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A wide range of viruses cause neurological manifestations in their hosts. Infection by neurotropic viruses as well as the resulting immune response can irreversibly disrupt the complex structural and functional architecture of the brain, depending in part on host genetic background. The interaction between host genetic background, neurological response to viral infection, and subsequent clinical manifestations remains poorly understood. In the present study, we used the genetically diverse Collaborative Cross (CC) mouse resource to better understand how differences in genetic background drive clinical signs and neuropathological manifestations of acute Theiler’s murine encephalomyelitis virus (TMEV) infection. For the first time, we characterized variations of TMEV viral tropism and load based on host genetic background, and correlated viral load with microglial/macrophage activation. For five CC strains (CC002, CC023, CC027, CC057, and CC078) infected with TMEV, we compared clinical signs, lesion distribution, microglial/macrophage response, expression, and distribution of TMEV mRNA, and identified genetic loci relevant to the early acute (4 days post-infection [dpi]) and late acute (14 dpi) timepoints. We examined brain pathology to determine possible causes of strain-specific differences in clinical signs, and found that fields CA1 and CA2 of the hippocampal formation were especially targeted by TMEV across all strains. Using Iba-1 immunolabeling, we identified and characterized strain- and timepoint-specific variation in microglial/macrophage reactivity in the hippocampal formation. Because viral clearance can influence disease outcome, we used RNA in situ hybridization to quantify viral load and TMEV mRNA distribution at both timepoints. TMEV mRNA expression was broadly distributed in the hippocampal formation at 4 dpi in all strains but varied between radiating and clustered distribution depending on the CC strain. We found a positive correlation between microglial/macrophage reactivity and TMEV mRNA expression at 4 dpi. At 14 dpi, we observed a dramatic reduction in TMEV mRNA expression, and localization to the medial portion of field CA1 and field CA2. To better understand how host genetic background can influence pathological outcomes, we identified quantitative trait loci associated with frequency of lesions in a particular brain region and with microglial/macrophage reactivity. These QTL were located near several loci of interest: lysosomal trafficking regulator (Lyst) and nidogen 1 (Nid1), and transmembrane protein 106 B (Tmem106b). Together, these results provide a novel understanding about the influences of genetic variation on the acute neuropathological and immunopathological environment and viral load, which collectively lead to variable disease outcomes. Our findings reveal possible avenues for future investigation which may lead to more effective intervention strategies and treatment regimens.

The outcome of an encounter withMycobacterium tuberculosis(Mtb) depends on the pathogen’s ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library ofMtbmutants to create a resource for associating bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis ofMtbtransposon mutant fitness (TnSeq) across the CC panel revealed that many virulence pathways are only required in specific host microenvironments, identifying a large fraction of the pathogen’s genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits can be associated with genetic variants distributed across the mouse genome, making the CC a unique population for identifying specific host-pathogen genetic interactions that influence pathogenesis.

The dysregulation of microRNA (miRNA) is implicated in cancer, inflammation, cardiovascular disorders, drug resistance, and aging. While most researchers study miRNA’s role as a biomarker, for example, to distinguish between various sub-forms or stages of a given disease of interest, research is also ongoing to utilize these small nucleic acids as therapeutics. An example of a common pleiotropic disease that could benefit from miRNA-based therapeutics is inflammatory bowel disease (IBD), which is characterized by chronic inflammation of the small and large intestines. Due to complex interactions between multiple factors in the etiology of IBD, development of therapies that effectively maintain remission for this disease is a significant challenge. In this review, we discuss the role of dysregulated miRNA expression in the context of clinical ulcerative colitis (UC) and Crohn’s disease (CD)—the two main forms of IBD—and the various preclinical mouse models of IBD utilized to validate the therapeutic potential of targeting these miRNA. Additionally, we highlight advances in the development of genetically engineered animal models that recapitulate clinical miRNA expression and provide powerful preclinical models to assess the diagnostic and therapeutic promise of miRNA in IBD.

Background Virus infections result in a range of clinical outcomes for the host, from asymptomatic to severe or even lethal disease. Despite global efforts to prevent and treat virus infections to limit morbidity and mortality, the continued emergence and re-emergence of new outbreaks as well as common infections such as influenza persist as a health threat. Challenges to the prevention of severe disease after virus infection include both a paucity of protective vaccines as well as the early identification of individuals with the highest risk that may require supportive treatment. Methods We completed a screen of mice from the Collaborative Cross (CC) that we infected with influenza, severe acute respiratory syndrome-coronavirus, and West Nile virus. Results The CC mice exhibited a range of disease manifestations upon infections, and we used this natural variation to identify strains with mortality after infection and strains exhibiting no mortality. We then used comprehensive preinfection immunophenotyping to identify global baseline immune correlates of protection from mortality to virus infection. Conclusions These data suggest that immune phenotypes might be leveraged to identify humans at highest risk of adverse clinical outcomes upon infection, who may most benefit from intensive clinical interventions, in addition to providing insight for rational vaccine design., We used a screen of genetically diverse mice from the Collaborative Cross infected with RNA viruses in combination with comprehensive preinfection immunophenotyping to identify baseline immune correlates of protection from mortality to virus infection.

Specific fat distributions are risk factors for complex diseases, including coronary heart disease and obstructive sleep apnea. To demonstrate the utility of high-diversity mouse models for elucidating genetic associations, we describe the phenotyping and heritability of fat distributions within the five classical inbred and three wild-derived founder mouse strains of the Collaborative Cross and Diversity Outbred mice. Measurements of subcutaneous and internal fat volumes in the abdomen, thorax and neck, and fat volumes in the tongue and pericardium were obtained using magnetic resonance imaging in male mice from the A/J (n = 12), C57BL/6J (n = 17), 129S1/SvlmJ (n = 12), NOD/LtJ (n = 14), NZO/HILtJ (n = 12), CAST/EiJ (n = 14), PWK/PhJ (n = 12), and WSB/EiJ (n = 15) strains. Phenotypes were compared across strains using analysis of variance and heritability estimated as the proportion of phenotypic variability attributable to strain. Heritability ranged from 44 to 91% across traits, including >70% heritability of tongue fat. A majority of heritability estimates remained significant controlling for body weight, suggesting genetic influences independent of general obesity. Principal components analysis supports genetic influences on overall obesity and specific to increased pericardial and intra-neck fat. Thus, among the founder strains of the Collaborative Cross and Diversity Outbred mice, we observed significant heritability of subcutaneous and internal fat volumes in the neck, thorax and abdomen, pericardial fat volume and tongue fat volume, consistent with genetic architecture playing an important role in explaining trait variability. Findings pave the way for studies utilizing high-diversity mouse models to identify genes affecting fat distributions and, in turn, influencing risk for associated complex disorders.

