Parameter Estimation and Quantitative Parametric Linkage Analysis with GENEHUNTER-QMOD

Objective: We present a parametric method for linkage analysis of quantitative phenotypes. The method provides a test for linkage as well as an estimate of different phenotype parameters. We have implemented our new method in the program GENEHUNTER-QMOD and evaluated its properties by performing simulations. Methods: The phenotype is modeled as a normally distributed variable, with a separate distribution for each genotype. Parameter estimates are obtained by maximizing the LOD score over the normal distribution parameters with a gradient-based optimization called PGRAD method. Results: The PGRAD method has lower power to detect linkage than the variance components analysis (VCA) in case of a normal distribution and small pedigrees. However, it outperforms the VCA and Haseman-Elston regression for extended pedigrees, nonrandomly ascertained data and non-normally distributed phenotypes. Here, the higher power even goes along with conservativeness, while the VCA has an inflated type I error. Parameter estimation tends to underestimate residual variances but performs better for expectation values of the phenotype distributions. Conclusion: With GENEHUNTER-QMOD, a powerful new tool is provided to explicitly model quantitative phenotypes in the context of linkage analysis. It is freely available at http://www.helmholtz-muenchen.de/genepi/downloads. Copyright (C) 2012 S. Karger AG, Base

Applied Theatre and Practice as Research: Polyphonic Conversations

Applied theatre practice as research might be perceived as a curious conflation. Not greatly foregrounded in the literature on applied theatre or performance practice as research, this article engages with the particularities of such a pairing. Beginning with identifying why a consideration is timely, ‘the practice as research’ and ‘social’ turns are invoked and analysed as relevant contexts to consider applied theatre practice as research. Two projects are offered, providing specific examples for discussion. Revealed by increased scrutiny, some broader epistemological questions emerge concerning power, hierarchy of knowledge and research ‘authoring’. A metaphor of polyphonic conversations is offered as an amplification of the applied theatre practical research methodological terrain. Encouraging the basis of many sets of voices contributing to research and potentially negotiating concerns about power hierarchies and knowledge production, the metaphor provokes a fluidity of epistemology, including expanding on the now familiar debates around theory and practice particularly relevant for socially engaged performance-related practical research

Quantitative trait locus analysis of hybrid pedigrees: variance-components model, inbreeding parameter, and power

<p>Abstract</p> <p>Background</p> <p>For the last years reliable mapping of quantitative trait loci (QTLs) has become feasible through linkage analysis based on the variance-components method. There are now many approaches to the QTL analysis of various types of crosses within one population (breed) as well as crosses between divergent populations (breeds). However, to analyse a complex pedigree with dominance and inbreeding, when the pedigree's founders have an inter-population (hybrid) origin, it is necessary to develop a high-powered method taking into account these features of the pedigree.</p> <p>Results</p> <p>We offer a universal approach to QTL analysis of complex pedigrees descended from crosses between outbred parental lines with different QTL allele frequencies. This approach improves the established variance-components method due to the consideration of the genetic effect conditioned by inter-population origin and inbreeding of individuals. To estimate model parameters, namely additive and dominant effects, and the allelic frequencies of the QTL analysed, and also to define the QTL positions on a chromosome with respect to genotyped markers, we used the maximum-likelihood method. To detect linkage between the QTL and the markers we propose statistics with a non-central χ²-distribution that provides the possibility to deduce analytical expressions for the power of the method and therefore, to estimate the pedigree's size required for 80% power. The method works for arbitrarily structured pedigrees with dominance and inbreeding.</p> <p>Conclusion</p> <p>Our method uses the phenotypic values and the marker information for each individual of the pedigree under observation as initial data and can be valuable for fine mapping purposes. The power of the method is increased if the QTL effects conditioned by inter-population origin and inbreeding are enhanced. Several improvements can be developed to take into account fixed factors affecting trait formation, such as age and sex.</p

Bayesian shrinkage mapping of quantitative trait loci in variance component models

<p>Abstract</p> <p>Background</p> <p>In this article, I propose a model-selection-free method to map multiple quantitative trait loci (QTL) in variance component model, which is useful in outbred populations. The new method can estimate the variance of zero-effect QTL infinitely to zero, but nearly unbiased for non-zero-effect QTL. It is analogous to Xu's Bayesian shrinkage estimation method, but his method is based on allelic substitution model, while the new method is based on the variance component models.</p> <p>Results</p> <p>Extensive simulation experiments were conducted to investigate the performance of the proposed method. The results showed that the proposed method was efficient in mapping multiple QTL simultaneously, and moreover it was more competitive than the reversible jump MCMC (RJMCMC) method and may even out-perform it.</p> <p>Conclusions</p> <p>The newly developed Bayesian shrinkage method is very efficient and powerful for mapping multiple QTL in outbred populations.</p

Obesity promotes 7,12-dimethylbenz(a)anthracene-induced mammary tumor development in female zucker rats

