After GWAS: mice to the rescue?

Probing the basis of disease heterogeneity in multiple sclerosis using genetically diverse mice

Multiple sclerosis (MS) is a complex disease with significant heterogeneity in disease course and progression. Genetic studies have identified numerous loci associated with MS risk, but the genetic basis of disease progression remains elusive. To address this, we leveraged the Collaborative Cross (CC), a genetically diverse mouse strain panel, and experimental autoimmune encephalomyelitis (EAE). The thirty-two CC strains studied captured a wide spectrum of EAE severity, trajectory, and presentation, including severe-progressive, monophasic, relapsing remitting, and axial rotary (AR)-EAE, accompanied by distinct immunopathology. Sex differences in EAE severity were observed in six strains. Quantitative trait locus analysis revealed distinct genetic linkage patterns for different EAE phenotypes, including EAE severity and incidence of AR-EAE. Machine learning-based approaches prioritized candidate genes for loci underlying EAE severity ( Abcc4 and Gpc6 ) and AR-EAE ( Yap1 and Dync2h1 ). This work expands the EAE phenotypic repertoire and identifies novel loci controlling unique EAE phenotypes, supporting the hypothesis that heterogeneity in MS disease course is driven by genetic variation.

Summary

The genetic basis of disease heterogeneity in multiple sclerosis (MS) remains elusive. We leveraged the Collaborative Cross to expand the phenotypic repertoire of the experimental autoimmune encephalomyelitis (EAE) model of MS and identify loci controlling EAE severity, trajectory, and presentation.

Genomic Basis for Individual Differences in Susceptibility to the Neurotoxic Effects of Diesel Exhaust

Air pollution is a known environmental health hazard. A major source of air pollution includes diesel exhaust (DE). Initially, research on DE focused on respiratory morbidities; however, more recently, exposures to DE have been associated with neurological developmental disorders and neurodegeneration. In this study, we investigated the effects of sub-chronic inhalation exposure to DE on neuroinflammatory markers in two inbred mouse strains and both sexes, including whole transcriptome examination of the medial prefrontal cortex. We exposed aged male and female C57BL/6J (B6) and DBA/2J (D2) mice to DE, which was cooled and diluted with HEPA-filtered compressed air for 2 h per day, 5 days a week, for 4 weeks. Control animals were exposed to HEPA-filtered air on the same schedule as DE-exposed animals. The prefrontal cortex was harvested and analyzed for proinflammatory cytokine gene expression (Il1β, Il6, Tnfα) and transcriptome-wide response by RNA-seq. We observed differential cytokine gene expression between strains and sexes in the DE-exposed vs. control-exposed groups for Il1β, Tnfα, and Il6. For RNA-seq, we identified 150 differentially expressed genes between air and DE treatment related to natural killer cell-mediated cytotoxicity per Kyoto Encyclopedia of Genes and Genomes pathways. Overall, our data show differential strain-related effects of DE on neuroinflammation and neurotoxicity and demonstrate that B6 are more susceptible than D2 to gene expression changes due to DE exposures than D2. These results are important because B6 mice are often used as the default mouse model for DE studies and strain-related effects of DE neurotoxicity warrant expanded studies.

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

Vaccines represent one of the major advances of modern medicine. Despite the many successes of vaccination, continuous efforts to design new vaccines are needed to fight "old" pandemics, such as tuberculosis and malaria, as well as emerging pathogens, such as Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Vaccination aims at reaching sterilizing immunity, however assessing vaccine efficacy is still challenging and underscores the need for a better understanding of immune protective responses. Identifying reliable predictive markers of immunogenicity can help to select and develop promising vaccine candidates during early preclinical studies and can lead to improved, personalized, vaccination strategies. A systems biology approach is increasingly being adopted to address these major challenges using multiple high-dimensional technologies combined with in silico models. Although the goal is to develop predictive models of vaccine efficacy in humans, applying this approach to animal models empowers basic and translational vaccine research. In this review, we provide an overview of vaccine immune signatures in preclinical models, as well as in target human populations. We also discuss high-throughput technologies used to probe vaccine-induced responses, along with data analysis and computational methodologies applied to the predictive modeling of vaccine efficacy.

