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Single Mutation (single + mutation)
Selected AbstractsThe role of the second binding loop of the cysteine protease inhibitor, cystatin A (stefin A), in stabilizing complexes with target proteases is exerted predominantly by Leu73FEBS JOURNAL, Issue 22 2002Alona Pavlova The aim of this work was to elucidate the roles of individual residues within the flexible second binding loop of human cystatin A in the inhibition of cysteine proteases. Four recombinant variants of the inhibitor, each with a single mutation, L73G, P74G, Q76G or N77G, in the most exposed part of this loop were generated by PCR-based site-directed mutagenesis. The binding of these variants to papain, cathepsin L, and cathepsin B was characterized by equilibrium and kinetic methods. Mutation of Leu73 decreased the affinity for papain, cathepsin L and cathepsin B by ,,300-fold, >10-fold and ,,4000-fold, respectively. Mutation of Pro74 decreased the affinity for cathepsin B by ,,10-fold but minimally affected the affinity for the other two enzymes. Mutation of Gln76 and Asn77 did not alter the affinity of cystatin A for any of the proteases studied. The decreased affinities were caused exclusively by increased dissociation rate constants. These results show that the second binding loop of cystatin A plays a major role in stabilizing the complexes with proteases by retarding their dissociation. In contrast with cystatin B, only one amino-acid residue of the loop, Leu73, is of principal importance for this effect, Pro74 assisting to a minor extent only in the case of cathepsin B binding. The contribution of the second binding loop of cystatin A to protease binding varies with the protease, being largest, ,,45% of the total binding energy, for inhibition of cathepsin B. [source] A single mutation in the GALC gene is responsible for the majority of late onset Krabbe disease patients in the Catania (Sicily, Italy) region,,HUMAN MUTATION, Issue 7 2007Willy Lissens Abstract A high proportion of patients with late onset forms of Krabbe disease is observed in a region north of Catania in Sicily. Molecular analysis in five families from this region shows that this condition is mainly due to a not previously described p.Gly41Ser substitution in the GALC gene that abolishes catalytic activity of the galactocerebrosidase enzyme, as shown by expression studies. Three patients were homozygous for this mutation, the other two were heterozygous, one with a frameshift mutation and one with a missense mutation on the second allele. Therefore, the mutation must be a mild one since it leads to late onset disease in all patients. In addition, it is on a unique haplotype indicating that it represents a founder mutation. This is also supported by the fact that the mutation was not found in three late onset patients from other regions in Sicily, in whom four novel mutations were identified. © 2007 Wiley-Liss, Inc. [source] Genetic stability (in vivo) of the attenuated oral rabies virus vaccine SAD B19MICROBIOLOGY AND IMMUNOLOGY, Issue 1 2009Aline Beckert ABSTRACT The distribution of oral rabies vaccine baits containing replication-competent live viruses poses certain environmental safety risks; among others, the possibility of reversion to or an increase in virulence. Hence, the genetic stability of the complete genome of the most widely used oral rabies vaccine virus, SAD B19, was examined after four and 10 serial i.c. passages in foxes and mice, respectively. It was shown that the consensus strain of SAD B19 was extremely stable in vivo. After 10 consecutive passages in mice not a single mutation was observed. In foxes, seven single nucleotide exchanges were found between the first and fourth passage, of which only one resulted in an amino acid exchange at position 9240 of the L-gene. This mutation was not observed during the first three passages and, furthermore, it was shown that this mutation was not linked to enhanced virulence. [source] Parkinson's disease due to the R1441G mutation in Dardarin: A founder effect in the basquesMOVEMENT DISORDERS, Issue 11 2006Javier Simón-Sánchez BSc Abstract The recent discovery of mutations in Dardarin (LRRK2) have been related to the appearance of Parkinson's disease in several families. Notably, one single mutation in this gene (R1441G) not only appeared in familial, but also in apparently sporadic Parkinson disease (PD) patients of Basque descent. A clinical population was ascertained, and subjects were classified into Basque and