Complex interactions of new quantitative trait loci, Sluc1, Sluc2, Sluc3, and Sluc4, that influence the susceptibility to lung cancer in the mouse

Early-Onset Ovarian Cancer <30 Years: What Do We Know about Its Genetic Predisposition?

Ovarian cancer (OC) is one of the leading causes of cancer-related deaths in women. Most patients are diagnosed with advanced epithelial OC in their late 60s, and early-onset adult OC diagnosed ≤30 years is rare, accounting for less than 5% of all OC cases. The most significant risk factor for OC development are germline pathogenic/likely pathogenic variants (GPVs) in OC predisposition genes (including BRCA1, BRCA2, BRIP1, RAD51C, RAD51D, Lynch syndrome genes, or BRIP1), which contribute to the development of over 20% of all OC cases. GPVs in BRCA1/BRCA2 are the most prevalent. The presence of a GPV directs tailored cancer risk-reducing strategies for OC patients and their relatives. Identification of OC patients with GPVs can also have therapeutic consequences. Despite the general assumption that early cancer onset indicates higher involvement of hereditary cancer predisposition, the presence of GPVs in early-onset OC is rare (<10% of patients), and their heritability is uncertain. This review summarizes the current knowledge on the genetic predisposition to early-onset OC, with a special focus on epithelial OC, and suggests other alternative genetic factors (digenic, oligogenic, polygenic heritability, genetic mosaicism, imprinting, etc.) that may influence the development of early-onset OC in adult women lacking GPVs in known OC predisposition genes.

A wild-derived inbred mouse strain, MSM/Ms, provides insights into novel skin tumor susceptibility genes

Cancer is one of the most catastrophic human genetic diseases. Experimental animal cancer models are essential for gaining insights into the complex interactions of different cells and genes in tumor initiation, promotion, and progression. Mouse models have been extensively used to analyze the genetic basis of cancer susceptibility. They have led to the identification of multiple loci that confer, either alone or in specific combinations, an increased susceptibility to cancer, some of which have direct translatability to human cancer. Additionally, wild-derived inbred mouse strains are an advantageous reservoir of novel genetic polymorphisms of cancer susceptibility genes, because of the evolutionary divergence between wild and classical inbred strains. Here, we review mapped Stmm (skintumor modifier of MSM) loci using a Japanese wild-derived inbred mouse strain, MSM/Ms, and describe recent advances in our knowledge of the genes responsible for Stmm loci in the 7,12-dimethylbenz(a)anthracene (DMBA)/12-O-tetradecanoylphorbol-13-acetate (TPA) two-stage skin carcinogenesis model.

The Japanese Wild-Derived Inbred Mouse Strain, MSM/Ms in Cancer Research

MSM/Ms is a unique inbred mouse strain derived from the Japanese wild mouse, Mus musculus molossinus, which has been approximately 1 million years genetically distant from standard inbred mouse strains mainly derived from M. m. domesticus. Due to its genetic divergence, MSM/Ms has been broadly used in linkage studies. A bacterial artificial chromosome (BAC) library was constructed for the MSM/Ms genome, and sequence analysis of the MSM/Ms genome showed approximately 1% of nucleotides differed from those in the commonly used inbred mouse strain, C57BL/6J. Therefore, MSM/Ms mice are thought to be useful for functional genome studies. MSM/Ms mice show unique characteristics of phenotypes, including its smaller body size, resistance to high-fat-diet-induced diabetes, high locomotive activity, and resistance to age-onset hearing loss, inflammation, and tumorigenesis, which are distinct from those of common inbred mouse strains. Furthermore, ES (Embryonic Stem) cell lines established from MSM/Ms allow the MSM/Ms genome to be genetically manipulated. Therefore, genomic and phenotypic analyses of MSM/Ms reveal novel insights into gene functions that were previously not obtained from research on common laboratory strains. Tumorigenesis-related MSM/Ms-specific genetic traits have been intensively investigated in Japan. Furthermore, radiation-induced thymic lymphomas and chemically-induced skin tumors have been extensively examined using MSM/Ms.

Combinatorial and statistical prediction of gene expression from haplotype sequence

MOTIVATION

Genome-wide association studies (GWAS) have discovered thousands of significant genetic effects on disease phenotypes. By considering gene expression as the intermediary between genotype and disease phenotype, expression quantitative trait loci studies have interpreted many of these variants by their regulatory effects on gene expression. However, there remains a considerable gap between genotype-to-gene expression association and genotype-to-gene expression prediction. Accurate prediction of gene expression enables gene-based association studies to be performed post hoc for existing GWAS, reduces multiple testing burden, and can prioritize genes for subsequent experimental investigation.

RESULTS

In this work, we develop gene expression prediction methods that relax the independence and additivity assumptions between genetic markers. First, we consider gene expression prediction from a regression perspective and develop the HAPLEXR algorithm which combines haplotype clusterings with allelic dosages. Second, we introduce the new gene expression classification problem, which focuses on identifying expression groups rather than continuous measurements; we formalize the selection of an appropriate number of expression groups using the principle of maximum entropy. Third, we develop the HAPLEXD algorithm that models haplotype sharing with a modified suffix tree data structure and computes expression groups by spectral clustering. In both models, we penalize model complexity by prioritizing genetic clusters that indicate significant effects on expression. We compare HAPLEXR and HAPLEXD with three state-of-the-art expression prediction methods and two novel logistic regression approaches across five GTEx v8 tissues. HAPLEXD exhibits significantly higher classification accuracy overall; HAPLEXR shows higher prediction accuracy on approximately half of the genes tested and the largest number of best predicted genes (r2>0.1) among all methods. We show that variant and haplotype features selected by HAPLEXR are smaller in size than competing methods (and thus more interpretable) and are significantly enriched in functional annotations related to gene regulation. These results demonstrate the importance of explicitly modeling non-dosage dependent and intragenic epistatic effects when predicting expression.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries are freely available at https://github.com/rapturous/HAPLEX.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Bronchioloalveolar lung tumors induced in “mice only” by non-genotoxic chemicals are not useful for quantitative assessment of pulmonary adenocarcinoma risk in humans

Chemicals classified as known human carcinogens by International Agency for Research on Cancer (IARC) show a low level of concordance between rodents and humans for induction of pulmonary carcinoma. Rats and mice exposed via inhalation for 2 years show a low level of concordance in both tumor development and organ site location. In 2-year inhalation studies using rats and mice, when pulmonary tumors are seen in only male or female mice or both, but not in either sex of rat, there is a high probability that the murine pulmonary tumor has been produced via Clara cell or club cell (CC) metabolism of the inhaled chemical to a cytotoxic metabolite. Cytotoxicity-induced mitogenesis increases mutagenesis via amplification of the background mutation rate. If the chemical being tested is also negative in the Ames Salmonella mutagenicity assay, and only mouse pulmonary tumors are induced, the probability that this pulmonary tumor is not relevant to human lung cancer risk goes even higher. Mice have a larger percentage of CCs in their distal airways than rats, and a much larger percentage than in humans. The CCs of mice have a much higher concentration of metabolic enzymes capable of metabolizing xenobiotics than CCs in either rats or humans. A principal threat to validity of extrapolating from the murine model lies in the unique capacity of murine CCs to metabolize a significant spectrum of xenobiotics which in turn produces toxicants not seen in rat or human pulmonary pathophysiology.

