Mapping novel QTL and fine mapping of previously identified QTL associated with glucose tolerance using the collaborative cross mice.

A chronic metabolic illness, type 2 diabetes (T2D) is a polygenic and multifactorial complicated disease. With an estimated 463 million persons aged 20 to 79 having diabetes, the number is expected to rise to 700 million by 2045, creating a significant worldwide health burden. Polygenic variants of diabetes are influenced by environmental variables. T2D is regarded as a silent illness that can advance for years before being diagnosed. Finding genetic markers for T2D and metabolic syndrome in groups with similar environmental exposure is therefore essential to understanding the mechanism of such complex characteristic illnesses. So herein, we demonstrated the exclusive use of the collaborative cross (CC) mouse reference population to identify novel quantitative trait loci (QTL) and, subsequently, suggested genes associated with host glucose tolerance in response to a high-fat diet. In this study, we used 539 mice from 60 different CC lines. The diabetogenic effect in response to high-fat dietary challenge was measured by the three-hour intraperitoneal glucose tolerance test (IPGTT) test after 12 weeks of dietary challenge. Data analysis was performed using a statistical software package IBM SPSS Statistic 23. Afterward, blood glucose concentration at the specific and between different time points during the IPGTT assay and the total area under the curve (AUC0-180) of the glucose clearance was computed and utilized as a marker for the presence and severity of diabetes. The observed AUC0-180 averages for males and females were 51,267.5 and 36,537.5 mg/dL, respectively, representing a 1.4-fold difference in favor of females with lower AUC0-180 indicating adequate glucose clearance. The AUC0-180 mean differences between the sexes within each specific CC line varied widely within the CC population. A total of 46 QTL associated with the different studied phenotypes, designated as T2DSL and its number, for Type 2 Diabetes Specific Locus and its number, were identified during our study, among which 19 QTL were not previously mapped. The genomic interval of the remaining 27 QTL previously reported, were fine mapped in our study. The genomic positions of 40 of the mapped QTL overlapped (clustered) on 11 different peaks or close genomic positions, while the remaining 6 QTL were unique. Further, our study showed a complex pattern of haplotype effects of the founders, with the wild-derived strains (mainly PWK) playing a significant role in the increase of AUC values.

Genetic mapping of novel modifiers for ApcMin induced intestinal polyps' development using the genetic architecture power of the collaborative cross mice.

BACKGROUND: Familial adenomatous polyposis is an inherited genetic disease, characterized by colorectal polyps. It is caused by inactivating mutations in the Adenomatous polyposis coli (Apc) gene. Mice carrying a nonsense mutation in the Apc gene at R850, which is designated ApcMin/+ (Multiple intestinal neoplasia), develop intestinal adenomas. Several genetic modifier loci of Min (Mom) were previously mapped, but so far, most of the underlying genes have not been identified. To identify novel modifier loci associated with ApcMin/+, we performed quantitative trait loci (QTL) analysis for polyp development using 49 F1 crosses between different Collaborative Cross (CC) lines and C57BL/6 J-ApcMin/+mice. The CC population is a genetic reference panel of recombinant inbred lines, each line independently descended from eight genetically diverse founder strains. C57BL/6 J-ApcMin/+ males were mated with females from 49 CC lines. F1 offspring were terminated at 23 weeks and polyp counts from three sub-regions (SB1-3) of small intestinal and colon were recorded. RESULTS: The number of polyps in all these sub-regions and colon varied significantly between the different CC lines. At 95% genome-wide significance, we mapped nine novel QTL for variation in polyp number, with distinct QTL associated with each intestinal sub-region. QTL confidence intervals varied in width between 2.63-17.79 Mb. We extracted all genes in the mapped QTL at 90 and 95% CI levels using the BioInfoMiner online platform to extract, significantly enriched pathways and key linker genes, that act as regulatory and orchestrators of the phenotypic landscape associated with the ApcMin/+ mutation. CONCLUSIONS: Genomic structure of the CC lines has allowed us to identify novel modifiers and confirmed some of the previously mapped modifiers. Key genes involved mainly in metabolic and immunological processes were identified. Future steps in this analysis will be to identify regulatory elements - and possible epistatic effects - located in the mapped QTL.

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.

Glucose tolerance female-specific QTL mapped in collaborative cross mice.

