes on inbred strains of mice (Paigen and Eppig (2000) [1]). The group concluded that cataloguing the extensive phenotypic diversity present among laboratory mice, and in particular providing the research community with data from cohorts of animals, phenotyped according to standardized protocols, was essential if we were to take advantage of the possibilities of mouse genetics. Beginning with the collection of basic physiological, biochemical and behavioral data on nine commonly used inbred strains, the project has expanded so that by the beginning of 2010 data for 178 strains had been collected, with 105 phenotype projects yielding over 2000 different measurements (Bogue et al. (2007) [2].

Strain screen and haplotype association mapping of wheel running in inbred mouse strains

Previous genetic association studies of physical activity, in both animal and human models, have been limited in number of subjects and genetically homozygous strains used as well as number of genomic markers available for analysis. Expansion of the available mouse physical activity strain screens and the recently published dense single-nucleotide polymorphism (SNP) map of the mouse genome (approximately 8.3 million SNPs) and associated statistical methods allowed us to construct a more generalizable map of the quantitative trait loci (QTL) associated with physical activity. Specifically, we measured wheel running activity in male and female mice (average age 9 wk) in 41 inbred strains and used activity data from 38 of these strains in a haplotype association mapping analysis to determine QTL associated with activity. As seen previously, there was a large range of activity patterns among the strains, with the highest and lowest strains differing significantly in daily distance run (27.4-fold), duration of activity (23.6-fold), and speed (2.9-fold). On a daily basis, female mice ran further (24%), longer (13%), and faster (11%). Twelve QTL were identified, with three (on Chr. 12, 18, and 19) in both male and female mice, five specific to males, and four specific to females. Eight of the 12 QTL, including the 3 general QTL found for both sexes, fell into intergenic areas. The results of this study further support the findings of a moderate to high heritability of physical activity and add general genomic areas applicable to a large number of mouse strains that can be further mined for candidate genes associated with regulation of physical activity. Additionally, results suggest that potential genetic mechanisms arising from traditional noncoding regions of the genome may be involved in regulation of physical activity.

Strain-specific susceptibility for pulmonary metastasis of sarcoma 180 cells in inbred mice

Most cancer deaths are a result of metastasis. To extend our understanding of the factors that influence the process, we aimed to develop a mouse model of pulmonary metastasis that can be assayed in multiple inbred mouse strains for further use in identification of host genetic variants that influence metastasis. We used i.v. injection of Sarcoma 180 (S180) cells, which can be tracked and quantified by bioluminescence imaging. We observed growth of S180 cells solely in the lung and observed a wide range of pulmonary metastasis among inbred mouse strains. Interestingly, we noted that the BTBRT+tf/J strain exhibited complete clearance and provide evidence that the mechanism of resistance may involve immune factors, as strains subjected to whole-body irradiation are significantly more susceptible to tumor growth. One possible mechanism of resistance to pulmonary metastasis in BTBRT+tf/J mice may require T-cell function. Our experiments present a new mouse model for further characterization of the genetics and mechanisms of pulmonary metastasis.

Interspecific resources: a major tool for quantitative trait locus cloning and speciation research

Positional cloning of the quantitative trait locus (QTL) still encounters numerous difficulties, which explains why thousands of QTL have been mapped, while only a few have been identified at the molecular level. Here, we focus on a specific mapping tool that exists in plant and animal model species: interspecific recombinant congenic strains (IRCSs) or interspecific nearly isogenic lines (NILs). Such panels exhibit a much higher sequence diversity than intraspecific sets, thus enhancing the contrasts between phenotypes. In animals, it allows statistical significance to be reached even when using a limited number of individuals. Therefore, we argue that interspecific resources may constitute a major genetic tool for positional cloning and for understanding some bases of speciation mechanisms.

Fine mapping in 94 inbred mouse strains using a high-density haplotype resource

The genetics of phenotypic variation in inbred mice has for nearly a century provided a primary weapon in the medical research arsenal. A catalog of the genetic variation among inbred mouse strains, however, is required to enable powerful positional cloning and association techniques. A recent whole-genome resequencing study of 15 inbred mouse strains captured a significant fraction of the genetic variation among a limited number of strains, yet the common use of hundreds of inbred strains in medical research motivates the need for a high-density variation map of a larger set of strains. Here we report a dense set of genotypes from 94 inbred mouse strains containing 10.77 million genotypes over 121,433 single nucleotide polymorphisms (SNPs), dispersed at 20-kb intervals on average across the genome, with an average concordance of 99.94% with previous SNP sets. Through pairwise comparisons of the strains, we identified an average of 4.70 distinct segments over 73 classical inbred strains in each region of the genome, suggesting limited genetic diversity between the strains. Combining these data with genotypes of 7570 gap-filling SNPs, we further imputed the untyped or missing genotypes of 94 strains over 8.27 million Perlegen SNPs. The imputation accuracy among classical inbred strains is estimated at 99.7% for the genotypes imputed with high confidence. We demonstrated the utility of these data in high-resolution linkage mapping through power simulations and statistical power analysis and provide guidelines for developing such studies. We also provide a resource of in silico association mapping between the complex traits deposited in the Mouse Phenome Database with our genotypes. We expect that these resources will facilitate effective designs of both human and mouse studies for dissecting the genetic basis of complex traits.

