WorldWideScience

Sample records for quantitative genetic interaction

  1. Interacting personalities: behavioural ecology meets quantitative genetics.

    Science.gov (United States)

    Dingemanse, Niels J; Araya-Ajoy, Yimen G

    2015-02-01

    Behavioural ecologists increasingly study behavioural variation within and among individuals in conjunction, thereby integrating research on phenotypic plasticity and animal personality within a single adaptive framework. Interactions between individuals (cf. social environments) constitute a major causative factor of behavioural variation at both of these hierarchical levels. Social interactions give rise to complex 'interactive phenotypes' and group-level emergent properties. This type of phenotype has intriguing evolutionary implications, warranting a cohesive framework for its study. We detail here how a reaction-norm framework might be applied to usefully integrate social environment theory developed in behavioural ecology and quantitative genetics. The proposed emergent framework facilitates firm integration of social environments in adaptive research on phenotypic characters that vary within and among individuals.

  2. Complex genetic interactions in a quantitative trait locus.

    Directory of Open Access Journals (Sweden)

    Himanshu Sinha

    2006-02-01

    Full Text Available Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs, characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg QTGs (MKT1, END3, and RHO2. We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3'UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.

  3. Quantitative genetic-interaction mapping in mammalian cells

    Science.gov (United States)

    Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

    2013-01-01

    Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

  4. Quantitative Genetic Interactions Reveal Layers of Biological Modularity

    Science.gov (United States)

    Beltrao, Pedro; Cagney, Gerard; Krogan, Nevan J.

    2010-01-01

    In the past, biomedical research has embraced a reductionist approach, primarily focused on characterizing the individual components that comprise a system of interest. Recent technical developments have significantly increased the size and scope of data describing biological systems. At the same time, advances in the field of systems biology have evoked a broader view of how the underlying components are interconnected. In this essay, we discuss how quantitative genetic interaction mapping has enhanced our view of biological systems, allowing a deeper functional interrogation at different biological scales. PMID:20510918

  5. Automated identification of pathways from quantitative genetic interaction data

    Science.gov (United States)

    Battle, Alexis; Jonikas, Martin C; Walter, Peter; Weissman, Jonathan S; Koller, Daphne

    2010-01-01

    High-throughput quantitative genetic interaction (GI) measurements provide detailed information regarding the structure of the underlying biological pathways by reporting on functional dependencies between genes. However, the analytical tools for fully exploiting such information lag behind the ability to collect these data. We present a novel Bayesian learning method that uses quantitative phenotypes of double knockout organisms to automatically reconstruct detailed pathway structures. We applied our method to a recent data set that measures GIs for endoplasmic reticulum (ER) genes, using the unfolded protein response as a quantitative phenotype. The results provided reconstructions of known functional pathways including N-linked glycosylation and ER-associated protein degradation. It also contained novel relationships, such as the placement of SGT2 in the tail-anchored biogenesis pathway, a finding that we experimentally validated. Our approach should be readily applicable to the next generation of quantitative GI data sets, as assays become available for additional phenotypes and eventually higher-level organisms. PMID:20531408

  6. Functional Maps of Protein Complexes from Quantitative Genetic Interaction Data

    OpenAIRE

    Sourav Bandyopadhyay; Ryan Kelley; Krogan, Nevan J.; Trey Ideker

    2008-01-01

    Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relat...

  7. Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

    Science.gov (United States)

    In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

  8. Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

    Directory of Open Access Journals (Sweden)

    Jaeyong Yee

    2015-01-01

    Full Text Available A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait.

  9. Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci

    NARCIS (Netherlands)

    Jansen, R.C.; Ooijen, J.W. van; Stam, P.; Lister, C.; Dean, C.

    1995-01-01

    The interval mapping method is widely used for the genetic mapping of quantitative trait loci (QTLs), though true resolution of quantitative variation into QTLs is hampered with this method. Separation of QTLs is troublesome, because single-QTL is models are fitted. Further, genotype-by-environment

  10. Kernel Approach for Modeling Interaction Effects in Genetic Association Studies of Complex Quantitative Traits.

    Science.gov (United States)

    Broadaway, K Alaine; Duncan, Richard; Conneely, Karen N; Almli, Lynn M; Bradley, Bekh; Ressler, Kerry J; Epstein, Michael P

    2015-07-01

    The etiology of complex traits likely involves the effects of genetic and environmental factors, along with complicated interaction effects between them. Consequently, there has been interest in applying genetic association tests of complex traits that account for potential modification of the genetic effect in the presence of an environmental factor. One can perform such an analysis using a joint test of gene and gene-environment interaction. An optimal joint test would be one that remains powerful under a variety of models ranging from those of strong gene-environment interaction effect to those of little or no gene-environment interaction effect. To fill this demand, we have extended a kernel machine based approach for association mapping of multiple SNPs to consider joint tests of gene and gene-environment interaction. The kernel-based approach for joint testing is promising, because it incorporates linkage disequilibrium information from multiple SNPs simultaneously in analysis and permits flexible modeling of interaction effects. Using simulated data, we show that our kernel machine approach typically outperforms the traditional joint test under strong gene-environment interaction models and further outperforms the traditional main-effect association test under models of weak or no gene-environment interaction effects. We illustrate our test using genome-wide association data from the Grady Trauma Project, a cohort of highly traumatized, at-risk individuals, which has previously been investigated for interaction effects. © 2015 WILEY PERIODICALS, INC.

  11. Quantitative genome-wide genetic interaction screens reveal global epistatic relationships of protein complexes in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Mohan Babu

    2014-02-01

    Full Text Available Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI screens can provide insights into the biological role(s of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.

  12. Quantitative genetics of disease traits.

    Science.gov (United States)

    Wray, N R; Visscher, P M

    2015-04-01

    John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971; 35: 47; Reich, James and Morris Annals of Human Genetics, 1972; 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics.

  13. Theory and Practice in Quantitative Genetics

    DEFF Research Database (Denmark)

    Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C

    2003-01-01

    With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative...... geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships......) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each...

  14. Quantitative genetic studies of antisocial behaviour.

    Science.gov (United States)

    Viding, Essi; Larsson, Henrik; Jones, Alice P

    2008-08-12

    This paper will broadly review the currently available twin and adoption data on antisocial behaviour (AB). It is argued that quantitative genetic research can make a significant contribution to further the understanding of how AB develops. Genetically informative study designs are particularly useful for investigating several important questions such as whether: the heritability estimates vary as a function of assessment method or gender; the relative importance of genetic and environmental influences varies for different types of AB; the environmental risk factors are truly environmental; and genetic vulnerability influences susceptibility to environmental risk. While the current data are not yet directly translatable for prevention and treatment programmes, quantitative genetic research has concrete translational potential. Quantitative genetic research can supplement neuroscience research in informing about different subtypes of AB, such as AB coupled with callous-unemotional traits. Quantitative genetic research is also important in advancing the understanding of the mechanisms by which environmental risk operates.

  15. Strategies for MCMC computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibánez, N.; Sorensen, Daniel

    2006-01-01

    Given observations of a trait and a pedigree for a group of animals, the basic model in quantitative genetics is a linear mixed model with genetic random effects. The correlation matrix of the genetic random effects is determined by the pedigree and is typically very highdimensional...

  16. Theory and practice in quantitative genetics.

    Science.gov (United States)

    Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C; van Baal, G Caroline M; von Hjelmborg, Jacob B; Iachine, Ivan; Boomsma, Dorret I

    2003-10-01

    With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each, we show how the theoretical biometrical model can be translated into algebraic equations that may be used to generate scripts for statistical genetic software packages, such as Mx, Lisrel, SOLAR, or MERLIN. For using the former program a web-library (available from http://www.psy.vu.nl/mxbib) has been developed of freely available scripts that can be used to conduct all genetic analyses described in this paper.

  17. Quantitative genetic studies of antisocial behaviour

    OpenAIRE

    Viding, Essi; Larsson, Henrik; Jones, Alice P.

    2008-01-01

    This paper will broadly review the currently available twin and adoption data on antisocial behaviour (AB). It is argued that quantitative genetic research can make a significant contribution to further the understanding of how AB develops. Genetically informative study designs are particularly useful for investigating several important questions such as whether: the heritability estimates vary as a function of assessment method or gender; the relative importance of genetic and environmental ...

  18. Evolutionary quantitative genetics of nonlinear developmental systems.

    Science.gov (United States)

    Morrissey, Michael B

    2015-08-01

    In quantitative genetics, the effects of developmental relationships among traits on microevolution are generally represented by the contribution of pleiotropy to additive genetic covariances. Pleiotropic additive genetic covariances arise only from the average effects of alleles on multiple traits, and therefore the evolutionary importance of nonlinearities in development is generally neglected in quantitative genetic views on evolution. However, nonlinearities in relationships among traits at the level of whole organisms are undeniably important to biology in general, and therefore critical to understanding evolution. I outline a system for characterizing key quantitative parameters in nonlinear developmental systems, which yields expressions for quantities such as trait means and phenotypic and genetic covariance matrices. I then develop a system for quantitative prediction of evolution in nonlinear developmental systems. I apply the system to generating a new hypothesis for why direct stabilizing selection is rarely observed. Other uses will include separation of purely correlative from direct and indirect causal effects in studying mechanisms of selection, generation of predictions of medium-term evolutionary trajectories rather than immediate predictions of evolutionary change over single generation time-steps, and the development of efficient and biologically motivated models for separating additive from epistatic genetic variances and covariances.

  19. Whole genome approaches to quantitative genetics.

    Science.gov (United States)

    Visscher, Peter M

    2009-06-01

    Apart from parent-offspring pairs and clones, relative pairs vary in the proportion of the genome that they share identical by descent. In the past, quantitative geneticists have used the expected value of sharing genes by descent to estimate genetic parameters and predict breeding values. With the possibility to genotype individuals for many markers across the genome it is now possible to empirically estimate the actual relationship between relatives. We review some of the theory underlying the variation in genetic identity, show applications to estimating genetic variance for height in humans and discuss other applications.

  20. Next generation quantitative genetics in plants.

    Science.gov (United States)

    Jiménez-Gómez, José M

    2011-01-01

    Most characteristics in living organisms show continuous variation, which suggests that they are controlled by multiple genes. Quantitative trait loci (QTL) analysis can identify the genes underlying continuous traits by establishing associations between genetic markers and observed phenotypic variation in a segregating population. The new high-throughput sequencing (HTS) technologies greatly facilitate QTL analysis by providing genetic markers at genome-wide resolution in any species without previous knowledge of its genome. In addition HTS serves to quantify molecular phenotypes, which aids to identify the loci responsible for QTLs and to understand the mechanisms underlying diversity. The constant improvements in price, experimental protocols, computational pipelines, and statistical frameworks are making feasible the use of HTS for any research group interested in quantitative genetics. In this review I discuss the application of HTS for molecular marker discovery, population genotyping, and expression profiling in QTL analysis.

  1. Genetic variability, heritability and genetic advance of quantitative ...

    African Journals Online (AJOL)

    ONOS

    2010-05-10

    May 10, 2010 ... clusters/plant, number of pods/plant, number of seeds/pod, yield/plant and 100 seed weight of black gram in M2 ... Key words: Genetic variability, gamma rays, quantitative traits, black gram. ... MATERIALS AND METHODS.

  2. The quantitative genetics of phenotypic robustness.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    Full Text Available Phenotypic robustness, or canalization, has been extensively investigated both experimentally and theoretically. However, it remains unknown to what extent robustness varies between individuals, and whether factors buffering environmental variation also buffer genetic variation. Here we introduce a quantitative genetic approach to these issues, and apply this approach to data from three species. In mice, we find suggestive evidence that for hundreds of gene expression traits, robustness is polymorphic and can be genetically mapped to discrete genomic loci. Moreover, we find that the polymorphisms buffering genetic variation are distinct from those buffering environmental variation. In fact, these two classes have quite distinct mechanistic bases: environmental buffers of gene expression are predominantly sex-specific and trans-acting, whereas genetic buffers are not sex-specific and often cis-acting. Data from studies of morphological and life-history traits in plants and yeast support the distinction between polymorphisms buffering genetic and environmental variation, and further suggest that loci buffering different types of environmental variation do overlap with one another. These preliminary results suggest that naturally occurring polymorphisms affecting phenotypic robustness could be abundant, and that these polymorphisms may generally buffer either genetic or environmental variation, but not both.

  3. The nature of quantitative genetic variation for Drosophila longevity.

    Science.gov (United States)

    Mackay, Trudy F C

    2002-01-01

    Longevity is a typical quantitative trait: the continuous variation in life span observed in natural populations is attributable to genetic variation at multiple quantitative trait loci (QTL), environmental sensitivity of QTL alleles, and truly continuous environmental variation. To begin to understand the genetic architecture of longevity at the level of individual QTL, we have mapped QTL for Drosophila life span that segregate between two inbred strains that were not selected for longevity. A mapping population of 98 recombinant inbred lines (RIL) was derived from these strains, and life span of virgin male and female flies measured under control culture conditions, chronic heat and cold stress, heat shock and starvation stress, and high and low density larval environments. The genotypes of the RIL were determined for polymorphic roo transposable element insertion sites, and life span QTL were mapped using composite interval mapping methods. A minimum of 19 life span QTL were detected by recombination mapping. The life span QTL exhibited strong genotype by sex, genotype by environment, and genotype by genotype (epistatic) interactions. These interactions complicate mapping efforts, but evolutionary theory predicts such properties of segregating QTL alleles. Quantitative deficiency mapping of four longevity QTL detected in the control environment by recombination mapping revealed a minimum of 11 QTL in these regions. Clearly, longevity is a complex quantitative trait. In the future, linkage disequilibrium mapping can be used to determine which candidate genes in a QTL region correspond to the genetic loci affecting variation in life span, and define the QTL alleles at the molecular level.

