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Gene Function (gene + function)
Selected AbstractsEuropean Mathematical Genetics Meeting, Heidelberg, Germany, 12th,13th April 2007ANNALS OF HUMAN GENETICS, Issue 4 2007Article first published online: 28 MAY 200 Saurabh Ghosh 11 Indian Statistical Institute, Kolkata, India High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both. In this study, we develop statistical methods to extract the contribution of a common QTL to the total correlation between the components of a bivariate phenotype. Using data on bivariate phenotypes and marker genotypes for sib-pairs, we propose a test for linkage between a common QTL and a marker locus based on the conditional cross-sib trait correlations (trait 1 of sib 1 , trait 2 of sib 2 and conversely) given the identity-by-descent sharing at the marker locus. The null hypothesis cannot be rejected unless there exists a common QTL. We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from the Collaborative Study On The Genetics Of Alcoholism project. Rémi Kazma 1 , Catherine Bonaďti-Pellié 1 , Emmanuelle Génin 12 INSERM UMR-S535 and Université Paris Sud, Villejuif, 94817, France Keywords: Gene-environment interaction, sibling recurrence risk, exposure correlation Gene-environment interactions may play important roles in complex disease susceptibility but their detection is often difficult. Here we show how gene-environment interactions can be detected by investigating the degree of familial aggregation according to the exposure of the probands. In case of gene-environment interaction, the distribution of genotypes of affected individuals, and consequently the risk in relatives, depends on their exposure. We developed a test comparing the risks in sibs according to the proband exposure. To evaluate the properties of this new test, we derived the formulas for calculating the expected risks in sibs according to the exposure of probands for various values of exposure frequency, relative risk due to exposure alone, frequencies of latent susceptibility genotypes, genetic relative risks and interaction coefficients. We find that the ratio of risks when the proband is exposed and not exposed is a good indicator of the interaction effect. We evaluate the power of the test for various sample sizes of affected individuals. We conclude that this test is valuable for diseases with moderate familial aggregation, only when the role of the exposure has been clearly evidenced. Since a correlation for exposure among sibs might lead to a difference in risks among sibs in the different proband exposure strata, we also add an exposure correlation coefficient in the model. Interestingly, we find that when this correlation is correctly accounted for, the power of the test is not decreased and might even be significantly increased. Andrea Callegaro 1 , Hans J.C. Van Houwelingen 1 , Jeanine Houwing-Duistermaat 13 Dept. of Medical Statistics and Bioinformatics, Leiden University Medical Center, The Netherlands Keywords: Survival analysis, age at onset, score test, linkage analysis Non parametric linkage (NPL) analysis compares the identical by descent (IBD) sharing in sibling pairs to the expected IBD sharing under the hypothesis of no linkage. Often information is available on the marginal cumulative hazards (for example breast cancer incidence curves). Our aim is to extend the NPL methods by taking into account the age at onset of selected sibling pairs using these known marginal hazards. Li and Zhong (2002) proposed a (retrospective) likelihood ratio test based on an additive frailty model for genetic linkage analysis. From their model we derive a score statistic for selected samples which turns out to be a weighed NPL method. The weights depend on the marginal cumulative hazards and on the frailty parameter. A second approach is based on a simple gamma shared frailty model. Here, we simply test whether the score function of the frailty parameter depends on the excess IBD. We compare the performance of these methods using simulated data. Céline Bellenguez 1 , Carole Ober 2 , Catherine Bourgain 14 INSERM U535 and University Paris Sud, Villejuif, France 5 Department of Human Genetics, The University of Chicago, USA Keywords: Linkage analysis, linkage disequilibrium, high density SNP data Compared with microsatellite markers, high density SNP maps should be more informative for linkage analyses. However, because they are much closer, SNPs present important linkage disequilibrium (LD), which biases classical nonparametric multipoint analyses. This problem is even stronger in population isolates where LD extends over larger regions with a more stochastic pattern. We investigate the issue of linkage analysis with a 500K SNP map in a large and inbred 1840-member Hutterite pedigree, phenotyped for asthma. Using an efficient pedigree breaking strategy, we first identified linked regions with a 5cM microsatellite map, on which we focused to evaluate the SNP map. The only method that models LD in the NPL analysis is limited in both the pedigree size and the number of markers (Abecasis and Wigginton, 2005) and therefore could not be used. Instead, we studied methods that identify sets of SNPs with maximum linkage information content in our pedigree and no LD-driven bias. Both algorithms that directly remove pairs of SNPs in high LD and clustering methods were evaluated. Null simulations were performed to control that Zlr calculated with the SNP sets were not falsely inflated. Preliminary results suggest that although LD is strong in such populations, linkage information content slightly better than that of microsatellite maps can be extracted from dense SNP maps, provided that a careful marker selection is conducted. In particular, we show that the specific LD pattern requires considering LD between a wide range of marker pairs rather than only in predefined blocks. Peter Van Loo 1,2,3 , Stein Aerts 1,2 , Diether Lambrechts 4,5 , Bernard Thienpont 2 , Sunit Maity 4,5 , Bert Coessens 3 , Frederik De Smet 4,5 , Leon-Charles Tranchevent 3 , Bart De Moor 2 , Koen Devriendt 3 , Peter Marynen 1,2 , Bassem Hassan 1,2 , Peter Carmeliet 4,5 , Yves Moreau 36 Department of Molecular and Developmental Genetics, VIB, Belgium 7 Department of Human Genetics, University of Leuven, Belgium 8 Bioinformatics group, Department of Electrical Engineering, University of Leuven, Belgium 9 Department of Transgene Technology and Gene Therapy, VIB, Belgium 10 Center for Transgene Technology and Gene Therapy, University of Leuven, Belgium Keywords: Bioinformatics, gene prioritization, data fusion The identification of genes involved in health and disease remains a formidable challenge. Here, we describe a novel bioinformatics method to prioritize candidate genes underlying pathways or diseases, based on their similarity to genes known to be involved in these processes. It is freely accessible as an interactive software tool, ENDEAVOUR, at http://www.esat.kuleuven.be/endeavour. Unlike previous methods, ENDEAVOUR generates distinct prioritizations from multiple heterogeneous data sources, which are then integrated, or fused, into one global ranking using order statistics. ENDEAVOUR prioritizes candidate genes in a three-step process. First, information about a disease or pathway is gathered from a set of known "training" genes by consulting multiple data sources. Next, the candidate genes are ranked based on similarity with the training properties obtained in the first step, resulting in one prioritized list for each data source. Finally, ENDEAVOUR fuses each of these rankings into a single global ranking, providing an overall prioritization of the candidate genes. Validation of ENDEAVOUR revealed it was able to efficiently prioritize 627 genes in disease data sets and 76 genes in biological pathway sets, identify candidates of 16 mono- or polygenic diseases, and discover regulatory genes of myeloid differentiation. Furthermore, the approach identified YPEL1 as a novel gene involved in craniofacial development from a 2-Mb chromosomal region, deleted in some patients with DiGeorge-like birth defects. Finally, we are currently evaluating a pipeline combining array-CGH, ENDEAVOUR and in vivo validation in zebrafish to identify novel genes involved in congenital heart defects. Mark Broom 1 , Graeme Ruxton 2 , Rebecca Kilner 311 Mathematics Dept., University of Sussex, UK 12 Division of Environmental and Evolutionary Biology, University of Glasgow, UK 13 Department of Zoology, University of Cambridge, UK Keywords: Evolutionarily stable strategy, parasitism, asymmetric game Brood parasites chicks vary in the harm that they do to their companions in the nest. In this presentation we use game-theoretic methods to model this variation. Our model considers hosts which potentially abandon single nestlings and instead choose to re-allocate their reproductive effort to future breeding, irrespective of whether the abandoned chick is the host's young or a brood parasite's. The parasite chick must decide whether or not to kill host young by balancing the benefits from reduced competition in the nest against the risk of desertion by host parents. The model predicts that three different types of evolutionarily stable strategies can exist. (1) Hosts routinely rear depleted broods, the brood parasite always kills host young and the host never then abandons the nest. (2) When adult survival after deserting single offspring is very high, hosts always abandon broods of a single nestling and the parasite never kills host offspring, effectively holding them as hostages to prevent nest desertion. (3) Intermediate strategies, in which parasites sometimes kill their nest-mates and host parents sometimes desert nests that contain only a single chick, can also be evolutionarily stable. We provide quantitative descriptions of how the values given to ecological and behavioral parameters of the host-parasite system influence the likelihood of each strategy and compare our results with real host-brood parasite associations in nature. Martin Harrison 114 Mathematics Dept, University of Sussex, UK Keywords: Brood parasitism, games, host, parasite The interaction between hosts and parasites in bird populations has been studied extensively. Game theoretical methods have been used to model this interaction previously, but this has not been studied extensively taking into account the sequential nature of this game. We consider a model allowing the host and parasite to make a number of decisions, which depend on a number of natural factors. The host lays an egg, a parasite bird will arrive at the nest with a certain probability and then chooses to destroy a number of the host eggs and lay one of it's own. With some destruction occurring, either natural or through the actions of the parasite, the host chooses to continue, eject an egg (hoping to eject the parasite) or abandon the nest. Once the eggs have hatched the game then falls to the parasite chick versus the host. The chick chooses to destroy or eject a number of eggs. The final decision is made by the host, choosing whether to raise or abandon the chicks that are in the nest. We consider various natural parameters and probabilities which influence these decisions. We then use this model to look at real-world situations of the interactions of the Reed Warbler and two different parasites, the Common Cuckoo and the Brown-Headed Cowbird. These two parasites have different methods in the way that they parasitize the nests of their hosts. The hosts in turn have a different reaction to these parasites. Arne Jochens 1 , Amke Caliebe 2 , Uwe Roesler 1 , Michael Krawczak 215 Mathematical Seminar, University of Kiel, Germany 16 Institute of Medical Informatics and Statistics, University of Kiel, Germany Keywords: Stepwise mutation model, microsatellite, recursion equation, temporal behaviour We consider the stepwise mutation model which occurs, e.g., in microsatellite loci. Let X(t,i) denote the allelic state of individual i at time t. We compute expectation, variance and covariance of X(t,i), i=1,,,N, and provide a recursion equation for P(X(t,i)=z). Because the variance of X(t,i) goes to infinity as t grows, for the description of the temporal behaviour, we regard the scaled process X(t,i)-X(t,1). The results furnish a better understanding of the behaviour of the stepwise mutation model and may in future be used to derive tests for neutrality under this model. Paul O'Reilly 1 , Ewan Birney 2 , David Balding 117 Statistical Genetics, Department of Epidemiology and Public Health, Imperial, College London, UK 18 European Bioinformatics Institute, EMBL, Cambridge, UK Keywords: Positive selection, Recombination rate, LD, Genome-wide, Natural Selection In recent years efforts to develop population genetics methods that estimate rates of recombination and levels of natural selection in the human genome have intensified. However, since the two processes have an