International audience; Natural Killer (NK) cells are innate effectors armed with cytotoxic and cytokine-secreting capacities whose spontaneous anti-tumor activity is key to numerous immunotherapeutic strategies. However, current mouse models fail to mirror the extensive human immune system variation that exists in the normal population which may impact on NK cell-based therapies. We performed a comprehensive profiling of NK cells in the Collaborative Cross (CC), a collection of novel recombinant inbred mouse strains whose genetic diversity matches that of humans, thereby providing a unique and highly diverse small animal model for the study of immune variation. We demonstrate that NK cells from CC lines displayed a breadth of phenotypic and functional variation reminiscent of that reported for humans with regards to cell numbers, key marker expression and functional capacities. We took advantage of the vast genetic diversity of the CC and identified 9 genomic loci through quantitative trait locus mapping driving these phenotypic variations. SNP haplotype-patterns and variant effect analyses identified candidate genes associated with lung NK cell numbers, frequencies of CD94+NK cells, and expression levels of NKp46. Thus, we demonstrate that the CC represents an outstanding resource to study NK cell diversity and its regulation by hostgenetics.

Background Familial adenomatous polyposis is an inherited genetic disease, characterized by colorectal polyps. It is caused by inactivating mutations in the Adenomatous polyposis coli (Apc) gene. Mice carrying a nonsense mutation in the Apc gene at R850, which is designated ApcMin/+ (Multiple intestinal neoplasia), develop intestinal adenomas. Several genetic modifier loci of Min (Mom) were previously mapped, but so far, most of the underlying genes have not been identified. To identify novel modifier loci associated with ApcMin/+, we performed quantitative trait loci (QTL) analysis for polyp development using 49 F1 crosses between different Collaborative Cross (CC) lines and C57BL/6 J-ApcMin/+mice. The CC population is a genetic reference panel of recombinant inbred lines, each line independently descended from eight genetically diverse founder strains. C57BL/6 J-ApcMin/+ males were mated with females from 49 CC lines. F1 offspring were terminated at 23 weeks and polyp counts from three sub-regions (SB1–3) of small intestinal and colon were recorded. Results The number of polyps in all these sub-regions and colon varied significantly between the different CC lines. At 95% genome-wide significance, we mapped nine novel QTL for variation in polyp number, with distinct QTL associated with each intestinal sub-region. QTL confidence intervals varied in width between 2.63–17.79 Mb. We extracted all genes in the mapped QTL at 90 and 95% CI levels using the BioInfoMiner online platform to extract, significantly enriched pathways and key linker genes, that act as regulatory and orchestrators of the phenotypic landscape associated with the ApcMin/+ mutation. Conclusions Genomic structure of the CC lines has allowed us to identify novel modifiers and confirmed some of the previously mapped modifiers. Key genes involved mainly in metabolic and immunological processes were identified. Future steps in this analysis will be to identify regulatory elements – and possible epistatic effects – located in the mapped QTL. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07890-x.

The COVID-19 pandemic has revealed that infection with SARS-CoV-2 can result in a wide range of clinical outcomes in humans, from asymptomatic or mild disease to severe disease that can require mechanical ventilation. An incomplete understanding of immune correlates of protection represents a major barrier to the design of vaccines and therapeutic approaches to prevent infection or limit disease. This deficit is largely due to the lack of prospectively collected, pre-infection samples from indiviuals that go on to become infected with SARS-CoV-2. Here, we utilized data from a screen of genetically diverse mice from the Collaborative Cross (CC) infected with SARS-CoV to determine whether circulating baseline T cell signatures are associated with a lack of viral control and severe disease upon infection. SARS-CoV infection of CC mice results in a variety of viral load trajectories and disease outcomes. Further, early control of virus in the lung correlates with an increased abundance of activated CD4 and CD8 T cells and regulatory T cells prior to infections across strains. A basal propensity of T cells to express IFNg and IL17 over TNFa also correlated with early viral control. Overall, a dysregulated, pro-inflammatory signature of circulating T cells at baseline was associated with severe disease upon infection. While future studies of human samples prior to infection with SARS-CoV-2 are required, our studies in mice with SARS-CoV serve as proof of concept that circulating T cell signatures at baseline can predict clinical and virologic outcomes upon SARS-CoV infection. Identification of basal immune predictors in humans could allow for identification of individuals at highest risk of severe clinical and virologic outcomes upon infection, who may thus most benefit from available clinical interventions to restrict infection and disease., Summary. We used a screen of genetically diverse mice from the Collaborative Cross infected with mouse-adapted SARS-CoV in combination with comprehensive pre-infection immunophenotyping to identify baseline circulating immune correlates of severe virologic and clinical outcomes upon SARS-CoV infection.

