Expression quantitative trait Loci for extreme host response to influenza a in pre-collaborative cross mice

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 few other mammals, to mice, affording the opportunity to exploit genetically diverse mouse panels to model the broad spectrum 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.

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 diversity drives extreme responses to traumatic brain injury and post-traumatic epilepsy

Traumatic brain injury (TBI) is a complex and heterogeneous condition that can cause wide-spectral neurological sequelae such as behavioral deficits, sleep abnormalities, and post-traumatic epilepsy (PTE). However, understanding the interaction of TBI phenome is challenging because few animal models can recapitulate the heterogeneity of TBI outcomes. We leveraged the genetically diverse recombinant inbred Collaborative Cross (CC) mice panel and systematically characterized TBI-related outcomes in males from 12 strains of CC and the reference C57BL/6J mice. We identified unprecedented extreme responses in multiple clinically relevant traits across CC strains, including weight change, mortality, locomotor activity, cognition, and sleep. Notably, we identified CC031 mouse strain as the first rodent model of PTE that exhibit frequent and progressive post-traumatic seizures after moderate TBI induced by lateral fluid percussion. Multivariate analysis pinpointed novel biological interactions and three principal components across TBI-related modalities. Estimate of the proportion of TBI phenotypic variability attributable to strain revealed large range of heritability, including >70% heritability of open arm entry time of elevated plus maze. Our work provides novel resources and models that can facilitate genetic mapping and the understanding of the pathobiology of TBI and PTE.

Differential lung gene expression changes in C57BL/6 and DBA/2 mice carrying an identical functional Mx1 gene reveals crucial differences in the host response

BACKGROUND

Influenza virus infections represent a major global health problem. The dynamin-like GTPase MX1 is an interferon-dependent antiviral host protein that confers resistance to influenza virus infections. Infection models in mice are an important experimental system to understand the host response and susceptibility to developing severe disease following influenza infections. However, almost all laboratory mouse strains carry a non-functional Mx1 gene whereas humans have a functional MX1 gene. Most studies in mice have been performed with strains carrying a non-functional Mx1 gene. It is therefore very important to investigate the host response in mouse strains with a functional Mx1 gene.

RESULTS

Here, we analyzed the host response to influenza virus infections in two congenic mouse strains carrying the functional Mx1 gene from the A2G strain. B6.A2G-Mx1r/r(B6-Mx1r/r) mice are highly resistant to influenza A virus (IAV) H1N1 infections. On the other hand, D2(B6).A2G-Mx1r/r(D2-Mx1r/r) mice, although carrying a functional Mx1 gene, were highly susceptible, exhibited rapid weight loss, and died. We performed gene expression analysis using RNAseq from infected lungs at days 3 and 5 post-infection (p.i.) of both mouse strains to identify genes and pathways that were differentially expressed between the two mouse strains. The susceptible D2-Mx1r/r mice showed a high viral replication already at day 3 p.i. and exhibited a much higher number of differentially expressed genes (DEGs) and many DEGs had elevated expression levels compared to B6-Mx1r/r mice. On the other hand, some DEGs were specifically up-regulated only in B6-Mx1r/r mice at day 3 p.i., many of which were related to host immune response functions.

CONCLUSIONS

From these results, we conclude that at early times of infection, D2-Mx1r/r mice showed a very high and rapid replication of the virus, which resulted in lung damage and a hyperinflammatory response leading to death. We hypothesize that the activation of certain immune response genes was missing and that others, especially Mx1, were expressed at a time in D2-Mx1r/r mice when the virus had already massively spread in the lung and were thus not able anymore to protect them from severe disease. Our study represents an important addition to previously published studies in mouse models and contributes to a better understanding of the molecular pathways and genes that protect against severe influenza disease.

Identifying genetic susceptibility to Aspergillus fumigatus infection using collaborative cross mice and RNA-Seq approach

BACKGROUND

Aspergillus fumigatus (Af) is one of the most ubiquitous fungi and its infection potency is suggested to be strongly controlled by the host genetic background. The aim of this study was to search for candidate genes associated with host susceptibility to Aspergillus fumigatus (Af) using an RNAseq approach in CC lines and hepatic gene expression.

METHODS

We studied 31 male mice from 25 CC lines at 8 weeks old; the mice were infected with Af. Liver tissues were extracted from these mice 5 days post-infection, and next-generation RNA-sequencing (RNAseq) was performed. The GENE-E analysis platform was used to generate a clustered heat map matrix.

RESULTS

Significant variation in body weight changes between CC lines was observed. Hepatic gene expression revealed 12 top prioritized candidate genes differentially expressed in resistant versus susceptible mice based on body weight changes. Interestingly, three candidate genes are located within genomic intervals of the previously mapped quantitative trait loci (QTL), including Gm16270 and Stox1 on chromosome 10 and Gm11033 on chromosome 8.

CONCLUSIONS

Our findings emphasize the CC mouse model's power in fine mapping the genetic components underlying susceptibility towards Af. As a next step, eQTL analysis will be performed for our RNA-Seq data. Suggested candidate genes from our study will be further assessed with a human cohort with aspergillosis.

Distinct gene programs underpinning disease tolerance and resistance in influenza virus infection

When challenged with an invading pathogen, the host-defense response is engaged to eliminate the pathogen (resistance) and to maintain health in the presence of the pathogen (disease tolerance). However, the identification of distinct molecular programs underpinning disease tolerance and resistance remained obscure. We exploited transcriptional and physiological monitoring across 33 mouse strains, during in vivo influenza virus infection, to identify two host-defense gene programs-one is associated with hallmarks of disease tolerance and the other with hallmarks of resistance. Both programs constitute generic responses in multiple mouse and human cell types. Our study describes the organizational principles of these programs and validates Arhgdia as a regulator of disease-tolerance states in epithelial cells. We further reveal that the baseline disease-tolerance state in peritoneal macrophages is associated with the pathophysiological response to injury and infection. Our framework provides a paradigm for the understanding of disease tolerance and resistance at the molecular level.