non-Basque descent according to their known ancestry. The R1441G mutation was assayed using an allele-specific polymerase chain reaction, and several single nucleotide polymorphisms surrounding this mutation were analyzed by direct sequencing. In addition to 22 members of the original Basque families where R1441G was identified, we observed 17 carriers of the mutation who were apparently related through a common ancestor. From a clinical perspective, the disease observed in mutation carriers is indistinguishable from that in noncarriers. The R1441G mutation causes a form of Parkinson's disease that is equivalent to that observed in idiopathic Parkinson's disease. This mutation appears in 16.4% and 4.0% of familial and sporadic PD in this Basque population, respectively. © 2006 Movement Disorder Society [source] Imprinted genes and human disease,AMERICAN JOURNAL OF MEDICAL GENETICS, Issue 3 2010Rosanna Weksberg Abstract This issue of Seminars of Medical Genetics features a series of articles on human disorders caused by the dysregulation of imprinted genes. At the outset, there is a review of the general mechanisms by which genomic imprinting is normally regulated followed by an exploration of the clinical and molecular aspects of human imprinting disorders. As we enter an era of bioinformatics and genome-wide analyses with increasing access to high density microarrays and next generation sequencing, it is becoming apparent that the concept of a single mutation or epimutation leading to a disease is outdated. The role of the clinician will become increasingly important, in concert with these molecular advances, in terms of evaluating phenotypic variation to further our understanding of imprinting disorders. Such investigations will benefit children and families as we become better able to define recurrence risk, predict phenotype, and tailor medical management. © 2010 Wiley-Liss, Inc. [source] Simulating evolution by gene duplication of protein features that require multiple amino acid residuesPROTEIN SCIENCE, Issue 10 2004Michael J. Behe MR, multiresidue Abstract Gene duplication is thought to be a major source of evolutionary innovation because it allows one copy of a gene to mutate and explore genetic space while the other copy continues to fulfill the original function. Models of the process often implicitly assume that a single mutation to the duplicated gene can confer a new selectable property. Yet some protein features, such as disulfide bonds or ligand binding sites, require the participation of two or more amino acid residues, which could require several mutations. Here we model the evolution of such protein features by what we consider to be the conceptually simplest route,point mutation in duplicated genes. We show that for very large population sizes N, where at steady state in the absence of selection the population would be expected to contain one or more duplicated alleles coding for the feature, the time to fixation in the population hovers near the inverse of the point mutation rate, and varies sluggishly with the ,th root of 1/N, where , is the number of nucleotide positions that must be mutated to produce the feature. At smaller population sizes, the time to fixation varies linearly with 1/N and exceeds the inverse of the point mutation rate. We conclude that, in general, to be fixed in 108 generations, the production of novel protein features that require the participation of two or more amino acid residues simply by multiple point mutations in duplicated genes would entail population sizes of no less than 109. [source] The nuclear gene HCF107 encodes a membrane-associated R-TPR (RNA tetratricopeptide repeat)-containing protein involved in expression of the plastidial psbH gene in ArabidopsisTHE PLANT JOURNAL, Issue 5 2005Aniruddha P. Sane Summary Expression of the genes of plastidial psbB operon (psbB-psbT-psbH-petB-petD) involves multiple processing events and formation of several mono-, di- and multi-cistronic transcripts which are further regulated by differential stability and expression. Here we describe the identification of the HCF107 gene that is involved in the 5,-end processing/stability and/or translation of the psbH gene and in the translation of the psbB gene. HCF107 is an RNA-TPR-containing protein with 11 RTPRs that are tandemly arranged. A single mutation in the third RTPR that changes a conserved alanine residue to a threonine affects both 5,-end-processed psbH transcript accumulation as well as psbB translation, resulting in