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.

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.

The Collaborative Cross-Mouse Population for Studying Genetic Determinants Underlying Alveolar Bone Loss Due to Polymicrobial Synergy and Dysbiosis

Dysbiosis of oral microbiota is associated with the initiation and progression of periodontitis. The cause-and-effect relationship between genetics, periodontitis, and oral microbiome dysbiosis is poorly understood. Here, we demonstrate the power of the collaborative cross (CC) mice model to assess the effect of the genetic background on microbiome diversity shifts during periodontal infection and host suitability status. We examined the bacterial composition in plaque samples from seven different CC lines using 16s rRNA sequencing before and during periodontal infection. The susceptibility/resistance of the CC lines to alveolar bone loss was determined using the micro-CT technique. A total of 53 samples (7 lines) were collected before and after oral infection using oral swaps followed by DNA extraction and 16 s rRNA sequencing analysis. CC lines showed a significant variation in response to the co-infection (p < 0.05). Microbiome compositions were significantly different before and after infection and between resistant and susceptible lines to periodontitis (p < 0.05). Gram-positive taxa were significantly higher at the resistant lines compared to susceptible lines (p < 0.05). Gram-positive bacteria were reduced after infection, and gram-negative bacteria, specifically anaerobic groups, increased after infection. Our results demonstrate the utility of the CC mice in exploring the interrelationship between genetic background, microbiome composition, and periodontitis.

Towards system genetics analysis of head and neck squamous cell carcinoma using the mouse model, cellular platform, and clinical human data

Head and neck squamous cell cancer (HNSCC) is a leading global malignancy. Every year, More than 830 000 people are diagnosed with HNSCC globally, with more than 430 000 fatalities. HNSCC is a deadly diverse malignancy with many tumor locations and biological characteristics. It originates from the squamous epithelium of the oral cavity, oropharynx, nasopharynx, larynx, and hypopharynx. The most frequently impacted regions are the tongue and larynx. Previous investigations have demonstrated the critical role of host genetic susceptibility in the progression of HNSCC. Despite the advances in our knowledge, the improved survival rate of HNSCC patients over the last 40 years has been limited. Failure to identify the molecular origins of development of HNSCC and the genetic basis of the disease and its biological heterogeneity impedes the development of new therapeutic methods. These results indicate a need to identify more genetic factors underlying this complex disease, which can be better used in early detection and prevention strategies. The lack of reliable animal models to investigate the underlying molecular processes is one of the most significant barriers to understanding HNSCC tumors. In this report, we explore and discuss potential research prospects utilizing the Collaborative Cross mouse model and crossing it to mice carrying single or double knockout genes (e.g. Smad4 and P53 genes) to identify genetic factors affecting the development of this complex disease using genome-wide association studies, epigenetics, microRNA, long noncoding RNA, lncRNA, histone modifications, methylation, phosphorylation, and proteomics.

Anterior Open Bite Malocclusion: From Clinical Treatment Strategies towards the Dissection of the Genetic Bases of the Disease Using Human and Collaborative Cross Mice Cohorts

Anterior open bite malocclusion is a complex dental condition characterized by a lack of contact or overlap between the upper and lower front teeth. It can lead to difficulties with speech, chewing, and biting. Its etiology is multifactorial, involving a combination of genetic, environmental, and developmental factors. Genetic studies have identified specific genes and signaling pathways involved in jaw growth, tooth eruption, and dental occlusion that may contribute to open bite development. Understanding the genetic and epigenetic factors contributing to skeletal open bite is crucial for developing effective prevention and treatment strategies. A thorough manual search was undertaken along with searches on PubMed, Scopus, Science Direct, and Web of Science for relevant studies published before June 2022. RCTs (clinical trials) and subsequent observational studies comprised the included studies. Orthodontic treatment is the primary approach for managing open bites, often involving braces, clear aligners, or other orthodontic appliances. In addition to orthodontic interventions, adjuvant therapies such as speech therapy and/or physiotherapy may be necessary. In some cases, surgical interventions may be necessary to correct underlying skeletal issues. Advancements in technology, such as 3D printing and computer-assisted design and manufacturing, have improved treatment precision and efficiency. Genetic research using animal models, such as the Collaborative Cross mouse population, offers insights into the genetic components of open bite and potential therapeutic targets. Identifying the underlying genetic factors and understanding their mechanisms can lead to the development of more precise treatments and preventive strategies for open bite. Here, we propose to perform human research using mouse models to generate debatable results. We anticipate that a genome-wide association study (GWAS) search for significant genes and their modifiers, an epigenetics-wide association study (EWAS), RNA-seq analysis, the integration of GWAS and expression-quantitative trait loci (eQTL), and micro-, small-, and long noncoding RNA analysis in tissues associated with open bite in humans and mice will uncover novel genes and genetic factors influencing this phenotype.

Host Genetic Background Effect on Body Weight Changes Influenced by Heterozygous Smad4 Knockout Using Collaborative Cross Mouse Population

Obesity and its attendant conditions have become major health problems worldwide, and obesity is currently ranked as the fifth most common cause of death globally. Complex environmental and genetic factors are causes of the current obesity epidemic. Diet, lifestyle, chemical exposure, and other confounding factors are difficult to manage in humans. The mice model is helpful in researching genetic BW gain because genetic and environmental risk factors can be controlled in mice. Studies in mouse strains with various genetic backgrounds and established genetic structures provide unparalleled opportunities to find and analyze trait-related genomic loci. In this study, we used the Collaborative Cross (CC), a large panel of recombinant inbred mouse strains, to present a predictive study using heterozygous Smad4 knockout profiles of CC mice to understand and effectively identify predispositions to body weight gain. Male C57Bl/6J Smad4+/- mice were mated with female mice from 10 different CC lines to create F1 mice (Smad4+/-x CC). Body weight (BW) was measured weekly until week 16 and then monthly until the end of the study (week 48). The heritability (H2) of the assessed traits was estimated and presented. Comparative analysis of various machine learning algorithms for predicting the BW changes and genotype of mice was conducted. Our data showed that the body weight records of F1 mice with different CC lines differed between wild-type and mutant Smad4 mice during the experiment. Genetic background affects weight gain and some lines gained more weight in the presence of heterozygous Smad4 knockout, while others gained less, but, in general, the mutation caused overweight mice, except for a few lines. In both control and mutant groups, female %BW had a higher heritability (H2) value than males. Additionally, both sexes with wild-type genotypes showed higher heritability values than the mutant group. Logistic regression provides the most accurate mouse genotype predictions using machine learning. We plan to validate the proposed method on more CC lines and mice per line to expand the literature on machine learning for BW prediction.

