High-resolution genetic mapping in the diversity outbred mouse population identifies Apobec1 as a candidate gene for atherosclerosis

Specific circulating miRNAs are associated with plasma lipids in a healthy American cohort

Low-density lipoprotein cholesterol (LDL-c) is both a therapeutic target and a risk factor for cardiovascular disease (CVD). MicroRNA (miRNA) has been shown to regulate cholesterol homeostasis, and miRNA in blood circulation has been linked to hypercholesterolemia. However, few studies to date have associated miRNA with phenotypes like LDL-c in a healthy population. To this end, we analyzed circulating miRNA in relation to LDL-c in a healthy cohort of 353 participants using two separate bioinformatic approaches. The first approach found that miR-15b-5p and miR-16-5p were upregulated in individuals with at-risk levels of LDL-c. The second approach identified two miRNA clusters, one that positively and a second that negatively correlated with LDL-c. Included in the cluster that positively correlated with LDL-c were miR-15b-5p and miR-16-5p, as well as other miRNA from the miR-15/107, miR-30, and let-7 families. Cross-species analyses suggested that several miRNAs that associated with LDL-c are conserved between mice and humans. Finally, we examined the influence of diet on circulating miRNA. Our results robustly linked circulating miRNA with LDL-c, suggesting that miRNA could be used as biomarkers for hypercholesterolemia or targets for developing cholesterol-lowering drugs.NEW & NOTEWORTHY This study explored the association between circulating microRNA (miRNA) and low-density lipoprotein cholesterol (LDL-c) in a healthy population of 353 participants. Two miRNAs, miR-15b-5p and miR-16-5p, were upregulated in individuals with at-risk LDL-c levels. Several miRNA clusters were positively and negatively correlated with LDL-c and are known to target mRNA involved in lipid metabolism. The study also investigated the influence of diet on circulating miRNA, suggesting potential biomarkers for hypercholesterolemia.

Genetic variation modulates susceptibility to aberrant DNA hypomethylation and imprint deregulation in naïve pluripotent stem cells

Naïve pluripotent stem cells (nPSC) frequently undergo pathological and not readily reversible loss of DNA methylation marks at imprinted gene loci. This abnormality poses a hurdle for using pluripotent cell lines in biomedical applications and underscores the need to identify the causes of imprint instability in these cells. We show that nPSCs from inbred mouse strains exhibit pronounced strain-specific susceptibility to locus-specific deregulation of imprinting marks during reprogramming to pluripotency and upon culture with MAP kinase inhibitors, a common approach to maintain naïve pluripotency. Analysis of genetically highly diverse nPSCs from the Diversity Outbred (DO) stock confirms that genetic variation is a major determinant of epigenome stability in pluripotent cells. We leverage the variable DNA hypomethylation in DO lines to identify several trans-acting quantitative trait loci (QTLs) that determine epigenome stability at either specific target loci or genome-wide. Candidate factors encoded by two multi-target QTLs on chromosomes 4 and 17 suggest specific transcriptional regulators that contribute to DNA methylation maintenance in nPSCs. We propose that genetic variants represent candidate biomarkers to identify pluripotent cell lines with desirable properties and might serve as entry points for the targeted engineering of nPSCs with stable epigenomes.

Highlights

Naïve pluripotent stem cells from distinct inbred mouse strains exhibit variable DNA methylation levels at imprinted gene loci.The vulnerability of pluripotent stem cells to loss of genomic imprinting caused by MAP kinase inhibition strongly differs between inbred mouse strains.Genetically diverse pluripotent stem cell lines from Diversity Outbred mouse stock allow the identification of quantitative trait loci controlling DNA methylation stability.Genetic variants may serve as biomarkers to identify naïve pluripotent stem cell lines that are epigenetically stable in specific culture conditions.

Identification of genetic drivers of plasma lipoprotein size in the Diversity Outbred mouse population

Despite great progress in understanding lipoprotein physiology, there is still much to be learned about the genetic drivers of lipoprotein abundance, composition, and function. We used ion mobility spectrometry to survey 16 plasma lipoprotein subfractions in 500 Diversity Outbred mice maintained on a Western-style diet. We identified 21 quantitative trait loci (QTL) affecting lipoprotein abundance. To refine the QTL and link them to disease risk in humans, we asked if the human homologs of genes located at each QTL were associated with lipid traits in human genome-wide association studies. Integration of mouse QTL with human genome-wide association studies yielded candidate gene drivers for 18 of the 21 QTL. This approach enabled us to nominate the gene encoding the neutral ceramidase, Asah2, as a novel candidate driver at a QTL on chromosome 19 for large HDL particles (HDL-2b). To experimentally validate Asah2, we surveyed lipoproteins in Asah2-/- mice. Compared to wild-type mice, female Asah2-/- mice showed an increase in several lipoproteins, including HDL. Our results provide insights into the genetic regulation of circulating lipoproteins, as well as mechanisms by which lipoprotein subfractions may affect cardiovascular disease risk in humans.

