Association studies in outbred mice in a new era of full-genome sequencing

Rodent models in sensorineural hearing loss research: A comprehensive review

Sensorineural hearing loss (SNHL) constitutes a major global health challenge, affecting millions of individuals and substantially impairing social integration and quality of life. The complexity of the auditory system and the multifaceted nature of SNHL necessitate advanced methodologies to understand its etiology, progression, and potential therapeutic interventions. This review provides a comprehensive overview of the current animal models used in SNHL research, focusing on their selection based on specific characteristics and their contributions to elucidating pathophysiological mechanisms and evaluating novel treatment strategies. It discusses the most commonly used rodent models in hearing research, including mice, rats, guinea pigs, Mongolian gerbils, and chinchillas. Through a comparative analysis, this review underscores the importance of selecting models that align with specific research objectives in SNHL studies, discussing the advantages and limitations of each model. By advocating for a multidisciplinary approach that leverages the strengths of various animal models with technological advancements, this review aims to facilitate significant advancements in the prevention, diagnosis, and treatment of sensorineural hearing loss.

Supervised machine learning of outbred mouse genotypes to predict hepatic immunological tolerance of individuals

It is essential to elucidate the molecular mechanisms underlying liver transplant tolerance and rejection. In cases of mouse liver transplantation between inbred strains, immunological rejection of the allograft is reduced with spontaneous apoptosis without immunosuppressive drugs, which differs from the actual clinical result. This may be because inbred strains are genetically homogeneous and less heterogeneous than others. We exploited outbred CD1 mice, which show highly heterogeneous genotypes among individuals, to search for biomarkers related to immune responses and to construct a model for predicting the outcome of liver allografting. Of the 36 mice examined, 18 died within 3 weeks after transplantation, while the others survived for more than 6 weeks. Whole-exome sequencing of the 36 donors revealed more than 9 million variants relative to the C57BL/6 J reference. We selected 6517 single-nucleotide and indel variants and performed machine learning to determine whether or not we could predict the prognosis of each genotype. Models were built by both deep learning with a one-dimensional convolutional neural network and linear classification and evaluated by leave-one-out cross-validation. Given that one short-lived mouse died early in an accident, the models perfectly predicted the outcome of all individuals, suggesting the importance of genotype collection. In addition, linear classification models provided a list of loci potentially responsible for these responses. The present methods as well as results is likely to be applicable to liver transplantation in humans.

Genetics of murine type 2 diabetes and comorbidities

ABSTRAC

Type 2 diabetes (T2D) is a polygenic and multifactorial complex disease, defined as chronic metabolic disorder. It's a major global health concern with an estimated 463 million adults aged 20-79 years with diabetes and projected to increase up to 700 million by 2045. T2D was reported to be one of the four leading causes of non-communicable disease (NCD) deaths in 2012. Environmental factors play a part in the development of polygenic forms of diabetes. Polygenic forms of diabetes often run-in families. Fortunately, T2D, which accounts for 90-95% of the entire four types of diabetes including, Type 1 diabetes (T1D), T2D, monogenic diabetes syndromes (MGDS), and Gestational diabetes mellitus, can be prevented or delayed through nutrition and lifestyle changes as well as through pharmacologic interventions. Typical symptom of the T2D is high blood glucose levels and comprehensive insulin resistance of the body, producing an impaired glucose tolerance. Impaired glucose tolerance of T2D is accompanied by extensive health complications, including cardiovascular diseases (CVD) that vary in morbidity and mortality among populations. The pathogenesis of T2D varies between populations and/or ethnic groupings and is known to be attributed extremely by genetic components and environmental factors. It is evident that genetic background plays a critical role in determining the host response toward certain environmental conditions, whether or not of developing T2D (susceptibility versus resistant). T2D is considered as a silent disease that can progress for years before its diagnosis. Once T2D is diagnosed, many metabolic malfunctions are observed whether as side effects or as independent comorbidity. Mouse models have been proven to be a powerful tool for mapping genetic factors that underline the susceptibility to T2D development as well its comorbidities. Here, we have conducted a comprehensive search throughout the published data covering the time span from early 1990s till the time of writing this review, for already reported quantitative trait locus (QTL) associated with murine T2D and comorbidities in different mouse models, which contain different genetic backgrounds. Our search has resulted in finding 54 QTLs associated with T2D in addition to 72 QTLs associated with comorbidities associated with the disease. We summarized the genomic locations of these mapped QTLs in graphical formats, so as to show the overlapping positions between of these mapped QTLs, which may suggest that some of these QTLs could be underlined by sharing gene/s. Finally, we reviewed and addressed published reports that show the success of translation of the identified mouse QTLs/genes associated with the disease in humans.