Background: The Collaborative Cross (CC) mouse population is a valuable resource to study the genetic basis of complex traits, such as obesity. Although the development of obesity is influenced by environmental factors, underlying genetic mechanisms play a crucial role in the response to these factors. The interplay between the genetic background and the gene expression pattern can provide further insight into this response, but we lack robust and easily reproducible workflows to integrate genomic and transcriptomic information in the CC mouse population. Results: We established an automated and reproducible integrative workflow to analyse complex traits in the CC mouse genetic reference panel at the genomic and transcriptomic levels. We implemented the analytical workflow to assess the underlying genetic mechanisms of host susceptibility to diet induced obesity and integrated these results with diet induced changes in the hepatic gene expression of susceptible and resistant mice. Hepatic gene expression differs significantly between obese and non-obese mice, with a significant sex effect, where male and female mice exhibit different responses and coping mechanisms. Conclusion: Integration of the data showed that different genes but similar pathways are involved in the genetic susceptibility and disturbed in diet induced obesity. Genetic mechanisms underlying susceptibility to high-fat diet induced obesity are different in female and male mice. The clear distinction we observed in the systemic response to the high-fat diet challenge and to obesity between male and female mice points to the need for further research into distinct sex-related mechanisms in metabolic disease. This work was funded by the Operational Program ”Competitiveness, Entrepreneurship and Innovation 2014–2020″ (co-funded by the European Regional Development Fund) and managed by the General Secretariat of Research and Technology, Ministry Of Education, Research & Religious Affairs, under the project” Innovative Nanopharmaceuticals: Targeting Breast CancerStem Cells by a Novel Combination of Epigenetic and Anticancer Drugs with Gene Therapy (INNOCENT)” (7th Joint Translational Call - 2016, European Innovative Research and Technological Development Projects In Nanomedicine) of the ERA-NET EuroNanoMed II and by “BioS: Digital Skills on Computational Biology”, ΕRASMUS+, EACEA/04/2017, “KA2: Cooperation for innovation and the exchange of good practices - Sector Skills Alliances” for the development of the bioinformatic analysis pipeline, Hendrech and Eiran Gotwert Fund for studying diabetes, Wellcome Trust grants 085906/Z/ 08/Z, 075491/Z/04 and 090532/Z/09/Z; for financially supporting the initiation, breeding, genotyping and maintaining the CC mouse colony at TAU, core funding by Tel-Aviv University (TAU) for supporting staff at Iraqi’s lab, Israeli Science foundation (ISF) grants 429/09 and 1085/18, Binational Science Foundation (BSF) grant number 2015077 and German Israeli Science Foundation (GIF) grant I-63-410.20-2017 for performing the mouse assessment for T2D and technical staff, and European Sequencing and Genotyping Infrastructure (ESGI) consortium grant for conducting the RNAseq analysis.Ilona Binenbaum’s PhD thesis was supported by a scholarship from the State Scholarship Foundation in Greece (IKY) (Operational Program “Human Resources Development - Education and Lifelong Learning” Partnership Agreement (PA) 2014–2020)

The laboratory mouse has proved an invaluable model to identify host factors that regulate the progression and outcome of virus-induced disease. The paradigm is to use single-gene knockouts in inbred mouse strains or genetic mapping studies using biparental mouse populations. However, genetic variation among these mouse strains is limited compared with the diversity seen in human populations. To address this disconnect, a multiparental mouse population has been developed to specifically dissect the multigenetic regulation of complex disease traits. The Collaborative Cross (CC) population of recombinant inbred mouse strains is a well-suited systems-genetics tool to identify susceptibility alleles that control viral and microbial infection outcomes and immune responses and to test the promise of personalized medicine., Highlights Viral infections are complex traits that are influenced by viral and environmental as well as host factors. Complete knockouts of genes are rare in humans whereas natural variation at the nucleotide level is abundant. Thus, successful translation from mice to humans is more likely working with natural variation in mouse populations. The Collaborative Cross is a mouse genetic reference population that is well suited to be utilized to identify networks of host genetics key players that influence complex traits such as viral infections. Indefinitely reproducible mouse strains with fully sequenced genomes offer the chance for wide collaborations across pathogens. Additionally, it offers the ability to identify cross-pathogen susceptibility or resistance alleles.

ObjectiveThe Collaborative Cross (CC) is a mouse population model with diverse and reproducible genetic backgrounds used to identify novel disease models and genes that contribute to human disease. Since spontaneous tumour susceptibility in CC mice remains unexplored, we assessed tumour incidence and spectrum.DesignWe monitored 293 mice from 18 CC strains for tumour development. Genetic association analysis and RNA sequencing were used to identify susceptibility loci and candidate genes. We analysed genomes of patients with gastric cancer to evaluate the relevance of genes identified in the CC mouse model and measured the expression levels of ISG15 by immunohistochemical staining using a gastric adenocarcinoma tissue microarray. Association of gene expression with overall survival (OS) was assessed by Kaplan-Meier analysis.ResultsCC mice displayed a wide range in the incidence and types of spontaneous tumours. More than 40% of CC036 mice developed gastric tumours within 1 year. Genetic association analysis identified Nfκb1 as a candidate susceptibility gene, while RNA sequencing analysis of non-tumour gastric tissues from CC036 mice showed significantly higher expression of inflammatory response genes. In human gastric cancers, the majority of human orthologues of the 166 mouse genes were preferentially altered by amplification or deletion and were significantly associated with OS. Higher expression of the CC036 inflammatory response gene signature is associated with poor OS. Finally, ISG15 protein is elevated in gastric adenocarcinomas and correlated with shortened patient OS.ConclusionsCC strains exhibit tremendous variation in tumour susceptibility, and we present CC036 as a spontaneous laboratory mouse model for studying human gastric tumourigenesis.

Virus-induced neurological sequelae resulting from infection by Theiler’s murine encephalomyelitis virus (TMEV) are used for studying human conditions ranging from epileptic seizures to demyelinating disease. Mouse strains are typically considered susceptible or resistant to TMEV infection based on viral persistence and extreme phenotypes, such as demyelination. We have identified a broader spectrum of phenotypic outcomes by infecting strains of the genetically diverse Collaborative Cross (CC) mouse resource. We evaluated the chronic-infection gene expression profiles of hippocampi and thoracic spinal cords for 19 CC strains in relation to phenotypic severity and TMEV persistence. Strains were clustered based on similar phenotypic profiles and TMEV levels at 90 days post-infection, and we categorized distinct TMEV response profiles. The three most common profiles included “resistant” and “susceptible,” as before, as well as a “resilient” TMEV response group which experienced both TMEV persistence and mild neurological phenotypes even at 90 days post-infection. Each profile had a distinct gene expression signature, allowing the identification of pathways and networks specific to each TMEV response group. CC founder haplotypes for genes involved in these pathways/networks revealed candidate response-specific alleles. These alleles demonstrated pleiotropy and epigenetic (miRNA) regulation in long-term TMEV infection, with particular relevance for resilient mouse strains.