INTRODUCTION: High body mass index has been associated with increased risk for various cancers, including breast cancer. Here we describe studies using 7,12-dimethylbenz(a)anthracene (DMBA) to investigate the role of obesity in DMBA-induced mammary tumor susceptibility in the female Zucker rat (fa/fa), which is the most widely used rat model of genetic obesity. METHOD: Fifty-day-old female obese (n = 25) and lean (n = 28) Zucker rats were orally gavaged with 65 mg/kg DMBA. Rats were weighed and palpated twice weekly for detection of mammary tumors. Rats were killed 139 days after DMBA treatment. RESULTS: The first mammary tumor was detected in the obese group at 49 days after DMBA treatment, as compared with 86 days in the lean group (P < 0.001). The median tumor-free time was significantly lower in the obese group (P < 0.001). Using the days after DMBA treatment at which 25% of the rats had developed mammary tumors as the marker of tumor latency, the obese group had a significantly shorter latency period (66 days) than did the lean group (118 days). At the end of the study, obese rats had developed a significantly (P < 0.001) greater mammary tumor incidence (68% versus 32%) compared with the lean group. The tumor histology of the mammary tumors revealed that obesity was associated with a significant (P < 0.05) increase in the number of rats with at least one invasive ductal and lobular carcinoma compared with lean rats. CONCLUSION: Our results indicate that obesity increases the susceptibility of female Zucker rats to DMBA-induced mammary tumors, further supporting the hypothesis that obesity and some of its mediators play a significant role in carcinogenesis

Genome Scan of M. tuberculosis Infection and Disease in Ugandans

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is an enduring public health problem globally, particularly in sub-Saharan Africa. Several studies have suggested a role for host genetic susceptibility in increased risk for TB but results across studies have been equivocal. As part of a household contact study of Mtb infection and disease in Kampala, Uganda, we have taken a unique approach to the study of genetic susceptibility to TB, by studying three phenotypes. First, we analyzed culture confirmed TB disease compared to latent Mtb infection (LTBI) or lack of Mtb infection. Second, we analyzed resistance to Mtb infection in the face of continuous exposure, defined by a persistently negative tuberculin skin test (PTST-); this outcome was contrasted to LTBI. Third, we analyzed an intermediate phenotype, tumor necrosis factor-alpha (TNFα) expression in response to soluble Mtb ligands enriched with molecules secreted from Mtb (culture filtrate). We conducted a full microsatellite genome scan, using genotypes generated by the Center for Medical Genetics at Marshfield. Multipoint model-free linkage analysis was conducted using an extension of the Haseman-Elston regression model that includes half sibling pairs, and HIV status was included as a covariate in the model. The analysis included 803 individuals from 193 pedigrees, comprising 258 full sibling pairs and 175 half sibling pairs. Suggestive linkage (p<10−3) was observed on chromosomes 2q21-2q24 and 5p13-5q22 for PTST-, and on chromosome 7p22-7p21 for TB; these findings for PTST- are novel and the chromosome 7 region contains the IL6 gene. In addition, we replicated recent linkage findings on chromosome 20q13 for TB (p = 0.002). We also observed linkage at the nominal α = 0.05 threshold to a number of promising candidate genes, SLC11A1 (PTST- p = 0.02), IL-1 complex (TB p = 0.01), IL12BR2 (TNFα p = 0.006), IL12A (TB p = 0.02) and IFNGR2 (TNFα p = 0.002). These results confirm not only that genetic factors influence the interaction between humans and Mtb but more importantly that they differ according to the outcome of that interaction: exposure but no infection, infection without progression to disease, or progression of infection to disease. Many of the genetic factors for each of these stages are part of the innate immune system

Differences in the carcinogenic evaluation of glyphosate between the International Agency for Research on Cancer (IARC) and the European Food Safety Authority (EFSA)

The International Agency for Research on Cancer (IARC) Monographs Programme identifies chemicals, drugs, mixtures, occupational exposures, lifestyles and personal habits, and physical and biological agents that cause cancer in humans and has evaluated about 1000 agents since 1971. Monographs are written by ad hoc Working Groups (WGs) of international scientific experts over a period of about 12 months ending in an eight-day meeting. The WG evaluates all of the publicly available scientific information on each substance and, through a transparent and rigorous process,1 decides on the degree to which the scientific evidence supports that substance's potential to cause or not cause cancer in humans. For Monograph 112,2 17 expert scientists evaluated the carcinogenic hazard for four insecticides and the herbicide glyphosate.3 The WG concluded that the data for glyphosate meet the criteria for classification as a probable human carcinogen. The European Food Safety Authority (EFSA) is the primary agency of the European Union for risk assessments regarding food safety. In October 2015, EFSA reported4 on their evaluation of the Renewal Assessment Report5 (RAR) for glyphosate that was prepared by the Rapporteur Member State, the German Federal Institute for Risk Assessment (BfR). EFSA concluded that ?glyphosate is unlikely to pose a carcinogenic hazard to humans and the evidence does not support classification with regard to its carcinogenic potential?. Addendum 1 (the BfR Addendum) of the RAR5 discusses the scientific rationale for differing from the IARC WG conclusion. Serious flaws in the scientific evaluation in the RAR incorrectly characterise the potential for a carcinogenic hazard from exposure to glyphosate. Since the RAR is the basis for the European Food Safety Agency (EFSA) conclusion,4 it is critical that these shortcomings are corrected