Architecture of the outbred brown fat proteome defines regulators of metabolic physiology.

Brown adipose tissue (BAT) regulates metabolic physiology. However, nearly all mechanistic studies of BAT protein function occur in a single inbred mouse strain, which has limited the understanding of generalizable mechanisms of BAT regulation over physiology. Here, we perform deep quantitative proteomics of BAT across a cohort of 163 genetically defined diversity outbred mice, a model that parallels the genetic and phenotypic variation found in humans. We leverage this diversity to define the functional architecture of the outbred BAT proteome, comprising 10,479 proteins. We assign co-operative functions to 2,578 proteins, enabling systematic discovery of regulators of BAT. We also identify 638 proteins that correlate with protection from, or sensitivity to, at least one parameter of metabolic disease. We use these findings to uncover SFXN5, LETMD1, and ATP1A2 as modulators of BAT thermogenesis or adiposity, and provide OPABAT as a resource for understanding the conserved mechanisms of BAT regulation over metabolic physiology.

GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.

Hundreds of inbred mouse strains and intercross populations have been used to characterize the function of genetic variants that contribute to disease. Thousands of disease-relevant traits have been characterized in mice and made publicly available. New strains and populations including consomics, the collaborative cross, expanded BXD, and inbred wild-derived strains add to existing complex disease mouse models, mapping populations, and sensitized backgrounds for engineered mutations. The genome sequences of inbred strains, along with dense genotypes from others, enable integrated analysis of trait-variant associations across populations, but these analyses are hampered by the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense variant resource by harmonizing multiple data sets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extendable to other model organisms. The result is a web- and programmatically accessible data service called GenomeMUSter, comprising single-nucleotide variants covering 657 strains at 106.8 million segregating sites. Interoperation with phenotype databases, analytic tools, and other resources enable a wealth of applications, including multitrait, multipopulation meta-analysis. We show this in cross-species comparisons of type 2 diabetes and substance use disorder meta-analyses, leveraging mouse data to characterize the likely role of human variant effects in disease. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

Variation in histone configurations correlates with gene expression across nine inbred strains of mice.

The Diversity Outbred (DO) mice and their inbred founders are widely used models of human disease. However, although the genetic diversity of these mice has been well documented, their epigenetic diversity has not. Epigenetic modifications, such as histone modifications and DNA methylation, are important regulators of gene expression and, as such, are a critical mechanistic link between genotype and phenotype. Therefore, creating a map of epigenetic modifications in the DO mice and their founders is an important step toward understanding mechanisms of gene regulation and the link to disease in this widely used resource. To this end, we performed a strain survey of epigenetic modifications in hepatocytes of the DO founders. We surveyed four histone modifications (H3K4me1, H3K4me3, H3K27me3, and H3K27ac), as well as DNA methylation. We used ChromHMM to identify 14 chromatin states, each of which represents a distinct combination of the four histone modifications. We found that the epigenetic landscape is highly variable across the DO founders and is associated with variation in gene expression across strains. We found that epigenetic state imputed into a population of DO mice recapitulated the association with gene expression seen in the founders, suggesting that both histone modifications and DNA methylation are highly heritable mechanisms of gene expression regulation. We illustrate how DO gene expression can be aligned with inbred epigenetic states to identify putative cis-regulatory regions. Finally, we provide a data resource that documents strain-specific variation in the chromatin state and DNA methylation in hepatocytes across nine widely used strains of laboratory mice.

Mouse Phenome Database: towards a more FAIR-compliant and TRUST-worthy data repository and tool suite for phenotypes and genotypes.

The Mouse Phenome Database (MPD; https://phenome.jax.org; RRID:SCR_003212), supported by the US National Institutes of Health, is a Biomedical Data Repository listed in the Trans-NIH Biomedical Informatics Coordinating Committee registry. As an increasingly FAIR-compliant and TRUST-worthy data repository, MPD accepts phenotype and genotype data from mouse experiments and curates, organizes, integrates, archives, and distributes those data using community standards. Data are accompanied by rich metadata, including widely used ontologies and detailed protocols. Data are from all over the world and represent genetic, behavioral, morphological, and physiological disease-related characteristics in mice at baseline or those exposed to drugs or other treatments. MPD houses data from over 6000 strains and populations, representing many reproducible strain types and heterogenous populations such as the Diversity Outbred where each mouse is unique but can be genotyped throughout the genome. A suite of analysis tools is available to aggregate, visualize, and analyze these data within and across studies and populations in an increasingly traceable and reproducible manner. We have refined existing resources and developed new tools to continue to provide users with access to consistent, high-quality data that has translational relevance in a modernized infrastructure that enables interaction with a suite of bioinformatics analytic and data services.