disruption of PSII and seedling lethal plants. The protein is localized to the plastid membranes and is present as part of a multi-subunit complex in the range of 60,190 and 600,800 kDa. HCF107 thus represents a new member of the growing helical repeat family of proteins that seem to play a gene-specific role in regulating plastidial gene expression and biogenesis. [source] European 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] Familial mediterranean fever with a single MEFV mutation: Where is the second hit?ARTHRITIS & RHEUMATISM, Issue 6 2009Matthew G. Booty Objective Familial Mediterranean fever (FMF) has traditionally been considered an autosomal-recessive disease; however, it has been observed that a substantial number of patients with clinical FMF possess only 1 demonstrable MEFV mutation. The purpose of this study was to perform an extensive search for a second MEFV mutation in 46 patients diagnosed clinically as having FMF and carrying only 1 high-penetrance FMF mutation. Methods MEFV and other candidate genes were sequenced by standard capillary electrophoresis. In 10 patients, the entire 15-kb MEFV genomic region was resequenced using hybridization-based chip technology. MEFV gene expression levels were determined by quantitative reverse transcription,polymerase chain reaction. Pyrin protein levels were examined by Western blotting. Results A second MEFV mutation was not identified in any of the patients who were screened. Haplotype analysis did not identify a common haplotype that might be associated with the transmission of a second FMF allele. Western blots did not demonstrate a significant difference in pyrin levels between patients with a single mutation and those with a double mutation; however, FMF patients of both types showed higher protein expression as compared with controls and with non-FMF patients with active inflammation. Screening of genes encoding pyrin-interacting proteins identified rare mutations in a small number of patients, suggesting the possibility of digenic inheritance. Conclusion Our data underscore the existence of a significant subset of FMF patients who are carriers of only 1 MEFV mutation and demonstrate that complete MEFV sequencing is not likely to yield a second mutation. Screening for the set of the most common mutations and detection of a single mutation appears to be sufficient in the presence of clinical symptoms for the diagnosis of FMF and the initiation of a trial of colchicine. [source] Clinical disease among patients heterozygous for familial mediterranean fever,ARTHRITIS & RHEUMATISM, Issue 6 2009Dina Marek-Yagel Objective To define the molecular basis of familial Mediterranean fever (FMF) in patients with only 1 mutation in the MEFV gene. Methods Genetic analysis was performed in 20 FMF patients, including full sequencing of complementary DNA (cDNA) samples and multiplex ligation-dependent probe amplification analysis. In patients with first-degree relatives with FMF, haplotype analysis was also performed. Results A second mutation was found in 2 patients. In the other 18 patients, we could not identify additional mutations, large genomic deletions, or duplications. Analysis of single-nucleotide polymorphisms along the cDNA ruled out a lack of expression of 1 of the alleles. In 2 of the 3 families in which more than 1 sibling had FMF, we showed that the affected siblings inherited a different MEFV allele from the parent who did not have the MEFV mutation. Conclusion These findings are highly consistent with the existence of a clinical phenotype among some patients who are heterozygous for FMF and could explain the vertical transmission in some families. A single mutation in the MEFV gene may be much more common than was previously thought and may include up to 25% of patients who are diagnosed as having FMF. [source] Systematic study on crystal-contact engineering of diphthine synthase: influence of mutations at crystal-packing regions on X-ray diffraction qualityACTA CRYSTALLOGRAPHICA SECTION D, Issue 10 2008Hisashi Mizutani It is well known that protein crystallizability can be influenced by site-directed mutagenesis of residues on the molecular surface of proteins, indicating that the intermolecular interactions in crystal-packing regions may play a crucial role in the structural regularity at atomic resolution of protein crystals. Here, a systematic examination was made of the improvement in the diffraction resolution of protein crystals on introducing a single mutation of a crystal-packing residue