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Eosinophils are a highly abundant cell type in the gastrointestinal tract during homeostatic conditions, where they have recently been reported to take on an activated phenotype following colonization by the bacterial microbiota. To date, there have been few studies investigating whether eosinophils respond to infection with enteric bacterial pathogens and/or investigating the requirements for eosinophils for effective bacterial pathogen control. In this study, we investigated the response of eosinophils to an acute enteric infection of mice with the bacterial pathogen Salmonella enterica serovar Typhimurium. We also assessed whether eosinophil deficiency impacted Salmonella burdens in the intestinal tract or impacted the systemic dissemination of Salmonella following an oral infection of littermate wild-type BALB/cJ and eosinophil-deficient ΔdblGATA BALB/cJ mice. We found comparable Salmonella burdens in the intestinal tract of wild-type and eosinophil-deficient mice and no significant differences in the levels of Salmonella disseminating to systemic organs within 3 days of infection. Despite our evidence suggesting that eosinophils are not an essential cell type for controlling bacterial burdens in this acute infection setting, we found higher levels of eosinophils in gut-draining lymph nodes following infection, indicating that eosinophils do respond to Salmonella infection. Our data contribute to the growing evidence that eosinophils are responsive to bacterial stimuli, yet the influence of and requirements for eosinophils during bacterial infection appear to be highly context-dependent., Competing Interests: The authors declare no conflict of interest.

Because most humans resist Mycobacterium tuberculosis infection, there is a paucity of lung samples to study. To address this gap, we infected Diversity Outbred mice with M. tuberculosis and studied the lungs of mice in different disease states. After a low-dose aerosol infection, progressors succumbed to acute, inflammatory lung disease within 60 days, while controllers maintained asymptomatic infection for at least 60 days, and then developed chronic pulmonary tuberculosis (TB) lasting months to more than 1 year. Here, we identified features of asymptomatic M. tuberculosis infection by applying computational and statistical approaches to multimodal data sets. Cytokines and anti- M . tuberculosis cell wall antibodies discriminated progressors vs controllers with chronic pulmonary TB but could not classify mice with asymptomatic infection. However, a novel deep-learning neural network trained on lung granuloma images was able to accurately classify asymptomatically infected lungs vs acute pulmonary TB in progressors vs chronic pulmonary TB in controllers, and discrimination was based on perivascular and peribronchiolar lymphocytes. Because the discriminatory lesion was rich in lymphocytes and CD4 T cell-mediated immunity is required for resistance, we expected CD4 T-cell genes would be elevated in asymptomatic infection. However, the significantly different, highly expressed genes were from B-cell pathways (e.g., Bank1 , Cd19 , Cd79 , Fcmr , Ms4a1 , Pax5 , and H2-Ob ), and CD20+ B cells were enriched in the perivascular and peribronchiolar regions of mice with asymptomatic M. tuberculosis infection. Together, these results indicate that genetically controlled B-cell responses are important for establishing asymptomatic M. tuberculosis lung infection., Competing Interests: The authors declare no conflict of interest.

To explore the influence of genetics on homeostatic regulation of dendritic cell (DC) numbers, we present a screen of DCs and their progenitors in lymphoid and non-lymphoid tissues in Collaborative Cross (CC) and Diversity Outbred (DO) mice. We report 30 and 71 loci with logarithm of the odds (LOD) scores >8.18 and ranging from 6.67 to 8.19, respectively. The analysis reveals the highly polygenic and pleiotropic architecture of this complex trait, including many of the previously identified genetic regulators of DC development and maturation. Two SNPs in genes potentially underlying variation in DC homeostasis, a splice variant in Gramd4 (rs235532740) and a missense variant in Orai3 (rs216659754), are confirmed by gene editing using CRISPR-Cas9. Gramd4 is a central regulator of DC homeostasis that impacts the entire DC lineage, and Orai3 regulates cDC2 numbers in tissues. Overall, the data reveal a large number of candidate genes regulating DC homeostasis in vivo., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Mycobacterium tuberculosis infects two billion people across the globe, and results in 8-9 million new tuberculosis (TB) cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. Here, we investigate the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using immune and inflammatory mediators; and clinical, microbiological, and granuloma correlates of disease identified five new loci on mouse chromosomes 1, 2, 4, 16; and three known loci on chromosomes 3 and 17. Further, multiple positively correlated traits shared loci on chromosomes 1, 16, and 17 and had similar patterns of allele effects, suggesting these loci contain critical genetic regulators of inflammatory responses to M. tuberculosis. To narrow the list of candidate genes, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks to generate scores representing functional relationships. The scores were used to rank candidates for each mapped trait, resulting in 11 candidate genes: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Although all candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling, and all contain single nucleotide polymorphisms (SNPs), SNPs in only four genes (S100a8, Itgb5, Fstl1, Zfp318) are predicted to have deleterious effects on protein functions. We performed methodological and candidate validations to (i) assess biological relevance of predicted allele effects by showing that Diversity Outbred mice carrying PWK/PhJ alleles at the H-2 locus on chromosome 17 QTL have shorter survival; (ii) confirm accuracy of predicted allele effects by quantifying S100A8 protein in inbred founder strains; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this body of work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and functionally relevant gene candidates that may be major regulators of complex host-pathogens interactions contributing to granuloma necrosis and acute inflammation in pulmonary TB., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Gatti et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The Canadian Society for Immunology (CSI) established a formal Equity, Diversity, and Inclusion (EDI) Committee with the goal of providing EDI advocacy and leadership within the CSI, as well as in the broader scientific community. A first task of this committee was to review the publicly available historical data on gender representation within the CSI's membership, leadership, award recipients, and conference chairs/presenters as a step in establishing a baseline reference point and monitoring the trajectory of future success in achieving true inclusion. We found that, except for overall membership and a specific subset of awards, all categories showed a historical bias toward men, particularly prior to 2010. Bias persists in various categories, evident even in recent years. However, we note an encouraging trend toward greater gender parity, particularly in the roles of President, symposium presenters, and workshop chairs, especially from 2017 onward. We present these findings as well as our recommendations to enhance inclusivity. These include a more comprehensive collection and secure storage of self-identification data, emphasis on EDI as an essential component of all annual meeting activities, and innovative measures of outreach, collaboration, and leadership with the aim of making the CSI a model for improving EDI in other professional research societies., (Copyright © 2024 by The American Association of Immunologists, Inc.)

