Increasing association mapping power and resolution in mouse genetic studies through the use of meta-analysis for structured populations

Genetic studies in mouse models have played an integral role in the discovery of the mechanisms underlying many human diseases. The primary mode of discovery has been the application of linkage analysis to mouse crosses. This approach results in high power to identify regions that affect traits, but in low resolution, making it difficult to identify the precise genomic location harboring the causal variant. Recently, a panel of mice referred to as the hybrid mouse diversity panel (HMDP) has been developed to overcome this problem. However, power in this panel is limited by the availability of inbred strains. Previous studies have suggested combining results across multiple panels as a means to increase power, but the methods employed may not be well suited to structured populations, such as the HMDP. In this article, we introduce a meta-analysis-based method that may be used to combine HMDP studies with F2 cross studies to gain power, while increasing resolution. Due to the drastically different genetic structure of F2s and the HMDP, the best way to combine two studies for a given SNP depends on the strain distribution pattern in each study. We show that combining results, while accounting for these patterns, leads to increased power and resolution. Using our method to map bone mineral density, we find that two previously implicated loci are replicated with increased significance and that the size of the associated is decreased. We also map HDL cholesterol and show a dramatic increase in the significance of a previously identified result.     

Genome-wide association mapping of blood cell traits in mice

Genetic variations in blood cell parameters can impact clinical traits. We report here the mapping of blood cell traits in a panel of 100 inbred strains of mice of the Hybrid Mouse Diversity Panel (HMDP) using genome-wide association (GWA). We replicated a locus previously identified in using linkage analysis in several genetic crosses for mean corpuscular volume (MCV) and a number of other red blood cell traits on distal chromosome 7. Our peak for SNP association to MCV occurred in a linkage disequilibrium (LD) block spanning from 109.38 to 111.75 Mb that includes Hbb-b1, the likely causal gene. Altogether, we identified five loci controlling red blood cell traits (on chromosomes 1, 7, 11, 12, and 16), and four of these correspond to loci for red blood cell traits reported in a recent human GWA study. For white blood cells, including granulocytes, monocytes, and lymphocytes, a total of six significant loci were identified on chromosomes 1, 6, 8, 11, 12, and 15. An average of ten candidate genes were found at each locus and those were prioritized by examining functional variants in the HMDP such as missense and expression variants. These results provide intermediate phenotypes and candidate loci for genetic studies of atherosclerosis and cancer as well as inflammatory and immune disorders in mice.     

An integrative approach for the identification of quantitative trait loci

The genetic dissection of complex traits is one of the most difficult and most important challenges facing science today. We discuss here an integrative approach to quantitative trait loci (QTL) mapping in mice. This approach makes use of the wealth of genetic tools available in mice, as well as the recent advances in genome sequence data already available for a number of inbred mouse strains. We have developed mapping strategies that allow a stepwise narrowing of a QTL mapping interval, prioritizing candidate genes for further analysis with the potential of identifying the most probable candidate gene for the given trait. This approach integrates traditional mapping tools, fine mapping tools, sequence-based analysis, bioinformatics and gene expression.     

Effects of ENU dosage on mouse strains

The germline supermutagen, N-ethyl-N-nitrosourea (ENU), has a variety of effects on mice. ENU is a toxin and carcinogen as well as a mutagen, and strains differ in their susceptibility to its effects. Therefore, it is necessary to determine an appropriate mutagenic, non-toxic dose of ENU for strains that are to be used in experiments. In order to provide some guidance, we have compiled data from a number of laboratories that have exposed male mice from inbred and non-inbred strains or their F₁ hybrids to ENU. The results show that most F₁ hybrid animals tolerate ENU well, but that inbred strains of mice vary in their longevity and in their ability to recover fertility after treatment with ENU. Received: 11 February 2000 / Accepted: 11 February 2000     

A comprehensive SNP-based genetic analysis of inbred mouse strains

Dense genetic maps of mammalian genomes facilitate a variety of biological studies including the mapping of polygenic traits, positional cloning of monogenic traits, mapping of quantitative or qualitative trait loci, marker association, allelic imbalance, speed congenic construction, and evolutionary or phylogenetic comparison. In particular, single nucleotide polymorphisms (SNPs) have proved useful because of their abundance and compatibility with multiple high-throughput technology platforms. SNP genotyping is especially suited for the genetic analysis of model organisms such as the mouse because biallelic markers remain fully informative when used to characterize crosses between inbred strains. Here we report the mapping and genotyping of 673 SNPs (including 519 novel SNPs) in 55 of the most commonly used mouse strains. These data have allowed us to construct a phylogenetic tree that correlates and expands known genealogical relationships and clarifies the origin of strains previously having an uncertain ancestry. All 55 inbred strains are distinguishable genetically using this SNP panel. Our data reveal an uneven SNP distribution consistent with a mosaic pattern of inheritance and provide some insight into the changing dynamics of the physical architecture of the genome. Furthermore, these data represent a valuable resource for the selection of markers and the design of experiments that require the genetic distinction of any pair of mouse inbred strains such as the generation of congenic mice, positional cloning, and the mapping of quantitative or qualitative trait loci.The content of this publication does not necessarily reflect the view or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.     

