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

Understanding Patterns of Life History Trait Covariation in an Untapped Resource, the Lab Mouse

AbstractThrough artificial selection and inbreeding, strains of laboratory mice have been developed that vary in the expression of a single or suite of desired traits valuable to biomedical research. In addition to the selected trait(s), these strains also display variation in pelage color, body size, physiology, and life history. This article exploits the broad phenotypic variation across lab mouse strains to evaluate the relationships between life history and metabolism. Life history variation tends to exist along a fast-slow continuum. There has been considerable interest in understanding the ecological and evolutionary factors underlying life history variation and the physiological and metabolic processes that support them. Yet it remains unclear how these key traits scale across hierarchical levels, as ambiguous empirical support has been garnered at the intraspecific level. Within-species investigations have been thwarted by methodological constraints and environmental factors that obscure the genetic architecture underlying the hypothesized functional integration of life history and metabolic traits. In this analysis, we used the publicly available Mouse Phenome Database by the Jackson Laboratory to investigate the relationships among life history traits (e.g., body size, reproduction, and life span) and metabolic traits (e.g., daily energy expenditure and insulin-like growth factor 1 concentration). Our findings revealed significant variation in reproductive characteristics across strains of mice as well as relationships among life history and metabolic traits. We found evidence of variation along the fast-slow life history continuum, though the direction of some relationships among these traits deviated from interspecific predictions laid out in previous literature. Furthermore, our results suggest that the strength of these relationships are strongest earlier in life.

Spironolactone alleviates schizophrenia-related reversal learning in Tcf4 transgenic mice subjected to social defeat

Cognitive deficits are a hallmark of schizophrenia, for which no convincing pharmacological treatment option is currently available. Here, we tested spironolactone as a repurposed compound in Tcf4 transgenic mice subjected to psychosocial stress. In this ‘2-hit’ gene by environment mouse (GxE) model, the animals showed schizophrenia-related cognitive deficits. We had previously shown that spironolactone ameliorates working memory deficits and hyperactivity in a mouse model of cortical excitatory/inhibitory (E/I) dysbalance caused by an overactive NRG1-ERBB4 signaling pathway. In an add-on clinical study design, we used spironolactone as adjuvant medication to the standard antipsychotic drug aripiprazole. We characterized the compound effects using our previously established Platform for Systematic Semi-Automated Behavioral and Cognitive Profiling (PsyCoP). PsyCoP is a widely applicable analysis pipeline based on the Research Domain Criteria (RDoC) framework aiming at facilitating translation into the clinic. In addition, we use dimensional reduction to analyze and visualize overall treatment effect profiles. We found that spironolactone and aripiprazole improve deficits of several cognitive domains in Tcf4tg x SD mice but partially interfere with each other’s effect in the combination therapy. A similar interaction was detected for the modulation of novelty-induced activity. In addition to its strong activity-dampening effects, we found an increase in negative valence measures as a side effect of aripiprazole treatment in mice. We suggest that repurposed drug candidates should first be tested in an adequate preclinical setting before initiating clinical trials. In addition, a more specific and effective NRG1-ERBB4 pathway inhibitor or more potent E/I balancing drug might enhance the ameliorating effect on cognition even further.

Morphine and high-fat diet differentially alter the gut microbiota composition and metabolic function in lean versus obese mice

There are known associations between opioids, obesity, and the gut microbiome, but the molecular connection/mediation of these relationships is not understood. To better clarify the interplay of physiological, genetic, and microbial factors, this study investigated the microbiome and host inflammatory responses to chronic opioid administration in genetically obese, diet-induced obese, and lean mice. Samples of feces, urine, colon tissue, and plasma were analyzed using targeted LC-MS/MS quantification of metabolites, immunoassays of inflammatory cytokine levels, genome-resolved metagenomics, and metaproteomics. Genetic obesity, diet-induced obesity, and morphine treatment in lean mice each showed increases in distinct inflammatory cytokines. Metagenomic assembly and binning uncovered over 400 novel gut bacterial genomes and species. Morphine administration impacted the microbiome's composition and function, with the strongest effect observed in lean mice. This microbiome effect was less pronounced than either diet or genetically driven obesity. Based on inferred microbial physiology from the metaproteome datasets, a high-fat diet transitioned constituent microbes away from harvesting diet-derived nutrients and towards nutrients present in the host mucosal layer. Considered together, these results identified novel host-dependent phenotypes, differentiated the effects of genetic obesity versus diet induced obesity on gut microbiome composition and function, and showed that chronic morphine administration altered the gut microbiome.

Snrpb is required in murine neural crest cells for proper splicing and craniofacial morphogenesis

Heterozygous mutations in SNRPB, an essential core component of the five small ribonucleoprotein particles of the spliceosome, are responsible for cerebrocostomandibular syndrome (CCMS). We show that Snrpb heterozygous mouse embryos arrest shortly after implantation. Additionally, heterozygous deletion of Snrpb in the developing brain and neural crest cells models craniofacial malformations found in CCMS, and results in death shortly after birth. RNAseq analysis of mutant heads prior to morphological defects revealed increased exon skipping and intron retention in association with increased 5′ splice site strength. We found increased exon skipping in negative regulators of the P53 pathway, along with increased levels of nuclear P53 and P53 target genes. However, removing Trp53 in Snrpb heterozygous mutant neural crest cells did not completely rescue craniofacial development. We also found a small but significant increase in exon skipping of several transcripts required for head and midface development, including Smad2 and Rere. Furthermore, mutant embryos exhibited ectopic or missing expression of Fgf8 and Shh, which are required to coordinate face and brain development. Thus, we propose that mis-splicing of transcripts that regulate P53 activity and craniofacial-specific genes contributes to craniofacial malformations.

This article has an associated First Person interview with the first author of the paper.

Summary: We report the first mouse model for cerebrocostomandibular syndrome, showing that mis-splicing of transcripts that regulate P53 activity and craniofacial-specific genes contributes to craniofacial malformations.

Effects of cigarette smoke exposure on a mouse model of multiple sclerosis

Multiple sclerosis (MS) is an inflammatory autoimmune disease associated with genetic and environmental factors. Cigarette smoking is harmful to health and may be one of the risk factors for MS. However, there have been no systematic investigations under controlled experimental conditions linking cigarette smoke (CS) and MS. The present study is the first inhalation study to correlate the pre-clinical and pathological manifestations affected by different doses of CS exposure in a mouse experimental autoimmune encephalomyelitis (EAE) model. Female C57BL/6 mice were whole-body exposed to either fresh air (sham) or three concentrations of CS from a reference cigarette (3R4F) for 2 weeks before and 4 weeks after EAE induction. The effects of exposure on body weight, clinical symptoms, spinal cord pathology, and serum biochemicals were then assessed. Exposure to low and medium concentrations of CS exacerbated the severity of symptoms and spinal cord pathology, while the high concentration had no effect relative to sham exposure in mice with EAE. Interestingly, the clinical chemistry parameters for metabolic profile as well as liver and renal function (e.g. triglycerides and creatinine levels, alkaline phosphatase activity) were lower in these mice than in naïve controls. Although the mouse EAE model does not fully recapitulate the pathology or symptoms of MS in humans, these findings largely corroborate previous epidemiological findings that exposure to CS can worsen the symptoms and pathology of MS. Furthermore, the study newly highlights the possible correlation of clinical chemistry findings such as metabolism and liver and renal function between MS patients and EAE mice.