The laboratory mouse has served as the premier animal model system for both basic and preclinical investigations for over a century. However, laboratory mice capture only a subset of the genetic variation found in wild mouse populations, ultimately limiting the potential of classical inbred strains to uncover phenotype-associated variants and pathways. Wild mouse populations are reservoirs of genetic diversity that could facilitate the discovery of new functional and disease-associated alleles, but the scarcity of commercially available, well-characterized wild mouse strains limits their broader adoption in biomedical research. To overcome this barrier, we have recently developed, sequenced, and phenotyped a set of 11 inbred strains derived from wild-caught Mus musculus domesticus. Each of these "Nachman strains" immortalizes a unique wild haplotype sampled from one of five environmentally distinct locations across North and South America. Whole genome sequence analysis reveals that each strain carries between 4.73-6.54 million single nucleotide differences relative to the GRCm39 mouse reference, with 42.5% of variants in the Nachman strain genomes absent from current classical inbred mouse strain panels. We phenotyped the Nachman strains on a customized pipeline to assess the scope of disease-relevant neurobehavioral, biochemical, physiological, metabolic, and morphological trait variation. The Nachman strains exhibit significant inter-strain variation in >90% of 1119 surveyed traits and expand the range of phenotypic diversity captured in classical inbred strain panels. These novel wild-derived inbred mouse strain resources are set to empower new discoveries in both basic and preclinical research., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Dumont et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Mycobacterium tuberculosis (M.tb.) infection leads to over 1.5 million deaths annually, despite widespread vaccination with BCG at birth. Causes for the ongoing tuberculosis endemic are complex and include the failure of BCG to protect many against progressive pulmonary disease. Host genetics is one of the known factors implicated in susceptibility to primary tuberculosis, but less is known about the role that host genetics plays in controlling host responses to vaccination against M.tb. Here, we addressed this gap by utilizing Diversity Outbred (DO) mice as a small animal model to query genetic drivers of vaccine-induced protection against M.tb. DO mice are a highly genetically and phenotypically diverse outbred population that is well suited for fine genetic mapping. Similar to outcomes in people, our previous studies demonstrated that DO mice have a wide range of disease outcomes following BCG vaccination and M.tb. challenge. In the current study, we used a large population of BCG-vaccinated/M.tb.-challenged mice to perform quantitative trait loci mapping of complex infection traits; these included lung and spleen M.tb. burdens, as well as lung cytokines measured at necropsy. We found sixteen chromosomal loci associated with complex infection traits and cytokine production. QTL associated with bacterial burdens included a region encoding major histocompatibility antigens that are known to affect susceptibility to tuberculosis, supporting validity of the approach. Most of the other QTL represent novel associations with immune responses to M.tb. and novel pathways of cytokine regulation. Most importantly, we discovered that protection induced by BCG is a multigenic trait, in which genetic loci harboring functionally-distinct candidate genes influence different aspects of immune responses that are crucial collectively for successful protection. These data provide exciting new avenues to explore and exploit in developing new vaccines against M.tb., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Eosinophils are present in the thymus of mammals, yet their function at this site during homeostatic development is unknown. We used flow cytometry to determine the abundance and phenotype of eosinophils (here defined as SSchigh SiglecF+ CD11b+ CD45+ cells) in the thymus of mice during the neonatal period, the later postnatal period, and into adulthood. We show that both the total number of thymic eosinophils and their frequency among leukocytes increase over the first 2 wk of life and that their accumulation in the thymus is dependent on the presence of an intact bacterial microbiota. We report that thymic eosinophils express the interleukin-5 receptor (CD125), CD80, and IDO, and that subsets of thymic eosinophils express CD11c and major histocompatibility complex II (MHCII). We found that the frequency of MHCII-expressing thymic eosinophils increases over the first 2 wk of life, and that during this early-life period the highest frequency of MHCII-expressing thymic eosinophils is located in the inner medullary region. These data suggest a temporal and microbiota-dependent regulation of eosinophil abundance and functional capabilities in the thymus., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Leukocyte Biology.)

The molecular bases of how host genetic variation impacts the gut microbiome remain largely unknown. Here we used a genetically diverse mouse population and applied systems genetics strategies to identify interactions between host and microbe phenotypes including microbial functions, using faecal metagenomics, small intestinal transcripts and caecal lipids that influence microbe-host dynamics. Quantitative trait locus (QTL) mapping identified murine genomic regions associated with variations in bacterial taxa; bacterial functions including motility, sporulation and lipopolysaccharide production and levels of bacterial- and host-derived lipids. We found overlapping QTL for the abundance of Akkermansia muciniphila and caecal levels of ornithine lipids. Follow-up in vitro and in vivo studies revealed that A. muciniphila is a major source of these lipids in the gut, provided evidence that ornithine lipids have immunomodulatory effects and identified intestinal transcripts co-regulated with these traits including Atf3, which encodes for a transcription factor that plays vital roles in modulating metabolism and immunity. Collectively, these results suggest that ornithine lipids are potentially important for A. muciniphila-host interactions and support the role of host genetics as a determinant of responses to gut microbes., (© 2023. The Author(s).)

The Collaborative Cross and the Diversity Outbred mouse populations are related multiparental populations, derived from the same 8 isogenic founder strains. They carry >50 M known genetic variants, which makes them ideal tools for mapping genetic loci that regulate phenotypes, including physiological and molecular traits. Mapping quantitative trait loci requires statistical and computational training, which can present a barrier to access for some researchers. The QTLViewer software allows users to graphically explore Collaborative Cross and Diversity Outbred quantitative trait locus mapping and related analyses performed through the R/qtl2 package. Additionally, the QTLViewer website serves as a repository for published Collaborative Cross and Diversity Outbred studies, increasing the accessibility of these genetic resources to the broader scientific community., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.)