  4. Quantitative genetic analysis of injury liability in infants and toddlers

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, K.; Matheny, A.P. Jr. [Univ. of Louisville Medical School, KY (United States)

    1995-02-27

    A threshold model of latent liability was applied to infant and toddler twin data on total count of injuries sustained during the interval from birth to 36 months of age. A quantitative genetic analysis of estimated twin correlations in injury liability indicated strong genetic dominance effects, but no additive genetic variance was detected. Because interpretations involving overdominance have little research support, the results may be due to low order epistasis or other interaction effects. Boys had more injuries than girls, but this effect was found only for groups whose parents were prompted and questioned in detail about their children`s injuries. Activity and impulsivity are two behavioral predictors of childhood injury, and the results are discussed in relation to animal research on infant and adult activity levels, and impulsivity in adult humans. Genetic epidemiological approaches to childhood injury should aid in targeting higher risk children for preventive intervention. 30 refs., 4 figs., 3 tabs.

  5. Integration of molecular genetic technology with quantitative genetic technology for maximizing the speed of genetic improvement

    Institute of Scientific and Technical Information of China (English)

    Jack; C.M.; DEKKERS

    2005-01-01

    To date,most genetic progress for quantita-tive traits in livestock has been made by selec-tion on phenotype or on estimates of breedingvalues(BBV)derived from phenotype,withoutknowledge of the number of genes that affect thetrait or the effects of each gene.In this quantita-tive genetic approach to genetic improvement,the genetic architecture of traits of interest hasessentially been treated as a‘black box’.De-spite this,the substantial rates of genetic im-provement that have been and continue to be a-chie...

  6. From classical genetics to quantitative genetics to systems biology: modeling epistasis.

    Directory of Open Access Journals (Sweden)

    David L Aylor

    2008-03-01

    Full Text Available Gene expression data has been used in lieu of phenotype in both classical and quantitative genetic settings. These two disciplines have separate approaches to measuring and interpreting epistasis, which is the interaction between alleles at different loci. We propose a framework for estimating and interpreting epistasis from a classical experiment that combines the strengths of each approach. A regression analysis step accommodates the quantitative nature of expression measurements by estimating the effect of gene deletions plus any interaction. Effects are selected by significance such that a reduced model describes each expression trait. We show how the resulting models correspond to specific hierarchical relationships between two regulator genes and a target gene. These relationships are the basic units of genetic pathways and genomic system diagrams. Our approach can be extended to analyze data from a variety of experiments, multiple loci, and multiple environments.

  7. A Quantitative Genetic Analysis of the Associations among Language Skills, Peer Interactions, and Behavioral Problems in Childhood: Results from a Sample of Twins

    Science.gov (United States)

    Beaver, Kevin M.; Boutwell, Brian B.; Barnes, J. C.; Schwartz, Joseph A.; Connolly, Eric J.

    2014-01-01

    A body of empirical research has revealed that there are associations among language skills, peer interactions, and behavioral problems in childhood. At the same time, however, there has been comparatively less research devoted to exploring the mutual unfolding of these factors over the first few years of life. The current study is designed to…

  8. A Quantitative Genetic Analysis of the Associations among Language Skills, Peer Interactions, and Behavioral Problems in Childhood: Results from a Sample of Twins

    Science.gov (United States)

    Beaver, Kevin M.; Boutwell, Brian B.; Barnes, J. C.; Schwartz, Joseph A.; Connolly, Eric J.

    2014-01-01

    A body of empirical research has revealed that there are associations among language skills, peer interactions, and behavioral problems in childhood. At the same time, however, there has been comparatively less research devoted to exploring the mutual unfolding of these factors over the first few years of life. The current study is designed to…

  9. Developments in statistical analysis in quantitative genetics

    DEFF Research Database (Denmark)

    Sorensen, Daniel

    2009-01-01

    A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap and ...

  10. Event History Analysis in Quantitative Genetics

    DEFF Research Database (Denmark)

    Maia, Rafael Pimentel

    Event history analysis is a clas of statistical methods specially designed to analyze time-to-event characteristics, e.g. the time until death. The aim of the thesis was to present adequate multivariate versions of mixed survival models that properly represent the genetic aspects related to a given...... time-to-event characteristic of interest. Real genetic longevity studies based on female animals of different species (sows, dairy cows, and sheep) exemplifies the use of the methods. Moreover these studies allow to understand som genetic mechanisms related to the lenght of the productive life...

  11. The quantitative genetics of disgust sensitivity.

    Science.gov (United States)

    Sherlock, James M; Zietsch, Brendan P; Tybur, Joshua M; Jern, Patrick

    2016-02-01

    [Correction Notice: An Erratum for this article was reported in Vol 16(1) of Emotion (see record 2015-57029-001). In the article, the name of author Joshua M. Tybur was misspelled as Joshua M. Tyber. All versions of this article have been corrected.] Response sensitivity to common disgust elicitors varies considerably among individuals. The sources of these individual differences are largely unknown. In the current study, we use a large sample of female identical and nonidentical twins (N = 1,041 individuals) and their siblings (N = 170) to estimate the proportion of variation due to genetic effects, the shared environment, and other (residual) sources across multiple domains of disgust sensitivity. We also investigate the genetic and environmental influences on the covariation between the different disgust domains. Twin modeling revealed that approximately half of the variation in pathogen, sexual, and moral disgust is due to genetic effects. An independent pathways twin model also revealed that sexual and pathogen disgust sensitivity were influenced by unique sources of genetic variation, while also being significantly affected by a general genetic factor underlying all 3 disgust domains. Moral disgust sensitivity, in contrast, did not exhibit domain-specific genetic variation. These findings are discussed in light of contemporary evolutionary approaches to disgust sensitivity.

  12. Parent-offspring conflict and co-adaptation: behavioural ecology meets quantitative genetics.

    Science.gov (United States)

    Smiseth, Per T; Wright, Jonathan; Kölliker, Mathias

    2008-08-22

    The evolution of the complex and dynamic behavioural interactions between caring parents and their dependent offspring is a major area of research in behavioural ecology and quantitative genetics. While behavioural ecologists examine the evolution of interactions between parents and offspring in the light of parent-offspring conflict and its resolution, quantitative geneticists explore the evolution of such interactions in the light of parent-offspring co-adaptation due to combined effects of parental and offspring behaviours on fitness. To date, there is little interaction or integration between these two fields. Here, we first review the merits and limitations of each of these two approaches and show that they provide important complementary insights into the evolution of strategies for offspring begging and parental resource provisioning. We then outline how central ideas from behavioural ecology and quantitative genetics can be combined within a framework based on the concept of behavioural reaction norms, which provides a common basis for behavioural ecologists and quantitative geneticists to study the evolution of parent-offspring interactions. Finally, we discuss how the behavioural reaction norm approach can be used to advance our understanding of parent-offspring conflict by combining information about the genetic basis of traits from quantitative genetics with key insights regarding the adaptive function and dynamic nature of parental and offspring behaviours from behavioural ecology.

  13. Global Quantitative Modeling of Chromatin Factor Interactions

    Science.gov (United States)

    Zhou, Jian; Troyanskaya, Olga G.

    2014-01-01

    Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

  14. Structural similarity of genetically interacting proteins

    Directory of Open Access Journals (Sweden)

    Nussinov Ruth

    2008-07-01

    Full Text Available Abstract Background The study of gene mutants and their interactions is fundamental to understanding gene function and backup mechanisms within the cell. The recent availability of large scale genetic interaction networks in yeast and worm allows the investigation of the biological mechanisms underlying these interactions at a global scale. To date, less than 2% of the known genetic interactions in yeast or worm can be accounted for by sequence similarity. Results Here, we perform a genome-scale structural comparison among protein pairs in the two species. We show that significant fractions of genetic interactions involve structurally similar proteins, spanning 7–10% and 14% of all known interactions in yeast and worm, respectively. We identify several structural features that are predictive of genetic interactions and show their superiority over sequence-based features. Conclusion Structural similarity is an important property that can explain and predict genetic interactions. According to the available data, the most abundant mechanism for genetic interactions among structurally similar proteins is a common interacting partner shared by two genetically interacting proteins.

  15. Data-driven encoding for quantitative genetic trait prediction.

    Science.gov (United States)

    He, Dan; Wang, Zhanyong; Parida, Laxmi

    2015-01-01

    Given a set of biallelic molecular markers, such as SNPs, with genotype values on a collection of plant, animal or human samples, the goal of quantitative genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Quantitative genetic trait prediction is usually represented as linear regression models which require quantitative encodings for the genotypes: the three distinct genotype values, corresponding to one heterozygous and two homozygous alleles, are usually coded as integers, and manipulated algebraically in the model. Further, epistasis between multiple markers is modeled as multiplication between the markers: it is unclear that the regression model continues to be effective under this. In this work we investigate the effects of encodings to the quantitative genetic trait prediction problem. We first showed that different encodings lead to different prediction accuracies, in many test cases. We then proposed a data-driven encoding strategy, where we encode the genotypes according to their distribution in the phenotypes and we allow each marker to have different encodings. We show in our experiments that this encoding strategy is able to improve the performance of the genetic trait prediction method and it is more helpful for the oligogenic traits, whose values rely on a relatively small set of markers. To the best of our knowledge, this is the first paper that discusses the effects of encodings to the genetic trait prediction problem.

  16. The balance of weak and strong interactions in genetic networks.

    Directory of Open Access Journals (Sweden)

    Juan F Poyatos

    Full Text Available Genetic interactions are being quantitatively characterized in a comprehensive way in several model organisms. These data are then globally represented in terms of genetic networks. How are interaction strengths distributed in these networks? And what type of functional organization of the underlying genomic systems is revealed by such distribution patterns? Here, I found that weak interactions are important for the structure of genetic buffering between signaling pathways in Caenorhabditis elegans, and that the strength of the association between two genes correlates with the number of common interactors they exhibit. I also determined that this network includes genetic cascades balancing weak and strong links, and that its hubs act as particularly strong genetic modifiers; both patterns also identified in Saccharomyces cerevisae networks. In yeast, I further showed a relation, although weak, between interaction strengths and some phenotypic/evolutionary features of the corresponding target genes. Overall, this work demonstrates a non-random organization of interaction strengths in genetic networks, a feature common to other complex networks, and that could reflect in this context how genetic variation is eventually influencing the phenotype.

  17. Automatic quantitative morphological analysis of interacting galaxies

    CERN Document Server

    Shamir, Lior; Wallin, John

    2013-01-01

    The large number of galaxies imaged by digital sky surveys reinforces the need for computational methods for analyzing galaxy morphology. While the morphology of most galaxies can be associated with a stage on the Hubble sequence, morphology of galaxy mergers is far more complex due to the combination of two or more galaxies with different morphologies and the interaction between them. Here we propose a computational method based on unsupervised machine learning that can quantitatively analyze morphologies of galaxy mergers and associate galaxies by their morphology. The method works by first generating multiple synthetic galaxy models for each galaxy merger, and then extracting a large set of numerical image content descriptors for each galaxy model. These numbers are weighted using Fisher discriminant scores, and then the similarities between the galaxy mergers are deduced using a variation of Weighted Nearest Neighbor analysis such that the Fisher scores are used as weights. The similarities between the ga...

  18. Multilevel selection 1: Quantitative genetics of inheritance and response to selection

    NARCIS (Netherlands)

    Bijma, P.; Muir, W.M.; Arendonk, van J.A.M.

    2007-01-01

    Interaction among individuals is universal, both in animals and in plants, and substantially affects evolution of natural populations and responses to artificial selection in agriculture. Although quantitative genetics has successfully been applied to many traits, it does not provide a general theor

  19. Genetic architecture of quantitative traits and complex diseases.

    Science.gov (United States)

    Fu, Wenqing; O'Connor, Timothy D; Akey, Joshua M

    2013-12-01

    More than 150 years after Mendel discovered the laws of heredity, the genetic architecture of phenotypic variation remains elusive. Here, we discuss recent progress in deciphering how genotypes map onto phenotypes, sources of genetic complexity, and how model organisms are illuminating general principles about the relationship between genetic and phenotypic variation. Moreover, we highlight insights gleaned from large-scale sequencing studies in humans, and how this knowledge informs outstanding questions about the genetic architecture of quantitative traits and complex diseases. Finally, we articulate how the confluence of technologies enabling whole-genome sequencing, comprehensive phenotyping, and high-throughput functional assays of polymorphisms will facilitate a more principled and mechanistic understanding of the genetic architecture of phenotypic variation.

  20. [Interactions between genetics and environment].