A survey of airway responsiveness in 36 inbred mouse strains facilitates gene mapping studies and identification of quantitative trait loci

Airway hyper-responsiveness (AHR) is a critical phenotype of human asthma and animal models of asthma. Other studies have measured AHR in nine mouse strains, but only six strains have been used to identify genetic loci underlying AHR. Our goals were to increase the genetic diversity of available strains by surveying 27 additional strains, to apply haplotype association mapping to the 36-strain survey, and to identify new genetic determinants for AHR. We derived AHR from the increase in airway resistance in females subjected to increasing levels of methacholine concentrations. We used haplotype association mapping to identify associations between AHR and haplotypes on chromosomes 3, 5, 8, 12, 13, and 14. And we used bioinformatics techniques to narrow the identified region on chromosome 13, reducing the region to 29 candidate genes, with 11 of considerable interest. Our combined use of haplotype association mapping with bioinformatics tools is the first study of its kind for AHR on these 36 strains of mice. Our analyses have narrowed the possible QTL genes and will facilitate the discovery of novel genes that regulate AHR in mice.

Assessing the prospects of genome-wide association studies performed in inbred mice

The remarkable success in mapping genes linked to a number of disease traits using genome-wide association studies (GWAS) in human cohorts has renewed interest in applying this same technique in model organisms such as inbred laboratory mice. Unlike humans, however, the limited genetic diversity in the ancestry of laboratory mice combined with selection pressure over the past decades have yielded an intricate population genetic structure that can complicate the results obtained from association studies. This problem is further exacerbated by the small number of strains typically used in such studies where multiple spurious associations arise as a result of random chance. We sought to empirically assess the viability of GWAS in inbred mice using hundreds of expression traits for which the true location of the expression quantitative trait locus was known a priori. We then measured transcript abundance levels for these expression traits in 16 classical and 3 wild-derived inbred strains and carried out a genome-wide association scan, demonstrating the low statistical power of such studies and empirically estimating the large extent to which allelic association of transcripts gives rise to spurious associations. We provide evidence illustrating that in a large fraction of cases, the marker with the most significant p values fails to map to the location of the true eQTL. Finally, we provide experimental support for hundreds of traits, and that combining linkage analysis with association mapping provides significant increases in statistical power over a stand-alone GWAS as well as significantly higher mapping resolution than either study alone.

A comprehensive linkage map of the dog genome

We have leveraged the reference sequence of a boxer to construct the first complete linkage map for the domestic dog. The new map improves access to the dog's unique biology, from human disease counterparts to fascinating evolutionary adaptations. The map was constructed with approximately 3000 microsatellite markers developed from the reference sequence. Familial resources afforded 450 mostly phase-known meioses for map assembly. The genotype data supported a framework map with approximately 1500 loci. An additional approximately 1500 markers served as map validators, contributing modestly to estimates of recombination rate but supporting the framework content. Data from approximately 22,000 SNPs informing on a subset of meioses supported map integrity. The sex-averaged map extended 21 M and revealed marked region- and sex-specific differences in recombination rate. The map will enable empiric coverage estimates and multipoint linkage analysis. Knowledge of the variation in recombination rate will also inform on genomewide patterns of linkage disequilibrium (LD), and thus benefit association, selective sweep, and phylogenetic mapping approaches. The computational and wet-bench strategies can be applied to the reference genome of any nonmodel organism to assemble a de novo linkage map.

A high-resolution association mapping panel for the dissection of complex traits in mice

Systems genetics relies on common genetic variants to elucidate biologic networks contributing to complex disease-related phenotypes. Mice are ideal model organisms for such approaches, but linkage analysis has been only modestly successful due to low mapping resolution. Association analysis in mice has the potential of much better resolution, but it is confounded by population structure and inadequate power to map traits that explain less than 10% of the variance, typical of mouse quantitative trait loci (QTL). We report a novel strategy for association mapping that combines classic inbred strains for mapping resolution and recombinant inbred strains for mapping power. Using a mixed model algorithm to correct for population structure, we validate the approach by mapping over 2500 cis-expression QTL with a resolution an order of magnitude narrower than traditional QTL analysis. We also report the fine mapping of metabolic traits such as plasma lipids. This resource, termed the Hybrid Mouse Diversity Panel, makes possible the integration of multiple data sets and should prove useful for systems-based approaches to complex traits and studies of gene-by-environment interactions.

Genetics of osteoporosis: accelerating pace in gene identification and validation

Osteoporosis is characterized by low bone mineral density and structural deterioration of bone tissue, leading to an increased risk of fractures. It is the most common metabolic bone disorder worldwide, affecting one in three women and one in eight men over the age of 50. In the past 15 years, a large number of genes have been reported as being associated with osteoporosis. However, only in the past 4 years we have witnessed an accelerated pace in identifying and validating osteoporosis susceptibility loci. This increase in pace is mostly due to large-scale association studies, meta-analyses, and genome-wide association studies of both single nucleotide polymorphisms and copy number variations. A comprehensive review of these developments revealed that, to date, at least 15 genes (VDR, ESR1, ESR2, LRP5, LRP4, SOST, GRP177, OPG, RANK, RANKL, COLIA1, SPP1, ITGA1, SP7, and SOX6) can be reasonably assigned as confirmed osteoporosis susceptibility genes, whereas, another >30 genes are promising candidate genes. Notably, confirmed and promising genes are clustered in three biological pathways, the estrogen endocrine pathway, the Wnt/beta-catenin signaling pathway, and the RANKL/RANK/OPG pathway. New biological pathways will certainly emerge when more osteoporosis genes are identified and validated. These genetic findings may provide new routes toward improved therapeutic and preventive interventions of this complex disease.

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.