Bayesian Diallel Analysis Reveals Mx1-Dependent and Mx1-Independent Effects on Response to Influenza A Virus in Mice

Sarbecovirus disease susceptibility is conserved across viral and host models

Coronaviruses have caused three severe epidemics since the start of the 21st 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.

Characterization of Collaborative Cross mouse founder strain CAST/EiJ as a novel model for lethal COVID-19

Mutations in SARS-CoV-2 variants of concern (VOCs) have expanded the viral host range beyond primates, and a limited range of other mammals, to mice, affording the opportunity to exploit genetically diverse mouse panels to model the broad range of responses to infection in patient populations. Here we surveyed responses to VOC infection in genetically diverse Collaborative Cross (CC) founder strains. Infection of wild-derived CC founder strains produced a broad range of viral burden, disease susceptibility and survival, whereas most other strains were resistant to disease despite measurable lung viral titers. In particular, CAST/EiJ, a wild-derived strain, developed high lung viral burdens, more severe lung pathology than seen in other CC strains, and a dysregulated cytokine profile resulting in morbidity and mortality. These inbred mouse strains may serve as a valuable platform to evaluate therapeutic countermeasures against severe COVID-19 and other coronavirus pandemics in the future.

Genetic loci regulate Sarbecovirus pathogenesis: A comparison across mice and humans

Coronavirus (CoV) cause considerable morbidity and mortality in humans and other mammals, as evidenced by the emergence of Severe Acute Respiratory CoV (SARS-CoV) in 2003, Middle East Respiratory CoV (MERS-CoV) in 2012, and SARS-CoV-2 in 2019. Although poorly characterized, natural genetic variation in human and other mammals modulate virus pathogenesis, as reflected by the spectrum of clinical outcomes ranging from asymptomatic infections to lethal disease. Using multiple human epidemic and zoonotic Sarbecoviruses, coupled with murine Collaborative Cross genetic reference populations, we identify several dozen quantitative trait loci that regulate SARS-like group-2B CoV pathogenesis and replication. Under a Chr4 QTL, we deleted a candidate interferon stimulated gene, Trim14 which resulted in enhanced SARS-CoV titers and clinical disease, suggesting an antiviral role during infection. Importantly, about 60 % of the murine QTL encode susceptibility genes identified as priority candidates from human genome-wide association studies (GWAS) studies after SARS-CoV-2 infection, suggesting that similar selective forces have targeted analogous genes and pathways to regulate Sarbecovirus disease across diverse mammalian hosts. These studies provide an experimental platform in rodents to investigate the molecular-genetic mechanisms by which potential cross mammalian susceptibility loci and genes regulate type-specific and cross-SARS-like group 2B CoV replication, immunity, and pathogenesis in rodent models. Our study also provides a paradigm for identifying susceptibility loci for other highly heterogeneous and virulent viruses that sporadically emerge from zoonotic reservoirs to plague human and animal populations.

A sexually selected male weapon characterized by strong additive genetic variance and no evidence for sexually antagonistic polyphenic maintenance

Sexual selection and sexual antagonism are important drivers of eco-evolutionary processes. The evolution of traits shaped by these processes depends on their genetic architecture, which remains poorly studied. Here, implementing a quantitative genetics approach using diallel crosses of the bulb mite, Rhizoglyphus robini, we investigated the genetic variance that underlies a sexually selected weapon that is dimorphic among males and female fecundity. Previous studies indicated that a negative genetic correlation between these two traits likely exists. We found male morph showed considerable additive genetic variance, which is unlikely to be explained solely by mutation-selection balance, indicating the likely presence of large-effect loci. However, a significant magnitude of inbreeding depression also indicates that morph expression is likely to be condition-dependent to some degree and that deleterious recessives can simultaneously contribute to morph expression. Female fecundity also showed a high degree of inbreeding depression, but the variance in female fecundity was mostly explained by epistatic effects, with very little contribution from additive effects. We found no significant genetic correlation, nor any evidence for dominance reversal, between male morph and female fecundity. The complex genetic architecture underlying male morph and female fecundity in this system has important implications for our understanding of the evolutionary interplay between purifying selection and sexually antagonistic selection.

An exploration into the conversion of dominance to additive genetic variance in contrasting environments

PREMISE

The evolutionary response of a trait to environmental change depends upon the level of additive genetic variance. It has been long argued that sustained selection will tend to deplete additive genetic variance as favored alleles approach fixation. Non-additive genetic variance, due to interactions among alleles within and between loci, does not immediately contribute to an evolutionary response. However, shifts in the allele frequencies within and between interacting loci may convert non-additive variance into additive variance. Here we consider the possibility that an environmental shift may alter allelic interactions in ways that convert dominance into additive genetic variance.

