Genetic analysis of albuminuria in collaborative cross and multiple mouse intercross populations

Utilizing preclinical models of genetic diversity to improve translation of phytochemical activities from rodents to humans and inform personalized nutrition

Mouse models are an essential tool in different areas of research, including nutrition and phytochemical research. Traditional inbred mouse models have allowed the discovery of therapeutical targets and mechanisms of action and expanded our knowledge of health and disease. However, these models lack the genetic variability typically found in human populations, which hinders the translatability of the results found in mice to humans. The development of genetically diverse mouse models, such as the collaborative cross (CC) or the diversity outbred (DO) models, has been a useful tool to overcome this obstacle in many fields, such as cancer, immunology and toxicology. However, these tools have not yet been widely adopted in the field of phytochemical research. As demonstrated in other disciplines, use of CC and DO models has the potential to provide invaluable insights for translation of phytochemicals from rodents to humans, which are desperately needed given the challenges and numerous failed clinical trials in this field. These models may prove informative for personalized use of phytochemicals in humans, including: predicting interindividual variability in phytochemical bioavailability and efficacy, identifying genetic loci or genes governing response to phytochemicals, identifying phytochemical mechanisms of action and therapeutic targets, and understanding the impact of genetic variability on individual response to phytochemicals. Such insights would prove invaluable for personalized implementation of phytochemicals in humans. This review will focus on the current work performed with genetically diverse mouse populations, and the research opportunities and advantages that these models can offer to phytochemical research.

Indirect podocyte injury manifested in a partial podocytectomy mouse model

In progressive glomerular diseases, segmental podocyte injury often expands, leading to global glomerulosclerosis by unclear mechanisms. To study the expansion of podocyte injury, we established a new mosaic mouse model in which a fraction of podocytes express human (h)CD25 and can be injured by the immunotoxin LMB2. hCD25⁺ and hCD25^- podocytes were designed to express tdTomato and enhanced green fluorescent protein (EGFP), respectively, which enabled cell sorting analysis of podocytes. After the injection of LMB2, mosaic mice developed proteinuria and glomerulosclerosis. Not only tdTomato⁺ podocytes but also EGFP⁺ podocytes were decreased in number and showed damage, as evidenced by a decrease in nephrin and an increase in desmin at both protein and RNA levels. Transcriptomics analysis found a decrease in the glucocorticoid-induced transcript 1 gene and an increase in the thrombospondin 4, heparin-binding EGF-like growth factor, and transforming growth factor-β genes in EGFP⁺ podocytes; these genes may be candidate mediators of secondary podocyte damage. Pathway analysis suggested that focal adhesion, integrin-mediated cell adhesion, and focal adhesion-phosphatidylinositol 3-kinase-Akt-mammalian target of rapamycin signaling are involved in secondary podocyte injury. Finally, treatment of mosaic mice with angiotensin II receptor blocker markedly ameliorated secondary podocyte injury. This mosaic podocyte injury model has distinctly demonstrated that damaged podocytes cause secondary podocyte damage, which may be a promising therapeutic target in progressive kidney diseases.NEW & NOTEWORTHY This novel mosaic model has demonstrated that when a fraction of podocytes is injured, other podocytes are subjected to secondary injury. This spreading of injury may occur ubiquitously irrespective of the primary cause of podocyte injury, leading to end-stage renal failure. Understanding the molecular mechanism of secondary podocyte injury and its prevention is important for the treatment of progressive kidney diseases. This model will be a powerful tool for studying the indirect podocyte injury.

Genetic basis of voluntary water consumption in two divergently selected strains of inbred mice

Background

Inbred mouse strains with normal renal function show a substantial difference in daily water consumption across strains. This study uses two strains of inbred mice C57BR/CDJ (BR), which are high consumers, and C57BL/10J (BL), which are low consumers, their reciprocal F₁ crosses, inter se bred F₂s and backcrosses produced by breeding high consuming F₂ animals to the low consumer parent strain and low consuming F₂ animals to the high consuming parent strain. Consumption was corrected for body weight prior to analysis.

Methods

The effective number of genes controlling water consumption was estimated using the Castle–Wright estimator. Additive and dominance genotypic values as well as the degree of dominance were calculated using estimated strain means.

Results

According to Castle–Wright, a minimum of 10 factors were estimated to affect the difference in consumption across the two strains. Between seven and eight are expected to be high effect factors. Using the Zeng adjustment, it was determined that 30–40 factors potentially affect the difference in consumption.

Conclusions

These numbers were surprising but may be related to several sources of variation present in the BR strain. A negative degree of dominance indicated the BL strain has more dominant factors.

High-Diversity Mouse Populations for Complex Traits

Contemporary mouse genetic reference populations are a powerful platform to discover complex disease mechanisms. Advanced high-diversity mouse populations include the Collaborative Cross (CC) strains, Diversity Outbred (DO) stock, and their isogenic founder strains. When used in systems genetics and integrative genomics analyses, these populations efficiently harnesses known genetic variation for precise and contextualized identification of complex disease mechanisms. Extensive genetic, genomic, and phenotypic data are already available for these high-diversity mouse populations and a growing suite of data analysis tools have been developed to support research on diverse mice. This integrated resource can be used to discover and evaluate disease mechanisms relevant across species.

