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

Previous studies in animal models and humans have shown that exposure to nutritional deficiencies in the perinatal period increases the risk of psychiatric disease. Less well understood is how such effects are modulated by the combination of genetic background and parent‐of‐origin (PO). To explore this, we exposed female mice from 20 Collaborative Cross (CC) strains to protein deficient, vitamin D deficient, methyl donor enriched or standard diet during the perinatal period. These CC females were then crossed to a male from a different CC strain to produce reciprocal F1 hybrid females comprising 10 distinct genetic backgrounds. The adult F1 females were then tested in the open field, light/dark, stress‐induced hyperthermia, forced swim and restraint stress assays. Our experimental design allowed us to estimate effects of genetic background, perinatal diet, PO and their interactions on behavior. Genetic background significantly affected all assessed phenotypes. Perinatal diet exposure interacted with genetic background to affect body weight, basal body temperature, anxiety‐like behavior and stress response. In 8 of 9 genetic backgrounds, PO effects were observed on multiple phenotypes. Additionally, we identified a small number of diet‐by‐PO effects on body weight, stress response, anxiety‐ and depressive‐like behavior. Our data show that rodent behaviors that model psychiatric disorders are affected by genetic background, PO and perinatal diet, as well as interactions among these factors. [ABSTRACT FROM AUTHOR]

Abstract A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

Abstract Background Genetic and environmental factors have important roles in multiple sclerosis (MS) susceptibility. A clear parent of origin effect has been shown in several populations, perhaps resulting from factors operating during gestation. Preterm birth (birth at less than 37 weeks gestational age) has been shown to result in long-term health problems, including impaired neurological development. Here, in a population-based cohort, we investigate whether preterm birth increases the risk to subsequently develop MS. Methods We identified 6585 MS index cases and 2509 spousal controls with preterm birth information from the Canadian Collaborative Project on Genetic Susceptibility to MS. Rates of individuals born preterm were compared for index cases and controls. Results There were no significant differences between cases and controls with respect to preterm births. 370 (5.6%) MS index cases and 130 (5.2%) spousal controls were born preterm, p = 0.41. Conclusion Preterm birth does not appear to contribute to MS aetiology. Other factors involved in foetal and early development need to be explored to elucidate the mechanism of the increased risk conferred by the apparent maternal effect.

Coronaviruses have caused three severe epidemics since the start of the 21 st century: SARS, MERS and COVID-19. The severity of the ongoing COVID-19 pandemic and increasing likelihood of future coronavirus outbreaks motivates greater understanding of factors leading to severe coronavirus disease. We screened ten strains from the Collaborative Cross mouse genetic reference panel and identified strains CC006/TauUnc (CC006) and CC044/Unc (CC044) as coronavirus-susceptible and resistant, respectively, as indicated by variable weight loss and lung congestion scores four days post-infection. We generated a genetic mapping population of 755 CC006xCC044 F2 mice and exposed the mice to one of three genetically distinct mouse-adapted coronaviruses: clade 1a SARS-CoV MA15 (n=391), clade 1b SARS-CoV-2 MA10 (n=274), and clade 2 HKU3-CoV MA (n=90). Quantitative trait loci (QTL) mapping in SARS-CoV MA15- and SARS-CoV-2 MA10-infected F2 mice identified genetic loci associated with disease severity. Specifically, we identified seven loci associated with variation in outcome following infection with either virus, including one, HrS43, that is present in both groups. Three of these QTL, including HrS43, were also associated with HKU3-CoV MA outcome. HrS43 overlaps with a QTL previously reported by our lab that is associated with SARS-CoV MA15 outcome in CC011xCC074 F2 mice and is also syntenic with a human chromosomal region associated with severe COVID-19 outcomes in humans GWAS. The results reported here provide: (a) additional support for the involvement of this locus in SARS-CoV MA15 infection, (b) the first conclusive evidence that this locus is associated with susceptibility across the Sarbecovirus subgenus, and (c) demonstration of the relevance of mouse models in the study of coronavirus disease susceptibility in humans., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: RSB and SRL are listed as inventors on a patent pertaining to the mouse-adapted SARS-CoV-2 (MA10) virus used in this study (Patent number: 11,225,508), (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The development of peanut allergy is due to a combination of genetic and environmental factors, although specific genes have proven difficult to identify. Previously, we reported that peanut-sensitized Collaborative Cross strain CC027/GeniUnc (CC027) mice develop anaphylaxis upon oral challenge to peanut, in contrast to C3H/HeJ (C3H) mice., Objective: This study aimed to determine the genetic basis of orally induced anaphylaxis to peanut in CC027 mice., Methods: A genetic mapping population between CC027 and C3H mice was designed to identify the genetic factors that drive oral anaphylaxis. A total of 356 CC027xC3H backcrossed mice were generated, sensitized to peanut, then challenged to peanut by oral gavage. Anaphylaxis and peanut-specific IgE were quantified for all mice. T-cell phenotyping was conducted on CC027 mice and 5 additional Collaborative Cross strains., Results: Anaphylaxis to peanut was absent in 77% of backcrossed mice, with 19% showing moderate anaphylaxis and 4% having severe anaphylaxis. There were 8 genetic loci associated with variation in response to peanut challenge-6 associated with anaphylaxis (temperature decrease) and 2 associated with peanut-specific IgE levels. There were 2 major loci that impacted multiple aspects of the severity of acute anaphylaxis, at which the CC027 allele was associated with worse outcome. At one of these loci, CC027 has a private genetic variant in the Themis gene. Consistent with described functions of Themis, we found that CC027 mice have more immature T cells with fewer CD8 + , CD4 + , and CD4 + CD25 + CD127 - regulatory T cells., Conclusions: Our results demonstrate a key role for Themis in the orally reactive CC027 mouse model of peanut allergy., (Copyright © 2024 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Introduction: Emerging data suggests liver disease may be initiated during development when there is high genome plasticity and the molecular pathways supporting liver function are being developed., Methods: Here, we leveraged our Collaborative Cross mouse model of developmental vitamin D deficiency (DVD) to investigate the role of DVD in dysregulating the molecular mechanisms underlying liver disease. We defined the effects on the adult liver transcriptome and metabolome and examined the role of epigenetic dysregulation. Given that the parental origin of the genome (POG) influences response to DVD, we used our established POG model [POG1-(CC011xCC001)F1 and POG2-(CC001xCC011)F1] to identify interindividual differences., Results: We found that DVD altered the adult liver transcriptome, primarily downregulating genes controlling liver development, response to injury/infection (detoxification & inflammation), cholesterol biosynthesis, and energy production. In concordance with these transcriptional changes, we found that DVD decreased liver cell membrane-associated lipids (including cholesterol) and pentose phosphate pathway metabolites. Each POG also exhibited distinct responses. POG1 exhibited almost 2X more differentially expressed genes (DEGs) with effects indicative of increased energy utilization. This included upregulation of lipid and amino acid metabolism genes and increased intermediate lipid and amino acid metabolites, increased energy cofactors, and decreased energy substrates. POG2 exhibited broader downregulation of cholesterol biosynthesis genes with a metabolomics profile indicative of decreased energy utilization. Although DVD primarily caused loss of liver DNA methylation for both POGs, only one epimutation was shared, and POG2 had 6.5X more differentially methylated genes. Differential methylation was detected at DEGs regulating developmental processes such as amino acid transport (POG1) and cell growth & differentiation (e.g., Wnt & cadherin signaling, POG2)., Conclusions: These findings implicate a novel role for maternal vitamin D in programming essential offspring liver functions that are dysregulated in liver disease. Importantly, impairment of these processes was not rescued by vitamin D treatment at weaning, suggesting these effects require preventative measures. Substantial differences in POG response to DVD demonstrate that the parental genomic context of exposure determines offspring susceptibility., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Knuth, Xue, Elnagheeb, Gharaibeh, Schoenrock, McRitchie, Brouwer, Sumner, Tarantino, Valdar, Rector, Simon and Ideraabdullah.)