Integrative analysis of hepatic transcriptional profiles reveals genetic regulation of atherosclerosis in hyperlipidemic Diversity Outbred-F1 mice

Atherogenesis is an insipidus but precipitating process leading to serious consequences of many cardiovascular diseases (CVD). Numerous genetic loci contributing to atherosclerosis have been identified in human genome-wide association studies, but these studies have limitations in the ability to control environmental factors and to decipher cause/effect relationships. To assess the power of hyperlipidemic Diversity Outbred (DO) mice in facilitating quantitative trait loci (QTL) analysis of complex traits, we generated a high-resolution genetic panel of atherosclerosis susceptible (DO-F1) mouse cohort by crossing 200 DO females with C57BL/6J males carrying two human genes: encoding apolipoprotein E3-Leiden and cholesterol ester transfer protein. We examined atherosclerotic traits including plasma lipids and glucose in the 235 female and 226 male progeny before and after 16 weeks of a high-fat/cholesterol diet, and aortic plaque size at 24 weeks. We also assessed the liver transcriptome using RNA-sequencing. Our QTL mapping for atherosclerotic traits identified one previously reported female-specific QTL on Chr10 with a narrower interval of 22.73 to 30.80 Mb, and one novel male-specific QTL at 31.89 to 40.25 Mb on Chr19. Liver transcription levels of several genes within each QTL were highly correlated with the atherogenic traits. A majority of these candidates have already known atherogenic potential in humans and/or mice, but integrative QTL, eQTL, and correlation analyses further pointed Ptprk as a major candidate of the Chr10 QTL, while Pten and Cyp2c67 of the Chr19 QTL in our DO-F1 cohort. Finally, through additional analyses of RNA-seq data we identified genetic regulation of hepatic transcription factors, including Nr1h3, contributes to atherogenesis in this cohort. Thus, an integrative approach using DO-F1 mice effectively validates the influence of genetic factors on atherosclerosis in DO mice and suggests an opportunity to discover therapeutics in the setting of hyperlipidemia.

The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases

Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.

Integrative systems analysis identifies genetic and dietary modulators of bile acid homeostasis

Bile acids (BAs) are complex and incompletely understood enterohepatic-derived hormones that control whole-body metabolism. Here, we profiled postprandial BAs in the liver, feces, and plasma of 360 chow- or high-fat-diet-fed BXD male mice and demonstrated that both genetics and diet strongly influence BA abundance, composition, and correlation with metabolic traits. Through an integrated systems approach, we mapped hundreds of quantitative trait loci that modulate BAs and identified both known and unknown regulators of BA homeostasis. In particular, we discovered carboxylesterase 1c (Ces1c) as a genetic determinant of plasma tauroursodeoxycholic acid (TUDCA), a BA species with established disease-preventing actions. The association between Ces1c and plasma TUDCA was validated using data from independent mouse cohorts and a Ces1c knockout mouse model. Collectively, our data are a unique resource to dissect the physiological importance of BAs as determinants of metabolic traits, as underscored by the identification of CES1C as a master regulator of plasma TUDCA levels.

Modeling human heterogeneity of obesity with diversity outbred mice reveals a fat mass-dependent therapeutic window for resolvin E1

Resolvin E1 (RvE1), a specialized pro-resolving mediator (SPM), improves glucose homeostasis in inbred mouse models of obesity. However, an impediment toward translation is that obesity is a highly heterogenous disease in which individuals will respond very differently to interventions such as RvE1. Thus, there is a need to study SPMs in the context of modeling the heterogeneity of obesity that is observed in humans. We investigated how RvE1 controls the concentration of key circulating metabolic biomarkers using diversity outbred (DO) mice, which mimic human heterogeneity. We first demonstrate that weights of DO mice can be classified into distinct distributions of fat mass (i.e., modeling differing classes of obesity) in response to a high-fat diet and in the human population when examining body composition. Next, we show RvE1 administration based on body weight for four consecutive days after giving mice a high-fat diet led to approximately half of the mice responding positively for serum total gastric inhibitory polypeptide (GIP), glucagon, insulin, glucose, leptin, and resistin. Interestingly, RvE1 improved hyperleptinemia most effectively in the lowest class of fat mass despite adjusting the dose of RvE1 with increasing adiposity. Furthermore, leptin levels after RvE1 treatment were the lowest in those mice that were also RvE1 positive responders for insulin and resistin. Collectively, these results suggest a therapeutic fat mass-dependent window for RvE1, which should be considered in future clinical trials. Moreover, the data underscore the importance of studying SPMs with heterogenous mice as a step toward precision SPM administration in humans.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Designing Relevant Preclinical Rodent Models for Studying Links Between Nutrition, Obesity, Metabolism, and Cancer

Diet and nutrition are intricately related to cancer prevention, growth, and treatment response. Preclinical rodent models are a cornerstone to biomedical research and remain instrumental in our understanding of the relationship between cancer and diet and in the development of effective therapeutics. However, the success rate of translating promising findings from the bench to the bedside is suboptimal. Well-designed rodent models will be crucial to improving the impact basic science has on clinical treatment options. This review discusses essential experimental factors to consider when designing a preclinical cancer model with an emphasis on incorporating these models into studies interrogating diet, nutrition, and metabolism. The aims of this review are to (a) provide insight into relevant considerations when designing cancer models for obesity, nutrition, and metabolism research; (b) identify common pitfalls when selecting a rodent model; and (c) discuss strengths and limitations of available preclinical models. Expected final online publication date for the Annual Review of Nutrition, Volume 41 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Genetic architecture modulates diet-induced hepatic mRNA and miRNA expression profiles in Diversity Outbred mice

Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Finally, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility

Heritability of fat distributions in male mice from the founder strains of the Diversity Outbred mouse population

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

Hepatic transcriptional profile reveals the role of diet and genetic backgrounds on metabolic traits in female progenitor strains of the Collaborative Cross

Mice have provided critical mechanistic understandings of clinical traits underlying metabolic syndrome (MetSyn) and susceptibility to MetSyn in mice is known to vary among inbred strains. We investigated the diet- and strain-dependent effects on metabolic traits in the eight Collaborative Cross (CC) founder strains (A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Liver transcriptomics analysis showed that both atherogenic diet and host genetics have profound effects on the liver transcriptome, which may be related to differences in metabolic traits observed between strains. We found strain differences in circulating trimethylamine N-oxide (TMAO) concentration and liver triglyceride content, both of which are traits associated with metabolic diseases. Using a network approach, we identified a module of transcripts associated with TMAO and liver triglyceride content, which was enriched in functional pathways. Interrogation of the module related to metabolic traits identified NADPH oxidase 4 (Nox4), a gene for a key enzyme in the production of reactive oxygen species, which showed a strong association with plasma TMAO and liver triglyceride. Interestingly, Nox4 was identified as the highest expressed in the C57BL/6J and NZO/HILtJ strains and the lowest expressed in the CAST/EiJ strain. Based on these results, we suggest that there may be genetic variation in the contribution of Nox4 to the regulation of plasma TMAO and liver triglyceride content. In summary, we show that liver transcriptomic analysis identified diet- or strain-specific pathways for metabolic traits in the Collaborative Cross (CC) founder strains.

Synergizing Mouse and Human Studies to Understand the Heterogeneity of Obesity

Obesity is routinely considered as a single disease state, which drives a "one-size-fits-all" approach to treatment. We recently convened the first annual University of North Carolina Interdisciplinary Nutrition Sciences Symposium to discuss the heterogeneity of obesity and the need for translational science to advance understanding of this heterogeneity. The symposium aimed to advance scientific rigor in translational studies from animal to human models with the goal of identifying underlying mechanisms and treatments. In this review, we discuss fundamental gaps in knowledge of the heterogeneity of obesity ranging from cellular to population perspectives. We also advocate approaches to overcoming limitations in the field. Examples include the use of contemporary mouse genetic reference population models such as the Collaborative Cross and Diversity Outbred mice that effectively model human genetic diversity and the use of translational models that integrate -omics and computational approaches from pre-clinical to clinical models of obesity. Finally, we suggest best scientific practices to ensure strong rigor that will allow investigators to delineate the sources of heterogeneity in the population with obesity. Collectively, we propose that it is critical to think of obesity as a heterogeneous disease with complex mechanisms and etiologies, requiring unique prevention and treatment strategies tailored to the individual.

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.

MicroRNAs in toxic acute kidney injury: Systematic scoping review of the current status

Acute kidney injury induced by nephrotoxic agents is common, increasing in incidence and associated with considerable morbidity and mortality in developing countries. MicroRNAs are stable biomarkers that can be detected in extracellular fluids. This systematic scoping review aims to describe published research on urinary and circulating microRNAs in toxic acute kidney injury in both animal and human studies. We conducted a literature search, using EMBASE and Medline, for articles on urinary and circulating microRNA in nephrotoxic injuries to February 2020. A total of 21 publications studied acute kidney injury from 12 different toxic agents. Cisplatin was the most common nephrotoxic agent (n = 10), followed by antibiotics (n = 4). There were no randomized controlled trials. An increase in urinary miR-218 predicted acute kidney injury in six different studies, suggesting it is a promising biomarker for nephrotoxin-induced acute kidney injury. There were many factors that prevented a more comprehensive synthesis of microRNA performance including highly variable models, no consistent protocols for RNA isolation, cDNA synthesis and PCR amplification, and variability in normalization methods using reference controls. In conclusion, while microRNAs are promising biomarkers to study nephrotoxic acute kidney injury, the replication of most positive findings is not assessable due to deficient reporting of negative outcomes. A very narrow range of poisons have been studied, and more human data are required. In particular, further studies are needed on the most important causes of nephrotoxic injury, such as pesticides, chemicals, snake envenoming, and medicines other than aminoglycosides and cisplatin.

Atherosclerosis in Different Vascular Locations Unbiasedly Approached with Mouse Genetics

Atherosclerosis in different vascular locations leads to distinct clinical consequences, such as ischemic stroke and myocardial infarction. Genome-wide association studies in humans revealed that genetic loci responsible for carotid plaque and coronary artery disease were not overlapping, suggesting that distinct genetic pathways might be involved for each location. While elevated plasma cholesterol is a common risk factor, plaque development in different vascular beds is influenced by hemodynamics and intrinsic vascular integrity. Despite the limitation of species differences, mouse models provide platforms for unbiased genetic approaches. Mouse strain differences also indicate that susceptibility to atherosclerosis varies, depending on vascular locations, and that the location specificity is genetically controlled. Quantitative trait loci analyses in mice suggested candidate genes, including Mertk and Stab2, although how each gene affects the location-specific atherosclerosis needs further elucidation. Another unbiased approach of single-cell transcriptome analyses revealed the presence of a small subpopulation of vascular smooth muscle cells (VSMCs), which are “hyper-responsive” to inflammatory stimuli. These cells are likely the previously-reported Sca1⁺ progenitor cells, which can differentiate into multiple lineages in plaques. Further spatiotemporal analyses of the progenitor cells are necessary, since their distribution pattern might be associated with the location-dependent plaque development.