METHODS

We grew a pedigreed population of Brassica rapa in greenhouse and field conditions. The field conditions mimicked agricultural conditions from which the base population was drawn, while the greenhouse featured benign conditions. We used Bayesian models to estimate the additive, dominance, and maternal components of quantitative genetic variance. We also estimated genetic correlations across environments using parental breeding values.

RESULTS

Although the additive genetic variance was elevated in the greenhouse condition, no consistent pattens emerged that would indicate a conversion of dominance variance. The unusually low genetic variance and broad confidence intervals for the variance estimates obtained through this analysis preclude definitive interpretations.

CONCLUSIONS

Further studies are needed to determine whether between-environment changes in additive genetic variance can be traced to conversion of dominance variance.

Elucidating the characteristics of Mx1 and resistance to influenza A virus subtype H1N1 in the newly developed KWM/Hym mice

Background

Inbred mice have several advantages, including genetic similarity to humans, a well-established gene manipulation system, and strong tolerance to inbreeding. However, inbred mice derived from a limited genetic pool have a small genetic diversity. Thus, the development of new inbred strains from wild mice is needed to overcome this limitation. Hence, in this study, we used a new strain of inbred mice called KWM/Hym. We sequenced the Mx1 gene to elucidate the genetic diversities of KWM/Hym mice and observed the biological alterations of the Mx1 protein upon influenza A infection.

Results

The Mx1 gene in KWM/Hym mice had 2, 4, and 38 nucleotide substitutions compared to those in the Mx1 gene in A2G, CAST/EiJ, and Mus spretus mice, respectively. Moreover, the Mx1 protein in KWM/Hym mice had 2 and 25 amino acid substitutions compared to those in the Mx1 protein in CAST/EiJ and M. spretus mice, respectively. To elucidate the function of the Mx1 protein, we inoculated the influenza A virus (A/WSN/1933) in KWM/Hym mice. Nine days after infection, all infected KWM/Hym mice survived without any weight loss. Four days after infection, the lungs of the infected KWM/Hym mice showed mild alveolitis and loss of bronchiolar epithelium; however, the pulmonary viral titers of the infected KWM/Hym mice were significantly lower than that in the infected BALB/c mice (2.17 × plaque-forming units mL⁻¹).

Conclusions

Our results demonstrate that the KWM/Hym mice are resistant to influenza A virus infection. Further, these mice can be used as a model organism to understand the mechanism of influenza A virus susceptibility.

Using the Collaborative Cross and Diversity Outbred Mice in Immunology

The Collaborative Cross (CC) and the Diversity Outbred (DO) stock mouse panels are the most powerful murine genetics tools available to the genetics community. Together, they combine the strength of inbred animal models with the diversity of outbred populations. Using the 63 CC strains or a panel of DO mice, each derived from the same 8 parental mouse strains, researchers can map genetic contributions to exceptionally complex immunological and infectious disease traits that would require far greater powering if performed by genome-wide association studies (GWAS) in human populations. These tools allow genes to be studied in heterozygous and homozygous states and provide a platform to study epistasis between interacting loci. Most importantly, once a quantitative phenotype is investigated and quantitative trait loci are identified, confirmatory genetic studies can be performed, which is often problematic using the GWAS approach. In addition, novel stable mouse models for immune phenotypes are often derived from studies utilizing the DO and CC mice that can serve as stronger model systems than existing ones in the field. The CC/DO systems have contributed to the fields of cancer immunology, autoimmunity, vaccinology, infectious disease, allergy, tissue rejection, and tolerance but have thus far been greatly underutilized. In this article, we present a recent review of the field and point out key areas of immunology that are ripe for further investigation and awaiting new CC/DO research projects. We also highlight some of the strong computational tools that have been developed for analyzing CC/DO genetic and phenotypic data. Additionally, we have formed a centralized community on the CyVerse infrastructure where immunogeneticists can utilize those software tools, collaborate with groups across the world, and expand the use of the CC and DO systems for investigating immunogenetic phenomena. © 2022 Wiley Periodicals LLC.