Modeling the Genetic Basis of Individual Differences in Susceptibility to Gulf War Illness

Between 25% and 30% of the nearly one million military personnel who participated in the 1991 Persian Gulf War became ill with chronic symptoms ranging from gastrointestinal to nervous system dysfunction. This disorder is now referred to as Gulf War Illness (GWI) and the underlying pathophysiology has been linked to exposure-based neuroinflammation caused by organophosphorous (OP) compounds coupled with high circulating glucocorticoids. In a mouse model of GWI we developed, corticosterone was shown to act synergistically with an OP (diisopropylflurophosphate) to dramatically increase proinflammatory cytokine gene expression in the brain. Because not all Gulf War participants became sick, the question arises as to whether differential genetic constitution might underlie individual differences in susceptibility. To address this question of genetic liability, we tested the impact of OP and glucocorticoid exposure in a genetic reference population of 30 inbred mouse strains. We also studied both sexes. The results showed wide differences among strains and overall that females were less sensitive to the combined treatment than males. Furthermore, we identified one OP-glucocorticoid locus and nominated a candidate gene-Spon1-that may underlie the marked differences in response.

LD-annot: A Bioinformatics Tool to Automatically Provide Candidate SNPs With Annotations for Genetically Linked Genes

A multitude of model and non-model species studies have now taken full advantage of powerful high-throughput genotyping advances such as SNP arrays and genotyping-by-sequencing (GBS) technology to investigate the genetic basis of trait variation. However, due to incomplete genome coverage by these technologies, the identified SNPs are likely in linkage disequilibrium (LD) with the causal polymorphisms, rather than be causal themselves. In addition, researchers could benefit from annotations for the identified candidate SNPs and, simultaneously, for all neighboring genes in genetic linkage. In such case, LD extent estimation surrounding the candidate SNPs is required to determine the regions encompassing genes of interest. We describe here an automated pipeline, “LD-annot,” designed to delineate specific regions of interest for a given experiment and candidate polymorphisms on the basis of LD extent, and furthermore, provide annotations for all genes within such regions. LD-annot uses standard file formats, bioinformatics tools, and languages to provide identifiers, coordinates, and annotations for genes in genetic linkage with each candidate polymorphism. Although the focus lies upon SNP arrays and GBS data as they are being routinely deployed, this pipeline can be applied to a variety of datasets as long as genotypic data are available for a high number of polymorphisms and formatted into a vcf file. A checkpoint procedure in the pipeline allows to test several threshold values for linkage without having to rerun the entire pipeline, thus saving the user computational time and resources. We applied this new pipeline to four different sample sets: two breeding populations GBS datasets, one within-pedigree SNP set coming from whole genome sequencing (WGS), and a very large multi-varieties SNP dataset obtained from WGS, representing variable sample sizes, and numbers of polymorphisms. LD-annot performed within minutes, even when very high numbers of polymorphisms are investigated and thus will efficiently assist research efforts aimed at identifying biologically meaningful genetic polymorphisms underlying phenotypic variation. LD-annot tool is available under a GPL license from https://github.com/ArnaudDroitLab/LD-annot.

Untangling the genomics of noise-induced hearing loss and tinnitus: Contributions of Mus musculus and Homo sapiens

Acoustic trauma is a feature of the industrial age, in general, and mechanized warfare, in particular. Noise-induced hearing loss (NIHL) and tinnitus have been the number 1 and number 2 disabilities at U.S. Veterans hospitals since 2006. In a reversal of original protocols to identify candidate genes associated with monogenic deafness disorders, unbiased genome-wide association studies now direct animal experiments in order to explore genetic variants common in Homo sapiens. However, even these approaches must utilize animal studies for validation of function and understanding of mechanisms. Animal research currently focuses on genetic expression profiles since the majority of variants occur in non-coding regions, implying regulatory divergences. Moving forward, it will be important in both human and animal research to define the phenotypes of hearing loss and tinnitus, as well as exposure parameters, in order to extricate genes related to acoustic trauma versus those related to aging. It has become clear that common disorders like acoustic trauma are influenced by large numbers of genes, each with small effects, which cumulatively lead to susceptibility to a disorder. A polygenic risk score, which aggregates these small effect sizes of multiple genes, may offer a more accurate description of risk for NIHL and/or tinnitus.