Integrating QTL and high-density SNP analyses in mice to identify Insig2 as a susceptibility gene for plasma cholesterol levels

The use of inbred strains of mice to dissect the genetic complexity of common diseases offers a viable alternative to human studies, given the control over experimental parameters that can be exercised. Central to efforts to map susceptibility loci for common diseases in mice is a comprehensive map of DNA variation among the common inbred strains of mice. Here we present one of the most comprehensive high-density, single nucleotide polymorphism (SNP) maps of mice constructed to date. This map consists of 10,350 SNPs genotyped in 62 strains of inbred mice. We demonstrate the utility of these data via a novel integrative genomics approach to mapping susceptibility loci for complex traits. By integrating in silico quantitative trait locus (QTL) mapping with progressive QTL mapping strategies in segregating mouse populations that leverage large-scale mapping of the genetic determinants of gene expression traits, we not only facilitate identification of candidate quantitative trait genes, but also protect against spurious associations that can arise in genetic association studies due to allelic association among unlinked markers. Application of this approach to our high-density SNP map and two previously described F2 crosses between strains C57BL/6J (B6) and DBA/2J and between B6 ApoE(-/-) and C3H/HeJ ApoE(-/-) results in the identification of Insig2 as a strong candidate susceptibility gene for total plasma cholesterol levels.     

Production of congenic mouse strains carrying NOD-derived diabetogenic genetic intervals: An approach for the genetic dissection of complex traits

Insulin-dependent (Type 1) diabetes (IDD) in the NOD mouse is inherited as a complex polygenic trait making the identification of susceptibility genes difficult. Currently none of the non-MHC IDD susceptibility genes in NOD have been identified. In this paper we describe the congenic mouse approach that we are using for the dissection of complex traits, such as IDD. We produced a series of six congenic strains carrying NOD-derived diabetogenic genomic intervals, which were previously identified by linkage analysis, on a resistant background. These congenic strains were produced for the purpose of characterizing the function of each of these genes, alone and in combinations, in IDD pathogenesis and to allow fine mapping of the NOD IDD susceptibility genes. Histological examination of pancreata from 6 to 8-month-old congenic mice reveals that intervals on Chromosomes (Chrs) 1 and 17, but not 3, 6, and 11, contain NOD-derived genes that can increase the trafficking of mononuclear cells into the pancreas. Insulitis was observed only very rarely, even in older congenic mice, indicating that multiple genes are required for this phenotype. These results demonstrate the utility of this congenic approach for the study of complex genetic traits. Received: 1 September 1995 / Accepted: 20 December 1995     

Convergent analysis of cDNA and short oligomer microarrays, mouse null mutants and bioinformatics resources to study complex traits

Gene expression data sets have recently been exploited to study genetic factors that modulate complex traits. However, it has been challenging to establish a direct link between variation in patterns of gene expression and variation in higher order traits such as neuropharmacological responses and patterns of behavior. Here we illustrate an approach that combines gene expression data with new bioinformatics resources to discover genes that potentially modulate behavior. We have exploited three complementary genetic models to obtain convergent evidence that differential expression of a subset of genes and molecular pathways influences ethanol-induced conditioned taste aversion (CTA). As a first step, cDNA microarrays were used to compare gene expression profiles of two null mutant mouse lines with difference in ethanol-induced aversion. Mice lacking a functional copy of G protein-gated potassium channel subunit 2 (Girk2) show a decrease in the aversive effects of ethanol, whereas preproenkephalin (Penk) null mutant mice show the opposite response. We hypothesize that these behavioral differences are generated in part by alterations in expression downstream of the null alleles. We then exploited the WebQTL databases to examine the genetic covariance between mRNA expression levels and measurements of ethanol-induced CTA in BXD recombinant inbred (RI) strains. Finally, we identified a subset of genes and functional groups associated with ethanol-induced CTA in both null mutant lines and BXD RI strains. Collectively, these approaches highlight the phosphatidylinositol signaling pathway and identify several genes including protein kinase C beta isoform and preproenkephalin in regulation of ethanol- induced conditioned taste aversion. Our results point to the increasing potential of the convergent approach and biological databases to investigate genetic mechanisms of complex traits.     