Background: A strong predictor for the development of alcohol use disorder (AUD) is altered sensitivity to the intoxicating effects of alcohol. Individual differences in the initial sensitivity to alcohol are controlled in part by genetic factors. Mice offer a powerful tool to elucidate the genetic basis of behavioral and physiological traits relevant to AUD, but conventional experimental crosses have only been able to identify large chromosomal regions rather than specific genes. Genetically diverse, highly recombinant mouse populations make it possible to observe a wider range of phenotypic variation, offer greater mapping precision, and thus increase the potential for efficient gene identification., Methods: We have taken advantage of the Diversity Outbred (DO) mouse population to identify and precisely map quantitative trait loci (QTL) associated with ethanol sensitivity. We phenotyped 798 male J:DO mice for three measures of ethanol sensitivity: ataxia, hypothermia, and loss of the righting response. We used high-density MegaMUGA and GigaMUGA to obtain genotypes ranging from 77,808 to 143,259 SNPs. We also performed RNA sequencing in striatum to map expression QTLs and identify gene expression-trait correlations. We then applied a systems genetic strategy to identify narrow QTLs and construct the network of correlations that exists between DNA sequence, gene expression values, and ethanol-related phenotypes to prioritize our list of positional candidate genes., Results: We observed large amounts of phenotypic variation with the DO population and identified suggestive and significant QTLs associated with ethanol sensitivity on chromosomes 1, 2, and 16. The implicated regions were narrow (4.5-6.9 Mb in size) and each QTL explained ~4-5% of the variance., Conclusions: Our results can be used to identify alleles that contribute to AUD in humans, elucidate causative biological mechanisms, or assist in the development of novel therapeutic interventions., (© 2022 by the Research Society on Alcoholism.)

More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, serum protein biomarkers to help diagnose TB, which afflicts millions of people in high-burden countries. However, the protein biomarker pipeline is small. Here, we used the Diversity Outbred (DO) mouse population to address this gap, identifying five protein biomarker candidates. One protein biomarker, serum CXCL1, met the World Health Organization's Targeted Product Profile for a triage test to diagnose active TB from latent M.tb infection (LTBI), non-TB lung disease, and normal sera in HIV-negative, adults from South Africa and Vietnam. To find the biomarker candidates, we quantified seven immune cytokines and four inflammatory proteins corresponding to highly expressed genes unique to progressor DO mice. Next, we applied statistical and machine learning methods to the data, i.e., 11 proteins in lungs from 453 infected and 29 non-infected mice. After searching all combinations of five algorithms and 239 protein subsets, validating, and testing the findings on independent data, two combinations accurately diagnosed progressor DO mice: Logistic Regression using MMP8; and Gradient Tree Boosting using a panel of 4: CXCL1, CXCL2, TNF, IL-10. Of those five protein biomarker candidates, two (MMP8 and CXCL1) were crucial for classifying DO mice; were above the limit of detection in most human serum samples; and had not been widely assessed for diagnostic performance in humans before. In patient sera, CXCL1 exceeded the triage diagnostic test criteria (>90% sensitivity; >70% specificity), while MMP8 did not. Using Area Under the Curve analyses, CXCL1 averaged 94.5% sensitivity and 88.8% specificity for active pulmonary TB (ATB) vs LTBI; 90.9% sensitivity and 71.4% specificity for ATB vs non-TB; and 100.0% sensitivity and 98.4% specificity for ATB vs normal sera. Our findings overall show that the DO mouse population can discover diagnostic-quality, serum protein biomarkers of human TB., Competing Interests: The authors have declared that no competing interests exist.

Background: Mutations in COL4A5 are responsible for 80% of cases of X-linked Alport Syndrome (XLAS). Although genes that cause AS are well characterized, people with AS who have similar genetic mutations present with a wide variation in the extent of kidney impairment and age of onset, suggesting the activities of modifier genes., Methods: We created a cohort of genetically diverse XLAS male and female mice using the Diversity Outbred mouse resource and measured albuminuria, GFR, and gene expression. Using a quantitative trait locus approach, we mapped modifier genes that can best explain the underlying phenotypic variation measured in our diverse population., Results: Genetic analysis identified several loci associated with the variation in albuminuria and GFR, including a locus on the X chromosome associated with X inactivation and a locus on chromosome 2 containing Fmn1 . Subsequent analysis of genetically reduced Fmn1 expression in Col4a5 knockout mice showed a decrease in albuminuria, podocyte effacement, and podocyte protrusions in the glomerular basement membrane, which support the candidacy of Fmn1 as a modifier gene for AS., Conclusion: With this novel approach, we emulated the variability in the severity of kidney phenotypes found in human patients with Alport Syndrome through albuminuria and GFR measurements. This approach can identify modifier genes in kidney disease that can be used as novel therapeutic targets., (Copyright © 2021 by the American Society of Nephrology.)

Intestinal helminth infection can impair host resistance to co-infection with enteric bacterial pathogens. However, it is not known whether helminth drug-clearance can restore host resistance to bacterial infection. Using a mouse helminth-Salmonella co-infection system, we show that anthelmintic treatment prior to Salmonella challenge is sufficient to restore host resistance to Salmonella. The presence of the small intestine-dwelling helminth Heligmosomoides polygyrus at the point of Salmonella infection supports the initial establishment of Salmonella in the small intestinal lumen. Interestingly, if helminth drug-clearance is delayed until Salmonella has already established in the small intestinal lumen, anthelmintic treatment does not result in complete clearance of Salmonella. This suggests that while the presence of helminths supports initial Salmonella colonization, helminths are dispensable for Salmonella persistence in the host small intestine. These data contribute to the mechanistic understanding of how an ongoing or prior helminth infection can affect pathogenic bacterial colonization and persistence in the mammalian intestine., Competing Interests: The authors have declared that no competing interests exist.