Gene-by-environment interactions in Alzheimer's disease and Parkinson's disease

Diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) arise from complex interactions of genetic and environmental factors, with genetic variants regulating individual responses to environmental exposures (i.e. gene-by-environment interactions). Identifying gene-by-environment interactions will be critical to fully understanding disease mechanisms and developing personalized therapeutics, though these interactions are still poorly understood and largely under-studied. Candidate gene approaches have shown that known disease risk variants often regulate response to environmental factors. However, recent improvements in exposome- and genome-wide association and interaction studies in humans and mice are enabling discovery of novel genetic variants and pathways that predict response to a variety of environmental factors. Here, we highlight recent approaches and ongoing developments in human and rodent studies to identify genetic modulators of environmental factors using AD and PD as exemplars. Identifying gene-by-environment interactions in disease will be critical to developing personalized intervention strategies and will pave the way for precision medicine.

Mouse models and strain-dependency of Chédiak-Higashi syndrome-associated neurologic dysfunction

Chédiak-Higashi syndrome (CHS) is a lethal disorder caused by mutations in the LYST gene that involves progressive neurologic dysfunction. Lyst-mutant mice exhibit neurologic phenotypes that are sensitive to genetic background. On the DBA/2J-, but not on the C57BL/6J-background, Lyst-mutant mice exhibit overt tremor phenotypes associated with loss of cerebellar Purkinje cells. Here, we tested whether assays for ataxia could measure this observed strain-dependency, and if so, establish parameters for empowering phenotype- and candidate-driven approaches to identify genetic modifier(s). A composite phenotypic scoring system distinguished phenotypes in Lyst-mutants and uncovered a previously unrecognized background difference between wild-type C57BL/6J and DBA/2J mice. Accelerating rotarod performance also distinguished phenotypes in Lyst-mutants, but at more advanced ages. These results establish that genetic background, Lyst genotype, and age significantly influence the severity of CHS-associated neurologic deficits. Purkinje cell quantifications likewise distinguished phenotypes of Lyst-mutant mice, as well as background differences between wild-type C57BL/6J and DBA/2J mice. To aid identification of potential genetic modifier genes causing these effects, we searched public datasets for cerebellar-expressed genes that are differentially expressed and/or contain potentially detrimental genetic variants. From these approaches, Nos1, Prdx2, Cbln3, Gnb1, Pttg1 were confirmed to be differentially expressed and leading candidates.

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.

Genetic modifiers as relevant biological variables of eye disorders

From early in the study of mammalian genetics, it was clear that modifiers can have a striking influence on phenotypes. Today, several modifiers have now been studied in enough detail to allow a glimpse of how they function and influence our perspective of disease. With respect to diseases of the eye, some modifiers are an important source of phenotypic variation that can elucidate how genes function in networks to collectively shape ocular anatomy and physiology, thus influencing our understanding of basic biology. Other modifiers represent an opportunity for new therapeutic targets, whose manipulation could be used to mitigate ophthalmic disease. Here, we review progress in the study of genetic modifiers of eye disorders, with examples from mice and humans that together illustrate the ubiquitous nature of genetic modifiers and why they are relevant biological variables in experimental design. Special emphasis is given to ophthalmic modifiers in mice, especially those relevant to selection of genetic background and those that might inadvertently be a source of experimental variability. These modifiers are capable of influencing interpretations of many experiments using targeted genome manipulations such as knockouts or transgenics. Whereas there are fewer examples of modifiers of eye disorders in humans with a molecular identification, there is ample evidence that they exist and should be considered as a relevant biological variable in human genetic studies as well.