    Science.gov (United States)

    Vineis, P

    1998-01-01

    From a scientific point of view, the idea that genes exert an important role in explaining human pathology has gained much popularity in recent decades. However, according to Stephen Jay Gould, the "genetic fallacy" has been repeatedly used to avoid environmental action. In the case of occupational cancer, genetic screening of workers for their susceptibility to the action of chemical carcinogens, on the basis of "metabolic polymorphisms", would be unacceptable because of racial discrimination, related to uneven racial distribution of most polymorphisms, for example, 90% of Africans and 10% of Asians have the "slow" acetylator genotype. Therefore, not only technical and scientific aspects of genetic susceptibility to cancer, but also ethical and social implication have to be considered.

  1. Genetic mapping of quantitative phenotypic traits in Saccharomyces cerevisiae.

    Science.gov (United States)

    Swinnen, Steve; Thevelein, Johan M; Nevoigt, Elke

    2012-03-01

    Saccharomyces cerevisiae has become a favorite production organism in industrial biotechnology presenting new challenges to yeast engineers in terms of introducing advantageous traits such as stress tolerances. Exploring subspecies diversity of S. cerevisiae has identified strains that bear industrially relevant phenotypic traits. Provided that the genetic basis of such phenotypic traits can be identified inverse engineering allows the targeted modification of production strains. Most phenotypic traits of interest in S. cerevisiae strains are quantitative, meaning that they are controlled by multiple genetic loci referred to as quantitative trait loci (QTL). A straightforward approach to identify the genetic basis of quantitative traits is QTL mapping which aims at the allocation of the genetic determinants to regions in the genome. The application of high-density oligonucleotide arrays and whole-genome re-sequencing to detect genetic variations between strains has facilitated the detection of large numbers of molecular markers thus allowing high-resolution QTL mapping over the entire genome. This review focuses on the basic principle and state of the art of QTL mapping in S. cerevisiae. Furthermore we discuss several approaches developed during the last decade that allow down-scaling of the regions identified by QTL mapping to the gene level. We also emphasize the particular challenges of QTL mapping in nonlaboratory strains of S. cerevisiae.

  2. Segregation Analysis on Genetic System of Quantitative Traits in Plants

    Institute of Scientific and Technical Information of China (English)

    Gai Junyi

    2006-01-01

    Based on the traditional polygene inheritance model of quantitative traits,the author suggests the major gene and polygene mixed inheritance model.The model was considered as a general one,while the pure major gene and pure polygene inheritance model was a specific case of the general model.Based on the proposed theory,the author established the segregation analysis procedure to study the genetic system of quantitative traits of plants.At present,this procedure can be used to evaluate the genetic effect of individual major genes (up to two to three major genes),the collective genetic effect of polygene,and their heritability value.This paper introduces how to establish the procedure,its main achievements,and its applications.An example is given to illustrate the steps,methods,and effectiveness of the procedure.

  3. Quantitative Genetics in the Era of Molecular Genetics: Learning Abilities and Disabilities as an Example

    Science.gov (United States)

    Haworth, Claire M. A.; Plomin, Robert

    2010-01-01

    Objective: To consider recent findings from quantitative genetic research in the context of molecular genetic research, especially genome-wide association studies. We focus on findings that go beyond merely estimating heritability. We use learning abilities and disabilities as examples. Method: Recent twin research in the area of learning…

  4. Multilevel selection 1: Quantitative genetics of inheritance and response to selection.

    Science.gov (United States)

    Bijma, Piter; Muir, William M; Van Arendonk, Johan A M

    2007-01-01

    Interaction among individuals is universal, both in animals and in plants, and substantially affects evolution of natural populations and responses to artificial selection in agriculture. Although quantitative genetics has successfully been applied to many traits, it does not provide a general theory accounting for interaction among individuals and selection acting on multiple levels. Consequently, current quantitative genetic theory fails to explain why some traits do not respond to selection among individuals, but respond greatly to selection among groups. Understanding the full impacts of heritable interactions on the outcomes of selection requires a quantitative genetic framework including all levels of selection and relatedness. Here we present such a framework and provide expressions for the response to selection. Results show that interaction among individuals may create substantial heritable variation, which is hidden to classical analyses. Selection acting on higher levels of organization captures this hidden variation and therefore always yields positive response, whereas individual selection may yield response in the opposite direction. Our work provides testable predictions of response to multilevel selection and reduces to classical theory in the absence of interaction. Statistical methodology provided elsewhere enables empirical application of our work to both natural and domestic populations.

  5. The quantitative basis of the Arabidopsis innate immune system to endemic pathogens depends on pathogen genetics

    DEFF Research Database (Denmark)

    Corwin, Jason A; Copeland, Daniel; Feusier, Julie;

    2016-01-01

    The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used...... the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B....... cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence...

  6. The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics.

    Directory of Open Access Journals (Sweden)

    Jason A Corwin

    2016-02-01

    Full Text Available The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs and nucleotide-binding site leucine-rich repeat proteins (NLRs, were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60% when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen

  7. Quantitative genetic activity graphical profiles for use in chemical evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Waters, M.D. [Environmental Protection Agency, Washington, DC (United States); Stack, H.F.; Garrett, N.E.; Jackson, M.A. [Environmental Health Research and Testing, Inc., Research Triangle Park, NC (United States)

    1990-12-31

    A graphic approach, terms a Genetic Activity Profile (GAP), was developed to display a matrix of data on the genetic and related effects of selected chemical agents. The profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each chemical. Either the lowest effective dose or highest ineffective dose is recorded for each agent and bioassay. Up to 200 different test systems are represented across the GAP. Bioassay systems are organized according to the phylogeny of the test organisms and the end points of genetic activity. The methodology for producing and evaluating genetic activity profile was developed in collaboration with the International Agency for Research on Cancer (IARC). Data on individual chemicals were compiles by IARC and by the US Environmental Protection Agency (EPA). Data are available on 343 compounds selected from volumes 1-53 of the IARC Monographs and on 115 compounds identified as Superfund Priority Substances. Software to display the GAPs on an IBM-compatible personal computer is available from the authors. Structurally similar compounds frequently display qualitatively and quantitatively similar profiles of genetic activity. Through examination of the patterns of GAPs of pairs and groups of chemicals, it is possible to make more informed decisions regarding the selection of test batteries to be used in evaluation of chemical analogs. GAPs provided useful data for development of weight-of-evidence hazard ranking schemes. Also, some knowledge of the potential genetic activity of complex environmental mixtures may be gained from an assessment of the genetic activity profiles of component chemicals. The fundamental techniques and computer programs devised for the GAP database may be used to develop similar databases in other disciplines. 36 refs., 2 figs.

  8. Genetic Architectures of Quantitative Variation in RNA Editing Pathways.

    Science.gov (United States)

    Gu, Tongjun; Gatti, Daniel M; Srivastava, Anuj; Snyder, Elizabeth M; Raghupathy, Narayanan; Simecek, Petr; Svenson, Karen L; Dotu, Ivan; Chuang, Jeffrey H; Keller, Mark P; Attie, Alan D; Braun, Robert E; Churchill, Gary A

    2016-02-01

    RNA editing refers to post-transcriptional processes that alter the base sequence of RNA. Recently, hundreds of new RNA editing targets have been reported. However, the mechanisms that determine the specificity and degree of editing are not well understood. We examined quantitative variation of site-specific editing in a genetically diverse multiparent population, Diversity Outbred mice, and mapped polymorphic loci that alter editing ratios globally for C-to-U editing and at specific sites for A-to-I editing. An allelic series in the C-to-U editing enzyme Apobec1 influences the editing efficiency of Apob and 58 additional C-to-U editing targets. We identified 49 A-to-I editing sites with polymorphisms in the edited transcript that alter editing efficiency. In contrast to the shared genetic control of C-to-U editing, most of the variable A-to-I editing sites were determined by local nucleotide polymorphisms in proximity to the editing site in the RNA secondary structure. Our results indicate that RNA editing is a quantitative trait subject to genetic variation and that evolutionary constraints have given rise to distinct genetic architectures in the two canonical types of RNA editing.

  9. Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

    Science.gov (United States)

    Albert, Réka; Collins, James J.; Glass, Leon

    2013-06-01

    All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

  10. Interactive Genetic Algorithms with Fitness Adjustment

    Institute of Scientific and Technical Information of China (English)

    GUO Guang-song; GONG Dun-wei; HAO Guo-sheng; ZHANG Yong

    2006-01-01

    Noises widely exist in interactive genetic algorithms. However, there is no effective method to solve this problem up to now. There are two kinds of noises, one is the noise existing in visual systems and the other is resulted from user's preference mechanisms. Characteristics of the two noises are presented aiming at the application of interactive genetic algorithms in dealing with images. The evolutionary phases of interactive genetic algorithms are determined according to differences in the same individual's fitness among different generations. Models for noises in different phases are established and the corresponding strategies for reducing noises are given. The algorithm proposed in this paper has been applied to fashion design, which is a typical example of image processing. The results show that the strategies can reduce noises in interactive genetic algorithms and improve the algorithm's performance effectively. However, a further study is needed to solve the problem of determining the evolution phase by using suitable objective methods so as to find out an effective method to decrease noises.

  11. A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibánez-Escriche, Noelia; Sorensen, Daniel

    2008-01-01

    In quantitative genetics, Markov chain Monte Carlo (MCMC) methods are indispensable for statistical inference in non-standard models like generalized linear models with genetic random effects or models with genetically structured variance heterogeneity. A particular challenge for MCMC applications...

  12. Quantitative timed analysis of interactive Markov chains

    NARCIS (Netherlands)

    Guck, Dennis; Han, Tingting; Katoen, Joost-Pieter; Neuhausser, M.

    2012-01-01

    This paper presents new algorithms and accompanying tool support for analyzing interactive Markov chains (IMCs), a stochastic timed 1 1/2-player game in which delays are exponentially distributed. IMCs are compositional and act as semantic model for engineering formalisms such as AADL and dynamic fa

  13. Fashion sketch design by interactive genetic algorithms

    Science.gov (United States)

    Mok, P. Y.; Wang, X. X.; Xu, J.; Kwok, Y. L.

    2012-11-01

    Computer aided design is vitally important for the modern industry, particularly for the creative industry. Fashion industry faced intensive challenges to shorten the product development process. In this paper, a methodology is proposed for sketch design based on interactive genetic algorithms. The sketch design system consists of a sketch design model, a database and a multi-stage sketch design engine. First, a sketch design model is developed based on the knowledge of fashion design to describe fashion product characteristics by using parameters. Second, a database is built based on the proposed sketch design model to define general style elements. Third, a multi-stage sketch design engine is used to construct the design. Moreover, an interactive genetic algorithm (IGA) is used to accelerate the sketch design process. The experimental results have demonstrated that the proposed method is effective in helping laypersons achieve satisfied fashion design sketches.

  14. Bayesian model choice and search strategies for mapping interacting quantitative trait Loci.

    Science.gov (United States)

    Yi, Nengjun; Xu, Shizhong; Allison, David B

    2003-01-01

    Most complex traits of animals, plants, and humans are influenced by multiple genetic and environmental factors. Interactions among multiple genes play fundamental roles in the genetic control and evolution of complex traits. Statistical modeling of interaction effects in quantitative trait loci (QTL) analysis must accommodate a very large number of potential genetic effects, which presents a major challenge to determining the genetic model with respect to the number of QTL, their positions, and their genetic effects. In this study, we use the methodology of Bayesian model and variable selection to develop strategies for identifying multiple QTL with complex epistatic patterns in experimental designs with two segregating genotypes. Specifically, we develop a reversible jump Markov chain Monte Carlo algorithm to determine the number of QTL and to select main and epistatic effects. With the proposed method, we can jointly infer the genetic model of a complex trait and the associated genetic parameters, including the number, positions, and main and epistatic effects of the identified QTL. Our method can map a large number of QTL with any combination of main and epistatic effects. Utility and flexibility of the method are demonstrated using both simulated data and a real data set. Sensitivity of posterior inference to prior specifications of the number and genetic effects of QTL is investigated. PMID:14573494

  15. Quantitative trait locus-specific genotype × alcoholism interaction on linkage for evoked electroencephalogram oscillations

    OpenAIRE

    Williams Jeff T; Avery Christy L; Martin Lisa J; North Kari E

    2005-01-01

    Abstract We explored the evidence for a quantitative trait locus (QTL)-specific genotype × alcoholism interaction for an evoked electroencephalogram theta band oscillation (ERP) phenotype on a region of chromosome 7 in participants of the US Collaborative Study on the Genetics of Alcoholism. Among 901 participants with both genotype and phenotype data available, we performed variance component linkage analysis (SOLAR version 2.1.2) in the full sample and stratified by DSM-III-R and Feighner-d...