•

Multiple sclerosis is an inflammatory autoimmune disease affected by many factors.

•

First inhalation study to correlate the different doses of cigarette smoke on MS.

•

Findings largely corroborate with previous epidemiological findings on CS exposure.

•

High concentration of CS had no observable effect on EAE, contrast to low and medium.

•

Potential correlation between MS and EAE model using clinical chemistry parameters.

Non-invasive breath collection in murine models using a newly developed sampling device

Volatile organic compounds (VOCs) in exhaled breath have the potential to be used as biomarkers for screening and diagnosis of diseases. Clinical studies are often complicated by both modifiable and non-modifiable factors influencing the composition of VOCs in exhaled breath. Small laboratory animal studies contribute in obtaining fundamental insight in alterations in VOC composition in exhaled breath and thereby facilitate the design and analysis of clinical research. However, long term animal experiments are often limited by invasive breath collection methods and terminal experiments. To overcome this problem, a novel device was developed for non-invasive breath collection in mice using glass nose-only restrainers thereby omitting the need of anesthetics. C57Bl/6J mice were used to test reproducibility and different air sampling settings for air-flow (ml/min) and time (minutes). Exhaled air was collected on desorption tubes and analysed for VOCs by gas chromatography time-of-flight mass spectrometry (GC-tof-MS). In total 27 compounds were putatively identified and used to assess the variability of the VOC measurements in the breath collections. Best reproducibility is obtained when using an air flow of 185 ml/min and a collection time of 20 minutes. Due to the non-invasive nature of breath collections in murine models, this device has the potential to facilitate VOC research in relation to disturbed metabolism and or disease pathways.

Bringing the Animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services

The Animal QTLdb (https://www.animalgenome.org/QTLdb) and CorrDB (https://www.animalgenome.org/CorrDB) are unique resources for livestock animal genetics and genomics research which have been used extensively by the international livestock genome research community. This is largely due to the active development of the databases over the years to keep up with the rapid advancement of genome sciences. The ongoing development has ensured that these databases provide researchers not only with continually updated data but also with new web tools to disseminate the data. Through our continued efforts, the databases have evolved from the original Pig QTLdb for cross-experiment QTL data comparisons to an Animal QTLdb hosting 220 401 QTL, SNP association and eQTL data linking phenotype to genotype for 2210 traits. In addition, there are 23 552 correlations for 866 traits and 4273 heritability data on 1069 traits in CorrDB. All these data were curated from 3157 publications that cover seven livestock species. Along with the continued data curation, new species, additional genome builds, and new functions and features have been built into the databases as well. Standardized procedures to support data mapping on multiple species/genome builds and the ability to browse data based on linked ontology terms are highlights of the recent developments.

Patterns and mechanisms of sex ratio distortion in the Collaborative Cross mouse mapping population

In species with single-locus, chromosome-based mechanisms of sex determination, the laws of segregation predict an equal ratio of females to males at birth. Here, we show that departures from this Mendelian expectation are commonplace in the 8-way recombinant inbred Collaborative Cross (CC) mouse population. More than one-third of CC strains exhibit significant sex ratio distortion (SRD) at wean, with twice as many male-biased than female-biased strains. We show that these pervasive sex biases persist across multiple breeding environments, are stable over time, and are not mediated by random maternal effects. SRD exhibits a heritable component, but QTL mapping analyses fail to nominate any large effect loci. These findings, combined with the reported absence of sex ratio biases in the CC founder strains, suggest that SRD manifests from multilocus combinations of alleles only uncovered in recombined CC genomes. We explore several potential complex genetic mechanisms for SRD, including allelic interactions leading to sex-biased lethality, genetic sex reversal, chromosome drive mediated by sex-linked selfish elements, and incompatibilities between specific maternal and paternal genotypes. We show that no one mechanism offers a singular explanation for this population-wide SRD. Instead, our data present preliminary evidence for the action of distinct mechanisms of SRD at play in different strains. Taken together, our work exposes the pervasiveness of SRD in the CC population and nominates the CC as a powerful resource for investigating diverse genetic causes of biased sex chromosome transmission.

Meta-analysis: Congruence of genomic and phenotypic differentiation across diverse natural study systems

Linking genotype to phenotype is a primary goal for understanding the genomic underpinnings of evolution. However, little work has explored whether patterns of linked genomic and phenotypic differentiation are congruent across natural study systems and traits. Here, we investigate such patterns with a meta-analysis of studies examining population-level differentiation at subsets of loci and traits putatively responding to divergent selection. We show that across the 31 studies (88 natural population-level comparisons) we examined, there was a moderate (R 2 = 0.39) relationship between genomic differentiation (F ST ) and phenotypic differentiation (P ST ) for loci and traits putatively under selection. This quantitative relationship between P ST and F ST for loci under selection in diverse taxa provides broad context and cross-system predictions for genomic and phenotypic adaptation by natural selection in natural populations. This context may eventually allow for more precise ideas of what constitutes "strong" differentiation, predictions about the effect size of loci, comparisons of taxa evolving in nonparallel ways, and more. On the other hand, links between P ST and F ST within studies were very weak, suggesting that much work remains in linking genomic differentiation to phenotypic differentiation at specific phenotypes. We suggest that linking genotypes to specific phenotypes can be improved by correlating genomic and phenotypic differentiation across a spectrum of diverging populations within a taxon and including wide coverage of both genomes and phenomes.

Genetic background determines behavioral responses during fear conditioning

Freezing behavior is used as a measure of a rodent's ability to learn during fear conditioning. However, it is possible that the expression of other behaviors may compete with freezing, particularly in rodent populations that have not been thoroughly studied in this context. Rearing and grooming are complex behaviors that are frequently exhibited by mice during fear conditioning. Both behaviors have been shown to be stress-sensitive, and the expression of these behaviors is dependent upon strain background. To better understand how genetic background impacts behavioral responses during fear conditioning, we examined freezing, rearing, and grooming frequencies prior to fear conditioning training and across different stages of fear conditioning testing in male mice from eight inbred mouse strains (C57BL/6J, DBA/2J, FVB/NJ, SWR/J, BTBR T + ltpr3Tf/J, SM/J, LP/J, 129S1/SvlmJ) that exhibited diverse freezing responses. We found that genetic background determined rearing and grooming expression throughout fear conditioning, and their patterns of expression across stages of fear conditioning were strain dependent. Using publicly available SNP data, we found that polymorphisms in Dab1, a gene that is implicated in both grooming and learning phenotypes, separated the strains with high contextual grooming from the others using a hierarchical clustering analysis. This suggested a potential genetic mechanism for the observed behavioral differences. These findings demonstrate that genetic background determines behavioral responses during fear conditioning and suggest that shared genetic substrates underlie fear conditioning behaviors.