Genetic Architecture Modulates Diet-Induced Hepatic mRNA and miRNA Expression Profiles in Diversity Outbred Mice

Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Lastly, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility.

Diversity Outbred Mice Reveal the Quantitative Trait Locus and Regulatory Cells of HER2 Immunity

The genetic basis and mechanisms of disparate antitumor immune response was investigated in Diversity Outbred (DO) F1 mice that express human HER2. DO mouse stock samples nearly the entire genetic repertoire of the species. We crossed DO mice with syngeneic HER2 transgenic mice to study the genetics of an anti-self HER2 response in a healthy outbred population. Anti-HER2 IgG was induced by Ad/E2TM or naked pE2TM, both encoding HER2 extracellular and transmembrane domains. The response of DO F1 HER2 transgenic mice was remarkably variable. Still, immune sera inhibited HER2+ SKBR3 cell survival in a dose-dependent fashion. Using DO quantitative trait locus (QTL) analysis, we mapped the QTL that influences both total IgG and IgG2(a/b/c) Ab response to either Ad/E2TM or pE2TM. QTL from these four datasets identified a region in chromosome 17 that was responsible for regulating the response. A/J and NOD segments of genes in this region drove elevated HER2 Ig levels. This region is rich in MHC-IB genes, several of which interact with inhibitory receptors of NK cells. (B6xA/J)F1 and (B6xNOD)F1 HER2 transgenic mice received Ad/E2TM after NK cell depletion, and they produced less HER2 IgG, demonstrating positive regulatory function of NK cells. Depletion of regulatory T cells enhanced response. Using DO QTL analysis, we show that MHC-IB reactive NK cells exert positive influence on the immunity, countering negative regulation by regulatory T cells. This new, to our knowledge, DO F1 platform is a powerful tool for revealing novel immune regulatory mechanisms and for testing new interventional strategies.

High-fat diet negatively impacts both metabolic and behavioral health in outbred heterogeneous stock rats

Obesity is influenced by genetics and diet and has wide ranging comorbidities, including anxiety and depressive disorders. Outbred heterogeneous stock (HS) rats are used for fine-genetic mapping of complex traits and may be useful for understanding gene by diet interactions. In this study, HS rats were fed diets containing 60% kcal from fat (high-fat diet, HFD) or 10% kcal from fat (low-fat diet, LFD) and tested for metabolic (study 1) and behavioral (study 2) outcomes. In study 1, we measured glucose tolerance, fasting glucose and insulin, fat pad weights and despair-like behavior in the forced swim test (FST). In study 2, we assessed anxiety-like (elevated plus maze, EPM; open field test, OFT) and despair-like/coping (splash test, SpT; and FST) behaviors. Body weight and food intake were measured weekly in both studies. We found negative effects of HFD on metabolic outcomes, including increased body weight and fat pad weights, decreased glucose tolerance, and increased fasting insulin. We also found negative effects of HFD on despair-like/coping and anxiety-like behaviors. These include increased immobility in the FST, decreased open arm time in the EPM, and increased movement and rest episodes and decreased rearing in the OFT. The diet-induced changes in EPM and OFT were independent of overall locomotion. Additionally, diet-induced changes in OFT behaviors were independent of adiposity, while adiposity was a confounding factor for EPM and FST behavior. This work establishes the HS as a model to study gene by diet interactions affecting metabolic and behavioral health.

Dissecting the Genetic Architecture of Cystatin C in Diversity Outbred Mice

Plasma concentration of Cystatin C (CysC) level is a biomarker of glomerular filtration rate in the kidney. We use a Systems Genetics approach to investigate the genetic determinants of plasma CysC concentration. To do so we perform Quantitative Trait Loci (QTL) and expression QTL (eQTL) analysis of 120 Diversity Outbred (DO) female mice, 56 weeks of age. We performed network analysis of kidney gene expression to determine if the gene modules with common functions are associated with kidney biomarkers of chronic kidney diseases. Our data demonstrates that plasma concentrations and kidney mRNA levels of CysC are associated with genetic variation and are transcriptionally coregulated by immune genes. Specifically, Type-I interferon signaling genes are coexpressed with Cst3 mRNA levels and associated with CysC concentrations in plasma. Our findings demonstrate the complex control of CysC by genetic polymorphisms and inflammatory pathways.