  16. A strategy for extracting and analyzing large-scale quantitative epistatic interaction data

    Science.gov (United States)

    Collins, Sean R; Schuldiner, Maya; Krogan, Nevan J; Weissman, Jonathan S

    2006-01-01

    Recently, approaches have been developed for high-throughput identification of synthetic sick/lethal gene pairs. However, these are only a specific example of the broader phenomenon of epistasis, wherein the presence of one mutation modulates the phenotype of another. We present analysis techniques for generating high-confidence quantitative epistasis scores from measurements made using synthetic genetic array and epistatic miniarray profile (E-MAP) technology, as well as several tools for higher-level analysis of the resulting data that are greatly enhanced by the quantitative score and detection of alleviating interactions. PMID:16859555

  17. Quantitative analysis of intermolecular interactions in orthorhombic rubrene

    Directory of Open Access Journals (Sweden)

    Venkatesha R. Hathwar

    2015-09-01

    Full Text Available Rubrene is one of the most studied organic semiconductors to date due to its high charge carrier mobility which makes it a potentially applicable compound in modern electronic devices. Previous electronic device characterizations and first principles theoretical calculations assigned the semiconducting properties of rubrene to the presence of a large overlap of the extended π-conjugated core between molecules. We present here the electron density distribution in rubrene at 20 K and at 100 K obtained using a combination of high-resolution X-ray and neutron diffraction data. The topology of the electron density and energies of intermolecular interactions are studied quantitatively. Specifically, the presence of Cπ...Cπ interactions between neighbouring tetracene backbones of the rubrene molecules is experimentally confirmed from a topological analysis of the electron density, Non-Covalent Interaction (NCI analysis and the calculated interaction energy of molecular dimers. A significant contribution to the lattice energy of the crystal is provided by H—H interactions. The electron density features of H—H bonding, and the interaction energy of molecular dimers connected by H—H interaction clearly demonstrate an importance of these weak interactions in the stabilization of the crystal structure. The quantitative nature of the intermolecular interactions is virtually unchanged between 20 K and 100 K suggesting that any changes in carrier transport at these low temperatures would have a different origin. The obtained experimental results are further supported by theoretical calculations.

  18. Skype Synchronous Interaction Effectiveness in a Quantitative Management Science Course

    Science.gov (United States)

    Strang, Kenneth David

    2012-01-01

    An experiment compared asynchronous versus synchronous instruction in an online quantitative course. Mann-Whitney U-tests, correlation, analysis of variance, t tests, and multivariate analysis of covariance (MANCOVA) were utilized to test the hypothesis that more high-quality online experiential learning interactions would increase grade.…

  19. Mapping Protein-Protein Interactions by Quantitative Proteomics

    DEFF Research Database (Denmark)

    Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

    2010-01-01

    spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used...

  20. A census of cells in time: quantitative genetics meets developmental biology.

    Science.gov (United States)

    Chitwood, Daniel H; Sinha, Neelima R

    2013-02-01

    Quantitative genetics has become a popular method for determining the genetic basis of natural variation. Combined with genomic methods, it provides a tool for discerning the genetic basis of gene expression. So-called genetical genomics approaches yield a wealth of genomic information, but by necessity, because of cost and time, fail to resolve the differences between organs, tissues, and/or cell types. Similarly, quantitative approaches in development that might potentially address these issues are seldom applied to quantitative genetics. We discuss recent advances in cell type-specific isolation methods, the quantitative analysis of phenotype, and developmental modeling that are compatible with quantitative genetics and, with time, promise to bridge the gap between these two powerful disciplines yielding unprecedented biological insight.

  1. Tests for genetic interactions in type 1 diabetes

    DEFF Research Database (Denmark)

    Morahan, Grant; Mehta, Munish; James, Ian

    2011-01-01

    Interactions between genetic and environmental factors lead to immune dysregulation causing type 1 diabetes and other autoimmune disorders. Recently, many common genetic variants have been associated with type 1 diabetes risk, but each has modest individual effects. Familial clustering of type 1...... diabetes has not been explained fully and could arise from many factors, including undetected genetic variation and gene interactions....

  2. Multiple genetic interaction experiments provide complementary information useful for gene function prediction.

    Directory of Open Access Journals (Sweden)

    Magali Michaut

    Full Text Available Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens.

  3. A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibánez-Escriche, Noelia; Sorensen, Daniel

    2008-01-01

    In quantitative genetics, Markov chain Monte Carlo (MCMC) methods are indispensable for statistical inference in non-standard models like generalized linear models with genetic random effects or models with genetically structured variance heterogeneity. A particular challenge for MCMC applications...... in quantitative genetics is to obtain efficient updates of the high-dimensional vectors of genetic random effects and the associated covariance parameters. We discuss various strategies to approach this problem including reparameterization, Langevin-Hastings updates, and updates based on normal approximations....... The methods are compared in applications to Bayesian inference for three data sets using a model with genetically structured variance heterogeneity...

  4. Predictability of Genetic Interactions from Functional Gene Modules

    Directory of Open Access Journals (Sweden)

    Jonathan H. Young

    2017-02-01

    Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

  5. Entering the second century of maize quantitative genetics

    Science.gov (United States)

    Maize is the most widely grown cereal in the world. In addition to its role in global agriculture, it has also long served as a model organism for genetic research. Maize stands at a genetic crossroads, as it has access to all the tools available for plant genetics but exhibits a genetic architectur...

  6. Quantitative sociodynamics stochastic methods and models of social interaction processes

    CERN Document Server

    Helbing, Dirk

    1995-01-01

    Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioural changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics but they have very often proved their explanatory power in chemistry, biology, economics and the social sciences. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces the most important concepts from nonlinear dynamics (synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches a very fundamental dynamic model is obtained which seems to open new perspectives in the social sciences. It includes many established models as special cases, e.g. the log...

  7. Quantitative Sociodynamics Stochastic Methods and Models of Social Interaction Processes

    CERN Document Server

    Helbing, Dirk

    2010-01-01

    This new edition of Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioral changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics and mathematics, but they have very often proven their explanatory power in chemistry, biology, economics and the social sciences as well. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces important concepts from nonlinear dynamics (e.g. synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches, a fundamental dynamic model is obtained, which opens new perspectives in the social sciences. It includes many established models a...

  8. Genetic interaction mapping with microfluidic-based single cell sequencing

    Science.gov (United States)

    Haliburton, John R.; Shao, Wenjun; Deutschbauer, Adam; Arkin, Adam; Abate, Adam R.

    2017-01-01

    Genetic interaction mapping is useful for understanding the molecular basis of cellular decision making, but elucidating interactions genome-wide is challenging due to the massive number of gene combinations that must be tested. Here, we demonstrate a simple approach to thoroughly map genetic interactions in bacteria using microfluidic-based single cell sequencing. Using single cell PCR in droplets, we link distinct genetic information into single DNA sequences that can be decoded by next generation sequencing. Our approach is scalable and theoretically enables the pooling of entire interaction libraries to interrogate multiple pairwise genetic interactions in a single culture. The speed, ease, and low-cost of our approach makes genetic interaction mapping viable for routine characterization, allowing the interaction network to be used as a universal read out for a variety of biology experiments, and for the elucidation of interaction networks in non-model organisms. PMID:28170417

  9. Advancing genetic theory and application by metabolic quantitative trait loci analysis.

    Science.gov (United States)

    Kliebenstein, Danielj

    2009-06-01

    This review describes recent advances in the analysis of metabolism using quantitative genetics. It focuses on how recent metabolic quantitative trait loci (QTL) studies enhance our understanding of the genetic architecture underlying naturally variable phenotypes and the impact of this fundamental research on agriculture, specifically crop breeding. In particular, the role of whole-genome duplications in generating quantitative genetic variation within a species is highlighted and the potential uses of this phenomenon presented. Additionally, the review describes how new observations from metabolic QTL mapping analyses are helping to shape and expand the concepts of genetic epistasis.

  10. The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis

    Science.gov (United States)

    Huang, Wen; Mackay, Trudy F. C.

    2016-01-01

    Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs). Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (VA), providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits. PMID:27812106

  11. The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis.

    Directory of Open Access Journals (Sweden)

    Wen Huang

    2016-11-01

    Full Text Available Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs. Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (VA, providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits.

  12. Multiple mating but not recombination causes quantitative increase in offspring genetic diversity for varying genetic architectures.

    Directory of Open Access Journals (Sweden)

    Olav Rueppell

    Full Text Available Explaining the evolution of sex and recombination is particularly intriguing for some species of eusocial insects because they display exceptionally high mating frequencies and genomic recombination rates. Explanations for both phenomena are based on the notion that both increase colony genetic diversity, with demonstrated benefits for colony disease resistance and division of labor. However, the relative contributions of mating number and recombination rate to colony genetic diversity have never been simultaneously assessed. Our study simulates colonies, assuming different mating numbers, recombination rates, and genetic architectures, to assess their worker genotypic diversity. The number of loci has a strong negative effect on genotypic diversity when the allelic effects are inversely scaled to locus number. In contrast, dominance, epistasis, lethal effects, or limiting the allelic diversity at each locus does not significantly affect the model outcomes. Mating number increases colony genotypic variance and lowers variation among colonies with quickly diminishing returns. Genomic recombination rate does not affect intra- and inter-colonial genotypic variance, regardless of mating frequency and genetic architecture. Recombination slightly increases the genotypic range of colonies and more strongly the number of workers with unique allele combinations across all loci. Overall, our study contradicts the argument that the exceptionally high recombination rates cause a quantitative increase in offspring genotypic diversity across one generation. Alternative explanations for the evolution of high recombination rates in social insects are therefore needed. Short-term benefits are central to most explanations of the evolution of multiple mating and high recombination rates in social insects but our results also apply to other species.

  13. Quantitative studies of antimicrobial peptide-lipid membrane interactions

    DEFF Research Database (Denmark)

    Kristensen, Kasper

    into such novel therapeutics. However, limited understanding of the mechanisms underlying microbicidal activity of antimicrobial peptides has slowed down this development. A central step toward understanding the microbicidal mechanisms of action of antimicrobial peptides is to understand the mechanisms by which......The increasing occurrence of multi-drug-resistant bacteria poses a serious threat to modern society. Therefore, novel types of anti-infective therapeutics are highly warranted. Antimicrobial peptides are a class of naturally occurring host-defense molecules that potentially might be developed...... antimicrobial peptides interact with phospholipid membranes. Motivated by that fact, the scope of this thesis is to study these antimicrobial peptide-lipid membrane interactions. In particular, we attempt to study these interactions with a quantitative approach. For that purpose, we consider the three...

  14. Genome-Wide Prediction of C. elegans Genetic Interactions

    OpenAIRE

    Zhong, Weiwei; Sternberg, Paul W.

    2006-01-01

    To obtain a global view of functional interactions among genes in a metazoan genome, we computationally integrated interactome data, gene expression data, phenotype data, and functional annotation data from three model organisms—Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster—and predicted genome-wide genetic interactions in C. elegans. The resulting genetic interaction network (consisting of 18,183 interactions) provides a framework for system-level understandin...

  15. Functional genomics bridges the gap between quantitative genetics and molecular biology.

    Science.gov (United States)

    Lappalainen, Tuuli

    2015-10-01

    Deep characterization of molecular function of genetic variants in the human genome is becoming increasingly important for understanding genetic associations to disease and for learning to read the regulatory code of the genome. In this paper, I discuss how recent advances in both quantitative genetics and molecular biology have contributed to understanding functional effects of genetic variants, lessons learned from eQTL studies, and future challenges in this field.

  16. Quantitative Genetics and Functional-Structural Plant Growth Models: Simulation of Quantitative Trait Loci Detection for Model Parameters and Application to Potential Yield Optimization

    CERN Document Server

    Letort, Veronique; Cournède, Paul-Henry; De Reffye, Philippe; Courtois, Brigitte; 10.1093/aob/mcm197

    2010-01-01

    Background and Aims: Prediction of phenotypic traits from new genotypes under untested environmental conditions is crucial to build simulations of breeding strategies to improve target traits. Although the plant response to environmental stresses is characterized by both architectural and functional plasticity, recent attempts to integrate biological knowledge into genetics models have mainly concerned specific physiological processes or crop models without architecture, and thus may prove limited when studying genotype x environment interactions. Consequently, this paper presents a simulation study introducing genetics into a functional-structural growth model, which gives access to more fundamental traits for quantitative trait loci (QTL) detection and thus to promising tools for yield optimization. Methods: The GreenLab model was selected as a reasonable choice to link growth model parameters to QTL. Virtual genes and virtual chromosomes were defined to build a simple genetic model that drove the settings ...

  17. [The study of tomato fruit weight quantitative trait locus and its application in genetics teaching].

    Science.gov (United States)

    Wang, Haiyan

    2015-08-01

    The classical research cases, which have greatly promoted the development of genetics in history, can be combined with the content of courses in genetics teaching to train students' ability of scientific thinking and genetic analysis. The localization and clone of gene controlling tomato fruit weight is a pioneer work in quantitative trait locus (QTL) studies and represents a complete process of QTL research in plants. Application of this integrated case in genetics teaching, which showed a wonderful process of scientific discovery and the fascination of genetic research, has inspired students' interest in genetics and achieved a good teaching effect.

  18. A quantitative genetic analysis of intermediate asthma phenotypes

    DEFF Research Database (Denmark)

    Thomsen, S.F.; Ferreira, M.A.R.; Kyvik, K.O.

    2009-01-01

    to the observed data using maximum likelihood methods. RESULTS: Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most...