Genetics of murine type 2 diabetes and comorbidities

ABSTRAC

Type 2 diabetes (T2D) is a polygenic and multifactorial complex disease, defined as chronic metabolic disorder. It's a major global health concern with an estimated 463 million adults aged 20-79 years with diabetes and projected to increase up to 700 million by 2045. T2D was reported to be one of the four leading causes of non-communicable disease (NCD) deaths in 2012. Environmental factors play a part in the development of polygenic forms of diabetes. Polygenic forms of diabetes often run-in families. Fortunately, T2D, which accounts for 90-95% of the entire four types of diabetes including, Type 1 diabetes (T1D), T2D, monogenic diabetes syndromes (MGDS), and Gestational diabetes mellitus, can be prevented or delayed through nutrition and lifestyle changes as well as through pharmacologic interventions. Typical symptom of the T2D is high blood glucose levels and comprehensive insulin resistance of the body, producing an impaired glucose tolerance. Impaired glucose tolerance of T2D is accompanied by extensive health complications, including cardiovascular diseases (CVD) that vary in morbidity and mortality among populations. The pathogenesis of T2D varies between populations and/or ethnic groupings and is known to be attributed extremely by genetic components and environmental factors. It is evident that genetic background plays a critical role in determining the host response toward certain environmental conditions, whether or not of developing T2D (susceptibility versus resistant). T2D is considered as a silent disease that can progress for years before its diagnosis. Once T2D is diagnosed, many metabolic malfunctions are observed whether as side effects or as independent comorbidity. Mouse models have been proven to be a powerful tool for mapping genetic factors that underline the susceptibility to T2D development as well its comorbidities. Here, we have conducted a comprehensive search throughout the published data covering the time span from early 1990s till the time of writing this review, for already reported quantitative trait locus (QTL) associated with murine T2D and comorbidities in different mouse models, which contain different genetic backgrounds. Our search has resulted in finding 54 QTLs associated with T2D in addition to 72 QTLs associated with comorbidities associated with the disease. We summarized the genomic locations of these mapped QTLs in graphical formats, so as to show the overlapping positions between of these mapped QTLs, which may suggest that some of these QTLs could be underlined by sharing gene/s. Finally, we reviewed and addressed published reports that show the success of translation of the identified mouse QTLs/genes associated with the disease in humans.

The First Immunocompetent Mouse Model of Strictly Human Pathogen, Borrelia recurrentis

The spirochetal bacterium Borrelia recurrentis causes louse-borne relapsing fever (LBRF). B. recurrentis is unique because, as opposed to other Borrelia spirochetes, this strictly human pathogen is transmitted by lice. Despite the high mortality and historically proven epidemic potential and current outbreaks in African countries and Western Europe, research on LBRF has been obstructed by the lack of suitable animal models. The previously used grivet monkey model is associated with ethical concerns, among other issues. An existing immunodeficient mouse model does not limit bacteremia due to its impaired immune system. In this study, we used genetically diverse Collaborative Cross (CC) lines to develop the first LBRF immunocompetent mouse model. Out of 12 CC lines tested, CC046 mice consistently developed B. recurrentis-induced spirochetemia during the first 3 days postchallenge as concordantly detected by dark-field microscopy, culture, and quantitative PCR. However, spirochetemia was not detected from day 4 through day 10 postchallenge. The high-level spirochetemia (>10⁷ cells/ml of blood) observed in CC046 mice was similar to that recorded in LBRF patients as well as immunocompetent mouse strains experimentally infected by tick-borne relapsing fever (RF) spirochetes, Borrelia hermsii and Borrelia persica. In contrast to the Old World and New World RF spirochetes, which develop multiple relapses (n = 3 to 9), B. recurrentis produced only single culture-detectable spirochetemia in CC046 mice. The lack of relapses may not be surprising, as LBRF patients and the grivet monkey model usually develop no or only 1 to 2 spirochetemic relapses. The novel model will now allow scientists to study B. recurrentis in the context of intact immunity.

Genetic Diversity of Collaborative Cross Mice Controls Viral Replication, Clinical Severity, and Brain Pathology Induced by Zika Virus Infection, Independently of Oas1b

The explosive spread of Zika virus (ZIKV) has been associated with major variations in severe disease and congenital afflictions among infected populations, suggesting an influence of host genes. We investigated how genome-wide variants could impact susceptibility to ZIKV infection in mice. We first describe that the susceptibility of Ifnar1-knockout mice is largely influenced by their genetic background. We then show that Collaborative Cross (CC) mice, which exhibit a broad genetic diversity, in which the type I interferon receptor (IFNAR) was blocked by an anti-IFNAR antibody expressed phenotypes ranging from complete resistance to severe symptoms and death, with large variations in the peak and the rate of decrease in the plasma viral load, in the brain viral load, in brain histopathology, and in the viral replication rate in infected cells. The differences in susceptibility to ZIKV between CC strains correlated with the differences in susceptibility to dengue and West Nile viruses between the strains. We identified highly susceptible and resistant mouse strains as new models to investigate the mechanisms of human ZIKV disease and other flavivirus infections. Genetic analyses revealed that phenotypic variations are driven by multiple genes with small effects, reflecting the complexity of ZIKV disease susceptibility in the human population. Notably, our results rule out the possibility of a role of the Oas1b gene in the susceptibility to ZIKV. Altogether, the findings of this study emphasize the role of host genes in the pathogeny of ZIKV infection and lay the foundation for further genetic and mechanistic studies.IMPORTANCE In recent outbreaks, ZIKV has infected millions of people and induced rare but potentially severe complications, including Guillain-Barré syndrome and encephalitis in adults. While several viral sequence variants were proposed to enhance the pathogenicity of ZIKV, the influence of host genetic variants in mediating the clinical heterogeneity remains mostly unexplored. We addressed this question using a mouse panel which models the genetic diversity of the human population and a ZIKV strain from a recent clinical isolate. Through a combination of in vitro and in vivo approaches, we demonstrate that multiple host genetic variants determine viral replication in infected cells and the clinical severity, the kinetics of blood viral load, and brain pathology in mice. We describe new mouse models expressing high degrees of susceptibility or resistance to ZIKV and to other flaviviruses. These models will facilitate the identification and mechanistic characterization of host genes that influence ZIKV pathogenesis.

Influenza Pathogenesis: The Effect of Host Factors on Severity of Disease

Influenza viruses continue to be a major global health threat. Severity and clinical outcome of influenza disease is determined by both viral and host factors. Viral factors have long been the subject of intense research and many molecular determinants have been identified. However, research into the host factors that protect or predispose to severe and fatal influenza A virus infections is lagging. The goal of this review is to highlight the recent insights into host determinants of influenza pathogenesis.

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.

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.

Advanced Genetic Approaches in Discovery and Characterization of Genes Involved With Osteoporosis in Mouse and Human

Osteoporosis is a complex condition with contributions from, and interactions between, multiple genetic loci and environmental factors. This review summarizes key advances in the application of genetic approaches for the identification of osteoporosis susceptibility genes. Genome-wide linkage analysis (GWLA) is the classical approach for identification of genes that cause monogenic diseases; however, it has shown limited success for complex diseases like osteoporosis. In contrast, genome-wide association studies (GWAS) have successfully identified over 200 osteoporosis susceptibility loci with genome-wide significance, and have provided most of the candidate genes identified to date. Phenome-wide association studies (PheWAS) apply a phenotype-to-genotype approach which can be used to complement GWAS. PheWAS is capable of characterizing the association between osteoporosis and uncommon and rare genetic variants. Another alternative approach, whole genome sequencing (WGS), will enable the discovery of uncommon and rare genetic variants in osteoporosis. Meta-analysis with increasing statistical power can offer greater confidence in gene searching through the analysis of combined results across genetic studies. Recently, new approaches to gene discovery include animal phenotype based models such as the Collaborative Cross and ENU mutagenesis. Site-directed mutagenesis and genome editing tools such as CRISPR/Cas9, TALENs and ZNFs have been used in functional analysis of candidate genes in vitro and in vivo. These resources are revolutionizing the identification of osteoporosis susceptibility genes through the use of genetically defined inbred mouse libraries, which are screened for bone phenotypes that are then correlated with known genetic variation. Identification of osteoporosis-related susceptibility genes by genetic approaches enables further characterization of gene function in animal models, with the ultimate aim being the identification of novel therapeutic targets for osteoporosis.