Mouse phenome database: curated data repository with interactive multi-population and multi-trait analyses.

The Mouse Phenome Database continues to serve as a curated repository and analysis suite for measured attributes of members of diverse mouse populations. The repository includes annotation to community standard ontologies and guidelines, a database of allelic states for 657 mouse strains, a collection of protocols, and analysis tools for flexible, interactive, user directed analyses that increasingly integrates data across traits and populations. The database has grown from its initial focus on a standard set of inbred strains to include heterogeneous mouse populations such as the Diversity Outbred and mapping crosses and well as Collaborative Cross, Hybrid Mouse Diversity Panel, and recombinant inbred strains. Most recently the system has expanded to include data from the International Mouse Phenotyping Consortium. Collectively these data are accessible by API and provided with an interactive tool suite that enables users' persistent selection, storage, and operation on collections of measures. The tool suite allows basic analyses, advanced functions with dynamic visualization including multi-population meta-analysis, multivariate outlier detection, trait pattern matching, correlation analyses and other functions. The data resources and analysis suite provide users a flexible environment in which to explore the basis of phenotypic variation in health and disease across the lifespan.

Author Correction: Comparing phenotypic variation between inbred and outbred mice.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

In vivo activity of the dual SYK/FLT3 inhibitor TAK-659 against pediatric acute lymphoblastic leukemia xenografts.

BACKGROUND: While children with acute lymphoblastic leukemia (ALL) experience close to a 90% likelihood of cure, the outcome for certain high-risk pediatric ALL subtypes remains dismal. Spleen tyrosine kinase (SYK) is a prominent cytosolic nonreceptor tyrosine kinase in pediatric B-lineage ALL (B-ALL). Activating mutations or overexpression of Fms-related receptor tyrosine kinase 3 (FLT3) are associated with poor outcome in hematological malignancies. TAK-659 (mivavotinib) is a dual SYK/FLT3 reversible inhibitor, which has been clinically evaluated in several other hematological malignancies. Here, we investigate the in vivo efficacy of TAK-659 against pediatric ALL patient-derived xenografts (PDXs). METHODS: SYK and FLT3 mRNA expression was quantified by RNA-seq. PDX engraftment and drug responses in NSG mice were evaluated by enumerating the proportion of human CD45+ cells (%huCD45+ ) in the peripheral blood. TAK-659 was administered per oral at 60 mg/kg daily for 21 days. Events were defined as %huCD45+ ≥ 25%. In addition, mice were humanely killed to assess leukemia infiltration in the spleen and bone marrow (BM). Drug efficacy was assessed by event-free survival and stringent objective response measures. RESULTS: FLT3 and SYK mRNA expression was significantly higher in B-lineage compared with T-lineage PDXs. TAK-659 was well tolerated and significantly prolonged the time to event in six out of eight PDXs tested. However, only one PDX achieved an objective response. The minimum mean %huCD45+ was significantly reduced in five out of eight PDXs in TAK-659-treated mice compared with vehicle controls. CONCLUSIONS: TAK-659 exhibited low to moderate single-agent in vivo activity against pediatric ALL PDXs representative of diverse subtypes.

High-Diversity Mouse Populations for Complex Traits.

Contemporary mouse genetic reference populations are a powerful platform to discover complex disease mechanisms. Advanced high-diversity mouse populations include the Collaborative Cross (CC) strains, Diversity Outbred (DO) stock, and their isogenic founder strains. When used in systems genetics and integrative genomics analyses, these populations efficiently harnesses known genetic variation for precise and contextualized identification of complex disease mechanisms. Extensive genetic, genomic, and phenotypic data are already available for these high-diversity mouse populations and a growing suite of data analysis tools have been developed to support research on diverse mice. This integrated resource can be used to discover and evaluate disease mechanisms relevant across species.

Large-scale discovery of mouse transgenic integration sites reveals frequent structural variation and insertional mutagenesis.

