While many cancers show a sex bias, the genetic basis and molecular mechanisms underlying sex bias are not always clear. Astrocytoma and glioblastoma show male predominance in humans. We have shown previously that glial tumors forming in the Nf1−/+; Trp53−/+cis (NPcis) mouse model also show a sex bias in some genetic contexts. Using cross-species comparisons we have identified candidate male-specific modifiers of astrocytoma/glioblastoma. Linkage analysis of B6X(B6X129)-NPcis mice identifies a modifier of astrocytoma resistance specific to males, named Arlm1, on distal mouse Chr 12. Arlm1 is syntenic to human Chr 7p15, 7p21, 7q36, and 14q32 regions that are altered in human glioblastoma. A subset of these genes shows male-specific correlations to glioblastoma patient survival time and represents strong candidates for the Arlm1 modifier gene. Identification of male-specific modifier genes will lead to a better understanding of the molecular basis of male predominance in astrocytoma and glioblastoma.

Despite advances in genetic mapping of quantitative traits and in phylogenetic comparative approaches, these two perspectives are rarely combined. The joint consideration of multiple crosses among related taxa (whether species or strains) not only allows more precise mapping of the genetic loci (called quantitative trait loci, QTL) that contribute to important quantitative traits, but also offers the opportunity to identify the origin of a QTL allele on the phylogenetic tree that relates the taxa. We describe a formal method for combining multiple crosses to infer the location of a QTL on a tree. We further discuss experimental design issues for such endeavors, such as how many crosses are required and which sets of crosses are best. Finally, we explore the method’s performance in computer simulations, and we illustrate its use through application to a set of four mouse intercrosses among five inbred strains, with data on HDL cholesterol.

Alleles derived from skin tumor−resistant Car-R mice provide resistance to both skin and lung tumorigenesis over the susceptibility of the SWR/J strain. In an effort to map tumor modifier loci affecting both tumor types, we carried out a genetic linkage analysis in backcross SWR/J x (SWR/J x Car-R) mice and identified a locus (Lsktm1) on chromosome 1 linked to both skin (LOD score = 3.93) and lung (LOD score = 8.74) tumorigenesis. Two genes, Igfbp5 and Igfbp2, residing in this locus and belonging to the insulin-like growth factor binding protein family were expressed at significantly greater levels in normal lung tissue from cancer-resistant Car-R mice than in cancer-susceptible SWR/J mice. Overexpression of the recombinant Igfbp5 and Igfbp2 genes in two lung cancer cell lines significantly inhibited clonogenicity (P < 0.0001). Collectively, we have identified a single polymorphic locus that affects skin and lung tumorigenesis and identify Igfbp5 and Igfbp2 as candidate modifier genes of lung tumorigenesis.

Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key importance. One approach, randomly allocating observed QTL across the genomic locations separately by trait, implicitly assumes all traits are uncorrelated. Recently, an empirical test for QTL hotspots was proposed on the basis of the number of traits that exceed a predetermined LOD value, such as the standard permutation LOD threshold. The permutation null distribution of the maximum number of traits across all genomic locations preserves the correlation structure among the phenotypes, avoiding the detection of spurious hotspots due to nongenetic correlation induced by uncontrolled environmental factors and unmeasured variables. However, by considering only the number of traits above a threshold, without accounting for the magnitude of the LOD scores, relevant information is lost. In particular, biologically interesting hotspots composed of a moderate to small number of traits with strong LOD scores may be neglected as nonsignificant. In this article we propose a quantile-based permutation approach that simultaneously accounts for the number and the LOD scores of traits within the hotspots. By considering a sliding scale of mapping thresholds, our method can assess the statistical significance of both small and large hotspots. Although the proposed approach can be applied to any type of heritable high-volume “omic” data set, we restrict our attention to expression (e)QTL analysis. We assess and compare the performances of these three methods in simulations and we illustrate how our approach can effectively assess the significance of moderate and small hotspots with strong LOD scores in a yeast expression data set.

Summary: xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator.

Availability: xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org.