Cell composition analysis of bulk genomics using single-cell data

Single-cell expression profiling (scRNA-seq) is a rich resource of cellular heterogeneity. While profiling every sample under study would be advantageous, it is time-consuming and costly. Here we introduce Cell Population Mapping (CPM), a deconvolution algorithm in which the composition of cell types and states is inferred from the bulk transcriptome using reference scRNA-seq profiles ('scBio' CRAN R-package). Analysis of individual variations in lungs of influenza virus-infected mice, using CPM, revealed that the relationship between cell abundance and clinical symptoms is a cell-state-specific property that varies gradually along the continuum of cell-activation states. The gradual change was confirmed in subsequent experiments and was further explained by a mathematical model in which clinical outcomes relate to cell-state dynamics along the activation process. Our results demonstrate the power of CPM in reconstructing the continuous spectrum of cell states within heterogeneous tissues.

C57BL/6J and C57BL/6NJ Mice Are Differentially Susceptible to Inflammation-Associated Disease Caused by Influenza A Virus

Influenza viruses cause seasonal epidemics and sporadic pandemics, and are a major burden on human health. To develop better countermeasures and improve influenza disease outcomes, a clearer understanding of influenza pathogenesis is necessary. Host genetic factors have emerged as potential regulators of human influenza disease susceptibility, and in the mouse model, genetic background has been clearly linked to influenza pathogenicity. Here, we show that C57BL/6J mice are significantly more susceptible to disease caused by a 2009 pandemic H1N1 virus, an H7N9 virus, and a highly pathogenic H5N1 influenza virus compared to the closely related substrain, C57BL/6NJ. Mechanistically, influenza virus infection in C57BL/6J mice results in earlier presentation of edema, increased immune cell infiltration, higher levels of inflammatory cytokines, greater tissue damage, and delayed activation of regenerative processes in infected lung tissues compared to C57BL/6NJ mice. These differences are not dependent on virus replication levels. Six genes with known coding region differences between C57BL/6J and C57BL/6NJ strains exhibit increased transcript levels in influenza virus-infected mouse lungs, suggesting potential contributions to regulation of disease susceptibility. This work uncovers a previously unappreciated difference in disease susceptibility between the closely related C57BL/6J and C57BL/6NJ mice, which may be exploited in future studies to identify host factors and/or specific genetic elements that regulate host-dependent inflammatory mechanisms involved in influenza virus pathogenicity.

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.

Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice

BACKGROUND

Liver weight is a complex trait, controlled by polygenic factors and differs within populations. Dissecting the genetic architecture underlying these variations will facilitate the search for key role candidate genes involved directly in the hepatomegaly process and indirectly involved in related diseases etiology.

METHODS

Liver weight of 506 mice generated from 39 different Collaborative Cross (CC) lines with both sexes at age 20 weeks old was determined using an electronic balance. Genomic DNA of the CC lines was genotyped with high-density single nucleotide polymorphic markers.

RESULTS

Statistical analysis revealed a significant (P < 0.05) variation of liver weight between the CC lines, with broad sense heritability (H 2) of 0.32 and genetic coefficient of variation (CVG) of 0.28. Subsequently, quantitative trait locus (QTL) mapping was performed, and results showed a significant QTL only for females on chromosome 8 at genomic interval 88.61-93.38 Mb (4.77 Mb). Three suggestive QTL were mapped at chromosomes 4, 12 and 13. The four QTL were designated as LWL1-LWL4 referring to liver weight loci 1-4 on chromosomes 8, 4, 12 and 13, respectively.

CONCLUSION

To our knowledge, this report presents, for the first time, the utilization of the CC for mapping QTL associated with baseline liver weight in mice. Our findings demonstrate that liver weight is a complex trait controlled by multiple genetic factors that differ significantly between sexes.

The Collaborative Cross mouse model for dissecting genetic susceptibility to infectious diseases

Infectious diseases, also known as communicable diseases, refer to a full range of maladies caused by pathogen invasion to the host body. Host response towards an infectious pathogen varies between individuals, and can be defined by responses from asymptomatic to lethal. Host response to infectious pathogens is considered as a complex trait controlled by gene-gene (host-pathogen) and gene-environment interactions, leading to the extensive phenotypic variations between individuals. With the advancement of the human genome mapping approaches and tools, various genome-wide association studies (GWAS) were performed, aimed at mapping the genetic basis underlying host susceptibility towards infectious pathogens. In parallel, immense efforts were invested in enhancing the genetic mapping resolution and gene-cloning efficacy, using advanced mouse models including advanced intercross lines; outbred populations; consomic, congenic; and recombinant inbred lines. Notwithstanding the evident advances achieved using these mouse models, the genetic diversity was low and quantitative trait loci (QTL) mapping resolution was inadequate. Consequently, the Collaborative Cross (CC) mouse model was established by full-reciprocal mating of eight divergent founder strains of mice (A/J, C57BL/6J, 129S1/SvImJ, NOD/LtJ, NZO/HiLtJ, CAST/Ei, PWK/PhJ, and WSB/EiJ) generating a next-generation mouse genetic reference population (CC lines). Presently, the CC mouse model population comprises a set of about 200 recombinant inbred CC lines exhibiting a unique high genetic diversity and which are accessible for multidisciplinary studies. The CC mouse model efficacy was validated by various studies in our lab and others, accomplishing high-resolution (< 1 MB) QTL genomic mapping for a variety of complex traits, using about 50 CC lines (3-4 mice per line). Herein, we present a number of studies demonstrating the power of the CC mouse model, which has been utilized in our lab for mapping the genetic basis of host susceptibility to various infectious pathogens. These include Aspergillus fumigatus, Klebsiella pneumoniae, Porphyromonas gingivalis and Fusobacterium nucleatum (causing oral mixed infection), Pseudomonas aeruginosa, and the bacterial toxins Lipopolysaccharide and Lipoteichoic acid.