  19. Quantitative Assessment of Eye Phenotypes for Functional Genetic Studies Using Drosophila melanogaster

    Science.gov (United States)

    Iyer, Janani; Wang, Qingyu; Le, Thanh; Pizzo, Lucilla; Grönke, Sebastian; Ambegaokar, Surendra S.; Imai, Yuzuru; Srivastava, Ashutosh; Troisí, Beatriz Llamusí; Mardon, Graeme; Artero, Ruben; Jackson, George R.; Isaacs, Adrian M.; Partridge, Linda; Lu, Bingwei; Kumar, Justin P.; Girirajan, Santhosh

    2016-01-01

    About two-thirds of the vital genes in the Drosophila genome are involved in eye development, making the fly eye an excellent genetic system to study cellular function and development, neurodevelopment/degeneration, and complex diseases such as cancer and diabetes. We developed a novel computational method, implemented as Flynotyper software (http://flynotyper.sourceforge.net), to quantitatively assess the morphological defects in the Drosophila eye resulting from genetic alterations affecting basic cellular and developmental processes. Flynotyper utilizes a series of image processing operations to automatically detect the fly eye and the individual ommatidium, and calculates a phenotypic score as a measure of the disorderliness of ommatidial arrangement in the fly eye. As a proof of principle, we tested our method by analyzing the defects due to eye-specific knockdown of Drosophila orthologs of 12 neurodevelopmental genes to accurately document differential sensitivities of these genes to dosage alteration. We also evaluated eye images from six independent studies assessing the effect of overexpression of repeats, candidates from peptide library screens, and modifiers of neurotoxicity and developmental processes on eye morphology, and show strong concordance with the original assessment. We further demonstrate the utility of this method by analyzing 16 modifiers of sine oculis obtained from two genome-wide deficiency screens of Drosophila and accurately quantifying the effect of its enhancers and suppressors during eye development. Our method will complement existing assays for eye phenotypes, and increase the accuracy of studies that use fly eyes for functional evaluation of genes and genetic interactions. PMID:26994292

  20. Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype.

    Directory of Open Access Journals (Sweden)

    Claudia Kappen

    Full Text Available The process of patterning along the anterior-posterior axis in vertebrates is highly conserved. The function of Hox genes in the axis patterning process is particularly well documented for bone development in the vertebral column and the limbs. We here show that Hoxb6, in skeletal elements at the cervico-thoracic junction, controls multiple independent aspects of skeletal pattern, implicating discrete developmental pathways as substrates for this transcription factor. In addition, we demonstrate that Hoxb6 function is subject to modulation by genetic factors. These results establish Hox-controlled skeletal pattern as a quantitative trait modulated by gene-gene interactions, and provide evidence that distinct modifiers influence the function of conserved developmental genes in fundamental patterning processes.

  1. A century after Fisher: time for a new paradigm in quantitative genetics.

    Science.gov (United States)

    Nelson, Ronald M; Pettersson, Mats E; Carlborg, Örjan

    2013-12-01

    Quantitative genetics traces its roots back through more than a century of theory, largely formed in the absence of directly observable genotype data, and has remained essentially unchanged for decades. By contrast, molecular genetics arose from direct observations and is currently undergoing rapid changes, making the amount of available data ever greater. Thus, the two disciplines are disparate both in their origins and their current states, yet they address the same fundamental question: how does the genotype affect the phenotype? The rapidly accumulating genomic data necessitate sophisticated analysis, but many of the current tools are adaptations of methods designed during the early days of quantitative genetics. We argue here that the present analysis paradigm in quantitative genetics is at its limits in regards to unraveling complex traits and it is necessary to re-evaluate the direction that genetic research is taking for the field to realize its full potential.

  2. Genetic mapping of quantitative trait loci in plants - a novel statistical approach.

    NARCIS (Netherlands)

    Jansen, R.C.

    1995-01-01

    Quantitative variation is a feature of many important traits such as yield, quality and disease resistance in crop plants and farm animals, and diseases in humans. The genetic mapping, understanding and manipulation of quantitative trait loci (QTLs) are therefore of prime importance. Only by using g

  3. A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.

    Science.gov (United States)

    Tucker, George; Loh, Po-Ru; Berger, Bonnie

    2013-10-04

    Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely

  4. Integrating Quantitative Genetics and Practical Aspects in a Fish Breeding Network in Denmark

    DEFF Research Database (Denmark)

    Meier, Kristian; Sørensen, Anders Christian; Norberg, Elise;

    simulations are given to show how different practical aspects of a breeding plan can be optimized. By combining quantitative genetic theory with current breeding practice we are able to optimize different breeding plans increasing genetic gain while controlling the level of inbreeding and building up...

  5. Genome-wide prediction of C. elegans genetic interactions.

    Science.gov (United States)

    Zhong, Weiwei; Sternberg, Paul W

    2006-03-10

    To obtain a global view of functional interactions among genes in a metazoan genome, we computationally integrated interactome data, gene expression data, phenotype data, and functional annotation data from three model organisms-Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster-and predicted genome-wide genetic interactions in C. elegans. The resulting genetic interaction network (consisting of 18,183 interactions) provides a framework for system-level understanding of gene functions. We experimentally tested the predicted interactions for two human disease-related genes and identified 14 new modifiers.

  6. Contribution and perspectives of quantitative genetics to plant breeding in Brazil

    Directory of Open Access Journals (Sweden)

    Fernando Henrique Ribeiro Barrozo Toledo

    2012-12-01

    Full Text Available The purpose of this article is to show how quantitative genetics has contributed to the huge genetic progress obtained inplant breeding in Brazil in the last forty years. The information obtained through quantitative genetics has given Brazilian breedersthe possibility of responding to innumerable questions in their work in a much more informative way, such as the use or not of hybridcultivars, which segregating population to use, which breeding method to employ, alternatives for improving the efficiency of selectionprograms, and how to handle the data of progeny and/or cultivars evaluations to identify the most stable ones and thus improverecommendations.

  7. Genetic mapping of quantitative trait loci (QTLs) with effects on ...

    African Journals Online (AJOL)

    SERVER

    2008-02-05

    Feb 5, 2008 ... 2Department of Crop Protection and Environmental Biology, ... identify genetic loci associated with the expression of resistance to FTh. ... indicated that resistance to FTh may be controlled by ... population or to pyramid resistance into new populations. .... environment and human health (Eigenbrode and.

  8. Genetic toxicology at the crossroads-from qualitative hazard evaluation to quantitative risk assessment.

    Science.gov (United States)

    White, Paul A; Johnson, George E

    2016-05-01

    Applied genetic toxicology is undergoing a transition from qualitative hazard identification to quantitative dose-response analysis and risk assessment. To facilitate this change, the Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC) sponsored a workshop held in Lancaster, UK on July 10-11, 2014. The event included invited speakers from several institutions and the contents was divided into three themes-1: Point-of-departure Metrics for Quantitative Dose-Response Analysis in Genetic Toxicology; 2: Measurement and Estimation of Exposures for Better Extrapolation to Humans and 3: The Use of Quantitative Approaches in Genetic Toxicology for human health risk assessment (HHRA). A host of pertinent issues were discussed relating to the use of in vitro and in vivo dose-response data, the development of methods for in vitro to in vivo extrapolation and approaches to use in vivo dose-response data to determine human exposure limits for regulatory evaluations and decision-making. This Special Issue, which was inspired by the workshop, contains a series of papers that collectively address topics related to the aforementioned themes. The Issue includes contributions that collectively evaluate, describe and discuss in silico, in vitro, in vivo and statistical approaches that are facilitating the shift from qualitative hazard evaluation to quantitative risk assessment. The use and application of the benchmark dose approach was a central theme in many of the workshop presentations and discussions, and the Special Issue includes several contributions that outline novel applications for the analysis and interpretation of genetic toxicity data. Although the contents of the Special Issue constitutes an important step towards the adoption of quantitative methods for regulatory assessment of genetic toxicity, formal acceptance of quantitative methods for HHRA and regulatory decision-making will require consensus regarding the

  9. Quantitative trait loci × environment interactions for plant morphology vary over ontogeny in Brassica rapa.

    Science.gov (United States)

    Dechaine, Jennifer M; Brock, Marcus T; Iniguez-Luy, Federico L; Weinig, Cynthia

    2014-01-01

    Growth in plants occurs via the addition of repeating modules, suggesting that the genetic architecture of similar subunits may vary between earlier- and later-developing modules. These complex environment × ontogeny interactions are not well elucidated, as studies examining quantitative trait loci (QTLs) expression over ontogeny have not included multiple environments. Here, we characterized the genetic architecture of vegetative traits and onset of reproduction over ontogeny in recombinant inbred lines of Brassica rapa in the field and glasshouse. The magnitude of genetic variation in plasticity of seedling internodes was greater than in those produced later in ontogeny. We correspondingly detected that QTLs for seedling internode length were environment-specific, whereas later in ontogeny the majority of QTLs affected internode lengths in all treatments. The relationship between internode traits and onset of reproduction varied with environment and ontogenetic stage. This relationship was observed only in the glasshouse environment and was largely attributable to one environment-specific QTL. Our results provide the first evidence of a QTL × environment × ontogeny interaction, and provide QTL resolution for differences between early- and later-stage plasticity for stem elongation. These results also suggest potential constraints on morphological evolution in early vs later modules as a result of associations with reproductive timing.

  10. Genotype-environment interactions for quantitative traits in Korea Associated Resource (KARE) cohorts

    Science.gov (United States)

    2014-01-01

    Background Due to the lack of statistical power and confounding effects of population structure in human population data, genotype-environment interaction studies have not yielded promising results and have provided only limited knowledge for exploring how genotype and environmental factors interact to in their influence onto risk. Results We analyzed 49 human quantitative traits in 7,170 unrelated Korean individuals on 326,262 autosomal single nucleotide polymorphisms (SNPs) collected from the KARE (Korean Association Resource) project, and we estimated the statistically significant proportion of variance that could be explained by genotype-area interactions in the supra-iliac skinfold thickness trait (hGE2 = 0.269 and P = 0.00032), which is related to abdominal obesity. Data suggested that the genotypes could have different effects on the phenotype (supra-iliac skinfold thickness) in different environmental settings (rural vs. urban areas). We then defined the genotype groups of individuals with similar genetic profiles based on the additive genetic relationships among individuals using SNPs. We observed the norms of reaction, and the differential phenotypic response of a genotype to a change in environmental exposure. Interestingly, we also found that the gene clusters responsible for cell-cell and cell-extracellular matrix interactions were enriched significantly for genotype-area interaction. Conclusions This significant heritability estimate of genotype-environment interactions will lead to conceptual advances in our understanding of the mechanisms underlying genotype-environment interactions, and could be ultimately applied to personalized preventative treatments based on environmental exposures. PMID:24491211

  11. Cheating for Problem Solving: A Genetic Algorithm with Social Interactions

    CERN Document Server

    Lahoz-Beltra, Rafeal; Aickelin, Uwe

    2010-01-01

    We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary role of social systems and its possible application as a non-genetic new step in evolutionary algorithms. In biological populations, ie animals, even human beings and microorganisms, social interactions often affect the fitness of individuals. It is conceivable that the perturbation of the fitness via social interactions is an evolutionary strategy to avoid trapping into local optimum, thus avoiding a fast convergence of the population. We model the social interactions according to Game Theory. The population is, therefore, composed by cooperator and defector individuals whose interactions produce payoffs according to well known game models (prisoner's dilemma, chicken game, and others). Our results on Knapsack problems show, for some game models, a significant performance improvement as compared to a standard genetic algorithm.

  12. Quantitative Modeling of Human-Environment Interactions in Preindustrial Time

    Science.gov (United States)

    Sommer, Philipp S.; Kaplan, Jed O.

    2017-04-01

    Quantifying human-environment interactions and anthropogenic influences on the environment prior to the Industrial revolution is essential for understanding the current state of the earth system. This is particularly true for the terrestrial biosphere, but marine ecosystems and even climate were likely modified by human activities centuries to millennia ago. Direct observations are however very sparse in space and time, especially as one considers prehistory. Numerical models are therefore essential to produce a continuous picture of human-environment interactions in the past. Agent-based approaches, while widely applied to quantifying human influence on the environment in localized studies, are unsuitable for global spatial domains and Holocene timescales because of computational demands and large parameter uncertainty. Here we outline a new paradigm for the quantitative modeling of human-environment interactions in preindustrial time that is adapted to the global Holocene. Rather than attempting to simulate agency directly, the model is informed by a suite of characteristics describing those things about society that cannot be predicted on the basis of environment, e.g., diet, presence of agriculture, or range of animals exploited. These categorical data are combined with the properties of the physical environment in coupled human-environment model. The model is, at its core, a dynamic global vegetation model with a module for simulating crop growth that is adapted for preindustrial agriculture. This allows us to simulate yield and calories for feeding both humans and their domesticated animals. We couple this basic caloric availability with a simple demographic model to calculate potential population, and, constrained by labor requirements and land limitations, we create scenarios of land use and land cover on a moderate-resolution grid. We further implement a feedback loop where anthropogenic activities lead to changes in the properties of the physical

  13. Using genetic programming to discover nonlinear variable interactions.

    Science.gov (United States)

    Westbury, Chris; Buchanan, Lori; Sanderson, Michael; Rhemtulla, Mijke; Phillips, Leah

    2003-05-01

    Psychology has to deal with many interacting variables. The analyses usually used to uncover such relationships have many constraints that limit their utility. We briefly discuss these and describe recent work that uses genetic programming to evolve equations to combine variables in nonlinear ways in a number of different domains. We focus on four studies of interactions from lexical access experiments and psychometric problems. In all cases, genetic programming described nonlinear combinations of items in a manner that was subsequently independently verified. We discuss the general implications of genetic programming and related computational methods for multivariate problems in psychology.