in order to provide more favourable packing interactions, using diphthine synthase from Pyrococcus horikoshii OT3 as a model system. All of a total of 21 designed mutants at 13 different crystal-packing residues yielded almost isomorphous crystals from the same crystallization conditions as those used for the wild-type crystals, which diffracted X-rays to 2.1,Ĺ resolution. Of the 21 mutants, eight provided crystals with an improved resolution of 1.8,Ĺ or better. Thus, it has been clarified that crystal quality can be improved by introducing a suitable single mutation of a crystal-packing residue. In the improved crystals, more intimate crystal-packing interactions than those in the wild-type crystal are observed. Notably, the mutants K49R and T146R yielded crystals with outstandingly improved resolutions of 1.5 and 1.6,Ĺ, respectively, in which a large-scale rearrangement of packing interactions was unexpectedly observed despite the retention of the same isomorphous crystal form. In contrast, the mutants that provided results that were in good agreement with the designed putative structures tended to achieve only moderate improvements in resolution of up to 1.75,Ĺ. These results suggest a difficulty in the rational prediction of highly effective mutations in crystal engineering. [source] Cre recombinase-mediated site-specific modification of a cellular genome using an integrase-defective retroviral vectorBIOTECHNOLOGY & BIOENGINEERING, Issue 4 2010Shuohao Huang Abstract Retroviral integrase is an enzyme responsible for the integration of retroviruses. A single mutation in the integrase core domain can severely compromise its integration ability, leading to the accumulation of circular retroviral cDNA in the nuclei of infected cells. We therefore attempted to use those cDNA as substrates for Cre recombinase to perform a recombinase-mediated cassette exchange (RMCE), thereby targeting retroviral vectors to a predetermined site. An expression unit containing a promoter, an ATG codon and marker genes (hygromycin resistance gene and red fluorescent protein gene) flanked by wild-type and mutant loxP sites was first introduced into cellular chromosome to build founder cell lines. We then constructed another plasmid for the production of integrase-defective retroviral vectors (IDRV), which contains an ATG-deficient neomycin resistance gene and green fluorescent protein gene, flanked by a compatible pair of loxPs. After providing founder cells with Cre and infecting with IDRV later, effective RMCE occurred, resulting in the appearance of G418-resistant colonies and a change in the color of fluorescence from red to green. Southern blot and PCR analyses on selected clones further confirmed site-specific recombination. The successful substitution of the original viral integration machinery with a non-viral mechanism could expand the application of retroviral vectors. Biotechnol. Bioeng. 2010;107:717,729. © 2010 Wiley Periodicals, Inc. [source] Functional expression and stabilization of horseradish peroxidase by directed evolution in Saccharomyces cerevisiaeBIOTECHNOLOGY & BIOENGINEERING, Issue 2 2001Birgit Morawski Abstract Biotechnology applications of horseradish peroxidase (HRP) would benefit from access to tailor-made variants with greater specific activity, lower Km for peroxide, and higher thermostability. Starting with a mutant that is functionally expressed in Saccharomyces cerevisiae, we used random mutagenesis, recombination, and screening to identify HRP-C mutants that are more active and stable to incubation in hydrogen peroxide at 50°C. A single mutation (N175S) in the HRP active site was found to improve thermal stability. Introducing this mutation into an HRP variant evolved for higher activity yielded HRP 13A7-N175S, whose half-life at 60°C and pH 7.0 is three times that of wild-type (recombinant) HRP and a commercially available HRP preparation from Sigma (St. Louis, MO). The variant is also more stable in the presence of H2O2, SDS, salts (NaCl and urea), and at different pH values. Furthermore, this variant is more active towards a variety of small organic substrates frequently used in diagnostic applications. Site-directed mutagenesis to replace each of the four methionine residues in HRP (M83, M181, M281, M284) with isoleucine revealed no mutation that significantly increased the enzyme's stability to hydrogen peroxide. © 2001 John Wiley & Sons, Inc. Biotechnol Bioeng 76: 99,107, 2001. [source] Testing for CHEK2 in the cancer genetics clinic: ready for