Contact: m.a.swertz@rug.nl

The mouse Collaborative Cross (CC) is a panel of eight-way recombinant inbred lines: eight diverse parental strains are intermated, followed by repeated sibling mating, many times in parallel, to create a new set of inbred lines whose genomes are random mosaics of the genomes of the original eight strains. Many generations are required to reach inbreeding, and so a number of investigators have sought to make use of phenotype and genotype data on mice from intermediate generations during the formation of the CC lines (so-called pre-CC mice). The development of a hidden Markov model for genotype reconstruction in such pre-CC mice, on the basis of incompletely informative genetic markers (such as single-nucleotide polymorphisms), formally requires the two-locus genotype probabilities at an arbitrary generation along the path to inbreeding. In this article, I describe my efforts to calculate such probabilities. While closed-form solutions for the two-locus genotype probabilities could not be derived, I provide a prescription for calculating such probabilities numerically. In addition, I present a number of useful quantities, including single-locus genotype probabilities, two-locus haplotype probabilities, and the fixation probability and map expansion at each generation along the course to inbreeding.

Advanced intercross populations, in which multiple inbred strains are mated at random for many generations, have the advantage of greater precision of genetic mapping because of the accumulation of recombination events across the multiple generations. Related designs include heterogeneous stock and the diversity outcross population. In this article, I derive the two-locus haplotype probabilities on the autosome and X chromosome with these designs. These haplotype probabilities provide the key quantities for developing hidden Markov models for the treatment of missing genotype information. I further derive the map expansion in these populations, which is the frequency of recombination breakpoints on a random chromosome.

Motivation: R/qtl is free and powerful software for mapping and exploring quantitative trait loci (QTL). R/qtl provides a fully comprehensive range of methods for a wide range of experimental cross types. We recently added multiple QTL mapping (MQM) to R/qtl. MQM adds higher statistical power to detect and disentangle the effects of multiple linked and unlinked QTL compared with many other methods. MQM for R/qtl adds many new features including improved handling of missing data, analysis of 10 000 s of molecular traits, permutation for determining significance thresholds for QTL and QTL hot spots, and visualizations for cis–trans and QTL interaction effects. MQM for R/qtl is the first free and open source implementation of MQM that is multi-platform, scalable and suitable for automated procedures and large genetical genomics datasets.

Availability: R/qtl is free and open source multi-platform software for the statistical language R, and is made available under the GPLv3 license. R/qtl can be installed from http://www.rqtl.org/. R/qtl queries should be directed at the mailing list, see http://www.rqtl.org/list/.

Contact: kbroman@biostat.wisc.edu

In mouse models of influenza, T cells can confer broad protection against multiple viral subtypes when antibodies raised against a single subtype fail to do so. However, the role of T cells in protecting humans against influenza remains unclear. Here we employ a translational nonhuman primate model to show that cross-reactive T cell responses play an important role in early clearance of infection with 2009 pandemic H1N1 influenza virus (H1N1pdm). To “prime” cellular immunity, we first infected 5 rhesus macaques with a seasonal human H1N1 isolate. These animals made detectable cellular and antibody responses against the seasonal H1N1 isolate but had no neutralizing antibodies against H1N1pdm. Four months later, we challenged the 5 “primed” animals and 7 naive controls with H1N1pdm. In naive animals, CD8+ T cells with an activated phenotype (Ki-67+ CD38+) appeared in blood and lung 5–7 days post inoculation (p.i.) with H1N1pdm and reached peak magnitude 7–10 days p.i. In contrast, activated T cells were recruited to the lung as early as 2 days p.i. in “primed” animals, and reached peak frequencies in blood and lung 4–7 days p.i. Interferon (IFN)-γ Elispot and intracellular cytokine staining assays showed that the virus-specific response peaked earlier and reached a higher magnitude in “primed” animals than in naive animals. This response involved both CD4+ and CD8+ T cells. Strikingly, “primed” animals cleared H1N1pdm infection significantly earlier from the upper and lower respiratory tract than the naive animals did, and before the appearance of H1N1pdm-specific neutralizing antibodies. Together, our results suggest that cross-reactive T cell responses can mediate early clearance of an antigenically novel influenza virus in primates. Vaccines capable of inducing such cross-reactive T cells may help protect humans against severe disease caused by newly emerging pandemic influenza viruses.