Quantitative trait loci for resistance to Flavobacterium psychrophilum in rainbow trout: effect of the mode of infection and evidence of epistatic interactions

Background

Bacterial cold-water disease, which is caused by Flavobacterium psychrophilum, is one of the major diseases that affect rainbow trout (Oncorhynchus mykiss) and a primary concern for trout farming. Better knowledge of the genetic basis of resistance to F. psychrophilum would help to implement this trait in selection schemes and to investigate the immune mechanisms associated with resistance. Various studies have revealed that skin and mucus may contribute to response to infection. However, previous quantitative trait loci (QTL) studies were conducted by using injection as the route of infection. Immersion challenge, which is assumed to mimic natural infection by F. psychrophilum more closely, may reveal different defence mechanisms.

Results

Two isogenic lines of rainbow trout with contrasting susceptibilities to F. psychrophilum were crossed to produce doubled haploid F2 progeny. Fish were infected with F. psychrophilum either by intramuscular injection (115 individuals) or by immersion (195 individuals), and genotyped for 9654 markers using RAD-sequencing. Fifteen QTL associated with resistance traits were detected and only three QTL were common between the injection and immersion. Using a model that accounted for epistatic interactions between QTL, two main types of interactions were revealed. A “compensation-like” effect was detected between several pairs of QTL for the two modes of infection. An “enhancing-like” interaction effect was detected between four pairs of QTL. Integration of the QTL results with results of a previous transcriptomic analysis of response to F. psychrophilum infection resulted in a list of potential candidate immune genes that belong to four relevant functional categories (bacterial sensors, effectors of antibacterial immunity, inflammatory factors and interferon-stimulated genes).

Conclusions

These results provide new insights into the genetic determinism of rainbow trout resistance to F. psychrophilum and confirm that some QTL with large effects are involved in this trait. For the first time, the role of epistatic interactions between resistance-associated QTL was evidenced. We found that the infection protocol used had an effect on the modulation of defence mechanisms and also identified relevant immune functional candidate genes.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0431-9) contains supplementary material, which is available to authorized users.

Dominant Epistasis Between Two Quantitative Trait Loci Governing Sporulation Efficiency in Yeast Saccharomyces cerevisiae

Sporulation efficiency in the yeast Saccharomyces cerevisiae is a well-established model for studying quantitative traits. A variety of genes and nucleotides causing different sporulation efficiencies in laboratory, as well as in wild strains, has already been extensively characterised (mainly by reciprocal hemizygosity analysis and nucleotide exchange methods). We applied a different strategy in order to analyze the variation in sporulation efficiency of laboratory yeast strains. Coupling classical quantitative genetic analysis with simulations of phenotypic distributions (a method we call phenotype modelling) enabled us to obtain a detailed picture of the quantitative trait loci (QTLs) relationships underlying the phenotypic variation of this trait. Using this approach, we were able to uncover a dominant epistatic inheritance of loci governing the phenotype. Moreover, a molecular analysis of known causative quantitative trait genes and nucleotides allowed for the detection of novel alleles, potentially responsible for the observed phenotypic variation. Based on the molecular data, we hypothesise that the observed dominant epistatic relationship could be caused by the interaction of multiple quantitative trait nucleotides distributed across a 60--kb QTL region located on chromosome XIV and the RME1 locus on chromosome VII. Furthermore, we propose a model of molecular pathways which possibly underlie the phenotypic variation of this trait.

Genetic interactions with sex make a relatively small contribution to the heritability of complex traits in mice

The extent to which sex-specific genetic effects contribute to phenotypic variation is largely unknown. We applied a novel Bayesian method, sparse partitioning, to detect gene by sex (GxS) and gene by gene (GxG) quantitative loci (QTLs) in 1,900 outbred heterogeneous stock mice. In an analysis of 55 phenotypes, we detected 16 GxS and 6 GxG QTLs. The increase in the amount of phenotypic variance explained by models including GxS was small, ranging from 0.14% to 4.30%. We conclude that GxS rarely make a large overall contribution to the heritability of phenotypes, however there are cases where these will be individually important.

Yeast growth plasticity is regulated by environment-specific multi-QTL interactions

For a unicellular, non-motile organism like Saccharomyces cerevisiae, carbon sources act both as nutrients and as signaling molecules and consequently affect various fitness parameters including growth. It is therefore advantageous for yeast strains to adapt their growth to carbon source variation. The ability of a given genotype to manifest different phenotypes in varying environments is known as phenotypic plasticity. To identify quantitative trait loci (QTL) that drive plasticity in growth, two growth parameters (growth rate and biomass) were measured in a published dataset from meiotic recombinants of two genetically divergent yeast strains grown in different carbon sources. To identify QTL contributing to plasticity across pairs of environments, gene–environment interaction mapping was performed, which identified several QTL that have a differential effect across environments, some of which act antagonistically across pairs of environments. Multi-QTL analysis identified loci interacting with previously known growth affecting QTL as well as novel two-QTL interactions that affect growth. A QTL that had no significant independent effect was found to alter growth rate and biomass for several carbon sources through two-QTL interactions. Our study demonstrates that environment-specific epistatic interactions contribute to the growth plasticity in yeast. We propose that a targeted scan for epistatic interactions, such as the one described here, can help unravel mechanisms regulating phenotypic plasticity.

Fence Methods for Backcross Experiments

Model search strategies play an important role in finding simultaneous susceptibility genes that are associated with a trait. More particularly, model selection via the information criteria, such as the BIC with modifications, have received considerable attention in quantitative trait loci (QTL) mapping. However, such modifications often depend upon several factors, such as sample size, prior distribution, and the type of experiment, e.g., backcross, intercross. These changes make it difficult to generalize the methods to all cases. The fence method avoids such limitations with a unified approach, and hence can be used more broadly. In this paper, this method is studied in the case of backcross experiments throughout a series of simulation studies. The results are compared with those of the modified BIC method as well as some of the most popular shrinkage methods for model selection.

Mice with different susceptibility to tick-borne encephalitis virus infection show selective neutralizing antibody response and inflammatory reaction in the central nervous system

Background

The clinical course of tick-borne encephalitis (TBE), a disease caused by TBE virus, ranges from asymptomatic or mild influenza-like infection to severe debilitating encephalitis or encephalomyelitis. Despite the medical importance of this disease, some crucial steps in the development of encephalitis remain poorly understood. In particular, the basis of the disease severity is largely unknown.

Methods

TBE virus growth, neutralizing antibody response, key cytokine and chemokine mRNA production and changes in mRNA levels of cell surface markers of immunocompetent cells in brain were measured in mice with different susceptibilities to TBE virus infection.

Results

An animal model of TBE based on BALB/c-c-STS/A (CcS/Dem) recombinant congenic mouse strains showing different severities of the infection in relation to the host genetic background was developed. After subcutaneous inoculation of TBE virus, BALB/c mice showed medium susceptibility to the infection, STS mice were resistant, and CcS-11 mice were highly susceptible. The resistant STS mice showed lower and delayed viremia, lower virus production in the brain and low cytokine/chemokine mRNA production, but had a strong neutralizing antibody response. The most sensitive strain (CcS-11) failed in production of neutralizing antibodies, but exhibited strong cytokine/chemokine mRNA production in the brain. After intracerebral inoculation, all mouse strains were sensitive to the infection and had similar virus production in the brain, but STS mice survived significantly longer than CcS-11 mice. These two strains also differed in the expression of key cytokines/chemokines, particularly interferon gamma-induced protein 10 (IP-10/CXCL10) and monocyte chemotactic protein-1 (MCP-1/CCL2) in the brain.