prime time?CLINICAL GENETICS, Issue 1 2010SA Narod Narod SA. Testing for CHEK2 in the cancer genetics clinic: ready for prime time? The 1100delC mutation of the CHEK2 gene was found to be a cause of breast cancer in 2002. The lifetime risk of breast cancer among women with a mutation and with a family history of breast cancer is approximately 25%. These women are good candidates for screening with MRI and for chemoprevention with tamoxifen. It is reasonable to test for this single mutation when women undergo testing for BRCA1 and BRCA2. [source] Role of menaquinone biosynthesis genes in selenate reduction by Enterobacter cloacae SLD1a-1 and Escherichia coli K12ENVIRONMENTAL MICROBIOLOGY, Issue 1 2009Jincai Ma Summary In this study, we investigated the role of menaquinone biosynthesis genes in selenate reduction by Enterobacter cloacae SLD1a-1 and Escherichia coli K12. A mini-Tn5 transposon mutant of E. cloacae SLD1a-1, designated as 4E6, was isolated that had lost the ability to reduce Se(VI) to Se(0). Genetic analysis of mutant strain 4E6 showed that the transposon was inserted within a menD gene among a menFDHBCE gene cluster that encodes for proteins required for menaquinone biosynthesis. A group of E. coli K12 strains with single mutations in the menF, menD, menC and menE genes were tested for loss of selenate reduction activity. The results showed that E. coli K12 carrying a deletion of either the menD, menC or menE gene was unable to reduce selenate. Complementation using wild-type sequences of the E. cloacae SLD1a-1 menFDHBCE sequence successfully restored the selenate reduction activity in mutant strain 4E6, and E. coli K12 menD and menE mutants. Selenate reduction activity in 4E6 was also restored by chemical complementation using the menaquinone precursor compound 1,4-dihydroxy-2-nathphoic acid. The results of this work suggest that menaquinones are an important source of electrons for the selenate reductase, and are required for selenate reduction activity in E. cloacae SLD1a-1 and E. coli K12. [source] Effect of the disease-causing mutations identified in human ribonuclease (RNase) H2 on the activities and stabilities of yeast RNase H2 and archaeal RNase HIIFEBS JOURNAL, Issue 19 2008Muhammad S. Rohman Eukaryotic ribonuclease (RNase) H2 consists of one catalytic and two accessory subunits. Several single mutations in any one of these subunits of human RNase H2 cause Aicardi,Goutičres syndrome. To examine whether these mutations affect the complex stability and activity of RNase H2, three mutant proteins of His-tagged Saccharomyces cerevisiae RNase H2 (Sc-RNase H2*) were constructed. Sc-G42S*, Sc-L52R*, and Sc-K46W* contain single mutations in Sc-Rnh2Ap*, Sc-Rnh2Bp*, and Sc-Rnh2Cp*, respectively. The genes encoding the three subunits were coexpressed in Escherichia coli, and Sc-RNase H2* and its derivatives were purified in a heterotrimeric form. All of these mutant proteins exhibited enzymatic activity. However, only the enzymatic activity of Sc-G42S* was greatly reduced compared to that of the wild-type protein. Gly42 is conserved as Gly10 in Thermococcus kodakareansis RNase HII. To analyze the role of this residue, four mutant proteins, Tk-G10S, Tk-G10A, Tk-G10L, and Tk-G10P, were constructed. All mutant proteins were less stable than the wild-type protein by 2.9,7.6 °C in Tm. A comparison of their enzymatic activities, substrate binding affinities, and CD spectra suggests that the introduction of a bulky side chain into this position induces a local conformational change, which is unfavorable for both activity and substrate binding. These results indicate that Gly10 is required to make the protein fully active and stable. [source] Critical role of C/EBP, and C/EBP, factors in the stimulation of the cyclooxygenase-2 gene transcription by interleukin-1, in articular chondrocytesFEBS JOURNAL, Issue 23 2000Béatrice Thomas The activity of the [,831; +103] promoter of the human cyclooxygenase-2 gene in cultured rabbit chondrocytes is stimulated 2.9 ± 0.3-fold by interleukin-1, and this stimulation depends on [,132; ,124] C/EBP binding-and [,223; ,214] NF-,B binding-sites. The C/EBP, and C/EBP, factors bind to the [,132; ,124] sequence. The [,61; ,53] sequence is also recognized by C/EBP, and C/EBP, as well as USF. Mutation of the whole [,61; ,53] sequence abolished the stimulation of transcription but single mutations of the C/EBP or USF site did not alter the activity of the promoter, suggesting that the factors bound to the proximal [,61; ,53] sequence