Transgenesis has been a mainstay of mouse genetics for over 30 yr, providing numerous models of human disease and critical genetic tools in widespread use today. Generated through the random integration of DNA fragments into the host genome, transgenesis can lead to insertional mutagenesis if a coding gene or an essential element is disrupted, and there is evidence that larger scale structural variation can accompany the integration. The insertion sites of only a tiny fraction of the thousands of transgenic lines in existence have been discovered and reported, due in part to limitations in the discovery tools. Targeted locus amplification (TLA) provides a robust and efficient means to identify both the insertion site and content of transgenes through deep sequencing of genomic loci linked to specific known transgene cassettes. Here, we report the first large-scale analysis of transgene insertion sites from 40 highly used transgenic mouse lines. We show that the transgenes disrupt the coding sequence of endogenous genes in half of the lines, frequently involving large deletions and/or structural variations at the insertion site. Furthermore, we identify a number of unexpected sequences in some of the transgenes, including undocumented cassettes and contaminating DNA fragments. We demonstrate that these transgene insertions can have phenotypic consequences, which could confound certain experiments, emphasizing the need for careful attention to control strategies. Together, these data show that transgenic alleles display a high rate of potentially confounding genetic events and highlight the need for careful characterization of each line to assure interpretable and reproducible experiments.

Author Correction: Comparing phenotypic variation between inbred and outbred mice.

In the version of this Comment originally published, the authors omitted a funding source. Grant 5 P50 DA039841 (to E.J.C.) from the US National Institute on Drug Abuse has been added to the Acknowledgements in the HTML and PDF versions of the paper.

Genome-wide association mapping of ethanol sensitivity in the Diversity Outbred mouse population.

BACKGROUND: A strong predictor for the development of alcohol use disorder (AUD) is altered sensitivity to the intoxicating effects of alcohol. Individual differences in the initial sensitivity to alcohol are controlled in part by genetic factors. Mice offer a powerful tool to elucidate the genetic basis of behavioral and physiological traits relevant to AUD, but conventional experimental crosses have only been able to identify large chromosomal regions rather than specific genes. Genetically diverse, highly recombinant mouse populations make it possible to observe a wider range of phenotypic variation, offer greater mapping precision, and thus increase the potential for efficient gene identification. METHODS: We have taken advantage of the Diversity Outbred (DO) mouse population to identify and precisely map quantitative trait loci (QTL) associated with ethanol sensitivity. We phenotyped 798 male J:DO mice for three measures of ethanol sensitivity: ataxia, hypothermia, and loss of the righting response. We used high-density MegaMUGA and GigaMUGA to obtain genotypes ranging from 77,808 to 143,259 SNPs. We also performed RNA sequencing in striatum to map expression QTLs and identify gene expression-trait correlations. We then applied a systems genetic strategy to identify narrow QTLs and construct the network of correlations that exists between DNA sequence, gene expression values, and ethanol-related phenotypes to prioritize our list of positional candidate genes. RESULTS: We observed large amounts of phenotypic variation with the DO population and identified suggestive and significant QTLs associated with ethanol sensitivity on chromosomes 1, 2, and 16. The implicated regions were narrow (4.5-6.9 Mb in size) and each QTL explained ~4-5% of the variance. CONCLUSIONS: Our results can be used to identify alleles that contribute to AUD in humans, elucidate causative biological mechanisms, or assist in the development of novel therapeutic interventions.

Mouse Phenome Database: a data repository and analysis suite for curated primary mouse phenotype data.

The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely accessed and highly functional data repository housing primary phenotype data for the laboratory mouse accessible via APIs and providing tools to analyze and visualize those data. Data come from investigators around the world and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD houses rigorously curated per-animal data with detailed protocols. Public ontologies and controlled vocabularies are used for annotation. In addition to phenotype tools, genetic analysis tools enable users to integrate and interpret genome-phenome relations across the database. Strain types and populations include inbred, recombinant inbred, F1 hybrid, transgenic, targeted mutants, chromosome substitution, Collaborative Cross, Diversity Outbred and other mapping populations. Our new analysis tools allow users to apply selected data in an integrated fashion to address problems in trait associations, reproducibility, polygenic syndrome model selection and multi-trait modeling. As we refine these tools and approaches, we will continue to provide users a means to identify consistent, quality studies that have high translational relevance.

Heritability of ethanol consumption and pharmacokinetics in a genetically diverse panel of collaborative cross mouse strains and their inbred founders.