Facial shape and allometry quantitative trait locus intervals in the Diversity Outbred mouse are enriched for known skeletal and facial development genes

The biology of how faces are built and come to differ from one another is complex. Discovering normal variants that contribute to differences in facial morphology is one key to untangling this complexity, with important implications for medicine and evolutionary biology. This study maps quantitative trait loci (QTL) for skeletal facial shape using Diversity Outbred (DO) mice. The DO is a randomly outcrossed population with high heterozygosity that captures the allelic diversity of eight inbred mouse lines from three subspecies. The study uses a sample of 1147 DO animals (the largest sample yet employed for a shape QTL study in mouse), each characterized by 22 three-dimensional landmarks, 56,885 autosomal and X-chromosome markers, and sex and age classifiers. We identified 37 facial shape QTL across 20 shape principal components (PCs) using a mixed effects regression that accounts for kinship among observations. The QTL include some previously identified intervals as well as new regions that expand the list of potential targets for future experimental study. Three QTL characterized shape associations with size (allometry). Median support interval size was 3.5 Mb. Narrowing additional analysis to QTL for the five largest magnitude shape PCs, we found significant overrepresentation of genes with known roles in growth, skeletal and facial development, and sensory organ development. For most intervals, one or more of these genes lies within 0.25 Mb of the QTL's peak. QTL effect sizes were small, with none explaining more than 0.5% of facial shape variation. Thus, our results are consistent with a model of facial diversity that is influenced by key genes in skeletal and facial development and, simultaneously, is highly polygenic.

Using Heterogeneous Stocks for Fine-Mapping Genetically Complex Traits

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

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.

The Collaborative Cross: A Systems Genetics Resource for Studying Host-Pathogen Interactions

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

microRNA-146a-5p association with the cardiometabolic disease risk factor TMAO

Trimethylamine-N-oxide (TMAO), a microbial choline metabolism byproduct that is processed in the liver and excreted into circulation, is associated with increased atherosclerotic lesion formation and cardiovascular disease risk. Genetic regulators of TMAO levels are largely unknown. In the present study, we used 288 mice from a genetically heterogeneous mouse population [Diversity Outbred (DO)] to determine hepatic microRNA associations with TMAO in the context of an atherogenic diet. We also validated findings in two additional animal models of atherosclerosis: liver-specific insulin receptor knockout mice fed a chow diet (LIRKO) and African green monkeys fed high-fat/high-cholesterol diet. Small RNA-sequencing analysis in DO mice, LIRKO mice, and African green monkeys identified only one hepatic microRNA (miR-146a-5p) that is aberrantly expressed across all three models. Moreover, miR-146a-5p levels are associated with circulating TMAO after atherogenic diet in each of these models. We also performed high-resolution genetic mapping and identified a novel quantitative trait locus on Chromosome 12 for TMAO levels. This interval includes two genes, Numb and Dlst, which are inversely correlated with both miR-146a and TMAO and are predicted targets of miR-146a. Both of these genes have been validated as direct targets of miR-146a, though in other cellular contexts. This is the first report to our knowledge of a link between miR-146 and TMAO. Our findings suggest that miR-146-5p, as well as one or more genes at the Chromosome 12 QTL (possibly Numb or Dlst), is strongly linked to TMAO levels and likely involved in the control of atherosclerosis.

Giving the Genes a Shuffle: Using Natural Variation to Understand Host Genetic Contributions to Viral Infections

The laboratory mouse has proved an invaluable model to identify host factors that regulate the progression and outcome of virus-induced disease. The paradigm is to use single-gene knockouts in inbred mouse strains or genetic mapping studies using biparental mouse populations. However, genetic variation among these mouse strains is limited compared with the diversity seen in human populations. To address this disconnect, a multiparental mouse population has been developed to specifically dissect the multigenetic regulation of complex disease traits. The Collaborative Cross (CC) population of recombinant inbred mouse strains is a well-suited systems-genetics tool to identify susceptibility alleles that control viral and microbial infection outcomes and immune responses and to test the promise of personalized medicine.

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.

Quantitative trait mapping in Diversity Outbred mice identifies two genomic regions associated with heart size

Heart size is an important factor in cardiac health and disease. In particular, increased heart weight is predictive of adverse cardiovascular outcomes in multiple large community-based studies. We use two cohorts of Diversity Outbred (DO) mice to investigate the role of genetics, sex, age, and diet on heart size. DO mice (n = 289) of both sexes from generation 10 were fed a standard chow diet, and analyzed at 12-15 weeks of age. Another cohort of female DO mice (n = 258) from generation 11 were fed either a high-fat, cholesterol-containing (HFC) diet or a low-fat, high-protein diet, and analyzed at 24-25 weeks. We did not observe an effect of diet on body or heart weight in generation 11 mice, although we previously reported an effect on other cardiovascular risk factors, including cholesterol, triglycerides, and insulin. We do observe a significant genetic effect on heart weight in this population. We identified two quantitative trait loci for heart weight, one (Hwtf1) at a genome-wide significance level of p ≤ 0.05 on MMU15 and one (Hwtf2) at a genome-wide suggestive level of p ≤ 0.1 on MMU10, that together explain 13.3% of the phenotypic variance. Hwtf1 contained collagen type XXII alpha 1 chain (Col22a1), and the NZO/HlLtJ and WSB/EiJ haplotypes were associated with larger hearts. This is consistent with heart tissue Col22a1 expression in DO founders and SNP patterns within Hwtf1 for Col22a1. Col22a1 has been previously associated with cardiac fibrosis in mice, suggesting that Col22a1 may be involved in pathological cardiac hypertrophy.