intimately related impact on genetic variation their inference is vulnerable to confounding. Genomic regions subject to recent selection are likely to have a relatively recent common ancestor and consequently less opportunity for historical recombinations that are detectable in contemporary populations. Here we show that selection can reduce the population-based recombination rate estimate substantially. In genome-wide studies for detecting selection we observe a tendency to highlight loci that are subject to low levels of recombination. We find that the outlier approach commonly adopted in such studies may have low power unless variable recombination is accounted for. We introduce a new genome-wide method for detecting selection that exploits the sensitivity to recent selection of methods for estimating recombination rates, while accounting for variable recombination using pedigree data. Through simulations we demonstrate the high power of the Ped/Pop approach to discriminate between neutral and adaptive evolution, particularly in the context of choosing outliers from a genome-wide distribution. Although methods have been developed showing good power to detect selection ,in action', the corresponding window of opportunity is small. In contrast, the power of the Ped/Pop method is maintained for many generations after the fixation of an advantageous variant Sarah Griffiths 1 , Frank Dudbridge 120 MRC Biostatistics Unit, Cambridge, UK Keywords: Genetic association, multimarker tag, haplotype, likelihood analysis In association studies it is generally too expensive to genotype all variants in all subjects. We can exploit linkage disequilibrium between SNPs to select a subset that captures the variation in a training data set obtained either through direct resequencing or a public resource such as the HapMap. These ,tag SNPs' are then genotyped in the whole sample. Multimarker tagging is a more aggressive adaptation of pairwise tagging that allows for combinations of two or more tag SNPs to predict an untyped SNP. Here we describe a new method for directly testing the association of an untyped SNP using a multimarker tag. Previously, other investigators have suggested testing a specific tag haplotype, or performing a weighted analysis using weights derived from the training data. However these approaches do not properly account for the imperfect correlation between the tag haplotype and the untyped SNP. Here we describe a straightforward approach to testing untyped SNPs using a missing-data likelihood analysis, including the tag markers as nuisance parameters. The training data is stacked on top of the main body of genotype data so there is information on how the tag markers predict the genotype of the untyped SNP. The uncertainty in this prediction is automatically taken into account in the likelihood analysis. This approach yields more power and also a more accurate prediction of the odds ratio of the untyped SNP. Anke Schulz 1 , Christine Fischer 2 , Jenny Chang-Claude 1 , Lars Beckmann 121 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany 22 Institute of Human Genetics, University of Heidelberg, Germany Keywords: Haplotype, haplotype sharing, entropy, Mantel statistics, marker selection We previously introduced a new method to map genes involved in complex diseases, using haplotype sharing-based Mantel statistics to correlate genetic and phenotypic similarity. Although the Mantel statistic is powerful in narrowing down candidate regions, the precise localization of a gene is hampered in genomic regions where linkage disequilibrium is so high that neighboring markers are found to be significant at similar magnitude and we are not able to discriminate between them. Here, we present a new approach to localize susceptibility genes by combining haplotype sharing-based Mantel statistics with an iterative entropy-based marker selection algorithm. For each marker at which the Mantel statistic is evaluated, the algorithm selects a subset of surrounding markers. The subset is chosen to maximize multilocus linkage disequilibrium, which is measured by the normalized entropy difference introduced by Nothnagel et al. (2002). We evaluated the algorithm with respect to type I error and power. Its ability to localize the disease variant was compared to the localization (i) without marker selection and (ii) considering haplotype block structure. Case-control samples were simulated from a set of 18 haplotypes, consisting of 15 SNPs in two haplotype blocks. The new algorithm gave correct type I error and yielded similar power to detect the disease locus compared to the alternative approaches. The neighboring markers were clearly less often significant than the causal locus, and also less often significant compared to the alternative approaches. Thus the new algorithm improved the precision of the localization of susceptibility genes. Mark M. Iles 123 Section of Epidemiology and Biostatistics, LIMM, University of Leeds, UK Keywords: tSNP, tagging, association, HapMap Tagging SNPs (tSNPs) are commonly used to capture genetic diversity cost-effectively. However, it is important that the efficacy of tSNPs is correctly estimated, otherwise coverage may be insufficient. If the pilot sample from which tSNPs are chosen is too small or the initial marker map too sparse, tSNP efficacy may be overestimated. An existing estimation method based on bootstrapping goes some way to correct for insufficient sample size and overfitting, but does not completely solve the problem. We describe a novel method, based on exclusion of haplotypes, that improves on the bootstrap approach. Using simulated data, the extent of the sample size problem is investigated and the performance of the bootstrap and the novel method are compared. We incorporate an existing method adjusting for marker density by ,SNP-dropping'. We find that insufficient sample size can cause large overestimates in tSNP efficacy, even with as many as 100 individuals, and the problem worsens as the region studied increases in size. Both the bootstrap and novel method correct much of this overestimate, with our novel method consistently outperforming the bootstrap method. We conclude that a combination of insufficient sample size and overfitting may lead to overestimation of tSNP efficacy and underpowering of studies based on tSNPs. Our novel approach corrects for much of this bias and is superior to the previous method. Sample sizes larger than previously suggested may still be required for accurate estimation of tSNP efficacy. This has obvious ramifications for the selection of tSNPs from HapMap data. Claudio Verzilli 1 , Juliet Chapman 1 , Aroon Hingorani 2 , Juan Pablo-Casas 1 , Tina Shah 2 , Liam Smeeth 1 , John Whittaker 124 Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, UK 25 Division of Medicine, University College London, UK Keywords: Meta-analysis, Genetic association studies We present a Bayesian hierarchical model for the meta-analysis of candidate gene studies with a continuous outcome. Such studies often report results from association tests for different, possibly study-specific and non-overlapping markers (typically SNPs) in the same genetic region. Meta analyses of the results at each marker in isolation are seldom appropriate as they ignore the correlation that may exist between markers due to linkage disequlibrium (LD) and cannot assess the relative importance of variants at each marker. Also such marker-wise meta analyses are restricted to only those studies that have typed the marker in question, with a potential loss of power. A better strategy is one which incorporates information about the LD between markers so that any combined estimate of the effect of each variant is corrected for the effect of other variants, as in multiple regression. Here we develop a Bayesian hierarchical linear regression that models the observed genotype group means and uses pairwise LD measurements between markers as prior information to make posterior inference on adjusted effects. The approach is applied to the meta analysis of 24 studies assessing the effect of 7 variants in the C-reactive protein (CRP) gene region on plasma CRP levels, an inflammatory biomarker shown in observational studies to be positively associated with cardiovascular disease. Cathryn M. Lewis 1 , Christopher G. Mathew 1 , Theresa M. Marteau 226 Dept. of Medical and Molecular Genetics, King's College London, UK 27 Department of Psychology, King's College London, UK Keywords: Risk, genetics, CARD15, smoking, model Recently progress has been made in identifying mutations that confer susceptibility to complex diseases, with the potential to use these mutations in determining disease risk. We developed methods to estimate disease risk based on genotype relative risks (for a gene G), exposure to an environmental factor (E), and family history (with recurrence risk ,R for a relative of type R). ,R must be partitioned into the risk due to G (which is modelled independently) and the residual risk. The risk model was then applied to Crohn's disease (CD), a severe gastrointestinal disease for which smoking increases disease risk approximately 2-fold, and mutations in CARD15 confer increased risks of 2.25 (for carriers of a single mutation) and 9.3 (for carriers of two mutations). CARD15 accounts for only a small proportion of the genetic component of CD, with a gene-specific ,S, CARD15 of 1.16, from a total sibling relative risk of ,S= 27. CD risks were estimated for high-risk individuals who are siblings of a CD case, and who also smoke. The CD risk to such individuals who carry two CARD15 mutations is approximately 0.34, and for those carrying a single CARD15 mutation the risk is 0.08, compared to a population prevalence of approximately 0.001. These results imply that complex disease genes may be valuable in estimating with greater precision than has hitherto been possible disease risks in specific, easily identified subgroups of the population with a view to prevention. Yurii Aulchenko 128 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Compression, information, bzip2, genome-wide SNP data, statistical genetics With advances in molecular technology, studies accessing millions of genetic polymorphisms in thousands of study subjects will soon become common. Such studies generate large amounts of data, whose effective storage and management is a challenge to the modern statistical genetics. Standard file compression utilities, such as Zip, Gzip and Bzip2, may be helpful to minimise the storage requirements. Less obvious is the fact that the data compression techniques may be also used in the analysis of genetic data. It is known that the efficiency of a particular compression algorithm depends on the probability structure of the data. In this work, we compared different standard and customised tools using the data from human HapMap project. Secondly, we investigate the potential uses of data compression techniques for the analysis of linkage, association and linkage disequilibrium Suzanne Leal 1 , Bingshan Li 129 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, USA Keywords: Consanguineous pedigrees, missing genotype data Missing genotype data can increase false-positive evidence for linkage when either parametric or nonparametric analysis is carried out ignoring intermarker linkage disequilibrium (LD). Previously it was demonstrated by Huang et al (2005) that no bias occurs in this situation for affected sib-pairs with unrelated parents when either both parents are genotyped or genotype data is available for two additional unaffected siblings when parental genotypes are missing. However, this is not the case for consanguineous pedigrees, where missing genotype data for any pedigree member within a consanguinity loop can increase false-positive evidence of linkage. The false-positive evidence for linkage is further increased when cryptic consanguinity is present. The amount of false-positive evidence for linkage is highly dependent on which family members are genotyped. When parental genotype data is available, the false-positive evidence for linkage is usually not as strong as when parental genotype data is unavailable. Which family members will aid in the reduction of false-positive evidence of linkage is highly dependent on which other family members are genotyped. For a pedigree with an affected proband whose first-cousin parents have been genotyped, further reduction in the false-positive evidence of linkage can be obtained by including genotype data from additional affected siblings of the proband or genotype data from the proband's sibling-grandparents. When parental genotypes are not available, false-positive evidence for linkage can be reduced by including in the analysis genotype data from either unaffected siblings of the proband or the proband's married-in-grandparents. Najaf Amin 1 , Yurii Aulchenko 130 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Genomic