Background: Identifying which individuals will develop tuberculosis (TB) remains an unresolved problem due to few animal models and computational approaches that effectively address its heterogeneity. To meet these shortcomings, we show that Diversity Outbred (DO) mice reflect human-like genetic diversity and develop human-like lung granulomas when infected with Mycobacterium tuberculosis (M.tb) ., Methods: Following M.tb infection, a "supersusceptible" phenotype develops in approximately one-third of DO mice characterized by rapid morbidity and mortality within 8 weeks. These supersusceptible DO mice develop lung granulomas patterns akin to humans. This led us to utilize deep learning to identify supersusceptibility from hematoxylin & eosin (H&E) lung tissue sections utilizing only clinical outcomes (supersusceptible or not-supersusceptible) as labels., Findings: The proposed machine learning model diagnosed supersusceptibility with high accuracy (91.50 ± 4.68%) compared to two expert pathologists using H&E stained lung sections (94.95% and 94.58%). Two non-experts used the imaging biomarker to diagnose supersusceptibility with high accuracy (88.25% and 87.95%) and agreement (96.00%). A board-certified veterinary pathologist (GB) examined the imaging biomarker and determined the model was making diagnostic decisions using a form of granuloma necrosis (karyorrhectic and pyknotic nuclear debris). This was corroborated by one other board-certified veterinary pathologist. Finally, the imaging biomarker was quantified, providing a novel means to convert visual patterns within granulomas to data suitable for statistical analyses., Implications: Overall, our results have translatable implication to improve our understanding of TB and also to the broader field of computational pathology in which clinical outcomes alone can drive automatic identification of interpretable imaging biomarkers, knowledge discovery, and validation of existing clinical biomarkers., Funding: National Institutes of Health and American Lung Association., Competing Interests: Declaration of Competing Interest Mr. Tavolara has nothing to disclose. Dr. Niazi has nothing to disclose. Ms. Ginese has nothing to disclose. Dr. Piedra-Mora has nothing to disclose. Dr. Gatti has nothing to disclose. Dr. Beamer has nothing to disclose. Dr. Gurcan has nothing to disclose., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Despite the crucial roles of lipids in metabolism, we are still at the early stages of comprehensively annotating lipid species and their genetic basis. Mass spectrometry-based discovery lipidomics offers the potential to globally survey lipids and their relative abundances in various biological samples. To discover the genetics of lipid features obtained through high-resolution liquid chromatography-tandem mass spectrometry, we analysed liver and plasma from 384 diversity outbred mice, and quantified 3,283 molecular features. These features were mapped to 5,622 lipid quantitative trait loci and compiled into a public web resource termed LipidGenie. The data are cross-referenced to the human genome and offer a bridge between genetic associations in humans and mice. Harnessing this resource, we used genome-lipid association data as an additional aid to identify a number of lipids, for example gangliosides through their association with B4galnt1, and found evidence for a group of sex-specific phosphatidylcholines through their shared locus. Finally, LipidGenie's ability to query either mass or gene-centric terms suggests acyl-chain-specific functions for proteins of the ABHD family.

Mouse embryonic stem cells (mESCs) cultured in the presence of LIF occupy a ground state with highly active pluripotency-associated transcriptional and epigenetic circuitry. However, ground state pluripotency in some inbred strain backgrounds is unstable in the absence of ERK1/2 and GSK3 inhibition. Using an unbiased genetic approach, we dissect the basis of this divergent response to extracellular cues by profiling gene expression and chromatin accessibility in 170 genetically heterogeneous mESCs. We map thousands of loci affecting chromatin accessibility and/or transcript abundance, including 10 QTL hotspots where genetic variation at a single locus coordinates the regulation of genes throughout the genome. For one hotspot, we identify a single enhancer variant ∼10 kb upstream of Lifr associated with chromatin accessibility and mediating a cascade of molecular events affecting pluripotency. We validate causation through reciprocal allele swaps, demonstrating the functional consequences of noncoding variation in gene regulatory networks that stabilize pluripotent states in vitro., Competing Interests: Declaration of Interests T.C. and D.K.P. have an equity interest in Predictive Biology., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Genetic mechanisms underlying age-related cognitive decline and dementia remain poorly understood. Here, we take advantage of the Diversity Outbred mouse population to utilize quantitative trait loci mapping and identify Dlgap2 as a positional candidate responsible for modifying working memory decline. To evaluate the translational relevance of this finding, we utilize longitudinal cognitive measures from human patients, RNA expression from post-mortem brain tissue, data from a genome-wide association study (GWAS) of Alzheimer's dementia (AD), and GWAS results in African Americans. We find an association between Dlgap2 and AD phenotypes at the variant, gene and protein expression, and methylation levels. Lower cortical DLGAP2 expression is observed in AD and is associated with more plaques and tangles at autopsy and faster cognitive decline. Results will inform future studies aimed at investigating the cross-species role of Dlgap2 in regulating cognitive decline and highlight the benefit of using genetically diverse mice to prioritize novel candidates., Competing Interests: Declaration of Interests C.C.K. and S.M.N. have filed a related patent application. The other authors declare no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Biomedical research is becoming increasingly data driven. New technologies that generate large-scale, complex data are continually emerging and evolving. As a result, there is a concurrent need for training researchers to use and understand new computational tools. Here we describe an efficient and effective approach to developing curriculum materials that can be deployed in a research environment to meet this need., Competing Interests: The authors have declared that no competing interests exist.