A Multitrait Locus Regulates Sarbecovirus Pathogenesis

Infectious diseases have shaped the human population genetic structure, and genetic variation influences the susceptibility to many viral diseases. However, a variety of challenges have made the implementation of traditional human Genome-wide Association Studies (GWAS) approaches to study these infectious outcomes challenging. In contrast, mouse models of infectious diseases provide an experimental control and precision, which facilitates analyses and mechanistic studies of the role of genetic variation on infection. Here we use a genetic mapping cross between two distinct Collaborative Cross mouse strains with respect to severe acute respiratory syndrome coronavirus (SARS-CoV) disease outcomes. We find several loci control differential disease outcome for a variety of traits in the context of SARS-CoV infection. Importantly, we identify a locus on mouse chromosome 9 that shows conserved synteny with a human GWAS locus for SARS-CoV-2 severe disease. We follow-up and confirm a role for this locus, and identify two candidate genes, CCR9 and CXCR6, that both play a key role in regulating the severity of SARS-CoV, SARS-CoV-2, and a distantly related bat sarbecovirus disease outcomes. As such we provide a template for using experimental mouse crosses to identify and characterize multitrait loci that regulate pathogenic infectious outcomes across species. IMPORTANCE Host genetic variation is an important determinant that predicts disease outcomes following infection. In the setting of highly pathogenic coronavirus infections genetic determinants underlying host susceptibility and mortality remain unclear. To elucidate the role of host genetic variation on sarbecovirus pathogenesis and disease outcomes, we utilized the Collaborative Cross (CC) mouse genetic reference population as a model to identify susceptibility alleles to SARS-CoV and SARS-CoV-2 infections. Our findings reveal that a multitrait loci found in chromosome 9 is an important regulator of sarbecovirus pathogenesis in mice. Within this locus, we identified and validated CCR9 and CXCR6 as important regulators of host disease outcomes. Specifically, both CCR9 and CXCR6 are protective against severe SARS-CoV, SARS-CoV-2, and SARS-related HKU3 virus disease in mice. This chromosome 9 multitrait locus may be important to help identify genes that regulate coronavirus disease outcomes in humans.

A Multitrait Locus Regulates Sarbecovirus Pathogenesis

Infectious diseases have shaped the human population genetic structure, and genetic variation influences the susceptibility to many viral diseases. However, a variety of challenges have made the implementation of traditional human Genome-wide Association Studies (GWAS) approaches to study these infectious outcomes challenging. In contrast, mouse models of infectious diseases provide an experimental control and precision, which facilitates analyses and mechanistic studies of the role of genetic variation on infection. Here we use a genetic mapping cross between two distinct Collaborative Cross mouse strains with respect to SARS-CoV disease outcomes. We find several loci control differential disease outcome for a variety of traits in the context of SARS-CoV infection. Importantly, we identify a locus on mouse Chromosome 9 that shows conserved synteny with a human GWAS locus for SARS-CoV-2 severe disease. We follow-up and confirm a role for this locus, and identify two candidate genes, CCR9 and CXCR6 that both play a key role in regulating the severity of SARS-CoV, SARS-CoV-2 and a distantly related bat sarbecovirus disease outcomes. As such we provide a template for using experimental mouse crosses to identify and characterize multitrait loci that regulate pathogenic infectious outcomes across species.

Genetic background influences survival of infections with Salmonella enterica serovar Typhimurium in the Collaborative Cross

Salmonella infections typically cause self-limiting gastroenteritis, but in some individuals these bacteria can spread systemically and cause disseminated disease. Salmonella Typhimurium (STm), which causes severe systemic disease in most inbred mice, has been used as a model for disseminated disease. To screen for new infection phenotypes across a range of host genetics, we orally infected 32 Collaborative Cross (CC) mouse strains with STm and monitored their disease progression for seven days by telemetry. Our data revealed a broad range of phenotypes across CC strains in many parameters including survival, bacterial colonization, tissue damage, complete blood counts (CBC), and serum cytokines. Eighteen CC strains survived to day 7, while fourteen susceptible strains succumbed to infection before day 7. Several CC strains had sex differences in survival and colonization. Surviving strains had lower pre-infection baseline temperatures and were less active during their daily active period. Core body temperature disruptions were detected earlier after STm infection than activity disruptions, making temperature a better detector of illness. All CC strains had STm in spleen and liver, but susceptible strains were more highly colonized. Tissue damage was weakly negatively correlated to survival. We identified loci associated with survival on Chromosomes (Chr) 1, 2, 4, 7. Polymorphisms in Ncf2 and Slc11a1, known to reduce survival in mice after STm infections, are located in the Chr 1 interval, and the Chr 7 association overlaps with a previously identified QTL peak called Ses2. We identified two new genetic regions on Chr 2 and 4 associated with susceptibility to STm infection. Our data reveal the diversity of responses to STm infection across a range of host genetics and identified new candidate regions for survival of STm infection.