  14. Developmental quantitative genetic analysis of body weights and morphological traits in the turbot, Scophthalmusmaximus

    Institute of Scientific and Technical Information of China (English)

    WANG Xinan; MA Aijun; MA Deyou

    2015-01-01

    In order to elucidate the genetic mechanism of growth traits in turbot during ontogeny, developmental genetic analysis of the body weights, total lengths, standard lengths and body heights of turbots was conducted by mixed genetic models with additive-dominance effects, based on complete diallel crosses with four different strains of Scophthalmus maximus from Denmark, Norway, Britain, and France. Unconditional genetic analysis revealed that the unconditional additive effects for the four traits were more significant than unconditional dominance effects, meanwhile, the alternative expressions were also observed between the additive and dominant effects for body weights, total lengths and standard lengths. Conditional analysis showed that the developmental periods with active gene expression for body weights, total lengths, standard lengths and body heights were 15–18, 15 and 21–24, 15 and 24, and 21 and 27 months of age, respectively. The proportions of unconditional/conditional variances indicated that the narrow-sense heritabilities of body weights, total lengths and standard lengths were all increased systematically. The accumulative effects of genes controlling the four quantitative traits were mainly additive effects, suggesting that the selection is more efficient for the genetic improvement of turbots. The conditional genetic procedure is a useful tool to understand the expression of genes controlling developmental quantitative traits at a specific developmental period (t-1→t) during ontogeny. It is also important to determine the appropriate developmental period (t-1→t) for trait measurement in developmental quantitative genetic analysis in fish.

  15. Predicting genetic interactions with random walks on biological networks

    Directory of Open Access Journals (Sweden)

    Singh Ambuj K

    2009-01-01

    Full Text Available Abstract Background Several studies have demonstrated that synthetic lethal genetic interactions between gene mutations provide an indication of functional redundancy between molecular complexes and pathways. These observations help explain the finding that organisms are able to tolerate single gene deletions for a large majority of genes. For example, system-wide gene knockout/knockdown studies in S. cerevisiae and C. elegans revealed non-viable phenotypes for a mere 18% and 10% of the genome, respectively. It has been postulated that the low percentage of essential genes reflects the extensive amount of genetic buffering that occurs within genomes. Consistent with this hypothesis, systematic double-knockout screens in S. cerevisiae and C. elegans show that, on average, 0.5% of tested gene pairs are synthetic sick or synthetic lethal. While knowledge of synthetic lethal interactions provides valuable insight into molecular functionality, testing all combinations of gene pairs represents a daunting task for molecular biologists, as the combinatorial nature of these relationships imposes a large experimental burden. Still, the task of mapping pairwise interactions between genes is essential to discovering functional relationships between molecular complexes and pathways, as they form the basis of genetic robustness. Towards the goal of alleviating the experimental workload, computational techniques that accurately predict genetic interactions can potentially aid in targeting the most likely candidate interactions. Building on previous studies that analyzed properties of network topology to predict genetic interactions, we apply random walks on biological networks to accurately predict pairwise genetic interactions. Furthermore, we incorporate all published non-interactions into our algorithm for measuring the topological relatedness between two genes. We apply our method to S. cerevisiae and C. elegans datasets and, using a decision tree

  16. A regression framework incorporating quantitative and negative interaction data improves quantitative prediction of PDZ domain-peptide interaction from primary sequence.

    Science.gov (United States)

    Shao, Xiaojian; Tan, Chris S H; Voss, Courtney; Li, Shawn S C; Deng, Naiyang; Bader, Gary D

    2011-02-01

    Predicting protein interactions involving peptide recognition domains is essential for understanding the many important biological processes they mediate. It is important to consider the binding strength of these interactions to help us construct more biologically relevant protein interaction networks that consider cellular context and competition between potential binders. We developed a novel regression framework that considers both positive (quantitative) and negative (qualitative) interaction data available for mouse PDZ domains to quantitatively predict interactions between PDZ domains, a large peptide recognition domain family, and their peptide ligands using primary sequence information. First, we show that it is possible to learn from existing quantitative and negative interaction data to infer the relative binding strength of interactions involving previously unseen PDZ domains and/or peptides given their primary sequence. Performance was measured using cross-validated hold out testing and testing with previously unseen PDZ domain-peptide interactions. Second, we find that incorporating negative data improves quantitative interaction prediction. Third, we show that sequence similarity is an important prediction performance determinant, which suggests that experimentally collecting additional quantitative interaction data for underrepresented PDZ domain subfamilies will improve prediction. The Matlab code for our SemiSVR predictor and all data used here are available at http://baderlab.org/Data/PDZAffinity.

  17. Quantitative trait locus mapping reveals complex genetic architecture of quantitative virulence in the wheat pathogen Zymoseptoria tritici.

    Science.gov (United States)

    Stewart, Ethan L; Croll, Daniel; Lendenmann, Mark H; Sanchez-Vallet, Andrea; Hartmann, Fanny E; Palma-Guerrero, Javier; Ma, Xin; McDonald, Bruce A

    2016-11-21

    We conducted a comprehensive analysis of virulence in the fungal wheat pathogen Zymoseptoria tritici using quantitative trait locus (QTL) mapping. High-throughput phenotyping based on automated image analysis allowed the measurement of pathogen virulence on a scale and with a precision that was not previously possible. Across two mapping populations encompassing more than 520 progeny, 540 710 pycnidia were counted and their sizes and grey values were measured. A significant correlation was found between pycnidia size and both spore size and number. Precise measurements of percentage leaf area covered by lesions provided a quantitative measure of host damage. Combining these large and accurate phenotypic datasets with a dense panel of restriction site-associated DNA sequencing (RADseq) genetic markers enabled us to genetically dissect pathogen virulence into components related to host damage and those related to pathogen reproduction. We showed that different components of virulence can be under separate genetic control. Large- and small-effect QTLs were identified for all traits, with some QTLs specific to mapping populations, cultivars and traits and other QTLs shared among traits within the same mapping population. We associated the presence of four accessory chromosomes with small, but significant, increases in several virulence traits, providing the first evidence for a meaningful function associated with accessory chromosomes in this organism. A large-effect QTL involved in host specialization was identified on chromosome 7, leading to the identification of candidate genes having a large effect on virulence.

  18. Genetic influences on attention deficit hyperactivity disorder symptoms from age 2 to 3: A quantitative and molecular genetic investigation

    Directory of Open Access Journals (Sweden)

    Saudino Kimberly J

    2010-12-01

    Full Text Available Abstract Background A twin study design was used to assess the degree to which additive genetic variance influences ADHD symptom scores across two ages during infancy. A further objective in the study was to observe whether genetic association with a number of candidate markers reflects results from the quantitative genetic analysis. Method We have studied 312 twin pairs at two time-points, age 2 and age 3. A composite measure of ADHD symptoms from two parent-rating scales: The Child Behavior Checklist/1.5 - 5 years (CBCL hyperactivity scale and the Revised Rutter Parent Scale for Preschool Children (RRPSPC was used for both quantitative and molecular genetic analyses. Results At ages 2 and 3 ADHD symptoms are highly heritable (h2 = 0.79 and 0.78, respectively with a high level of genetic stability across these ages. However, we also observe a significant level of genetic change from age 2 to age 3. There are modest influences of non-shared environment at each age independently (e2 = 0.22 and 0.21, respectively, with these influences being largely age-specific. In addition, we find modest association signals in DAT1 and NET1 at both ages, along with suggestive specific effects of 5-HTT and DRD4 at age 3. Conclusions ADHD symptoms are heritable at ages 2 and 3. Additive genetic variance is largely shared across these ages, although there are significant new effects emerging at age 3. Results from our genetic association analysis reflect these levels of stability and change and, more generally, suggest a requirement for consideration of age-specific genotypic effects in future molecular studies.

  19. Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches.

    Science.gov (United States)

    Bérénos, Camillo; Ellis, Philip A; Pilkington, Jill G; Pemberton, Josephine M

    2014-07-01

    The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genomewide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long-term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (i) Pedigree 1, using observation-derived maternal links and microsatellite-derived paternal links; (ii) Pedigree 2, using SNP-derived assignment of both maternity and paternity; and (iii) whole-genome relatedness at 37 037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods, while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics

  20. Adaptive interactive genetic algorithms with individual interval fitness

    Institute of Scientific and Technical Information of China (English)

    Dunwei Gong; Guangsong Guo; Li Lu; Hongmei Ma

    2008-01-01

    It is necessary to enhance the performance of interactive genetic algorithms in order to apply them to complicated optimization problems successfully. An adaptive interactive genetic algorithm with individual interval fitness is proposed in this paper in which an individual fitness is expressed by an interval. Through analyzing the fitness, information reflecting the distribution of an evolutionary population is picked up, namely, the difference of evaluating superior individuals and the difference of evaluating a population. Based on these, the adaptive probabilities of crossover and mutation operators of an individual are presented. The algorithm proposed in this paper is applied to a fashion evolutionary design system, and the results show that it can find many satisfactory solutions per generation. The achievement of the paper provides a new approach to enhance the performance of interactive genetic algorithms.

  1. The current and future use of ridge regression for prediction in quantitative genetics

    NARCIS (Netherlands)

    R. de Vlaming (Ronald); P.J.F. Groenen (Patrick)

    2015-01-01

    textabstractIn recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge

  2. Quantitative PCR for Detection and Enumeration of Genetic Markers of Bovine Fecal Pollution

    Science.gov (United States)

    Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described cow feces-spec...

  3. Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

    Science.gov (United States)

    Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

    2009-11-01

    The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that

  4. Predicting human genetic interactions from cancer genome evolution.

    Directory of Open Access Journals (Sweden)

    Xiaowen Lu

    Full Text Available Synthetic Lethal (SL genetic interactions play a key role in various types of biological research, ranging from understanding genotype-phenotype relationships to identifying drug-targets against cancer. Despite recent advances in empirical measuring SL interactions in human cells, the human genetic interaction map is far from complete. Here, we present a novel approach to predict this map by exploiting patterns in cancer genome evolution. First, we show that empirically determined SL interactions are reflected in various gene presence, absence, and duplication patterns in hundreds of cancer genomes. The most evident pattern that we discovered is that when one member of an SL interaction gene pair is lost, the other gene tends not to be lost, i.e. the absence of co-loss. This observation is in line with expectation, because the loss of an SL interacting pair will be lethal to the cancer cell. SL interactions are also reflected in gene expression profiles, such as an under representation of cases where the genes in an SL pair are both under expressed, and an over representation of cases where one gene of an SL pair is under expressed, while the other one is over expressed. We integrated the various previously unknown cancer genome patterns and the gene expression patterns into a computational model to identify SL pairs. This simple, genome-wide model achieves a high prediction power (AUC = 0.75 for known genetic interactions. It allows us to present for the first time a comprehensive genome-wide list of SL interactions with a high estimated prediction precision, covering up to 591,000 gene pairs. This unique list can potentially be used in various application areas ranging from biotechnology to medical genetics.

  5. Prediction of quantitative phenotypes based on genetic networks: a case study in yeast sporulation

    Directory of Open Access Journals (Sweden)

    Shen Li

    2010-09-01

    Full Text Available Abstract Background An exciting application of genetic network is to predict phenotypic consequences for environmental cues or genetic perturbations. However, de novo prediction for quantitative phenotypes based on network topology is always a challenging task. Results Using yeast sporulation as a model system, we have assembled a genetic network from literature and exploited Boolean network to predict sporulation efficiency change upon deleting individual genes. We observe that predictions based on the curated network correlate well with the experimentally measured values. In addition, computational analysis reveals the robustness and hysteresis of the yeast sporulation network and uncovers several patterns of sporulation efficiency change caused by double gene deletion. These discoveries may guide future investigation of underlying mechanisms. We have also shown that a hybridized genetic network reconstructed from both temporal microarray data and literature is able to achieve a satisfactory prediction accuracy of the same quantitative phenotypes. Conclusions This case study illustrates the value of predicting quantitative phenotypes based on genetic network and provides a generic approach.

  6. Quantitative Genetic Analysis of Biomass and Wood Chemistry of Populus under Different Nitrogen Levels

    Energy Technology Data Exchange (ETDEWEB)

    Novaes, E.; Osorio, L.; Drost, D. R.; Miles, B. L.; Boaventura-Novaes, C. R. D.; Benedict, C.; Dervinis, C.; Yu, Q.; Sykes, R.; Davis, M.; Martin, T. A.; Peter, G. F.; Kirst, M.