Background: The gut microbiota is modulated by a combination of diet, host genetics, and sex effects. The magnitude of these effects and interactions among them is important to understanding inter-individual variability in gut microbiota. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed along with several QTLs for metabolic traits. In the current study, we searched for genetic variants underlying differences in the gut microbiota in response to American and ketogenic diets, which are high in fat and vary in carbohydrate composition, between C57BL/6 J (B6) and FVB/NJ (FVB) mouse strains., Results: Genetic mapping of microbial features revealed 18 loci under the QTL model (i.e., marginal effects that are not specific to diet or sex), 12 loci under the QTL by diet model, and 1 locus under the QTL by sex model. Multiple metabolic and microbial features map to the distal part of Chr 1 and Chr 16 along with eigenvectors extracted from principal coordinate analysis of measures of β-diversity. Bilophila, Ruminiclostridium 9, and Rikenella (Chr 1) were identified as sex- and diet-independent QTL candidate keystone organisms, and Parabacteroides (Chr 16) was identified as a diet-specific, candidate keystone organism in confirmatory factor analyses of traits mapping to these regions. For many microbial features, irrespective of which QTL model was used, diet or the interaction between diet and a genotype were the strongest predictors of the abundance of each microbial trait. Sex, while important to the analyses, was not as strong of a predictor for microbial abundances., Conclusions: These results demonstrate that sex, diet, and genetic background have different magnitudes of effects on inter-individual differences in gut microbiota. Therefore, Precision Nutrition through the integration of genetic variation, microbiota, and sex affecting microbiota variation will be important to predict response to diets varying in carbohydrate composition. Video Abstract., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Toxicology research has rapidly evolved, leveraging increasingly advanced technologies in high-throughput approaches to yield important information on toxicological mechanisms and health outcomes. Data produced through toxicology studies are consequently becoming larger, often producing high-dimensional data. These types of data hold promise for imparting new knowledge, yet inherently have complexities causing them to be a rate-limiting element for researchers, particularly those that are housed in "wet lab" settings (i.e., researchers that use liquids to analyze various chemicals and biomarkers as opposed to more computationally focused, "dry lab" researchers). These types of challenges represent topics of ongoing conversation amongst our team and researchers in the field. The aim of this perspective is to i) summarize hurdles in analyzing high-dimensional data in toxicology that require improved training and translation for wet lab researchers, ii) highlight example methods that have aided in translating data analysis techniques to wet lab researchers; and iii) describe challenges that remain to be effectively addressed, to date, in toxicology research. Specific aspects include methodologies that could be introduced to wet lab researchers, including data pre-processing, machine learning, and data reduction. Current challenges discussed include model interpretability, study biases, and data analysis training. Example efforts implemented to translate these data analysis techniques are also mentioned, including online data analysis resources and hands-on workshops. Questions are also posed to continue conversation in the toxicology community. Contents of this perspective represent timely issues broadly occurring in the fields of bioinformatics and toxicology that require ongoing dialogue between wet and dry lab researchers., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Payton, Roell, Rebuli, Valdar, Jaspers and Rager.)

Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids, and other metabolic traits. Physiological traits were measured in 1,519 male HS rats, with liver and adipose transcriptomes measured in >410 rats. Genotypes were imputed from low-coverage whole-genome sequencing. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), using both single nucleotide polymorphism (SNP)- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 14 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 10 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for fat pad weight and serum triglyceride pQTLs on Chr1, Krtcap3 for fat pad weight and serum triglyceride pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20, and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knockdown/out models, thereby shedding light on novel regulators of obesity., (© 2022 by the American Diabetes Association.)

Transcriptomic analysis in metabolically active tissues allows a systems genetics approach to identify causal genes and networks involved in metabolic disease. Outbred heterogeneous stock (HS) rats are used for genetic mapping of complex traits, but to-date, a systems genetics analysis of metabolic tissues has not been done. We investigated whether adiposity-associated genes and gene coexpression networks in outbred heterogeneous stock (HS) rats overlap those found in humans. We analyzed RNAseq data from adipose tissue of 415 male HS rats, correlated these transcripts with body weight (BW) and compared transcriptome signatures to two human cohorts: the "African American Genetics of Metabolism and Expression" and "Metabolic Syndrome in Men." We used weighted gene coexpression network analysis to identify adiposity-associated gene networks and mediation analysis to identify genes under genetic control whose expression drives adiposity. We identified 554 orthologous "consensus genes" whose expression correlates with BW in the rat and with body mass index (BMI) in both human cohorts. Consensus genes fell within eight coexpressed networks and were enriched for genes involved in immune system function, cell growth, extracellular matrix organization, and lipid metabolic processes. We identified 19 consensus genes for which genetic variation may influence BW via their expression, including those involved in lipolysis (e.g., Hcar1) , inflammation (e.g., Rgs1 ), adipogenesis (e.g., Tmem120b ), or no previously known role in obesity (e.g., St14 and Ms4a6a). Strong concordance between HS rat and human BW/BMI associated transcripts demonstrates translational utility of the rat model, while identification of novel genes expands our knowledge of the genetics underlying obesity.

Genetic studies often seek to establish a causal chain of events originating from genetic variation through to molecular and clinical phenotypes. When multiple phenotypes share a common genetic association, one phenotype may act as an intermediate for the genetic effects on the other. Alternatively, the phenotypes may be causally unrelated but share genetic loci. Mediation analysis represents a class of causal inference approaches used to determine which of these scenarios is most plausible. We have developed a general approach to mediation analysis based on Bayesian model selection and have implemented it in an R package, bmediatR. Bayesian model selection provides a flexible framework that can be tailored to different analyses. Our approach can incorporate prior information about the likelihood of models and the strength of causal effects. It can also accommodate multiple genetic variants or multi-state haplotypes. Our approach reports posterior probabilities that can be useful in interpreting uncertainty among competing models. We compared bmediatR with other popular methods, including the Sobel test, Mendelian randomization, and Bayesian network analysis using simulated data. We found that bmediatR performed as well or better than these alternatives in most scenarios. We applied bmediatR to proteome data from Diversity Outbred (DO) mice, a multi-parent population, and demonstrate the power of mediation with multi-state haplotypes. We also applied bmediatR to data from human cell lines to identify transcripts that are mediated through or are expressed independently from local chromatin accessibility. We demonstrate that Bayesian model selection provides a powerful and versatile approach to identify causal relationships in genetic studies using model organism or human data., Competing Interests: The authors have declared that no competing interests exist.