Zileuton is an orally active inhibitor of leukotriene synthesis for maintenance treatment of asthma, for which clinical usage has been associated with idiosyncratic liver injury. Mechanistic understanding of zileuton toxicity is hampered by the rarity of the cases and lack of an animal model. A promising model for mechanistic study of rare liver injury is the Diversity Outbred (J:DO) mouse population, with genetic variation similar to that found in humans. In this study, female DO mice were administered zileuton or vehicle daily for 7 days (i.g.). Serum liver enzymes were elevated in the zileuton group, with marked interindividual variability in response. Zileuton exposure-induced findings in susceptible DO mice included microvesicular fatty change, hepatocellular mitosis, and hepatocellular necrosis. Inducible nitric oxide synthase and nitrotyrosine abundance were increased in livers of animals with necrosis and those with fatty change, implicating nitrosative stress as a possible injury mechanism. Conversely, DO mice lacking adverse liver pathology following zileuton exposure experienced decreased hepatic concentrations of resistin and increased concentrations of insulin and leptin, providing potential clues into mechanisms of toxicity resistance. Transcriptome pathway analysis highlighted mitochondrial dysfunction and altered fatty acid oxidation as key molecular perturbations associated with zileuton exposure, and suggested that interindividual differences in cytochrome P450 metabolism, glutathione-mediated detoxification, and farnesoid X receptor signaling may contribute to zileuton-induced liver injury (ZILI). Taken together, DO mice provided a platform for investigating mechanisms of toxicity and resistance in context of ZILI which may lead to targeted therapeutic interventions., (Published by Oxford University Press on behalf of the Society of Toxicology 2020. This work is written by US Government employees and is in the public domain in the US.)

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., (© Sleep Research Society 2020. Published by Oxford University Press [on behalf of the Sleep Research Society]. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Many studies of Mycobacterium tuberculosis infection and immunity have used mouse models. However, outcomes of vaccination and challenge with M. tuberculosis in inbred mouse strains do not reflect the full range of outcomes seen in people. Previous studies indicated that the novel Diversity Outbred (DO) mouse population exhibited a spectrum of outcomes after primary aerosol infection with M. tuberculosis Here, we demonstrate the value of this novel mouse population for studies of vaccination against M. tuberculosis aerosol challenge. Using the only currently licensed tuberculosis vaccine, we found that the DO population readily controlled systemic Mycobacterium bovis BCG bacterial burdens and that BCG vaccination significantly improved survival across the DO population upon challenge with M. tuberculosis Many individual DO mice that were vaccinated with BCG and then challenged with M. tuberculosis exhibited low bacterial burdens, low or even no systemic dissemination, little weight loss, and only minor lung pathology. In contrast, some BCG-vaccinated DO mice progressed quickly to fulminant disease upon M. tuberculosis challenge. Across the population, most of these disease parameters were at most modestly correlated with each other and were often discordant. This result suggests the need for a multiparameter metric to better characterize "disease" and "protection," with closer similarity to the complex case definitions used in people. Taken together, these results demonstrate that DO mice provide a novel small-animal model of vaccination against tuberculosis that better reflects the wide spectrum of outcomes seen in people. IMPORTANCE We vaccinated the Diversity Outbred (DO) population of mice with BCG, the only vaccine currently used to protect against tuberculosis, and then challenged them with M. tuberculosis by aerosol. We found that the BCG-vaccinated DO mouse population exhibited a wide range of outcomes, in which outcomes in individual mice ranged from minimal respiratory or systemic disease to fulminant disease and death. The breadth of these outcomes appears similar to the range seen in people, indicating that DO mice may serve as an improved small-animal model to study tuberculosis infection and immunity. Moreover, sophisticated tools are available for the use of these mice to map genes contributing to control of vaccination. Thus, the present studies provided an important new tool in the fight against tuberculosis.

Cancer risk from galactic cosmic radiation exposure is considered a potential "showstopper" for a manned mission to Mars. Calculating the actual risks confronted by spaceflight crews is complicated by our limited understanding of the carcinogenic effects of high-charge, high-energy (HZE) ions, a radiation type for which no human exposure data exist. Using a mouse model of genetic diversity, we find that the histotype spectrum of HZE ion-induced tumors is similar to the spectra of spontaneous and γ-ray-induced tumors and that the genomic loci controlling susceptibilities overlap between groups for some tumor types. Where it occurs, this overlap indicates shared tumorigenesis mechanisms regardless of the type of radiation exposure and supports the use of human epidemiological data from γ-ray exposures to predict cancer risks from galactic cosmic rays., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

The microbial communities that inhabit the distal gut of humans and other mammals exhibit large inter-individual variation. While host genetics is a known factor that influences gut microbiota composition, the mechanisms underlying this variation remain largely unknown. Bile acids (BAs) are hormones that are produced by the host and chemically modified by gut bacteria. BAs serve as environmental cues and nutrients to microbes, but they can also have antibacterial effects. We hypothesized that host genetic variation in BA metabolism and homeostasis influence gut microbiota composition. To address this, we used the Diversity Outbred (DO) stock, a population of genetically distinct mice derived from eight founder strains. We characterized the fecal microbiota composition and plasma and cecal BA profiles from 400 DO mice maintained on a high-fat high-sucrose diet for ~22 weeks. Using quantitative trait locus (QTL) analysis, we identified several genomic regions associated with variations in both bacterial and BA profiles. Notably, we found overlapping QTL for Turicibacter sp. and plasma cholic acid, which mapped to a locus containing the gene for the ileal bile acid transporter, Slc10a2. Mediation analysis and subsequent follow-up validation experiments suggest that differences in Slc10a2 gene expression associated with the different strains influences levels of both traits and revealed novel interactions between Turicibacter and BAs. This work illustrates how systems genetics can be utilized to generate testable hypotheses and provide insight into host-microbe interactions., Competing Interests: The authors have declared that no competing interests exist.