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.

Genetic, maternal, and heterosis effects on voluntary water consumption in mice

In standard laboratory conditions, inbred mouse strains with normal kidney function show a 4-fold range of daily water consumption. This study uses two strains of inbred mice identified as high and low consumers, their reciprocal F1 crosses, and inter se bred F2s. Daily consumption data were collected on 607 animals for 4 d during the 4th, 5th, and 6th wk using custom water bottles. Animals were weighed at the beginning of the 4th, 5th, 6th, and 7th wk. Consumption data were corrected for metabolic BW (Bwt0.67) prior to analysis, so units of water consumption are expressed in mL consumed per gram of Bwt0.67 per day. Variables BW and water consumption were fitted to a mixed model including the effects of sex, strain, and their interaction with sire within strain fitted as a random effect. Contrasts were designed to test the direct genetic, maternal genetic, individual heterosis, and maternal heterosis effects. An interaction (P < 0.0001) was observed between sex and strain so all analyses were conducted separately for each sex. C57Brown/CDJ animals (Brown) consumed more water than C57Black/10J animals (Black) (P < 0.0001). A maternal effect (P = 0.036, P = 0.029) was observed in males at the 4th and 5th wk as F1 animals with a Black dam (F1Black) consumed less than F1 animals with a Brown dam (F1Brown) males. No significant heterosis effect was observed for water consumption. For weight analysis, Black animals were significantly larger than Brown animals at 28 d (males P = 0.004, females P = 0.026), but no difference was observed the remainder of the trial. Further, F1Brown females were significantly smaller than F1Black females at 28 d (P < 0.0001) and F1Brown males tended to be smaller than F1Black males (P = 0.078). Animals from the reciprocal F1 crosses showed an increase in birth weight (P < 0.0001) over pure strains. These strains form the foundation stock of an experiment designed to isolate genes influencing water consumption by reciprocal backcrossing and selection.

Dissecting the Effect of Genetic Variation on the Hepatic Expression of Drug Disposition Genes across the Collaborative Cross Mouse Strains

A central challenge in pharmaceutical research is to investigate genetic variation in response to drugs. The Collaborative Cross (CC) mouse reference population is a promising model for pharmacogenomic studies because of its large amount of genetic variation, genetic reproducibility, and dense recombination sites. While the CC lines are phenotypically diverse, their genetic diversity in drug disposition processes, such as detoxification reactions, is still largely uncharacterized. Here we systematically measured RNA-sequencing expression profiles from livers of 29 CC lines under baseline conditions. We then leveraged a reference collection of metabolic biotransformation pathways to map potential relations between drugs and their underlying expression quantitative trait loci (eQTLs). By applying this approach on proximal eQTLs, including eQTLs acting on the overall expression of genes and on the expression of particular transcript isoforms, we were able to construct the organization of hepatic eQTL-drug connectivity across the CC population. The analysis revealed a substantial impact of genetic variation acting on drug biotransformation, allowed mapping of potential joint genetic effects in the context of individual drugs, and demonstrated crosstalk between drug metabolism and lipid metabolism. Our findings provide a resource for investigating drug disposition in the CC strains, and offer a new paradigm for integrating biotransformation reactions to corresponding variations in DNA sequences.

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.

Contrasting genetic architectures in different mouse reference populations used for studying complex traits

Quantitative trait loci (QTLs) are being used to study genetic networks, protein functions, and systems properties that underlie phenotypic variation and disease risk in humans, model organisms, agricultural species, and natural populations. The challenges are many, beginning with the seemingly simple tasks of mapping QTLs and identifying their underlying genetic determinants. Various specialized resources have been developed to study complex traits in many model organisms. In the mouse, remarkably different pictures of genetic architectures are emerging. Chromosome Substitution Strains (CSSs) reveal many QTLs, large phenotypic effects, pervasive epistasis, and readily identified genetic variants. In contrast, other resources as well as genome-wide association studies (GWAS) in humans and other species reveal genetic architectures dominated with a relatively modest number of QTLs that have small individual and combined phenotypic effects. These contrasting architectures are the result of intrinsic differences in the study designs underlying different resources. The CSSs examine context-dependent phenotypic effects independently among individual genotypes, whereas with GWAS and other mouse resources, the average effect of each QTL is assessed among many individuals with heterogeneous genetic backgrounds. We argue that variation of genetic architectures among individuals is as important as population averages. Each of these important resources has particular merits and specific applications for these individual and population perspectives. Collectively, these resources together with high-throughput genotyping, sequencing and genetic engineering technologies, and information repositories highlight the power of the mouse for genetic, functional, and systems studies of complex traits and disease models.

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.