Author Summary

Antibodies against influenza target the highly mutable proteins on the virus surface. Influenza pandemics are caused by novel viruses whose surface proteins are so different from previously circulating viruses as to be unrecognizable by most individuals' antibodies. We hypothesized that T cells might be capable of reducing the severity of infection with pandemic influenza viruses, against which antibodies are ineffective. Experiments in mice have supported this idea, but the ability of T cells to protect humans against influenza has remained unclear. We therefore tested our hypothesis in macaque monkeys, whose physiology and immune systems closely resemble those of humans. We used a seasonal virus to “prime” macaques to make immune responses against influenza and found that these animals were able to control infection with 2009 H1N1 pandemic influenza viruses more effectively than animals that had not been “primed.” Protection was associated with T cell responses, but not antibodies, that were quickly “recalled” after challenge with the pandemic virus. Our results suggest that “cross-reactive” T cells could play an important role in controlling influenza in humans. Vaccines designed to induce strong T cell responses in addition to antibodies could offer enhanced protection against emerging influenza viruses.

A surprising diversity of mechanisms controls sex determination of vertebrate organisms, even among closely related species. Both genetic and temperature-dependent systems of sex determination have been described in teleost fish. In the common zebrafish model organism, heteromorphic sex chromosomes are not observed, and the potential role of a genetic component of sex determination remains largely unknown. Here we report a genome-wide linkage study of sex determination in zebrafish using a novel SNP genetic map. We identified loci on zebrafish chromosomes 5 (LOD score 7.9) and 16 (LOD score 9.3) governing sex determination as a complex trait, rather than as an XY or ZW genetic system. Each of these loci contains a prominent candidate gene with a conserved role in sex determination across additional species that suggest potential mechanisms of sex determination in zebrafish. The chromosome 5 locus harbors dmrt1, a key gene in sex determination from fruit flies to humans; mutation of the human DMRT1 ortholog is a cause of complete sex reversal of XY individuals. The chromosome 16 locus harbors cyp21a2; mutation of the human CYP21A2 ortholog is one of the more common causes of pseudohermaphroditism. Mutation detection at each of these candidate genes within the zebrafish cross identified hypomorphic variants on the female-associated allele of each locus. The two loci together accounted for 16% of variance of the trait. Interacting environmental cues are likely to be an additional important component of sex determination in zebrafish.

Background

Human killer immunoglobulin-like receptors (KIRs) play a critical role in governing the immune response to neoplastic and infectious disease. Rhesus macaques serve as important animal models for many human diseases in which KIRs are implicated; however, the study of KIR activity in this model is hindered by incomplete characterization of KIR genetics.

Results

Here we present a characterization of KIR genetics in rhesus macaques (Macaca mulatta). We conducted a survey of KIRs in this species, identifying 47 novel full-length KIR sequences. Using this expanded sequence library to build upon previous work, we present evidence supporting the existence of 22 Mamu-KIR genes, providing a framework within which to describe macaque KIRs. We also developed a novel pyrosequencing-based technique for KIR genotyping. This method provides both comprehensive KIR genotype and frequency estimates of transcript level, with implications for the study of KIRs in all species.

Conclusions

The results of this study significantly improve our understanding of macaque KIR genetic organization and diversity, with implications for the study of many human diseases that use macaques as a model. The ability to obtain comprehensive KIR genotypes is of basic importance for the study of KIRs, and can easily be adapted to other species. Together these findings both advance the field of macaque KIRs and facilitate future research into the role of KIRs in human disease.

A surprising diversity of mechanisms controls sex determination of vertebrate organisms, even among closely related species. Both genetic and temperature-dependent systems of sex determination have been described in teleost fish. In the common zebrafish model organism, heteromorphic sex chromosomes are not observed, and the potential role of a genetic component of sex determination remains largely unknown. Here we report a genome-wide linkage study of sex determination in zebrafish using a novel SNP genetic map. We identified loci on zebrafish chromosomes 5 (LOD score 7.9) and 16 (LOD score 9.3) governing sex determination as a complex trait, rather than as an XY or ZW genetic system. Each of these loci contains a prominent candidate gene with a conserved role in sex determination across additional species that suggest potential mechanisms of sex determination in zebrafish. The chromosome 5 locus harbors dmrt1, a key gene in sex determination from fruit flies to humans; mutation of the human DMRT1 ortholog is a cause of complete sex reversal of XY individuals. The chromosome 16 locus harbors cyp21a2; mutation of the human CYP21A2 ortholog is one of the more common causes of pseudohermaphroditism. Mutation detection at each of these candidate genes within the zebrafish cross identified hypomorphic variants on the female-associated allele of each locus. The two loci together accounted for 16% of variance of the trait. Interacting environmental cues are likely to be an additional important component of sex determination in zebrafish.