Anthracyclines cause progressive cardiotoxicity whose ultimate severity is individual to the patient. Genetic determinants contributing to this variation are difficult to study using current mouse models. Our objective was to determine whether a spectrum of anthracycline induced cardiac disease can be elicited across 10 Collaborative Cross mouse strains given the same dose of doxorubicin. Mice from ten distinct strains were given 5 mg/kg of doxorubicin intravenously once weekly for 5 weeks (total 25 mg/kg). Mice were killed at acute or chronic timepoints. Body weight was assessed weekly, followed by terminal complete blood count, pathology and a panel of biomarkers. Linear models were fit to assess effects of treatment, sex, and sex-by-treatment interactions for each timepoint. Impaired growth and cardiac pathology occurred across all strains. Severity of these varied by strain and sex, with greater severity in males. Cardiac troponin I and myosin light chain 3 demonstrated strain- and sex-specific elevations in the acute phase with subsequent decline despite ongoing progression of cardiac disease. Acute phase cardiac troponin I levels predicted the ultimate severity of cardiac pathology poorly, whereas myosin light chain 3 levels predicted the extent of chronic cardiac injury in males. Strain- and sex-dependent renal toxicity was evident. Regenerative anemia manifested during the acute period. We confirm that variable susceptibility to doxorubicin-induced cardiotoxicity observed in humans can be modeled in a panel of CC strains. In addition, we identified a potential predictive biomarker in males. CC strains provide reproducible models to explore mechanisms contributing to individual susceptibility in humans., (Copyright © 2019 Zeiss et al.)

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

Genetic susceptibility to type 2 diabetes is primarily due to β-cell dysfunction. However, a genetic study to directly interrogate β-cell function ex vivo has never been previously performed. We isolated 233,447 islets from 483 Diversity Outbred (DO) mice maintained on a Western-style diet, and measured insulin secretion in response to a variety of secretagogues. Insulin secretion from DO islets ranged >1,000-fold even though none of the mice were diabetic. The insulin secretory response to each secretagogue had a unique genetic architecture; some of the loci were specific for one condition, whereas others overlapped. Human loci that are syntenic to many of the insulin secretion QTL from mouse are associated with diabetes-related SNPs in human genome-wide association studies. We report on three genes, Ptpn18, Hunk and Zfp148, where the phenotype predictions from the genetic screen were fulfilled in our studies of transgenic mouse models. These three genes encode a non-receptor type protein tyrosine phosphatase, a serine/threonine protein kinase, and a Krϋppel-type zinc-finger transcription factor, respectively. Our results demonstrate that genetic variation in insulin secretion that can lead to type 2 diabetes is discoverable in non-diabetic individuals.

Data cleaning is an important first step in most statistical analyses, including efforts to map the genetic loci that contribute to variation in quantitative traits. Here we illustrate approaches to quality control and cleaning of array-based genotyping data for multiparent populations (experimental crosses derived from more than two founder strains), using MegaMUGA array data from a set of 291 Diversity Outbred (DO) mice. Our approach employs data visualizations that can reveal problems at the level of individual mice or with individual SNP markers. We find that the proportion of missing genotypes for each mouse is an effective indicator of sample quality. We use microarray probe intensities for SNPs on the X and Y chromosomes to confirm the sex of each mouse, and we use the proportion of matching SNP genotypes between pairs of mice to detect sample duplicates. We use a hidden Markov model (HMM) reconstruction of the founder haplotype mosaic across each mouse genome to estimate the number of crossovers and to identify potential genotyping errors. To evaluate marker quality, we find that missing data and genotyping error rates are the most effective diagnostics. We also examine the SNP genotype frequencies with markers grouped according to their minor allele frequency in the founder strains. For markers with high apparent error rates, a scatterplot of the allele-specific probe intensities can reveal the underlying cause of incorrect genotype calls. The decision to include or exclude low-quality samples can have a significant impact on the mapping results for a given study. We find that the impact of low-quality markers on a given study is often minimal, but reporting problematic markers can improve the utility of the genotyping array across many studies., (Copyright © 2019 Broman et al.)

Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P = 3.1 x 10-12) BMD locus on Chromosome 3@52.5 Mbp that replicated in two separate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts. Furthermore, its expression was regulated by a local expression QTL (eQTL), which overlapped the BMD association. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp-/- mice displayed increased osteogenic differentiation. Lhfp-/- mice also had elevated BMD due to increased cortical bone mass. Lastly, we identified SNPs in human LHFP that were associated (P = 1.2 x 10-5) with heel BMD. In conclusion, we used GWAS and systems genetics to identify Lhfp as a regulator of osteoblast activity and bone mass., Competing Interests: The authors have declared that no competing interests exist.

R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely used R/qtl software package to include multiparent populations derived from more than two founder strains, such as the Collaborative Cross and Diversity Outbred mice, heterogeneous stocks, and MAGIC plant populations. R/qtl2 is designed to handle modern high-density genotyping data and high-dimensional molecular phenotypes, including gene expression and proteomics. R/qtl2 includes the ability to perform genome scans using a linear mixed model to account for population structure, and also includes features to impute SNPs based on founder strain genomes and to carry out association mapping. The R/qtl2 software provides all of the basic features needed for QTL mapping, including graphical displays and summary reports, and it can be extended through the creation of add-on packages. R/qtl2, which is free and open source software written in the R and C++ programming languages, comes with a test framework., (Copyright © 2019 Broman et al.)

The original article has been published with an incorrect text in Materials and Methods section. The corrected text should read as.