Conclusions

Our data indicate that the genetic control is an important factor influencing the clinical course of TBE. High neutralizing antibody response might be crucial for preventing host fatality, but high expression of various cytokines/chemokines during TBE can mediate immunopathology and be associated with more severe course of the infection and increased fatality.

Independent genetic control of early and late stages of chemically induced skin tumors in a cross of a Japanese wild-derived inbred mouse strain, MSM/Ms

MSM/Ms is an inbred mouse strain derived from a Japanese wild mouse, Mus musculus molossinus. In this study, we showed that MSM/Ms mice exhibit dominant resistance when crossed with susceptible FVB/N mice and subjected to the two-stage skin carcinogenesis protocol using 7,12-dimethylbenz(a)anthracene (DMBA)/ 12-O-tetradecanoylphorbol-13-acetate (TPA). A series of F1 backcross mice were generated by crossing p53(+/+) or p53(+/-) F1 (FVB/N × MSM/Ms) males with FVB/N female mice. These generated 228 backcross animals, approximately half of which were p53(+/-), enabling us to search for p53-dependent skin tumor modifier genes. Highly significant linkage for papilloma multiplicity was found on chromosomes 6 and 7 and suggestive linkage was found on chromosomes 3, 5 and 12. Furthermore, in order to identify stage-dependent linkage loci we classified tumors into three categories (<2mm, 2-6mm and >6mm), and did linkage analysis. The same locus on chromosome 7 showed strong linkage in groups with <2mm or 2-6mm papillomas. No linkage was detected on chromosome 7 to papillomas >6mm, but a different locus on chromosome 4 showed strong linkage both to papillomas >6mm and to carcinomas. This locus, which maps near the Cdkn2a/p19(Arf) gene, was entirely p53-dependent, and was not seen in p53 (+/-) backcross animals. Suggestive linkage conferring susceptibility to carcinoma was also found on chromosome 5. These results clearly suggest distinct loci regulate each stage of tumorigenesis, some of which are p53-dependent.

Functional epistatic interaction between rs6046G>A in F7 and rs5355C>T in SELE modifies systolic blood pressure levels

Background

Although numerous genetic studies have been performed, only 0.9% of blood pressure phenotypic variance has been elucidated. This phenomenon could be partially due to epistatic interactions. Our aim was to identify epistatic interaction(s) associated with blood pressure levels in a pre-planned two-phase approach.

Methods and Results

In a discovery cohort composed of 3,600 French individuals, we found rs6046A allele in F7 associated with decreased blood pressure levels (P≤3.7×10⁻³) and rs5355T allele in SELE associated with decreased diastolic blood pressure levels (P = 5×10⁻³). Both variants interacted in order to influence blood pressure levels (P≤0.048). This interaction was replicated with systolic blood pressure in 4,620 additional European individuals (P = 0.03). Similarly, in this replication cohort, rs6046A was associated with decreased blood pressure levels (P≤8.5×10⁻⁴). Furthermore, in peripheral blood mononuclear cells of a subsample of 90 supposed healthy individuals, we found rs6046A positively associated with NAMPT mRNA levels (P≤9.1×10⁻⁵), suggesting an eventual involvement of NAMPT expression in blood pressure regulation. Confirming this hypothesis, further transcriptomic analyses showed that increased NAMPT mRNA levels were positively correlated with ICAM1, SELL, FPR1, DEFA1-3, and LL-37 genes expression (P≤5×10⁻³). The last two mRNA levels were positively associated with systolic blood pressure levels (P≤0.01) and explained 4% of its phenotypic variation.

Conclusion

These findings reveal the importance of epistatic interactions in blood pressure genetics and give new insights for the role of inflammation in its complex regulation.

Synchronizing allelic effects of opposing quantitative trait loci confirmed a major epistatic interaction affecting acute lung injury survival in mice

Increased oxygen (O₂) levels help manage severely injured patients, but too much for too long can cause acute lung injury (ALI), acute respiratory distress syndrome (ARDS) and even death. In fact, continuous hyperoxia has become a prototype in rodents to mimic salient clinical and pathological characteristics of ALI/ARDS. To identify genes affecting hyperoxia-induced ALI (HALI), we previously established a mouse model of differential susceptibility. Genetic analysis of backcross and F₂ populations derived from sensitive (C57BL/6J; B) and resistant (129X1/SvJ; X1) inbred strains identified five quantitative trait loci (QTLs; Shali1-5) linked to HALI survival time. Interestingly, analysis of these recombinant populations supported opposite within-strain effects on survival for the two major-effect QTLs. Whereas Shali1 alleles imparted the expected survival time effects (i.e., X1 alleles increased HALI resistance and B alleles increased sensitivity), the allelic effects of Shali2 were reversed (i.e., X1 alleles increased HALI sensitivity and B alleles increased resistance). For in vivo validation of these inverse allelic effects, we constructed reciprocal congenic lines to synchronize the sensitivity or resistance alleles of Shali1 and Shali2 within the same strain. Specifically, B-derived Shali1 or Shali2 QTL regions were transferred to X1 mice and X1-derived QTL segments were transferred to B mice. Our previous QTL results predicted that substituting Shali1 B alleles onto the resistant X1 background would add sensitivity. Surprisingly, not only were these mice more sensitive than the resistant X1 strain, they were more sensitive than the sensitive B strain. In stark contrast, substituting the Shali2 interval from the sensitive B strain onto the X1 background markedly increased the survival time. Reciprocal congenic lines confirmed the opposing allelic effects of Shali1 and Shali2 on HALI survival time and provide unique models to identify their respective quantitative trait genes and to critically assess the apparent bidirectional epistatic interactions between these major-effect loci.

Using mice to unveil the genetics of cancer resistance

In the UK, four in ten people will develop some form of cancer during their lifetime, with an individual's relative risk depending on many factors, including age, lifestyle and genetic make-up. Much research has gone into identifying the genes that are mutated in tumorigenesis with the overwhelming majority of genetically-modified (GM) mice in cancer research showing accelerated tumorigenesis or recapitulating key aspects of the tumorigenic process. Yet if six out of ten people will not develop some form of cancer during their lifetime, together with the fact that some cancer patients experience spontaneous regression/remission, it suggests there are ways of 'resisting' cancer. Indeed, there are wildtype, spontaneously-arising mutants and GM mice that show some form of 'resistance' to cancer. Identification of mice with increased resistance to cancer is a novel aspect of cancer research that is important in terms of providing both chemopreventative and therapeutic options. In this review we describe the different mouse lines that display a 'cancer resistance' phenotype and discuss the molecular basis of their resistance.

Most lung and colon cancer susceptibility genes are pair-wise linked in mice, humans and rats

Genetic predisposition controlled by susceptibility quantitative trait loci (QTLs) contributes to a large proportion of common cancers. Studies of genetics of cancer susceptibility, however, did not address systematically the relationship between susceptibility to cancers in different organs. We present five sets of data on genetic architecture of colon and lung cancer susceptibility in mice, humans and rats. They collectively show that the majority of genes for colon and lung cancer susceptibility are linked pair-wise and are likely identical or related. Four CcS/Dem recombinant congenic strains, each differing from strain BALB/cHeA by a different small random subset of ±12.5% of genes received from strain STS/A, suggestively show either extreme susceptibility or extreme resistance for both colon and lung tumors, which is unlikely if the two tumors were controlled by independent susceptibility genes. Indeed, susceptibility to lung cancer (Sluc) loci underlying the extreme susceptibility or resistance of such CcS/Dem strains, mapped in 226 (CcS-10×CcS-19)F2 mice, co-localize with susceptibility to colon cancer (Scc) loci. Analysis of additional Sluc loci that were mapped in OcB/Dem strains and Scc loci in CcS/Dem strains, respectively, shows their widespread pair-wise co-localization (P = 0.0036). Finally, the majority of published human and rat colon cancer susceptibility genes map to chromosomal regions homologous to mouse Sluc loci. 12/12 mouse Scc loci, 9/11 human and 5/7 rat colon cancer susceptibility loci are close to a Sluc locus or its homologous site, forming 21 clusters of lung and colon cancer susceptibility genes from one, two or three species. Our data shows that cancer susceptibility QTLs can have much broader biological effects than presently appreciated. It also demonstrates the power of mouse genetics to predict human susceptibility genes. Comparison of molecular mechanisms of susceptibility genes that are organ-specific and those with trans-organ effects can provide a new dimension in understanding individual cancer susceptibility.