The Collaborative Cross (CC) is a panel of recently established multiparental recombinant inbred mouse strains. For the CC, as for any multiparental population (MPP), effective experimental design and analysis benefit from detailed knowledge of the genetic differences between strains. Such differences can be directly determined by sequencing, but until now whole-genome sequencing was not publicly available for individual CC strains. An alternative and complementary approach is to infer genetic differences by combining two pieces of information: probabilistic estimates of the CC haplotype mosaic from a custom genotyping array, and probabilistic variant calls from sequencing of the CC founders. The computation for this inference, especially when performed genome-wide, can be intricate and time-consuming, requiring the researcher to generate nontrivial and potentially error-prone scripts. To provide standardized, easy-to-access CC sequence information, we have developed the Inbred Strain Variant Database (ISVdb). The ISVdb provides, for all the exonic variants from the Sanger Institute mouse sequencing dataset, direct sequence information for CC founders and, critically, the imputed sequence information for CC strains. Notably, the ISVdb also: (1) provides predicted variant consequence metadata; (2) allows rapid simulation of F1 populations; and (3) preserves imputation uncertainty, which will allow imputed data to be refined in the future as additional sequencing and genotyping data are collected. The ISVdb information is housed in an SQL database and is easily accessible through a custom online interface (http://isvdb.unc.edu), reducing the analytic burden on any researcher using the CC.

Host genetic variation has a major impact on infectious disease susceptibility. The study of pathogen resistance genes, largely aided by mouse models, has significantly advanced our understanding of infectious disease pathogenesis. The Collaborative Cross (CC), a newly developed multi-parental mouse genetic reference population, serves as a tractable model system to study how pathogens interact with genetically diverse populations. In this review, we summarize progress utilizing the CC as a platform to develop improved models of pathogen-induced disease and to map polymorphic host response loci associated with variation in susceptibility to pathogens., Host genetic variation plays an important role in shaping infectious disease susceptibility. Noll et al. review the application of a genetically diverse mouse reference population, the Collaborative Cross, to study variation in disease response across multiple pathogens, highlighting advances in model development and genetic mapping.

An increasing body of evidence highlights the role of host genetic variation in driving susceptibility to severe disease following pathogen infection. In order to fully appreciate the importance of host genetics on infection susceptibility and resulting disease, genetically variable experimental model systems should be employed. These systems allow for the identification, characterization, and mechanistic dissection of genetic variants that cause differential disease responses. Herein we discuss application of the Collaborative Cross (CC) panel of recombinant inbred strains to study viral pathogenesis, focusing on practical considerations for experimental design, assessment and analysis of disease responses within the CC, as well as some of the resources developed for the CC. Although the focus of this chapter is on viral pathogenesis, many of the methods presented within are applicable to studies of other pathogens, as well as to case-control designs in genetically diverse populations.

R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely-used R/qtl software package to include multiparental populations, better handles modern high-dimensional data...., R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely used R/qtl software package to include multiparent populations derived from more than two founder strains, such as the Collaborative Cross and Diversity Outbred mice, heterogeneous stocks, and MAGIC plant populations. R/qtl2 is designed to handle modern high-density genotyping data and high-dimensional molecular phenotypes, including gene expression and proteomics. R/qtl2 includes the ability to perform genome scans using a linear mixed model to account for population structure, and also includes features to impute SNPs based on founder strain genomes and to carry out association mapping. The R/qtl2 software provides all of the basic features needed for QTL mapping, including graphical displays and summary reports, and it can be extended through the creation of add-on packages. R/qtl2, which is free and open source software written in the R and C++ programming languages, comes with a test framework.

Multi-parental recombinant inbred populations, such as the Collaborative Cross (CC) mouse genetic reference population, are increasingly being used for analysis of quantitative trait loci (QTL). However specialized analytic software for these complex populations is typically built in R that works only on command-line, which limits the utility of these powerful resources for many users. To overcome analytic limitations, we developed gQTL, a web accessible, simple graphical user interface application based on the DOQTL platform in R to perform QTL mapping using data from CC mice.

Commensals are important for the proper functioning of multicellular organisms. How a commensal establishes persistent colonization of its host is little understood. Studies of this aspect of microbe-host interactions are impeded by the absence of an animal model. We have developed a natural small animal model for identifying host and commensal determinants of colonization and of the elusive process of persistence. Our system couples a commensal bacterium of wild mice, Neisseria musculi , with the laboratory mouse. The pairing of a mouse commensal with its natural host circumvents issues of host restriction. Studies are performed in the absence of antibiotics, hormones, invasive procedures, or genetic manipulation of the host. A single dose of N. musculi , administered orally, leads to long-term colonization of the oral cavity and gut. All mice are healthy. Susceptibility to colonization is determined by host genetics and innate immunity. For N. musculi , colonization requires the type IV pilus. Reagents and powerful tools are readily available for manipulating the laboratory mouse, allowing easy dissection of host determinants controlling colonization resistance. N. musculi is genetically related to human-dwelling commensal and pathogenic Neisseria and encodes host interaction factors and vaccine antigens of pathogenic Neisseria . Our system provides a natural approach for studying Neisseria -host interactions and is potentially useful for vaccine efficacy studies.