    2009-01-01

    The genetic control of carbon allocation and partitioning in woody perennial plants is poorly understood despite its importance for carbon sequestration, biofuels and other wood-based industries. It is also unclear how environmental cues, such as nitrogen availability, impact the genes that regulate growth, biomass allocation and wood composition in trees. We phenotyped 396 clonally replicated genotypes of an interspecific pseudo-backcross pedigree of Populus for wood composition and biomass traits in above- and below-ground organs. The loci that regulate growth, carbon allocation and partitioning under two nitrogen conditions were identified, defining the contribution of environmental cues to their genetic control. Sixty-three quantitative trait loci were identified for the 20 traits analyzed. The majority of quantitative trait loci are specific to one of the two nitrogen treatments, demonstrating significant nitrogen-dependent genetic control. A highly significant genetic correlation was observed between plant growth and lignin/cellulose composition, and quantitative trait loci co-localization identified the genomic position of potential pleiotropic regulators. Pleiotropic loci linking higher growth rates to wood with less lignin are excellent targets to engineer tree germplasm improved for pulp, paper and cellulosic ethanol production. The causative genes are being identified with a genetical genomics approach.

  7. Investigation of the genetic association between quantitative measures of psychosis and schizophrenia

    DEFF Research Database (Denmark)

    Derks, Eske M; Vorstman, Jacob A S; Ripke, Stephan

    2012-01-01

    The presence of subclinical levels of psychosis in the general population may imply that schizophrenia is the extreme expression of more or less continuously distributed traits in the population. In a previous study, we identified five quantitative measures of schizophrenia (positive, negative......, disorganisation, mania, and depression scores). The aim of this study is to examine the association between a direct measure of genetic risk of schizophrenia and the five quantitative measures of psychosis. Estimates of the log of the odds ratios of case/control allelic association tests were obtained from...... the Psychiatric GWAS Consortium (PGC) (minus our sample) which included genome-wide genotype data of 8,690 schizophrenia cases and 11,831 controls. These data were used to calculate genetic risk scores in 314 schizophrenia cases and 148 controls from the Netherlands for whom genotype data and quantitative symptom...

  8. Spontaneous mutations and the origin and maintenance of quantitative genetic variation.

    Science.gov (United States)

    Huang, Wen; Lyman, Richard F; Lyman, Rachel A; Carbone, Mary Anna; Harbison, Susan T; Magwire, Michael M; Mackay, Trudy Fc

    2016-05-23

    Mutation and natural selection shape the genetic variation in natural populations. Here, we directly estimated the spontaneous mutation rate by sequencing new Drosophila mutation accumulation lines maintained with minimal natural selection. We inferred strong stabilizing natural selection on quantitative traits because genetic variation among wild-derived inbred lines was much lower than predicted from a neutral model and the mutational effects were much larger than allelic effects of standing polymorphisms. Stabilizing selection could act directly on the traits, or indirectly from pleiotropic effects on fitness. However, our data are not consistent with simple models of mutation-stabilizing selection balance; therefore, further empirical work is needed to assess the balance of evolutionary forces responsible for quantitative genetic variation.

  9. The quantitative basis of the Arabidopsis innate immune system to endemic pathogens depends on pathogen genetics

    DEFF Research Database (Denmark)

    Corwin, Jason A; Copeland, Daniel; Feusier, Julie

    2016-01-01

    the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B...... of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total......, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study...

  10. Quantitative trait loci mapping and genetic dissection for lint percentage in upland cotton (Gossypium hirsutum)

    Indian Academy of Sciences (India)

    Min Wang; Chengqi Li; Qinglian Wang

    2014-08-01

    Lint percentage is an important character of cotton yield components and it is also correlated with cotton fibre development. In this study, we used a high lint percentage variety, Baimian1, and a low lint percentage, TM-1 genetic standard for Gossypium hirsutum, as parents to construct a mapping populations in upland cotton (G. hirsutum). A quantitative trait locus/loci (QTL) analysis of lint percentage was performed by using two mapping procedures; composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and the F2:3 populations in 2 years. Six main-effect QTL (M-QTL) for lint percentage (four significant and two suggestive) were detected in both years by CIM, and were located on chr. 3, chr. 19, chr. 26 and chr. 5 /chr. 19. Of the six QTL, marker intervals and favourable gene sources of the significant M-QTL, qLP-3(2010) and qLP-3(2011) were consistent. These QTL were also detected by ICIM, and therefore, should preferentially be used for marker-assisted selection (MAS) of lint percentage. Another M-QTL, qLP-19(2010), was detected by two mapping procedures, and it could also be a candidate for MAS. We detected the interaction between two M-QTL and environment, and 11 epistatic QTL (E-QTL) and their interaction with environment by using ICIM. The study also found two EST-SSRs, NAU1187 and NAU1255, linked to M-QTL for lint percentage that could be candidate markers affecting cotton fibre development.

  11. Quantitative trait loci mapping and genetic dissection for lint percentage in upland cotton (Gossypium hirsutum).

    Science.gov (United States)

    Wang, Min; Li, Chengqi; Wang, Qinglian

    2014-08-01

    Lint percentage is an important character of cotton yield components and it is also correlated with cotton fibre development. In this study, we used a high lint percentage variety, Baimian1, and a low lint percentage, TM-1 genetic standard for Gossypium hirsutum, as parents to construct a mapping populations in upland cotton (G. hirsutum). A quantitative trait locus/loci (QTL) analysis of lint percentage was performed by using two mapping procedures; composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and the F2:3 populations in 2 years. Six main-effect QTL (M-QTL) for lint percentage (four significant and two suggestive) were detected in both years by CIM, and were located on chr. 3, chr. 19, chr. 26 and chr. 5/chr. 19. Of the six QTL, marker intervals and favourable gene sources of the significant M-QTL, qLP-3(2010) and qLP-3(2011) were consistent. These QTL were also detected by ICIM, and therefore, should preferentially be used for markerassisted selection (MAS) of lint percentage. Another M-QTL, qLP-19(2010), was detected by two mapping procedures, and it could also be a candidate for MAS. We detected the interaction between two M-QTL and environment, and 11 epistatic QTL (E-QTL) and their interaction with environment by using ICIM. The study also found two EST-SSRs, NAU1187 and NAU1255, linked to M-QTL for lint percentage that could be candidate markers affecting cotton fibre development.

  12. The quantitative genetic basis of polyandry in the parasitoid wasp, Nasonia vitripennis.

    Science.gov (United States)

    Shuker, D M; Phillimore, A J; Burton-Chellew, M N; Hodge, S E; West, S A

    2007-02-01

    Understanding the evolution of female multiple mating (polyandry) is crucial for understanding sexual selection and sexual conflict. Despite this interest, little is known about its genetic basis or whether genetics influences the evolutionary origin or maintenance of polyandry. Here, we explore the quantitative genetic basis of polyandry in the parasitoid wasp Nasonia vitripennis, a species in which female re-mating has been observed to evolve in the laboratory. We performed a quantitative genetic experiment on a recently collected population of wasps. We found low heritabilities of female polyandry (re-mating frequency after 18 h), low heritability of courtship duration and a slightly higher heritability of copulation duration. However, the coefficients of additive genetic variance for these traits were all reasonably large (CV(A)>7.0). We also found considerable dam effects for all traits after controlling for common environment, suggesting either dominance or maternal effects. Our work adds to the evidence that nonadditive genetic effects may influence the evolution of mating behaviour in Nasonia vitripennis, and the evolution of polyandry more generally.

  13. Gene-Environment Interactions in Asthma: Genetic and Epigenetic Effects.

    Science.gov (United States)

    Lee, Jong-Uk; Kim, Jeong Dong; Park, Choon-Sik

    2015-07-01

    Over the past three decades, a large number of genetic studies have been aimed at finding genetic variants associated with the risk of asthma, applying various genetic and genomic approaches including linkage analysis, candidate gene polymorphism studies, and genome-wide association studies (GWAS). However, contrary to general expectation, even single nucleotide polymorphisms (SNPs) discovered by GWAS failed to fully explain the heritability of asthma. Thus, application of rare allele polymorphisms in well defined phenotypes and clarification of environmental factors have been suggested to overcome the problem of 'missing' heritability. Such factors include allergens, cigarette smoke, air pollutants, and infectious agents during pre- and post-natal periods. The first and simplest interaction between a gene and the environment is a candidate interaction of both a well known gene and environmental factor in a direct physical or chemical interaction such as between CD14 and endotoxin or between HLA and allergens. Several GWAS have found environmental interactions with occupational asthma, aspirin exacerbated respiratory disease, tobacco smoke-related airway dysfunction, and farm-related atopic diseases. As one of the mechanisms behind gene-environment interaction is epigenetics, a few studies on DNA CpG methylation have been reported on subphenotypes of asthma, pitching the exciting idea that it may be possible to intervene at the junction between the genome and the environment. Epigenetic studies are starting to include data from clinical samples, which will make them another powerful tool for re-search on gene-environment interactions in asthma.

  14. A Simple Interactive Introduction to Teaching Genetic Engineering

    Science.gov (United States)

    Child, Paula

    2013-01-01

    In the UK, at key stage 4, students aged 14-15 studying GCSE Core Science or Unit 1 of the GCSE Biology course are required to be able to describe the process of genetic engineering to produce bacteria that can produce insulin. The simple interactive introduction described in this article allows students to consider the problem, devise a model and…

  15. Quantitative genetics of shape in cricket wings: developmental integration in a functional structure.

    Science.gov (United States)

    Klingenberg, Christian Peter; Debat, Vincent; Roff, Derek A

    2010-10-01

    The role of developmental and genetic integration for evolution is contentious. One hypothesis states that integration acts as a constraint on evolution, whereas an alternative is that developmental and genetic systems evolve to match the functional modularity of organisms. This study examined a morphological structure, the cricket wing, where developmental and functional modules are discordant, making it possible to distinguish the two alternatives. Wing shape was characterized with geometric morphometrics, quantitative genetic information was extracted using a full-sibling breeding design, and patterns of developmental integration were inferred from fluctuating asymmetry of wing shape. The patterns of genetic, phenotypic, and developmental integration were clearly similar, but not identical. Heritabilities for different shape variables varied widely, but no shape variables were devoid of genetic variation. Simulated selection for specific shape changes produced predicted responses with marked deflections due to the genetic covariance structure. Three hypotheses of modularity according to the wing structures involved in sound production were inconsistent with the genetic, phenotypic, or developmental covariance structure. Instead, there appears to be strong integration throughout the wing. The hypothesis that genetic and developmental integration evolve to match functional modularity can therefore be rejected for this example.

  16. Are Genetically Informed Designs Genetically Informative?: Comment on McGue, Elkins, Walden, and Iacono (2005) and Quantitative Behavioral Genetics

    Science.gov (United States)

    Partridge, Ty

    2005-01-01

    M. McGue, I. Elkins, B. Walden, and W. G. Iacono (see record 2005-14938-011) presented the findings from a twin study examining the relative contributions of genetic and environmental factors to the developmental trajectories of parent-adolescent relationships. From a behavioral genetics perspective, this study is well conceptualized, is well…

  17. Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development

    NARCIS (Netherlands)

    Pires, Nuno D.; Bemer, Marian; Müller, Lena M.; Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

    2016-01-01

    Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship) theory proposes that imprinting can

  18. Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development.

    Science.gov (United States)

    Pires, Nuno D; Bemer, Marian; Müller, Lena M; Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

    2016-01-01

    Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship) theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict.

  19. Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development.

    Directory of Open Access Journals (Sweden)

    Nuno D Pires

    2016-01-01

    Full Text Available Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict.

  20. Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development.

    Directory of Open Access Journals (Sweden)

    Nuno D Pires

    2016-01-01

    Full Text Available Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict.

  1. The quantitative genetics of indirect genetic effects: a selective review of modelling issues : Review

    NARCIS (Netherlands)

    Bijma, P.

    2014-01-01

    Indirect genetic effects (IGE) occur when the genotype of an individual affects the phenotypic trait value of another conspecific individual. IGEs can have profound effects on both the magnitude and the direction of response to selection. Models of inheritance and response to selection in traits sub

  2. Inferring modulators of genetic interactions with epistatic nested effects models.

    Science.gov (United States)

    Pirkl, Martin; Diekmann, Madeline; van der Wees, Marlies; Beerenwinkel, Niko; Fröhlich, Holger; Markowetz, Florian

    2017-04-01

    Maps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in different ways (called mixed epistasis). Here we test the hypothesis that mixed epistasis between a gene pair can be explained by the action of a third gene that modulates the interaction. We have extended the framework of Nested Effects Models (NEMs), a type of graphical model specifically tailored to analyze high-dimensional gene perturbation data, to incorporate logical functions that describe interactions between regulators on downstream genes and proteins. We benchmark our approach in the controlled setting of a simulation study and show high accuracy in inferring the correct model. In an application to data from deletion mutants of kinases and phosphatases in S. cerevisiae we show that epistatic NEMs can point to modulators of genetic interactions. Our approach is implemented in the R-package 'epiNEM' available from https://github.com/cbg-ethz/epiNEM and https://bioconductor.org/packages/epiNEM/.