Mining the Unknown: Assigning Function to Noncoding Single Nucleotide Polymorphisms

One of the formative goals of genetics research is to understand how genetic variation leads to phenotypic differences and human disease. Genome-wide association studies (GWASs) bring us closer to this goal by linking variation with disease faster than ever before. Despite this, GWASs alone are unable to pinpoint disease-causing single nucleotide polymorphisms (SNPs). Noncoding SNPs, which represent the majority of GWAS SNPs, present a particular challenge. To address this challenge, an array of computational tools designed to prioritize and predict the function of noncoding GWAS SNPs have been developed. However, fewer than 40% of GWAS publications from 2015 utilized these tools. We discuss several leading methods for annotating noncoding variants and how they can be integrated into research pipelines in hopes that they will be broadly applied in future GWAS analyses.

Animal models of RLS phenotypes

Restless legs syndrome (RLS) is a complex disorder that involves sensory and motor systems. The major pathophysiology of RLS is low iron concentration in the substantia nigra containing the cell bodies of dopamine neurons that project to the striatum, an area that is crucial for modulating movement. People who have RLS often present with normal iron values outside the brain; recent studies implicate several genes are involved in the syndrome. Like most complex diseases, animal models usually do not faithfully capture the full phenotypic spectrum of "disease," which is a uniquely human construct. Nonetheless, animal models have proven useful in helping to unravel the complex pathophysiology of diseases such as RLS and suggesting novel treatment paradigms. For example, hypothesis-independent genome-wide association studies (GWAS) have identified several genes as increasing the risk for RLS, including BTBD9. Independently, the murine homolog Btbd9 was identified as a candidate gene for iron regulation in the midbrain in mice. The relevance of the phenotype of another of the GWAS identified genes, MEIS1, has also been explored. The role of Btbd9 in iron regulation and RLS-like behaviors has been further evaluated in mice carrying a null mutation of the gene and in fruit flies when the BTBD9 protein is degraded. The BTBD9 and MEIS1 stories originate from human GWAS research, supported by work in a genetic reference population of mice (forward genetics) and further verified in mice, fish flies, and worms. Finally, the role of genetics is further supported by an inbred mouse strain that displays many of the phenotypic characteristics of RLS. The role of animal models of RLS phenotypes is also extended to include periodic limb movements.

Early Interactions of Murine Macrophages with Francisella tularensis Map to Mouse Chromosome 19

Differences among individuals in susceptibility to infectious diseases can be modulated by host genetics. Much of the research in this field has aimed to identify loci within the host genome that are associated with these differences. In mice, A/J (AJ) and C57BL/6J (B6) mice show differential susceptibilities to various pathogens, including the intracellular pathogen Francisella tularensis. Because macrophages are the main initial target during F. tularensis infection, we explored early interactions of macrophages from these two mouse strains with F. tularensis as well as the genetic factors underlying these interactions. Our results indicate that bacterial interactions with bone marrow-derived macrophages (BMDMs) during early stages of infection are different in the AJ and B6 strains. During these early stages, bacteria are more numerous in B6 than in AJ macrophages and display differences in trafficking and early transcriptional response within these macrophages. To determine the genetic basis for these differences, we infected BMDMs isolated from recombinant inbred (RI) mice derived from reciprocal crosses between AJ and B6, and we followed early bacterial counts within these macrophages. Quantitative trait locus (QTL) analysis revealed a locus on chromosome 19 that is associated with early differences in bacterial counts in AJ versus B6 macrophages. QTL analysis of published data that measured the differential susceptibilities of the same RI mice to an in vivo challenge with F. tularensis confirmed the F. tularensis susceptibility QTL on chromosome 19. Overall, our results show that early interactions of macrophages with F. tularensis are dependent on the macrophage genetic background.

IMPORTANCE

Francisella tularensis is a highly pathogenic bacterium with a very low infectious dose in humans. Some mechanisms of bacterial virulence have been elucidated, but the host genetic factors that contribute to host resistance or susceptibility are largely unknown. In this work, we have undertaken a genetic approach to assess what these factors are in mice. Analyzing early interactions of macrophages with the bacteria as well as data on overall susceptibility to infection revealed a locus on chromosome 19 that is associated with both phenotypes. In addition, our work revealed differences in the early macrophage response between macrophages with different genetic backgrounds. Overall, this work suggests some intriguing links between in vitro and in vivo infection models and should aid in further elucidating the genetic circuits behind the host response to Francisella tularensis infection.