Developmental constraint through negative pleiotropy in the zygomatic arch

BACKGROUND

Previous analysis suggested that the relative contribution of individual bones to regional skull lengths differ between inbred mouse strains. If the negative correlation of adjacent bone lengths is associated with genetic variation in a heterogeneous population, it would be an example of negative pleiotropy, which occurs when a genetic factor leads to opposite effects in two phenotypes. Confirming negative pleiotropy and determining its basis may reveal important information about the maintenance of overall skull integration and developmental constraint on skull morphology.

RESULTS

We identified negative correlations between the lengths of the frontal and parietal bones in the midline cranial vault as well as the zygomatic bone and zygomatic process of the maxilla, which contribute to the zygomatic arch. Through gene association mapping of a large heterogeneous population of Diversity Outbred (DO) mice, we identified a quantitative trait locus on chromosome 17 driving the antagonistic contribution of these two zygomatic arch bones to total zygomatic arch length. Candidate genes in this region were identified and real-time PCR of the maxillary processes of DO founder strain embryos indicated differences in the RNA expression levels for two of the candidate genes, Camkmt and Six2.

CONCLUSIONS

A genomic region underlying negative pleiotropy of two zygomatic arch bones was identified, which provides a mechanism for antagonism in component bone lengths while constraining overall zygomatic arch length. This type of mechanism may have led to variation in the contribution of individual bones to the zygomatic arch noted across mammals. Given that similar genetic and developmental mechanisms may underlie negative correlations in other parts of the skull, these results provide an important step toward understanding the developmental basis of evolutionary variation and constraint in skull morphology.

Genetics of metabolic syndrome: potential clues from wild-derived inbred mouse strains

The metabolic syndrome (MetS) is a complex constellation of metabolic abnormalities including obesity, abnormal glucose metabolism, dyslipidemia, and elevated blood pressure that together substantially increase risk for cardiovascular disease and Type 2 diabetes. Both genetic and environmental factors contribute to the development of MetS, but this process is still far from understood. Human studies have revealed only part of the underlying basis. Studies in mice offer many strengths that can complement human studies to help elucidate the etiology and pathophysiology of MetS. Here we review the ways mice can contribute to MetS research. In particular, we focus on the information that can be obtained from studies of the inbred strains, with specific focus on the phenotypes of the wild-derived inbred strains. These are newly derived inbred strains that were created from wild-caught mice. They contain substantial genetic variation that is not present in the classical inbred strains, have phenotypes of relevance for MetS, and various mouse strain resources have been created to facilitate the mining of this new genetic variation. Thus studies using wild-derived inbred strains hold great promise for increasing our understanding of MetS.

Adropin: An endocrine link between the biological clock and cholesterol homeostasis

Objective

Identify determinants of plasma adropin concentrations, a secreted peptide translated from the Energy Homeostasis Associated (ENHO) gene linked to metabolic control and vascular function.

Methods

Associations between plasma adropin concentrations, demographics (sex, age, BMI) and circulating biomarkers of lipid and glucose metabolism were assessed in plasma obtained after an overnight fast in humans. The regulation of adropin expression was then assessed in silico, in cultured human cells, and in animal models.

Results

In humans, plasma adropin concentrations are inversely related to atherogenic LDL-cholesterol (LDL-C) levels in men (n = 349), but not in women (n = 401). Analysis of hepatic Enho expression in male mice suggests control by the biological clock. Expression is rhythmic, peaking during maximal food consumption in the dark correlating with transcriptional activation by RORα/γ. The nadir in the light phase coincides with the rest phase and repression by Rev-erb. Plasma adropin concentrations in nonhuman primates (rhesus monkeys) also exhibit peaks coinciding with feeding times (07:00 h, 15:00 h). The ROR inverse agonists SR1001 and the 7-oxygenated sterols 7-β-hydroxysterol and 7-ketocholesterol, or the Rev-erb agonist SR9009, suppress ENHO expression in cultured human HepG2 cells. Consumption of high-cholesterol diets suppress expression of the adropin transcript in mouse liver. However, adropin over expression does not prevent hypercholesterolemia resulting from a high cholesterol diet and/or LDL receptor mutations.

Conclusions

In humans, associations between plasma adropin concentrations and LDL-C suggest a link with hepatic lipid metabolism. Mouse studies suggest that the relationship between adropin and cholesterol metabolism is unidirectional, and predominantly involves suppression of adropin expression by cholesterol and 7-oxygenated sterols. Sensing of fatty acids, cholesterol and oxysterols by the RORα/γ ligand-binding domain suggests a plausible functional link between adropin expression and cellular lipid metabolism. Furthermore, the nuclear receptors RORα/γ and Rev-erb may couple adropin synthesis with circadian rhythms in carbohydrate and lipid metabolism.

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In male humans, plasma adropin concentrations are inversely related to low-density circulating cholesterol (LDL-C) levels.

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Adropin expression is regulated by core elements of the biological clock (RORA/G, Rev-Erb).

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Sterol-sensing by the ROR ligand-binding domain provides a plausible link between adropin expression and lipid metabolism.