Reduced Chronic Toxicity and Carcinogenicity in A/J Mice in Response to Life-Time Exposure to Aerosol From a Heated Tobacco Product Compared With Cigarette Smoke

We conducted an inhalation study, in accordance with Organisation for Economic Co-operation and Development Test Guideline 453, exposing A/J mice to tobacco heating system (THS) 2.2 aerosol or 3R4F reference cigarette smoke (CS) for up to 18 months to evaluate chronic toxicity and carcinogenicity. All exposed mice showed lower thymus and spleen weight, blood lymphocyte counts, and serum lipid concentrations than sham mice, most likely because of stress and/or nicotine effects. Unlike THS 2.2 aerosol-exposed mice, CS-exposed mice showed increased heart weight, changes in red blood cell profiles and serum liver function parameters. Similarly, increased pulmonary inflammation, altered lung function, and emphysematous changes were observed only in CS-exposed mice. Histopathological changes in other respiratory tract organs were significantly lower in the THS 2.2 aerosol-exposed groups than in the CS-exposed group. Chronic exposure to THS 2.2 aerosol also did not increase the incidence or multiplicity of bronchioloalveolar adenomas or carcinomas relative to sham, whereas CS exposure did. Male THS 2.2 aerosol-exposed mice had a lower survival rate than sham mice, related to an increased incidence of urogenital issues that appears to be related to congenital factors rather than test item exposure. The lower impact of THS 2.2 aerosol exposure on tumor development and chronic toxicity is consistent with the significantly reduced levels of harmful and potentially harmful constituents in THS 2.2 aerosol relative to CS. The totality of the evidence from this study further supports the risk reduction potential of THS 2.2 for lung diseases in comparison with cigarettes.

The Jackson Laboratory Nathan Shock Center: impact of genetic diversity on aging

Healthspan is a complex trait, influenced by many genes and environmental factors that accelerate or delay aging, reduce or increase disease risk, and extend or reduce lifespan. Thus, assessing the role of genetic variation in aging requires an experimental strategy capable of modeling the genetic and biological complexity of human populations. The goal of the The Jackson Laboratory Nathan Shock Center (JAX NSC) is to provide research resources and training for geroscience investigators that seek to understand the role of genetics and genetic diversity on the fundamental process of aging and diseases of human aging using the laboratory mouse as a model system. The JAX NSC has available novel, deeply characterized populations of aged mice, performs state-of-the-art phenotyping of age-relevant traits, provides systems genetics analysis of complex data sets, and provides all of these resources to the geroscience community. The aged animal resources, phenotyping capacity, and genetic expertise available through the JAX NSC benefit the geroscience community by fostering cutting-edge, novel lines of research that otherwise would not be possible. Over the past 15 years, the JAX NSC has transformed aging research across the geroscience community, providing aging mouse resources and tissues to researchers. All JAX NSC data and tools are publicly disseminated on the Mouse Phenome Database and the JAX NSC website, thus ensuring that the resources generated and expertise acquired through the Center are readily available to the aging research community. The JAX NSC will continue to enhance its ability to perform innovative research using a mammalian model to illuminate novel genotype-phenotype relationships and provide a rational basis for designing effective risk assessments and therapeutic interventions to boost longevity and disease-free healthspan.

In Vitro, In Vivo, and In Silico Methods for Assessment of Muscle Size and Muscle Growth Regulation

Trauma, burn injury, sepsis, and ischemia lead to acute and chronic loss of skeletal muscle mass and function. Healthy muscle is essential for eating, posture, respiration, reproduction, and mobility, as well as for appropriate function of the senses including taste, vision, and hearing. Beyond providing support and contraction, skeletal muscle also exerts essential roles in temperature regulation, metabolism, and overall health. As the primary reservoir for amino acids, skeletal muscle regulates whole-body protein and glucose metabolism by providing substrate for protein synthesis and supporting hepatic gluconeogenesis during illness and starvation. Overall, greater muscle mass is linked to greater insulin sensitivity and glucose disposal, strength, power, and longevity. In contrast, low muscle mass correlates with dysmetabolism, dysmobility, and poor survival. Muscle mass is highly plastic, appropriate to its role as reservoir, and subject to striking genetic control. Defining mechanisms of muscle growth regulation holds significant promise to find interventions that promote health and diminish morbidity and mortality after trauma, sepsis, inflammation, and other systemic insults. In this invited review, we summarize techniques and methods to assess and manipulate muscle size and muscle mass in experimental systems, including cell culture and rodent models. These approaches have utility for studies of myopenia, sarcopenia, cachexia, and acute muscle growth or atrophy in the setting of health or injury.

Human megakaryocytic microparticles induce de novo platelet biogenesis in a wild-type murine model

Platelet transfusions are used to treat idiopathic or drug-induced thrombocytopenia. Platelets are an expensive product in limited supply, with limited storage and distribution capabilities because they cannot be frozen. We have demonstrated that, in vitro, human megakaryocytic microparticles (huMkMPs) target human CD34+ hematopoietic stem and progenitor cells (huHSPCs) and induce their Mk differentiation and platelet biogenesis in the absence of thrombopoietin. In this study, we showed that, in vitro, huMkMPs can also target murine HSPCs (muHSPCs) to induce them to differentiate into megakaryocytes in the absence of thrombopoietin. Based on that, using wild-type BALB/c mice, we demonstrated that intravenously administering 2 × 106 huMkMPs triggered de novo murine platelet biogenesis to increase platelet levels up to 49% 16 hours after administration. huMkMPs also largely rescued low platelet levels in mice with induced thrombocytopenia 16 hours after administration by increasing platelet counts by 51%, compared with platelet counts in thrombocytopenic mice. Normalized on a tissue-mass basis, biodistribution experiments show that MkMPs localized largely to the bone marrow, lungs, and liver 24 hours after huMkMP administration. Beyond the bone marrow, CD41+ (megakaryocytes and Mk-progenitor) cells were frequent in lungs, spleen, and especially, liver. In the liver, infused huMKMPs colocalized with Mk progenitors and muHSPCs, thus suggesting that huMkMPs interact with muHSPCs in vivo to induce platelet biogenesis. Our data demonstrate the potential of huMkMPs, which can be stored frozen, to treat thrombocytopenias and serve as effective carriers for in vivo, target-specific cargo delivery to HSPCs.