Development of TAK-875 was discontinued when a small number of serious drug-induced liver injury (DILI) cases were observed in Phase 3 clinical trials. Subsequent studies have identified hepatocellular oxidative stress, mitochondrial dysfunction, altered bile acid homeostasis, and immune response as mechanisms of TAK-875 DILI and the contribution of genetic risk factors in oxidative response and mitochondrial pathways to the toxicity susceptibility observed in patients. We tested the hypothesis that a novel preclinical approach based on gene pathway analysis in the livers of Collaborative Cross mice could be used to identify human-relevant mechanisms of toxicity and genetic risk factors at the level of the hepatocyte as reported in a human genome-wide association study. Eight (8) male mice (4 matched pairs) from each of 45 Collaborative Cross lines were treated with a single oral (gavage) dose of either vehicle or 600 mg/kg TAK-875. As expected, liver injury was not detected histologically and few changes in plasma biomarkers of hepatotoxicity were observed. However, gene expression profiling in the liver identified hundreds of transcripts responsive to TAK-875 treatment across all strains reflecting alterations in immune response and bile acid homeostasis and the interaction of treatment and strain reflecting oxidative stress and mitochondrial dysfunction. Fold-change expression values were then used to develop pathway-based phenotypes for genetic mapping which identified candidate risk factor genes for TAK-875 toxicity susceptibility at the level of the hepatocyte. Taken together, these findings support our hypothesis that a gene pathway-based approach using Collaborative Cross mice could inform sensitive strains, human-relevant mechanisms of toxicity, and genetic risk factors for TAK-875 DILI. This novel preclinical approach may be helpful in understanding, predicting, and ultimately preventing clinical DILI for other drugs., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Female mammals are functional mosaics of their parental X-linked gene expression due to X chromosome inactivation (XCI). This process inactivates one copy of the X chromosome in each cell during embryogenesis and that state is maintained clonally through mitosis. In mice, the choice of which parental X chromosome remains active is determined by the X chromosome controlling element (Xce), which has been mapped to a 176-kb candidate interval. A series of functional Xce alleles has been characterized or inferred for classical inbred strains based on biased, or skewed, inactivation of the parental X chromosomes in crosses between strains. To further explore the function structure basis and location of the Xce, we measured allele-specific expression of X-linked genes in a large population of F1 females generated from Collaborative Cross (CC) strains. Using published sequence data and applying a Bayesian "Pólya urn" model of XCI skew, we report two major findings. First, inter-individual variability in XCI suggests mouse epiblasts contain on average 20-30 cells contributing to brain. Second, CC founder strain NOD/ShiLtJ has a novel and unique functional allele, Xceg, that is the weakest in the Xce allelic series. Despite phylogenetic analysis confirming that NOD/ShiLtJ carries a haplotype almost identical to the well-characterized C57BL/6J (Xceb), we observed unexpected patterns of XCI skewing in females carrying the NOD/ShiLtJ haplotype within the Xce. Copy number variation is common at the Xce locus and we conclude that the observed allelic series is a product of independent and recurring duplications shared between weak Xce alleles., (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Chronic kidney disease (CKD), which can ultimately progress to kidney failure, is influenced by genetics and the environment. Genes identified in human genome wide association studies (GWAS) explain only a small proportion of the heritable variation and lack functional validation, indicating the need for additional model systems. Outbred heterogeneous stock (HS) rats have been used for genetic fine-mapping of complex traits, but have not previously been used for CKD traits. We performed GWAS for urinary protein excretion (UPE) and CKD related serum biochemistries in 245 male HS rats. Quantitative trait loci (QTL) were identified using a linear mixed effect model that tested for association with imputed genotypes. Candidate genes were identified using bioinformatics tools and targeted RNAseq followed by testing in a novel in vitro model of human tubule, hypoxia-induced damage. We identified two QTL for UPE and five for serum biochemistries. Protein modeling identified a missense variant within Septin 8 (Sept8) as a candidate for UPE. Sept8/SEPTIN8 expression increased in HS rats with elevated UPE and tubulointerstitial injury and in the in vitro hypoxia model. SEPTIN8 is detected within proximal tubule cells in human kidney samples and localizes with acetyl-alpha tubulin in the culture system. After hypoxia, SEPTIN8 staining becomes diffuse and appears to relocalize with actin. These data suggest a role of SEPTIN8 in cellular organization and structure in response to environmental stress. This study demonstrates that integration of a rat genetic model with an environmentally induced tubule damage system identifies Sept8/SEPTIN8 and informs novel aspects of the complex gene by environmental interactions contributing to CKD risk.

Multiparental populations (MPPs) are experimental populations in which the genome of every individual is a mosaic of known founder haplotypes. These populations are useful for detecting quantitative trait loci (QTL) because tests of association can leverage inferred founder haplotype descent. It is difficult, however, to determine how haplotypes at a locus group into distinct functional alleles, termed the allelic series. The allelic series is important because it provides information about the number of causal variants at a QTL and their combined effects. In this study, we introduce a fully Bayesian model selection framework for inferring the allelic series. This framework accounts for sources of uncertainty found in typical MPPs, including the number and composition of functional alleles. Our prior distribution for the allelic series is based on the Chinese restaurant process, a relative of the Dirichlet process, and we leverage its connection to the coalescent to introduce additional prior information about haplotype relatedness via a phylogenetic tree. We evaluate our approach via simulation and apply it to QTL from two MPPs: the Collaborative Cross (CC) and the Drosophila Synthetic Population Resource (DSPR). We find that, although posterior inference of the exact allelic series is often uncertain, we are able to distinguish biallelic QTL from more complex multiallelic cases. Additionally, our allele-based approach improves haplotype effect estimation when the true number of functional alleles is small. Our method, Tree-Based Inference of Multiallelism via Bayesian Regression (TIMBR), provides new insight into the genetic architecture of QTL in MPPs., (Copyright © 2020 Crouse et al.)

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of X O and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research., (Copyright © 2020 by the Genetics Society of America.)

Background: Liver metabolite concentrations have the potential to be key biomarkers of systemic metabolic dysfunction and overall health. However, for most conditions we do not know the extent to which genetic differences regulate susceptibility to metabolic responses. This limits our ability to detect and diagnose effects in heterogeneous populations., Objectives: Here, we investigated the extent to which naturally occurring genetic differences regulate maternal liver metabolic response to vitamin D deficiency (VDD), particularly during perinatal periods when such changes can adversely affect maternal and fetal health., Methods: We used a panel of 8 inbred Collaborative Cross (CC) mouse strains, each with a different genetic background (72 dams, 3-6/treatment group, per strain). We identified robust maternal liver metabolic responses to vitamin D depletion before and during gestation and lactation using a vitamin-D-deficient (VDD; 0 IU vitamin D 3 /kg) or -sufficient diet (1000 IU vitamin D 3 /kg). We then identified VDD-induced metabolite changes influenced by strain genetic background., Results: We detected a significant VDD effect by orthogonal partial least squares discriminant analysis (Q2 = 0.266, pQ2 = 0.002): primarily, altered concentrations of 78 metabolites involved in lipid, amino acid, and nucleotide metabolism (variable importance to projection score ≥1.5). Metabolites in unsaturated fatty acid and glycerophospholipid metabolism pathways were significantly enriched [False Discovery Rate (FDR) <0.05]. VDD also significantly altered concentrations of putative markers of uremic toxemia, acylglycerols, and dipeptides. The extent of the metabolic response to VDD was strongly dependent on genetic strain, ranging from robustly responsive to nonresponsive. Two strains (CC017/Unc and CC032/GeniUnc) were particularly sensitive to VDD; however, each strain altered different pathways., Conclusions: These novel findings demonstrate that maternal VDD induces different liver metabolic effects in different genetic backgrounds. Strains with differing susceptibility and metabolic response to VDD represent unique tools to identify causal susceptibility factors and further elucidate the role of VDD-induced metabolic changes in maternal and/or fetal health for ultimately translating findings to human populations., (Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.)