Control, pedigree structure, quantitative traits The Genomic Control (GC) method was originally developed to control for population stratification and cryptic relatedness in association studies. This method assumes that the effect of population substructure on the test statistics is essentially constant across the genome, and therefore unassociated markers can be used to estimate the effect of confounding onto the test statistic. The properties of GC method were extensively investigated for different stratification scenarios, and compared to alternative methods, such as the transmission-disequilibrium test. The potential of this method to correct not for occasional cryptic relations, but for regular pedigree structure, however, was not investigated before. In this work we investigate the potential of the GC method for pedigree-based association analysis of quantitative traits. The power and type one error of the method was compared to standard methods, such as the measured genotype (MG) approach and quantitative trait transmission-disequilibrium test. In human pedigrees, with trait heritability varying from 30 to 80%, the power of MG and GC approach was always higher than that of TDT. GC had correct type 1 error and its power was close to that of MG under moderate heritability (30%), but decreased with higher heritability. William Astle 1 , Chris Holmes 2 , David Balding 131 Department of Epidemiology and Public Health, Imperial College London, UK 32 Department of Statistics, University of Oxford, UK Keywords: Population structure, association studies, genetic epidemiology, statistical genetics In the analysis of population association studies, Genomic Control (Devlin & Roeder, 1999) (GC) adjusts the Armitage test statistic to correct the type I error for the effects of population substructure, but its power is often sub-optimal. Turbo Genomic Control (TGC) generalises GC to incorporate co-variation of relatedness and phenotype, retaining control over type I error while improving power. TGC is similar to the method of Yu et al. (2006), but we extend it to binary (case-control) in addition to quantitative phenotypes, we implement improved estimation of relatedness coefficients, and we derive an explicit statistic that generalizes the Armitage test statistic and is fast to compute. TGC also has similarities to EIGENSTRAT (Price et al., 2006) which is a new method based on principle components analysis. The problems of population structure(Clayton et al., 2005) and cryptic relatedness (Voight & Pritchard, 2005) are essentially the same: if patterns of shared ancestry differ between cases and controls, whether distant (coancestry) or recent (cryptic relatedness), false positives can arise and power can be diminished. With large numbers of widely-spaced genetic markers, coancestry can now be measured accurately for each pair of individuals via patterns of allele-sharing. Instead of modelling subpopulations, we work instead with a coancestry coefficient for each pair of individuals in the study. We explain the relationships between TGC, GC and EIGENSTRAT. We present simulation studies and real data analyses to illustrate the power advantage of TGC in a range of scenarios incorporating both substructure and cryptic relatedness. References Clayton, D. G.et al. (2005) Population structure, differential bias and genomic control in a large-scale case-control association study. Nature Genetics37(11) November 2005. Devlin, B. & Roeder, K. (1999) Genomic control for association studies. Biometics55(4) December 1999. Price, A. L.et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics38(8) (August 2006). Voight, B. J. & Pritchard, J. K. (2005) Confounding from cryptic relatedness in case-control association studies. Public Library of Science Genetics1(3) September 2005. Yu, J.et al. (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics38(2) February 2006. Hervé Perdry 1 , Marie-Claude Babron 1 , Françoise Clerget-Darpoux 133 INSERM U535 and Univ. Paris Sud, UMR-S 535, Villejuif, France Keywords: Modifier genes, case-parents trios, ordered transmission disequilibrium test A modifying locus is a polymorphic locus, distinct from the disease locus, which leads to differences in the disease phenotype, either by modifying the penetrance of the disease allele, or by modifying the expression of the disease. The effect of such a locus is a clinical heterogeneity that can be reflected by the values of an appropriate covariate, such as the age of onset, or the severity of the disease. We designed the Ordered Transmission Disequilibrium Test (OTDT) to test for a relation between the clinical heterogeneity, expressed by the covariate, and marker genotypes of a candidate gene. The method applies to trio families with one affected child and his parents. Each family member is genotyped at a bi-allelic marker M of a candidate gene. To each of the families is associated a covariate value; the families are ordered on the values of this covariate. As the TDT (Spielman et al. 1993), the OTDT is based on the observation of the transmission rate T of a given allele at M. The OTDT aims to find a critical value of the covariate which separates the sample of families in two subsamples in which the transmission rates are significantly different. We investigate the power of the method by simulations under various genetic models and covariate distributions. Acknowledgments H Perdry is funded by ARSEP. Pascal Croiseau 1 , Heather Cordell 2 , Emmanuelle Génin 134 INSERM U535 and University Paris Sud, UMR-S535, Villejuif, France 35 Institute of Human Genetics, Newcastle University, UK Keywords: Association, missing data, conditionnal logistic regression Missing data is an important problem in association studies. Several methods used to test for association need that individuals be genotyped at the full set of markers. Individuals with missing data need to be excluded from the analysis. This could involve an important decrease in sample size and a loss of information. If the disease susceptibility locus (DSL) is poorly typed, it is also possible that a marker in linkage disequilibrium gives a stronger association signal than the DSL. One may then falsely conclude that the marker is more likely to be the DSL. We recently developed a Multiple Imputation method to infer missing data on case-parent trios Starting from the observed data, a few number of complete data sets are generated by Markov-Chain Monte Carlo approach. These complete datasets are analysed using standard statistical package and the results are combined as described in Little & Rubin (2002). Here we report the results of simulations performed to examine, for different patterns of missing data, how often the true DSL gives the highest association score among different loci in LD. We found that multiple imputation usually correctly detect the DSL site even if the percentage of missing data is high. This is not the case for the naďve approach that consists in discarding trios with missing data. In conclusion, Multiple imputation presents the advantage of being easy to use and flexible and is therefore a promising tool in the search for DSL involved in complex diseases. Salma Kotti 1 , Heike Bickeböller 2 , Françoise Clerget-Darpoux 136 University Paris Sud, UMR-S535, Villejuif, France 37 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany Keywords: Genotype relative risk, internal controls, Family based analyses Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRRs. We will analytically derive the GRR estimators for the 1:1 and 1:3 matching and will present the results at the meeting. Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRR. We will analytically derive the GRR estimator for the 1:1 and 1:3 matching and will present the results at the meeting. Luigi Palla 1 , David Siegmund 239 Department of Mathematics,Free University Amsterdam, The Netherlands 40 Department of Statistics, Stanford University, California, USA Keywords: TDT, assortative mating, inbreeding, statistical power A substantial amount of Assortative Mating (AM) is often recorded on physical and psychological, dichotomous as well as quantitative traits that are supposed to have a multifactorial genetic component. In particular AM has the effect of increasing the genetic variance, even more than inbreeding because it acts across loci beside within loci, when the trait has a multifactorial origin. Under the assumption of a polygenic model for AM dating back to Wright (1921) and refined by Crow and Felsenstein (1968,1982), the effect of assortative mating on the power to detect genetic association in the Transmission Disequilibrium Test (TDT) is explored as parameters, such as the effective number of genes and the allelic frequency vary. The power is reflected by the non centrality parameter of the TDT and is expressed as a function of the number of trios, the relative risk of the heterozygous genotype and the allele frequency (Siegmund and Yakir, 2007). The noncentrality parameter of the relevant score statistic is updated considering the effect of AM which is expressed in terms of an ,effective' inbreeding coefficient. In particular, for dichotomous traits it is apparent that the higher the number of genes involved in the trait, the lower the loss in power due to AM. Finally an attempt is made to extend this relation to the Q-TDT (Rabinowitz, 1997), which involves considering the effect of AM also on the phenotypic variance of the trait of interest, under the assumption that AM affects only its additive genetic component. References Crow, & Felsenstein, (1968). The effect of assortative mating on the genetic composition of a population. Eugen.Quart.15, 87,97. Rabinowitz,, 1997. A Transmission Disequilibrium Test for Quantitative Trait Loci. Human Heredity47, 342,350. Siegmund, & Yakir, (2007) Statistics of gene mapping, Springer. Wright, (1921). System of mating.III. Assortative mating based on somatic resemblance. Genetics6, 144,161. Jérémie Nsengimana 1 , Ben D Brown 2 , Alistair S Hall 2 , Jenny H Barrett 141 Leeds Institute of Molecular Medicine, University of Leeds, UK 42 Leeds Institute for Genetics, Health and Therapeutics, University of Leeds, UK Keywords: Inflammatory genes, haplotype, coronary artery disease Genetic Risk of Acute Coronary Events (GRACE) is an initiative to collect cases of coronary artery disease (CAD) and their unaffected siblings in the UK and to use them to map genetic variants increasing disease risk. The aim of the present study was to test the association between CAD and 51 single nucleotide polymorphisms (SNPs) and their haplotypes from 35 inflammatory genes. Genotype data were available for 1154 persons affected before age 66 (including 48% before age 50) and their 1545 unaffected siblings (891 discordant families). Each SNP was tested for association to CAD, and haplotypes within genes or gene clusters were tested using FBAT (Rabinowitz & Laird, 2000). For the most significant results, genetic effect size was estimated using conditional logistic regression (CLR) within STATA adjusting for other risk factors. Haplotypes were assigned using HAPLORE (Zhang et al., 2005), which considers all parental mating types consistent with offspring genotypes and assigns them a probability of occurence. This probability was used in CLR to weight the haplotypes. In the single SNP analysis, several SNPs showed some evidence for association, including one SNP in the interleukin-1A gene. Analysing haplotypes in the interleukin-1 gene cluster, a common 3-SNP haplotype was found to increase the risk of CAD (P = 0.009). In an additive genetic model adjusting for covariates the odds ratio (OR) for this haplotype is 1.56 (95% CI: 1.16-2.10, p = 0.004) for early-onset CAD (before age 50). This study illustrates the utility of haplotype analysis in family-based association studies to investigate candidate genes. References Rabinowitz, D. & Laird, N. M. (2000) Hum Hered50, 211,223. Zhang, K., Sun, F. & Zhao, H. (2005) Bioinformatics21, 90,103. Andrea Foulkes 1 , Recai Yucel 1 , Xiaohong Li 143 Division of Biostatistics, University of Massachusetts, USA Keywords: Haploytpe, high-dimensional, mixed modeling The explosion of molecular level information coupled with large epidemiological studies presents an exciting opportunity to uncover the genetic underpinnings of complex diseases; however, several analytical challenges remain to be addressed. Characterizing the components to complex diseases inevitably requires consideration of synergies across multiple genetic loci and environmental and demographic factors. In addition, it is critical to capture information on allelic phase, that is whether alleles within a gene are in cis (on the same chromosome) or in trans (on different chromosomes.) In associations studies of unrelated individuals, this alignment of alleles within a chromosomal copy is generally not observed. We address the potential ambiguity in allelic phase in this high