Anthracycline chemotherapy (AC) is associated with decline in left ventricular ejection fraction (LVEF), yet the mechanisms remain unclear. Although changes in microRNAs (miRs) have been identified in adult cardiovascular disease, miR profiles in pediatric patients with AC have not been well studied. The goal of this study was to examine miR profiles (unbiased array) in pediatric patients with AC compared with age-matched referent normal patients. We hypothesize that pediatric patients with AC will express a unique miR profile at the initiation and completion of therapy and will be related to LVEF. Serum was collected in pediatric patients (10-22 yr, n = 12) with newly diagnosed malignancy requiring AC within 24-48 h after the initiation of therapy (30-60 mg/m 2 ) and ~1 yr after completing therapy. A custom microarray of 84 miRs associated with cardiovascular disease was used (quantitative RT-PCR) and indexed to referent normal profiles (13-17 yr, n = 17). LVEF was computed by cardiac MRI. LVEF fell from AC initiation at ~1 yr after AC completion (64.28 ± 1.78% vs. 57.53 ± 0.95%, respectively, P = 0.004). Of the 84 miRs profiled, significant shifts in 17 miRs occurred relative to referent normal ( P ≤ 0.05). Moreover, the functional domain of miRs associated with myocardial differentiation and development fell over threefold at the completion of AC ( P ≤ 0.05). Moreover, eight miRs were significantly downregulated after AC completion in those patients with the greatest decline in LVEF (≥10%, P < 0.05). This study demonstrates, for the first time, that changes in miR expression occur in pediatric patients with AC. These findings suggest that miRs are a potential strategy for the early identification of patients with AC susceptible to left ventricular dysfunction. NEW & NOTEWORTHY Although anthracycline chemotherapy (AC) is effective for a number of pediatric cancers, an all too often consequence of AC is the development of left ventricular failure. The present study identified that specific shifts in the pattern of microRNAs, which regulate myocardial growth, function, and viability, occurred during and after AC in pediatric patients, whereby the magnitude of this shift was associated with the degree of left ventricular failure.

[This corrects the article DOI: http://dx.doi.org/10.1289/ehp.1408202.].

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.

The majority of gene loci that have been associated with type 2 diabetes play a role in pancreatic islet function. To evaluate the role of islet gene expression in the etiology of diabetes, we sensitized a genetically diverse mouse population with a Western diet high in fat (45% kcal) and sucrose (34%) and carried out genome-wide association mapping of diabetes-related phenotypes. We quantified mRNA abundance in the islets and identified 18,820 expression QTL. We applied mediation analysis to identify candidate causal driver genes at loci that affect the abundance of numerous transcripts. These include two genes previously associated with monogenic diabetes ( PDX1 and HNF4A ), as well as three genes with nominal association with diabetes-related traits in humans ( FAM83E , IL6ST , and SAT2 ). We grouped transcripts into gene modules and mapped regulatory loci for modules enriched with transcripts specific for α-cells, and another specific for δ-cells. However, no single module enriched for β-cell-specific transcripts, suggesting heterogeneity of gene expression patterns within the β-cell population. A module enriched in transcripts associated with branched-chain amino acid metabolism was the most strongly correlated with physiological traits that reflect insulin resistance. Although the mice in this study were not overtly diabetic, the analysis of pancreatic islet gene expression under dietary-induced stress enabled us to identify correlated variation in groups of genes that are functionally linked to diabetes-associated physiological traits. Our analysis suggests an expected degree of concordance between diabetes-associated loci in the mouse and those found in human populations, and demonstrates how the mouse can provide evidence to support nominal associations found in human genome-wide association mapping., (Copyright © 2018 by the Genetics Society of America.)

Hematotoxicity is a life-threatening side effect of many chemotherapy regimens. Although 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 subpopulations 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.

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.

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.

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.)

Background: Anthracycline induced cardiomyopathy is a major cause of mortality and morbidity among pediatric cancer survivors. It has been postulated that oxidative stress induction and inflammation may play a role in the pathogenesis of this process. Accordingly, the present study performed an assessment of biomarker profiles and functional imaging parameters focused upon potential early determinants of anthracycline induced cardiomyopathy., Methods: Patients (10-22 years) were prospectively enrolled between January 2013 and November 2014. Thirteen subjects completed the study and underwent serial cardiac magnetic resonance imaging and plasma biomarker profiling performed 24-48 h after the first anthracycline dose and at set dose intervals. In addition, we collected plasma samples from 62 healthy controls to examine normal plasma biomarker profiles., Results: Left ventricular ejection fraction (LVEF) decreased from 64.3 ± 6.2 at the first visit to 57.5 ± 3.3 ( p = 0.004) 1 year after chemotherapy. A decline in longitudinal strain magnitude occurred at lower cumulative doses. A differential inflammatory/matrix signature emerged in anthracycline induced cardiomyopathy patients compared to normal including increased interleukin-8 and MMP levels. With longer periods of anthracycline dosing, MMP-7, a marker of macrophage proteolytic activation, increased by 165 ± 54% whereas interleukin-10 an anti-inflammatory marker decreased by 75 ± 13% (both p < 0.05). MMP7 correlated with time dependent changes in EF., Conclusions: Asymptomatic pediatric patients exposed to anthracycline therapy develop abnormal strain parameters at lower cumulative doses when compared to changes in EF. A differential biomarker signature containing both inflammatory and matrix domains occur early in anthracycline treatment. Dynamic changes in these domains occur with increased anthracycline doses and progression to anthracycline induced cardiomyopathy. These findings provide potential prognostic and mechanistic insights into the natural history of anthracycline induced cardiomyopathy., Trial Registration Number: NCT03211520 Date of Registration February 13, 2017, retrospectively registered., Competing Interests: Competing interests The authors declare that they have no competing interests.

Summary: We present CloudNeo, a cloud-based computational workflow for identifying patient-specific tumor neoantigens from next generation sequencing data. Tumor-specific mutant peptides can be detected by the immune system through their interactions with the human leukocyte antigen complex, and neoantigen presence has recently been shown to correlate with anti T-cell immunity and efficacy of checkpoint inhibitor therapy. However computing capabilities to identify neoantigens from genomic sequencing data are a limiting factor for understanding their role. This challenge has grown as cancer datasets become increasingly abundant, making them cumbersome to store and analyze on local servers. Our cloud-based pipeline provides scalable computation capabilities for neoantigen identification while eliminating the need to invest in local infrastructure for data transfer, storage or compute. The pipeline is a Common Workflow Language (CWL) implementation of human leukocyte antigen (HLA) typing using Polysolver or HLAminer combined with custom scripts for mutant peptide identification and NetMHCpan for neoantigen prediction. We have demonstrated the efficacy of these pipelines on Amazon cloud instances through the Seven Bridges Genomics implementation of the NCI Cancer Genomics Cloud, which provides graphical interfaces for running and editing, infrastructure for workflow sharing and version tracking, and access to TCGA data., Availability and Implementation: The CWL implementation is at: https://github.com/TheJacksonLaboratory/CloudNeo. For users who have obtained licenses for all internal software, integrated versions in CWL and on the Seven Bridges Cancer Genomics Cloud platform (https://cgc.sbgenomics.com/, recommended version) can be obtained by contacting the authors., Contact: jeff.chuang@jax.org., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2017. Published by Oxford University Press.)