Periodontitis is one of the most common inflammatory human diseases with a strong genetic component. Due to the limited sample size of available periodontitis cohorts and the underlying trait heterogeneity, genome-wide association studies (GWASs) of chronic periodontitis (CP) have largely been unsuccessful in identifying common susceptibility factors. A combination of quantitative trait loci (QTL) mapping in mice with association studies in humans has the potential to discover novel risk loci. To this end, we assessed alveolar bone loss in response to experimental periodontal infection in 25 lines (286 mice) from the Collaborative Cross (CC) mouse population using micro-computed tomography (µCT) analysis. The orthologous human chromosomal regions of the significant QTL were analyzed for association using imputed genotype data (OmniExpress BeadChip arrays) derived from case-control samples of aggressive periodontitis (AgP; 896 cases, 7,104 controls) and chronic periodontitis (CP; 2,746 cases, 1,864 controls) of northwest European and European American descent, respectively. In the mouse genome, QTL mapping revealed 2 significant loci (-log P = 5.3; false discovery rate = 0.06) on chromosomes 1 ( Perio3) and 14 ( Perio4). The mapping resolution ranged from ~1.5 to 3 Mb. Perio3 overlaps with a previously reported QTL associated with residual bone volume in F2 cross and includes the murine gene Ccdc121. Its human orthologue showed previously a nominal significant association with CP in humans. Use of variation data from the genomes of the CC founder strains further refined the QTL and suggested 7 candidate genes ( CAPN8, DUSP23, PCDH17, SNORA17, PCDH9, LECT1, and LECT2). We found no evidence of association of these candidates with the human orthologues. In conclusion, the CC populations enabled mapping of confined QTL that confer susceptibility to alveolar bone loss in mice and larger human phenotype-genotype samples and additional expression data from gingival tissues are likely required to identify true positive signals.

Significance How species differ from each other is a key question in biology. However, genetic mapping between species often fails because of sterile hybrid crosses. Here, we have developed a technique called in vitro recombination to circumvent breeding. We induced genetic reshuffling through mitotic recombination with the drug ML216 and mapped trait variations in a dish. Starting with hybrid embryonic stem cells between the Mus musculus laboratory mouse and Mus spretus spanning ∼1.5 million years of divergence, we show that it is possible to map the gene responsible for differential resistance to the drug tioguanine in as few as 21 days. Our technique opens up experimental avenues in genetic mapping of various traits and diseases across mouse species., Discovering the genetic changes underlying species differences is a central goal in evolutionary genetics. However, hybrid crosses between species in mammals often suffer from hybrid sterility, greatly complicating genetic mapping of trait variation across species. Here, we describe a simple, robust, and transgene-free technique to generate “in vitro crosses” in hybrid mouse embryonic stem (ES) cells by inducing random mitotic cross-overs with the drug ML216, which inhibits the DNA helicase Bloom syndrome (BLM). Starting with an interspecific F1 hybrid ES cell line between the Mus musculus laboratory mouse and Mus spretus (∼1.5 million years of divergence), we mapped the genetic basis of drug resistance to the antimetabolite tioguanine to a single region containing hypoxanthine–guanine phosphoribosyltransferase (Hprt) in as few as 21 d through “flow mapping” by coupling in vitro crosses with fluorescence-activated cell sorting (FACS). We also show how our platform can enable direct study of developmental variation by rederiving embryos with contribution from the recombinant ES cell lines. We demonstrate how in vitro crosses can overcome major bottlenecks in mouse complex trait genetics and address fundamental questions in evolutionary biology that are otherwise intractable through traditional breeding due to high cost, small litter sizes, and/or hybrid sterility. In doing so, we describe an experimental platform toward studying evolutionary systems biology in mouse and potentially in human and other mammals, including cross-species hybrids.

Surveys of inbred strains of mice are standard approaches to determine the heritability and range of phenotypic variation for biomedical traits. In addition, they may lead to the identification of novel phenotypes and models of human disease. Surprisingly, male reproductive phenotypes are among the least-represented traits in the Mouse Phenome Database. Here we report the results of a broad survey of the eight founder inbred strains of both the Collaborative Cross (CC) and the Diversity Outbred populations, two new mouse resources that are being used as platforms for systems genetics and sources of mouse models of human diseases. Our survey includes representatives of the three main subspecies of the house mice and a mix of classical and wild-derived inbred strains. In addition to standard staples of male reproductive phenotyping such as reproductive organ weights, sperm counts, and sperm morphology, our survey includes sperm motility and the first detailed survey of testis histology. As expected for such a broad survey, heritability varies widely among traits. We conclude that although all eight inbred strains are fertile, most display a mix of advantageous and deleterious male reproductive traits. The CAST/EiJ strain is an outlier, with an unusual combination of deleterious male reproductive traits including low sperm counts, high levels of morphologically abnormal sperm, and poor motility. In contrast, sperm from the PWK/PhJ and WSB/EiJ strains had the greatest percentages of normal morphology and vigorous motility. Finally, we report an abnormal testis phenotype that is highly heritable and restricted to the WSB/EiJ strain. This phenotype is characterized by the presence of a large, but variable, number of vacuoles in at least 10% of the seminiferous tubules. The onset of the phenotype between 2 and 3 wk of age is temporally correlated with the formation of the blood-testis barrier. We speculate that this phenotype may play a role in high rates of extinction in the CC project and in the phenotypes associated with speciation in genetic crosses that use the WSB/EiJ strain as representative of the Mus muculus domesticus subspecies.

Host genetic variation is known to contribute to differential pathogenesis following infection. Mouse models allow direct assessment of host genetic factors responsible for susceptibility to Severe Acute Respiratory Syndrome coronavirus (SARS-CoV). Based on an assessment of early stage lines from the Collaborative Cross mouse multi-parent population, we identified two lines showing highly divergent susceptibilities to SARS-CoV: the resistant CC003/Unc and the susceptible CC053/Unc. We generated 264 F2 mice between these strains, and infected them with SARS-CoV. Weight loss, pulmonary hemorrhage, and viral load were all highly correlated disease phenotypes. We identified a quantitative trait locus of major effect on chromosome 18 (27.1–58.6 Mb) which affected weight loss, viral titer and hemorrhage. Additionally, each of these three phenotypes had distinct quantitative trait loci [Chr 9 (weight loss), Chrs 7 and 12 (virus titer), and Chr 15 (hemorrhage)]. We identified Ticam2, an adaptor protein in the TLR signaling pathways, as a candidate driving differential disease at the Chr 18 locus. Ticam2−/− mice were highly susceptible to SARS-CoV infection, exhibiting increased weight loss and more pulmonary hemorrhage than control mice. These results indicate a critical role for Ticam2 in SARS-CoV disease, and highlight the importance of host genetic variation in disease responses.