Utilizing preclinical models of genetic diversity to improve translation of phytochemical activities from rodents to humans and inform personalized nutrition

Mouse models are an essential tool in different areas of research, including nutrition and phytochemical research. Traditional inbred mouse models have allowed the discovery of therapeutical targets and mechanisms of action and expanded our knowledge of health and disease. However, these models lack the genetic variability typically found in human populations, which hinders the translatability of the results found in mice to humans. The development of genetically diverse mouse models, such as the collaborative cross (CC) or the diversity outbred (DO) models, has been a useful tool to overcome this obstacle in many fields, such as cancer, immunology and toxicology. However, these tools have not yet been widely adopted in the field of phytochemical research. As demonstrated in other disciplines, use of CC and DO models has the potential to provide invaluable insights for translation of phytochemicals from rodents to humans, which are desperately needed given the challenges and numerous failed clinical trials in this field. These models may prove informative for personalized use of phytochemicals in humans, including: predicting interindividual variability in phytochemical bioavailability and efficacy, identifying genetic loci or genes governing response to phytochemicals, identifying phytochemical mechanisms of action and therapeutic targets, and understanding the impact of genetic variability on individual response to phytochemicals. Such insights would prove invaluable for personalized implementation of phytochemicals in humans. This review will focus on the current work performed with genetically diverse mouse populations, and the research opportunities and advantages that these models can offer to phytochemical research.

5' UTR variants in the quantitative trait gene Hnrnph1 support reduced 5' UTR usage and hnRNP H protein as a molecular mechanism underlying reduced methamphetamine sensitivity

We previously identified a 210 kb region on chromosome 11 (50.37-50.58 Mb, mm10) containing two protein-coding genes (Hnrnph1, Rufy1) that was necessary for reduced methamphetamine-induced locomotor activity in C57BL/6J congenic mice harboring DBA/2J polymorphisms. Gene editing of a small deletion in the first coding exon supported Hnrnph1 as a quantitative trait gene. We have since shown that Hnrnph1 mutants also exhibit reduced methamphetamine-induced reward, reinforcement, and dopamine release. However, the quantitative trait variants (QTVs) that modulate Hnrnph1 function at the molecular level are not known. Nine single nucleotide polymorphisms and seven indels distinguish C57BL/6J from DBA/2J within Hnrnph1, including four variants within the 5' untranslated region (UTR). Here, we show that a 114 kb introgressed region containing Hnrnph1 and Rufy1 was sufficient to cause a decrease in MA-induced locomotor activity. Gene-level transcriptome analysis of striatal tissue from 114 kb congenics vs Hnrnph1 mutants identified a nearly perfect correlation of fold-change in expression for those differentially expressed genes that were common to both mouse lines, indicating functionally similar effects on the transcriptome and behavior. Exon-level analysis (including noncoding exons) revealed decreased 5' UTR usage of Hnrnph1 and immunoblot analysis identified a corresponding decrease in hnRNP H protein in 114 kb congenic mice. Molecular cloning of the Hnrnph1 5' UTR containing all four variants (but none of them individually) upstream of a reporter induced a decrease in reporter signal in both HEK293 and N2a cells, thus, identifying a set of QTVs underlying molecular regulation of Hnrnph1.