Purpose

To quantify the risk for age-related cortical cataract and posterior subcapsular cataract (PSC) associated with having an affected sibling after adjusting for known environmental and personal risk factors.

Design

Sibling cohort study.

Participants

Participants in the ongoing Salisbury Eye Evaluation (SEE) study (n = 321; mean age, 78.1±4.2 years) and their locally resident siblings (n = 453; mean age, 72.6±7.4 years) were recruited at the time of Rounds 3 and 4 of the SEE study.

Intervention/Testing Methods

Retroillumination photographs of the lens were graded for the presence of cortical cataract and PSC with the Wilmer grading system. The residual correlation between siblings' cataract grades was estimated after adjustment for a number of factors (age; gender; race; lifetime exposure to ultraviolet-B light; cigarette, alcohol, estrogen, and steroid use; serum antioxidants; history of diabetes; blood pressure; and body mass index) suspected to be associated with the presence of cataract.

Results

The average sibship size was 2.7 per family. Multivariate analysis revealed the magnitude of heritability (h2) for cortical cataract to be 24% (95% CI, 6%–42%), whereas that for PSC was not statistically significant (h2 4%; 95% CI, 0%–11%) after adjustment for the covariates. The model revealed that increasing age, female gender, a history of diabetes, and black race increased the odds of cortical cataract, whereas higher levels of provitamin A were protective. A history of diabetes and steroid use increased the odds for PSC.

Conclusions

This study is consistent with a significant genetic effect for age-related cortical cataract but not PSC.

Purpose

To quantify the association between siblings in age-related nuclear cataract, after adjusting for known environmental and personal risk factors.

Methods

All participants (probands) in the Salisbury Eye Evaluation (SEE) project and their locally resident siblings underwent digital slit lamp photography and were administered a questionnaire to assess risk factors for cataract including: age, gender, lifetime sun exposure, smoking and diabetes history, and use of alcohol and medications such as estrogens and steroids. In addition, blood pressure, body mass index, and serum antioxidants were measured in all participants. Lens photographs were graded by trained observers masked to the subjects' identity, using the Wilmer Cataract Grading System. The odds ratio for siblings for affectedness with nuclear cataract and the sibling correlation of nuclear cataract grade, after adjusting for covariates, were estimated with generalized estimating equations.

Results

Among 307 probands (mean age, 77.6 ± 4.5 years) and 434 full siblings (mean age, 72.4 ± 7.4 years), the average sibship size was 2.7 per family. After adjustment for covariates, the probability of development of nuclear cataract was significantly increased (odds ratio [OR] = 2.07, 95% confidence interval [CI], 1.30–3.30) among individuals with a sibling with nuclear cataract (nuclear grade ≥ 3.0). The final fitted model indicated a magnitude of heritability for nuclear cataract of 35.6% (95% CI: 21.0%–50.3%) after adjustment for the covariates.

Conclusions

Findings in this study are consistent with a genetic effect for age-related nuclear cataract, a common and clinically significant form of lens opacity.

Recent linkage-based studies in humans suggest the presence of loci that affect either genome-wide recombination rates, utilization of recombination hotspots, or both. We have been interested in utilizing cytological methodology to directly assess recombination in mammalian meiocytes and to identify recombination-associated loci. In the present report we summarize studies in which we combined a cytological assay of recombination in mouse pachytene spermatocytes with QTL analyses to identify loci that contribute to genome-wide levels of recombination in male meiosis. Specifically, we analyzed MLH1 foci, a marker of crossovers, in 194 F2 male mice derived from a subspecific cross between CAST/EiJ and C57BL/6J parental strains. We then used these data to uncover loci associated with individual variation in mean MLH1 values. We identified seven recombination-associated loci across the genome (on chromosomes 2, 3, 4, 14, 15, 17, and X), indicating that there are multiple recombination “setting” loci in mammalian male meiosis.