High-throughput sleep phenotyping produces robust and heritable traits in Diversity Outbred mice and their founder strains

STUDY OBJECTIVES

This study describes high-throughput phenotyping strategies for sleep and circadian behavior in mice, including examinations of robustness, reliability, and heritability among Diversity Outbred (DO) mice and their eight founder strains.

METHODS

We performed high-throughput sleep and circadian phenotyping in male mice from the DO population (n = 338) and their eight founder strains: A/J (n = 6), C57BL/6J (n = 14), 129S1/SvlmJ (n = 6), NOD/LtJ (n = 6), NZO/H1LtJ (n = 6), CAST/EiJ (n = 8), PWK/PhJ (n = 8), and WSB/EiJ (n = 6). Using infrared beam break systems, we defined sleep as at least 40 s of continuous inactivity and quantified sleep-wake amounts and bout characteristics. We developed assays to measure sleep latency in a new environment and during a modified Murine Multiple Sleep Latency Test, and estimated circadian period from wheel-running experiments. For each trait, broad-sense heritability (proportion of variability explained by all genetic factors) was derived in founder strains, while narrow-sense heritability (proportion of variability explained by additive genetic effects) was calculated in DO mice.

RESULTS

Phenotypes were robust to different inactivity durations to define sleep. Differences across founder strains and moderate/high broad-sense heritability were observed for most traits. There was large phenotypic variability among DO mice, and phenotypes were reliable, although estimates of heritability were lower than in founder mice. This likely reflects important nonadditive genetic effects.

CONCLUSIONS

A high-throughput phenotyping strategy in mice, based primarily on monitoring of activity patterns, provides reliable and heritable estimates of sleep and circadian traits. This approach is suitable for discovery analyses in DO mice, where genetic factors explain some proportion of phenotypic variation.

Systems genetic analysis of nicotine withdrawal deficits in hippocampus-dependent learning

Cognitive deficits, such as disrupted learning, are a major symptom of nicotine withdrawal. These deficits are heritable, yet their genetic basis is largely unknown. Our lab has developed a mouse model of nicotine withdrawal deficits in learning, using chronic nicotine exposure via osmotic minipumps and fear conditioning. Here, we utilized the BXD genetic reference panel to identify genetic variants underlying nicotine withdrawal deficits in learning. Male and female mice (n = 6-11 per sex per strain, 31 strains) received either chronic saline or nicotine (6.3 mg/kg per day for 12 days), and were then tested for hippocampus-dependent learning deficits using contextual fear conditioning. Quantitative trait locus (QTL) mapping analyses using GeneNetwork identified a significant QTL on Chromosome 4 (82.13 Mb, LRS = 20.03, p < 0.05). Publicly available hippocampal gene expression data were used to identify eight positional candidates (Snacpc3, Mysm1, Rps6, Plaa, Lurap1l, Slc24a2, Hacd4, Ptprd) that overlapped with our behavioral QTL and correlated with our behavioral data. Overall, this study demonstrates that genetic factors impact cognitive deficits during nicotine withdrawal in the BXD recombinant inbred panel and identifies candidate genes for future research.

Transcriptional circuitry atlas of genetic diverse unstimulated murine and human macrophages define disparity in population-wide innate immunity

Macrophages are ubiquitous custodians of tissues, which play decisive role in maintaining cellular homeostasis through regulatory immune responses. Within tissues, macrophage exhibit extremely heterogeneous population with varying functions orchestrated through regulatory response, which can be further exacerbated in diverse genetic backgrounds. Gene regulatory networks (GRNs) offer comprehensive understanding of cellular regulatory behavior by unfolding the transcription factors (TFs) and regulated target genes. RNA-Seq coupled with ATAC-Seq has revolutionized the regulome landscape influenced by gene expression modeling. Here, we employ an integrative multi-omics systems biology-based analysis and generated GRNs derived from the unstimulated bone marrow-derived macrophages of five inbred genetically defined murine strains, which are reported to be linked with most of the population-wide human genetic variants. Our probabilistic modeling of a basal hemostasis pan regulatory repertoire in diverse macrophages discovered 96 TFs targeting 6279 genes representing 468,291 interactions across five inbred murine strains. Subsequently, we identify core and distinctive GRN sub-networks in unstimulated macrophages to describe the system-wide conservation and dissimilarities, respectively across five murine strains. Our study concludes that discrepancies in unstimulated macrophage-specific regulatory networks not only drives the basal functional plasticity within genetic backgrounds, additionally aid in understanding the complexity of racial disparity among the human population during stress.

In silico candidate variant and gene identification using inbred mouse strains

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

A Genetic Mouse Model Recapitulates Immune Checkpoint Inhibitor-Associated Myocarditis and Supports a Mechanism-Based Therapeutic Intervention

Immune checkpoint inhibitors (ICI) targeting CTLA4 or PD-1/PD-L1 have transformed cancer therapy but are associated with immune-related adverse events, including myocarditis. Here, we report a robust preclinical mouse model of ICI-associated myocarditis in which monoallelic loss of Ctla4 in the context of complete genetic absence of Pdcd1 leads to premature death in approximately half of mice. Premature death results from myocardial infiltration by T cells and macrophages and severe ECG abnormalities, closely recapitulating the clinical and pathologic hallmarks of ICI-associated myocarditis observed in patients. Using this model, we show that Ctla4 and Pdcd1 functionally interact in a gene dosage-dependent manner, providing a mechanism by which myocarditis arises with increased frequency in the setting of combination ICI therapy. We demonstrate that intervention with CTLA4-Ig (abatacept) is sufficient to ameliorate disease progression and additionally provide a case series of patients in which abatacept mitigates the fulminant course of ICI myocarditis. SIGNIFICANCE: We provide a preclinical model of ICI-associated myocarditis which recapitulates this clinical syndrome. Using this model, we demonstrate that CTLA4 and PD-1 (ICI targets) functionally interact for myocarditis development and that intervention with CTLA4-Ig (abatacept) attenuates myocarditis, providing mechanistic rationale and preclinical support for therapeutic clinical studies.See related commentary by Young and Bluestone, p. 537.This article is highlighted in the In This Issue feature, p. 521.

Biological sex, not reproductive cycle, influences peripheral blood immune cell prevalence in mice

KEY POINTS

Traditionally the female sex, compared with the male sex, has been perceived as having greater variability in many physiological traits, including within the immune system. We investigated effects of biological sex and the female reproductive cycle on numbers of circulating leukocytes in C57BL/6J mice. We show that biological sex, but not female reproductive cyclicity, has a significant effect on peripheral blood immune cell prevalence and variability, and that sex differences were not consistent amongst common inbred laboratory mouse strains. We found that male C57BL/6J mice, compared with female mice, have greater variability in peripheral blood immunophenotype, and that this was influenced by body weight. We created summary tables for researchers to facilitate experiment planning and sample size calculations for peripheral immune cells that consider the effects of biological sex.