Using Heterogeneous Stocks for Fine-Mapping Genetically Complex Traits

In this chapter we will review both the rationale and experimental design for using Heterogeneous Stock (HS) populations for fine-mapping of complex traits in mice and rats. We define an HS as an outbred population derived from an intercross between two or more inbred strains. HS have been used to perform genome-wide association studies (GWAS) for multiple behavioral, physiological, and gene expression traits. GWAS using HS require four key steps, which we review: selection of an appropriate HS population, phenotyping, genotyping, and statistical analysis. We provide advice on the selection of an HS, comment on key issues related to phenotyping, discuss genotyping methods relevant to these populations, and describe statistical genetic analyses that are applicable to genetic analyses that use HS.

Immune Relevant and Immune Deficient Mice: Options and Opportunities in Translational Research

In 1989 ILAR published a list and description of immunodeficient rodents used in research. Since then, advances in understanding of molecular mechanisms; recognition of genetic, epigenetic microbial, and other influences on immunity; and capabilities in manipulating genomes and microbiomes have increased options and opportunities for selecting mice and designing studies to answer important mechanistic and therapeutic questions. Despite numerous scientific breakthroughs that have benefitted from research in mice, there is debate about the relevance and predictive or translational value of research in mice. Reproducibility of results obtained from mice and other research models also is a well-publicized concern. This review summarizes resources to inform the selection and use of immune relevant mouse strains and stocks, aiming to improve the utility, validity, and reproducibility of research in mice. Immune sufficient genetic variations, immune relevant spontaneous mutations, immunodeficient and autoimmune phenotypes, and selected induced conditions are emphasized.

Untangling the genomics of noise-induced hearing loss and tinnitus: Contributions of Mus musculus and Homo sapiens

Acoustic trauma is a feature of the industrial age, in general, and mechanized warfare, in particular. Noise-induced hearing loss (NIHL) and tinnitus have been the number 1 and number 2 disabilities at U.S. Veterans hospitals since 2006. In a reversal of original protocols to identify candidate genes associated with monogenic deafness disorders, unbiased genome-wide association studies now direct animal experiments in order to explore genetic variants common in Homo sapiens. However, even these approaches must utilize animal studies for validation of function and understanding of mechanisms. Animal research currently focuses on genetic expression profiles since the majority of variants occur in non-coding regions, implying regulatory divergences. Moving forward, it will be important in both human and animal research to define the phenotypes of hearing loss and tinnitus, as well as exposure parameters, in order to extricate genes related to acoustic trauma versus those related to aging. It has become clear that common disorders like acoustic trauma are influenced by large numbers of genes, each with small effects, which cumulatively lead to susceptibility to a disorder. A polygenic risk score, which aggregates these small effect sizes of multiple genes, may offer a more accurate description of risk for NIHL and/or tinnitus.

Heterogeneous Stock Populations for Analysis of Complex Traits

Heterogeneous Stock (HS) populations allow for fine-resolution genetic mapping of a variety of complex traits. HS mice and rats were created from breeding together eight inbred strains, followed by maintaining the colony in a manner that minimizes inbreeding. After 50 or more generations of breeding, the resulting animals' chromosomes represent a genetic mosaic of the founders' haplotypes, with the average distance between recombination events in the centiMorgan range. This allows for genetic mapping to only a few Mb, a much smaller region than what can be identified using traditional F2 intercross or backcross mapping strategies. HS animals have been used to fine-map a variety of complex traits including anxiety and fear behaviors, diabetes, asthma, and heart disease, among others. Once a quantitative trait locus (QTL) has been identified, founder sequence and expression analysis can be used to identify underlying causal genes. In the following review, we provide an overview of how HS rats and mice have been used to identify genetic loci, and in some cases the causal genes, underlying complex traits. We discuss the creation and breeding strategies for both HS rats and mice. We then discuss the statistical analyses used to identify genetic loci, as well as strategies to identify causal genes underlying these loci. We end the chapter by discussing limitations faced when using HS populations, including several statistical challenges that have not been fully resolved.