Comprehensive Deciphering the Complexity of the Deep Bite: Insight from Animal Model to Human Subjects

Deep bite is a malocclusion phenotype, defined as the misalignment in the vertical dimension of teeth and jaws and characterized by excessive overlap of the upper front teeth over the lower front teeth. Numerous factors, including genetics, environmental factors, and behavioral ones, might contribute to deep bite. In this study, we discuss the current clinical treatment strategies for deep bite, summarize the already published findings of genetic analysis associated with this complex phenotype, and their constraints. Finally, we propose a comprehensive roadmap to facilitate investigations for determining the genetic bases of this complex phenotype development. Initially, human deep bite phenotype, genetics of human deep bite, the prevalence of human deep bite, diagnosis, and treatment of human deep bite were the search terms for published publications. Here, we discuss these findings and their limitations and our view on future strategies for studying the genetic bases of this complex phenotype. New preventative and treatment methods for this widespread dental issue can be developed with the help of an understanding of the genetic and epigenetic variables that influence malocclusion. Additionally, malocclusion treatment may benefit from technological developments like 3D printing and computer-aided design and manufacture (CAD/CAM). These technologies enable the development of personalized surgical and orthodontic guidelines, enhancing the accuracy and effectiveness of treatment. Overall, the most significant results for the patient can only be achieved with a customized treatment plan created by an experienced orthodontic professional. To design a plan that meets the patient's specific requirements and expectations, open communication between the patient and the orthodontist is essential. Here, we propose to conduct a genome-wide association study (GWAS), RNAseq analysis, integrating GWAS and expression quantitative trait loci (eQTL), micro and small RNA, and long noncoding RNA analysis in tissues associated with deep bite malocclusion in human, and complement it by the same approaches in the collaborative cross (CC) mouse model which offer a novel platform for identifying genetic factors as a cause of deep bite in mice, and subsequently can then be translated to humans. An additional direct outcome of this study is discovering novel genetic elements to advance our knowledge of how this malocclusion phenotype develops and open the venue for early identification of patients carrying the susceptible genetic factors so that we can offer early prevention and treatment strategies, a step towards applying a personalized medicine approach.

Narrating the Genetic Landscape of Human Class I Occlusion: A Perspective-Infused Review

This review examines a prevalent condition with multifaceted etiology encompassing genetic, environmental, and oral behavioral factors. It stands as a significant ailment impacting oral functionality, aesthetics, and quality of life. Longitudinal studies indicate that malocclusion in primary dentition may progress to permanent malocclusion. Recognizing and managing malocclusion in primary dentition is gaining prominence. The World Health Organization ranks malocclusions as the third most widespread oral health issue globally. Angle's classification system is widely used to categorize malocclusions, with Class I occlusion considered the norm. However, its prevalence varies across populations due to genetic and examination disparities. Genetic factors, including variants in genes like MSX1, PAX9, and AXIN2, have been associated with an increased risk of Class I occlusion. This review aims to provide a comprehensive overview of clinical strategies for managing Class I occlusion and consolidate genetic insights from both human and murine populations. Additionally, genomic relationships among craniofacial genes will be assessed in individuals with Class I occlusion, along with a murine model, shedding light on phenotype-genotype associations of clinical relevance. The prevalence of Class I occlusion, its impact, and treatment approaches will be discussed, emphasizing the importance of early intervention. Additionally, the role of RNA alterations in skeletal Class I occlusion will be explored, focusing on variations in expression or structure that influence craniofacial development. Mouse models will be highlighted as crucial tools for investigating mandible size and prognathism and conducting QTL analysis to gain deeper genetic insights. This review amalgamates cellular, molecular, and clinical trait data to unravel correlations between malocclusion and Class I phenotypes.

Skeletal Class II Malocclusion: From Clinical Treatment Strategies to the Roadmap in Identifying the Genetic Bases of Development in Humans with the Support of the Collaborative Cross Mouse Population

Depending on how severe it is, malocclusion, which may involve misaligned teeth, jaws, or a combination of the two, can hurt a person's overall facial aesthetics. The maxillary molar develops before the mandibular molar in class II malocclusion, which affects 15% of the population in the United States. With a retrusive mandible, patients typically have a convex profile. The goal of this study is to classify the skeletal and dental variability present in class II malocclusion, to reduce heterogeneity, present the current clinical treatment strategies, to summarize the previously published findings of genetic analysis, discuss these findings and their constraints, and finally, propose a comprehensive roadmap to facilitate investigations aimed at determining the genetic bases of malocclusion development using a variety of genomic approaches. To further comprehend the hereditary components involved in the onset and progression of class II malocclusion, a novel animal model for class II malocclusion should be developed while considering the variety of the human population. To overcome the constraints of the previous studies, here, we propose to conduct novel research on humans with the support of mouse models to produce contentious findings. We believe that carrying out a genome-wide association study (GWAS) on a large human cohort to search for significant genes and their modifiers; an epigenetics-wide association study (EWAS); RNA-seq analysis; integrating GWAS and the expression of quantitative trait loci (eQTL); and the testing of microRNAs, small RNAs, and long noncoding RNAs in tissues related to the skeletal class II malocclusion (SCIIMO) phenotype, such as mandibular bone, gum, and jaw in humans and the collaborative cross (CC) mouse model, will identify novel genes and genetic factors affecting this phenotype. We anticipate discovering novel genetic elements to advance our knowledge of how this malocclusion phenotype develops and open the venue for the early identification of patients carrying the susceptible genetic factors so that we can offer early prevention treatment strategies.

A study of the influence of genetic variance and sex on the density and thickness of the calvarial bone in collaborative cross mice

BACKGROUND

Bone microarchitecture is affected by multiple genes, each having a small effect on the external appearance. It is thus challenging to characterize the genes and their specific effect on bone thickness and porosity. The purpose of this study was to assess the heritability and the genetic variation effect, as well as the sex effect on the calvarial bone thickness (Ca.Th) and calvarial porosity (%PoV) using the Collaborative Cross (CC) mouse population.

METHODS

In the study we examined the parietal bones of 56 mice from 9 lines of CC mice. Morphometric parameters were evaluated using microcomputed tomography (μCT) and included Ca.Th and %PoV. We then evaluated heritability, genetic versus environmental variance and the sex effect for these parameters.