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In mouse liver, adropin expression is rhythmic and suppressed by exogenous (dietary) cholesterol.

Systems genetics identifies a co-regulated module of liver microRNAs associated with plasma LDL cholesterol in murine diet-induced dyslipidemia

Chronically altered levels of circulating lipids, termed dyslipidemia, is a significant risk factor for a number of metabolic and cardiovascular morbidities. MicroRNAs (miRNAs) have emerged as important regulators of lipid balance, have been implicated in dyslipidemia, and have been proposed as candidate therapeutic targets in lipid-related disorders including atherosclerosis. A major limitation of most murine studies of miRNAs in lipid metabolic disorders is that they have been performed in just one (or very few) inbred strains, such as C57BL/6. Moreover, although individual miRNAs have been associated with lipid phenotypes, it is well understood that miRNAs likely work together in functional modules. To address these limitations, we implemented a systems genetics strategy using the Diversity Outbred (DO) mouse population. Specifically, we performed gene and miRNA expression profiling in the livers from ~300 genetically distinct DO mice after 18 wk on either a high-fat/high-cholesterol diet or a high-protein diet. Large-scale correlative analysis of these data with a wide range of cardio-metabolic end points revealed a co-regulated module of miRNAs significantly associated with circulating low-density lipoprotein cholesterol (LDL-C) levels. The hubs of this module were identified as miR-199a, miR-181b, miR-27a, miR-21_-_1, and miR-24. In sum, we demonstrate that a high-fat/high-cholesterol diet robustly rewires the miRNA regulatory network, and we identify a small group of co-regulated miRNAs that may exert coordinated effects to control circulating LDL-C.

New Rodent Population Models May Inform Human Health Risk Assessment and Identification of Genetic Susceptibility to Environmental Exposures

BACKGROUND

This paper provides an introduction for environmental health scientists to emerging population-based rodent resources. Mouse reference populations provide an opportunity to model environmental exposures and gene-environment interactions in human disease and to inform human health risk assessment.

OBJECTIVES

This review will describe several mouse populations for toxicity assessment, including older models such as the Mouse Diversity Panel (MDP), and newer models that include the Collaborative Cross (CC) and Diversity Outbred (DO) models.

METHODS

This review will outline the features of the MDP, CC, and DO mouse models and will discuss published case studies investigating the use of these mouse population resources in each step of the risk assessment paradigm.

DISCUSSION

These unique resources have the potential to be powerful tools for generating hypotheses related to gene-environment interplay in human disease, performing controlled exposure studies to understand the differential responses in humans for susceptibility or resistance to environmental exposures, and identifying gene variants that influence sensitivity to toxicity and disease states.

CONCLUSIONS

These new resources offer substantial advances to classical toxicity testing paradigms by including genetically sensitive individuals that may inform toxicity risks for sensitive subpopulations. Both in vivo and complementary in vitro resources provide platforms with which to reduce uncertainty by providing population-level data around biological variability. https://doi.org/10.1289/EHP1274.

Genetic background influences susceptibility to chemotherapy-induced hematotoxicity

Hematotoxicity is a life-threatening side effect of many chemotherapy regimens. While clinical factors influence patient responses, genetic factors may also play an important role. We sought to identify genomic loci that influence chemotherapy-induced hematotoxicity by dosing Diversity Outbred mice with one of three chemotherapy drugs; doxorubicin, cyclophosphamide or docetaxel. We observed that each drug had a distinct effect on both the changes in blood cell sub-populations and the underlying genetic architecture of hematotoxicity. For doxorubicin, we mapped the change in cell counts before and after dosing and found that alleles of ATP-binding cassette B1B (Abcb1b) on chromosome 5 influence all cell populations. For cyclophosphamide and docetaxel, we found that each cell population was influenced by distinct loci, none of which overlapped between drugs. These results suggest that susceptibility to chemotherapy-induced hematotoxicity is influenced by different genes for different chemotherapy drugs.

Diversity Outbred Mice at 21: Maintaining Allelic Variation in the Face of Selection

Multi-parent populations (MPPs) capture and maintain the genetic diversity from multiple inbred founder strains to provide a resource for high-resolution genetic mapping through the accumulation of recombination events over many generations. Breeding designs that maintain a large effective population size with randomized assignment of breeders at each generation can minimize the impact of selection, inbreeding, and genetic drift on allele frequencies. Small deviations from expected allele frequencies will have little effect on the power and precision of genetic analysis, but a major distortion could result in reduced power and loss of important functional alleles. We detected strong transmission ratio distortion in the Diversity Outbred (DO) mouse population on chromosome 2, caused by meiotic drive favoring transmission of the WSB/EiJ allele at the R2d2 locus. The distorted region harbors thousands of polymorphisms derived from the seven non-WSB founder strains and many of these would be lost if the sweep was allowed to continue. To ensure the utility of the DO population to study genetic variation on chromosome 2, we performed an artificial selection against WSB/EiJ alleles at the R2d2 locus. Here, we report that we have purged the WSB/EiJ allele from the drive locus while preserving WSB/EiJ alleles in the flanking regions. We observed minimal disruption to allele frequencies across the rest of the autosomal genome. However, there was a shift in haplotype frequencies of the mitochondrial genome and an increase in the rate of an unusual sex chromosome aneuploidy. The DO population has been restored to genome-wide utility for genetic analysis, but our experience underscores that vigilant monitoring of similar genetic resource populations is needed to ensure their long-term utility.