Identifying genes for neurobehavioural traits in rodents: progress and pitfalls

Identifying genes and pathways that contribute to differences in neurobehavioural traits is a key goal in psychiatric research. Despite considerable success in identifying quantitative trait loci (QTLs) associated with behaviour in laboratory rodents, pinpointing the causal variants and genes is more challenging. For a long time, the main obstacle was the size of QTLs, which could encompass tens if not hundreds of genes. However, recent studies have exploited mouse and rat resources that allow mapping of phenotypes to narrow intervals, encompassing only a few genes. Here, we review these studies, showcase the rodent resources they have used and highlight the insights into neurobehavioural traits provided to date. We discuss what we see as the biggest challenge in the field - translating QTLs into biological knowledge by experimentally validating and functionally characterizing candidate genes - and propose that the CRISPR/Cas genome-editing system holds the key to overcoming this obstacle. Finally, we challenge traditional views on inbred versus outbred resources in the light of recent resource and technology developments.

Genetic Mapping of Quantitative Trait Loci for Egg Production and Egg Quality Traits in Chickens: a Review

Chickens display a wide spectrum of phenotypic variations in quantitative traits such as egg-related traits. Quantitative trait locus (QTL) analysis is a statistical method used to understand the relationship between phenotypic (trait measurements) and genotypic data (molecular markers). We have performed QTL analyses for egg-related traits using an original resource population based on the Japanese Large Game (Oh-Shamo) and the White Leghorn breeds of chickens. In this article, we summarize the results of our extensive QTL analyses for 11 and 66 traits for egg production and egg quality, respectively. We reveal that at least 30 QTL regions on 17 different chromosomes affect phenotypic variation in egg-related traits. Each locus had an age-specific effect on traits, and a variety in effects was also apparent, such as additive, dominance, and epistatic-interaction effects. Although genome-wide association study (GWAS) is suitable for gene-level resolution mapping of GWAS loci with additive effects, QTL mapping studies enable us to comprehensively understand genetic control, such as chromosomal regions, genetic contribution to phenotypic variance, mode of inheritance, and age-specificity of both common and rare alleles. QTL analyses also describe the relationship between genotypes and phenotypes in experimental populations. Accumulation of QTL information, including GWAS loci, is also useful for studies of population genomics approached without phenotypic data in order to validate the identified genomic signatures of positive selection. The combination of QTL studies and next-generation sequencing techniques with uncharacterized genetic resources will enhance current understanding of the relationship between genotypes and phenotypes in livestock animals.

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins

Infection is one of the leading causes of human mortality and morbidity. Exposure to microbial agents is obviously required. However, also non-microbial environmental and host factors play a key role in the onset, development and outcome of infectious disease, resulting in large of clinical variability between individuals in a population infected with the same microbe. Controlled and standardized investigations of the genetics of susceptibility to infectious disease are almost impossible to perform in humans whereas mouse models allow application of powerful genomic techniques to identify and validate causative genes underlying human diseases with complex etiologies. Most of current animal models used in complex traits diseases genetic mapping have limited genetic diversity. This limitation impedes the ability to create incorporated network using genetic interactions, epigenetics, environmental factors, microbiota, and other phenotypes. A novel mouse genetic reference population for high-resolution mapping and subsequently identifying genes underlying the QTL, namely the Collaborative Cross (CC) mouse genetic reference population (GRP) was recently developed. In this chapter, we discuss a variety of approaches using CC mice for mapping genes underlying quantitative trait loci (QTL) to dissect the host response to polygenic traits, including infectious disease caused by bacterial agents and its toxins.

Application of Mouse Models to Research in Hearing and Balance

Laboratory mice (Mus musculus) have become the major model species for inner ear research. The major uses of mice include gene discovery, characterization, and confirmation. Every application of mice is founded on assumptions about what mice represent and how the information gained may be generalized. A host of successes support the continued use of mice to understand hearing and balance. Depending on the research question, however, some mouse models and research designs will be more appropriate than others. Here, we recount some of the history and successes of the use of mice in hearing and vestibular studies and offer guidelines to those considering how to apply mouse models.