Rationale: Few effective treatments exist for cocaine use disorders due to gaps in knowledge about its complex etiology. Genetically defined animal models provide a useful tool for advancing our understanding of the biological and genetic underpinnings of addiction-related behavior and evaluating potential treatments. However, many attempts at developing mouse models of behavioral disorders were based on overly simplified single gene perturbations, often leading to inconsistent and misleading results in pre-clinical pharmacology studies. A genetically complex mouse model may better reflect disease-related behaviors., Objectives: Screening defined, yet genetically complex, intercrosses of the Collaborative Cross (CC) mice revealed two lines, RIX04/17 and RIX41/51, with extreme high and low behavioral responses to cocaine. We characterized these lines as well as their CC parents, CC004/TauUnc and CC041/TauUnc, to evaluate their utility as novel model systems for studying the biological and genetic mechanisms underlying behavioral responses to cocaine., Methods: Behavioral responses to acute (initial locomotor sensitivity) and repeated (behavioral sensitization, conditioned place preference, intravenous self-administration) exposures to cocaine were assessed. We also examined the monoaminergic system (striatal tissue content and in vivo fast scan cyclic voltammetry), HPA axis reactivity, and circadian rhythms as potential mechanisms for the divergent phenotypic behaviors observed in the two strains, as these systems have a previously known role in mediating addiction-related behaviors., Results: RIX04/17 and 41/51 show strikingly divergent initial locomotor sensitivity to cocaine with RIX04/17 exhibiting very high and RIX41/51 almost no response. The lines also differ in the emergence of behavioral sensitization with RIX41/51 requiring more exposures to exhibit a sensitized response. Both lines show conditioned place preference for cocaine. We determined that the cocaine sensitivity phenotype in each RIX line was largely driven by the genetic influence of one CC parental strain, CC004/TauUnc and CC041/TauUnc. CC004 demonstrates active operant cocaine self-administration and CC041 is unable to acquire under the same testing conditions, a deficit which is specific to cocaine as both strains show operant response for a natural food reward. Examination of potential mechanisms driving differential responses to cocaine show strain differences in molecular and behavioral circadian rhythms. Additionally, while there is no difference in striatal dopamine tissue content or dynamics, there are selective differences in striatal norepinephrine and serotonergic tissue content., Conclusions: These CC strains offer a complex polygenic model system to study underlying mechanisms of cocaine response. We propose that CC041/TauUnc and CC004/TauUnc will be useful for studying genetic and biological mechanisms underlying resistance or vulnerability to the stimulatory and reinforcing effects of cocaine.

Gene transcription profiles across tissues are largely defined by the activity of regulatory elements, most of which correspond to regions of accessible chromatin. Regulatory element activity is in turn modulated by genetic variation, resulting in variable transcription rates across individuals. The interplay of these factors, however, is poorly understood. Here we characterize expression and chromatin state dynamics across three tissues-liver, lung, and kidney-in 47 strains of the Collaborative Cross (CC) mouse population, examining the regulation of these dynamics by expression quantitative trait loci (eQTL) and chromatin QTL (cQTL). QTL whose allelic effects were consistent across tissues were detected for 1,101 genes and 133 chromatin regions. Also detected were eQTL and cQTL whose allelic effects differed across tissues, including local-eQTL for Pik3c2g detected in all three tissues but with distinct allelic effects. Leveraging overlapping measurements of gene expression and chromatin accessibility on the same mice from multiple tissues, we used mediation analysis to identify chromatin and gene expression intermediates of eQTL effects. Based on QTL and mediation analyses over multiple tissues, we propose a causal model for the distal genetic regulation of Akr1e1, a gene involved in glycogen metabolism, through the zinc finger transcription factor Zfp985 and chromatin intermediates. This analysis demonstrates the complexity of transcriptional and chromatin dynamics and their regulation over multiple tissues, as well as the value of the CC and related genetic resource populations for identifying specific regulatory mechanisms within cells and tissues., Competing Interests: The authors have declared that no competing interests exist.