interact with different members of the general transcription machinery. The [,223; ,214] site binds only the p50/p50 homodimer and a non-rel-related protein, but not the transcriptionally active heterodimer p50/p65. The p50/p50 homodimer could interact with the C/EBP family members bound to the [,132; ,124] sequence for full stimulation of the COX-2 transcription by interleukin-1, in chondrocytes. By contrast, the [,448; ,449] sequence binds with a low affinity both the p50/p50 homodimeric and p50/p65 heterodimeric forms of NF-,B but has no role in the regulation of the human COX-2 promoter in chondrocytes. [source] Mutations towards enantioselectivity adversely affect secretion of Pseudomonas aeruginosa lipaseFEMS MICROBIOLOGY LETTERS, Issue 1 2008Sascha Hausmann Abstract Lipases are important biocatalysts used as detergent additives to manufacture biodiesel, and in particular, for the production of enantiopure compounds such as alcohols, amines and carboxylic acids. Extensive efforts were conducted trying to optimize lipase properties and lipase LipA of Pseudomonas aeruginosa comprises the best-studied example in terms of optimizing enantioselectivity by application of numerous directed evolution methods. Its enantioselectivity in the asymmetric hydrolysis of the model substrate 2-methyldecanoic acid p -nitrophenyl ester was increased from E=1.1 for the wild-type enzyme to E=51 for the best (S)-enantioselective variant which carried six amino acid exchanges. We have observed that overexpression of this variant in the homologous host resulted in only marginal yields of enzyme in the bacterial culture supernatant, suggesting that the enantioselective LipA variant was secreted with only low efficiency. Hence, we have analysed the secretion of this lipase variant and compared it to variants carrying either the respective single mutations or some combinations. We report here the identification of two amino acid substitutions located on the protein surface, which significantly impair lipase secretion. [source] Differential regulation of amoA and amoB gene copies in Nitrosomonas europaeaFEMS MICROBIOLOGY LETTERS, Issue 2 2000Lisa Y Stein Abstract Nitrosomonas europaea contains two nearly identical copies of the operon, amoCAB, which encodes the ammonia monooxygenase (AMO) enzyme. Cells of N. europaea containing single mutations in either amoA or amoB gene copies were incubated in ammonium both prior to and after exposure to acetylene or light. For each strain, the O2 consumption rates and amounts of AmoA polypeptide, the active site-containing subunit of AMO, produced in each strain were determined. Strains carrying a mutation in either the amoA2 or amoB2 genes responded similarly to wild-type cells, but the strains carrying mutations in the amoA1 or amoB1 genes responded differently from the wild-type, or from each other. These results suggest that the copies of amoA and amoB are differentially regulated upon exposure to different external stimuli. [source] A Diversified Library of Bacterial and Fungal Bifunctional Cytochrome P450 Enzymes for Drug Metabolite SynthesisADVANCED SYNTHESIS & CATALYSIS (PREVIOUSLY: JOURNAL FUER PRAKTISCHE CHEMIE), Issue 13 2009Roland Weis Abstract Innovative biohydroxylation catalysts for the preparation of drug metabolites were developed from scratch. A set of bacterial and fungal sequences of putative and already known bifunctional P450 enzymes was identified by protein sequence alignments, expressed in Escherichia coli and characterised. Notably, a fungal self-sufficient cytochrome P450 (CYP) from Aspergillus fumigatus turned out to be especially stable during catalyst preparation and application and also in presence of organic co-solvents. To enhance the catalytic activity and broaden the substrate specificity of those variants with high expression levels prominent single mutations were introduced. Selected improved variants were then used as lyophilised bacterial lysates for the synthesis of 4,-hydroxydiclofenac and 6-hydroxychlorzoxazone, the two metabolites of active pharmaceutical compounds diclofenac and chlorzoxazone representing the same metabolites as generated by human P450s. [source] Interactive signalling by phytochromes and cryptochromes generates de-etiolation homeostasis in Arabidopsis thalianaPLANT CELL & ENVIRONMENT, Issue 2 2001M. A. Mazzella ABSTRACT Single, double, triple and quadruple mutants of phyA, phyB, cry1 and cry2 were exposed to different sunlight irradiances and photoperiods to investigate the roll played by