The phenotypic distribution of quantitative traits in a wild mouse F1 population

The human complex diseases such as hypertension, precocious puberty, and diabetes have their own diagnostic thresholds, which are usually estimated from the epidemiological data of nature populations. In the mouse models, numerous phenotypic data of complex traits have been accumulated; however, knowledge of the phenotypic distribution of the natural mouse populations remains quite limited. In order to investigate the distribution of quantitative traits of wild mice, 170 F1 progeny aged 8-10?weeks and derived from wild mice collected from eight spots in the suburbs of Shanghai were tested for their values of anatomic, blood chemical, and blood hematological parameters. All the wild mice breeders were of Mus. m. musculus and Mus. m. castaneus maternal origin according to the single nucleotide polymorphism (SNP) markers of the mitochondrial DNA. The results showed that phenotypes in wild mice had a normal distribution with four to six times the standard deviation. For the majority of the traits, the wild outbred mice and laboratory inbred mice have significantly different ranges and mean values, whereas the wild mice did not necessarily show more phenotypic diversity than the inbred ones. Our data also showed that natural populations may have some unique phenotypes related to sugar and protein metabolism, as the mean value of wild mice differ dramatically from the inbred mice in the levels of blood glucose, BUN (blood urea nitrogen), and total blood protein. The epidemiological information of the complex traits in the nature population from our study provided valuable reference for the application of mouse models in those complex disease studies.     

Nucleotide variation in wild and inbred mice

The house mouse is a well-established model organism, particularly for studying the genetics of complex traits. However, most studies of mice use classical inbred strains, whose genomes derive from multiple species. Relatively little is known about the distribution of genetic variation among these species or how variation among strains relates to variation in the wild. We sequenced intronic regions of five X-linked loci in large samples of wild Mus domesticus and M. musculus, and we found low levels of nucleotide diversity in both species. We compared these data to published data from short portions of six X-linked and 18 autosomal loci in wild mice. We estimate that M. domesticus and M. musculus diverged <500,000 years ago. Consistent with this recent divergence, some gene genealogies were reciprocally monophyletic between these species, while others were paraphyletic or polyphyletic. In general, the X chromosome was more differentiated than the autosomes. We resequenced classical inbred strains for all 29 loci and found that inbred strains contain only a small amount of the genetic variation seen in wild mice. Notably, the X chromosome contains proportionately less variation among inbred strains than do the autosomes. Moreover, variation among inbred strains derives from differences between species as well as from differences within species, and these proportions differ in different genomic regions. Wild mice thus provide a reservoir of additional genetic variation that may be useful for mapping studies. Together these results suggest that wild mice will be a valuable complement to laboratory strains for studying the genetics of complex traits.     

Multiple trait measurements in 43 inbred mouse strains capture the phenotypic diversity characteristic of human populations.

The breadth of genetic and phenotypic variation among inbred strains is often underappreciated because assessments include only a limited number of strains. Evaluation of a larger collection of inbred strains provides not only a greater understanding of this variation but collectively mimics much of the variation observed in human populations. We used a high-throughput phenotyping protocol to measure females and males of 43 inbred strains for body composition (weight, fat, lean tissue mass, and bone mineral density), plasma triglycerides, high-density lipoprotein and total cholesterol, glucose, insulin, and leptin levels while mice consumed a high-fat, high-cholesterol diet. Mice were fed a chow diet until they were 6-8 wk old and then fed the high-fat diet for an additional 18 wk. As expected, broad phenotypic diversity was observed among these strains. Significant variation between the sexes was also observed for most traits measured. Additionally, the response to the high-fat diet differed considerably among many strains. By the testing of such a large set of inbred strains for many traits, multiple phenotypes can be considered simultaneously and thereby aid in the selection of certain inbred strains as models for complex human diseases. These data are publicly available in the web-accessible Mouse Phenome Database (http://www.jax.org/phenome), an effort established to promote systematic characterization of biochemical and behavioral phenotypes of commonly used and genetically diverse inbred mouse strains. Data generated by this effort builds on the value of inbred mouse strains as a powerful tool for biomedical research.     