High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model

Investigations on the influence of nature vs. nurture on Alcoholism (Alcohol Use Disorder) in human have yet to provide a clear view on potential genomic etiologies. To address this issue, we sequenced a replicated animal model system bidirectionally-selected for alcohol preference (AP). This model is uniquely suited to map genetic effects with high reproducibility, and resolution. The origin of the rat lines (an 8-way cross) resulted in small haplotype blocks (HB) with a corresponding high level of resolution. We sequenced DNAs from 40 samples (10 per line of each replicate) to determine allele frequencies and HB. We achieved ~46X coverage per line and replicate. Excessive differentiation in the genomic architecture between lines, across replicates, termed signatures of selection (SS), were classified according to gene and region. We identified SS in 930 genes associated with AP. The majority (50%) of the SS were confined to single gene regions, the greatest numbers of which were in promoters (284) and intronic regions (169) with the least in exon's (4), suggesting that differences in AP were primarily due to alterations in regulatory regions. We confirmed previously identified genes and found many new genes associated with AP. Of those newly identified genes, several demonstrated neuronal function involved in synaptic memory and reward behavior, e.g. ion channels (Kcnf1, Kcnn3, Scn5a), excitatory receptors (Grin2a, Gria3, Grip1), neurotransmitters (Pomc), and synapses (Snap29). This study not only reveals the polygenic architecture of AP, but also emphasizes the importance of regulatory elements, consistent with other complex traits.

Alcohol Used Disorder (AUD) or Alcoholism extracts a great societal cost in terms of human suffering. Understanding the genetic basis is critical to comprehend, treat and prevent this disease, but difficult in humans, as choice is influenced by nature and nurture. To discover its genetic basis, we used an animal model system that controlled for genetic and non-genetic factors through randomization, study replication, long-term divergent selection, and a controlled environment. We conducted whole genome sequencing in breeds that were either compulsive excessive drinkers or completely abstinent. We discovered consistent alterations in several genes and neurological pathways previously unassociated with alcoholism. These results strengthened our understanding of the genetic basis of alcoholism and revealed potential genetic- and neurological-based treatments.

Characterization of Three Rice Multiparent Advanced Generation Intercross (MAGIC) Populations for Quantitative Trait Loci Identification

Three new rice ( L.) multiparent advanced generation intercross (MAGIC) populations were developed using eight elite rice varieties from different breeding programs. These three populations were two recombinant inbred line (RIL) populations derived from two 4-way crosses, DC1 and DC2, and one RIL population derived from an 8-way cross. These populations were genotyped using an Illumina Infinium rice 6K SNP chip. The potential of the three MAGIC populations in identifying marker-trait associations was demonstrated using the plant height (PH) and heading date (HD) measured in 2014. A population of 248 IRRI breeding lines and a population of 323 Chinese breeding lines were also included to compare genetic diversity and linkage disequilibrium (LD) pattern. Our study discovered that (i) the 8-way population had a higher gene diversity than the DC1, DC2, and IRRI populations; (ii) all three MAGIC populations showed no clear population structure; (iii) LD decayed to < 0.2 at about 2.5, 2.5, 1.25, 1.75, and 4.0 Mb for the DC1, DC2, 8-way, IRRI, and Chinese populations, respectively; and (iv) the 8-way population was more powerful than the DC1, DC2, and IRRI populations on QTL identification. The association analysis identified two and three QTL for PH and HD, respectively. Four of the five QTL had peak markers close to known genes. A novel QTL for PH was identified on chromosome 12 using the 8-way population. Therefore, our study suggests that the three new MAGIC populations are valuable resources for QTL identification.

Collaborative Cross and Diversity Outbred data resources in the Mouse Phenome Database

The Mouse Phenome Database was originally conceived as a platform for the integration of phenotype data collected on a defined collection of 40 inbred mouse strains--the "phenome panel." This model provided an impetus for community data sharing, and integration was readily achieved through the reproducible genotypes of the phenome panel strains. Advances in the development of mouse populations lead to an expanded role of the Mouse Phenome Database to encompass new strain panels and inbred strain crosses. The recent introduction of the Collaborative Cross and Diversity Outbred mice, which share an extensive pool of genetic variation from eight founder inbred strains, presents new opportunities and challenges for community data resources. A wide variety of molecular and clinical phenotypes are being collected across genotypes, tissues, ages, environmental exposures, interventions, and treatments. The Mouse Phenome Database provides a framework for retrieval, integration, analysis, and display of these data, enabling them to be evaluated in the context of existing data from standard inbred strains. Primary data in the Mouse Phenome Database are supported by extensive metadata on protocols and procedures. These are centrally curated to ensure accuracy and reproducibility and to provide data in consistent formats. The Mouse Phenome Database represents an established and growing community data resource for mouse phenotype data and encourages submissions from new mouse resources, enabling investigators to integrate existing data into their studies of the phenotypic consequences of genetic variation.

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

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