Haloperidol is an efficacious antipsychotic drug that has serious, unpredictable motor side effects that limit its utility and cause noncompliance in many patients. Using a drug–placebo diallel of the eight founder strains of the Collaborative Cross and their F1 hybrids, we characterized aggregate effects of genetics, sex, parent of origin, and their combinations on haloperidol response. Treating matched pairs of both sexes with drug or placebo, we measured changes in the following: open field activity, inclined screen rigidity, orofacial movements, prepulse inhibition of the acoustic startle response, plasma and brain drug level measurements, and body weight. To understand the genetic architecture of haloperidol response we introduce new statistical methodology linking heritable variation with causal effect of drug treatment. Our new estimators, “difference of models” and “multiple-impute matched pairs”, are motivated by the Neyman–Rubin potential outcomes framework and extend our existing Bayesian hierarchical model for the diallel (Lenarcic et al. 2012). Drug-induced rigidity after chronic treatment was affected by mainly additive genetics and parent-of-origin effects (accounting for 28% and 14.8% of the variance), with NZO/HILtJ and 129S1/SvlmJ contributions tending to increase this side effect. Locomotor activity after acute treatment, by contrast, was more affected by strain-specific inbreeding (12.8%). In addition to drug response phenotypes, we examined diallel effects on behavior before treatment and found not only effects of additive genetics (10.2–53.2%) but also strong effects of epistasis (10.64–25.2%). In particular: prepulse inhibition showed additivity and epistasis in about equal proportions (26.1% and 23.7%); there was evidence of nonreciprocal epistasis in pretreatment activity and rigidity; and we estimated a range of effects on body weight that replicate those found in our previous work. Our results provide the first quantitative description of the genetic architecture of haloperidol response in mice and indicate that additive, dominance-like inbreeding and parent-of-origin effects contribute strongly to treatment effect heterogeneity for this drug.

Sex differences in recombination are widespread in mammals, but the causes of this pattern are poorly understood. Previously, males from two interfertile subspecies of house mice, Mus musculus musculus and M. m. castaneus, were shown to exhibit a ∼30% difference in their global crossover frequencies. Much of this crossover rate divergence is explained by six autosomal loci and a large-effect locus on the X chromosome. Intriguingly, the allelic effects at this X-linked locus are transgressive, with the allele conferring increased crossover rate being transmitted by the low crossover rate M. m. castaneus parent. Despite the pronounced divergence between males, females from these subspecies exhibit similar crossover rates, raising the question of how recombination is genetically controlled in this sex. Here, I analyze publicly available genotype data from early generations of the Collaborative Cross, an eight-way panel of recombinant inbred strains, to estimate crossover frequencies in female mice with sex-chromosome genotypes of diverse subspecific origins. Consistent with the transgressive influence of the X chromosome in males, I show that females inheriting an M. m. castaneus X possess higher average crossover rates than females lacking the M. m. castaneus X chromosome. The differential inheritance of the X chromosome in males and females provides a simple genetic explanation for sex-limited evolution of this trait. Further, the presence of X-linked and autosomal crossover rate modifiers with antagonistic effects hints at an underlying genetic conflict fueled by selection for distinct crossover rate optima in males and females.

Background Influenza A virus is a zoonotic pathogen that poses a major threat to human and animal health. The severe course of influenza infection is not only influenced by viral virulence factors but also by individual differences in the host response. To determine the extent to which the genetic background can modulate severity of an infection, we studied the host responses to influenza infections in the eight genetically highly diverse Collaborative Cross (CC) founder mouse strains. Results We observed highly divergent host responses between the CC founder strains with respect to survival, body weight loss, hematological parameters in the blood, relative lung weight and viral load. Mouse strain was the main factor with highest effect size on body weight loss after infection, demonstrating that this phenotype was highly heritable. Sex represented another significant main effect, although it was less strong. Analysis of survival rates and mean time to death suggested three groups of susceptibility phenotypes: highly susceptible (A/J, CAST/EiJ, WSB/EiJ), intermediate susceptible (C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ) and highly resistant strains (NZO/HlLtJ, PWK/PhJ). These three susceptibility groups were significantly different with respect to death/survival counts. Viral load was significantly different between susceptible and resistant strains but not between intermediate and highly susceptible strains. CAST/EiJ mice showed a unique phenotype. Despite high viral loads in their lungs, CAST/EiJ mice exhibited low counts of infiltrating granulocytes and showed increased numbers of macrophages in the lung. Histological studies of infected lungs and transcriptome analyses of peripheral blood cells and lungs confirmed an abnormal response in the leukocyte recruitment in CAST/EiJ mice. Conclusions The eight CC founder strains exhibited a large diversity in their response to influenza infections. Therefore, the CC will represent an ideal mouse genetic reference population to study the influence of genetic variation on the susceptibility and resistance to influenza infections which will be important to understand individual variations of disease severity in humans. The unique phenotype combination in the CAST/EiJ strain resembles human leukocyte adhesion deficiency and may thus represent a new mouse model to understand this and related abnormal immune responses to infections in humans. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2483-y) contains supplementary material, which is available to authorized users.