phytochrome A, phytochrome B, cryptochrome 1 and cryptochrome 2 during de-etiolation of Arabidopsis thaliana seedlings under natural radiation. Even the quadruple mutant retained some hypocotyl-growth inhibition by sunlight. Hypocotyl length was strongly affected by interactions among photoreceptors. Double phyA phyB, phyA cry1, and cry1 cry2 mutants were taller than expected from the additive action of single mutations. Some of these redundant interactions required the presence of phytochromes A and/or B. Interactions among photoreceptors resulted in a 44% reduction of the response to irradiance and a 70% reduction of the response to photoperiod. The complex network of interactions among photoreceptors is proposed to buffer de-etiolation against changes in irradiance and photoperiod, i.e light fluctuations not related to the positions of the shoot above or below soil level [source] Mutations of key hydrophobic surface residues of 11,-hydroxysteroid dehydrogenase type 1 increase solubility and monodispersity in a bacterial expression systemPROTEIN SCIENCE, Issue 7 2009Alexander J. Lawson Abstract 11,-Hydroxysteroid dehydrogenase type 1 (11,-HSD1) is a key enzyme in the conversion of cortisone to the functional glucocorticoid hormone cortisol. This activation has been implicated in several human disorders, notably the metabolic syndrome where 11,-HSD1 has been identified as a novel target for potential therapeutic drugs. Recent crystal structures have revealed the presence of a pronounced hydrophobic surface patch lying on two helices at the C-terminus. The physiological significance of this region has been attributed to facilitating substrate access by allowing interactions with the endoplasmic reticulum membrane. Here, we report that single mutations that alter the hydrophobicity of this patch (I275E, L266E, F278E, and L279E in the human enzyme and I275E, Y266E, F278E, and L279E in the guinea pig enzyme) result in greatly increased yields of soluble protein on expression in E. coli. Kinetic analyses of both reductase and dehydrogenase reactions indicate that the F278E mutant has unaltered Km values for steroids and an unaltered or increased kcat. Analytical ultracentrifugation shows that this mutation also decreases aggregation of both the human and guinea pig enzymes, resulting in greater monodispersity. One of the mutants (guinea pig F278E) has proven easy to crystallize and has been shown to have a virtually identical structure to that previously reported for the wild-type enzyme. The human F278E enzyme is shown to be a suitable background for analyzing the effects of naturally occurring mutations (R137C, K187N) on enzyme activity and stability. Hence, the F278E mutants should be useful for many future biochemical and biophysical studies of the enzyme. [source] Plumage colour mutations and melanins in the feathers of the Japanese quail: a first comparisonANIMAL GENETICS, Issue 6 2009F. Minvielle Summary The absorbance of melanin content from dorsal feathers was compared between wild-type Japanese quail and nine other quail plumage colours determined by single mutations in one of seven genes: extended brown (MC1R), yellow (ASIP), silver (MITF), lavender (MLPH), roux (TYRP1), imperfect albinism (SLC45A2) and rusty. As compared with wild-type quail, all mutations but extended brown decreased total melanins. The largest decrease was observed in quail with one of the dilution mutations at TYRP1, MLPH or SLCA45A2. No difference in eumelanins was found between the 10 plumage colours. Despite visible colour differences, homozygous and heterozygous mutants at MITF, or the two imperfect albino (white) and cinnamon (pale yellow) alleles at SLC45A2, could not be differentiated on the basis of melanins. In contrast, the two white phenotypes caused by mutations at MITF and SLC45A2, or the two reddish plumage colours caused by the roux and rusty non-allelic mutations had different total melanin contents. The results showed that rusty was not likely to be a dilution mutation. [source] A polymorphism within the equine CRISP3 gene is associated with stallion fertility in Hanoverian warmblood horsesANIMAL GENETICS, Issue 3 2007H. Hamann Summary Fertility of stallions is of high economic importance, especially for large breeding organisations and studs. Breeding schemes with respect to fertility traits and selection of stallions at an early stage may be improved by including molecular genetic markers associated with traits. The genes coding for equine cysteine-rich secretory