Idelalisib is a phosphatidylinositol 3-kinase inhibitor highly selective for the delta isoform that has shown good efficacy in treating chronic lymphocytic leukemia and follicular lymphoma. In clinical trials, however, idelalisib was associated with rare, but potentially serious liver and lung toxicities. In this study, we used the Collaborative Cross (CC) mouse population to identify genetic factors associated with the drug response that may inform risk management strategies for idelalisib in humans. Eight male mice (4 matched pairs) from 50 CC lines were treated once daily for 14 days by oral gavage with either vehicle or idelalisib at a dose selected to achieve clinically relevant peak plasma concentrations (150 mg/kg/day). The drug was well tolerated across all CC lines, and there were no observations of overt liver injury. Differences across CC lines were seen in drug concentration in plasma samples collected at the approximate Tmax on study Days 1, 7, and 14. There were also small but statistically significant treatment-induced alterations in plasma total bile acids and microRNA-122, and these may indicate early hepatocellular stress required for immune-mediated hepatotoxicity in humans. Idelalisib treatment further induced significant elevations in the total cell count of terminal bronchoalveolar lavage fluid, which may be analogous to pneumonitis observed in the clinic. Genetic mapping identified loci associated with interim plasma idelalisib concentration and the other 3 treatment-related endpoints. Thirteen priority candidate quantitative trait genes identified in CC mice may now guide interrogation of risk factors for adverse drug responses associated with idelalisib in humans., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses from extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments., (Copyright © 2019 Keele et al.)

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., (Copyright © 2019 Shorter et al.)

Standard QTL mapping procedures seek to identify genetic loci affecting the phenotypic mean while assuming that all individuals have the same residual variance. But when the residual variance differs systematically between groups, perhaps due to a genetic or environmental factor, such standard procedures can falter: in testing for QTL associations, they attribute too much weight to observations that are noisy and too little to those that are precise, resulting in reduced power and and increased susceptibility to false positives. The negative effects of such "background variance heterogeneity" (BVH) on standard QTL mapping have received little attention until now, although the subject is closely related to work on the detection of variance-controlling genes. Here we use simulation to examine how BVH affects power and false positive rate for detecting QTL affecting the mean (mQTL), the variance (vQTL), or both (mvQTL). We compare linear regression for mQTL and Levene's test for vQTL, with tests more recently developed, including tests based on the double generalized linear model (DGLM), which can model BVH explicitly. We show that, when used in conjunction with a suitable permutation procedure, the DGLM-based tests accurately control false positive rate and are more powerful than the other tests. We also find that some adverse effects of BVH can be mitigated by applying a rank inverse normal transform. We apply our novel approach, which we term "mean-variance QTL mapping", to publicly available data on a mouse backcross and, after accommodating BVH driven by sire, detect a new mQTL for bodyweight., (Copyright © 2018 Corty, Valdar.)

We present vqtl, an R package for mean-variance QTL mapping. This QTL mapping approach tests for genetic loci that influence the mean of the phenotype, termed mean QTL, the variance of the phenotype, termed variance QTL, or some combination of the two, termed mean-variance QTL. It is unique in its ability to correct for variance heterogeneity arising not only from the QTL itself but also from nuisance factors, such as sex, batch, or housing. This package provides functions to conduct genome scans, run permutations to assess the statistical significance, and make informative plots to communicate results. Because it is inter-operable with the popular qtl package and uses many of the same data structures and input patterns, it will be straightforward for geneticists to analyze future experiments with vqtl as well as re-analyze past experiments, possibly discovering new QTL., (Copyright © 2018 Corty, Valdar.)

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., (Copyright © 2018 Corty et al.)

Parent-of-origin effects (POE) in mammals typically arise from maternal effects or imprinting. In some instances, such POE have been associated with psychiatric disorders, as well as with changes in a handful of animal behaviors. However, POE on complex traits such as behavior remain largely uncharacterized. Moreover, although both behavior and epigenetic effects are known to be modified by perinatal environmental exposures such as nutrient deficiency, the architecture of such environment-by-POE is mostly unexplored. To study POE and environment-by-POE, we employ a relatively neglected but especially powerful experimental system for POE-detection: reciprocal F1 hybrids (RF1s). We exposed female NOD/ShiLtJ×C57Bl/6J and C57Bl/6J×NOD/ShiLtJ mice, perinatally, to one of four different diets, then after weaning recorded a set of behaviors that model psychiatric disease. Whole-brain microarray expression data revealed an imprinting-enriched set of 15 genes subject to POE. The most-significant expression POE, on the non-imprinted gene Carmil1 (a.k.a. Lrrc16a ), was validated using qPCR in the same and in a new set of mice. Several behaviors, especially locomotor behaviors, also showed POE. Bayesian mediation analysis suggested Carmil1 expression suppresses behavioral POE, and that the imprinted gene Airn suppresses POE on Carmil1 expression. A suggestive diet-by-POE was observed on percent center time in the open field test, and a significant diet-by-POE was observed on one imprinted gene, Mir341 , and on 16 non-imprinted genes. The relatively small, tractable set of POE and diet-by-POE detected on behavior and expression here motivates further studies examining such effects across RF1s on multiple genetic backgrounds., (Copyright © 2018 Oreper et al.)