Live-attenuated vaccination with simian immunodeficiency virus (SIV) SIVmac239Δnef is the most successful vaccine product tested to date in macaques. However, the mechanisms that explain the efficacy of this vaccine remain largely unknown. We utilized an ex vivo viral suppression assay to assess the quality of the immune response in SIVmac239Δnef-immunized animals. Using major histocompatibility complex-matched Mauritian cynomolgus macaques, we did not detect SIV-specific functional immune responses in the blood by gamma interferon (IFN-γ) enzyme-linked immunospot assay at select time points; however, we found that lung CD8+ T cells, unlike blood CD8+ T cells, effectively suppress virus replication by up to 80%. These results suggest that SIVmac239Δnef may be an effective vaccine because it elicits functional immunity at mucosal sites. Moreover, these results underscore the limitations of relying on immunological measurements from peripheral blood lymphocytes in studies of protective immunity to HIV/SIV.

The objective of this study was to detect interactions between relevant single-nucleotide polymorphisms (SNPs) associated with rheumatoid arthritis (RA). Data from Problem 1 of the Genetic Analysis Workshop 16 were used. These data consisted of 868 cases and 1,194 controls genotyped with the 500 k Illumina chip. First, machine learning methods were applied for preselecting SNPs. One hundred SNPs outside the HLA region and 1,500 SNPs in the HLA region were preselected using information-gain theory. The software weka was used to reduce colinearity and redundancy in the HLA region, resulting in a subset of 6 SNPs out of 1,500. In a second step, a parametric approach to account for interactions between SNPs in the HLA region, as well as HLA-nonHLA interactions was conducted using a Bayesian threshold least absolute shrinkage and selection operator (LASSO) model incorporating 2,560 covariates. This approach detected some main and interaction effects for SNPs in genes that have previously been associated with RA (e.g., rs2395175, rs660895, rs10484560, and rs2476601). Further, some other SNPs detected in this study may be considered in candidate gene studies.

Studies of human trisomies indicate a remarkable relationship between abnormal meiotic recombination and subsequent nondisjunction at maternal meiosis I or II. Specifically, failure to recombine or recombination events located either too near to or too far from the centromere have been linked to the origin of human trisomies. It should be possible to identify these abnormal crossover configurations by using immunofluorescence methodology to directly examine the meiotic recombination process in the human female. Accordingly, we initiated studies of crossover-associated proteins (e.g., MLH1) in human fetal oocytes to analyze their number and distribution on nondisjunction-prone human chromosomes and, more generally, to characterize genome-wide levels of recombination in the human female. Our analyses indicate that the number of MLH1 foci is lower than predicted from genetic linkage analysis, but its localization pattern conforms to that expected for a crossover-associated protein. In studies of individual chromosomes, our observations provide evidence for the presence of “vulnerable” crossover configurations in the fetal oocyte, consistent with the idea that these are subsequently translated into nondisjunctional events in the adult oocyte.

Author Summary

One of the defining events in the formation of eggs and sperm is meiotic recombination, a process in which DNA is exchanged between “partner” chromosomes. If this process is perturbed, chromosomes often go astray during meiotic division, resulting in eggs or sperm with too many or too few chromosomes. In humans, the resulting embryos are almost always abnormal and are a major source of miscarriages or congenital birth defects (e.g., Down syndrome). Over the past decade, techniques have become available that make possible the examination of meiotic recombination “as it happens” in the human egg, and this has allowed us to define the properties of this process. In the present study, we used this methodology to characterize meiotic recombination in human fetal oocytes and to ask whether we could identify abnormal recombination patterns. Such patterns were, indeed, observed for each chromosome we studied, although different abnormalities were observed among the individual chromosomes. Thus, factors operating before birth influence the likelihood of chromosome misdivision in the adult oocyte, although those that make chromosome 21 misdivide (leading to Down syndrome) may not be the same as those that make other chromosomes misdivide.

The transcription factor GATA4 is essential for heart morphogenesis. Heterozygous mutation of GATA4 causes familial septal defects. However, the phenotypic spectrum of heterozygous GATA4 mutation is not known. In this study, we defined the cardiac phenotypes that result from heterozygous mutation of murine Gata4. We then asked if GATA4 mutation occurs in humans with these forms of congenital heart disease (CHD). In mice, heterozygous Gata4 mutation was associated with atrial and ventricular septal defect (ASD, VSD), endocardial cushion defect (ECD), RV hypoplasia, and cardiomyopathy. Genetic background strongly influenced the expression of ECD and cardiomyopathy, indicating the presence of important genetic modifiers. In humans, non-synonymous GATA4 sequence variants were associated with ECD (2/43), ASD (1/8), and RV hypoplasia in the context of double inlet left ventricle (1/9), forms of CHD that overlapped with abnormalities seen in the mouse model. These variants were not found in at least 500 control chromosomes, and encode proteins with non-conservative amino acid substitutions at phylogenetically conserved positions, suggesting that they are disease-causing mutations. Cardiomyopathy was not associated with GATA4 mutation in humans. These data establish the phenotypic spectrum of heterozygous Gata4 mutation in mice, and suggest that heterozygous GATA4 mutation leads to partially overlapping phenotypes in humans. Additional studies will be required to determine the degree to which GATA4 mutation contributes to human CHD characterized by ECD or RV hypoplasia.