Modeling pathogenesis of emergent and pre-emergent human coronaviruses in mice

The emergence of highly pathogenic human coronaviruses (hCoVs) in the last two decades has illuminated their potential to cause high morbidity and mortality in human populations and disrupt global economies. Global pandemic concerns stem from their high mortality rates, capacity for human-to-human spread by respiratory transmission, and complete lack of approved therapeutic countermeasures. Limiting disease may require the development of virus-directed and host-directed therapeutic strategies due to the acute etiology of hCoV infections. Therefore, understanding how hCoV–host interactions cause pathogenic outcomes relies upon mammalian models that closely recapitulate the pathogenesis of hCoVs in humans. Pragmatism has largely been the driving force underpinning mice as highly effective mammalian models for elucidating hCoV–host interactions that govern pathogenesis. Notably, tractable mouse genetics combined with hCoV reverse genetic systems has afforded the concomitant manipulation of virus and host genetics to evaluate virus–host interaction networks in disease. In addition to assessing etiologies of known hCoVs, mouse models have clinically predictive value as tools to appraise potential disease phenotypes associated with pre-emergent CoVs. Knowledge of CoV pathogenic potential before it crosses the species barrier into the human population provides a highly desirable preclinical platform for addressing global pathogen preparedness, an overarching directive of the World Health Organization. Although we recognize that results obtained in robust mouse models require evaluation in non-human primates, we focus this review on the current state of hCoV mouse models, their use as tractable complex genetic organisms for untangling complex hCoV–host interactions, and as pathogenesis models for preclinical evaluation of novel therapeutic interventions.

"Gnothi Seauton": Leveraging the Host Response to Improve Influenza Virus Vaccine Efficacy

Vaccination against the seasonal influenza virus is the best way to prevent infection. Nevertheless, vaccine efficacy remains far from optimal especially in high-risk populations such as the elderly. Recent technological advancements have facilitated rapid and precise identification of the B and T cell epitopes that are targets for protective responses. While these discoveries have undoubtedly brought the field closer to "universal" influenza virus vaccines, choosing the correct antigen is only one piece of the equation. Achieving efficacy and durability requires a detailed understanding of the diverse host factors and pathways that are required for attaining optimal responses. Sequencing technologies, systems biology, and immunological studies have recently advanced our understanding of the diverse aspects of the host response required for vaccine efficacy. In this paper, we review the critical role of the host response in determining efficacious responses and discuss the gaps in knowledge that will need to be addressed if the field is to be successful in developing new and more effective influenza virus vaccines.

Genome-wide Analysis of Transcriptional Variability in a Large Maize-Teosinte Population

Gene expression regulation plays an important role in controlling plant phenotypes and adaptation. Here, we report a comprehensive assessment of gene expression variation through the transcriptome analyses of a large maize-teosinte experimental population. Genome-wide mapping identified 25 660 expression quantitative trait loci (eQTL) for 17 311 genes, capturing an unprecedented range of expression variation. We found that local eQTL were more frequently mapped to adjacent genes, displaying a mode of expression piggybacking, which consequently created co-regulated gene clusters. Genes within the co-regulated gene clusters tend to have relevant functions and shared chromatin modifications. Distant eQTL formed 125 significant distant eQTL hotspots with their targets significantly enriched in specific functional categories. By integrating different sources of information, we identified putative trans- regulators for a variety of metabolic pathways. We demonstrated that the bHLH transcription factor R1 and hexokinase HEX9 might act as crucial regulators for flavonoid biosynthesis and glycolysis, respectively. Moreover, we showed that domestication or improvement has significantly affected global gene expression, with many genes targeted by selection. Of particular interest, the Bx genes for benzoxazinoid biosynthesis may have undergone coordinated cis-regulatory divergence between maize and teosinte, and a transposon insertion that inactivates Bx12 was under strong selection as maize spread into temperate environments with a distinct herbivore community.

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

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

Inter-individual variation in adaptations to endurance and resistance exercise training: genetic approaches towards understanding a complex phenotype

Exercise training which meets the recommendations set by the National Physical Activity Guidelines ensues a multitude of health benefits towards the prevention and treatment of various chronic diseases. However, not all individuals respond well to exercise training. That is, some individuals have no response, while others respond poorly. Genetic background is known to contribute to the inter-individual (human) and -strain (e.g., mice, rats) variation with acute exercise and exercise training, though to date, no specific genetic factors have been identified that explain the differential responses to exercise. In this review, we provide an overview of studies in human and animal models that have shown a significant contribution of genetics in acute exercise and exercise training-induced adaptations with standardized endurance and resistance training regimens, and further describe the genetic approaches which have been used to demonstrate such responses. Finally, our current understanding of the role of genetics and exercise is limited primarily to the nuclear genome, while only a limited focus has been given to a potential role of the mitochondrial genome and its interactions with the nuclear genome to predict the exercise training-induced phenotype(s) responses. We therefore discuss the mitochondrial genome and literature that suggests it may play a significant role, particularly through interactions with the nuclear genome, in the inherent ability to respond to exercise.

Host genetic background influences diverse neurological responses to viral infection in mice

Infection by Theiler's murine encephalomyelitis virus (TMEV) is a model for neurological outcomes caused by virus infection because it leads to diverse neurological conditions in mice, depending on the strain infected. To extend knowledge on the heterogeneous neurological outcomes caused by TMEV and identify new models of human neurological diseases associated with antecedent infections, we analyzed the phenotypic consequences of TMEV infection in the Collaborative Cross (CC) mouse population. We evaluated 5 different CC strains for outcomes of long-term infection (3 months) and acute vs. early chronic infection (7 vs. 28 days post-infection), using neurological and behavioral phenotyping tests and histology. We correlated phenotypic observations with haplotypes of genomic regions previously linked to TMEV susceptibility to test the hypothesis that genomic diversity within CC mice results in variable disease phenotypes in response to TMEV. None of the 5 strains analyzed had a response identical to that of any other CC strain or inbred strain for which prior data are available, indicating that strains of the CC can produce novel models of neurological disease. Thus, CC strains can be a powerful resource for studying how viral infection can cause different neurological outcomes depending on host genetic background.

The Collaborative Cross Resource for Systems Genetics Research of Infectious Diseases

An increasing body of evidence highlights the role of host genetic variation in driving susceptibility to severe disease following pathogen infection. In order to fully appreciate the importance of host genetics on infection susceptibility and resulting disease, genetically variable experimental model systems should be employed. These systems allow for the identification, characterization, and mechanistic dissection of genetic variants that cause differential disease responses. Herein we discuss application of the Collaborative Cross (CC) panel of recombinant inbred strains to study viral pathogenesis, focusing on practical considerations for experimental design, assessment and analysis of disease responses within the CC, as well as some of the resources developed for the CC. Although the focus of this chapter is on viral pathogenesis, many of the methods presented within are applicable to studies of other pathogens, as well as to case-control designs in genetically diverse populations.