Missing heritability and strategies for finding the underlying causes of complex disease

Although recent genome-wide studies have provided valuable insights into the genetic basis of human disease, they have explained relatively little of the heritability of most complex traits, and the variants identified through these studies have small effect sizes. This has led to the important and hotly debated issue of where the 'missing heritability' of complex diseases might be found. Here, seven leading geneticists offer their opinion about where this heritability is likely to lie, what this could tell us about the underlying genetic architecture of common diseases and how this could inform research strategies for uncovering genetic risk factors.

A locus on chromosome 8 controlling tumor regionality-a new type of tumor diversity in the mouse lung

Regional specificity of lung tumor formation has rarely been studied in mouse or human. By using crosses of strains semi-congenic for lung cancer susceptibility locus Sluc20, we have analyzed the genetic influences of Sluc20 and 5 other loci on tumor regionality in the mouse lung. We have mapped Sluc20 to a 27.92-MB proximal region of chromosome 8 and found that it controls the number and load of only those tumors that surround or are directly adjacent to the bronchi or bronchioli (peribronchial tumors). These tumors lie outside the bronchial basement membrane and tend to reach a larger size than the tumors at other locations in the lung. Similar to tumors of alveolar lineage at other locations, peribronchial tumors stain with SP-C but not CC10 antibody. The effects of Sluc20 alleles are additive because the number of peribronchial tumors in heterozygotes is intermediate. These findings show that tumor regionality in the mouse lung, which represents a novel level of lung tumor heterogeneity, is under specific genetic control. The identification of genes controlling lung tumor regionality will provide novel insights into the biology of lung tumors and potentially improve the possibilities of individualized prognosis and treatment in human lung cancer.

Epistatic interactions govern chemically-induced lung tumor susceptibility and Kras mutation site in murine C57BL/6J-ChrA/J chromosome substitution strains

Cancer susceptibility results from interactions between sensitivity and resistance alleles. We employed murine chromosome substitution strains to study how resistance alleles affected sensitive alleles during chemically-induced lung carcinogenesis. The C57BL/6J-Chr#(A/J) strains, constructed by selectively breeding sensitive A/J and resistant C57BL/6J (B6) mice, each contain one pair of A/J chromosomes within an otherwise B6 genome. Pas1, the major locus responsible for this differential strain response to urethane carcinogenesis, resides on Chr 6, but C57BL/6J-Chr6(A/J) mice (hereafter CSS-6) developed few tumors following a single urethane injection, which demonstrates epistatic interactions with other B6 alleles. CSS6 mice developed dozens of lung tumors after chronic urethane exposure, however, indicating that these epistatic interactions could be overcome by repeated carcinogen administration. Unlike A/J, but similar to B6 mice, CSS6 mice were resistant to lung carcinogenesis induced by 3-methylcholanthrene (MCA). Tumor multiplicity increased if BHT administration followed urethane exposure, showing that a Chr 6 gene(s) regulates sensitivity to chemically-induced tumor promotion. Unlike A/J tumors (predominantly codon 61 A-->T transversions), Kras mutations in tumors induced by urethane in CSS-6 mice were similar to B6 tumors (codon 61 A-->G transitions). DNA repair genes not located on Chr 6 may determine the nature of Kras mutations. CSS-6 mice are a valuable resource for testing the ability of candidate genes to modulate lung carcinogenesis.

ANALYSIS OF THEPar2MODIFIER OF PULMONARY ADENOMA FORMATION IN MICE

Inbred strains of mouse show various susceptibilities to spontaneous and chemical-induced lung tumorigenesis. Genetic analyses have revealed that lung tumor susceptibilities of inbred mouse strains are governed by quantitative trait loci (QLTs) located on multiple chromosomes. A major lung tumor resistance QLT, designated pulmonary adenoma resistance 2 (Par2), was mapped to the mouse chromosome 18 independently by several groups and accounted for up to 60% phenotype variance between susceptible A/J and more resistant BALB/c strains. The authors recently conducted studies to positionally clone the Par2 gene. This review summarizes the effort and progress towards the identification of Par2 candidates.

Strain-dependent differences in susceptibility to lung cancer in inbred mice exposed to mainstream cigarette smoke

It is becoming increasingly clear that genetic susceptibility is an important host factor determining the effects of exposure to a number of airborne particles and gases. Although numerous studies have identified a genetic component for spontaneous pulmonary tumor development and for chemically induced lung cancer (e.g., urethane) in mice, a systematic examination of murine inter-strain differences in response to cigarette smoke inhalation has not been conducted. We addressed this research gap by examining the strain distribution pattern of lung cancer in nine inbred strains of mice exposed to 258 mg/m(3) mainstream cigarette smoke for 5 months followed by 4 months of rest. Lung tumors were enumerated on fixed lungs visualized at low magnification and on serial step sections examined microscopically. With the low magnification examination, we observed statistically significant increases in the number of lung tumors in cigarette smoke-exposed A/J and the genetically-related A/HeJ mice (p<0.05). While fewer tumors were identified by the microscopic enumeration method, it confirmed that significant increases in lung tumors occurred only in A/J and A/HeJ mice exposed to cigarette smoke (p<0.05). Thus, as predicted by epidemiologic studies and animal experiments using chemically induced lung cancer models, these findings suggest that genetic host factors play a significant role in the pulmonary tumorigenic response of mice to mainstream cigarette smoke.

Review paper: the role of inflammation in mouse pulmonary neoplasia

Inflammation is a risk factor for the development of many types of neoplasia, including skin, colon, gastric, and mammary cancers, among others. Chronic pulmonary diseases, such as chronic bronchitis and asthma, predispose to lung neoplasia. We will review the mouse literature examining the role of inflammation in lung neoplasia, focusing specifically on genetic susceptibility, pharmacologic modulation of inflammatory pathways, and both transgenic and knockout mouse models used to assess pro- and anti-inflammatory pathways involved in lung neoplasia. Identification of molecular mechanisms that govern the association between inflammation and pulmonary neoplasia could provide novel preventive, diagnostic, and therapeutic strategies for a disease in which few biomarkers currently exist.

Genetic influences on growth and body composition in mice: multilocus interactions

BACKGROUND

The genetic architecture of body weight and body composition is complex because these traits are normally influenced by multiple genes and their interactions, even after controlling for the environment. Bayesian methodology provides an efficient way of estimating these interactions.

SUBJECTS AND MEASUREMENTS

We used Bayesian model selection techniques to simultaneously estimate the main effects, epistasis and gene-sex interactions on age-related body weight (at 3, 6 and 10 weeks, denoted as WT3wk, WT6wk and WT10wk) and body composition (organ weights and fat-related traits) in an F(2) sample obtained from a cross between high-growth (M16i) mice and low-growth (L6) mice.