RESULTS

Our morphometric analysis showed that Ca.Th and %PoV are both significantly different among the CC lines with a broad sense heritability of 0.78 and 0.90, respectively. The sex effect within the lines was significant in line IL111 and showed higher values of Ca.Th and %PoV in females compared to males. In line IL19 there was a borderline sex effect in Ca.Th in which males showed higher values than females.

CONCLUSIONS

These results stress the complexity of sex and genotype interactions controlling Ca.Th and %PoV, as the skeletal sexual dimorphism was dependent on the genetic background. This study also shows that the CC population is a powerful tool for establishing the genetic effect on these traits.

Lowering fasting blood glucose with non-dialyzable material of cranberry extract is dependent on host genetic background, sex and diet

BACKGROUND

Type 2 diabetes (T2D) is a polygenic metabolic disease, characterized by high fasting blood glucose (FBG). The ability of cranberry (CRN) fruit to regulate glycemia in T2D patients is well known. Here, a cohort of 13 lines of the genetically diverse Collaborative Cross (CC) mouse model was assessed for the effect of non-dialyzable material (NDM) of cranberry extract in lowering fasting blood glucose.

METHODS

Eight-week-old mice were maintained on either a standard chow diet (control group) or a high-fat diet (HFD) for 12 weeks, followed by injections of intraperitoneal (IP) NDM (50 mg/kg) per mouse, three times a week for the next 6 weeks. Absolute FBG (mg/dl) was measured bi-weekly and percentage changes in FBG (%FBG) between weeks 0 and 12 were calculated.

RESULTS

Statistical analysis showed a significant decrease in FBG between weeks 0 and 12 in male and female mice maintained on CHD. However, a non-significant increase in FBG values was observed in male and female mice maintained on HFD during the same period. Following administration of NDM during the following 6 weeks, the results show a variation in significant levels of FBG lowering between lines, male and female mice and under the different diets.

CONCLUSION

The results suggest that the efficacy of NDM treatment in lowering FGB depends on host genetic background (pharmacogenetics), sex of the mouse (pharmacosex), and diet (pharmacodiet). All these results support the need for follow-up research to better understand and implement a personalized medicine approach/utilization of NDM for reducing FBG.

Unraveling the Host Genetic Background Effect on Internal Organ Weight Influenced by Obesity and Diabetes Using Collaborative Cross Mice

Type 2 diabetes mellitus (T2DM) is a severe chronic epidemic that results from the body's improper usage of the hormone insulin. Globally, 700 million people are expected to have received a diabetes diagnosis by 2045, according to the International Diabetes Federation (IDF). Cancer and macro- and microvascular illnesses are only a few immediate and long-term issues it could lead to. T2DM accelerates the effect of organ weights by triggering a hyperinflammatory response in the body's organs, inhibiting tissue repair and resolving inflammation. Understanding how genetic variation translates into different clinical presentations may highlight the mechanisms through which dietary elements may initiate or accelerate inflammatory disease processes and suggest potential disease-prevention techniques. To address the host genetic background effect on the organ weight by utilizing the newly developed mouse model, the Collaborative Cross mice (CC). The study was conducted on 207 genetically different CC mice from 8 CC lines of both sexes. The experiment started with 8-week-old mice for 12 weeks. During this period, one group maintained a standard chow diet (CHD), while the other group maintained a high-fat diet (HFD). In addition, body weight was recorded bi-weekly, and at the end of the study, a glucose tolerance test, as well as tissue collection (liver, spleen, heart), were conducted. Our study observed a strong effect of HFD on blood glucose clearance among different CC lines. The HFD decreased the blood glucose clearance displayed by the significant Area Under Curve (AUC) values in both populations. In addition, variation in body weight changes among the different CC lines in response to HFD. The female liver weight significantly increased compared to males in the overall population when exposed to HFD. Moreover, males showed higher heritability values than females on the same diet. Regardless of the dietary challenge, the liver weight in the overall male population correlated positively with the final body weight. The liver weight results revealed that three different CC lines perform well under classification models. The regression results also varied among organs. Accordingly, the differences among these lines correspond to the genetic variance, and we suspect that some genetic factors invoke different body responses to HFD. Further investigations, such as quantitative trait loci (QTL) analysis and genomic studies, could find these genetic elements. These findings would prove critical factors for developing personalized medicine, as they could indicate future body responses to numerous situations early, thus preventing the development of complex diseases.

Towards Genetic Dissection of Skeletal Class III Malocclusion: A Review of Genetic Variations Underlying the Phenotype in Humans and Future Directions

INTRODUCTION

Skeletal abnormalities and malocclusions have varied features that impact populations globally, impairing aesthetics and lowering life quality. The prevalence of the Skeletal Class III disease is the lowest among all angle malocclusions, with varied prevalence across nations. Environmental, genetic, and societal factors play a role in its numerous etiologies. In this study, we conducted a thorough search across the published data relating to quantitative trait loci (QTL) and the genes associated with Class III progression in humans, discussed these findings and their limitations, and proposed future directions and strategies for studying this phenotype.

METHODS

An inclusive search of published papers in the PubMed and Google Scholar search engines using the following terms: 1. Human skeletal Class III; 2. Genetics of Human skeletal Class III; 3. QTL mapping and gene associated with human skeletal Class III; 4. enriched skeletal Class-III-malocclusion-associated pathways.

RESULTS

Our search has found 53 genes linked with skeletal Class III malocclusion reported in humans, genes associated with epigenetics and phenomena, and the top 20 enriched pathways associated with skeletal Class III malocclusion.

CONCLUSIONS

The human investigations yielded some contentious conclusions. We conducted a genome-wide association study (GWAS), an epigenetics-wide association study (EWAS), RNA-seq analysis, integrating GWAS and expression quantitative trait loci (eQTL), micro- and small-RNA, and long non-coding RNA analysis in tissues connected to skeletal Class III malocclusion phenotype in tissues connected with the skeletal phenotype. Finally, we invite regional, national, and international orthodontists and surgeons to join this effort by contributing human samples with skeletal Class III malocclusion following the accepted Helsinki ethical protocol to challenge these phenomena jointly.