ABSTRACT

Immunophenotyping (i.e. quantifying the number and types of circulating leukocytes) is used to characterize immune changes during health and disease, and in response to pharmacological and other interventions. Despite the importance of biological sex in immune function, there is considerable uncertainty amongst researchers as to the extent to which biological sex or the female reproductive cycle influence blood immunophenotype. We quantified circulating leukocytes by multicolour flow cytometry in young C57BL/6J mice and assessed the effects of the reproductive cycle, biological sex, and other experimental and biological factors on data variability. We found that there are no significant effects of the female reproductive cycle on the prevalence of peripheral blood B cells, NK cells, CD4⁺ T cells, CD8⁺ T cells, monocytes, or neutrophils. Immunophenotype composition and variability do not significantly change between stages of the female reproductive cycle. There are, however, sex-specific differences in immune cell prevalence, with fewer monocytes, neutrophils, and NK cells in female mice. Surprisingly, immunophenotype is more variable in male mice, and weight is a significant contributing factor. We provide tools for researchers to perform a priori sample size calculations for two-group and factorial analyses. We show that immunophenotype varies between inbred mouse strains, and that using equal sample sizes of male and female mice is not always appropriate for within-sex evaluations of immune cell populations in peripheral blood.

Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration

Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes.

The influence of sex and strain on trace element dysregulation in the brain due to diet-induced obesity

BACKGROUND

The objective of this study was to identify interaction effects between diet, sex, and strain on trace element dysregulation and gene expression alterations due to diet-induced obesity (DIO) in the hippocampus, striatum, and midbrain.

METHODS

Male and female C57BL/6 J (B6 J) and DBA/2 J (D2 J) mice were fed either a low fat (10 % kcal) diet (LFD) or high fat (60 % kcal) diet (HFD) for 16 weeks, then assessed for trace element concentrations and gene expression patterns in the brain.

RESULTS

In the hippocampus, zinc was significantly increased by 48 % in D2 J males but decreased by 44 % in D2 J females, and divalent metal transporter 1 was substantially upregulated in B6 J males due to DIO. In the striatum, iron was significantly elevated in B6 J female mice, and ceruloplasmin was significantly upregulated in D2 J female mice due to DIO. In the midbrain, D2 J males fed a HFD had a 48 % reduction in Cu compared to the LFD group, and D2 J females had a 37 % reduction in Cu compared to the control group.

CONCLUSIONS

The alteration of trace element homeostasis and gene expression due to DIO was brain-region dependent and was highly influenced by sex and strain. A significant three-way interaction between diet, sex, and strain was discovered for zinc in the hippocampus (for mice fed a HFD, zinc increased in male D2 Js, decreased in female D2 Js, and had no effect in B6 J mice). A significant diet by sex interaction was observed for iron in the striatum (iron increased only in female mice fed a HFD). A main effect of decreased copper in the midbrain was found for the D2 J strain fed a HFD. These results emphasize the importance of considering sex and genetics as biological factors when investigating potential associations between DIO and neurodegenerative disease.

System-level analyses of keystone genes required for mammalian tooth development

When a null mutation of a gene causes a complete developmental arrest, the gene is typically considered essential for life. Yet, in most cases, null mutations have more subtle effects on the phenotype. Here we used the phenotypic severity of mutations as a tool to examine system‐level dynamics of gene expression. We classify genes required for the normal development of the mouse molar into different categories that range from essential to subtle modification of the phenotype. Collectively, we call these the developmental keystone genes. Transcriptome profiling using microarray and RNAseq analyses of patterning stage mouse molars show highly elevated expression levels for genes essential for the progression of tooth development, a result reminiscent of essential genes in single‐cell organisms. Elevated expression levels of progression genes were also detected in developing rat molars, suggesting evolutionary conservation of this system‐level dynamics. Single‐cell RNAseq analyses of developing mouse molars reveal that even though the size of the expression domain, measured in the number of cells, is the main driver of organ‐level expression, progression genes show high cell‐level transcript abundances. Progression genes are also upregulated within their pathways, which themselves are highly expressed. In contrast, a high proportion of the genes required for normal tooth patterning are secreted ligands that are expressed in fewer cells than their receptors and intracellular components. Overall, even though expression patterns of individual genes can be highly different, conserved system‐level principles of gene expression can be detected using phenotypically defined gene categories.

The phenotypic severity of mutations on mouse teeth is used to classify genes.

Genes essential for the progression of odontogenesis are highly expressed at the organ and cell level.

Many of the genes required for normal patterning are locally expressed ligands.

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

Mouse Genome Database (MGD) 2019

The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the community model organism genetic and genome resource for the laboratory mouse. MGD is the authoritative source for biological reference data sets related to mouse genes, gene functions, phenotypes, and mouse models of human disease. MGD is the primary outlet for official gene, allele and mouse strain nomenclature based on the guidelines set by the International Committee on Standardized Nomenclature for Mice. In this report we describe significant enhancements to MGD, including two new graphical user interfaces: (i) the Multi Genome Viewer for exploring the genomes of multiple mouse strains and (ii) the Phenotype-Gene Expression matrix which was developed in collaboration with the Gene Expression Database (GXD) and allows researchers to compare gene expression and phenotype annotations for mouse genes. Other recent improvements include enhanced efficiency of our literature curation processes and the incorporation of Transcriptional Start Site (TSS) annotations from RIKEN's FANTOM 5 initiative.

Using Zebrafish to Analyze the Genetic and Environmental Etiologies of Congenital Heart Defects

Congenital heart defects (CHDs) are among the most common human birth defects. However, the etiology of a large proportion of CHDs remains undefined. Studies identifying the molecular and cellular mechanisms that underlie cardiac development have been critical to elucidating the origin of CHDs. Building upon this knowledge to understand the pathogenesis of CHDs requires examining how genetic or environmental stress changes normal cardiac development. Due to strong molecular conservation to humans and unique technical advantages, studies using zebrafish have elucidated both fundamental principles of cardiac development and have been used to create cardiac disease models. In this chapter we examine the unique toolset available to zebrafish researchers and how those tools are used to interrogate the genetic and environmental contributions to CHDs.