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins

Infection is one of the leading causes of human mortality and morbidity. Exposure to microbial agents is obviously required. However, also non-microbial environmental and host factors play a key role in the onset, development and outcome of infectious disease, resulting in large of clinical variability between individuals in a population infected with the same microbe. Controlled and standardized investigations of the genetics of susceptibility to infectious disease are almost impossible to perform in humans whereas mouse models allow application of powerful genomic techniques to identify and validate causative genes underlying human diseases with complex etiologies. Most of current animal models used in complex traits diseases genetic mapping have limited genetic diversity. This limitation impedes the ability to create incorporated network using genetic interactions, epigenetics, environmental factors, microbiota, and other phenotypes. A novel mouse genetic reference population for high-resolution mapping and subsequently identifying genes underlying the QTL, namely the Collaborative Cross (CC) mouse genetic reference population (GRP) was recently developed. In this chapter, we discuss a variety of approaches using CC mice for mapping genes underlying quantitative trait loci (QTL) to dissect the host response to polygenic traits, including infectious disease caused by bacterial agents and its toxins.

Genomic Signatures of Emerging Viruses: A New Era of Systems Epidemiology

Compared to classical epidemiologic methods, genomics can be used to precisely monitor virus evolution and transmission in real time across large, diverse populations. Integration of pathogen genomics with data about host genetics and global transcriptional responses to infection allows for comprehensive studies of population-level responses to infection and provides novel methods for predicting clinical outcomes. As genomic technologies become more accessible, these methods will redefine how emerging viruses are studied and outbreaks are contained. Here we review the existing and emerging genomic technologies that are enabling systems epidemiology and systems virology and making it possible to respond rapidly to emerging viruses such as Zika.

Using the Collaborative Cross to Study the Role of Genetic Diversity in Cancer-Related Phenotypes

Human populations are genetically diverse and often a single mouse model can only represent a small subset of the human population. Studying genetic diversity directly can improve the predictive value of mouse models of cancer biology and research on the effects of carcinogens and therapeutics in humans. The collaborative cross is a panel of inbred mouse lines that captures 90% of the genetic diversity of the Mus musculus strain and can help identify regions of the genome that are responsible for variation in cancer phenotypes across the population. The appropriate procedure will depend on the mouse model used; here, three mouse cross designs are described as examples.

Influenza H3N2 infection of the collaborative cross founder strains reveals highly divergent host responses and identifies a unique phenotype in CAST/EiJ mice

BACKGROUND

Influenza A virus is a zoonotic pathogen that poses a major threat to human and animal health. The severe course of influenza infection is not only influenced by viral virulence factors but also by individual differences in the host response. To determine the extent to which the genetic background can modulate severity of an infection, we studied the host responses to influenza infections in the eight genetically highly diverse Collaborative Cross (CC) founder mouse strains.

RESULTS

We observed highly divergent host responses between the CC founder strains with respect to survival, body weight loss, hematological parameters in the blood, relative lung weight and viral load. Mouse strain was the main factor with highest effect size on body weight loss after infection, demonstrating that this phenotype was highly heritable. Sex represented another significant main effect, although it was less strong. Analysis of survival rates and mean time to death suggested three groups of susceptibility phenotypes: highly susceptible (A/J, CAST/EiJ, WSB/EiJ), intermediate susceptible (C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ) and highly resistant strains (NZO/HlLtJ, PWK/PhJ). These three susceptibility groups were significantly different with respect to death/survival counts. Viral load was significantly different between susceptible and resistant strains but not between intermediate and highly susceptible strains. CAST/EiJ mice showed a unique phenotype. Despite high viral loads in their lungs, CAST/EiJ mice exhibited low counts of infiltrating granulocytes and showed increased numbers of macrophages in the lung. Histological studies of infected lungs and transcriptome analyses of peripheral blood cells and lungs confirmed an abnormal response in the leukocyte recruitment in CAST/EiJ mice.

CONCLUSIONS

The eight CC founder strains exhibited a large diversity in their response to influenza infections. Therefore, the CC will represent an ideal mouse genetic reference population to study the influence of genetic variation on the susceptibility and resistance to influenza infections which will be important to understand individual variations of disease severity in humans. The unique phenotype combination in the CAST/EiJ strain resembles human leukocyte adhesion deficiency and may thus represent a new mouse model to understand this and related abnormal immune responses to infections in humans.

Systems biology: A tool for charting the antiviral landscape

•

Conventional approaches overlook the complexity of the antiviral response.

•

Systems biology approaches provide a comprehensive and unbiased analysis.

•

The Collaborative Cross studies how host genetics influences antiviral immunity.

•

Transcriptomics is a powerful tool to study tissue and cellular antiviral responses.

•

Single cell analysis allows for discrimination between bystander and infected cells.

The host antiviral programs that are initiated following viral infection form a dynamic and complex web of responses that we have collectively termed as “the antiviral landscape”. Conventional approaches to studying antiviral responses have primarily used reductionist systems to assess the function of a single or a limited subset of molecules. Systems biology is a holistic approach that considers the entire system as a whole, rather than individual components or molecules. Systems biology based approaches facilitate an unbiased and comprehensive analysis of the antiviral landscape, while allowing for the discovery of emergent properties that are missed by conventional approaches. The antiviral landscape can be viewed as a hierarchy of complexity, beginning at the whole organism level and progressing downward to isolated tissues, populations of cells, and single cells. In this review, we will discuss how systems biology has been applied to better understand the antiviral landscape at each of these layers. At the organismal level, the Collaborative Cross is an invaluable genetic resource for assessing how genetic diversity influences the antiviral response. Whole tissue and isolated bulk cell transcriptomics serves as a critical tool for the comprehensive analysis of antiviral responses at both the tissue and cellular levels of complexity. Finally, new techniques in single cell analysis are emerging tools that will revolutionize our understanding of how individual cells within a bulk infected cell population contribute to the overall antiviral landscape.

High-fat-diet induced development of increased fasting glucose levels and impaired response to intraperitoneal glucose challenge in the collaborative cross mouse genetic reference population

Background

The prevalence of Type 2 Diabetes (T2D) mellitus in the past decades, has reached epidemic proportions. Several lines of evidence support the role of genetic variation in the pathogenesis of T2D and insulin resistance. Elucidating these factors could contribute to developing new medical treatments and tools to identify those most at risk. The aim of this study was to characterize the phenotypic response of the Collaborative Cross (CC) mouse genetic resource population to high-fat diet (HFD) induced T2D-like disease to evluate its suitability for this purpose.