The scientific community is increasingly concerned with the proportion of published "discoveries" that are not replicated in subsequent studies. The field of rodent behavioral phenotyping was one of the first to raise this concern, and to relate it to other methodological issues: the complex interaction between genotype and environment; the definitions of behavioral constructs; and the use of laboratory mice and rats as model species for investigating human health and disease mechanisms. In January 2015, researchers from various disciplines gathered at Tel Aviv University to discuss these issues. The general consensus was that the issue is prevalent and of concern, and should be addressed at the statistical, methodological and policy levels, but is not so severe as to call into question the validity and the usefulness of model organisms as a whole. Well-organized community efforts, coupled with improved data and metadata sharing, have a key role in identifying specific problems and promoting effective solutions. Replicability is closely related to validity, may affect generalizability and translation of findings, and has important ethical implications., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Crop establishment in carrot ( Daucus carota L.) is limited by slow seedling growth and delayed canopy closure, resulting in high management costs for weed control. Varieties with improved growth habit ( i.e. , larger canopy and increased shoot biomass) may help mitigate weed control, but the underlying genetics of these traits in carrot is unknown. This project used a diallel mating design coupled with recent Bayesian analytical methods to determine the genetic basis of carrot shoot growth. Six diverse carrot inbred lines with variable shoot size were crossed in WI in 2014. F1 hybrids, reciprocal crosses, and parental selfs were grown in a randomized complete block design with two blocks in WI (2015) and CA (2015, 2016). Measurements included canopy height, canopy width, shoot biomass, and root biomass. General and specific combining abilities were estimated using Griffing's Model I, which is a common analysis for plant breeding experiments. In parallel, additive, inbred, cross-specific, and maternal effects were estimated from a Bayesian mixed model, which is robust to dealing with data imbalance and outliers. Both additive and nonadditive effects significantly influenced shoot traits, with nonadditive effects playing a larger role early in the growing season, when weed control is most critical. Results suggest the presence of heritable variation and thus potential for improvement of these phenotypes in carrot. In addition, results present evidence of heterosis for root biomass, which is a major component of carrot yield., (Copyright © 2018 Turner et al.)

Influenza A virus (IAV) is a respiratory pathogen that causes substantial morbidity and mortality during both seasonal and pandemic outbreaks. Infection outcomes in unexposed populations are affected by host genetics, but the host genetic architecture is not well understood. Here, we obtain a broad view of how heritable factors affect a mouse model of response to IAV infection using an 8 × 8 diallel of the eight inbred founder strains of the Collaborative Cross (CC). Expanding on a prior statistical framework for modeling treatment response in diallels, we explore how a range of heritable effects modify acute host response to IAV through 4 d postinfection. Heritable effects in aggregate explained ∼57% of the variance in IAV-induced weight loss. Much of this was attributable to a pattern of additive effects that became more prominent through day 4 postinfection and was consistent with previous reports of antiinfluenza myxovirus resistance 1 ( Mx1 ) polymorphisms segregating between these strains; these additive effects largely recapitulated haplotype effects observed at the Mx1 locus in a previous study of the incipient CC, and are also replicated here in a CC recombinant intercross population. Genetic dominance of protective Mx1 haplotypes was observed to differ by subspecies of origin: relative to the domesticus null Mx1 allele, musculus acts dominantly whereas castaneus acts additively. After controlling for Mx1 , heritable effects, though less distinct, accounted for ∼34% of the phenotypic variance. Implications for future mapping studies are discussed., (Copyright © 2018 Maurizio et al.)

Objective: Obesity is a major risk factor for multiple diseases and is in part heritable, yet the majority of causative genetic variants that drive excessive adiposity remain unknown. Here, outbred heterogeneous stock (HS) rats were used in controlled environmental conditions to fine-map novel genetic modifiers of adiposity., Methods: Body weight and visceral fat pad weights were measured in male HS rats that were also genotyped genome-wide. Quantitative trait loci (QTL) were identified by genome-wide association of imputed single-nucleotide polymorphism (SNP) genotypes using a linear mixed effect model that accounts for unequal relatedness between the HS rats. Candidate genes were assessed by protein modeling and mediation analysis of expression for coding and noncoding variants, respectively., Results: HS rats exhibited large variation in adiposity traits, which were highly heritable and correlated with metabolic health. Fine-mapping of fat pad weight and body weight revealed three QTL and prioritized five candidate genes. Fat pad weight was associated with missense SNPs in Adcy3 and Prlhr and altered expression of Krtcap3 and Slc30a3, whereas Grid2 was identified as a candidate within the body weight locus., Conclusions: These data demonstrate the power of HS rats for identification of known and novel heritable mediators of obesity traits., (© 2017 The Obesity Society.)

Suboptimal environmental conditions during development can substantially alter the epigenome. Stable environmentally-induced changes to the germline epigenome, in particular, have important implications for the health of the next generation. We showed previously that developmental vitamin D depletion (DVD) resulted in loss of DNA methylation at several imprinted loci over two generations. Here, we assessed the impact of DVD on genome-wide methylation in mouse sperm in order to characterize the number, extent and distribution of methylation changes in response to DVD and to find genes that may be susceptible to this prevalent environmental perturbation. We detected 15,827 loci that were differentially methylated in DVD mouse sperm vs. controls. Most epimutations (69%) were loss of methylation, and the extent of methylation change and number of CpGs affected in a region were associated with genic location and baseline methylation state. Methylation response to DVD at validated loci was only detected in offspring that exhibited a phenotypic response to DVD (increased body and testes weight) suggesting the two types of responses are linked, though a causal relationship is unclear. Epimutations localized to regions enriched for developmental and metabolic genes and pathway analyses showed enrichment for Cadherin, Wnt, PDGF and Integrin signaling pathways. These findings show for the first time that vitamin D status during development leads to substantial DNA methylation changes across the sperm genome and that locus susceptibility is linked to genomic and epigenomic context.