PATHBIO: an international training program for precision mouse phenotyping

Design and production of genetically engineered mouse strains by individual research laboratories, research teams, large-scale consortia, and the biopharmaceutical industry have magnified the need for qualified personnel to identify, annotate, and validate (phenotype) these potentially new mouse models of human disease. The PATHBIO project has been recently established and funded by the European Union's ERASMUS+ Knowledge Alliance program to address the current shortfall in formally trained personnel. A series of teaching workshops will be given by experts on anatomy, histology, embryology, imaging, and comparative pathology to increase the availability of individuals with formal training to contribute to this important niche of Europe's biomedical research enterprise. These didactic and hands-on workshops are organized into three modules: (1) embryology, anatomy, histology, and the anatomical basis of imaging, (2) image-based phenotyping, and (3) pathology. The workshops are open to all levels of participants from recent graduates to Ph.D., M.D., and veterinary scientists. Participation is available on a competitive basis at no cost for attending. The first series of Workshop Modules was held in 2019 and these will continue for the next 2 years.

A comprehensive and comparative phenotypic analysis of the collaborative founder strains identifies new and known phenotypes

The collaborative cross (CC) is a large panel of mouse-inbred lines derived from eight founder strains (NOD/ShiLtJ, NZO/HILtJ, A/J, C57BL/6J, 129S1/SvImJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Here, we performed a comprehensive and comparative phenotyping screening to identify phenotypic differences and similarities between the eight founder strains. In total, more than 300 parameters including allergy, behavior, cardiovascular, clinical blood chemistry, dysmorphology, bone and cartilage, energy metabolism, eye and vision, immunology, lung function, neurology, nociception, and pathology were analyzed; in most traits from sixteen females and sixteen males. We identified over 270 parameters that were significantly different between strains. This study highlights the value of the founder and CC strains for phenotype-genotype associations of many genetic traits that are highly relevant to human diseases. All data described here are publicly available from the mouse phenome database for analyses and downloads.

Network-Based Functional Prediction Augments Genetic Association To Predict Candidate Genes for Histamine Hypersensitivity in Mice

Genetic mapping is a primary tool of genetics in model organisms; however, many quantitative trait loci (QTL) contain tens or hundreds of positional candidate genes. Prioritizing these genes for validation is often ad hoc and biased by previous findings. Here we present a technique for prioritizing positional candidates based on computationally inferred gene function. Our method uses machine learning with functional genomic networks, whose links encode functional associations among genes, to identify network-based signatures of functional association to a trait of interest. We demonstrate the method by functionally ranking positional candidates in a large locus on mouse Chr 6 (45.9 Mb to 127.8 Mb) associated with histamine hypersensitivity (Histh). Histh is characterized by systemic vascular leakage and edema in response to histamine challenge, which can lead to multiple organ failure and death. Although Histh risk is strongly influenced by genetics, little is known about its underlying molecular or genetic causes, due to genetic and physiological complexity of the trait. To dissect this complexity, we ranked genes in the Histh locus by predicting functional association with multiple Histh-related processes. We integrated these predictions with new single nucleotide polymorphism (SNP) association data derived from a survey of 23 inbred mouse strains and congenic mapping data. The top-ranked genes included Cxcl12, Ret, Cacna1c, and Cntn3, all of which had strong functional associations and were proximal to SNPs segregating with Histh. These results demonstrate the power of network-based computational methods to nominate highly plausible quantitative trait genes even in challenging cases involving large QTL and extreme trait complexity.

Computational tools for geroscience

The rapid progress of the past three decades has led the geroscience field near a point where human interventions in aging are plausible. Advances across scientific areas, such as high throughput "-omics" approaches, have led to an exponentially increasing quantity of data available for biogerontologists. To best translate the lifespan and healthspan extending interventions discovered by basic scientists into preventative medicine, it is imperative that the current data are comprehensively utilized to generate testable hypotheses about translational interventions. Building a translational pipeline for geroscience will require both systematic efforts to identify interventions that extend healthspan across taxa and diagnostics that can identify patients who may benefit from interventions prior to the onset of an age-related morbidity. Databases and computational tools that organize and analyze both the wealth of information available on basic biogerontology research and clinical data on aging populations will be critical in developing such a pipeline. Here, we review the current landscape of databases and computational resources available for translational aging research. We discuss key platforms and tools available for aging research, with a focus on how each tool can be used in concert with hypothesis driven experiments to move closer to human interventions in aging.

A multi-omics digital research object for the genetics of sleep regulation

With the aim to uncover the molecular pathways underlying the regulation of sleep, we recently assembled an extensive and comprehensive systems genetics dataset interrogating a genetic reference population of mice at the levels of the genome, the brain and liver transcriptomes, the plasma metabolome, and the sleep-wake phenome. To facilitate a meaningful and efficient re-use of this public resource by others we designed, describe in detail, and made available a Digital Research Object (DRO), embedding data, documentation, and analytics. We present and discuss both the advantages and limitations of our multi-modal resource and analytic pipeline. The reproducibility of the results was tested by a bioinformatician not implicated in the original project and the robustness of results was assessed by re-annotating genetic and transcriptome data from the mm9 to the mm10 mouse genome assembly.

A natural mouse model reveals genetic determinants of systemic capillary leak syndrome (Clarkson disease)

The systemic capillary leak syndrome (SCLS, Clarkson disease) is a disorder of unknown etiology characterized by recurrent episodes of vascular leakage of proteins and fluids into peripheral tissues, resulting in whole-body edema and hypotensive shock. The pathologic mechanisms and genetic basis for SCLS remain elusive. Here we identify an inbred mouse strain, SJL, which recapitulates cardinal features of SCLS, including susceptibility to histamine- and infection-triggered vascular leak. We named this trait "Histamine hypersensitivity" (Hhs/Hhs) and mapped it to Chromosome 6. Hhs is syntenic to the genomic locus most strongly associated with SCLS in humans (3p25.3), revealing that the predisposition to develop vascular hyperpermeability has a strong genetic component conserved between humans and mice and providing a naturally occurring animal model for SCLS. Genetic analysis of Hhs may reveal orthologous candidate genes that contribute not only to SCLS, but also to normal and dysregulated mechanisms underlying vascular barrier function more generally.

Genetic mapping in Diversity Outbred mice identifies a Trpa1 variant influencing late-phase formalin response

Identification of genetic variants that influence susceptibility to pain is key to identifying molecular mechanisms and targets for effective and safe therapeutic alternatives to opioids. To identify genes and variants associated with persistent pain, we measured late-phase response to formalin injection in 275 male and female Diversity Outbred mice genotyped for over 70,000 single nucleotide polymorphisms. One quantitative trait locus reached genome-wide significance on chromosome 1 with a support interval of 3.1 Mb. This locus, Nociq4 (nociceptive sensitivity quantitative trait locus 4; MGI: 5661503), harbors the well-known pain gene Trpa1 (transient receptor potential cation channel, subfamily A, member 1). Trpa1 is a cation channel known to play an important role in acute and chronic pain in both humans and mice. Analysis of Diversity Outbred founder strain allele effects revealed a significant effect of the CAST/EiJ allele at Trpa1, with CAST/EiJ carrier mice showing an early, but not late, response to formalin relative to carriers of the 7 other inbred founder alleles (A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ). We characterized possible functional consequences of sequence variants in Trpa1 by assessing channel conductance, TRPA1-TRPV1 interactions, and isoform expression. The phenotypic differences observed in CAST/EiJ relative to C57BL/6J carriers were best explained by Trpa1 isoform expression differences, implicating a splice junction variant as the causal functional variant. This study demonstrates the utility of advanced, high-precision genetic mapping populations in resolving specific molecular mechanisms of variation in pain sensitivity.