Genome Sequencing of Chromosome 1 Substitution Lines Derived from Chinese Wild Mice Revealed a Unique Resource for Genetic Studies of Complex Traits

Mouse resources such as Collaborative Cross, outbred stocks, Hybrid Mouse Diversity Panel, and chromosome substitution strains have been instrumental to many progresses in the studies of complex traits genetics. We have established a population of chromosome 1 (Chr 1) substitution lines (C1SLs) in which donor chromosomes were derived from Chinese wild mice. Genome sequencing of 18 lines of this population showed that Chr 1 had been replaced by the donor chromosome. About 4.5 million unique single nucleotide polymorphisms and indels were discovered on Chr 1, of which 1.3 million were novel. Compared with sequenced classical inbred strains, Chr 1 of each C1SL had fivefold more variants, and more loss of function and potentially regulatory variants. Further haplotype analysis showed that the donor chromosome accumulated more historical recombination events, with the largest haplotype block being only 100 kb, and about 57% of the blocks were <1 kb. Subspecies origin analysis showed that these chromosomes had a mosaic genome structure that dominantly originated from Mus musculus musculus and M. m. castaneus subspecies, except for the C57BL/6J-Chr1^KM line from M. m. domesticus. In addition, phenotyping four of these lines on blood biochemistry suggested that there were substantial phenotypic variations among our lines, especially line C57BL/6J-Chr1^HZ and donor strain C57BL/6J. Further gene ontology enrichment revealed that the differentially expressed genes among liver-expressed genes between C57BL/6J and C57BL/6J-Chr1^HZ were enriched in lipid metabolism biological processes. All these characteristics enable C1SLs to be a unique resource for identifying and fine mapping quantitative trait loci on mouse Chr 1, and carrying out systems genetics studies of complex traits.

Association of physical performance and biochemical profile of mice with intrinsic endurance swimming

We aimed to investigate the potential mediators and relationship affecting congenital exercise performance in an animal model with physical activity challenge from physiological and biochemical perspectives. A total of 75 male ICR mice (5 weeks old) were adapted for 1 week, then mice performed a non-loading and exhaustive swimming test and were assigned to 3 groups by exhaustive swimming time: low exercise capacity (LEC) (<3 hr), medium exercise capacity (MEC) (3-5 hr), and high exercise capacity (HEC) (>5 hr). After a 1-week rest, the 3 groups of mice performed an exhaustive swimming test with a 5% and 7.5% weight load and a forelimb grip-strength test, with a 1-week rest between tests. Blood samples were collected immediately after an acute exercise challenge and at the end of the experiment (resting status) to evaluate biochemical blood variables and their relation with physical performance. Physical activity, including exhaustive swimming and grip strength, was greater for HEC than other mice. The swimming performance and grip strength between groups were moderately correlated (r=0.443, p<0.05). Resting serum ammonium level was moderately correlated with endurance with a 7.5% weight load (r=-0.447, p<0.05) and with lactate level (r=0.598, p<0.05). The pulmonary morphology of the HEC group seemed to indicate benefits for aerobic exercise. Mice showed congenital exercise performance, which was significantly correlated with different physical challenges and biochemical variable values. This study may have implications for interference in intrinsic characteristics.

Strain differences in temporal changes of nesting behaviors in C57BL/6N, DBA/2N, and their F1 hybrid mice assessed by a three-dimensional monitoring system