Selection in males purges the mutation load on female fitness

Theory predicts that the ability of selection and recombination to purge mutation load is enhanced if selection against deleterious genetic variants operates more strongly in males than females. However, direct empirical support for this tenet is limited, in part because traditional quantitative genetic approaches allow dominance and intermediate-frequency polymorphisms to obscure the effects of the many rare and partially recessive deleterious alleles that make up the main part of a population's mutation load. Here, we exposed the partially recessive genetic load of a population of Callosobruchus maculatus seed beetles via successive generations of inbreeding, and quantified its effects by measuring heterosis-the increase in fitness experienced when masking the effects of deleterious alleles by heterozygosity-in a fully factorial sex-specific diallel cross among 16 inbred strains. Competitive lifetime reproductive success (i.e., fitness) was measured in male and female outcrossed F1s as well as inbred parental "selfs," and we estimated the 4 × 4 male-female inbred-outbred genetic covariance matrix for fitness using Bayesian Markov chain Monte Carlo simulations of a custom-made general linear mixed effects model. We found that heterosis estimated independently in males and females was highly genetically correlated among strains, and that heterosis was strongly negatively genetically correlated to outbred male, but not female, fitness. This suggests that genetic variation for fitness in males, but not in females, reflects the amount of (partially) recessive deleterious alleles segregating at mutation-selection balance in this population. The population's mutation load therefore has greater potential to be purged via selection in males. These findings contribute to our understanding of the prevalence of sexual reproduction in nature and the maintenance of genetic variation in fitness-related traits.

Complex Genetic Architecture Underlies Regulation of Influenza-A-Virus-Specific Antibody Responses in the Collaborative Cross

Host genetic factors play a fundamental role in regulating humoral immunity to viral infection, including influenza A virus (IAV). Here, we utilize the Collaborative Cross (CC), a mouse genetic reference population, to study genetic regulation of variation in antibody response following IAV infection. CC mice show significant heritable variation in the magnitude, kinetics, and composition of IAV-specific antibody response. We map 23 genetic loci associated with this variation. Analysis of a subset of these loci finds that they broadly affect the antibody response to IAV as well as other viruses. Candidate genes are identified based on predicted variant consequences and haplotype-specific expression patterns, and several show overlap with genes identified in human mapping studies. These findings demonstrate that the host antibody response to IAV infection is under complex genetic control and highlight the utility of the CC in modeling and identifying genetic factors with translational relevance to human health and disease.

Mx genes: host determinants controlling influenza virus infection and trans-species transmission

The human MxA protein, encoded by the interferon-inducible MX1 gene, is an intracellular influenza A virus (IAV) restriction factor. It can protect transgenic mice from severe IAV-induced disease, indicating a key role of human MxA for host survival and suggesting that natural variations in MX1 may account for inter-individual differences in disease severity among humans. MxA also provides a robust barrier against zoonotic transmissions of avian and swine IAV strains. Therefore, zoonotic IAV must acquire MxA escape mutations to achieve sustained human-to-human transmission. Here, we discuss recent progress in the field.

Mouse Models as Resources for Studying Infectious Diseases

Mouse models are important tools both for studying the pathogenesis of infectious diseases and for the preclinical evaluation of vaccines and therapies against a wide variety of human pathogens. The use of genetically defined inbred mouse strains, humanized mice, and gene knockout mice has allowed the research community to explore how pathogens cause disease, define the role of specific host genes in either controlling or promoting disease, and identify potential targets for the prevention or treatment of a wide range of infectious agents. This review discusses several of the most commonly used mouse model systems, as well as new resources such as the Collaborative Cross as models for studying infectious diseases.

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

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

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

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

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

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

Dissecting the Genetic Architecture of Shoot Growth in Carrot (Daucus carota L.) Using a Diallel Mating Design

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.

Advancing chemical risk assessment decision-making with population variability data: challenges and opportunities

Characterizing population variability, including identifying susceptible populations and quantifying their increased susceptibility, is an important aspect of chemical risk assessment, but one that is challenging with traditional experimental models and risk assessment methods. New models and methods to address population variability can be used to advance the human health assessments of chemicals in three key areas. First, with respect to hazard identification, evaluating toxicity using population-based in vitro and in vivo models can potentially reduce both false positive and false negative signals. Second, with respect to evaluating mechanisms of toxicity, enhanced ability to do genetic mapping using these models allows for the identification of key biological pathways and mechanisms that may be involved in toxicity and/or susceptibility. Third, with respect to dose-response assessment, population-based toxicity data can serve as a surrogate for human variability, and thus be used to quantitatively estimate the degree of human toxicokinetic/toxicodynamic variability and thereby increase confidence in setting health-protective exposure limits. A number of case studies have been published that demonstrate the potential opportunities for improving risk assessment and decision-making, and include studies using Collaborative Cross and Diversity Outbred mice, as well as populations of human cell lines from the 1000 Genomes project. Key challenges include the need to apply more sophisticated computational and statistical models analyzing population-based toxicity data, and the need to integrate these more complex analyses into risk assessments and decision-making.