dimensional data setting using mixed effects models. Both a semi-parametric and fully likelihood-based approach to estimation are considered to account for missingness in cluster identifiers. In the first case, we apply a multiple imputation procedure coupled with a first stage expectation maximization algorithm for parameter estimation. A bootstrap approach is employed to assess sensitivity to variability induced by parameter estimation. Secondly, a fully likelihood-based approach using an expectation conditional maximization algorithm is described. Notably, these models allow for characterizing high-order gene-gene interactions while providing a flexible statistical framework to account for the confounding or mediating role of person specific covariates. The proposed method is applied to data arising from a cohort of human immunodeficiency virus type-1 (HIV-1) infected individuals at risk for therapy associated dyslipidemia. Simulation studies demonstrate reasonable power and control of family-wise type 1 error rates. Vivien Marquard 1 , Lars Beckmann 1 , Jenny Chang-Claude 144 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Genotyping errors, type I error, haplotype-based association methods It has been shown in several simulation studies that genotyping errors may have a great impact on the type I error of statistical methods used in genetic association analysis of complex diseases. Our aim was to investigate type I error rates in a case-control study, when differential and non-differential genotyping errors were introduced in realistic scenarios. We simulated case-control data sets, where individual genotypes were drawn from a haplotype distribution of 18 haplotypes with 15 markers in the APM1 gene. Genotyping errors were introduced following the unrestricted and symmetric with 0 edges error models described by Heid et al. (2006). In six scenarios, errors resulted from changes of one allele to another with predefined probabilities of 1%, 2.5% or 10%, respectively. A multiple number of errors per haplotype was possible and could vary between 0 and 15, the number of markers investigated. We examined three association methods: Mantel statistics using haplotype-sharing; a haplotype-specific score test; and Armitage trend test for single markers. The type I error rates were not influenced for any of all the three methods for a genotyping error rate of less than 1%. For higher error rates and differential errors, the type I error of the Mantel statistic was only slightly and of the Armitage trend test moderately increased. The type I error rates of the score test were highly increased. The type I error rates were correct for all three methods for non-differential errors. Further investigations will be carried out with different frequencies of differential error rates and focus on power. Arne Neumann 1 , Dörthe Malzahn 1 , Martina Müller 2 , Heike Bickeböller 145 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany 46 GSF-National Research Center for Environment and Health, Neuherberg & IBE-Institute of Epidemiology, Ludwig-Maximilians University München, Germany Keywords: Interaction, longitudinal, nonparametric Longitudinal data show the time dependent course of phenotypic traits. In this contribution, we consider longitudinal cohort studies and investigate the association between two candidate genes and a dependent quantitative longitudinal phenotype. The set-up defines a factorial design which allows us to test simultaneously for the overall gene effect of the loci as well as for possible gene-gene and gene time interaction. The latter would induce genetically based time-profile differences in the longitudinal phenotype. We adopt a non-parametric statistical test to genetic epidemiological cohort studies and investigate its performance by simulation studies. The statistical test was originally developed for longitudinal clinical studies (Brunner, Munzel, Puri, 1999 J Multivariate Anal 70:286-317). It is non-parametric in the sense that no assumptions are made about the underlying distribution of the quantitative phenotype. Longitudinal observations belonging to the same individual can be arbitrarily dependent on one another for the different time points whereas trait observations of different individuals are independent. The two loci are assumed to be statistically independent. Our simulations show that the nonparametric test is comparable with ANOVA in terms of power of detecting gene-gene and gene-time interaction in an ANOVA favourable setting. Rebecca Hein 1 , Lars Beckmann 1 , Jenny Chang-Claude 147 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Indirect association studies, interaction effects, linkage disequilibrium, marker allele frequency Association studies accounting for gene-environment interactions (GxE) may be useful for detecting genetic effects and identifying important environmental effect modifiers. Current technology facilitates very dense marker spacing in genetic association studies; however, the true disease variant(s) may not be genotyped. In this situation, an association between a gene and a phenotype may still be detectable, using genetic markers associated with the true disease variant(s) (indirect association). Zondervan and Cardon [2004] showed that the odds ratios (OR) of markers which are associated with the disease variant depend highly on the linkage disequilibrium (LD) between the variant and the markers, and whether the allele frequencies match and thereby influence the sample size needed to detect genetic association. We examined the influence of LD and allele frequencies on the sample size needed to detect GxE in indirect association studies, and provide tables for sample size estimation. For discordant allele frequencies and incomplete LD, sample sizes can be unfeasibly large. The influence of both factors is stronger for disease loci with small rather than moderate to high disease allele frequencies. A decline in D' of e.g. 5% has less impact on sample size than increasing the difference in allele frequencies by the same percentage. Assuming 80% power, large interaction effects can be detected using smaller sample sizes than those needed for the detection of main effects. The detection of interaction effects involving rare alleles may not be possible. Focussing only on marker density can be a limited strategy in indirect association studies for GxE. Cyril Dalmasso 1 , Emmanuelle Génin 2 , Catherine Bourgain 2 , Philippe Broët 148 JE 2492 , Univ. Paris-Sud, France 49 INSERM UMR-S 535 and University Paris Sud, Villejuif, France Keywords: Linkage analysis, Multiple testing, False Discovery Rate, Mixture model In the context of genome-wide linkage analyses, where a large number of statistical tests are simultaneously performed, the False Discovery Rate (FDR) that is defined as the expected proportion of false discoveries among all discoveries is nowadays widely used for taking into account the multiple testing problem. Other related criteria have been considered such as the local False Discovery Rate (lFDR) that is a variant of the FDR giving to each test its own measure of significance. The lFDR is defined as the posterior probability that a null hypothesis is true. Most of the proposed methods for estimating the lFDR or the FDR rely on distributional assumption under the null hypothesis. However, in observational studies, the empirical null distribution may be very different from the theoretical one. In this work, we propose a mixture model based approach that provides estimates of the lFDR and the FDR in the context of large-scale variance component linkage analyses. In particular, this approach allows estimating the empirical null distribution, this latter being a key quantity for any simultaneous inference procedure. The proposed method is applied on a real dataset. Arief Gusnanto 1 , Frank Dudbridge 150 MRC Biostatistics Unit, Cambridge UK Keywords: Significance, genome-wide, association, permutation, multiplicity Genome-wide association scans have introduced statistical challenges, mainly in the multiplicity of thousands of tests. The question of what constitutes a significant finding remains somewhat unresolved. Permutation testing is very time-consuming, whereas Bayesian arguments struggle to distinguish direct from indirect association. It seems attractive to summarise the multiplicity in a simple form that allows users to avoid time-consuming permutations. A standard significance level would facilitate reporting of results and reduce the need for permutation tests. This is potentially important because current scans do not have full coverage of the whole genome, and yet, the implicit multiplicity is genome-wide. We discuss some proposed summaries, with reference to the empirical null distribution of the multiple tests, approximated through a large number of random permutations. Using genome-wide data from the Wellcome Trust Case-Control Consortium, we use a sub-sampling approach with increasing density to estimate the nominal p-value to obtain family-wise significance of 5%. The results indicate that the significance level is converging to about 1e-7 as the marker spacing becomes infinitely dense. We considered the concept of an effective number of independent tests, and showed that when used in a Bonferroni correction, the number varies with the overall significance level, but is roughly constant in the region of interest. We compared several estimators of the effective number of tests, and showed that in the region of significance of interest, Patterson's eigenvalue based estimator gives approximately the right family-wise error rate. Michael Nothnagel 1 , Amke Caliebe 1 , Michael Krawczak 151 Institute of Medical Informatics and Statistics, University Clinic Schleswig-Holstein, University of Kiel, Germany Keywords: Association scans, Bayesian framework, posterior odds, genetic risk, multiplicative model Whole-genome association scans have been suggested to be a cost-efficient way to survey genetic variation and to map genetic disease factors. We used a Bayesian framework to investigate the posterior odds of a genuine association under multiplicative disease models. We demonstrate that the p value alone is not a sufficient means to evaluate the findings in association studies. We suggest that likelihood ratios should accompany p values in association reports. We argue, that, given the reported results of whole-genome scans, more associations should have been successfully replicated if the consistently made assumptions about considerable genetic risks were correct. We conclude that it is very likely that the vast majority of relative genetic risks are only of the order of 1.2 or lower. Clive Hoggart 1 , Maria De Iorio 1 , John Whittakker 2 , David Balding 152 Department of Epidemiology and Public Health, Imperial College London, UK 53 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: Genome-wide association analyses, shrinkage priors, Lasso Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants of small effect, which is a plausible scenario for many complex diseases. Moreover, many simulation studies assume a single causal variant and so more complex realities are ignored. Analysing large numbers of variants simultaneously is now becoming feasible, thanks to developments in Bayesian stochastic search methods. We pose the problem of SNP selection as variable selection in a regression model. In contrast to single SNP tests this approach simultaneously models the effect of all SNPs. SNPs are selected by a Bayesian interpretation of the lasso (Tibshirani, 1996); the maximum a posterior (MAP) estimate of the regression coefficients, which have been given independent, double exponential prior distributions. The double exponential distribution is an example of a shrinkage prior, MAP estimates with shrinkage priors can be zero, thus all SNPs with non zero regression coefficients are selected. In addition to the commonly-used double exponential (Laplace) prior, we also implement the normal exponential gamma prior distribution. We show that use of the Laplace prior improves SNP selection in comparison with single -SNP tests, and that the normal exponential gamma prior leads to a further improvement. Our method is fast and can handle very large numbers of SNPs: we demonstrate its performance using both simulated and real genome-wide data sets with 500 K SNPs, which can be analysed in 2 hours on a desktop workstation. Mickael Guedj 1,2 , Jerome Wojcik 2 , Gregory Nuel 154 Laboratoire Statistique et Génome, Université d'Evry, Evry France 55 Serono Pharmaceutical Research Institute, Plan-les-Ouates, Switzerland Keywords: Local Replication, Local Score, Association In gene-mapping, replication of initial findings has been put forwards as the approach of choice for filtering false-positives from true signals for underlying loci. In practice, such replications are however too poorly observed. Besides the statistical and technical-related