High-fat diet and oral infection induced type 2 diabetes and obesity development under different genetic backgrounds

BACKGROUND

Type 2 diabetes (T2D) is an adult-onset and obese form of diabetes caused by an interplay between genetic, epigenetic, and environmental components. Here, we have assessed a cohort of 11 genetically different collaborative cross (CC) mouse lines comprised of both sexes for T2D and obesity developments in response to oral infection and high-fat diet (HFD) challenges.

METHODS

Mice were fed with either the HFD or the standard chow diet (control group) for 12 weeks starting at the age of 8 weeks. At week 5 of the experiment, half of the mice of each diet group were infected with Porphyromonas gingivalis and Fusobacterium nucleatum bacteria strains. Throughout the 12-week experimental period, body weight (BW) was recorded biweekly, and intraperitoneal glucose tolerance tests were performed at weeks 6 and 12 of the experiment to evaluate the glucose tolerance status of mice.

RESULTS

Statistical analysis has shown the significance of phenotypic variations between the CC lines, which have different genetic backgrounds and sex effects in different experimental groups. The heritability of the studied phenotypes was estimated and ranged between 0.45 and 0.85. We applied machine learning methods to make an early call for T2D and its prognosis. The results showed that classification with random forest could reach the highest accuracy classification (ACC = 0.91) when all the attributes were used.

CONCLUSION

Using sex, diet, infection status, initial BW, and area under the curve (AUC) at week 6, we could classify the final phenotypes/outcomes at the end stage of the experiment (at 12 weeks).

Intestinal cancer development in response to oral infection with high-fat diet-induced Type 2 diabetes (T2D) in collaborative cross mice under different host genetic background effects

Type 2 diabetes (T2D) is a metabolic disease with an imbalance in blood glucose concentration. There are significant studies currently showing association between T2D and intestinal cancer developments. High-fat diet (HFD) plays part in the disease development of T2D, intestinal cancer and infectious diseases through many biological mechanisms, including but not limited to inflammation. Understanding the system genetics of the multimorbidity of these diseases will provide an important knowledge and platform for dissecting the complexity of these diseases. Furthermore, in this study we used some machine learning (ML) models to explore more aspects of diabetes mellitus. The ultimate aim of this project is to study the genetic factors, which underline T2D development, associated with intestinal cancer in response to a HFD consumption and oral coinfection, jointly or separately, on the same host genetic background. A cohort of 307 mice of eight different CC mouse lines in the four experimental groups was assessed. The mice were maintained on either HFD or chow diet (CHD) for 12-week period, while half of each dietary group was either coinfected with oral bacteria or uninfected. Host response to a glucose load and clearance was assessed using intraperitoneal glucose tolerance test (IPGTT) at two time points (weeks 6 and 12) during the experiment period and, subsequently, was translated to area under curve (AUC) values. At week 5 of the experiment, mice of group two and four were coinfected with Porphyromonas gingivalis (Pg) and Fusobacterium nucleatum (Fn) strains, three times a week, while keeping the other uninfected mice as a control group. At week 12, mice were killed, small intestines and colon were extracted, and subsequently, the polyp counts were assessed; as well, the intestine lengths and size were measured. Our results have shown that there is a significant variation in polyp's number in different CC lines, with a spectrum between 2.5 and 12.8 total polyps on average. There was a significant correlation between area under curve (AUC) and intestine measurements, including polyp counts, length and size. In addition, our results have shown a significant sex effect on polyp development and glucose tolerance ability with males more susceptible to HFD than females by showing higher AUC in the glucose tolerance test. The ML results showed that classification with random forest could reach the highest accuracy when all the attributes were used. These results provide an excellent platform for proceeding toward understanding the nature of the genes involved in resistance and rate of development of intestinal cancer and T2D induced by HFD and oral coinfection. Once obtained, such data can be used to predict individual risk for developing these diseases and to establish the genetically based strategy for their prevention and treatment.

Dissecting the Complexity of Skeletal-Malocclusion-Associated Phenotypes: Mouse for the Rescue

Skeletal deformities and malocclusions being heterogeneous traits, affect populations worldwide, resulting in compromised esthetics and function and reduced quality of life. Skeletal Class III prevalence is the least common of all angle malocclusion classes, with a frequency of 7.2%, while Class II prevalence is approximately 27% on average, varying in different countries and between ethnic groups. Orthodontic malocclusions and skeletal deformities have multiple etiologies, often affected and underlined by environmental, genetic and social aspects. Here, we have conducted a comprehensive search throughout the published data until the time of writing this review for already reported quantitative trait loci (QTL) and genes associated with the development of skeletal deformation-associated phenotypes in different mouse models. Our search has found 72 significant QTL associated with the size of the mandible, the character, shape, centroid size and facial shape in mouse models. We propose that using the collaborative cross (CC), a highly diverse mouse reference genetic population, may offer a novel venue for identifying genetic factors as a cause for skeletal deformations, which may help to better understand Class III malocclusion-associated phenotype development in mice, which can be subsequently translated to humans. We suggest that by performing a genome-wide association study (GWAS), an epigenetics-wide association study (EWAS), RNAseq analysis, integrating GWAS and expression quantitative trait loci (eQTL), micro and small RNA, and long noncoding RNA analysis in tissues associated with skeletal deformation and Class III malocclusion characterization/phenotypes, including mandibular basic bone, gum, and jaw, in the CC mouse population, we expect to better identify genetic factors and better understand the development of this disease.

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.

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.

Systems genetics analysis of oral squamous cell carcinoma susceptibility using the mouse model: current position and new perspective

Oral squamous cell carcinoma (OSCC) is one of the most common human malignancies with complex etiology and poor prognosis. Although environmental carcinogens and carcinogenic viruses are still considered the main etiologic factors for OSCC development, genetic factors obviously play a key role in the initiation and progression of this neoplasm, given that not all individuals exposed to carcinogens develop the same severity of the disease, if any. Identifying genetic loci modulating OSCC risk may have several important clinical implications, including early detection, prevention and developing new treatment strategies. Due to limitations in controlled and standardized genetic studies in humans, genetic components underlying susceptibility of OSCC development remain largely unknown. A combination of quantitative trait loci mapping in mice, with complementary association studies in humans, has the potential to discover novel cancer risk loci. As of today, a limited number of genetic analyses were applied on rodent models to locate novel genetic loci associated with human OSCC. Here, we discuss the current status of the mouse models use for dissecting the genetic basis of OSCC and highlight how systems genetics analysis using mouse models, may increase our understanding of human OSCC susceptibility.