Genetics of coronary artery disease and myocardial infarction

Atherosclerotic coronary artery disease (CAD) comprises a broad spectrum of clinical entities that include asymptomatic subclinical atherosclerosis and its clinical complications, such as angina pectoris, myocardial infarction (MI) and sudden cardiac death. CAD continues to be the leading cause of death in industrialized society. The long-recognized familial clustering of CAD suggests that genetics plays a central role in its development, with the heritability of CAD and MI estimated at approximately 50% to 60%. Understanding the genetic architecture of CAD and MI has proven to be difficult and costly due to the heterogeneity of clinical CAD and the underlying multi-decade complex pathophysiological processes that involve both genetic and environmental interactions. This review describes the clinical heterogeneity of CAD and MI to clarify the disease spectrum in genetic studies, provides a brief overview of the historical understanding and estimation of the heritability of CAD and MI, recounts major gene discoveries of potential causal mutations in familial CAD and MI, summarizes CAD and MI-associated genetic variants identified using candidate gene approaches and genome-wide association studies (GWAS), and summarizes the current status of the construction and validations of genetic risk scores for lifetime risk prediction and guidance for preventive strategies. Potential protective genetic factors against the development of CAD and MI are also discussed. Finally, GWAS have identified multiple genetic factors associated with an increased risk of in-stent restenosis following stent placement for obstructive CAD. This review will also address genetic factors associated with in-stent restenosis, which may ultimately guide clinical decision-making regarding revascularization strategies for patients with CAD and MI.

Role of non-coding sequence variants in cancer

Patients with cancer carry somatic sequence variants in their tumour in addition to the germline variants in their inherited genome. Although variants in protein-coding regions have received the most attention, numerous studies have noted the importance of non-coding variants in cancer. Moreover, the overwhelming majority of variants, both somatic and germline, occur in non-coding portions of the genome. We review the current understanding of non-coding variants in cancer, including the great diversity of the mutation types--from single nucleotide variants to large genomic rearrangements--and the wide range of mechanisms by which they affect gene expression to promote tumorigenesis, such as disrupting transcription factor-binding sites or functions of non-coding RNAs. We highlight specific case studies of somatic and germline variants, and discuss how non-coding variants can be interpreted on a large-scale through computational and experimental methods.

Sleeping Beauty Transposon Mutagenesis as a Tool for Gene Discovery in the NOD Mouse Model of Type 1 Diabetes

A number of different strategies have been used to identify genes for which genetic variation contributes to type 1 diabetes (T1D) pathogenesis. Genetic studies in humans have identified >40 loci that affect the risk for developing T1D, but the underlying causative alleles are often difficult to pinpoint or have subtle biological effects. A complementary strategy to identifying "natural" alleles in the human population is to engineer "artificial" alleles within inbred mouse strains and determine their effect on T1D incidence. We describe the use of the Sleeping Beauty (SB) transposon mutagenesis system in the nonobese diabetic (NOD) mouse strain, which harbors a genetic background predisposed to developing T1D. Mutagenesis in this system is random, but a green fluorescent protein (GFP)-polyA gene trap within the SB transposon enables early detection of mice harboring transposon-disrupted genes. The SB transposon also acts as a molecular tag to, without additional breeding, efficiently identify mutated genes and prioritize mutant mice for further characterization. We show here that the SB transposon is functional in NOD mice and can produce a null allele in a novel candidate gene that increases diabetes incidence. We propose that SB transposon mutagenesis could be used as a complementary strategy to traditional methods to help identify genes that, when disrupted, affect T1D pathogenesis.