Nest building is one of the innate behaviors that are widely observed throughout the animal kingdom. Previous studies have reported specific brain regions and genetic loci associated with nest building in mice. These studies mainly evaluated the nest structure, without observing the nesting process. In this study, we evaluated the effects of strain and learning on the nesting process of mice using a 3D depth camera. To determine the quality of the nest structure, a conventional scoring method, Deacon scores 1-5, was applied to the recorded depth images. The final score of the nest, latency to start nesting behavior, and latencies to reach Deacon scores 3-5, were determined using three genetically different mouse strains-C57BL/6NCrl (B6), DBA/2NCrlCrlj (DBA), and B6D2F1/Crl (B6D2F1). The final score of the DBA nest was significantly lower than that of the B6D2F1 nest, and DBA mice showed significantly longer latency to start nest building than the other two strains in the first trial. By observing the time course of nest building, we confirmed that DBA mice took significantly longer to build their nests than B6 and B6D2F1 mice. Although we did not find any significant differences between DBA and B6 mice in the final assessment of the nest based on the Deacon method, overnight monitoring of the nesting behavior using a 3D depth camera could elucidate the clear differences in the amount of time spent nesting between DBA and B6 mice. In addition, the learning effect was more evident in DBA mice than it was in B6 in terms of latencies to reach Deacon score 3-5 in five repeated trials. DBA mice showed a gradual decrease in latency to build, whereas nesting behaviors of B6 mice were relatively consistent throughout the five trials. Therefore, our 3D depth image method gives higher resolution and structural information regarding the nesting process in mice. Future genetic analyses using the 3D assessment system will provide novel insights into the complex genetic basis for nesting and other behaviors in animals.

Contrasting genetic architectures in different mouse reference populations used for studying complex traits

Quantitative trait loci (QTLs) are being used to study genetic networks, protein functions, and systems properties that underlie phenotypic variation and disease risk in humans, model organisms, agricultural species, and natural populations. The challenges are many, beginning with the seemingly simple tasks of mapping QTLs and identifying their underlying genetic determinants. Various specialized resources have been developed to study complex traits in many model organisms. In the mouse, remarkably different pictures of genetic architectures are emerging. Chromosome Substitution Strains (CSSs) reveal many QTLs, large phenotypic effects, pervasive epistasis, and readily identified genetic variants. In contrast, other resources as well as genome-wide association studies (GWAS) in humans and other species reveal genetic architectures dominated with a relatively modest number of QTLs that have small individual and combined phenotypic effects. These contrasting architectures are the result of intrinsic differences in the study designs underlying different resources. The CSSs examine context-dependent phenotypic effects independently among individual genotypes, whereas with GWAS and other mouse resources, the average effect of each QTL is assessed among many individuals with heterogeneous genetic backgrounds. We argue that variation of genetic architectures among individuals is as important as population averages. Each of these important resources has particular merits and specific applications for these individual and population perspectives. Collectively, these resources together with high-throughput genotyping, sequencing and genetic engineering technologies, and information repositories highlight the power of the mouse for genetic, functional, and systems studies of complex traits and disease models.

Identification of structural variation in mouse genomes

Structural variation is variation in structure of DNA regions affecting DNA sequence length and/or orientation. It generally includes deletions, insertions, copy-number gains, inversions, and transposable elements. Traditionally, the identification of structural variation in genomes has been challenging. However, with the recent advances in high-throughput DNA sequencing and paired-end mapping (PEM) methods, the ability to identify structural variation and their respective association to human diseases has improved considerably. In this review, we describe our current knowledge of structural variation in the mouse, one of the prime model systems for studying human diseases and mammalian biology. We further present the evolutionary implications of structural variation on transposable elements. We conclude with future directions on the study of structural variation in mouse genomes that will increase our understanding of molecular architecture and functional consequences of structural variation.

The Collaborative Cross as a resource for modeling human disease: CC011/Unc, a new mouse model for spontaneous colitis

Inflammatory bowel disease (IBD) is an immune-mediated condition driven by improper responses to intestinal microflora in the context of environmental and genetic background. GWAS in humans have identified many loci associated with IBD, but animal models are valuable for dissecting the underlying molecular mechanisms, characterizing environmental and genetic contributions and developing treatments. Mouse models rely on interventions such as chemical treatment or introduction of an infectious agent to induce disease. Here, we describe a new model for IBD in which the disease develops spontaneously in 20-week-old mice in the absence of known murine pathogens. The model is part of the Collaborative Cross and came to our attention due to a high incidence of rectal prolapse in an incompletely inbred line. Necropsies revealed a profound proliferative colitis with variable degrees of ulceration and vasculitis, splenomegaly and enlarged mesenteric lymph nodes with no discernible anomalies of other organ systems. Phenotypic characterization of the CC011/Unc mice with homozygosity ranging from 94.1 to 99.8% suggested that the trait was fixed and acted recessively in crosses to the colitis-resistant C57BL/6J inbred strain. Using a QTL approach, we identified four loci, Ccc1, Ccc2, Ccc3 and Ccc4 on chromosomes 12, 14, 1 and 8 that collectively explain 27.7% of the phenotypic variation. Surprisingly, we also found that minute levels of residual heterozygosity in CC011/Unc have significant impact on the phenotype. This work demonstrates the utility of the CC as a source of models of human disease that arises through new combinations of alleles at susceptibility loci.