Gene-by-environment interactions in Alzheimer's disease and Parkinson's disease

Diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) arise from complex interactions of genetic and environmental factors, with genetic variants regulating individual responses to environmental exposures (i.e. gene-by-environment interactions). Identifying gene-by-environment interactions will be critical to fully understanding disease mechanisms and developing personalized therapeutics, though these interactions are still poorly understood and largely under-studied. Candidate gene approaches have shown that known disease risk variants often regulate response to environmental factors. However, recent improvements in exposome- and genome-wide association and interaction studies in humans and mice are enabling discovery of novel genetic variants and pathways that predict response to a variety of environmental factors. Here, we highlight recent approaches and ongoing developments in human and rodent studies to identify genetic modulators of environmental factors using AD and PD as exemplars. Identifying gene-by-environment interactions in disease will be critical to developing personalized intervention strategies and will pave the way for precision medicine.

Dusp6 is a genetic modifier of growth through enhanced ERK activity

Like other single-gene disorders, muscular dystrophy displays a range of phenotypic heterogeneity even with the same primary mutation. Identifying genetic modifiers capable of altering the course of muscular dystrophy is one approach to deciphering gene-gene interactions that can be exploited for therapy development. To this end, we used an intercross strategy in mice to map modifiers of muscular dystrophy. We interrogated genes of interest in an interval on mouse chromosome 10 associated with body mass in muscular dystrophy as skeletal muscle contributes significantly to total body mass. Using whole-genome sequencing of the two parental mouse strains combined with deep RNA sequencing, we identified the Met62Ile substitution in the dual-specificity phosphatase 6 (Dusp6) gene from the DBA/2 J (D2) mouse strain. DUSP6 is a broadly expressed dual-specificity phosphatase protein, which binds and dephosphorylates extracellular-signal-regulated kinase (ERK), leading to decreased ERK activity. We found that the Met62Ile substitution reduced the interaction between DUSP6 and ERK resulting in increased ERK phosphorylation and ERK activity. In dystrophic muscle, DUSP6 Met62Ile is strongly upregulated to counteract its reduced activity. We found that myoblasts from the D2 background were insensitive to a specific small molecule inhibitor of DUSP6, while myoblasts expressing the canonical DUSP6 displayed enhanced proliferation after exposure to DUSP6 inhibition. These data identify DUSP6 as an important regulator of ERK activity in the setting of muscle growth and muscular dystrophy.

A Diallel of the Mouse Collaborative Cross Founders Reveals Strong Strain-Specific Maternal Effects on Litter Size

Reproductive success in the eight founder strains of the Collaborative Cross (CC) was measured using a diallel-mating scheme. Over a 48-month period we generated 4,448 litters, and provided 24,782 weaned pups for use in 16 different published experiments. We identified factors that affect the average litter size in a cross by estimating the overall contribution of parent-of-origin, heterosis, inbred, and epistatic effects using a Bayesian zero-truncated overdispersed Poisson mixed model. The phenotypic variance of litter size has a substantial contribution (82%) from unexplained and environmental sources, but no detectable effect of seasonality. Most of the explained variance was due to additive effects (9.2%) and parental sex (maternal vs. paternal strain; 5.8%), with epistasis accounting for 3.4%. Within the parental effects, the effect of the dam's strain explained more than the sire's strain (13.2% vs. 1.8%), and the dam's strain effects account for 74.2% of total variation explained. Dams from strains C57BL/6J and NOD/ShiLtJ increased the expected litter size by a mean of 1.66 and 1.79 pups, whereas dams from strains WSB/EiJ, PWK/PhJ, and CAST/EiJ reduced expected litter size by a mean of 1.51, 0.81, and 0.90 pups. Finally, there was no strong evidence for strain-specific effects on sex ratio distortion. Overall, these results demonstrate that strains vary substantially in their reproductive ability depending on their genetic background, and that litter size is largely determined by dam's strain rather than sire's strain effects, as expected. This analysis adds to our understanding of factors that influence litter size in mammals, and also helps to explain breeding successes and failures in the extinct lines and surviving CC strains.

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

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

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

Significant Strain Variation in the Mutation Spectra of Inbred Laboratory Mice

Mutation provides the ultimate source of all new alleles in populations, including variants that cause disease and fuel adaptation. Recent whole genome sequencing studies have uncovered variation in the mutation rate among individuals and differences in the relative frequency of specific nucleotide changes (the mutation spectrum) between populations. Although parental age is a major driver of differences in overall mutation rate among individuals, the causes of variation in the mutation spectrum remain less well understood. Here, I use high-quality whole genome sequences from 29 inbred laboratory mouse strains to explore the root causes of strain variation in the mutation spectrum. My analysis leverages the unique, mosaic patterns of genetic relatedness among inbred mouse strains to identify strain private variants residing on haplotypes shared between multiple strains due to their recent descent from a common ancestor. I show that these strain-private alleles are strongly enriched for recent de novo mutations and lack signals of widespread purifying selection, suggesting their faithful recapitulation of the spontaneous mutation landscape in single strains. The spectrum of strain-private variants varies significantly among inbred mouse strains reared under standardized laboratory conditions. This variation is not solely explained by strain differences in age at reproduction, raising the possibility that segregating genetic differences affect the constellation of new mutations that arise in a given strain. Collectively, these findings imply the action of remarkably precise nucleotide-specific genetic mechanisms for tuning the de novo mutation landscape in mammals and underscore the genetic complexity of mutation rate control.

Robust mouse tracking in complex environments using neural networks

The ability to track animals accurately is critical for behavioral experiments. For video-based assays, this is often accomplished by manipulating environmental conditions to increase contrast between the animal and the background in order to achieve proper foreground/background detection (segmentation). Modifying environmental conditions for experimental scalability opposes ethological relevance. The biobehavioral research community needs methods to monitor behaviors over long periods of time, under dynamic environmental conditions, and in animals that are genetically and behaviorally heterogeneous. To address this need, we applied a state-of-the-art neural network-based tracker for single mice. We compare three different neural network architectures across visually diverse mice and different environmental conditions. We find that an encoder-decoder segmentation neural network achieves high accuracy and speed with minimal training data. Furthermore, we provide a labeling interface, labeled training data, tuned hyperparameters, and a pretrained network for the behavior and neuroscience communities.

Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies

Data are increasingly annotated with multiple ontologies to capture rich information about the features of the subject under investigation. Analysis may be performed over each ontology separately, but recently there has been a move to combine multiple ontologies to provide more powerful analytical possibilities. However, it is often not clear how to combine ontologies or how to assess or evaluate the potential design patterns available. Here we use a large and well-characterized dataset of anatomic pathology descriptions from a major study of aging mice. We show how different design patterns based on the MPATH and MA ontologies provide orthogonal axes of analysis, and perform differently in over-representation and semantic similarity applications. We discuss how such a data-driven approach might be used generally to generate and evaluate ontology design patterns.

Precision epidemiology for infectious disease control

Advances in genomics and computing are transforming the capacity for the characterization of biological systems, and researchers are now poised for a precision-focused transformation in the way they prepare for, and respond to, infectious diseases. This includes the use of genome-based approaches to inform molecular diagnosis and individual-level treatment regimens. In addition, advances in the speed and granularity of pathogen genome generation have improved the capability to track and understand pathogen transmission, leading to potential improvements in the design and implementation of population-level public health interventions. In this Perspective, we outline several trends that are driving the development of precision epidemiology of infectious disease and their implications for scientists' ability to respond to outbreaks.

Mean-Variance QTL Mapping Identifies Novel QTL for Circadian Activity and Exploratory Behavior in Mice

We illustrate, through two case studies, that "mean-variance QTL mapping"-QTL mapping that models effects on the mean and the variance simultaneously-can discover QTL that traditional interval mapping cannot. Mean-variance QTL mapping is based on the double generalized linear model, which extends the standard linear model used in interval mapping by incorporating not only a set of genetic and covariate effects for mean but also set of such effects for the residual variance. Its potential for use in QTL mapping has been described previously, but it remains underutilized, with certain key advantages undemonstrated until now. In the first case study, a reduced complexity intercross of C57BL/6J and C57BL/6N mice examining circadian behavior, our reanalysis detected a mean-controlling QTL for circadian wheel running activity that interval mapping did not; mean-variance QTL mapping was more powerful than interval mapping at the QTL because it accounted for the fact that mice homozygous for the C57BL/6N allele had less residual variance than other mice. In the second case study, an intercross between C57BL/6J and C58/J mice examining anxiety-like behaviors, our reanalysis detected a variance-controlling QTL for rearing behavior; interval mapping did not identify this QTL because it does not target variance QTL. We believe that the results of these reanalyses, which in other respects largely replicated the original findings, support the use of mean-variance QTL mapping as standard practice.

Two Novel Candidate Genes for Insulin Secretion Identified by Comparative Genomics of Multiple Backcross Mouse Populations

To identify novel disease genes for type 2 diabetes (T2D) we generated two backcross populations of obese and diabetes-susceptible New Zealand Obese (NZO/HI) mice with the two lean mouse strains 129P2/OlaHsd and C3HeB/FeJ. Subsequent whole-genome linkage scans revealed 30 novel quantitative trait loci (QTL) for T2D-associated traits. The strongest association with blood glucose [12 cM, logarithm of the odds (LOD) 13.3] and plasma insulin (17 cM, LOD 4.8) was detected on proximal chromosome 7 (designated Nbg7p, NZO blood glucose on proximal chromosome 7) exclusively in the NZOxC3H crossbreeding, suggesting that the causal gene is contributed by the C3H genome. Introgression of the critical C3H fragment into the genetic NZO background by generating recombinant congenic strains and metabolic phenotyping validated the phenotype. For the detection of candidate genes in the critical region (30-46 Mb), we used a combined approach of haplotype and gene expression analysis to search for C3H-specific gene variants in the pancreatic islets, which appeared to be the most likely target tissue for the QTL. Two genes, Atp4a and Pop4, fulfilled the criteria from our candidate gene approaches. The knockdown of both genes in MIN6 cells led to decreased glucose-stimulated insulin secretion, indicating a regulatory role of both genes in insulin secretion, thereby possibly contributing to the phenotype linked to Nbg7p In conclusion, our combined- and comparative-cross analysis approach has successfully led to the identification of two novel diabetes susceptibility candidate genes, and thus has been proven to be a valuable tool for the discovery of novel disease genes.

Chemical-Induced Phenotypes at CTD Help Inform the Predisease State and Construct Adverse Outcome Pathways

The Comparative Toxicogenomics Database (CTD; http://ctdbase.org) is a public resource that manually curates the scientific literature to provide content that illuminates the molecular mechanisms by which environmental exposures affect human health. We introduce our new chemical-phenotype module that describes how chemicals can affect molecular, cellular, and physiological phenotypes. At CTD, we operationally distinguish between phenotypes and diseases, wherein a phenotype refers to a nondisease biological event: eg, decreased cell cycle arrest (phenotype) versus liver cancer (disease), increased fat cell proliferation (phenotype) versus morbid obesity (disease), etc. Chemical-phenotype interactions are expressed in a formal structured notation using controlled terms for chemicals, phenotypes, taxon, and anatomical descriptors. Combining this information with CTD's chemical-disease module allows inferences to be made between phenotypes and diseases, yielding potential insight into the predisease state. Integration of all 4 CTD modules furnishes unique opportunities for toxicologists to generate computationally predictive adverse outcome pathways, linking chemical-gene molecular initiating events with phenotypic key events, adverse diseases, and population-level health outcomes. As examples, we present 3 diverse case studies discerning the effect of vehicle emissions on altered leukocyte migration, the role of cadmium in influencing phenotypes preceding Alzheimer disease, and the connection of arsenic-induced glucose metabolic phenotypes with diabetes. To date, CTD contains over 165 000 interactions that connect more than 6400 chemicals to 3900 phenotypes for 760 anatomical terms in 215 species, from over 19 000 scientific articles. To our knowledge, this is the first comprehensive set of manually curated, literature-based, contextualized, chemical-induced, nondisease phenotype data provided to the public.

Analysis of Genetically Diverse Macrophages Reveals Local and Domain-wide Mechanisms that Control Transcription Factor Binding and Function

Non-coding genetic variation is a major driver of phenotypic diversity and allows the investigation of mechanisms that control gene expression. Here, we systematically investigated the effects of >50 million variations from five strains of mice on mRNA, nascent transcription, transcription start sites, and transcription factor binding in resting and activated macrophages. We observed substantial differences associated with distinct molecular pathways. Evaluating genetic variation provided evidence for roles of ∼100 TFs in shaping lineage-determining factor binding. Unexpectedly, a substantial fraction of strain-specific factor binding could not be explained by local mutations. Integration of genomic features with chromatin interaction data provided evidence for hundreds of connected cis-regulatory domains associated with differences in transcription factor binding and gene expression. This system and the >250 datasets establish a substantial new resource for investigation of how genetic variation affects cellular phenotypes.