RESULTS

We observed epistatic and main-effect quantitative trait loci (QTL) that controlled both body weight and body composition. Epistatic effects were generally more significant for WT6wk than WT10wk. Chromosomes 5 and 13 interacted strongly to control body weight at 3 weeks. A pleiotropic QTL on chromosome 2 was associated with body weight and some body composition phenotypes. Testis weight was regulated by a QTL on chromosome 13 with a significantly large main effect (2log(e)BF approximately 15).

CONCLUSION

By analyzing epistatic interactions, we detected QTL not found in a previous analysis of this mouse population. Hence, the detection of gene-gene interactions may provide new information about the genetic architecture of complex obesity-related traits and may lead to the detection of additional obesity genes.

Unraveling epistasis with triple testcross progenies of near-isogenic lines

Libraries of near-isogenic lines (NILs) are a powerful plant genetic resource to map quantitative trait loci (QTL). Nevertheless, QTL mapping with NILs is mostly restricted to genetic main effects. Here we propose a two-step procedure to map additive-by-additive digenic epistasis with NILs. In the first step, a generation means analysis of parents, their F(1) hybrid, and one-segment NILs and their triple testcross (TTC) progenies is used to identify in a one-dimensional scan loci exhibiting QTL-by-background interactions. In a second step, one-segment NILs with significant additive-by-additive background interactions are used to produce particular two-segment NILs to test for digenic epistatic interactions between these segments. We evaluated our approach by analyzing a random subset of a genomewide Arabidopsis thaliana NIL library for growth-related traits. The results of our experimental study illustrated the potential of the presented two-step procedure to map additive-by-additive digenic epistasis with NILs. Furthermore, our findings suggested that additive main effects as well as additive-by-additive digenic epistasis strongly influence the genetic architecture underlying growth-related traits of A. thaliana.

The genetic basis of psoriasis

For a complex genetic disease, psoriasis has a high penetration within families and a concordance rate of up to 70% in identical twins. Despite this and the endeavors of many research groups for more than a decade, no susceptibility allele has so far been unequivocally identified, although about 20 genetic loci associated with psoriasis have been reported from linkage-based studies. Moreover, only 1 of these linkage-based loci, PSORS1, that includes the HLA-C gene on chromosome 6p21, has been universally confirmed. Very recent data strongly indicate that HLA-Cw*0602 is the susceptibility allele in this locus, a finding that is consistent with the notion that the pathogenesis of psoriasis involves autoantigen recognition by epidermal CD8+ T lymphocytes. Several candidate genes in some of the other 7 PSORS designated loci are currently being evaluated. The relative lack of success in elucidating the genetic basis of psoriasis highlights the formidable challenge of dissecting the genetic basis of diseases with a complex mode of inheritance.

Association of KRAS polymorphisms with risk for lung adenocarcinoma accompanied by atypical adenomatous hyperplasias

The pulmonary adenoma susceptibility 1 (Pas1) gene affects susceptibility to the development of lung adenomas in mice with a subset of the adenomas progressing to adenocarcinoma (ADC). In this study, genotype distributions for 10 polymorphisms in the human counterparts for three mouse candidate Pas1 genes, KRAS, CASC1/LAS1 and LRMP, were examined in a hospital-based case-control study consisting of 364 lung ADC cases and 253 controls. All the ADC cases were subjected to lobectomy and subsequent pathological investigation of atypical adenomatous hyperplasia (AAH), a putative precursor for peripheral lung ADC, including bronchioloalveolar carcinoma, in the resected lobes. Eighty-one (22%) of the ADC cases carried at least one AAH lesion in addition to the primary ADC and 34 (9%) of them carried multiple AAH lesions. None of the 10 polymorphisms examined showed significant associations with overall lung ADC risk (P > 0.05). However, minor allele carriers for two polymorphisms in the KRAS gene, KRAS-1 and -6, showed significantly increased odds ratios (ORs) for ADC accompanied by multiple AAHs [OR = 3.0; 95% confidence interval (CI) = 1.4-6.2, P = 0.004 and OR = 2.4; 95% CI = 1.1-4.7, P = 0.02, respectively]. Minor haplotypes including the minor allele for the KRAS-6 polymorphism showed increased ORs for ADC accompanied by multiple AAHs, and KRAS transcripts from the minor allele for this polymorphism were more abundantly detected in lung tissues than those from the major allele. Thus, KRAS polymorphisms were indicated to be involved in risk for the development of AAHs that progress to ADC by causing differential KRAS oncogene expression in the lungs.

Extending the modified bayesian information criterion (mBIC) to dense markers and multiple interval mapping

SUMMARY

The modified version of Bayesian Information Criterion (mBIC) is a relatively simple model selection procedure that can be used when locating multiple interacting quantitative trait loci (QTL). Our earlier work demonstrated the statistical properties of mBIC for situations where the average genetic map interval is at least 5 cM. In this work mBIC is adapted to genome searches based on a dense map and, more importantly, to the situation where consecutive QTL and interactions are located by multiple interval mapping. Easy to use formulas for the extended mBIC are given. A simulation study, as well as the analysis of real data, confirm the good properties of the extended mBIC.

Chromosomal changes in high- and low-invasive mouse lung adenocarcinoma cell strains derived from early passage mouse lung adenocarcinoma cell strains

The incidence of adenocarcinoma of the lung is increasing in the United States, however, the difficulties in obtaining lung cancer families and representative samples of early to late stages of the disease have lead to the study of mouse models for lung cancer. We used Spectral Karyotyping (SKY), mapping with fluorescently labeled genomic clones (FISH), comparative genomic hybridization (CGH) arrays, gene expression arrays, Western immunoblot and real time polymerase chain reaction (PCR) to analyze nine pairs of high-invasive and low-invasive tumor cell strains derived from early passage mouse lung adenocarcinoma cells to detect molecular changes associated with tumor invasion. The duplication of chromosomes 1 and 15 and deletion of chromosome 8 were significantly associated with a high-invasive phenotype. The duplication of chromosome 1 at band C4 and E1/2-H1 were the most significant chromosomal changes in the high-invasive cell strains. Mapping with FISH and CGH array further narrowed the minimum region of duplication of chromosome 1 to 71-82 centimorgans (cM). Expression array analysis and confirmation by real time PCR demonstrated increased expression of COX-2, Translin (TB-RBP), DYRK3, NUCKS and Tubulin-alpha4 genes in the high-invasive cell strains. Elevated expression and copy number of these genes, which are involved in inflammation, cell movement, proliferation, inhibition of apoptosis and telomere elongation, were associated with an invasive phenotype. Similar linkage groups are altered in invasive human lung adenocarcinoma, implying that the mouse is a valid genetic model for the study of the progression of human lung adenocarcinoma.

Control of lymphocyte infiltration of lung tumors in mice by host's genes: mapping of four Lynf (lymphocyte infiltration) loci

Tumor infiltration by lymphocytes is essential for cell-mediated immune elimination of tumors in experimental systems and in immunotherapy of cancer. Presence of lymphocytes in several human cancers has been associated with a better prognosis. We present evidence that individual propensity to tumor infiltration is genetically controlled. Infiltrating lymphocytes are present in 50% of lung tumors in O20/A mice, but in only 10% of lung tumors in OcB-9/Dem mice. This difference has been consistent in experiments conducted over 8 years in two different animal facilities. To test whether this strain difference is controlled genetically, we analyzed the presence of infiltrating lymphocytes in N-ethyl-N-nitroso-urea (ENU) induced lung tumors in (O20 x OcB-9) F(2) hybrids. We mapped four genetic loci, Lynf1 (Lymphocyte infiltration 1), Lynf2, Lynf3, and Lynf4 that significantly modify the presence and intensity of intra-tumoral infiltrates containing CD4(+) and CD8(+) T lymphocytes. These loci appear to be distinct from the genes encoding the molecules that are presently implicated in lymphocyte infiltration. Our findings open a novel approach for the assessment of individual propensity for tumor infiltration by genotyping the genes of the host that influence this process using DNA from any normal tissue. Such prediction of probability of tumor infiltration in individual cancer patients could help considerably to assess their prognosis and to decide about the application and the type of immunotherapy.