Host genetic diversity influences the severity of Pseudomonas aeruginosa pneumonia in the Collaborative Cross mice

BACKGROUND

Pseudomonas aeruginosa is one of the top three causes of opportunistic infections in humans. Patients with a compromised immune system, due to immunosuppressive therapies or underlying diseases such as cancer, AIDS or the hereditary disease cystic fibrosis, are at risk of developing P. aeruginosa infection. However, clinical evidence indicates extremely variable outcomes of P. aeruginosa infections in individuals at risk, suggesting that host multi-complex genetic traits may influence the severity of this opportunistic infection. Here, we have used an innovative experimental model to dissect whether host genetic background, such as those found in the outbred population, could influence the risk of morbidity and mortality to P. aeruginosa pneumonia.

RESULTS

A highly genetically-diverse mouse resource population, Collaborative Cross (CC) mice, was infected with a clinical strain of P. aeruginosa and subsequently monitored for mortality, mean survival time, and morbidity, change in body weight for seven days post infection. Disease phenotypes ranged from complete resistance and recovery of body weight to lethal disease. Initial variables, including body weight, age and gender, have limited influence on P. aeruginosa outcome, emphasizing the role of host genetic background in defining the risk of morbidity and mortality. When broad-sense heritability of phenotypic traits was evaluated, it confirmed the influence of genetic profile rather than environmental factors among the CC lines during P. aeruginosa infection.

CONCLUSION

This innovative model system can potentially reproduce the variables responses of disease severity observed in humans during P. aeruginosa pneumonia. Our results demonstrated that a widely-marked differential response to P. aeruginosa airway infection in term of morbidity and mortality, is mainly affected by host genetic factors, as multiple genetic loci or polymorphic variations.

Using genetic mouse models to gain insight into glaucoma: Past results and future possibilities

While all forms of glaucoma are characterized by a specific pattern of retinal ganglion cell death, they are clinically divided into several distinct subclasses, including normal tension glaucoma, primary open angle glaucoma, congenital glaucoma, and secondary glaucoma. For each type of glaucoma there are likely numerous molecular pathways that control susceptibility to the disease. Given this complexity, a single animal model will never precisely model all aspects of all the different types of human glaucoma. Therefore, multiple animal models have been utilized to study glaucoma but more are needed. Because of the powerful genetic tools available to use in the laboratory mouse, it has proven to be a highly useful mammalian system for studying the pathophysiology of human disease. The similarity between human and mouse eyes coupled with the ability to use a combination of advanced cell biological and genetic tools in mice have led to a large increase in the number of studies using mice to model specific glaucoma phenotypes. Over the last decade, numerous new mouse models and genetic tools have emerged, providing important insight into the cell biology and genetics of glaucoma. In this review, we describe available mouse genetic models that can be used to study glaucoma-relevant disease/pathobiology. Furthermore, we discuss how these models have been used to gain insights into ocular hypertension (a major risk factor for glaucoma) and glaucomatous retinal ganglion cell death. Finally, the potential for developing new mouse models and using advanced genetic tools and resources for studying glaucoma are discussed.

Matrix metalloproteinases and genetic mouse models in cancer research: a mini-review

Carcinogenesis is a multistep and also a multifactorial process that involves agents like genetic and environmental factors. Matrix metalloproteinases (MMPs) are major proteolytic enzymes which are involved in cancer cell migration, invasion, and metastasis. Genetic variations in genes encoding the MMPs were shown in human studies to influence cancer risk and phenotypic features of a tumor. The complex role of MMPs seems to be important in the mechanism of carcinogenesis, but it is not well recognized. Rodent studies concentrated particularly on the better understanding of the biological functions of the MMPs and their impact on the pathological process, also through the modification of Mmp genes. This review presents current knowledge and the existing evidence on the importance of selected MMPs in genetic mouse models of cancer and human genetic association studies. Further, this work can be useful for scientists studying the role of the genetic impact of MMPs in carcinogenesis.

Toxicogenetics: in search of host susceptibility to environmental toxicants

Heavy metals, various pesticide and herbicides are implicated as risk factors for human health. Paraquat, maneb, and rotenone, carbamate, and organophosphorous insecticides are examples of toxicants for which acute and chronic exposure are associated with multiple neurological disorders including Parkinson’s disease. Nevertheless, the role of pesticide exposure in neurodegenerative diseases is not clear-cut, as there are inconsistencies in both the epidemiological and preclinical research. The aim of this short review is to show that at least, some of the inconsistencies are related to individual differences in susceptibility to the effects of neurotoxicants, individual differences that can be traced to the genetic constitution of the individuals and animals studies, i.e., host-based susceptibility.