Results

We studied 683 mice of 21 different lines of the CC population. Of these, 265 mice (149 males and 116 females) were challenged by HFD (42 % fat); and 384 mice (239 males and145 females) of 17 of the 21 lines were reared as control group on standard Chow diet (18 % fat). Briefly, 8 week old mice were maintained on HFD until 20 weeks of age, and subsequently assessed by intraperitoneal glucose tolerance test (IPGTT). Biweekly body weight (BW), body length (BL), waist circumstance (WC), and body mass index (BMI) were measured. On statistical analysis, trait measurements taken at 20 weeks of age showed significant sex by diet interaction across the different lines and traits. Consequently, males and females were analyzed, separately. Differences among lines were analyzed by ANOVA and shown to be significant (P <0.05), for BW, WC, BMI, fasting blood glucose, and IPGTT-AUC. We use these data to infer broad sense heritability adjusted for number of mice tested in each line; coefficient of genetic variation; genetic correlations between the same trait in the two sexes, and phenotypic correlations between different traits in the same sex.

Conclusions

These results are consistent with the hypothesis that host susceptibility to HFD-induced T2D is a complex trait and controlled by multiple genetic factors and sex, and that the CC population can be a powerful tool for genetic dissection of this trait.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0321-x) contains supplementary material, which is available to authorized users.

Modeling Influenza Virus Infection: A Roadmap for Influenza Research

Influenza A virus (IAV) infection represents a global threat causing seasonal outbreaks and pandemics. Additionally, secondary bacterial infections, caused mainly by Streptococcus pneumoniae, are one of the main complications and responsible for the enhanced morbidity and mortality associated with IAV infections. In spite of the significant advances in our knowledge of IAV infections, holistic comprehension of the interplay between IAV and the host immune response (IR) remains largely fragmented. During the last decade, mathematical modeling has been instrumental to explain and quantify IAV dynamics. In this paper, we review not only the state of the art of mathematical models of IAV infection but also the methodologies exploited for parameter estimation. We focus on the adaptive IR control of IAV infection and the possible mechanisms that could promote a secondary bacterial coinfection. To exemplify IAV dynamics and identifiability issues, a mathematical model to explain the interactions between adaptive IR and IAV infection is considered. Furthermore, in this paper we propose a roadmap for future influenza research. The development of a mathematical modeling framework with a secondary bacterial coinfection, immunosenescence, host genetic factors and responsiveness to vaccination will be pivotal to advance IAV infection understanding and treatment optimization.

Genome Wide Identification of SARS-CoV Susceptibility Loci Using the Collaborative Cross

New systems genetics approaches are needed to rapidly identify host genes and genetic networks that regulate complex disease outcomes. Using genetically diverse animals from incipient lines of the Collaborative Cross mouse panel, we demonstrate a greatly expanded range of phenotypes relative to classical mouse models of SARS-CoV infection including lung pathology, weight loss and viral titer. Genetic mapping revealed several loci contributing to differential disease responses, including an 8.5Mb locus associated with vascular cuffing on chromosome 3 that contained 23 genes and 13 noncoding RNAs. Integrating phenotypic and genetic data narrowed this region to a single gene, Trim55, an E3 ubiquitin ligase with a role in muscle fiber maintenance. Lung pathology and transcriptomic data from mice genetically deficient in Trim55 were used to validate its role in SARS-CoV-induced vascular cuffing and inflammation. These data establish the Collaborative Cross platform as a powerful genetic resource for uncovering genetic contributions of complex traits in microbial disease severity, inflammation and virus replication in models of outbred populations.

Genome-wide Analysis of Host-Plasmodium yoelii Interactions Reveals Regulators of the Type I Interferon Response

Invading pathogens trigger specific host responses, an understanding of which might identify genes that function in pathogen recognition and elimination. In this study, we performed trans-species expression quantitative trait locus (ts-eQTL) analysis using genotypes of the Plasmodium yoelii malaria parasite and phenotypes of mouse gene expression. We significantly linked 1,054 host genes to parasite genetic loci (LOD score ≥ 3.0). Using LOD score patterns, which produced results that differed from direct expression-level clustering, we grouped host genes that function in related pathways, allowing functional prediction of unknown genes. As a proof of principle, 14 of 15 randomly selected genes predicted to function in type I interferon (IFN-I) responses were experimentally validated using overexpression, small hairpin RNA knockdown, viral infection, and/or infection of knockout mice. This study demonstrates an effective strategy for studying gene function, establishes a functional gene database, and identifies regulators in IFN-I pathways.

MAGIC populations in crops: current status and future prospects

MAGIC populations present novel challenges and opportunities in crops due to their complex pedigree structure. They offer great potential both for dissecting genomic structure and for improving breeding populations. The past decade has seen the rise of multiparental populations as a study design offering great advantages for genetic studies in plants. The genetic diversity of multiple parents, recombined over several generations, generates a genetic resource population with large phenotypic diversity suitable for high-resolution trait mapping. While there are many variations on the general design, this review focuses on populations where the parents have all been inter-mated, typically termed Multi-parent Advanced Generation Intercrosses (MAGIC). Such populations have already been created in model animals and plants, and are emerging in many crop species. However, there has been little consideration of the full range of factors which create novel challenges for design and analysis in these populations. We will present brief descriptions of large MAGIC crop studies currently in progress to motivate discussion of population construction, efficient experimental design, and genetic analysis in these populations. In addition, we will highlight some recent achievements and discuss the opportunities and advantages to exploit the unique structure of these resources post-QTL analysis for gene discovery.

Molecular determinants of influenza virus pathogenesis in mice

Mice are widely used for studying influenza virus pathogenesis and immunology because of their low cost, the wide availability of mouse-specific reagents, and the large number of mouse strains available, including knockout and transgenic strains. However, mice do not fully recapitulate the signs of influenza infection of humans: transmission of influenza between mice is much less efficient than in humans, and influenza viruses often require adaptation before they are able to efficiently replicate in mice. In the process of mouse adaptation, influenza viruses acquire mutations that enhance their ability to attach to mouse cells, replicate within the cells, and suppress immunity, among other functions. Many such mouse-adaptive mutations have been identified, covering all 8 genomic segments of the virus. Identification and analysis of these mutations have provided insight into the molecular determinants of influenza virulence and pathogenesis, not only in mice but also in humans and other species. In particular, several mouse-adaptive mutations of avian influenza viruses have proved to be general mammalian-adaptive changes that are potential markers of pre-pandemic viruses. As well as evaluating influenza pathogenesis, mice have also been used as models for evaluation of novel vaccines and anti-viral therapies. Mice can be a useful animal model for studying influenza biology as long as differences between human and mice infections are taken into account.

Splicing landscape of the eight collaborative cross founder strains

Background

The Collaborative Cross (CC) is a large panel of genetically diverse recombinant inbred mouse strains specifically designed to provide a systems genetics resource for the study of complex traits. In part, the utility of the CC stems from the extensive genome-wide annotations of founder strain sequence and structural variation. Still missing, however, are transcriptome-specific annotations of the CC founder strains that could further enhance the utility of this resource.