The Collaborative Cross (CC) is a panel of recently established multiparental recombinant inbred mouse strains. For the CC, as for any multiparental population (MPP), effective experimental design and analysis benefit from detailed knowledge of the genetic differences between strains. Such differences can be directly determined by sequencing, but until now whole-genome sequencing was not publicly available for individual CC strains. An alternative and complementary approach is to infer genetic differences by combining two pieces of information: probabilistic estimates of the CC haplotype mosaic from a custom genotyping array, and probabilistic variant calls from sequencing of the CC founders. The computation for this inference, especially when performed genome-wide, can be intricate and time-consuming, requiring the researcher to generate nontrivial and potentially error-prone scripts. To provide standardized, easy-to-access CC sequence information, we have developed the Inbred Strain Variant Database (ISVdb). The ISVdb provides, for all the exonic variants from the Sanger Institute mouse sequencing dataset, direct sequence information for CC founders and, critically, the imputed sequence information for CC strains. Notably, the ISVdb also: (1) provides predicted variant consequence metadata; (2) allows rapid simulation of F1 populations; and (3) preserves imputation uncertainty, which will allow imputed data to be refined in the future as additional sequencing and genotyping data are collected. The ISVdb information is housed in an SQL database and is easily accessible through a custom online interface (http://isvdb.unc.edu), reducing the analytic burden on any researcher using the CC., (Copyright © 2017 Oreper et al.)

Clinical trials of tolvaptan showed it to be a promising candidate for the treatment of Autosomal Dominant Polycystic Kidney Disease (ADPKD) but also revealed potential for idiosyncratic drug-induced liver injury (DILI) in this patient population. To identify risk factors and mechanisms underlying tolvaptan DILI, 8 mice in each of 45 strains of the genetically diverse Collaborative Cross (CC) mouse population were treated with a single oral dose of either tolvaptan or vehicle. Significant elevations in plasma alanine aminotransferase (ALT) were observed in tolvaptan-treated animals in 3 of the 45 strains. Genetic mapping coupled with transcriptomic analysis in the liver was used to identify several candidate susceptibility genes including epoxide hydrolase 2, interferon regulatory factor 3, and mitochondrial fission factor. Gene pathway analysis revealed that oxidative stress and immune response pathways were activated in response to tolvaptan treatment across all strains, but genes involved in regulation of bile acid homeostasis were most associated with tolvaptan-induced elevations in ALT. Secretory leukocyte peptidase inhibitor (Slpi) mRNA was also induced in the susceptible strains and was associated with increased plasma levels of Slpi protein, suggesting a potential serum marker for DILI susceptibility. In summary, tolvaptan induced signs of oxidative stress, mitochondrial dysfunction, and innate immune response in all strains, but variation in bile acid homeostasis was most associated with susceptibility to the liver response. This CC study has indicated potential mechanisms underlying tolvaptan DILI and biomarkers of susceptibility that may be useful in managing the risk of DILI in ADPKD patients., (© The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Women are at an increased risk for developing affective disorders during times of hormonal flux, including menopause when the ovaries cease production of estrogen. However, while all women undergo menopause, not all develop an affective disorder. Increased vulnerability can result from genetic predisposition, environmental factors and gene by environment interactions. In order to investigate interactions between genetic background and estrogen depletion, we performed bilateral ovariectomy, a surgical procedure that results in estrogen depletion and is thought to model the post-menopausal state, in a genetically defined panel of 37 inbred mouse strains. Seventeen days post-ovariectomy, we assessed behavior in two standard rodent assays of anxiety- and depressive-like behavior, the open field and forced swim tests. We detected a significant interaction between ovariectomy and genetic background on anxiety-like behavior in the open field. No strain specific effects of ovariectomy were observed in the forced swim assay. However, we did observe significant strain effects for all behaviors in both the open field and forced swim tests. This study is the largest to date to look at the effects of ovariectomy on behavior and provides evidence that ovariectomy interacts with genetic background to alter anxiety-like behavior in an animal model of menopause., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Environmental perturbation of epigenetic mechanisms is linked to a growing number of diseases. Characterizing the role environmental factors play in modifying the epigenome is important for disease etiology. Vitamin D is an essential nutrient affecting brain, bone, heart, immune and reproductive health. Vitamin D insufficiency is a global issue, and the role in maternal and child health remains under investigation., Methods: We used Collaborative Cross (CC) inbred mice to characterize the effect of maternal vitamin D depletion on offspring phenotypic and epigenetic outcomes at imprinted domains ( H19/Igf2 , Snrpn , Dlk1/Gtl2 , and Grb10 ) in the soma (liver) and germline (sperm). We assessed outcomes in two generations of offspring to determine heritability. We used reciprocal crosses between lines CC001/Unc and CC011/Unc to investigate parent of origin effects., Results: Maternal vitamin D deficiency led to altered body weight and DNA methylation in two generations of offspring. Loci assayed in adult liver and sperm were mostly hypomethylated, but changes were few and small in effect size (<7 % difference on average). There was no change in total expression of genes adjacent to methylation changes in neonatal liver. Methylation changes were cell type specific such that changes at IG-DMR were present in sperm but not in liver. Some methylation changes were distinct between generations such that methylation changes at the H19ICR in second-generation liver were not present in first-generation sperm or liver. Interestingly, some diet-dependent changes in body weight and methylation were seemingly influenced by parent of origin such that reciprocal crosses exhibited inverse effects., Conclusions: These findings demonstrate that maternal vitamin D status plays a role in determining DNA methylation state in the germline and soma. Detection of methylation changes in the unexposed second-generation demonstrates that maternal vitamin D depletion can have long-term effects on the epigenome of subsequent generations. Differences in vitamin D-dependent epigenetic state between cell types and generations indicate perturbation of the epigenetic landscape rather than a targeted, locus-specific effect. While the biological importance of these subtle changes remains unclear, they warrant an investigation of epigenome-wide effects of maternal vitamin D depletion.