factors (lack of power, multiple-testing, stratification, quality control,) inconsistent conclusions obtained from independent populations might result from real biological differences. In particular, the high degree of variation in the strength of LD among populations of different origins is a major challenge to the discovery of genes. Seeking for Local Replications (defined as the presence of a signal of association in a same genomic region among populations) instead of strict replications (same locus, same risk allele) may lead to more reliable results. Recently, a multi-markers approach based on the Local Score statistic has been proposed as a simple and efficient way to select candidate genomic regions at the first stage of genome-wide association studies. Here we propose an extension of this approach adapted to replicated association studies. Based on simulations, this method appears promising. In particular it outperforms classical simple-marker strategies to detect modest-effect genes. Additionally it constitutes, to our knowledge, a first framework dedicated to the detection of such Local Replications. Juliet Chapman 1 , Claudio Verzilli 1 , John Whittaker 156 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: FDR, Association studies, Bayesian model selection As genomewide association studies become commonplace there is debate as to how such studies might be analysed and what we might hope to gain from the data. It is clear that standard single locus approaches are limited in that they do not adjust for the effects of other loci and problematic since it is not obvious how to adjust for multiple comparisons. False discovery rates have been suggested, but it is unclear how well these will cope with highly correlated genetic data. We consider the validity of standard false discovery rates in large scale association studies. We also show that a Bayesian procedure has advantages in detecting causal loci amongst a large number of dependant SNPs and investigate properties of a Bayesian FDR. Peter Kraft 157 Harvard School of Public Health, Boston USA Keywords: Gene-environment interaction, genome-wide association scans Appropriately analyzed two-stage designs,where a subset of available subjects are genotyped on a genome-wide panel of markers at the first stage and then a much smaller subset of the most promising markers are genotyped on the remaining subjects,can have nearly as much power as a single-stage study where all subjects are genotyped on the genome-wide panel yet can be much less expensive. Typically, the "most promising" markers are selected based on evidence for a marginal association between genotypes and disease. Subsequently, the few markers found to be associated with disease at the end of the second stage are interrogated for evidence of gene-environment interaction, mainly to understand their impact on disease etiology and public health impact. However, this approach may miss variants which have a sizeable effect restricted to one exposure stratum and therefore only a modest marginal effect. We have proposed to use information on the joint effects of genes and a discrete list of environmental exposures at the initial screening stage to select promising markers for the second stage [Kraft et al Hum Hered 2007]. This approach optimizes power to detect variants that have a sizeable marginal effect and variants that have a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. As an example, I discuss a proposed genome-wide association scan for Type II diabetes susceptibility variants based in several large nested case-control studies. Beate Glaser 1 , Peter Holmans 158 Biostatistics and Bioinformatics Unit, Cardiff University, School of Medicine, Heath Park, Cardiff, UK Keywords: Combined case-control and trios analysis, Power, False-positive rate, Simulation, Association studies The statistical power of genetic association studies can be enhanced by combining the analysis of case-control with parent-offspring trio samples. Various combined analysis techniques have been recently developed; as yet, there have been no comparisons of their power. This work was performed with the aim of identifying the most powerful method among available combined techniques including test statistics developed by Kazeem and Farrall (2005), Nagelkerke and colleagues (2004) and Dudbridge (2006), as well as a simple combination of ,2-statistics from single samples. Simulation studies were performed to investigate their power under different additive, multiplicative, dominant and recessive disease models. False-positive rates were determined by studying the type I error rates under null models including models with unequal allele frequencies between the single case-control and trios samples. We identified three techniques with equivalent power and false-positive rates, which included modifications of the three main approaches: 1) the unmodified combined Odds ratio estimate by Kazeem & Farrall (2005), 2) a modified approach of the combined risk ratio estimate by Nagelkerke & colleagues (2004) and 3) a modified technique for a combined risk ratio estimate by Dudbridge (2006). Our work highlights the importance of studies investigating test performance criteria of novel methods, as they will help users to select the optimal approach within a range of available analysis techniques. David Almorza 1 , M.V. Kandus 2 , Juan Carlos Salerno 2 , Rafael Boggio 359 Facultad de Ciencias del Trabajo, University of Cádiz, Spain 60 Instituto de Genética IGEAF, Buenos Aires, Argentina 61 Universidad Nacional de La Plata, Buenos Aires, Argentina Keywords: Principal component analysis, maize, ear weight, inbred lines The objective of this work was to evaluate the relationship among different traits of the ear of maize inbred lines and to group genotypes according to its performance. Ten inbred lines developed at IGEAF (INTA Castelar) and five public inbred lines as checks were used. A field trial was carried out in Castelar, Buenos Aires (34° 36' S , 58° 39' W) using a complete randomize design with three replications. At harvest, individual weight (P.E.), diameter (D.E.), row number (N.H.) and length (L.E.) of the ear were assessed. A principal component analysis, PCA, (Infostat 2005) was used, and the variability of the data was depicted with a biplot. Principal components 1 and 2 (CP1 and CP2) explained 90% of the data variability. CP1 was correlated with P.E., L.E. and D.E., meanwhile CP2 was correlated with N.H. We found that individual weight (P.E.) was more correlated with diameter of the ear (D.E.) than with length (L.E). Five groups of inbred lines were distinguished: with high P.E. and mean N.H. (04-70, 04-73, 04-101 and MO17), with high P.E. but less N.H. (04-61 and B14), with mean P.E. and N.H. (B73, 04-123 and 04-96), with high N.H. but less P.E. (LP109, 04-8, 04-91 and 04-76) and with low P.E. and low N.H. (LP521 and 04-104). The use of PCA showed which variables had more incidence in ear weight and how is the correlation among them. Moreover, the different groups found with this analysis allow the evaluation of inbred lines by several traits simultaneously. Sven Knüppel 1 , Anja Bauerfeind 1 , Klaus Rohde 162 Department of Bioinformatics, MDC Berlin, Germany Keywords: Haplotypes, association studies, case-control, nuclear families The area of gene chip technology provides a plethora of phase-unknown SNP genotypes in order to find significant association to some genetic trait. To circumvent possibly low information content of a single SNP one groups successive SNPs and estimates haplotypes. Haplotype estimation, however, may reveal ambiguous haplotype pairs and bias the application of statistical methods. Zaykin et al. (Hum Hered, 53:79-91, 2002) proposed the construction of a design matrix to take this ambiguity into account. Here we present a set of functions written for the Statistical package R, which carries out haplotype estimation on the basis of the EM-algorithm for individuals (case-control) or nuclear families. The construction of a design matrix on basis of estimated haplotypes or haplotype pairs allows application of standard methods for association studies (linear, logistic regression), as well as statistical methods as haplotype sharing statistics and TDT-Test. Applications of these methods to genome-wide association screens will be demonstrated. Manuela Zucknick 1 , Chris Holmes 2 , Sylvia Richardson 163 Department of Epidemiology and Public Health, Imperial College London, UK 64 Department of Statistics, Oxford Center for Gene Function, University of Oxford, UK Keywords: Bayesian, variable selection, MCMC, large p, small n, structured dependence In large-scale genomic applications vast numbers of markers or genes are scanned to find a few candidates which are linked to a particular phenotype. Statistically, this is a variable selection problem in the "large p, small n" situation where many more variables than samples are available. An additional feature is the complex dependence structure which is often observed among the markers/genes due to linkage disequilibrium or their joint involvement in biological processes. Bayesian variable selection methods using indicator variables are well suited to the problem. Binary phenotypes like disease status are common and both Bayesian probit and logistic regression can be applied in this context. We argue that logistic regression models are both easier to tune and to interpret than probit models and implement the approach by Holmes & Held (2006). Because the model space is vast, MCMC methods are used as stochastic search algorithms with the aim to quickly find regions of high posterior probability. In a trade-off between fast-updating but slow-moving single-gene Metropolis-Hastings samplers and computationally expensive full Gibbs sampling, we propose to employ the dependence structure among the genes/markers to help decide which variables to update together. Also, parallel tempering methods are used to aid bold moves and help avoid getting trapped in local optima. Mixing and convergence of the resulting Markov chains are evaluated and compared to standard samplers in both a simulation study and in an application to a gene expression data set. Reference Holmes, C. C. & Held, L. (2006) Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis1, 145,168. Dawn Teare 165 MMGE, University of Sheffield, UK Keywords: CNP, family-based analysis, MCMC Evidence is accumulating that segmental copy number polymorphisms (CNPs) may represent a significant portion of human genetic variation. These highly polymorphic systems require handling as phenotypes rather than co-dominant markers, placing new demands on family-based analyses. We present an integrated approach to meet these challenges in the form of a graphical model, where the underlying discrete CNP phenotype is inferred from the (single or replicate) quantitative measure within the analysis, whilst assuming an allele based system segregating through the pedigree. [source] Primary mouse embryonic fibroblasts: A model of mesenchymal cartilage formation,JOURNAL OF CELLULAR PHYSIOLOGY, Issue 3 2004Christopher J. Lengner Cartilage formation is an intricate process that requires temporal and spatial organization of regulatory factors in order for a mesenchymal progenitor cell to differentiate through the distinct stages of chondrogenesis. Gene function during this process has best been studied by analysis of in vivo cartilage formation in genetically altered mouse models. Mouse embryonic fibroblasts (MEFs) isolated from such mouse models have been widely used for the study of growth control and DNA damage response. Here, we address the potential of MEFs to undergo chondrogenic differentiation. We demonstrate for the first time that MEFs can enter and complete the program of chondrogenic differentiation ex vivo, from undifferentiated progenitor cells to mature, hypertrophic chondrocytes. We show that chondrogenic differentiation can be induced by cell,cell contact or BMP-2 treatment, while in combination, these conditions synergistically enhance chondrocyte differentiation resulting in the formation of 3-dimensional (3-D) cartilaginous tissue ex vivo. Temporal expression profiles of pro-chondrogenic transcription factors Bapx1 and Sox9 and cartilaginous extracellular matrix (ECM) proteins Collagen Type II and X (Coll II and Coll X) demonstrate that the in vivo progression of chondrocyte maturation is recapitulated in the MEF model system. Our findings establish the MEF as a powerful tool for the generation of cartilaginous tissue ex vivo and for the study of gene function during chondrogenesis. © 2004 Wiley-Liss, Inc. [source] Gene function beyond the single trait: natural variation, gene effects, and evolutionary ecology in Arabidopsis thalianaPLANT CELL & ENVIRONMENT, Issue 1 2005S. J. TONSOR ABSTRACT The purpose of plant functional genomics is to describe the patterns of gene expression and internal