Genetic dissection of susceptibility genes for diabetes and related phenotypes on mouse chromosome 14 by means of congenic strains

Background

A susceptibility locus, Nidd2n, for type 2 diabetes has been mapped to mouse chromosome 14 (Chr 14) and confirmed using the consomic strain (C3H-Chr 14^NSY) of the Nagoya-Shibata-Yasuda (NSY) mouse, an animal model of spontaneous type 2 diabetes. The aim of this study was to localize and characterize Nidd2n.

Results

We constructed two novel congenic strains homozygous for different segments of NSY-Chr 14 on the control C3H/HeNcrj (C3H) background: R1 (C3H.NSY-(D14Mit206-D14Mit5)) possesses the proximal and middle segment, and R2 (C3H.NSY-(D14Mit206-D14Mit186)) possesses the most proximal segment of NSY-Chr 14. Diabetes-related phenotypes were studied in comparison with those of consomic C3H-Chr 14^NSY (R0) and parental NSY and C3H strains. Congenic R1 and R2 showed significantly higher post-challenge glucose than that in C3H mice. Fasting glucose, in contrast, was significantly lower in R1 and R2 than in C3H mice. Insulin sensitivity was significantly impaired in R1 and R2 compared to C3H mice. R2 showed significantly higher body weight and fat-pad weight than those in C3H and R1. Leptin level was significantly higher in R0, R1 and R2 than in C3H mice, with R2 showing the highest level, similar to that in NSY mice. Serum adiponectin level was significantly lower in R0, R1 and R2 than in C3H mice, while it was significantly higher in NSY than in C3H mice.

Conclusions

These data indicate that Chr 14 harbors multiple genes for diabetes-related phenotypes. The original Nidd2n, which is located in the middle region of Chr 14, was divided into two segments; Nidd2.1n in proximal Chr 14 and Nidd2.2n in distal Chr 14. Nidd2.1n contributes to post-challenge hyperglycemia, insulin resistance and adiposity. Nidd2.2n contributes to fasting as well as post-challenge hyperglycemia and insulin resistance. Adp1n, which contributes to decreased adiposity and increased insulin sensitivity, rather than a diabetogenic gene, was mapped in the middle segment.

The perplexing paradox of paraquat: the case for host-based susceptibility and postulated neurodegenerative effects

Paraquat is an herbicide used extensively in agriculture and has also been proposed to be a risk factor for Parkinson's disease. To date, experimental, clinical, and epidemiological data on paraquat neurotoxicity have been equivocal. In this short review, we discuss some technical and biological mechanisms that contribute to inconsistencies regarding paraquat neurotoxicity. We hypothesize that individual genetic variations in susceptibility generate major differences in neurotoxic risk and functional outcome. Identifying these heritable sources of variation in host susceptibility, and their role in complex gene-environment interactions, is crucial to identify risk biomarkers and to devise better prevention and treatment for those exposed to paraquat and other potential neurotoxicants.

Beyond GWASs: illuminating the dark road from association to function

Genome-wide association studies (GWASs) have enabled the discovery of common genetic variation contributing to normal and pathological traits and clinical drug responses, but recognizing the precise targets of these associations is now the major challenge. Here, we review recent approaches to the functional follow-up of GWAS loci, including fine mapping of GWAS signal(s), prioritization of putative functional SNPs by the integration of genetic epidemiological and bioinformatic methods, and in vitro and in vivo experimental verification of predicted molecular mechanisms for identifying the targeted genes. The majority of GWAS-identified variants fall in noncoding regions of the genome. Therefore, this review focuses on strategies for assessing likely mechanisms affected by noncoding variants; such mechanisms include transcriptional regulation, noncoding RNA function, and epigenetic regulation. These approaches have already accelerated progress from genetic studies to biological knowledge and might ultimately guide the development of prognostic, preventive, and therapeutic measures.