Studying the pharmacogenomic effect of cranberry extract on reducing body weight using collaborative cross mice

The non-dialyzable material (NDM) of polyphenol-rich cranberry extract (CRE) powder (NDM-CRE) was studied for its effect of inducing body weight (BW) loss in 13 different mouse lines with well-defined genetically diverse backgrounds, named the collaborative cross (CC). From the age of 8 weeks, the mice were maintained on a high-fat diet (HFD) for 18 weeks, to induce obesity, and BW was measured biweekly. From week 12, CRE was injected intraperitoneally (IP) (50 mg kg^-1) 3 times a week per mouse for a 6 week period. Statistical analysis results have shown a significant increase in body weight between week 0 and week 12; the increase in BW of 13 lines of mice on HFD was in the range of 10.41% to 68.65% for males and 9.78% to 64.74% for females. After injecting NDM-CRE extract, our analysis has shown an induced change in BW between week 12 and week 18. In males, NDM-CRE caused a significant decrease in BW of 5 out of the 13 lines in the range of -5.68% to -16.69% and a significant increase of 8.31% in BW of one male line, whereas in seven lines there was no significant decrease (-2.14% to -4.09%). In females, NDM-CRE caused a significant decrease in BW of 5 out of the 13 lines in the range of -3.90% to -11.83%, whereas in eight lines there were no significant changes in BW and it ranged between -1.50% and 4.90%. The broad-sense heritability (H²) and genetic coefficient of variation (CV_g) were estimated and found to be between 0.71 and 0.81 for H², and 0.18 and 0.24 for CV_g of females and males, respectively, with respect to the efficacy of NDM-CRE on body weight reduction. Our results have shown that hosts with different genetic backgrounds respond differently to body weight increase, as well as to NDM-CRE treatment for body weight reduction. These results provide a platform for assessing more CC lines and mapping genes underlying the efficacy of the NDM-CRE treatment as a way of understanding pharmacogenomics.

Leveraging the cell lineage to predict cell-type specificity of regulatory variation from bulk genomics

Recent computational methods have enabled the inference of the cell-type-specificity of eQTLs based on bulk transcriptomes from highly heterogeneous tissues. However, these methods are limited in their scalability to highly heterogeneous tissues and limited in their broad applicability to any cell-type specificity of eQTLs. Here we present and demonstrate Cell Lineage Genetics (CeL-Gen), a novel computational approach that allows inference of eQTLs together with the subsets of cell types in which they have an effect, from bulk transcriptome data. To obtain improved scalability and broader applicability, CeL-Gen takes as input the known cell lineage tree and relies on the observation that dynamic changes in genetic effects occur relatively infrequently during cell differentiation. CeL-Gen can therefore be used not only to tease apart genetic effects derived from different cell types but also to infer the particular differentiation steps in which genetic effects are altered.

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.

Container-aided integrative QTL and RNA-seq analysis of Collaborative Cross mice supports distinct sex-oriented molecular modes of response in obesity

BACKGROUND

The Collaborative Cross (CC) mouse population is a valuable resource to study the genetic basis of complex traits, such as obesity. Although the development of obesity is influenced by environmental factors, underlying genetic mechanisms play a crucial role in the response to these factors. The interplay between the genetic background and the gene expression pattern can provide further insight into this response, but we lack robust and easily reproducible workflows to integrate genomic and transcriptomic information in the CC mouse population.

RESULTS

We established an automated and reproducible integrative workflow to analyse complex traits in the CC mouse genetic reference panel at the genomic and transcriptomic levels. We implemented the analytical workflow to assess the underlying genetic mechanisms of host susceptibility to diet induced obesity and integrated these results with diet induced changes in the hepatic gene expression of susceptible and resistant mice. Hepatic gene expression differs significantly between obese and non-obese mice, with a significant sex effect, where male and female mice exhibit different responses and coping mechanisms.

CONCLUSION

Integration of the data showed that different genes but similar pathways are involved in the genetic susceptibility and disturbed in diet induced obesity. Genetic mechanisms underlying susceptibility to high-fat diet induced obesity are different in female and male mice. The clear distinction we observed in the systemic response to the high-fat diet challenge and to obesity between male and female mice points to the need for further research into distinct sex-related mechanisms in metabolic disease.

Impact of host genetics on gut microbiome: Take-home lessons from human and mouse studies

The intestinal microbiome has emerged as an important component involved in various diseases. Therefore, the interest in understanding the factors shaping its composition is growing. The gut microbiome, often defined as a complex trait, contains diverse components and its properties are determined by a combination of external and internal effects. Although much effort has been invested so far, it is still difficult to evaluate the extent to which human genetics shape the composition of the gut microbiota. However, in mouse studies, where the environmental factors are better controlled, the effect of the genetic background was significant. The purpose of this paper is to provide a current assessment of the role of human host genetics in shaping the gut microbiome composition. Despite the inconsistency of the reported results, it can be estimated that the genetic factor affects a portion of the microbiome. However, this effect is currently lower than the initial estimates, and it is difficult to separate the genetic influence from the environmental effect. Additionally, despite the differences between the microbial composition of humans and mice, results from mouse models can strengthen our knowledge of host genetics underlying the human gut microbial variation.

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.

Translation of mouse model to human gives insights into periodontitis etiology

To suggest candidate genes involved in periodontitis, we combined gene expression data of periodontal biopsies from Collaborative Cross (CC) mouse lines, with previous reported quantitative trait loci (QTL) in mouse and with human genome-wide association studies (GWAS) associated with periodontitis. Periodontal samples from two susceptible, two resistant and two lines that showed bone formation after periodontal infection were collected during infection and naïve status. Differential expressed genes (DEGs) were analyzed in a case-control and case-only design. After infection, eleven protein-coding genes were significantly stronger expressed in resistant CC lines compared to susceptible ones. Of these, the most upregulated genes were MMP20 (P = 0.001), RSPO4 (P = 0.032), CALB1 (P = 1.06×10-4), and AMTN (P = 0.05). In addition, human orthologous of candidate genes were tested for their association in a case-controls samples of aggressive (AgP) and chronic (CP) periodontitis (5,095 cases, 9,908 controls). In this analysis, variants at two loci, TTLL11/PTGS1 (rs9695213, P = 5.77×10-5) and RNASE2 (rs2771342, P = 2.84×10-5) suggested association with both AgP and CP. In the association analysis with AgP only, the most significant associations were located at the HLA loci HLA-DQH1 (rs9271850, P = 2.52×10-14) and HLA-DPA1 (rs17214512, P = 5.14×10-5). This study demonstrates the utility of the CC RIL populations as a suitable model to investigate the mechanism of periodontal disease.