Development of a SNP genotyping panel for genetic monitoring of the laboratory mouse

We have developed a genotyping system for detecting genetic contamination in the laboratory mouse based on assaying single-nucleotide polymorphism (SNP) markers positioned on all autosomes and the X chromosome. This system provides a fast, reliable, and cost-effective way for genetic monitoring, while maintaining a very high degree of confidence. We describe the allelic distribution of 235 SNPs in 48 mouse strains, thereby creating a database of polymorphisms useful for genotyping purposes. The SNP markers used in this study were chosen from publicly available SNP databases. Four genotyping methods were evaluated, and dynamic two-tube allele-specific PCR assays were developed for each marker and tested on a set of 48 inbred mouse strains. The minimal number of assays sufficient to distinguish groups consisting of different numbers of mouse strains was estimated, and a panel of 28 SNPs sufficient to distinguish virtually all of the inbred strains tested was selected. Amplifluor SNP detection assays were developed for these markers and tested on an extended list of 96 strains. This panel was used as a genetic quality control approach to monitor the genotypes of nearly 300 inbred, wild-derived, congenic, consomic, and recombinant inbred strains maintained at The Jackson Laboratory. We have concluded that this marker panel is sufficient for genetic contamination monitoring in colonies containing a large number of genetically diverse mouse strains and that reduced versions of the panel could be implemented in facilities housing a lower number of strains.     

An imputed genotype resource for the laboratory mouse

We have created a high-density SNP resource encompassing 7.87 million polymorphic loci across 49 inbred mouse strains of the laboratory mouse by combining data available from public databases and training a hidden Markov model to impute missing genotypes in the combined data. The strong linkage disequilibrium found in dense sets of SNP markers in the laboratory mouse provides the basis for accurate imputation. Using genotypes from eight independent SNP resources, we empirically validated the quality of the imputed genotypes and demonstrated that they are highly reliable for most inbred strains. The imputed SNP resource will be useful for studies of natural variation and complex traits. It will facilitate association study designs by providing high-density SNP genotypes for large numbers of mouse strains. We anticipate that this resource will continue to evolve as new genotype data become available for laboratory mouse strains. The data are available for bulk download or query at /. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A protocol for high-throughput phenotyping, suitable for quantitative trait analysis in mice

Whole-genome genetic association studies in outbred mouse populations represent a novel approach to identifying the molecular basis of naturally occurring genetic variants, the major source of quantitative variation between inbred strains of mice. Measuring multiple phenotypes in parallel on each mouse would make the approach cost effective, but protocols for phenotyping on a large enough scale have not been developed. In this article we describe the development and deployment of a protocol to collect measures on three models of human disease (anxiety, type II diabetes, and asthma) as well as measures of mouse blood biochemistry, immunology, and hematology. We report that the protocol delivers highly significant differences among the eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6 J, DBA/2 J, and LP/J), the progenitors of a genetically heterogeneous stock (HS) of mice. We report the successful collection of multiple phenotypes from 2000 outbred HS animals. The phenotypes measured in the protocol form the basis of a large-scale investigation into the genetic basis of complex traits in mice designed to examine interactions between genes and between genes and environment, as well as the main effects of genetic variants on phenotypes.     

Reward-related behavioral paradigms for addiction research in the mouse: performance of common inbred strains

The mouse has emerged as a uniquely valuable species for studying the molecular and genetic basis of complex behaviors and modeling neuropsychiatric disease states. While valid and reliable preclinical assays for reward-related behaviors are critical to understanding addiction-related processes, and various behavioral procedures have been developed and characterized in rats and primates, there have been relatively few studies using operant-based addiction-relevant behavioral paradigms in the mouse. Here we describe the performance of the C57BL/6J inbred mouse strain on three major reward-related paradigms, and replicate the same procedures in two other commonly used inbred strains (DBA/2J, BALB/cJ). We examined Pavlovian-instrumental transfer (PIT) by measuring the ability of an auditory cue associated with food reward to promote an instrumental (lever press) response. In a separate experiment, we assessed the acquisition and extinction of a simple stimulus-reward instrumental behavior on a touch screen based task. Reinstatement of this behavior was then examined following either continuous exposure to cues (conditioned reinforcers, CRs) associated with reward, brief reward and CR exposure, or brief reward exposure followed by continuous CR exposure. The third paradigm examined sensitivity of an instrumental (lever press) response to devaluation of food reward (a probe for outcome insensitive, habitual behavior) by repeated pairing with malaise. Results showed that C57BL/6J mice displayed robust PIT, as well as clear extinction and reinstatement, but were insensitive to reinforcer devaluation. DBA/2J mice showed good PIT and (rewarded) reinstatement, but were slow to extinguish and did not show reinforcer devaluation or significant CR-reinstatement. BALB/cJ mice also displayed good PIT, extinction and reinstatement, and retained instrumental responding following devaluation, but, unlike the other strains, demonstrated reduced Pavlovian approach behavior (food magazine head entries). Overall, these assays provide robust paradigms for future studies using the mouse to elucidate the neural, molecular and genetic factors underpinning reward-related behaviors relevant to addiction research.