Identification of novel modifier loci of Apc Min affecting mammary tumor development

Genetic background affects the susceptibility to mammary tumor development in Apc(Min/+) mice. Here we report the identification of four novel modifier loci that influence different aspects of mammary tumor development in Apc(Min/+) mice. Analysis of tumor development in a backcross of (FVBB6 Apc(Min/+)) x B6 Apc(Min/+) mice has identified a modifier on chromosome 9 that significantly affects tumor multiplicity, and a modifier on chromosome 4 that significantly affects tumor latency and affects tumor number with suggestive significance. This modifier was also identified in a backcross involving 129X1/SvJ and B6 Apc(Min/+) mice. A modifier on chromosome 18 specifically affects tumor latency but not tumor number. Kaplan-Meier analysis suggests there is at least an additive interaction affecting tumor latency between the loci on chromosomes 4 and 18. We also identified a modifier locus on chromosome 6 that interacts with the loci on chromosome 4 and chromosome 9 to affect tumor number. These results suggest that multiple genetic loci control different aspects of mammary tumor development. None of these modifiers is associated with intestinal tumor susceptibility, which indicates that these modifiers act on tumor development in a tissue-specific manner.

Mapping QTLs with digenic epistasis under multiple environments and predicting heterosis based on QTL effects

Mixed linear model approach was proposed for mapping QTLs with the digenic epistasis and QTL by environment (QE) interaction as well as additive and dominant effects. Monte Carlo simulations indicated that the proposed method could provide unbiased estimations for both positions and genetic main effects of QTLs, as well as unbiased predictions for QE interaction effects. A method was suggested for predicting heterosis based on individual QTL effects. The immortalized F(2) (IF(2)) population constructed by random mating among RI or DH lines is appropriate for mapping QTLs with epistasis and their QE interaction. Based on the models and methodology proposed, we developed a QTL mapping software, QTLMapper 2.0 on the basis of QTLmapper 1.0, which is suitable for analyzing populations of DH, RIL, F(2) and IF(2). Data of thousand grain weight of IF(2) population with 240 lines derived from elite hybrid rice Shanyou 63 were analyzed as a worked example.

New chemically induced skin tumour susceptibility loci identified in a mouse backcross between FVB and dominant resistant PWK

Background

A variety of skin cancer susceptibility among mouse strains has allowed identification of genes responsible for skin cancer development. Fifteen Skts loci for skin tumour susceptibility have been mapped so far by using the two-stage skin carcinogenesis model [induced by 7.12-dimethylbenz(a)anthracene (DMBA)/12-O-tetradecanoylphorbol-13-acetate (TPA)]. A few responsible genes have been identified using wild-derived dominant resistant Mus spretus mice, and one has been confirmed as a low penetrance cancer susceptibility gene in a variety of human cancers.

Results

In the present study, we found that wild-derived PWK mice developed no tumour by treatment with the two-stage skin carcinogenesis protocol. This phenotype is dominant resistant when crossed with the highly susceptible strain FVB. By analyzing the F1 backcross generation between PWK and FVB, we found empirical evidence of significant linkage at the new loci Skts-fp1 on chromosome 4 and suggestive linkage on chromosomes 1, 3, 11, 12 and 14 for skin tumour susceptibility. Skts-fp1 includes the Skts7 interval, which was previously mapped by a Mus spretus and NIH backcross. We also observed suggestive linkage on chromosomes 1 and 2 in the female population only, while suggestive linkage on chromosomes 14 and 15 only was observed in the male population. A significant genetic interaction was seen between markers of D11Mit339 and D16Mit14.

Conclusion

Analysis of this new cross may facilitate the identification of genes responsible for mouse skin cancer susceptibility and may reveal their biological interactions.

Mapping the genetic architecture of complex traits in experimental populations

SUMMARY

Understanding how interactions among set of genes affect diverse phenotypes is having a greater impact on biomedical research, agriculture and evolutionary biology. Mapping and characterizing the isolated effects of single quantitative trait locus (QTL) is a first step, but we also need to assemble networks of QTLs and define non-additive interactions (epistasis) together with a host of potential environmental modulators. In this article, we present a full-QTL model with which to explore the genetic architecture of complex trait in multiple environments. Our model includes the effects of multiple QTLs, epistasis, QTL-by-environment interactions and epistasis-by-environment interactions. A new mapping strategy, including marker interval selection, detection of marker interval interactions and genome scans, is used to evaluate putative locations of multiple QTLs and their interactions. All the mapping procedures are performed in the framework of mixed linear model that are flexible to model environmental factors regardless of fix or random effects being assumed. An F-statistic based on Henderson method III is used for hypothesis tests. This method is less computationally greedy than corresponding likelihood ratio test. In each of the mapping procedures, permutation testing is exploited to control for genome-wide false positive rate, and model selection is used to reduce ghost peaks in F-statistic profile. Parameters of the full-QTL model are estimated using a Bayesian method via Gibbs sampling. Monte Carlo simulations help define the reliability and efficiency of the method. Two real-world phenotypes (BXD mouse olfactory bulb weight data and rice yield data) are used as exemplars to demonstrate our methods.

AVAILABILITY

A software package is freely available at http://ibi.zju.edu.cn/software/qtlnetwork

Fine mapping and candidate gene analyses of pulmonary adenoma resistance 1, a major genetic determinant of mouse lung adenoma resistance

Pulmonary adenoma resistance 1 (Par1) is a major genetic determinant of mouse lung adenoma resistance. Although Par1 was previously mapped to mouse chromosome 11 by conventional linkage analyses, its candidate region was broad and undefined. In our present study, we generated Par1 congenic mice using two mouse strains A/J (Par1/-) and Mus spretus (Par1/+). Analyzing these congenic mice enabled us to fine map the Par1 quantitative trait loci (QTL) into a 2.0-cM (2.2 Mb) chromosomal region between genetic marker D11Mit70 and the gene Hoxb9. We then conducted systematic candidate gene screening through nucleotide polymorphism and expression analyses. Genes showing differential lung tissue expression or carrying nonsynonymous single nucleotide polymorphisms were identified and discussed. In particular, we evaluated tumor suppressor gene Tob1 for its Par1 candidacy. Our findings have narrowed the Par1 QTL region and will greatly facilitate the identification of the major genetic determinant of mouse lung adenoma resistance.

Genetic mapping of a new heart rate QTL on chromosome 8 of spontaneously hypertensive rats

Background

Tachycardia is commonly observed in hypertensive patients, predominantly mediated by regulatory mechanisms integrated within the autonomic nervous system. The genetic loci and genes associated with increased heart rate in hypertension, however, have not yet been identified.

Methods

An F2 intercross of Spontaneously Hypertensive Rats (SHR) × Brown Norway (BN) linkage analysis of quantitative trait loci mapping was utilized to identify candidate genes associated with an increased heart rate in arterial hypertension.