Type-2 diabetes (T2D) is a complex metabolic disease characterized by impaired glucose tolerance. Despite environmental high risk factors, host genetic background is a strong component of T2D development. Herein, novel highly genetically diverse strains of collaborative cross (CC) lines from mice were assessed to map quantitative trait loci (QTL) associated with variations of glucose-tolerance response. In total, 501 mice of 58 CC lines were maintained on high-fat (42 % fat) diet for 12 weeks. Thereafter, an intraperitoneal glucose tolerance test (IPGTT) was performed for 180 min. Subsequently, the values of Area under curve for the glucose at zero and 180 min (AUC0-180), were measured, and used for QTL mapping. Heritability and coefficient of variations in glucose tolerance (CVg) were calculated. One-way analysis of variation was significant (P < 0.001) for AUC0-180 between the CC lines as well between both sexes. Despite Significant variations for both sexes, QTL analysis was significant, only for females, reporting a significant female-sex-dependent QTL (~2.5 Mbp) associated with IPGTT AUC0-180 trait, located on Chromosome 8 (32-34.5 Mbp, containing 51 genes). Gene browse revealed QTL for body weight/size, genes involved in immune system, and two main protein-coding genes involved in the Glucose homeostasis, Mboat4 and Leprotl1. Heritability and coefficient of genetic variance (CVg) were 0.49 and 0.31 for females, while for males, these values 0.34 and 0.22, respectively. Our findings demonstrate the roles of genetic factors controlling glucose tolerance, which significantly differ between sexes requiring independent studies for females and males toward T2D prevention and therapy.

Studying host genetic background effects on multimorbidity of intestinal cancer development, type 2 diabetes and obesity in response to oral bacterial infection and high-fat diet using the collaborative cross (CC) lines.

Background: Multimorbidity of intestinal cancer (IC), type 2 diabetes (T2D) and obesity is a complex set of diseases, affected by environmental and genetic risk factors. High-fat diet (HFD) and oral bacterial infection play important roles in the etiology of these diseases through inflammation and various biological mechanisms. Methods: To study the complexity of this multimorbidity, we used the collaborative cross (CC) mouse genetics reference population. We aimed to study the multimorbidity of IC, T2D, and obesity using CC lines, measuring their responses to HFD and oral bacterial infection. The study used 63 mice of both sexes generated from two CC lines (IL557 and IL711). For 12 weeks, experimental mice were maintained on specific dietary regimes combined with co-infection with oral bacteria Porphyromonas gingivalis and Fusobacterium nucleatum, while control groups were not infected. Body weight (BW) and results of a intraperitoneal glucose tolerance test (IPGTT) were recorded at the end of 12 weeks, after which length and size of the intestines were assessed for polyp counts. Results: Polyp counts ranged between 2 and 10 per CC line. The combination of HFD and infection significantly reduced (P < .01) the colon polyp size of IL557 females to 2.5 cm2, compared to the other groups. Comparing BW gain, IL557 males on HFD gained 18 g, while the females gained 10 g under the same conditions and showed the highest area under curve (AUC) values of 40 000-45 000 (min mg/dL) in the IPGTT. Conclusion: The results show that mice from different genetic backgrounds respond differently to a high fat diet and oral infection in terms of polyp development and glucose tolerance, and this effect is gender related.

Assessing the host genetic background effects on type 2 diabetes and obesity development in response to mixed-oral bacteria and high-fat diet using the collaborative cross mouse model.

BACKGROUND: Host genetic background and sex, play central roles in defining the pathogenesis of type 2 diabetes (T2D), obesity and infectious diseases. Our previous studies demonstrated the utilization of genetically highly diverse inbred mouse lines, namely collaborative cross (CC), for dissecting host susceptibility for the development of T2D and obesity, showing significant variations following high-fat (42% fat) diet (HFD). Here, we aimed to assessing the host genetic background and sex effects on T2D and obesity development in response to oral-mixed bacterial infection and HFD using the CC lines. MATERIALS AND METHODS: Study cohort consists of 97 mice from 2 CC lines (both sexes), maintained on either HFD or Standard diet (CHD) for 12 weeks. At week 5 a group of mice from each diet were infected with Porphyromonas gingivalis (Pg) and Fusobacterium nucleatum (Fn) bacteria (control groups without infection). Body weight (BW) and glucose tolerance ability were assessed at the end time point of the experiment. RESULTS: The CC lines varied (P < .05) at their BW gain and glucose tolerance ability (with sex effect) in response to diets and/or infection, showing opposite responses despite sharing the same environmental conditions. The combination of diet and infection enhances BW accumulation for IL1912, while restraints it for IL72. As for glucose tolerance ability, only females (both lines) were deteriorated in response to infection. CONCLUSIONS: This study emphasizes the power of the CC mouse population for the characterization of host genetic makeup for defining the susceptibility of the individual to development of obesity and/or impaired glucose tolerance.

Efficient protocols and methods for high-throughput utilization of the Collaborative Cross mouse model for dissecting the genetic basis of complex traits.