plant function underlying the ecological functions that sustain plant growth and reproduction. Plants function as integrated systems in which metabolic and developmental pathways draw on common resource pools and respond to a relatively small number of signal/response systems. Plants are also integrated with their environment, exchanging energy and matter with their surroundings and are consequently sensitive to changes in energy and resource fluxes. These two levels of integration complicate the description of gene function. Internal integration results in single genes often affecting multiple characteristics (pleiotropy) and interacting with multiple other genes (epistasis). Integration with the external environment leads to gene expression and the genes' phenotypic effects varying across environmental backgrounds (gene,environment interaction). An accurate description of the function of all genes requires an augmentation, already underway, of the study of isolated developmental and metabolic pathways to a more integrated approach involving the study of genetic effects across scales of variation usually regarded as the purview of ecological and evolutionary research. Since the evolution of gene function also depends on this complex of gene effects, progress in evolutionary genetics will also require understanding the nature of gene interactions and pleiotropy and the constraints and patterns they impose on adaptive evolution. Studying gene function in the context of the integrated organism is a major challenge, best met by developing co-ordinated research efforts in model systems. This review highlights natural variation in A. thaliana as a system for understanding integrated gene function in an ecological and evolutionary context. The current state of this research integration in A. thaliana is described by summarizing relevant approaches, current knowledge, and some potentially fruitful future studies. By introducing some of the fundamental questions of ecological and evolutionary research, experimental approaches and systems that can reveal new facets of gene function and gene effect are also described. A glossary is included in the Appendix. [source] Network of gene function and its modification by environmental factors and epigenetic events in the formation of head structuresCONGENITAL ANOMALIES, Issue 4 2000Hiroki Otani ABSTRACT A few important aspects when considering the etiology and pathogenesis of congenital anomalies are reviewed and discussed using examples related to morphogenesis of the head and craniofacial structures. Namely, the network and cascade of gene functions, modification by environmental or exogenous factors, and morphogenetic characteristics (epigenetic events) of each body part as the result of a genetic program. [source] Manipulating gene activity in Wnt1-expressing precursors of neural epithelial and neural crest cellsDEVELOPMENTAL DYNAMICS, Issue 1 2010Wei Hsu Abstract Targeted gene disruption or expression often encounters lethality. Conditional approaches, permitting manipulation at desired stages, are required to overcome this problem in order to analyze gene function in later developmental processes. Wnt1 has been shown to be expressed in neural crest precursors at the dorsal midline region. However, its expression was not detected in emigrated neural crest cells, the descendants of Wnt1-expressing precursors. We have developed mouse transgenic systems to manipulate gene activity in the Wnt1-expressing precursors and their derivatives by integrating the tetracycline-dependent activation and Cre-mediated recombination methods. A new Wnt1-rtTA strain, carrying rtTA under control of Wnt1 regulatory elements, has been created for gene manipulation in a spatiotemporal-specific fashion. Together with our previously developed Wnt1-Cre;R26STOPrtTA model, these systems permit conditional gene expression and ablation in pre-migratory and/or post-migratory neural crest cells. This study demonstrated the versatility of our mouse models to achieve gene manipulation in early neural development. Developmental Dynamics 239:338,345, 2010. © 2009 Wiley-Liss, Inc. [source] Database of queryable gene expression patterns for XenopusDEVELOPMENTAL DYNAMICS, Issue 6 2009Michael J. Gilchrist Abstract The precise localization of gene expression within the developing embryo, and how it changes over time, is one of the most important sources of information for elucidating gene function. As a searchable resource, this information has up until now been largely inaccessible to the Xenopus community. Here, we present a new database of Xenopus gene expression patterns, queryable by specific location or region in the embryo. Pattern matching can be driven either from an existing in situ image, or from a user-defined pattern based on development stage schematic diagrams. The data are derived from the work of a group of 21 Xenopus researchers over a period of 4 days. We used a novel, rapid manual annotation tool, XenMARK, which exploits the ability of the human brain to make the necessary distortions in transferring data from the in situ images to the standard schematic geometry. Developmental Dynamics 238:1379,1388, 2009. © 2009 Wiley-Liss, Inc. [source] The Tol2kit: A multisite gateway-based construction kit for Tol2 transposon transgenesis constructsDEVELOPMENTAL DYNAMICS, Issue 11 2007Kristen M. Kwan Abstract Transgenesis is an important tool for assessing gene function. In zebrafish, transgenesis has suffered from three problems: the labor of building complex expression constructs using conventional subcloning; low transgenesis efficiency, leading to mosaicism in transient transgenics and infrequent germline incorporation; and difficulty in identifying germline integrations unless using a fluorescent marker transgene. The Tol2kit system uses site-specific recombination-based cloning (multisite Gateway technology) to allow quick, modular assembly of [promoter],[coding sequence],[3, tag] constructs in a Tol2 transposon backbone. It includes a destination vector with a cmlc2:EGFP (enhanced green fluorescent protein) transgenesis marker and a variety of widely useful entry clones, including hsp70 and beta-actin promoters; cytoplasmic, nuclear, and membrane-localized fluorescent proteins; and internal ribosome entry sequence,driven EGFP cassettes for bicistronic expression. The Tol2kit greatly facilitates zebrafish transgenesis, simplifies the sharing of clones, and enables large-scale projects testing the functions of libraries of regulatory or coding sequences. Developmental Dynamics 236:3088,3099, 2007. © 2007 Wiley-Liss, Inc. [source] Novel genes involved in Ciona intestinalis embryogenesis: Characterization of gene knockdown embryosDEVELOPMENTAL DYNAMICS, Issue 7 2007Mayuko Hamada Abstract The sequenced genome of the urochordate ascidian Ciona intestinalis contains nearly 2,500 genes that have vertebrate homologues, but their functions are as yet unknown. To identify novel genes involved in early chordates embryogenesis, we previously screened 200 Ciona genes by knockdown experiments using specific morpholino oligonucleotides and found that suppression of the translation of 40 genes caused embryonic defects (Yamada et al. [2003] Development 130:6485,6495). We have since examined an additional 304 genes, that is, screening 504 genes overall, and a total of 111 genes showed morphological defects when gene function was suppressed. We further examined the role of these genes in the differentiation of six major tissues of the embryo: endoderm, muscle, epidermis, neural tissue, mesenchyme, and notochord. Based on the similarity of phenotypes of gene knockdown embryos, genes were categorized into several groups, with the suggestion that the genes within a given group are involved in similar developmental processes. For example, five were shown to be novel genes that are likely involved in ,-catenin,mediated endoderm formation. The type of large-scale screening used is, therefore, a powerful approach to identify novel genes with significant developmental functions, the details of which will be determined in future studies. Developmental Dynamics 236:1820,1831, 2007. © 2007 Wiley-Liss, Inc. [source] Bapx1 homeobox gene gain-of-function mice show preaxial polydactyly and activated Shh signaling in the developing limbDEVELOPMENTAL DYNAMICS, Issue 9 2006Carla Tribioli Abstract To explore Bapx1 homeobox gene function in embryonic control of development, we employed a gain-of-function approach to complement our previous loss-of-function mutant analysis. We show that transgenic mice overexpressing Bapx1 are affected by skeletal defects including hindlimb preaxial polydactyly and tibial hypoplasia. Bapx1 overexpression generates limb anteroposterior patterning defects including induction of Shh signaling and ectopic activation of functions downstream of Shh signaling into the anterior region of the autopod. Moreover, Bapx1 overexpression stimulates formation of limb prechondrogenic condensations. We also show that Shh is reciprocally able to activate Bapx1 expression in mouse embryos as the orthologous hedgehog (hh) does with the bagpipe/Bapx1 gene in Drosophila. Our results indicate that Bapx1 can modulate appendicular skeletal formation, that the genetic hierarchy between Shh/hh and Bapx1/bagpipe has been conserved during evolution, and that in mouse embryos these two genes can influence one another in a genetically reciprocal manner. We conclude that it is reasonable to expect overexpression of Bapx1 in certain forms of polydactyly. Developmental Dynamics 235:2483,2492, 2006. © 2006 Wiley-Liss, Inc. [source] Visualizing neurons one-by-one in vivo: Optical dissection and reconstruction of neural networks with reversible fluorescent proteinsDEVELOPMENTAL DYNAMICS, Issue 8 2006Shinsuke Aramaki Abstract A great many axons and dendrites intermingle to fasciculate, creating synapses as well as glomeruli. During live imaging in particular, it is often impossible to distinguish between individual neurons when they are contiguous spatially and labeled in the same fluorescent color. In an attempt to solve this problem, we have taken advantage of Dronpa, a green fluorescent protein whose fluorescence can be erased with strong blue light, and reversibly highlighted with violet or ultraviolet light. We first visualized a neural network with fluorescent Dronpa using the Gal4-UAS system. During the time-lapse imaging of axonal navigation, we erased the Dronpa fluorescence entirely; re-highlighted it in a single neuron anterogradely from the soma or retrogradely from the axon; then repeated this procedure for other single neurons. After collecting images of several individual neurons, we then recombined them in multiple pseudo-colors to reconstruct the network. We have also successfully re-highlighted Dronpa using two-photon excitation microscopy to label individual cells located inside of tissues and were able to demonstrate visualization of a Mauthner neuron extending an axon. These "optical dissection" techniques have the potential to be automated in the future and may provide an effective means to identify gene function in morphogenesis and network formation at the single cell level. Developmental Dynamics 235:2192,2199, 2006. © 2006 Wiley-Liss, Inc. [source] Conditional expression of a myocardium-specific transgene in zebrafish transgenic linesDEVELOPMENTAL DYNAMICS, Issue 4 2005Chiu-Ju Huang Abstract To develop the first heart-specific tetracycline (Tet)-On system in zebrafish, we constructed plasmids in which the cardiac myosin light chain 2 promoter of zebrafish was used to drive the reverse Tet-controlled transactivator (rtTA) and the green fluorescent protein (GFP) reporter gene was preceded by an rtTA-responsive element. In the zebrafish fibroblast cell-line, rtTA-M2, one of rtTA's derivatives, demonstrated the highest increase in luciferase activity upon doxycycline (Dox) induction. We then generated two germ lines of transgenic zebrafish: line T03 was derived from microinjection of a plasmid containing rtTA-M2 and a plasmid containing a responsive reporter gene, whereas line T21 was derived from microinjection of a single dual plasmid. Results showed that line T21 was superior to line T03 in terms of greater GFP intensity after induction and with of minimal leakiness before induction. The photographic images of induced GFP in the heart of F2 larvae showed that the fluorescent level of GFP was dose-responsive. The level of GFP expressed in the F3 3 days postfertilization larvae that were treated with Dox for 1 hr decreased gradually after the withdrawal of the inducer; and the fluorescent signal disappeared after 5 days. The GFP induction and reduction were also tightly controlled by Dox in the F3 adult fish from line T21. This Tet-On system developed in zebrafish shows much promise for the study of the gene function in a specific tissue at the later developmental stage. Developmental Dynamics 