Background The microstructure of trabecular bone is a composite trait governed by a complex interaction of multiple genetic determinants. Identifying these genetic factors should significantly improve our ability to predict of osteoporosis and its associated risks. Genetic mapping using collaborative cross mice (CC), a genetically diverse recombinant inbred mouse reference panel, offers a powerful tool to identify causal loci at a resolution under one mega base-pairs, with a relatively small cohort size. Here, we utilized 31 CC lines (160 mice of both sexes in total) to perform genome-wide haplotype mapping across 77,808 single-nucleotide polymorphisms (SNPs). Haplotype scans were refined by imputation with the catalogue of sequence variation segregating in the CC to suggest potential candidate genes. Trabecular traits were obtained following microtomographic analysis, performed on 10-μm resolution scans of the femoral distal metaphysis. We measured the trabecular bone volume fraction (BV/TV), number (Tb.N), thickness (Tb.Th), and connectivity density (Conn.D). Results Heritability of these traits ranged from 0.6 to 0.7. In addition there was a significant (P

A general Bayesian model, Diploffect, is described for estimating the effects of founder haplotypes at quantitative trait loci (QTL) detected in multiparental genetic populations; such populations include the Collaborative Cross (CC), Heterogeneous Socks (HS), and many others for which local genetic variation is well described by an underlying, usually probabilistically inferred, haplotype mosaic. Our aim is to provide a framework for coherent estimation of haplotype and diplotype (haplotype pair) effects that takes into account the following: uncertainty in haplotype composition for each individual; uncertainty arising from small sample sizes and infrequently observed haplotype combinations; possible effects of dominance (for noninbred subjects); genetic background; and that provides a means to incorporate data that may be incomplete or has a hierarchical structure. Using the results of a probabilistic haplotype reconstruction as prior information, we obtain posterior distributions at the QTL for both haplotype effects and haplotype composition. Two alternative computational approaches are supplied: a Markov chain Monte Carlo sampler and a procedure based on importance sampling of integrated nested Laplace approximations. Using simulations of QTL in the incipient CC (pre-CC) and Northport HS populations, we compare the accuracy of Diploffect, approximations to it, and more commonly used approaches based on Haley–Knott regression, describing trade-offs between these methods. We also estimate effects for three QTL previously identified in those populations, obtaining posterior intervals that describe how the phenotype might be affected by diplotype substitutions at the modeled locus.

The Collaborative Cross (CC) is an emerging panel of recombinant inbred (RI) mouse strains. Each strain is genetically distinct but all descended from the same eight inbred founders. In 66 strains from incipient lines of the CC (pre-CC), as well as the 8 CC founders and some of their F1 offspring, we examined subsets of lymphocytes and antigen-presenting cells. We found significant variation among the founders, with even greater diversity in the pre-CC. Genome-wide association using inferred haplotypes detected highly significant loci controlling B-to-T cell ratio, CD8 T-cell numbers, CD11c and CD23 expression. Comparison of overall strain effects in the CC founders with strain effects at QTL in the pre-CC revealed sharp contrasts in the genetic architecture of two traits with significant loci: variation in CD23 can be explained largely by additive genetics at one locus, whereas variation in B-to-T ratio has a more complex etiology. For CD23, we found a strong QTL whose confidence interval contained the CD23 structural gene Fcer2a. Our data on the pre-CC demonstrate the utility of the CC for studying immunophenotypes and the value of integrating founder, CC and F1 data. The extreme immunophenotypes observed could have pleiotropic effects in other CC experiments.

Genetic variation between diverse mouse species is well-characterized, yet existing knowledge of the mouse transcriptome comes largely from one mouse strain (C57BL/6J). As such, it is unlikely to reflect the transcriptional complexity of the mouse species. Gene transcription is dynamic and condition-specific; therefore, to better understand the mouse transcriptional response to respiratory virus infection, we infected the eight founder strains of the Collaborative Cross with either influenza A virus or severe acute respiratory syndrome coronavirus and sequenced lung RNA samples at 2 and 4 days after infection. We found numerous instances of transcripts that were not present in the C57BL/6J reference annotation, indicating that a nontrivial proportion of the mouse genome is transcribed but poorly annotated. Of these novel transcripts, 2150 could be aligned to human or rat genomes, but not to existing mouse genomes, suggesting functionally conserved sequences not yet recorded in mouse genomes. We also found that respiratory virus infection induced differential expression of 4287 splicing junctions, resulting in strain-specific isoform expression. Of these, 59 were influenced by strain-specific mutations within 2 base pairs of key intron–exon boundaries, suggesting cis-regulated expression. Our results reveal the complexity of the transcriptional response to viral infection, previously undocumented genomic elements, and extensive diversity in the response across mouse strains. These findings identify hitherto unexplored transcriptional patterns and undocumented transcripts in genetically diverse mice. Host genetic variation drives the complexity and diversity of the host response by eliciting starkly different transcriptional profiles in response to a viral infection.

Background Periodontal infection (Periodontitis) is a chronic inflammatory disease, which results in the breakdown of the supporting tissues of the teeth. Previous epidemiological studies have suggested that resistance to chronic periodontitis is controlled to some extent by genetic factors of the host. The aim of this study was to determine the phenotypic response of inbred and Collaborative Cross (CC) mouse populations to periodontal bacterial challenge, using an experimental periodontitis model. In this model, mice are co-infected with Porphyromonas gingivalis and Fusobacterium nucleatum, bacterial strains associated with human periodontal disease. Six weeks following the infection, the maxillary jaws were harvested and analyzed for alveolar bone loss relative to uninfected controls, using computerized microtomography (microCT). Initially, four commercial inbred mouse strains were examined to calibrate the procedure and test for gender effects. Subsequently, we applied the same protocol to 23 lines (at inbreeding generations 10–18) from the newly developed mouse genetic reference population, the Collaborative Cross (CC) to determine heritability and genetic variation of control bone volume prior to infection (CBV, naïve bone volume around the teeth of uninfected mice), and residual bone volume (RBV, bone volume after infection) and loss of bone volume (LBV, the difference between CBV and RBV) following infection. Results BALB/CJ mice were highly susceptible (P Conclusions The moderate heritability values indicate that the variation in host susceptibility to the disease is controlled to an appreciable extent by genetic factors. These results strongly support the possibility of using the Collaborative Cross, as well as developing dedicated F2 (resistant x susceptible inbred strains) resource populations, for future dissection of genetic factors in periodontitis.