Results

We provide a comprehensive survey of the splicing landscape of the 8 CC founder strains by leveraging the high level of alternative splicing within the brain. Using deep transcriptome sequencing, we found that a majority of the splicing landscape is conserved among the 8 strains, with ~65% of junctions being shared by at least 2 strains. We, however, found a large number of potential strain-specific splicing events as well, with an average of ~3000 and ~500 with ≥3 and ≥10 sequence read coverage, respectively, within each strain. To better understand strain-specific splicing within the CC founder strains, we defined criteria for and identified high-confidence strain-specific splicing events. These splicing events were defined as exon-exon junctions 1) found within only one strain, 2) with a read coverage ≥10, and 3) defined by a canonical splice site. With these criteria, a total of 1509 high-confidence strain-specific splicing events were identified, with the majority found within two of the wild-derived strains, CAST and PWK. Strikingly, the overwhelming majority, 94%, of these strain-specific splicing events are not yet annotated. Strain-specific splicing was also located within genomic regions recently reported to be over- and under-represented within CC populations.

Conclusions

Phenotypic characterization of CC populations is increasing; thus these results will not only aid in further elucidating the transcriptomic architecture of the individual CC founder strains, but they will also help in guiding the utilization of the CC populations in the study of complex traits. This report is also the first to establish guidelines in defining and identifying strain-specific splicing across different mouse strains.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1267-0) contains supplementary material, which is available to authorized users.

Host genetic diversity enables Ebola hemorrhagic fever pathogenesis and resistance

Existing mouse models of lethal Ebola virus infection do not reproduce hallmark symptoms of Ebola hemorrhagic fever, neither delayed blood coagulation and disseminated intravascular coagulation nor death from shock, thus restricting pathogenesis studies to nonhuman primates. Here we show that mice from the Collaborative Cross panel of recombinant inbred mice exhibit distinct disease phenotypes after mouse-adapted Ebola virus infection. Phenotypes range from complete resistance to lethal disease to severe hemorrhagic fever characterized by prolonged coagulation times and 100% mortality. Inflammatory signaling was associated with vascular permeability and endothelial activation, and resistance to lethal infection arose by induction of lymphocyte differentiation and cellular adhesion, probably mediated by the susceptibility allele Tek. These data indicate that genetic background determines susceptibility to Ebola hemorrhagic fever.

The interferon-induced gene Ifi27l2a is active in lung macrophages and lymphocytes after influenza A infection but deletion of Ifi27l2a in mice does not increase susceptibility to infection

Interferons represent one of the first and essential host defense mechanisms after infection, and the activation of the IFN-pathway results in the transcriptional activation of hundreds of interferon-stimulated genes. The alpha-inducible protein 27 like 2A (Ifi27l2a) gene (human synonym: ISG12) is strongly up-regulated in the lung after influenza A infection in mice and has been shown in gene expression studies to be highly correlated to other activated genes. Therefore, we investigated the role of Ifi27l2a for the host defense to influenza A infections in more detail. RT-PCR analyses in non-infected mice demonstrated that Ifi27l2a was expressed in several tissues, including the lung. Detailed analyses of reporter gene expression in lungs from Ifi27l2a-LacZ mice revealed that Ifi27l2a was expressed in macrophages and lymphocytes but not in alveolar cells or bronchiolar epithelium cells. The number of macrophages and lymphocyte strongly increased in the lung after infection, but no significant increase in expression levels of the LacZ reporter gene was found within individual immune cells. Also, no reporter gene expression was found in bronchiolar epithelial cells, alveolar cells or infiltrating neutrophils after infection. Thus, up-regulation of Ifi27l2a in infected lungs is mainly due to the infiltration of macrophages and lymphocytes. Most surprisingly, deletion of Ifi27l2a in mouse knock-out lines did not result in increased susceptibility to infections with H1N1 or H7N7 influenza A virus compared to wild type C57BL/6N mice, suggesting a less important role of the gene for the host response to influenza infections than for bacterial infections.

Integrative genetic analysis of allergic inflammation in the murine lung

Airway allergen exposure induces inflammation among individuals with atopy that is characterized by altered airway gene expression, elevated levels of T helper type 2 cytokines, mucus hypersecretion, and airflow obstruction. To identify the genetic determinants of the airway allergen response, we employed a systems genetics approach. We applied a house dust mite mouse model of allergic airway disease to 151 incipient lines of the Collaborative Cross, a new mouse genetic reference population, and measured serum IgE, airway eosinophilia, and gene expression in the lung. Allergen-induced serum IgE and airway eosinophilia were not correlated. We detected quantitative trait loci (QTL) for airway eosinophilia on chromosome (Chr) 11 (71.802-87.098 megabases [Mb]) and allergen-induced IgE on Chr 4 (13.950-31.660 Mb). More than 4,500 genes expressed in the lung had gene expression QTL (eQTL), the majority of which were located near the gene itself. However, we also detected approximately 1,700 trans-eQTL, and many of these trans-eQTL clustered into two regions on Chr 2. We show that one of these loci (at 147.6 Mb) is associated with the expression of more than 100 genes, and, using bioinformatics resources, fine-map this locus to a 53 kb-long interval. We also use the gene expression and eQTL data to identify a candidate gene, Tlcd2, for the eosinophil QTL. Our results demonstrate that hallmark allergic airway disease phenotypes are associated with distinct genetic loci on Chrs 4 and 11, and that gene expression in the allergically inflamed lung is controlled by both cis and trans regulatory factors.

Genetic regulation of Zfp30, CXCL1, and neutrophilic inflammation in murine lung

Allergic asthma is a complex disease characterized in part by granulocytic inflammation of the airways. In addition to eosinophils, neutrophils (PMN) are also present, particularly in cases of severe asthma. We sought to identify the genetic determinants of neutrophilic inflammation in a mouse model of house dust mite (HDM)-induced asthma. We applied an HDM model of allergic asthma to the eight founder strains of the Collaborative Cross (CC) and 151 incipient lines of the CC (preCC). Lung lavage fluid was analyzed for PMN count and the concentration of CXCL1, a hallmark PMN chemokine. PMN and CXCL1 were strongly correlated in preCC mice. We used quantitative trait locus (QTL) mapping to identify three variants affecting PMN, one of which colocalized with a QTL for CXCL1 on chromosome (Chr) 7. We used lung eQTL data to implicate a variant in the gene Zfp30 in the CXCL1/PMN response. This genetic variant regulates both CXCL1 and PMN by altering Zfp30 expression, and we model the relationships between the QTL and these three endophenotypes. We show that Zfp30 is expressed in airway epithelia in the normal mouse lung and that altering Zfp30 expression in vitro affects CXCL1 responses to an immune stimulus. Our results provide strong evidence that Zfp30 is a novel regulator of neutrophilic airway inflammation.