Among mammals, genetic recombination occurs at highly delimited sites known as recombination hotspots. They are typically 1–2 kb long and vary as much as a 1,000-fold or more in recombination activity. Although much is known about the molecular details of the recombination process itself, the factors determining the location and relative activity of hotspots are poorly understood. To further our understanding, we have collected and mapped the locations of 5,472 crossover events along mouse Chromosome 1 arising in 6,028 meioses of male and female reciprocal F1 hybrids of C57BL/6J and CAST/EiJ mice. Crossovers were mapped to a minimum resolution of 225 kb, and those in the telomere-proximal 24.7 Mb were further mapped to resolve individual hotspots. Recombination rates were evolutionarily conserved on a regional scale, but not at the local level. There was a clear negative-exponential relationship between the relative activity and abundance of hotspot activity classes, such that a small number of the most active hotspots account for the majority of recombination. Females had 1.2× higher overall recombination than males did, although the sex ratio showed considerable regional variation. Locally, entirely sex-specific hotspots were rare. The initiation of recombination at the most active hotspot was regulated independently on the two parental chromatids, and analysis of reciprocal crosses indicated that parental imprinting has subtle effects on recombination rates. It appears that the regulation of mammalian recombination is a complex, dynamic process involving multiple factors reflecting species, sex, individual variation within species, and the properties of individual hotspots.

Author Summary

In most eukaryotic organisms, recombination—the exchange of genetic information between homologous chromosomes—ensures the proper recognition and segregation of chromosomes during meiosis. Recombination events in mammals are not randomly positioned along the chromosomes but occur in preferential 1–2-kilobase sequences termed hotspots. Different species such as humans and mice do not share hotspots, although the same principles almost certainly regulate their placement in the genome. Hotspot positions and activities depend on genetic background and show sex-specific differences. In this study, we present a detailed analysis of recombination activity along the largest mouse chromosome, finding that recombination is regulated on multiple levels, including regional positioning relative to the chromosomal ends, local gene content, sex-specific mechanisms of hotspot recognition, and parental origin. Our results will contribute to further understanding of one of the most fundamental biological processes and are likely to cast light on several aspects of population genetics and evolutionary biology, as well as enhance our practical ability to define the genetic components of human disease.

An investigator planning a QTL (quantitative trait locus) experiment has to choose which strains to cross, the type of cross, genotyping strategies, and the number of progeny to raise and phenotype. To help make such choices, we have developed an interactive program for power and sample size calculations for QTL experiments, R/qtlDesign. Our software includes support for selective genotyping strategies, variable marker spacing, and tools to optimize information content subject to cost constraints for backcross, intercross, and recombinant inbred lines from two parental strains. We review the impact of experimental design choices on the variance attributable to a segregating locus, the residual error variance, and the effective sample size. We give examples of software usage in real-life settings. The software is available at http://www.biostat.ucsf.edu/sen/software.html.

Background

Advanced intercross lines (AIL) are segregating populations created using a multi-generation breeding protocol for fine mapping complex trait loci (QTL) in mice and other organisms. Applying QTL mapping methods for intercross and backcross populations, often followed by naïve permutation of individuals and phenotypes, does not account for the effect of AIL family structure in which final generations have been expanded and leads to inappropriately low significance thresholds. The critical problem with naïve mapping approaches in AIL populations is that the individual is not an exchangeable unit.