Results

Basal heart rate in SHR was higher compared to that of normotensive BN rats (365 ± 3 vs. 314 ± 6 bpm, p < 0.05 for SHR and BN, respectively). A total genome scan identified one quantitative trait locus in a 6.78 cM interval on rat chromosome 8 (8q22–q24) that was responsible for elevated heart rate. This interval contained 241 genes, of which 65 are known genes.

Conclusion

Our data suggest that an influential genetic region located on the rat chromosome 8 contributes to the regulation of heart rate. Candidate genes that have previously been associated with tachycardia and/or hypertension were found within this QTL, strengthening our hypothesis that these genes are, potentially, associated with the increase in heart rate in a hypertension rat model.

Efficiency of triple test cross for detecting epistasis with marker information

The triple test cross (TTC) is an experimental design for detecting epistasis and estimating the components of genetic variance for quantitative traits. In this paper, we extend the analysis to include molecular information. The statistical power of the mating design was assessed under a model assuming that a finite number of loci affect the trait in question. Formulae are developed for the analysis with or without marker information relating to the recombination fraction between loci, the genetical properties of quantitative trait controlled by the quantitative trait loci (QTL), the linkage phases of the parents and population size. Application of these formulae showed that the recombination fraction between genes and the magnitude and the types of epistasis have important interactions in their effects on power. The results demonstrate that the TTC may have increased power to detect epistasis when marker information is present. However, the simulation experiments show that the standard deviation of the estimated expected mean square was higher with one marker than that with two, whereas the corresponding value without marker information was the lowest. In addition, we demonstrate that the relative position of QTL and markers and the number of markers can both affect the power of epistatic detection.

Convergence of congenic mapping and allele-specific alterations in tumors for the resolution of the Skts1 skin tumor susceptibility locus

Although several familial cancer genes with high-penetrance mutations have been identified, the major genetic component of susceptibility to sporadic cancers is attributable to low-penetrance alleles. These 'weak' tumor susceptibility genes do not segregate as single Mendelian traits and are therefore difficult to find in studies of human populations. Previously, we have proposed that a combination of germline mapping and analysis of allele-specific imbalance in tumors may be used to refine the locations of susceptibility genes using mouse models of cancer. Here, we have used linkage analysis and congenic mouse strains to map the major skin tumor susceptibility locus Skts1 within a genetic interval of 0.9 cM on proximal chromosome 7. This interval lies in an apparent recombination cold spot, and corresponds to a physical distance of about 15 Mb. We therefore, used patterns of allele-specific imbalances in tumors from backcross and congenic mice to refine the location of Skts1. We demonstrate that this single tumor modifier locus has a dramatic effect on the allelic preference for imbalance on chromosome 7, with at least 90% of tumors from the congenics showing preferential gain of markers on the chromosome carrying the susceptibility variant. Importantly, these alterations enabled us to refine the location of Skts1 at higher resolution than that attained using the congenic mice. We conclude that low-penetrance susceptibility genes can have strong effects on patterns of allele-specific somatic genetic changes in tumors, and that analysis of the directionality of these somatic events provides an important and rapid route to identification of germline genetic variants that confer increased cancer risk.

Mouse genetic model for antigen-induced airway manifestations of asthma

Allergic asthma is a genetically complex disease characterized by allergen-specific immunoglobulin (Ig)E, eosinophilic inflammation of the lungs and airway hyper-responsiveness to bronchospasmogenic stimuli. In this study, we compared 13 recombinant congenic (RC) mouse strains in an ovalbumin model of allergic asthma. Different intensities and types of responses are observed throughout the RC strains. Intensities range from resistance to asthma in CcS05, to a very severe bronchoconstrictive reaction upon methacholine challenge for the parental STS strain. All strains show a 'modified' Th2 response except CcS14, which shows a 'true' Th2 response. When data from all strains are pooled, airway reactivity shows significant correlations with the serum Ig levels and the levels of interleukin (IL)-4, IL-5 and IL-13 in the broncho-alveolar lavage (BAL), at low dosage of methacholine (below 25 mg/ml), whereas at high dosage airway reactivity only correlates with BAL neutrophil levels. This indicates that at least two different mechanisms are involved in the airway reactivity to methacholine. None of these correlations can be found in every individual strain, which demonstrates that the asthma traits in this mouse model are genetically dissociated and that the loci can be genetically mapped.

Two-dimensional genome-scan identifies novel epistatic loci for essential hypertension

It is well established that gene interactions influence common human diseases, but to date linkage studies have been constrained to searching for single genes across the genome. We applied a novel approach to uncover significant gene-gene interactions in a systematic two-dimensional (2D) genome-scan of essential hypertension. The study cohort comprised 2076 affected sib-pairs and 66 affected half-sib-pairs of the British Genetics of HyperTension study. Extensive simulations were used to establish significance thresholds in the context of 2D genome-scans. Our analyses found significant and suggestive evidence for loci on chromosomes 5, 9, 11, 15, 16 and 19, which influence hypertension when gene-gene interactions are taken into account (5q13.1 and 11q22.1, two-locus lod score=5.72; 5q13.1 and 19q12, two-locus lod score=5.35; 9q22.3 and 15q12, two-locus lod score=4.80; 16p12.3 and 16q23.1, two-locus lod score=4.50). For each significant and suggestive pairwise interaction, the two-locus genetic model that best fitted the data was determined. Regions that were not detected using single-locus linkage analysis were identified in the 2D scan as contributing significant epistatic effects. This approach has discovered novel loci for hypertension and offers a unique potential to use existing data to uncover novel regions involved in complex human diseases.

Mouse model for analysis of non-MHC genes that influence allogeneic response: recombinant congenic strains of OcB/Dem series that carry identical H2 locus

Alloreactivity is the strongest known primary immune response. Its clinical manifestations are graft rejection, graft-versus-host disease and graft-versus-leukemia effect. The strongest stimulation by allogeneic cells is due to incompatibility at the major histocompatibility complex (MHC) genes. However, the non-MHC genes also participate in allogeneic response. Here we present a mouse model for study of the role of non-MHC genes in regulation of alloreactivity and show that they besides encoding antigens also regulate the responsiveness. Recombinant congenic strains (RCS) of O20/A (O20)-c-B10.O20/Dem (OcB/Dem) series have been derived from the parental strains O20 and B10.O20, which carry identical MHC haplotypes (H2pz) and therefore their differences in alloantigen response depend only on non-MHC genes. We have tested a MLR response by spleen cells of the strains O20, B10.O20, and 16 OcB/Dem strains through stimulation by cells from strains C57BL/10 (H2b), BALB/c (H2d), CBA (H2k), and DBA/1 (H2q) alloantigens. Proliferative response of O20, B10.O20 and OcB/Dem strains to these four alloantigens exhibited a similar but not completely identical pattern of reactivity. The responses to different alloantigens were highly correlated: C57BL/10-BALB/c r = 0.87, C57BL/10-CBA r = 0.84, C57BL/10-DBA/1 r = 0.83. Cluster analysis of the responses by O20, B10.O20, and OcB mice identified groups of strains with distinct patterns of response. This data shows that two main types of genes influence MLR: 1. structural genes for major and minor alloantigens and 2. genes regulating T-cell receptor signal transduction or mediating costimulatory signals by antigen-presenting cells.