Quantitative genetics in the study of virus-induced disease

While the role of viral variants has long been known to play a key role in causing variation in disease severity, it is also clear that host genetic variation plays a critical role in determining virus-induced disease responses. However, a variety of factors, including confounding environmental variables, rare genetic variants requiring extremely large cohorts, the temporal dynamics of infections, and ethical limitation on human studies, have made the identification and dissection of variant host genes and pathways difficult within human populations. This difficulty has led to the development of a variety of experimental approaches used to identify host genetic contributions to disease responses. In this chapter, we describe the history of genetic associations within the human population, the development of experimentally tractable systems, and the insights these specific approaches provide. We conclude with a discussion of recent advances that allow for the investigation of the role of complex genetic networks that underlie host responses to infection, with the goal of drawing connections to human infections. In particular, we highlight the need for robust animal models with which to directly control and assess the role of host genetics on viral infection outcomes.

Allele-specific expression and eQTL analysis in mouse adipose tissue

Background

The simplest definition of cis-eQTLs versus trans, refers to genetic variants that affect expression in an allele specific manner, with implications on underlying mechanism. Yet, due to technical limitations of expression microarrays, the vast majority of eQTL studies performed in the last decade used a genomic distance based definition as a surrogate for cis, therefore exploring local rather than cis-eQTLs.

Results

In this study we use RNAseq to explore allele specific expression (ASE) in adipose tissue of male and female F1 mice, produced from reciprocal crosses of C57BL/6J and DBA/2J strains. Comparison of the identified cis-eQTLs, to local-eQTLs, that were obtained from adipose tissue expression in two previous population based studies in our laboratory, yields poor overlap between the two mapping approaches, while both local-eQTL studies show highly concordant results. Specifically, local-eQTL studies show ~60% overlap between themselves, while only 15-20% of local-eQTLs are identified as cis by ASE, and less than 50% of ASE genes are recovered in local-eQTL studies. Utilizing recently published ENCODE data, we also find that ASE genes show significant bias for SNPs prevalence in DNase I hypersensitive sites that is ASE direction specific.

Conclusions

We suggest a new approach to analysis of allele specific expression that is more sensitive and accurate than the commonly used fisher or chi-square statistics. Our analysis indicates that technical differences between the cis and local-eQTL approaches, such as differences in genomic background or sex specificity, account for relatively small fraction of the discrepancy. Therefore, we suggest that the differences between two eQTL mapping approaches may facilitate sorting of SNP-eQTL interactions into true cis and trans, and that a considerable portion of local-eQTL may actually represent trans interactions.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-471) contains supplementary material, which is available to authorized users.

Genomic profiling of collaborative cross founder mice infected with respiratory viruses reveals novel transcripts and infection-related strain-specific gene and isoform expression

Genetic variation between diverse mouse species is well-characterized, yet existing knowledge of the mouse transcriptome comes largely from one mouse strain (C57BL/6J). As such, it is unlikely to reflect the transcriptional complexity of the mouse species. Gene transcription is dynamic and condition-specific; therefore, to better understand the mouse transcriptional response to respiratory virus infection, we infected the eight founder strains of the Collaborative Cross with either influenza A virus or severe acute respiratory syndrome coronavirus and sequenced lung RNA samples at 2 and 4 days after infection. We found numerous instances of transcripts that were not present in the C57BL/6J reference annotation, indicating that a nontrivial proportion of the mouse genome is transcribed but poorly annotated. Of these novel transcripts, 2150 could be aligned to human or rat genomes, but not to existing mouse genomes, suggesting functionally conserved sequences not yet recorded in mouse genomes. We also found that respiratory virus infection induced differential expression of 4287 splicing junctions, resulting in strain-specific isoform expression. Of these, 59 were influenced by strain-specific mutations within 2 base pairs of key intron–exon boundaries, suggesting cis-regulated expression. Our results reveal the complexity of the transcriptional response to viral infection, previously undocumented genomic elements, and extensive diversity in the response across mouse strains. These findings identify hitherto unexplored transcriptional patterns and undocumented transcripts in genetically diverse mice. Host genetic variation drives the complexity and diversity of the host response by eliciting starkly different transcriptional profiles in response to a viral infection.

Systems approaches to Coronavirus pathogenesis

Coronaviruses comprise a large group of emergent human and animal pathogens, including the highly pathogenic SARS-CoV and MERS-CoV strains that cause significant morbidity and mortality in infected individuals, especially the elderly. As emergent viruses may cause episodic outbreaks of disease over time, human samples are limited. Systems biology and genetic technologies maximize opportunities for identifying critical host and viral genetic factors that regulate susceptibility and virus-induced disease severity. These approaches provide discovery platforms that highlight and allow targeted confirmation of critical targets for prophylactics and therapeutics, especially critical in an outbreak setting. Although poorly understood, it has long been recognized that host regulation of virus-associated disease severity is multigenic. The advent of systems genetic and biology resources provides new opportunities for deconvoluting the complex genetic interactions and expression networks that regulate pathogenic or protective host response patterns following virus infection. Using SARS-CoV as a model, dynamic transcriptional network changes and disease-associated phenotypes have been identified in different genetic backgrounds, leading to the promise of population-wide discovery of the underpinnings of Coronavirus pathogenesis.

Systems analysis of West Nile virus infection

•

Emerging/re-emerging mosquito-borne viruses are a significant public health threat.

•

There is a need define the virus–host interactions that govern immunity to infection.

•

Systems biology provides a comprehensive analysis of the host response.

•

High-throughput based assays provide rapid identification of host targets.

Emerging and re-emerging mosquito-borne viruses continue to pose a significant threat to human health throughout the world. Over the past decade, West Nile virus (WNV), Dengue virus (DENV), and Chikungunya virus (CHIKV), have caused annual epidemics of virus-induced encephalitis, hemorrhagic fever\shock syndromes, and arthritis, respectively. Currently, no specific antiviral therapies or vaccines exist for use in humans to combat or prevent these viral infections. Thus, there is a pressing need to define the virus–host interactions that govern immunity and infection outcome. Recent technological breakthroughs in ‘omics’ resources and high-throughput based assays are beginning to accelerate antiviral drug discovery and improve on current strategies for vaccine design. In this review, we highlight studies with WNV and discuss how traditional and systems biological approaches are being used to rapidly identify novel host targets for therapeutic intervention and develop a deeper conceptual understanding of the host response to virus infection.

Systems biology and systems genetics - novel innovative approaches to study host-pathogen interactions during influenza infection

Influenza represents a serious threat to public health with thousands of deaths each year. A deeper understanding of the host-pathogen interactions is urgently needed to evaluate individual and population risks for severe influenza disease and to identify new therapeutic targets. Here, we review recent progress in large scale omics technologies, systems genetics as well as new mathematical and computational developments that are now in place to apply a systems biology approach for a comprehensive description of the multidimensional host response to influenza infection. In addition, we describe how results from experimental animal models can be translated to humans, and we discuss some of the future challenges ahead.