Genetic determinants of atherosclerosis, obesity, and energy balance in consomic mice

Metabolic diseases such as obesity and atherosclerosis result from complex interactions between environmental factors and genetic variants. A panel of chromosome substitution strains (CSSs) was developed to characterize genetic and dietary factors contributing to metabolic diseases and other biological traits and biomedical conditions. Our goal here was to identify quantitative trait loci (QTLs) contributing to obesity, energy expenditure, and atherosclerosis. Parental strains C57BL/6 and A/J together with a panel of 21 CSSs derived from these progenitors were subjected to chronic feeding of rodent chow and atherosclerotic (females) or diabetogenic (males) test diets, and evaluated for a variety of metabolic phenotypes including several traits unique to this report, namely fat pad weights, energy balance, and atherosclerosis. A total of 297 QTLs across 35 traits were discovered, two of which provided significant protection from atherosclerosis, and several dozen QTLs modulated body weight, body composition, and circulating lipid levels in females and males. While several QTLs confirmed previous reports, most QTLs were novel. Finally, we applied the CSS quantitative genetic approach to energy balance, and identified three novel QTLs controlling energy expenditure and one QTL modulating food intake. Overall, we identified many new QTLs and phenotyped several novel traits in this mouse model of diet-induced metabolic diseases.

Fine-mapping QTLs in advanced intercross lines and other outbred populations

Quantitative genetic studies in model organisms, particularly in mice, have been extremely successful in identifying chromosomal regions that are associated with a wide variety of behavioral and other traits. However, it is now widely understood that identification of the underlying genes will be far more challenging. In the last few years, a variety of populations have been utilized in an effort to more finely map these chromosomal regions with the goal of identifying specific genes. The common property of these newer populations is that linkage disequilibrium spans relatively short distances, which permits fine-scale mapping resolution. This review focuses on advanced intercross lines (AILs) which are the simplest such population. As originally proposed in 1995 by Darvasi and Soller, an AIL is the product of intercrossing two inbred strains beyond the F2 generation. Unlike recombinant inbred strains, AILs are maintained as outbred populations; brother-sister matings are specifically avoided. Each generation of intercrossing beyond the F2 further degrades linkage disequilibrium between adjacent makers, which allows for fine-scale mapping of quantitative trait loci (QTLs). Advances in genotyping technology and techniques for the statistical analysis of AILs have permitted rapid advances in the application of AILs. We review some of the analytical issues and available software, including QTLRel, EMMA, EMMAX, GEMMA, TASSEL, GRAMMAR, WOMBAT, Mendel, and others.

QTL mapping in outbred populations: successes and challenges

Quantitative trait locus (QTL) mapping in animal populations has been a successful strategy for identifying genomic regions that play a role in complex diseases and traits. When conducted in an F2 intercross or backcross population, the resulting QTL is frequently large, often encompassing 30 Mb or more and containing hundreds of genes. To narrow the locus and identify candidate genes, additional strategies are needed. Congenic strains have proven useful but work less well when there are multiple tightly linked loci, frequently resulting in loss of phenotype. As an alternative, we discuss the use of highly recombinant outbred models for directly fine-mapping QTL to only a few megabases. We discuss the use of several currently available models such as the advanced intercross (AI), heterogeneous stocks (HS), the diversity outbred (DO), and commercially available outbred stocks (CO). Once a QTL has been fine-mapped, founder sequence and expression QTL mapping can be used to identify candidate genes. In this regard, the large number of alleles found in outbred stocks can be leveraged to identify causative genes and variants. We end this review by discussing some important statistical considerations when analyzing outbred populations. Fine-resolution mapping in outbred models, coupled with full genome sequence, has already led to the identification of several underlying causative genes for many complex traits and diseases. These resources will likely lead to additional successes in the coming years.

Out of the bottleneck: the Diversity Outcross and Collaborative Cross mouse populations in behavioral genetics research

The historical origins of classical laboratory mouse strains have led to a relatively limited range of genetic and phenotypic variation, particularly for the study of behavior. Many recent efforts have resulted in improved diversity and precision of mouse genetic resources for behavioral research, including the Collaborative Cross and Diversity Outcross population. These two populations, derived from an eight way cross of common and wild-derived strains, have high precision and allelic diversity. Behavioral variation in the population is expanded, both qualitatively and quantitatively. Variation that had once been canalized among the various inbred lines has been made amenable to genetic dissection. The genetic attributes of these complementary populations, along with advances in genetic and genomic technologies, makes a systems genetic analyses of behavior more readily tractable, enabling discovery of a greater range of neurobiological phenomena underlying behavioral variation.

Mouse phenome database

The Mouse Phenome Database (MPD; phenome.jax.org) was launched in 2001 as the data coordination center for the international Mouse Phenome Project. MPD integrates quantitative phenotype, gene expression and genotype data into a common annotated framework to facilitate query and analysis. MPD contains >3500 phenotype measurements or traits relevant to human health, including cancer, aging, cardiovascular disorders, obesity, infectious disease susceptibility, blood disorders, neurosensory disorders, drug addiction and toxicity. Since our 2012 NAR report, we have added >70 new data sets, including data from Collaborative Cross lines and Diversity Outbred mice. During this time we have completely revamped our homepage, improved search and navigational aspects of the MPD application, developed several web-enabled data analysis and visualization tools, annotated phenotype data to public ontologies, developed an ontology browser and released new single nucleotide polymorphism query functionality with much higher density coverage than before. Here, we summarize recent data acquisitions and describe our latest improvements.