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).

Hepatic gene expression variations in response to high-fat diet-induced impaired glucose tolerance using RNAseq analysis in collaborative cross mouse population

Hepatic gene expression is known to differ between healthy and type 2 diabetes conditions. Identifying these variations will provide better knowledge to the development of gene-targeted therapies. The aim of this study is to assess diet-induced hepatic gene expression of susceptible versus resistant CC lines to T2D development. Next-generation RNA-sequencing was performed for 84 livers of diabetic and non-diabetic mice of 41 different CC lines (both sexes) following 12 weeks on high-fat diet (42% fat). Data analysis revealed significant variations of hepatic gene expression in diabetic versus non-diabetic mice with significant sex effect, where 601 genes were differentially expressed (DE) in overall population (males and females), 718 genes in female mice, and 599 genes in male mice. Top prioritized DE candidate genes were Lepr, Ins2, Mb, Ckm, Mrap2, and Ckmt2 for the overall population; for females-only group were Hdc, Serpina12, Socs1, Socs2, and Mb, while for males-only group were Serpine1, Mb, Ren1, Slc4a1, and Atp2a1. Data analysis for sex differences revealed 193 DE genes in health (Top: Lepr, Cav1, Socs2, Abcg2, and Col5a3), and 389 genes DE between diabetic females versus males (Top: Lepr, Clps, Ins2, Cav1, and Mrap2). Furthermore, integrating gene expression results with previously published QTL, we identified significant variants mapped at chromosomes at positions 36-49 Mb, 62-71 Mb, and 79-99 Mb, on chromosomes 9, 11, and 12, respectively. Our findings emphasize the complexity of T2D development and that significantly controlled by host complex genetic factors. As well, we demonstrate the significant sex differences between males and females during health and increasing to extent levels during disease/diabetes. Altogether, opening the venue for further studies targets the discovery of effective sex-specific and personalized preventions and therapies.

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.

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.

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.

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.

Integration of Murine and Human Studies for Mapping Periodontitis Susceptibility

Periodontitis is one of the most common inflammatory human diseases with a strong genetic component. Due to the limited sample size of available periodontitis cohorts and the underlying trait heterogeneity, genome-wide association studies (GWASs) of chronic periodontitis (CP) have largely been unsuccessful in identifying common susceptibility factors. A combination of quantitative trait loci (QTL) mapping in mice with association studies in humans has the potential to discover novel risk loci. To this end, we assessed alveolar bone loss in response to experimental periodontal infection in 25 lines (286 mice) from the Collaborative Cross (CC) mouse population using micro-computed tomography (µCT) analysis. The orthologous human chromosomal regions of the significant QTL were analyzed for association using imputed genotype data (OmniExpress BeadChip arrays) derived from case-control samples of aggressive periodontitis (AgP; 896 cases, 7,104 controls) and chronic periodontitis (CP; 2,746 cases, 1,864 controls) of northwest European and European American descent, respectively. In the mouse genome, QTL mapping revealed 2 significant loci (-log P = 5.3; false discovery rate = 0.06) on chromosomes 1 ( Perio3) and 14 ( Perio4). The mapping resolution ranged from ~1.5 to 3 Mb. Perio3 overlaps with a previously reported QTL associated with residual bone volume in F2 cross and includes the murine gene Ccdc121. Its human orthologue showed previously a nominal significant association with CP in humans. Use of variation data from the genomes of the CC founder strains further refined the QTL and suggested 7 candidate genes ( CAPN8, DUSP23, PCDH17, SNORA17, PCDH9, LECT1, and LECT2). We found no evidence of association of these candidates with the human orthologues. In conclusion, the CC populations enabled mapping of confined QTL that confer susceptibility to alveolar bone loss in mice and larger human phenotype-genotype samples and additional expression data from gingival tissues are likely required to identify true positive signals.

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.

The PF4/PPBP/CXCL5 Gene Cluster Is Associated with Periodontitis

Periodontitis is a common dysbiotic inflammatory disease with an estimated heritability of 50%. Due to the limited sample size of available periodontitis cohorts and the underlying trait heterogeneity, genome-wide association studies (GWAS) of chronic periodontitis (CP) have been unsuccessful in discovering susceptibility factors. A strategy that combines agnostic GWAS with a well-powered candidate-gene approach has the potential to discover novel loci. We combined RNA-seq data from gingival tissues with quantitative trait loci (QTLs) that were identified in a F₂-cross of mice resistant and susceptible to infection with oral bacterial pathogens. Four genes, which were located within the mapped QTLs, showed differential expression. The chromosomal regions across the human orthologous were interrogated for putative periodontitis-associated variants using existing GWAS data from a German case-control sample of aggressive periodontitis (AgP; 651 cases, 4,001 controls), the most severe and early onset form of periodontitis. Two haplotype blocks, one upstream to the coding region of UGT2A1 (rs146712414, P = 9.1 × 10^-5; odds ratio [OR], 1.34; 95% confidence interval [CI], 1.16-1.56) and one downstream of the genes PF4/PPBP/CXCL5 (rs1595009, P = 1.3 × 10^-4; OR, 1.32; 95% CI, 1.15-1.52), were associated with AgP. The association of rs1595009 was validated in an independent cohort of CP of European Americans (1,961 cases and 1,864 controls; P = 0.03; OR, 1.45; 95% CI, 1.01-1.29). This association was further replicated in another sample of 399 German CP cases (disease onset <60 y of age) and 1,633 controls ( P = 0.03; OR, 1.75; 95% CI, 1.06-2.90). The combined estimates of association from all samples were P = 2.9 × 10^-5 (OR, 1.2; 95% CI, 1.1-1.3). This study shows the strength of combining QTL mapping and RNA-Seq data from a mouse model with association studies in human case-control samples to identify genetic risk variants of periodontitis.

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.

Mapping genetic determinants of host susceptibility to Pseudomonas aeruginosa lung infection in mice

Background

P. aeruginosa is one of the top three causes of opportunistic human bacterial infections. The remarkable variability in the clinical outcomes of this infection is thought to be associated with genetic predisposition. However, the genes underlying host susceptibility to P. aeruginosa infection are still largely unknown.