Methodology/Principal Findings

The effect of family structure has immediate implications for the optimal AIL creation (many crosses, few animals per cross, and population expansion before the final generation) and we discuss these and the utility of AIL populations for QTL fine mapping. We also describe Genome Reshuffling for Advanced Intercross Permutation, (GRAIP) a method for analyzing AIL data that accounts for family structure. GRAIP permutes a more interchangeable unit in the final generation crosses – the parental genome – and simulating regeneration of a permuted AIL population based on exchanged parental identities. GRAIP determines appropriate genome-wide significance thresholds and locus-specific P-values for AILs and other populations with similar family structures. We contrast GRAIP with naïve permutation using a large densely genotyped mouse AIL population (1333 individuals from 32 crosses). A naïve permutation using coat color as a model phenotype demonstrates high false-positive locus identification and uncertain significance levels, which are corrected using GRAIP. GRAIP also detects an established hippocampus weight locus and a new locus, Hipp9a.

Conclusions and Significance

GRAIP determines appropriate genome-wide significance thresholds and locus-specific P-values for AILs and other populations with similar family structures. The effect of family structure has immediate implications for the optimal AIL creation and we discuss these and the utility of AIL populations.

Several important syndromes are caused by deleterious germline mutations of individual genes. In both clinical and research applications it is useful to evaluate the probability that an individual carries an inherited genetic variant of these genes, and to predict the risk of disease for that individual, using information on his/her family history. Mendelian risk prediction models accomplish these goals by integrating Mendelian principles and state-of-the-art statistical models to describe phenotype/genotype relationships. Here we introduce an R library called BayesMendel that allows implementation of Mendelian models in research and counseling settings. Bayes-Mendel is implemented in an object-oriented structure in the language R and distributed freely as an open source library. In its first release, it includes two major cancer syndromes: the breast-ovarian cancer syndrome and the hereditary non-polyposis colorectal cancer syndrome, along with up-to-date estimates of penetrance and prevalence for the corresponding genes. Input genetic parameters can be easily modified by users. BayesMendel can also serve as a generic tool for genetic epidemiologists to flexibly implement their own Mendelian models for novel syndromes and local subpopulations, without reprogramming complex statistical analyses and prediction tools.

Cancer is a complex disease in which cells acquire many genetic and epigenetic alterations. We have examined how three types of alterations, mutations in tumor suppressor genes, changes in an imprinted locus, and polymorphic loci, interact to affect tumor susceptibility in a mouse model of neurofibromatosis type 1 (NF1). Mutations in tumor suppressor genes such as TP53 and in oncogenes such as KRAS have major effects on tumorigenesis, due to the central roles of these genes in cell proliferation and cell survival. Imprinted genes expressed from only one parental chromosome affect tumorigenesis if their monoallelic expression is lost or duplicated. Because imprinted loci are within regions deleted or amplified in cancer, the parental origin of genomic rearrangements could affect tumorigenesis. Gene polymorphisms can vary tumor incidence by affecting rate-limiting steps in tumorigenesis within tumor cells or surrounding stroma. In our mouse model of NF1, the incidence of tumors mutant for the tumor suppressor genes Nf1 and Trp53 is strongly modified by a linked imprinted locus acting epistatically on two unlinked polymorphic loci, Nstr1 and Nstr2. This interaction of an imprinted locus and polymorphic susceptibility loci has profound implications for human mapping studies, where the parental contribution of alleles is often unknown.

Background

Over the past decade many linkage studies have defined chromosomal intervals containing polymorphisms that modulate a variety of traits. Many phenotypes are now associated with enough mapping data that meta-analysis could help refine locations of known QTLs and detect many novel QTLs.

Methodology/Principal Findings

We describe a simple approach to combining QTL mapping results for multiple studies and demonstrate its utility using two hippocampus weight loci. Using data taken from two populations, a recombinant inbred strain set and an advanced intercross population we demonstrate considerable improvements in significance and resolution for both loci. 1-LOD support intervals were improved 51% for Hipp1a and 37% for Hipp9a. We first generate locus-wise permuted P-values for association with the phenotype from multiple maps, which can be done using a permutation method appropriate to each population. These results are then assigned to defined physical positions by interpolation between markers with known physical and genetic positions. We then use Fisher's combination test to combine position-by-position probabilities among experiments. Finally, we calculate genome-wide combined P-values by generating locus-specific P-values for each permuted map for each experiment. These permuted maps are then sampled with replacement and combined. The distribution of best locus-specific P-values for each combined map is the null distribution of genome-wide adjusted P-values.

Conclusions/Significance

Our approach is applicable to a wide variety of segregating and non-segregating mapping populations, facilitates rapid refinement of physical QTL position, is complementary to other QTL fine mapping methods, and provides an appropriate genome-wide criterion of significance for combined mapping results.