The genetics of gene expression in complex mouse crosses as a tool to study the molecular underpinnings of behavior traits

Complex Mus musculus crosses provide increased resolution to examine the relationships between gene expression and behavior. While the advantages are clear, there are numerous analytical and technological concerns that arise from the increased genetic complexity that must be considered. Each of these issues is discussed, providing an initial framework for complex cross study design and planning.

QTL mapping in outbred populations: successes and challenges

Quantitative trait locus (QTL) mapping in animal populations has been a successful strategy for identifying genomic regions that play a role in complex diseases and traits. When conducted in an F2 intercross or backcross population, the resulting QTL is frequently large, often encompassing 30 Mb or more and containing hundreds of genes. To narrow the locus and identify candidate genes, additional strategies are needed. Congenic strains have proven useful but work less well when there are multiple tightly linked loci, frequently resulting in loss of phenotype. As an alternative, we discuss the use of highly recombinant outbred models for directly fine-mapping QTL to only a few megabases. We discuss the use of several currently available models such as the advanced intercross (AI), heterogeneous stocks (HS), the diversity outbred (DO), and commercially available outbred stocks (CO). Once a QTL has been fine-mapped, founder sequence and expression QTL mapping can be used to identify candidate genes. In this regard, the large number of alleles found in outbred stocks can be leveraged to identify causative genes and variants. We end this review by discussing some important statistical considerations when analyzing outbred populations. Fine-resolution mapping in outbred models, coupled with full genome sequence, has already led to the identification of several underlying causative genes for many complex traits and diseases. These resources will likely lead to additional successes in the coming years.

Out of the bottleneck: the Diversity Outcross and Collaborative Cross mouse populations in behavioral genetics research

The historical origins of classical laboratory mouse strains have led to a relatively limited range of genetic and phenotypic variation, particularly for the study of behavior. Many recent efforts have resulted in improved diversity and precision of mouse genetic resources for behavioral research, including the Collaborative Cross and Diversity Outcross population. These two populations, derived from an eight way cross of common and wild-derived strains, have high precision and allelic diversity. Behavioral variation in the population is expanded, both qualitatively and quantitatively. Variation that had once been canalized among the various inbred lines has been made amenable to genetic dissection. The genetic attributes of these complementary populations, along with advances in genetic and genomic technologies, makes a systems genetic analyses of behavior more readily tractable, enabling discovery of a greater range of neurobiological phenomena underlying behavioral variation.

Next-generation sequencing of experimental mouse strains

Since the turn of the century the complete genome sequence of just one mouse strain, C57BL/6J, has been available. Knowing the sequence of this strain has enabled large-scale forward genetic screens to be performed, the creation of an almost complete set of embryonic stem (ES) cell lines with targeted alleles for protein-coding genes, and the generation of a rich catalog of mouse genomic variation. However, many experiments that use other common laboratory mouse strains have been hindered by a lack of whole-genome sequence data for these strains. The last 5 years has witnessed a revolution in DNA sequencing technologies. Recently, these technologies have been used to expand the repertoire of fully sequenced mouse genomes. In this article we review the main findings of these studies and discuss how the sequence of mouse genomes is helping pave the way from sequence to phenotype. Finally, we discuss the prospects for using de novo assembly techniques to obtain high-quality assembled genome sequences of these laboratory mouse strains, and what advances in sequencing technologies may be required to achieve this goal.