233:1294,1303, 2005. © 2005 Wiley-Liss, Inc. [source] Complementation of melanocyte development in SOX10 mutant neural crest using lineage-directed gene transferDEVELOPMENTAL DYNAMICS, Issue 1 2004Ling Hou Abstract An in vitro gene complementation approach has been developed to dissect gene function and regulation in neural crest (NC) development and disease. The approach uses the avian RCAS virus to express genes in NC cells derived from transgenic mice expressing the RCAS receptor TVA, under the control of defined promoter elements. Constructs for creating TVA transgenic mice were developed using site-specific recombination GATEWAY (GW), compatible vectors that can also be used to facilitate analysis of genomic fragments for transcriptional regulatory elements. By using these GW vectors to facilitate cloning, transgenic mouse lines were generated that express TVA in SOX10-expressing NC stem cells under the control of the Pax3 promoter. The Pax3-tv-a transgene was bred onto a Sox10 -deficient background, and the feasibility of complementing genetic NC defects was demonstrated by infecting the Pax3-tv-a cells with an RCAS- Sox10 expression virus, thereby rescuing melanocyte development of Sox10 -deficient NC cells. This system will be useful for assessing genetic hierarchies in NC development. Developmental Dynamics 229:54,62, 2004. © 2003 Wiley-Liss, Inc. [source] Electroporation as a tool to study in vivo spinal cord regenerationDEVELOPMENTAL DYNAMICS, Issue 2 2003K. Echeverri Abstract Tailed amphibians such as axolotls and newts have the unique ability to fully regenerate a functional spinal cord throughout life. Where the cells come from and how they form the new structure is still poorly understood. Here, we describe the development of a technique that allows the visualization of cells in the living animal during spinal cord regeneration. A microelectrode needle is inserted into the lumen of the spinal cord and short rapid pulses are applied to transfer the plasmids encoding the green or red fluorescent proteins into ependymal cells close to the plane of amputation. The use of small, transparent axolotls permits imaging with epifluorescence and differential interference contrast microscopy to track the transfected cells as they contribute to the spinal cord. This technique promises to be useful in understanding how neural progenitors are recruited to the regenerating spinal cord and opens up the possibility of testing gene function during this process. Developmental Dynamics 226:418,425, 2003. © 2003 Wiley-Liss, Inc. [source] RD Lawrence Lecture 2009 Old genes, new tricks: learning about blood glucose regulation from naturally occurring genetic variation in humansDIABETIC MEDICINE, Issue 11 2009A. L. Gloyn Abstract The study of rare monogenic forms of diabetes and pancreatic B-cell dysfunction provides an unrivalled opportunity to link a specific change in gene function with precise cellular consequences and clinical phenotype in humans. Over the past 20 years there has been considerable success in determining the genetic aetiology of a number of rare monogenic forms of diabetes, which has had a significant impact on both our understanding of normal physiology and on translational medicine. The impact of these discoveries has been substantial, with insights into both developmental biology and normal physiology. There are clear examples where determining the genetic aetiology for individuals with rare monogenic subtypes of diabetes has led to improved treatment. Although formerly in the shadow of the monogenic diabetes field, over the past 3 years there has been staggering progress in our understanding of the genetic basis of Type 2 diabetes. This has been largely as a result of genome-wide association studies and has seen the list of ,diabetes susceptibility genes' increase from three to close to 20. There is now encouraging evidence to support a potential role for genetics in determining the response of individuals with Type 2 diabetes to different therapeutic options. One of the challenges that lies ahead is determining how the non-coding genetic variants exert their pathogenicity. It is possible that parallels can be drawn from functional work on rare regulatory mutations causing monogenic forms of diabetes. However, it is more likely that comprehensive approaches will be necessary. [source] Targeting the p53 tumor suppressor gene function in glioblastomas using small chemical moleculesDRUG DEVELOPMENT RESEARCH, Issue 10 2006Roberta Magrini Abstract Glioblastoma multiforme (GBM) is recognized as the most frequent and malignant glioma of which two genetically different subtypes can be distinguished. Primary, de novo glioblastomas show a p53 wild type (wt) status and in 10% of the cases hdm2 overexpression/amplifications occur. In these tumors, the inactivation of the tumor suppressor p53 is elicited by enhanced hdm2-mediated degradation of p53. Secondary glioblastomas, on the other hand, show inactivating p53 mutations (mut) in 40% of the cases. Based on these observations, reactivating the function of p53 might hold promise for treatment of GBM. In wt p53 tumors showing increased hdm2 levels, the therapeutic strategy might be to inhibit the activity of hdm2 by treatment with small molecules like nutlin-3. For mut p53 glioblastomas, p53 function might be restored using small chemical entities such as PRIMA-1. Drug Dev. Res. 67:790,800, 2006. © 2007 Wiley-Liss, Inc. [source] PERSPECTIVE: EVOLUTIONARY DEVELOPMENTAL BIOLOGY AND THE PROBLEM OF VARIATIONEVOLUTION, Issue 4 2000David L. Stern Abstract. One of the oldest problems in evolutionary biology remains largely unsolved. Which mutations generate evolutionarily relevant phenotypic variation? What kinds of molecular changes do they entail? What are the phenotypic magnitudes, frequencies of origin, and pleiotropic effects of such mutations? How is the genome constructed to allow the observed abundance of phenotypic diversity? Historically, the neo-Darwinian synthesizers stressed the predominance of micromutations in evolution, whereas others noted the similarities between some dramatic mutations and evolutionary transitions to argue for macromutationism. Arguments on both sides have been biased by misconceptions of the developmental effects of mutations. For example, the traditional view that mutations of important developmental genes always have large pleiotropic effects can now be seen to be a conclusion drawn from observations of a small class of mutations with dramatic effects. It is possible that some mutations, for example, those in cis -regulatory DNA, have few or no pleiotropic effects and may be the predominant source of morphological evolution. In contrast, mutations causing dramatic phenotypic effects, although superficially similar to hypothesized evolutionary transitions, are unlikely to fairly represent the true path of evolution. Recent developmental studies of gene function provide a new way of conceptualizing and studying variation that contrasts with the traditional genetic view that was incorporated into neo-Darwinian theory and population genetics. This new approach in developmental biology is as important for micro-evolutionary studies as the actual results from recent evolutionary developmental studies. In particular, this approach will assist in the task of identifying the specific mutations generating phenotypic variation and elucidating how they alter gene function. These data will provide the current missing link between molecular and phenotypic variation in natural populations. [source] Silencing of an abdominal Hox gene during early development is correlated with limb development in a crustacean trunkEVOLUTION AND DEVELOPMENT, Issue 2 2010Cheryl C. Hsia SUMMARY We tested whether Artemia abd-A could repress limbs in Drosophila embryos, and found that although abd-A transcripts were produced, ABD-A protein was not. Similarly, developing Artemia epidermal cells showed expression of abd-A transcripts without accumulation of ABD-A protein. This finding in Artemia reveals a new variation in Hox gene function that is associated with morphological evolution. In this case, a HOX protein expression pattern is completely absent during early development, although the HOX protein is expressed at later stages in the central nervous system in a "homeotic-like" pattern. The combination of an absence of ABD-A protein expression in the Artemia limb primordia and the weak repressive function of Artemia UBX protein on the limb-promoting gene Dll are likely to be two reasons why homonomous limbs develop throughout the entire Artemia trunk. [source] Embryonic Stem Cells and Gene TargetingEXPERIMENTAL PHYSIOLOGY, Issue 6 2000Birgit Ledermann The development of gene targeting technology, the exchange of an endogenous allele of a target gene for a mutated copy via homologous recombination, and the application of this technique to murine embryonic stem cells has made it possible to alter the germ-line of mice in a predetermined way. Gene targeting has enabled researchers to generate mouse strains with defined mutations in their genome allowing the analysis of gene function in vivo. This review presents the essential tools and methodologies used for gene targeting that have been developed over the past decade. Special emphasis has been laid on the available embryonic stem cell lines and the importance of the genetic background. Also, the state-of-the art of gene targeting approaches in species other than mice will be discussed. [source] Gene Transfer Strategies for the PhysiologistEXPERIMENTAL PHYSIOLOGY, Issue 6 2000Liang-Fong Wong Foreign genes can be introduced into whole animals using methods of germline transgenesis and somatic gene delivery. While germline transgenesis can generate useful animal models for genetic studies, it can be costly, time-consuming and requires the use of a large number of animals. An alternative means of gene transfer is to deliver genes to somatic cells using non-viral and viral technologies. Non-viral methods such as naked DNA injection, electroporation and liposome/cation lipid-mediated gene transfer are relatively inefficient. In contrast, viruses are effective vehicles that carry foreign genes into a cell rapidly and efficiently. Here we illustrate the usefulness of adenoviral vectors to express a potent and specific inhibitor of cAMP-dependent protein kinase (PKA) to study the role of cyclic 3,,5,-cyclic AMP (cAMP) in the osmotic regulation of the vasopressin gene in a transgenic rat model. The ability to modify endogenous systems within specific cells in a whole animal model allows gene effects to be studied with physiological relevance. The combination of molecular biology and integrative physiology is a powerful application that can aid in the elucidation of how gene function can translate into complex systems in an organism [source] Systemic RNAi of the cockroach vitellogenin receptor results in a phenotype similar to that of the Drosophila yolkless mutantFEBS JOURNAL, Issue 2 2006Laura Ciudad During vitellogenesis, one of the most tightly regulated processes in oviparous reproduction, vitellogenins are incorporated into the oocyte through vitellogenin receptor (VgR)-mediated endocytosis. In this paper, we report the cloning of the VgR cDNA from Blattella germanica, as well as the first functional analysis of VgR following an RNA interference (RNAi) approach. We characterized the VgR, VgR mRNA and protein expression patterns in pre-adult and adult stages of this cockroach, as well as VgR immunolocalization in ovarioles, belonging to the panoistic type. We then specifically disrupted VgR gene function using RNAi techniques. Knockdown of VgR expression led to a phenotype characterized by low yolk content in the ovary and high vitellogenin concentration in the haemolymph. This phenotype is equivalent to that of the yolkless mutant of Drosophila melanogaster, which have the yl (VgR) gene disrupted. The results additionally open the perspective that development genes can be functionally analyzed via systemic RNAi in this basal species. [source] Emergence of a subfamily of xylanase inhibitors within glycoside hydrolase family 18FEBS JOURNAL, Issue 7 2005Anne Durand The xylanase inhibitor protein I (XIP-I), recently identified in wheat, inhibits xylanases belonging to glycoside hydrolase families 10 (GH10) and 11 (GH11). Sequence and structural similarities indicate that XIP-I is related to chitinases of family GH18, despite its lack of enzymatic activity. Here we report the identification and biochemical characterization of a XIP-type inhibitor from rice. Despite its initial classification as a chitinase, the rice inhibitor does not exhibit chitinolytic activity but shows specificities towards fungal GH11 xylanases similar to that of its wheat counterpart. This, together, with an analysis of approximately 150 plant members of glycosidase family GH18 provides compelling evidence that xylanase inhibitors