The Collaborative Cross (CC) mouse model is a next-generation mouse genetic reference population (GRP) designated for a high-resolution quantitative trait loci (QTL) mapping of complex traits during health and disease. The CC lines were generated from reciprocal crosses of eight divergent mouse founder strains composed of five classical and three wild-derived strains. Complex traits are defined to be controlled by variations within multiple genes and the gene/environment interactions. In this article, we introduce and present variety of protocols and results of studying the host response to infectious and chronic diseases, including type 2 diabetes and metabolic diseases, body composition, immune response, colorectal cancer, susceptibility to Aspergillus fumigatus, Klebsiella pneumoniae, Pseudomonas aeruginosa, sepsis, and mixed infections of Porphyromonas gingivalis and Fusobacterium nucleatum, which were conducted at our laboratory using the CC mouse population. These traits are observed at multiple levels of the body systems, including metabolism, body weight, immune profile, susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present full protocols and step-by-step methods, implemented in our laboratory for the phenotypic and genotypic characterization of the different CC lines, mapping the gene underlying the host response to these infections and chronic diseases. The CC mouse model is a unique and powerful GRP for dissecting the host genetic architectures underlying complex traits, including chronic and infectious diseases.

Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population.

The Collaborative Cross (CC) mouse resource is a next-generation mouse genetic reference population (GRP) designed for high-resolution mapping of quantitative trait loci (QTL) of large effect affecting complex traits during health and disease. The CC resource consists of a set of 72 recombinant inbred lines (RILs) generated by reciprocal crossing of five classical and three wild-derived mouse founder strains. Complex traits are controlled by variations within multiple genes and environmental factors, and their mutual interactions. These traits are observed at multiple levels of the animals' systems, including metabolism, body weight, immune profile, and susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present general guidelines for design of QTL mapping experiments using the CC resource-along with full step-by-step protocols and methods that were implemented in our lab for the phenotypic and genotypic characterization of the different CC lines-for mapping the genes underlying host response to infectious and chronic diseases. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: CC lines for whole body mass index (BMI) Basic Protocol 2: A detailed assessment of the power to detect effect sizes based on the number of lines used, and the number of replicates per line Basic Protocol 3: Obtaining power for QTL with given target effect by interpolating in Table 1 of Keele et al. (2019).

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.

Modeling the quantitative nature of neurodevelopmental disorders using Collaborative Cross mice.

Background: Animal models for neurodevelopmental disorders (NDD) generally rely on a single genetic mutation on a fixed genetic background. Recent human genetic studies however indicate that a clinical diagnosis with ASDAutism Spectrum Disorder (ASD) is almost always associated with multiple genetic fore- and background changes. The translational value of animal model studies would be greatly enhanced if genetic insults could be studied in a more quantitative framework across genetic backgrounds. Methods: We used the Collaborative Cross (CC), a novel mouse genetic reference population, to investigate the quantitative genetic architecture of mouse behavioral phenotypes commonly used in animal models for NDD. Results: Classical tests of social recognition and grooming phenotypes appeared insufficient for quantitative studies due to genetic dilution and limited heritability. In contrast, digging, locomotor activity, and stereotyped exploratory patterns were characterized by continuous distribution across our CC sample and also mapped to quantitative trait loci containing genes associated with corresponding phenotypes in human populations. Conclusions: These findings show that the CC can move animal model studies beyond comparative single gene-single background designs, and point out which type of behavioral phenotypes are most suitable to quantify the effect of developmental etiologies across multiple genetic backgrounds.

Collaborative Cross Mouse Population for Studying Alveolar Bone Changes and Impaired Glucose Tolerance Comorbidity After High-Fat Diet Consumption.

BACKGROUND: High-fat diet (HFD), body weight (BW) gain, and impaired glucose tolerance development are associated with alveolar bone loss (ABL) in susceptible individuals. This report explores the Collaborative Cross (CC) mouse population for studying the impact of genetic background on comorbidity of alveolar bone change and glucose tolerance after HFD consumption. METHODS: Seventy-eight mice from 19 different CC lines were maintained on rodent chow diet for 8 weeks and were subsequently transferred to an HFD (42% fat) for an additional 12 weeks. BW changes were assessed, and glucose tolerance was measured using an intraperitoneal glucose tolerance test (IPGTT). Six cytokines/chemokines were quantified by multiplex immunoassay, alveolar bone volume was quantified by microcomputed tomography, and the ABL phenotype was calculated relative to a control group (143 mice maintained on standard chow diet for 20 weeks). RESULTS: The glucose tolerance response after HFD significantly varied among CC lines (P <0.01), with a significant effect of sex (P <0.01). Alveolar bone changes significantly varied among CC lines (P <0.01). Overall, there was no significant correlation between alveolar bone volume changes and increased BW or glucose tolerance response. However, individual CC lines were identified that showed type 2 diabetes mellitus (t2DM) development and significant alveolar bone volume change (P <0.05), whereas others showed t2DM development, regardless of periodontitis. Interleukin-6 significantly correlated with alveolar bone changes (P <0.05), whereas adipsin showed a negative correlation with IPGTT area under the curve values (P <0.05). CONCLUSION: The present results demonstrate the power of CC mice for studying the genetic background impact between comorbidity of t2DM and bone loss.

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.