BACKGROUND: Interindividual variation in voluntary ethanol consumption and ethanol response is partially influenced by genetic variation. Discovery of the genes and allelic variants that affect these phenotypes may clarify the etiology and pathophysiology of problematic alcohol use, including alcohol use disorder. Genetically diverse mouse populations, which demonstrate heritable variation in ethanol consumption, can be utilized to discover the genes and gene networks that influence this trait. The Collaborative Cross (CC) recombinant inbred strains, Diversity Outbred (DO) population and their 8 founder strains are complementary mouse resources that capture substantial genetic diversity and can demonstrate expansive phenotypic variation in heritable traits. These populations may be utilized to discover candidate genes and gene networks that moderate ethanol consumption and other ethanol-related traits. METHODS: We characterized ethanol consumption, preference, and pharmacokinetics in the 8 founder strains and 10 CC strains in 12-hour drinking sessions during the dark phase of the circadian cycle. RESULTS: Ethanol consumption was substantially heritable, both early in ethanol access and over a chronic intermittent access schedule. Ethanol pharmacokinetics were also heritable; however, no association between strain-level ethanol consumption and pharmacokinetics was detected. The PWK/PhJ strain was the highest drinking strain, with consumption substantially exceeding that of the C57BL/6J strain, which is commonly used as a model of "high" or "binge" drinking. Notably, we found strong evidence that sex moderated genetic effects on voluntary ethanol drinking. CONCLUSIONS: Collectively, this research serves as a foundation for expanded genetic study of ethanol consumption in the CC/DO and related populations. Moreover, we identified reference strains with extreme consumption phenotypes that effectively represent polygenic models of excessive ethanol use.

Identifying the molecular systems that influence cognitive resilience to Alzheimer's disease in genetically diverse mice.

Individual differences in cognitive decline during normal aging and Alzheimer's disease (AD) are common, but the molecular mechanisms underlying these distinct outcomes are not fully understood. We utilized a combination of genetic, molecular, and behavioral data from a mouse population designed to model human variation in cognitive outcomes to search for the molecular mechanisms behind this population-wide variation. Specifically, we used a systems genetics approach to relate gene expression to cognitive outcomes during AD and normal aging. Statistical causal-inference Bayesian modeling was used to model systematic genetic perturbations matched with cognitive data that identified astrocyte and microglia molecular networks as drivers of cognitive resilience to AD. Using genetic mapping, we identified Fgf2 as a potential regulator of the astrocyte network associated with individual differences in short-term memory. We also identified several immune genes as regulators of a microglia network associated with individual differences in long-term memory, which was partly mediated by amyloid burden. Finally, significant overlap between mouse and two different human coexpression networks provided strong evidence of translational relevance for the genetically diverse AD-BXD panel as a model of late-onset AD. Together, this work identified two candidate molecular pathways enriched for microglia and astrocyte genes that serve as causal AD cognitive biomarkers, and provided a greater understanding of processes that modulate individual and population-wide differences in cognitive outcomes during AD.

Mouse Phenome Database: an integrative database and analysis suite for curated empirical phenotype data from laboratory mice.

The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely used resource that provides access to primary experimental trait data, genotypic variation, protocols and analysis tools for mouse genetic studies. Data are contributed by investigators worldwide and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD houses individual animal data with detailed, searchable protocols, and makes these data available to other resources via API. MPD provides rigorous curation of experimental data and supporting documentation using relevant ontologies and controlled vocabularies. Most data in MPD are from inbreds and other reproducible strains such that the data are cumulative over time and across laboratories. The resource has been expanded to include the QTL Archive and other primary phenotype data from mapping crosses as well as advanced high-diversity mouse populations including the Collaborative Cross and Diversity Outbred mice. Furthermore, MPD provides a means of assessing replicability and reproducibility across experimental conditions and protocols, benchmarking assays in users' own laboratories, identifying sensitized backgrounds for making new mouse models with genome editing technologies, analyzing trait co-inheritance, finding the common genetic basis for multiple traits and assessing sex differences and sex-by-genotype interactions.

Genetic and Small Molecule Disruption of the AID/RAD51 Axis Similarly Protects Nonobese Diabetic Mice from Type 1 Diabetes through Expansion of Regulatory B Lymphocytes.

B lymphocytes play a key role in type 1 diabetes (T1D) development by serving as a subset of APCs preferentially supporting the expansion of autoreactive pathogenic T cells. As a result of their pathogenic importance, B lymphocyte-targeted therapies have received considerable interest as potential T1D interventions. Unfortunately, the B lymphocyte-directed T1D interventions tested to date failed to halt ß cell demise. IgG autoantibodies marking humans at future risk for T1D indicate that B lymphocytes producing them have undergone the affinity-maturation processes of class switch recombination and, possibly, somatic hypermutation. This study found that CRISPR/Cas9-mediated ablation of the activation-induced cytidine deaminase gene required for class switch recombination/somatic hypermutation induction inhibits T1D development in the NOD mouse model. The activation-induced cytidine deaminase protein induces genome-wide DNA breaks that, if not repaired through RAD51-mediated homologous recombination, result in B lymphocyte death. Treatment with the RAD51 inhibitor 4,4'-diisothiocyanatostilbene-2, 2'-disulfonic acid also strongly inhibited T1D development in NOD mice. The genetic and small molecule-targeting approaches expanded CD73+ B lymphocytes that exert regulatory activity suppressing diabetogenic T cell responses. Hence, an initial CRISPR/Cas9-mediated genetic modification approach has identified the AID/RAD51 axis as a target for a potentially clinically translatable pharmacological approach that can block T1D development by converting B lymphocytes to a disease-inhibitory CD73+ regulatory state.