Results

As a step towards mapping these genes, we applied a genome wide linkage analysis approach to a mouse model. A large F2 intercross population, obtained by mating P. aeruginosa-resistant C3H/HeOuJ, and susceptible A/J mice, was used for quantitative trait locus (QTL) mapping. The F2 progenies were challenged with a P. aeruginosa clinical strain and monitored for the survival time up to 7 days post-infection, as a disease phenotype associated trait. Selected phenotypic extremes of the F2 distribution were genotyped with high-density single nucleotide polymorphic (SNP) markers, and subsequently QTL analysis was performed. A significant locus was mapped on chromosome 6 and was named P. aeruginosa infection resistance locus 1 (Pairl1). The most promising candidate genes, including Dok1, Tacr1, Cd207, Clec4f, Gp9, Gata2, Foxp1, are related to pathogen sensing, neutrophils and macrophages recruitment and inflammatory processes.

Conclusions

We propose a set of genes involved in the pathogenesis of P. aeruginosa infection that may be explored to complement human studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2676-4) contains supplementary material, which is available to authorized users.

Genetic analysis of intestinal polyp development in Collaborative Cross mice carrying the Apc (Min/+) mutation

Background

Colorectal cancer is an abnormal tissue development in the colon or rectum. Most of CRCs develop due to somatic mutations, while only a small proportion is caused by inherited mutations. Familial adenomatous polyposis is an inherited genetic disease, which is characterized by colorectal polyps. It is caused by inactivating mutations in the Adenomatous polyposis coli gene. Mice carrying and non-sense mutation in Adenomatous polyposis coli gene at site R850, which designated Apc^R850X/+ (Min), develop intestinal adenomas, while the bulk of the disease is in the small intestine. A number of genetic modifier loci of Min have been mapped, but so far most of the underlying genes have not been identified. In our previous studies, we have shown that Collaborative Cross mice are a powerful tool for mapping loci responsible for phenotypic variation. As a first step towards identification of novel modifiers of Min, we assessed the phenotypic variation between 27 F1 crosses between different Collaborative cross mice and C57BL/6-Min lines.

Results

Here, C57BL/6-Min male mice were mated with females from 27 Collaborative cross lines. F1 offspring were terminated at 23 weeks old and multiple phenotypes were collected: polyp counts, intestine length, intestine weight, packed cell volume and spleen weight. Additionally, in eight selected F1 Collaborative cross-C57BL/6-Min lines, body weight was monitored and compared to control mice carry wildtype Adenomatous polyposis coli gene. We found significant (p < 0.05) phenotypic variation between the 27 F1 Collaborative cross-C57BL/6-Min lines for all the tested phenotypes, and sex differences with traits; Colon, body weight and intestine length phenotypes, only. Heritability calculation showed that these phenotypes are mainly controlled by genetic factors.

Conclusions

Variation in polyp development is controlled, an appreciable extent, by genetic factors segregating in the Collaborative cross population and suggests that it is suited for identifying modifier genes associated with Apc^Min/+ mutation, after assessing sufficient number of lines for quantitative trait loci analysis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0349-6) contains supplementary material, which is available to authorized users.

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.

Collaborative cross mice in a genetic association study reveal new candidate genes for bone microarchitecture

Background

The microstructure of trabecular bone is a composite trait governed by a complex interaction of multiple genetic determinants. Identifying these genetic factors should significantly improve our ability to predict of osteoporosis and its associated risks. Genetic mapping using collaborative cross mice (CC), a genetically diverse recombinant inbred mouse reference panel, offers a powerful tool to identify causal loci at a resolution under one mega base-pairs, with a relatively small cohort size.

Here, we utilized 31 CC lines (160 mice of both sexes in total) to perform genome-wide haplotype mapping across 77,808 single-nucleotide polymorphisms (SNPs). Haplotype scans were refined by imputation with the catalogue of sequence variation segregating in the CC to suggest potential candidate genes. Trabecular traits were obtained following microtomographic analysis, performed on 10-μm resolution scans of the femoral distal metaphysis. We measured the trabecular bone volume fraction (BV/TV), number (Tb.N), thickness (Tb.Th), and connectivity density (Conn.D).

Results

Heritability of these traits ranged from 0.6 to 0.7. In addition there was a significant (P < 0.01) sex effect in all traits except Tb.Th. Our haplotype scans yielded six quantitative trait loci (QTL) at 1 % false discovery rate; BV/TV and Tb.Th produced two proximal loci each, on chromosome 2 and 7, respectively, and Tb.N and Conn.D yielded one locus on chromosomes 8 and 14, respectively. We identified candidate genes with previously-reported functions in bone biology, and implicated unexpected genes whose function in bone biology has yet to be assigned. Based on the literature, among the genes that ranked particularly high in our analyses (P < 10^-6) and which have a validated causal role in skeletal biology, are Avp, Oxt, B2m (associated with BV/TV), Cnot7 (with Tb.N), Pcsk6, Rgma (with Tb.Th), Rb1, and Cpb2 (with Conn.D). Other candidate genes strongly suggested by our analyses are Sgcz, Fgf20 (associated with Tb.N), and Chd2 (with Tb.Th).

Conclusion

We have demonstrated for the first time genome-wide significant association between several genetic loci and trabecular microstructural parameters for genes with previously reported experimental observations, as well as proposing a role for new candidate genes with no previously characterized skeletal function.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2213-x) contains supplementary material, which is available to authorized users.

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.

Intestinal microbiota and diet in IBS: causes, consequences, or epiphenomena?

Irritable bowel syndrome (IBS) is a heterogeneous functional disorder with a multifactorial etiology that involves the interplay of both host and environmental factors. Among environmental factors relevant for IBS etiology, the diet stands out given that the majority of IBS patients report their symptoms to be triggered by meals or specific foods. The diet provides substrates for microbial fermentation, and, as the composition of the intestinal microbiota is disturbed in IBS patients, the link between diet, microbiota composition, and microbial fermentation products might have an essential role in IBS etiology. In this review, we summarize current evidence regarding the impact of diet and the intestinal microbiota on IBS symptoms, as well as the reported interactions between diet and the microbiota composition. On the basis of the existing data, we suggest pathways (mechanisms) by which diet components, via the microbial fermentation, could trigger IBS symptoms. Finally, this review provides recommendations for future studies that would enable elucidation of the role of diet and microbiota and how these factors may be (inter)related in the pathophysiology of IBS.