Genetic studies of multidimensional phenotypes can potentially link genetic variation, gene expression, and physiological data to create multi-scale models of complex traits. The challenge of reducing these data to specific hypotheses has become increasingly acute with the advent of genome-scale data resources. Multi-parent populations derived from model organisms provide a resource for developing methods to understand this complexity. In this study, we simultaneously modeled body composition, serum biomarkers, and liver transcript abundances from 474 Diversity Outbred mice. This population contained both sexes and two dietary cohorts. Transcript data were reduced to functional gene modules with weighted gene coexpression network analysis (WGCNA), which were used as summary phenotypes representing enriched biological processes. These module phenotypes were jointly analyzed with body composition and serum biomarkers in a combined analysis of pleiotropy and epistasis (CAPE), which inferred networks of epistatic interactions between quantitative trait loci that affect one or more traits. This network frequently mapped interactions between alleles of different ancestries, providing evidence of both genetic synergy and redundancy between haplotypes. Furthermore, a number of loci interacted with sex and diet to yield sex-specific genetic effects and alleles that potentially protect individuals from the effects of a high-fat diet. Although the epistatic interactions explained small amounts of trait variance, the combination of directional interactions, allelic specificity, and high genomic resolution provided context to generate hypotheses for the roles of specific genes in complex traits. Our approach moves beyond the cataloging of single loci to infer genetic networks that map genetic etiology by simultaneously modeling all phenotypes., (Copyright © 2017 by the Genetics Society of America.)

Meiotic recombination is an essential feature of sexual reproduction that ensures faithful segregation of chromosomes and redistributes genetic variants in populations. Multiparent populations such as the Diversity Outbred (DO) mouse stock accumulate large numbers of crossover (CO) events between founder haplotypes, and thus present a unique opportunity to study the role of genetic variation in shaping the recombination landscape. We obtained high-density genotype data from [Formula: see text] DO mice, and localized 2.2 million CO events to intervals with a median size of 28 kb. The resulting sex-averaged genetic map of the DO population is highly concordant with large-scale (order 10 Mb) features of previously reported genetic maps for mouse. To examine fine-scale (order 10 kb) patterns of recombination in the DO, we overlaid putative recombination hotspots onto our CO intervals. We found that CO intervals are enriched in hotspots compared to the genomic background. However, as many as [Formula: see text] of CO intervals do not overlap any putative hotspots, suggesting that our understanding of hotspots is incomplete. We also identified coldspots encompassing 329 Mb, or [Formula: see text] of observable genome, in which there is little or no recombination. In contrast to hotspots, which are a few kilobases in size, and widely scattered throughout the genome, coldspots have a median size of 2.1 Mb and are spatially clustered. Coldspots are strongly associated with copy-number variant (CNV) regions, especially multi-allelic clusters, identified from whole-genome sequencing of 228 DO mice. Genes in these regions have reduced expression, and epigenetic features of closed chromatin in male germ cells, which suggests that CNVs may repress recombination by altering chromatin structure in meiosis. Our findings demonstrate how multiparent populations, by bridging the gap between large-scale and fine-scale genetic mapping, can reveal new features of the recombination landscape., (Copyright © 2017 by the Genetics Society of America.)

It is unclear how standing genetic variation affects the prognosis of prostate cancer patients. To provide one controlled answer to this problem, we crossed a dominant, penetrant mouse model of prostate cancer to Diversity Outbred mice, a collection of animals that carries over 40 million SNPs. Integration of disease phenotype and SNP variation data in 493 F1 males identified a metastasis modifier locus on Chromosome 8 (LOD = 8.42); further analysis identified the genes Rwdd4, Cenpu, and Casp3 as functional effectors of this locus. Accordingly, analysis of over 5,300 prostate cancer patient samples revealed correlations between the presence of genetic variants at these loci, their expression levels, cancer aggressiveness, and patient survival. We also observed that ectopic overexpression of RWDD4 and CENPU increased the aggressiveness of two human prostate cancer cell lines. In aggregate, our approach demonstrates how well-characterized genetic variation in mice can be harnessed in conjunction with systems genetics approaches to identify and characterize germline modifiers of human disease processes., (Published by Elsevier Inc.)

Background: Advances in experimental biology have enabled the collection of enormous troves of data on genomic variation in living organisms. The interpretation of this data to extract actionable information is one of the keys to developing novel therapeutic strategies to treat complex diseases. Network organization of biological data overcomes measurement noise in several biological contexts. Does a network approach, combining information about the linear organization of genomic markers with correlative information on these markers in a Bayesian formulation, lead to an analytic method with higher power for detecting quantitative trait loci?, Results: Block Network Mapping, combining Similarity Network Fusion (Wang et al., NM 11:333-337, 2014) with a Bayesian locus likelihood evaluation, leads to large improvements in area under the receiver operating characteristic and power over interval mapping with expectation maximization. The method has a monotonically decreasing false discovery rate as a function of effect size, unlike interval mapping., Conclusions: Block Network Mapping provides an alternative data-driven approach to mapping quantitative trait loci that leverages correlations in the sampled genotypes. The evaluation methodology can be combined with existing approaches such as Interval Mapping. Python scripts are available at http://lbm.niddk.nih.gov/vipulp/ . Genotype data is available at http://churchill-lab.jax.org/website/GattiDOQTL .