are largely represented in this family, and that this novel function has recently emerged based on a common scaffold. The plurifunctionality of GH18 members has major implications for genomic annotations and predicted gene function. This study provides new information which will lead to a better understanding of the biological significance of a number of GH18 ,inactivated' chitinases. [source] Genome-wide DNA methylation profile of tissue-dependent and differentially methylated regions (T-DMRs) residing in mouse pluripotent stem cellsGENES TO CELLS, Issue 6 2010Shinya Sato DNA methylation profile, consisting of tissue-dependent and differentially methylated regions (T-DMRs), has elucidated tissue-specific gene function in mouse tissues. Here, we identified and profiled thousands of T-DMRs in embryonic stem cells (ESCs), embryonic germ cells (EGCs) and induced pluripotent stem cells (iPSCs). T-DMRs of ESCs compared with somatic tissues well illustrated gene function of ESCs, by hypomethylation at genes associated with CpG islands and nuclear events including transcriptional regulation network of ESCs, and by hypermethylation at genes for tissue-specific function. These T-DMRs in EGCs and iPSCs showed DNA methylation similar to ESCs. iPSCs, however, showed hypomethylation at a considerable number of T-DMRs that were hypermethylated in ESCs, suggesting existence of traceable progenitor epigenetic information. Thus, DNA methylation profile of T-DMRs contributes to the mechanism of pluripotency, and can be a feasible solution for identification and evaluation of the pluripotent cells. [source] Requirement of Runx1/AML1/PEBP2,B for the generation of haematopoietic cells from endothelial cellsGENES TO CELLS, Issue 1 2001Tomomasa Yokomizo Recent studies revealing that endothelial cells derived from E8.5-E10.5 mouse embryos give rise to haematopoietic cells appear to correspond to previous histological observations that haematopoietic cell clusters are attached to the ventral aspect of dorsal aorta in such a way as if they were budding from the endothelial cell layer. Gene disruption studies have revealed that Runx1/AML1 is required for definitive haematopoiesis but not for primitive haematopoiesis, but the precise stage of gene function is not yet known. We found that mice deficient in Runx1/AML1 (an , subunit of the transcription factor PEBP2/CBF) lack c-Kit+ haematopoietic cell clusters in the dorsal aorta, omphalomesenteric and umbilical arteries, as well as yolk sac vessels. Moreover, endothelial cells sorted from the embryo proper and the yolk sac of AML1,/, embryos are unable to differentiate into haematopoietic cells on OP9 stromal cells, whereas colonies of AML1,/, endothelial cells can be formed in culture. These results strongly suggest that the emergence of haematopoietic cells from endothelial cells represents a major pathway of definitive haematopoiesis and is an event that also occurs in the yolk sac in vivo, as suggested by earlier in vitro experiments. [source] Chromosomal fragile sites FRA3B and FRA16D show correlated expression and association with failure of apoptosis in lymphocytes from patients with thyroid cancerGENES, CHROMOSOMES AND CANCER, Issue 5 2006Isabella Sbrana It has been suggested that common fragile sites (cFSs) are related to cancer development. This appears to be the case for FRA3B and FRA16D, localized in two tumor-suppressor genes (FHIT and WWOX, respectively) that are altered by deletions or loss of heterozygosity (LOH) in many cancers. The features responsible for fragility have not yet been identified. Furthermore, it is still unclear whether instability at these regions causes chance deletions and loss of function of the associated genes, or whether the gene function itself is related to the appearance of fragility. In this study, we analyzed cFS expression in lymphocytes from 20 healthy or thyroid cancer,affected subjects exposed to radiation after the Chernobyl accident. The same cells were examined for apoptosis, a principal function of both the FHIT and WWOX genes. Exceptionally elevated chromosome fragility was observed, particularly in cancer patients, affecting FRA3B, FRA16D, and a cluster of less highly expressed cFSs; levels of chromosome fragility were found to be correlated among these cFSs. Interestingly, most expressed cFSs were sites of LOH reported for thyroid tumors; moreover, cells with the highest fragility also had a reduced ability to undergo apoptosis. These findings reveal previously unknown genetic interactions affecting fragile loci, suggestive of a shared function inside mitotic cells. Attenuation of checkpoint control and apoptosis resistance seem to be the cell phenotypes associated with unusual chromosome fragility. We propose that breakage at specific cFS could derive from early epigenetic events at loci involved in radiation carcinogenesis. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat. © 2006 Wiley-Liss, Inc. [source] Construction and characterization of a doxycycline-inducible transgenic system in Msx2 expressing cellsGENESIS: THE JOURNAL OF GENETICS AND DEVELOPMENT, Issue 5 2009Congxing Lin Abstract Homeobox gene Msx2 is widely expressed during both embryogenesis and postnatal development and plays important roles during organogenesis. We developed an Msx2 -rtTA BAC transgenic line which can activate TetO-Cre expression in Msx2 -expressing cells upon doxycycline (Dox) treatment. Using the Rosa26-LacZ (R26R) reporter line, we show that rtTA is activated in Msx2 -expressing organs including the limb, heart, external genitalia, urogenital system, hair follicles and craniofacial regions. Moreover, we show that in body appendages, the transgene can be activated in different domains depending on the timing of Dox treatment. In addition, the transgene can also be effectively activated in adult tissues such as the hair follicle and the urogenital system. Taken together, this Msx2 -rtTA;TetO-Cre system is a valuable tool for studying gene function in the development of the aforementioned organs in a temporal and spatially-restricted manner, as well as for tissue lineage tracing of Msx2 -expressing cells. When induced postnatally, this system can also be used to study gene function in adult tissues without compromising normal development and patterning. genesis 47:352,359, 2009. © 2009 Wiley-Liss, Inc. [source] Conditional transgene expression mediated by the mouse ,-actin locusGENESIS: THE JOURNAL OF GENETICS AND DEVELOPMENT, Issue 11 2007Ulrike Jägle Abstract Transgenic mice are an effective model to study gene function in vivo; however, position effects can complicate tissue-specific transgene analysis. To facilitate precise targeting of a transgenic construct into the mouse genome, we combined the Cre/lox and Flp/FRT recombination systems to allow for rapid transgene replacement and conditional transgene expression from the endogenous ,-actin locus. Flp/FRT recombination was used to rapidly exchange FRT-flanked transgene cassettes by recombinase-mediated cassette exchange in embryonic stem cells, while transgene expression can be activated in mice after Cre-mediated excision of a floxed STOP cassette. To validate our system, we analyzed the expression profile of an EGFP reporter gene after integration into the ,-actin locus and Cre-mediated excision of the floxed STOP cassette. Breeding of EGFP reporter mice with various Cre mouse lines resulted in the expected expression profiles, demonstrating the feasibility of the model to facilitate predictable and strong transgene expression in a spatially and temporally controlled manner. genesis 45:659,666, 2007. © 2007 Wiley-Liss, Inc. [source] Temporal control of gene recombination in astrocytes by transgenic expression of the tamoxifen-inducible DNA recombinase variant CreERT2GLIA, Issue 1 2006Petra G. Hirrlinger Abstract Inducible gene modification using the Cre/loxP system provides a valuable tool for the analysis of gene function in the active animal. GFAP-Cre transgenic mice have been developed to achieve gene recombination in astrocytes, the most abundant cells of the central nervous system, with pivotal roles during brain function and pathology. Unfortunately, these mice displayed neuronal recombination as well, since the GFAP promoter is also active in embryonic radial glia, which possess a substantial neurogenic potential. To enable the temporal control of gene deletions in astrocytes only, we generated a transgenic mouse with expression of CreERT2, a fusion protein of the DNA recombinase Cre and a mutated ligand-binding domain of the estrogen receptor, under the control of the human GFAP promoter. In offspring originating from crossbreedings of GFAP-CreERT2-transgenic mice with various Cre-sensitive reporter mice, consecutive intraperitoneal injections of tamoxifen induced genomic recombination selectively in astrocytes of almost all brain regions. In Bergmann glia, which represent the main astroglial cell population of the cerebellum, virtually all cells showed successful gene recombination. When adult mice received cortical stab wound lesions, simultaneously given tamoxifen induced substantial recombination in reactive glia adjacent to the site of injury. These transgenic GFAP-CreERT2 mice will allow the functional analysis of loxP-modified genes in astroglia of the postnatal and adult brain. © 2006 Wiley-Liss, Inc. [source] Imaging genetics and development: Challenges and promisesHUMAN BRAIN MAPPING, Issue 6 2010B.J. Casey Abstract Excitement with the publication of the human genome has served as catalyst for scientists to uncover the functions of specific genes. The main avenues for understanding gene function have been in behavioral genetics on one end and on the other end, molecular mouse models. Attempts to bridge these approaches have used brain imaging to conveniently link anatomical abnormalities seen in knockout/transgenic mouse models and abnormal patterns of brain activity seen in humans. Although a convenient approach, this article provides examples of challenges for imaging genetics, its application to developmental questions, and promises for future directions. Attempts to link genes, brain, and behavior using behavioral genetics, imaging genetics, and mouse models of behavior are described. Each of these approaches alone, provide limited information on gene function in complex human behavior, but together, they are forming bridges between animal models and human psychiatric disorders. Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc. [source] Prolonged gene knockdown in the tsetse fly Glossina by feeding double stranded RNAINSECT MOLECULAR BIOLOGY, Issue 1 2009D. P. Walshe Abstract Reverse genetic studies based on RNA interference (RNAi) have revolutionized analysis of gene function in most insects. However the necessity of injecting double stranded RNA (dsRNA) inevitably compromises many investigations particularly those on immunity. Additionally, injection of tsetse flies often causes significant mortality. We demonstrate, at transcript and protein level, that delivering dsRNA in the bloodmeal to Glossina morsitans morsitans is as effective as injection in knockdown of the immunoresponsive midgut-expressed gene TsetseEP. However, feeding dsRNA fails to knockdown the fat body expressed transferrin gene, 2A192, previously shown to be silenced by dsRNA injection. Mortality rates of the dsRNA fed flies were significantly reduced compared to injected flies 14 days after treatment (Fed: 10.1%± 1.8%; injected: 37.9% ± 3.6% (Mean ± SEM)). This is the first demonstration in Diptera of gene knockdown by feeding and the first example of knockdown in a blood-sucking insect by including dsRNA in the bloodmeal. [source] RNA interference in ticks: a study using histamine binding protein dsRNA in the female tick Amblyomma americanumINSECT MOLECULAR BIOLOGY, Issue 3 2003M. N. Aljamali Abstract RNA interference (RNAi), a gene silencing process, has been recently exploited to determine gene function by degrading specific mRNAs in several eukaryotic organisms. We constructed a double stranded RNA (dsRNA) from a previously cloned putative Amblyomma americanum histamine binding protein (HBP) to test the significance of using this methodology in the assessment of the function and importance of gene products in ectoparasitic ticks. The female salivary glands incubated in vitro with HBP dsRNA had a significantly lower histamine binding ability. In addition, the injection of HBP dsRNA into the unfed females led both to a reduced histamine binding ability in the isolated salivary glands and to an aberrant tick feeding pattern or host response. Molecular data demonstrated less expression of the HBP mRNA in the RNAi group. Taken together, these results suggest that RNAi might be an important tool for assessing the significance of tick salivary gland secreted proteins modulating responses at the tick,host interface. [source] | |||||||||||||||||||||||||||||||||||||||||||