Susceptibility to Klebsiella pneumonaie infection in collaborative cross mice is a complex trait controlled by at least three loci acting at different time points

BACKGROUND

Klebsiella pneumoniae (Kp) is a bacterium causing severe pneumonia in immunocompromised hosts and is often associated with sepsis. With the rise of antibiotic resistant bacteria, there is a need for new effective and affordable control methods; understanding the genetic architecture of susceptibility to Kp will help in their development. We performed the first quantitative trait locus (QTL) mapping study of host susceptibility to Kp infection in immunocompetent Collaborative Cross mice (CC). We challenged 328 mice from 73 CC lines intraperitoneally with 104 colony forming units of Kp strain K2. Survival and body weight were monitored for 15 days post challenge. 48 of the CC lines were genotyped with 170,000 SNPs, with which we mapped QTLs.

RESULTS

CC lines differed significantly (P < 0.05) in mean survival time, between 1 to 15 days post infection, and broad sense heritability was 0.45. Distinct QTL were mapped at specific time points during the challenge. A QTL on chromosome 4 was found only on day 2 post infection, and QTL on chromosomes 8 and 18, only on day 8. By using the sequence variations of the eight inbred strain founders of the CC to refine QTL localization we identify several candidate genes.

CONCLUSION

Host susceptibility to Kp is a complex trait, controlled by multiple genetic factors that act sequentially during the course of infection.

Host genetic background influences the response to the opportunistic Pseudomonas aeruginosa infection altering cell-mediated immunity and bacterial replication

Pseudomonas aeruginosa is a common cause of healthcare-associated infections including pneumonia, bloodstream, urinary tract, and surgical site infections. The clinical outcome of P. aeruginosa infections may be extremely variable among individuals at risk and patients affected by cystic fibrosis. However, risk factors for P. aeruginosa infection remain largely unknown. To identify and track the host factors influencing P. aeruginosa lung infections, inbred immunocompetent mouse strains were screened in a pneumonia model system. A/J, BALB/cJ, BALB/cAnNCrl, BALB/cByJ, C3H/HeOuJ, C57BL/6J, C57BL/6NCrl, DBA/2J, and 129S2/SvPasCRL mice were infected with P. aeruginosa clinical strain and monitored for body weight and mortality up to seven days. The most deviant survival phenotypes were observed for A/J, 129S2/SvPasCRL and DBA/2J showing high susceptibility while BALB/cAnNCrl and C3H/HeOuJ showing more resistance to P. aeruginosa infection. Next, one of the most susceptible and resistant mouse strains were characterized for their deviant clinical and immunological phenotype by scoring bacterial count, cell-mediated immunity, cytokines and chemokines profile and lung pathology in an early time course. Susceptible A/J mice showed significantly higher bacterial burden, higher cytokines and chemokines levels but lower leukocyte recruitment, particularly neutrophils, when compared to C3H/HeOuJ resistant mice. Pathologic scores showed lower inflammatory severity, reduced intraluminal and interstitial inflammation extent, bronchial and parenchymal involvement and diminished alveolar damage in the lungs of A/J when compared to C3H/HeOuJ. Our findings indicate that during an early phase of infection a prompt inflammatory response in the airways set the conditions for a non-permissive environment to P. aeruginosa replication and lock the spread to other organs. Host gene(s) may have a role in the reduction of cell-mediated immunity playing a critical role in the control of P. aeruginosa infection. These results now provide a basis for mapping genomic regions underlying host susceptibility to P. aeruginosa infection.

Heritability and coefficient of genetic variation analyses of phenotypic traits provide strong basis for high-resolution QTL mapping in the Collaborative Cross mouse genetic reference population

Most biological traits of human importance are complex in nature; their manifestation controlled by the cumulative effect of many genetic factors interacting with one another and with the individual's life history. Because of this, mouse genetic reference populations (GRPs) consisting of collections of inbred lines or recombinant inbred lines (RIL) derived from crosses between inbred lines are of particular value in analysis of complex traits, since massive amounts of data can be accumulated on the individual lines. However, existing mouse GRPs are derived from inbred lines that share a common history, resulting in limited genetic diversity, and reduced mapping precision due to long-range gametic disequilibrium. To overcome these limitations, the Collaborative Cross (CC) a genetically highly diverse collection of mouse RIL was established. The CC, now in advanced stages of development, will eventually consist of about 500 RIL derived from reciprocal crosses of eight divergent founder strains of mice, including three wild subspecies. Previous studies have shown that the CC indeed contains enormous diversity at the DNA level, that founder haplotypes are inherited in expected frequency, and that long-range gametic disequilibrium is not present. We here present data, primarily from our own laboratory, documenting extensive genetic variation among CC lines as expressed in broad-sense heritability (H(2)) and by the well-known "coefficient of genetic variation," demonstrating the ability of the CC resource to provide unprecedented mapping precision leading to identification of strong candidate genes.

Host susceptibility to malaria in human and mice: compatible approaches to identify potential resistant genes

There is growing evidence for human genetic factors controlling the outcome of malaria infection, while molecular basis of this genetic control is still poorly understood. Case-control and family-based studies have been carried out to identify genes underlying host susceptibility to malarial infection. Parasitemia and mild malaria have been genetically linked to human chromosomes 5q31-q33 and 6p21.3, and several immune genes located within those regions have been associated with malaria-related phenotypes. Association and linkage studies of resistance to malaria are not easy to carry out in human populations, because of the difficulty in surveying a significant number of families. Murine models have proven to be an excellent genetic tool for studying host response to malaria; their use allowed mapping 14 resistance loci, eight of them controlling parasitic levels and six controlling cerebral malaria. Once quantitative trait loci or genes have been identified, the human ortholog may then be identified. Comparative mapping studies showed that a couple of human and mouse might share similar genetically controlled mechanisms of resistance. In this way, char8, which controls parasitemia, was mapped on chromosome 11; char8 corresponds to human chromosome 5q31-q33 and contains immune genes, such as Il3, Il4, Il5, Il12b, Il13, Irf1, and Csf2. Nevertheless, part of the genetic factors controlling malaria traits might differ in both hosts because of specific host-pathogen interactions. Finally, novel genetic tools including animal models were recently developed and will offer new opportunities for identifying genetic factors underlying host phenotypic response to malaria, which will help in better therapeutic strategies including vaccine and drug development.