proteins (CRISPs) are promising candidate genes because previous studies have shown that CRISPs play a role in the fertilising ability of male animals. We have previously characterised the three equine CRISP genes and identified a non-synonymous polymorphism in the CRISP1 gene. In this study, we report one non-synonymous polymorphism in the CRISP2 gene and four non-synonymous polymorphisms in the CRISP3 gene. All six CRISP polymorphisms were genotyped in 107 Hanoverian breeding stallions. Insemination records of stallions were used to analyse the association between CRISP polymorphisms and fertility traits. Three statistical models were used to evaluate the influence of single mutations, genotypes and haplotypes of the polymorphisms. The CRISP3 AJ459965:c.+622G>A SNP leading to the amino acid substitution E208K was significantly associated with the fertility of stallions. Stallions heterozygous for the CRISP3 c.+622G>A SNP had lower fertility than homozygous stallions (P = 0.0234). The pregnancy rate per cycle in these stallions was estimated to be ,7% lower than in stallions homozygous at this position. [source] Structure of a highly stable mutant of human fibroblast growth factor 1ACTA CRYSTALLOGRAPHICA SECTION D, Issue 1 2009Anna Szlachcic Fibroblast growth factors (FGFs) are involved in diverse cellular processes such as cell migration, angiogenesis, osteogenesis, wound healing and embryonic and foetal development. Human acidic fibroblast growth factor (FGF-1) is the only member of the FGF family that binds with high affinity to all four FGF receptors and thus is considered to be the human mitogen with the broadest specificity. However, pharmacological applications of FGF-1 are limited owing to its low stability. It has previously been reported that the introduction of single mutations can significantly improve the stability of FGF-1 and its resistance to proteolytic degradation. Here, the structure of the Q40P/S47I/H93G triple mutant of FGF-1, which exhibits much higher stability, a prolonged half-life and enhanced mitogenic activity, is presented. Compared with the wild-type structure, three localized conformational changes in the stable triple mutant were observed, which is in agreement with the perfect energetic additivity of the single mutations described in a previous study. The huge change in FGF-1 stability (the denaturation temperature increased by 21.5,K, equivalent to ,,Gden = 24.3,kJ,mol,1) seems to result from the formation of a short 310 -helix (position 40), an improvement in the propensity of amino acids to form ,-sheets (position 47) and the rearrangement of a local hydrogen-bond network (positions 47 and 93). [source] Theoretical Study of Catalytic Efficiency of a Diels,Alderase Catalytic Antibody: An Indirect Effect Produced During the Maturation ProcessCHEMISTRY - A EUROPEAN JOURNAL, Issue 2 2008Sergio Martí Dr. Abstract The Diels,Alder reaction is one of the most important and versatile transformations available to organic chemists for the construction of complex natural products, therapeutics agents, and synthetic materials. Given the lack of efficient enzymes capable of catalyzing this kind of reaction, it is of interest to ask whether a biological catalyst could be designed from an antibody-combining site. In the present work, a theoretical study of the different behavior of a germline catalytic antibody (CA) and its matured form, 39,A-11, that catalyze a Diels,Alder reaction has been carried out. A free-energy perturbation technique based on a hybrid quantum-mechanics/molecular-mechanics scheme, together with internal energy minimizations, has allowed free-energy profiles to be obtained for both CAs. The profiles show a smaller barrier for the matured form, which is in agreement with the experimental observation. Free-energy profiles were obtained with this methodology, thereby avoiding the much more demanding two-dimensional calculations of the energy surfaces that are normally required to study this kind of reaction. Structural analysis and energy evaluations of substrate,protein interactions have been performed from averaged structures, which allows understanding of how the single mutations carried out during the maturation process can be responsible for the observed fourfold enhancement of the catalytic rate constant. The conclusion is that the mutation effect in this studied germline CA produces a complex indirect effect through coupled movements of the backbone of the protein and the substrate. [source] | ||||||||||||||||||||||||||||