Gender-specific polygenic control of ethylnitrosourea-induced oncogenesis in the rat peripheral nervous system

The inbred BD rat strains constitute a model system for analysis of the genetic basis of susceptibility or resistance to the development of neural tumors, as they exhibit distinct strain-specific differences regarding the sensitivity to tumor induction by the alkylating carcinogen N-ethyl-N-nitrosourea (EtNU). Among the different BD strains, BDIX and BDIV rats, respectively, are either highly susceptible or entirely resistant to the development of EtNU-induced malignant schwannomas of the peripheral nervous system (PNS), predominantly of the trigeminal nerves. We have previously mapped one locus associated with susceptibility/resistance to schwannoma induction to the telomeric third of chromosome 10 (Mss1) in segregating (BDIX x BDIV) crosses. We report on the genetic mapping of 6 further loci controlling tumor incidence or survival time on chromosomes 1 (Mss2), 3 (Mss3), 6 (Mss4), 13 (Mss5) and 15 (Mss6) as well as on chromosome 10 (Mss7) close to the centromere. Interestingly, most of these loci mediate gender-specific effects of variable strength ranging from minor influences on tumor development to complete tumor resistance. The gender specificity is reflected by the fact that male (BDIX x BDIV) F2 rats exhibit a 2-fold higher incidence of EtNU-induced schwannomas than females as well as a shorter survival time. A number of human nervous system tumors too arise with a marked gender bias. Genes mediating gender-specific predisposition of developing malignant schwannomas in the rat may be relevant for the human individual risk of developing nervous system tumors.

Hepatocellular carcinoma as a complex polygenic disease. Interpretive analysis of recent developments on genetic predisposition

The different frequency of hepatocellular carcinoma (HCC) in humans at risk suggests a polygenic predisposition. However, detection of genetic variants is difficult in genetically heterogeneous human population. Studies on mouse and rat models identified 7 hepatocarcinogenesis susceptibility (Hcs) and 2 resistance (Hcr) loci in mice, and 7 Hcs and 9 Hcr loci in rats, controlling multiplicity and size of neoplastic liver lesions. Six liver neoplastic nodule remodeling (Lnnr) loci control number and volume of re-differentiating lesions in rat. A Hcs locus, with high phenotypic effects, and various epistatic gene-gene interactions were identified in rats, suggesting a genetic model of predisposition to hepatocarcinogenesis with different subset of low-penetrance genes, at play in different subsets of population, and a major locus. This model is in keeping with human HCC epidemiology. Several putative modifier genes in rodents, deregulated in HCC, are located in chromosomal segments syntenic to sites of chromosomal aberrations in humans, suggesting possible location of predisposing loci. Resistance to HCC is associated with lower genomic instability and downregulation of cell cycle key genes in preneoplastic and neoplastic lesions. p16(INK4A) upregulation occurs in susceptible and resistant rat lesions. p16(INK4A)-induced growth restraint was circumvented by Hsp90/Cdc37 chaperons and E2f4 nuclear export by Crm1 in susceptible, but not in resistant rats and human HCCs with better prognosis. Thus, protective mechanisms seem to be modulated by HCC modifiers, and differences in their efficiency influence the susceptibility to hepatocarcinogenesis and probably the prognosis of human HCC.

Lung tumor location and lymphocyte infiltration in mice are genetically determined

Lung cancer is a heterogeneous disease with individual differences in histological type, rate of progression, and response to therapy. Definition of the molecular and genetic basis of specific tumor characteristics would provide a better assessment of prognosis and a basis for a more individualized therapy. Here the authors compare the quantitative and qualitative phenotypes of lung tumors in mice of O20/A and OcB-9/Dem strains subjected to 2 regimens of N-ethyl-N-nitrosourea (ENU) treatment: (1) prenatal tumor induction by a single intraperitoneal (IP) injection of 40 mg/kg body weight into pregnant females and (2) after the same prenatal induction, the progeny received on weeks 9 and 11 additional IP ENU injections. The numbers, size, and histological characteristics of tumors were determined microscopically in semiserial lung sections. Unexpectedly, the authors observed very highly significant strain differences in a novel polymorphic phenotype-peribronchial versus nonperibronchial location of lung tumors, as well as in frequency of lymphocyte infiltration. To assess the reproducibility of these genetic differences, the authors classified both tumor location and lymphocyte infiltration also in an independent set of lung tumors that were induced in these strains in experiments performed more than 10 years ago in a different mouse facility and found the same strain differences. These results indicate that these qualitative phenotypes are very robust (P(c) 5.52 x 10(-6) and 2.27 x 10(-8), respectively) and relatively independent of environmental influences. They likely reflect different stages of lung differentiation at the time of tumor induction and differences in molecules involved in intercellular signaling, respectively. The definition of genes controlling these traits will provide novel insights into the determination of tumor phenotype.

Simultaneous mapping of epistatic QTL in DU6i × DBA/2 mice

We have mapped epistatic quantitative trait loci (QTL) in an F2 cross between DU6i x DBA/2 mice. By including these epistatic QTL and their interaction parameters in the genetic model, we were able to increase the genetic variance explained substantially (8.8%-128.3%) for several growth and body composition traits. We used an analysis method based on a simultaneous search for epistatic QTL pairs without assuming that the QTL had any effect individually. We were able to detect several QTL that could not be detected in a search for marginal QTL effects because the epistasis cancelled out the individual effects of the QTL. In total, 23 genomic regions were found to contain QTL affecting one or several of the traits and eight of these QTL did not have significant individual effects. We identified 44 QTL pairs with significant effects on the traits, and, for 28 of the pairs, an epistatic QTL model fit the data significantly better than a model without interactions. The epistatic pairs were classified by the significance of the epistatic parameters in the genetic model, and visual inspection of the two-locus genotype means identified six types of related genotype-phenotype patterns among the pairs. Five of these patterns resembled previously published patterns of QTL interactions.

Methods for predicting superior genotypes under multiple environments based on QTL effects

Methods were developed for predicting two kinds of superior genotypes (superior line and superior hybrid) based on quantative trait locus (QTL) effects including epistatic and QTL x environment interaction effects. Formulae were derived for predicting the total genetic effect of any individual with known QTLs genotype derived from the mapping population in a specific environment. Two algorithms, enumeration algorithm and stepwise tuning algorithm, were used to select the best multi-locus combination of all the putative QTLs. Grain weight per plant (GW) in rice was analyzed as a working example to demonstrate the proposed methods. Results showed that the predicted superior lines and superior hybrids had great superiorities over the F(1) hybrid, indicating large breeding potential remained for further improvement on GW. Results also showed that epistatic effects and their interaction with environments largely contributed to the superiorities of the predicted superior lines and superior hybrids. User-friendly software, QTLNetwork, version 1.0, was developed based on the methods in the present paper.

Modifying the Schwarz Bayesian information criterion to locate multiple interacting quantitative trait loci

The problem of locating multiple interacting quantitative trait loci (QTL) can be addressed as a multiple regression problem, with marker genotypes being the regressor variables. An important and difficult part in fitting such a regression model is the estimation of the QTL number and respective interactions. Among the many model selection criteria that can be used to estimate the number of regressor variables, none are used to estimate the number of interactions. Our simulations demonstrate that epistatic terms appearing in a model without the related main effects cause the standard model selection criteria to have a strong tendency to overestimate the number of interactions, and so the QTL number. With this as our motivation we investigate the behavior of the Schwarz Bayesian information criterion (BIC) by explaining the phenomenon of the overestimation and proposing a novel modification of BIC that allows the detection of main effects and pairwise interactions in a backcross population. Results of an extensive simulation study demonstrate that our modified version of BIC performs very well in practice. Our methodology can be extended to general populations and higher-order interactions.