Genome-wide association for testis weight in the diversity outbred mouse population.

Testis weight is a genetically mediated trait associated with reproductive efficiency across numerous species. We sought to evaluate the genetically diverse, highly recombinant Diversity Outbred (DO) mouse population as a tool to identify and map quantitative trait loci (QTLs) associated with testis weight. Testis weights were recorded for 502 male DO mice and the mice were genotyped on the GIGAMuga array at ~ 143,000 SNPs. We performed a genome-wide association analysis and identified one significant and two suggestive QTLs associated with testis weight. Using bioinformatic approaches, we developed a list of candidate genes and identified those with known roles in testicular size and development. Candidates of particular interest include the RNA demethylase gene Alkbh5, the cyclin-dependent kinase inhibitor gene Cdkn2c, the dynein axonemal heavy chain gene Dnah11, the phospholipase D gene Pld6, the trans-acting transcription factor gene Sp4, and the spermatogenesis-associated gene Spata6, each of which has a human ortholog. Our results demonstrate the utility of DO mice in high-resolution genetic mapping of complex traits, enabling us to identify developmentally important genes in adult mice. Understanding how genetic variation in these genes influence testis weight could aid in the understanding of mechanisms of mammalian reproductive function.

Molecular identification of collagen 17a1 as a major genetic modifier of laminin gamma 2 mutation-induced junctional epidermolysis bullosa in mice.

Epidermolysis Bullosa (EB) encompasses a spectrum of mechanobullous disorders caused by rare mutations that result in structural weakening of the skin and mucous membranes. While gene mutated and types of mutations present are broadly predictive of the range of disease to be expected, a remarkable amount of phenotypic variability remains unaccounted for in all but the most deleterious cases. This unexplained variance raises the possibility of genetic modifier effects. We tested this hypothesis using a mouse model that recapitulates a non-Herlitz form of junctional EB (JEB) owing to the hypomorphic jeb allele of laminin gamma 2 (Lamc2). By varying normally asymptomatic background genetics, we document the potent impact of genetic modifiers on the strength of dermal-epidermal adhesion and on the clinical severity of JEB in the context of the Lamc2(jeb) mutation. Through an unbiased genetic approach involving a combination of QTL mapping and positional cloning, we demonstrate that Col17a1 is a strong genetic modifier of the non-Herlitz JEB that develops in Lamc2(jeb) mice. This modifier is defined by variations in 1-3 neighboring amino acids in the non-collagenous 4 domain of the collagen XVII protein. These allelic variants alter the strength of dermal-epidermal adhesion in the context of the Lamc2(jeb) mutation and, consequentially, broadly impact the clinical severity of JEB. Overall the results provide an explanation for how normally innocuous allelic variants can act epistatically with a disease causing mutation to impact the severity of a rare, heritable mechanobullous disorder.

Minor genomic differences between related B6 and B10 mice affect severity of schistosome infection by governing the mode of dendritic cell activation.

Infection with the helminth Schistosoma mansoni results in hepatointestinal granulomatous inflammation mediated by CD4 T cells directed against parasite eggs. The severity of disease varies greatly in humans and mice; however, the genetic basis of such a heterogenous immune response remains poorly understood. Here we show that, despite their close genetic relationship, C57BL/10SnJ (B10) mice developed significantly more pronounced immunopathology and higher T helper 17 cell responses than C57BL/6J (B6) mice. Similarly, live egg-stimulated B10-derived dendritic cells (DCs) produced significantly more IL-1ß and IL-23, resulting in higher IL-17 production by CD4 T cells. Gene expression analysis disclosed a heightened proinflammatory cytokine profile together with a strikingly lower expression of Ym1 in B10 versus B6 mice, consistent with failure of B10 DCs to attain alternative activation. To genetically dissect the differential response, we developed and analyzed congenic mouse strains that capture major regions of allelic variation, and found that the level of inflammation was controlled by a relatively small number of genes in a locus mapping to chromosome 4 117-143 MB. Our study has thus identified novel genomic regions that regulate the severity of the schistosome infection by way of controlling the mode of DC activation and consequent CD4 T-cell subset development.