Historically our ability to identify genetic variants underlying complex behavioral traits in mice has been limited by low mapping resolution of conventional mouse crosses. The newly developed Diversity Outbred (DO) population promises to deliver improved resolution that will circumvent costly fine-mapping studies. The DO is derived from the same founder strains as the Collaborative Cross (CC), including three wild-derived strains. Thus the DO provides more allelic diversity and greater potential for discovery compared to crosses involving standard mouse strains. We have characterized 283 male and female DO mice using open-field, light-dark box, tail-suspension and visual-cliff avoidance tests to generate 38 behavioral measures. We identified several quantitative trait loci (QTL) for these traits with support intervals ranging from 1 to 3 Mb in size. These intervals contain relatively few genes (ranging from 5 to 96). For a majority of QTL, using the founder allelic effects together with whole genome sequence data, we could further narrow the positional candidates. Several QTL replicate previously published loci. Novel loci were also identified for anxiety- and activity-related traits. Half of the QTLs are associated with wild-derived alleles, confirming the value to behavioral genetics of added genetic diversity in the DO. In the presence of wild-alleles we sometimes observe behaviors that are qualitatively different from the expected response. Our results demonstrate that high-precision mapping of behavioral traits can be achieved with moderate numbers of DO animals, representing a significant advance in our ability to leverage the mouse as a tool for behavioral genetics.

During a meeting of the SYSGENET working group 'Bioinformatics', currently available software tools and databases for systems genetics in mice were reviewed and the needs for future developments discussed. The group evaluated interoperability and performed initial feasibility studies. To aid future compatibility of software and exchange of already developed software modules, a strong recommendation was made by the group to integrate HAPPY and R/qtl analysis toolboxes, GeneNetwork and XGAP database platforms, and TIQS and xQTL processing platforms. R should be used as the principal computer language for QTL data analysis in all platforms and a 'cloud' should be used for software dissemination to the community. Furthermore, the working group recommended that all data models and software source code should be made visible in public repositories to allow a coordinated effort on the use of common data structures and file formats.

The challenge of precision medicine is to model complex interactions among DNA variants, phenotypes, development, environments, and treatments. We address this challenge by expanding the BXD family of mice to 140 fully isogenic strains, creating a uniquely powerful model for precision medicine. This family segregates for 6 million common DNA variants—a level that exceeds many human populations. Because each member can be replicated, heritable traits can be mapped with high power and precision. Current BXD phenomes are unsurpassed in coverage and include much omics data and thousands of quantitative traits. The BXDs can be extended by a single-generation cross to as many as 19,460 isogenic F1 progeny, and this extended BXD family is an effective platform for testing causal modeling and for predictive validation. The BXDs are a unique core resource for the field of experimental precision medicine.

Background Colorectal cancer is an abnormal tissue development in the colon or rectum. Most of CRCs develop due to somatic mutations, while only a small proportion is caused by inherited mutations. Familial adenomatous polyposis is an inherited genetic disease, which is characterized by colorectal polyps. It is caused by inactivating mutations in the Adenomatous polyposis coli gene. Mice carrying and non-sense mutation in Adenomatous polyposis coli gene at site R850, which designated ApcR850X/+ (Min), develop intestinal adenomas, while the bulk of the disease is in the small intestine. A number of genetic modifier loci of Min have been mapped, but so far most of the underlying genes have not been identified. In our previous studies, we have shown that Collaborative Cross mice are a powerful tool for mapping loci responsible for phenotypic variation. As a first step towards identification of novel modifiers of Min, we assessed the phenotypic variation between 27 F1 crosses between different Collaborative cross mice and C57BL/6-Min lines. Results Here, C57BL/6-Min male mice were mated with females from 27 Collaborative cross lines. F1 offspring were terminated at 23 weeks old and multiple phenotypes were collected: polyp counts, intestine length, intestine weight, packed cell volume and spleen weight. Additionally, in eight selected F1 Collaborative cross-C57BL/6-Min lines, body weight was monitored and compared to control mice carry wildtype Adenomatous polyposis coli gene. We found significant (p

Background The Collaborative Cross (CC) is a large panel of genetically diverse recombinant inbred mouse strains specifically designed to provide a systems genetics resource for the study of complex traits. In part, the utility of the CC stems from the extensive genome-wide annotations of founder strain sequence and structural variation. Still missing, however, are transcriptome-specific annotations of the CC founder strains that could further enhance the utility of this resource. Results We provide a comprehensive survey of the splicing landscape of the 8 CC founder strains by leveraging the high level of alternative splicing within the brain. Using deep transcriptome sequencing, we found that a majority of the splicing landscape is conserved among the 8 strains, with ~65% of junctions being shared by at least 2 strains. We, however, found a large number of potential strain-specific splicing events as well, with an average of ~3000 and ~500 with ≥3 and ≥10 sequence read coverage, respectively, within each strain. To better understand strain-specific splicing within the CC founder strains, we defined criteria for and identified high-confidence strain-specific splicing events. These splicing events were defined as exon-exon junctions 1) found within only one strain, 2) with a read coverage ≥10, and 3) defined by a canonical splice site. With these criteria, a total of 1509 high-confidence strain-specific splicing events were identified, with the majority found within two of the wild-derived strains, CAST and PWK. Strikingly, the overwhelming majority, 94%, of these strain-specific splicing events are not yet annotated. Strain-specific splicing was also located within genomic regions recently reported to be over- and under-represented within CC populations. Conclusions Phenotypic characterization of CC populations is increasing; thus these results will not only aid in further elucidating the transcriptomic architecture of the individual CC founder strains, but they will also help in guiding the utilization of the CC populations in the study of complex traits. This report is also the first to establish guidelines in defining and identifying strain-specific splicing across different mouse strains. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1267-0) contains supplementary material, which is available to authorized users.