  3. The quantitative genetic architecture of the bold-shy continuum in zebrafish, Danio rerio.

    Directory of Open Access Journals (Sweden)

    Mary E Oswald

    Full Text Available In studies of consistent individual differences (personality along the bold-shy continuum, a pattern of behavioral correlations frequently emerges: individuals towards the bold end of the continuum are more likely to utilize risky habitat, approach potential predators, and feed under risky conditions. Here, we address the hypothesis that observed phenotypic correlations among component behaviors of the bold-shy continuum are a result of underlying genetic correlations (quantitative genetic architecture. We used a replicated three-generation pedigree of zebrafish (Danio rerio to study three putative components of the bold-shy continuum: horizontal position, swim level, and feeding latency. We detected significant narrow-sense heritabilities as well as significant genetic and phenotypic correlations among all three behaviors, such that fish selected for swimming at the front of the tank swam closer to the observer, swam higher in the water column, and fed more quickly than fish selected for swimming at the back of the tank. Further, the lines varied in their initial open field behavior (swim level and activity level. The quantitative genetic architecture of the bold-shy continuum indicates that the multivariate behavioral phenotype characteristic of a "bold" personality type may be a result of correlated evolution via underlying genetic correlations.

  4. On the physical basis for ambiguity in genetic coding interactions.

    Science.gov (United States)

    Grosjean, H J; de Henau, S; Crothers, D M

    1978-02-01

    We report the relative stabilities, in the form of complex lifetimes, of complexes between the tRNAs complementary, or nearly so, in their anticodons. The results show striking parallels with the genetic coding rules, including the wobble interaction and the role of modified nucleotides S2U and V (a 5-oxyacetic acid derivative of U). One important difference between the genetic code and the pairing rules in the tRNA-tRNA interaction is the stability in the latter of the short wobble pairs, which the wobble hypothesis excludes. We stress the potential of U for translational errors, and suggest a simple stereochemical basis for ribosome-mediated discrimination against short wobble pairs. Surprisingly, the stability of anticodon-anticodon complexes does not vary systematically on base sequence. Because of the close similarity to the genetic coding rules, it is tempting to speculate that the interaction between two RNA loops may have been part of the physical basis for the evolutionary origin of the genetic code, and that this mechanism may still be utilized by folding the mRNA on the ribosome into a loop similar to the anticodon loop.

  5. On the Mapping of Epistatic Genetic Interactions in Natural Isolates: Combining Classical Genetics and Genomics.

    Science.gov (United States)

    Hou, Jing; Schacherer, Joseph

    2016-01-01

    Genetic variation within species is the substrate of evolution. Epistasis, which designates the non-additive interaction between loci affecting a specific phenotype, could be one of the possible outcomes of genetic diversity. Dissecting the basis of such interactions is of current interest in different fields of biology, from exploring the gene regulatory network, to complex disease genetics, to the onset of reproductive isolation and speciation. We present here a general workflow to identify epistatic interactions between independently evolving loci in natural populations of the yeast Saccharomyces cerevisiae. The idea is to exploit the genetic diversity present in the species by evaluating a large number of crosses and analyzing the phenotypic distribution in the offspring. For a cross of interest, both parental strains would have a similar phenotypic value, whereas the resulting offspring would have a bimodal distribution of the phenotype, possibly indicating the presence of epistasis. Classical segregation analysis of the tetrads uncovers the penetrance and complexity of the interaction. In addition, this segregation could serve as the guidelines for choosing appropriate mapping strategies to narrow down the genomic regions involved. Depending on the segregation patterns observed, we propose different mapping strategies based on bulk segregant analysis or consecutive backcrosses followed by high-throughput genome sequencing. Our method is generally applicable to all systems with a haplodiplobiontic life cycle and allows high resolution mapping of interacting loci that govern various DNA polymorphisms from single nucleotide mutations to large-scale structural variations.

  6. Huntingtin interacting proteins are genetic modifiers of neurodegeneration.

    Directory of Open Access Journals (Sweden)

    Linda S Kaltenbach

    2007-05-01

    Full Text Available Huntington's disease (HD is a fatal neurodegenerative condition caused by expansion of the polyglutamine tract in the huntingtin (Htt protein. Neuronal toxicity in HD is thought to be, at least in part, a consequence of protein interactions involving mutant Htt. We therefore hypothesized that genetic modifiers of HD neurodegeneration should be enriched among Htt protein interactors. To test this idea, we identified a comprehensive set of Htt interactors using two complementary approaches: high-throughput yeast two-hybrid screening and affinity pull down followed by mass spectrometry. This effort led to the identification of 234 high-confidence Htt-associated proteins, 104 of which were found with the yeast method and 130 with the pull downs. We then tested an arbitrary set of 60 genes encoding interacting proteins for their ability to behave as genetic modifiers of neurodegeneration in a Drosophila model of HD. This high-content validation assay showed that 27 of 60 orthologs tested were high-confidence genetic modifiers, as modification was observed with more than one allele. The 45% hit rate for genetic modifiers seen among the interactors is an order of magnitude higher than the 1%-4% typically observed in unbiased genetic screens. Genetic modifiers were similarly represented among proteins discovered using yeast two-hybrid and pull-down/mass spectrometry methods, supporting the notion that these complementary technologies are equally useful in identifying biologically relevant proteins. Interacting proteins confirmed as modifiers of the neurodegeneration phenotype represent a diverse array of biological functions, including synaptic transmission, cytoskeletal organization, signal transduction, and transcription. Among the modifiers were 17 loss-of-function suppressors of neurodegeneration, which can be considered potential targets for therapeutic intervention. Finally, we show that seven interacting proteins from among 11 tested were able to

  7. A consensus map of rapeseed (Brassica napus L.) based on diversity array technology markers: applications in genetic dissection of qualitative and quantitative traits

    National Research Council Canada - National Science Library

    Raman, Harsh; Raman, Rosy; Kilian, Andrzej; Detering, Frank; Long, Yan; Edwards, David; Parkin, Isobel A P; Sharpe, Andrew G; Nelson, Matthew N; Larkan, Nick; Zou, Jun; Meng, Jinling; Aslam, M Naveed; Batley, Jacqueline; Cowling, Wallace A; Lydiate, Derek

    2013-01-01

    Dense consensus genetic maps based on high-throughput genotyping platforms are valuable for making genetic gains in Brassica napus through quantitative trait locus identification, efficient predictive...

  8. Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

    Science.gov (United States)

    Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

    2016-01-01

    Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability

  9. Genetic diversity among exotic cotton accessions as for qualitative and quantitative traits.

    Science.gov (United States)

    de Carvalho, L P; Farias, F J C; Rodrigues, J I S; Suassuna, N D; Teodoro, P E

    2017-02-08

    Studying genetic diversity among a group of genotypes is important in genetic breeding because identifying hybrid combinations of greater heterotic effect also increases the chance of obtaining plants with favorable allele combinations in an intra-population selection program. The objective of this study was to compare different types of long and extra-long staple cotton and their genetic diversity in relation to the fiber traits and some agronomic traits in order to grant breeding programs. Diversity analysis among 29 cotton accessions based on qualitative and quantitative traits and joint including qualitative and quantitative traits was performed. Analysis based on qualitative and quantitative traits and joint met the accessions in three, two, and three groups, respectively. The cross between genotypes Giza 59 and Pima unknown was the most promising to generate segregating populations, comprising simultaneously resistance (based on molecular markers) to blue disease and bacterial blight, partial resistance to root-knot nematode, smaller size, in addition to good fiber characteristics. These populations can be used in recurrent selection programs as donors of alleles for development of long-staple cotton genotypes.

  10. Uncovering the genetic signature of quantitative trait evolution with replicated time series data.

    Science.gov (United States)

    Franssen, S U; Kofler, R; Schlötterer, C

    2017-01-01

    The genetic architecture of adaptation in natural populations has not yet been resolved: it is not clear to what extent the spread of beneficial mutations (selective sweeps) or the response of many quantitative trait loci drive adaptation to environmental changes. Although much attention has been given to the genomic footprint of selective sweeps, the importance of selection on quantitative traits is still not well studied, as the associated genomic signature is extremely difficult to detect. We propose 'Evolve and Resequence' as a promising tool, to study polygenic adaptation of quantitative traits in evolving populations. Simulating replicated time series data we show that adaptation to a new intermediate trait optimum has three characteristic phases that are reflected on the genomic level: (1) directional frequency changes towards the new trait optimum, (2) plateauing of allele frequencies when the new trait optimum has been reached and (3) subsequent divergence between replicated trajectories ultimately leading to the loss or fixation of alleles while the trait value does not change. We explore these 3 phase characteristics for relevant population genetic parameters to provide expectations for various experimental evolution designs. Remarkably, over a broad range of parameters the trajectories of selected alleles display a pattern across replicates, which differs both from neutrality and directional selection. We conclude that replicated time series data from experimental evolution studies provide a promising framework to study polygenic adaptation from whole-genome population genetics data.

  11. EVOLUTION AND EXTINCTION IN A CHANGING ENVIRONMENT: A QUANTITATIVE-GENETIC ANALYSIS.

    Science.gov (United States)

    Bürger, Reinhard; Lynch, Michael

    1995-02-01

    Because of the ubiquity of genetic variation for quantitative traits, virtually all populations have some capacity to respond evolutionarily to selective challenges. However, natural selection imposes demographic costs on a population, and if these costs are sufficiently large, the likelihood of extinction will be high. We consider how the mean time to extinction depends on selective pressures (rate and stochasticity of environmental change, and strength of selection), population parameters (carrying capacity, and reproductive capacity), and genetics (rate of polygenic mutation). We assume that in a randomly mating, finite population subject to density-dependent population growth, individual fitness is determined by a single quantitative-genetic character under Gaussian stabilizing selection with the optimum phenotype exhibiting directional change, or random fluctuations, or both. The quantitative trait is determined by a finite number of freely recombining, mutationally equivalent, additive loci. The dynamics of evolution and extinction are investigated, assuming that the population is initially under mutation-selection-drift balance. Under this model, in a directionally changing environment, the mean phenotype lags behind the optimum, but on the average evolves parallel to it. The magnitude of the lag determines the vulnerability to extinction. In finite populations, stochastic variation in the genetic variance can be quite pronounced, and bottlenecks in the genetic variance temporarily can impair the population's adaptive capacity enough to cause extinction when it would otherwise be unlikely in an effectively infinite population. We find that maximum sustainable rates of evolution or, equivalently, critical rates of environmental change, may be considerably less than 10% of a phenotypic standard deviation per generation. © 1995 The Society for the Study of Evolution.

  12. A bivariate quantitative genetic model for a linear Gaussian trait and a survival trait

    Directory of Open Access Journals (Sweden)

    Damgaard Lars

    2005-12-01

    Full Text Available Abstract With the increasing use of survival models in animal breeding to address the genetic aspects of mainly longevity of livestock but also disease traits, the need for methods to infer genetic correlations and to do multivariate evaluations of survival traits and other types of traits has become increasingly important. In this study we derived and implemented a bivariate quantitative genetic model for a linear Gaussian and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted. Model parameters were inferred from their marginal posterior distributions. The required fully conditional posterior distributions were derived and issues on implementation are discussed. The twoWeibull baseline parameters were updated jointly using a Metropolis-Hastingstep. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. Simulation results showed that the estimated marginal posterior distributions covered well and placed high density to the true parameter values used in the simulation of data. In conclusion, the proposed method allows inferring additive genetic and environmental correlations, and doing multivariate genetic evaluation of a linear Gaussian trait and a survival trait.

  13. A bivariate quantitative genetic model for a linear Gaussian trait and a survival trait.

    Science.gov (United States)

    Damgaard, Lars Holm; Korsgaard, Inge Riis

    2006-01-01

    With the increasing use of survival models in animal breeding to address the genetic aspects of mainly longevity of livestock but also disease traits, the need for methods to infer genetic correlations and to do multivariate evaluations of survival traits and other types of traits has become increasingly important. In this study we derived and implemented a bivariate quantitative genetic model for a linear Gaussian and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted. Model parameters were inferred from their marginal posterior distributions. The required fully conditional posterior distributions were derived and issues on implementation are discussed. The two Weibull baseline parameters were updated jointly using a Metropolis-Hasting step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. Simulation results showed that the estimated marginal posterior distributions covered well and placed high density to the true parameter values used in the simulation of data. In conclusion, the proposed method allows inferring additive genetic and environmental correlations, and doing multivariate genetic evaluation of a linear Gaussian trait and a survival trait.

  14. Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

    Science.gov (United States)

    Baker, Robert L; Leong, Wen Fung; Brock, Marcus T; Markelz, R J Cody; Covington, Michael F; Devisetty, Upendra K; Edwards, Christine E; Maloof, Julin; Welch, Stephen; Weinig, Cynthia

    2015-10-01

    Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange.

  15. WOMBAT: a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML).

    Science.gov (United States)

    Meyer, Karin

    2007-11-01

    WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses. Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from (http://agbu. une.edu.au/~kmeyer/wombat.html).

  16. Genetic algorithm based image binarization approach and its quantitative evaluation via pooling

    Science.gov (United States)

    Hu, Huijun; Liu, Ya; Liu, Maofu

    2015-12-01

    The binarized image is very critical to image visual feature extraction, especially shape feature, and the image binarization approaches have been attracted more attentions in the past decades. In this paper, the genetic algorithm is applied to optimizing the binarization threshold of the strip steel defect image. In order to evaluate our genetic algorithm based image binarization approach in terms of quantity, we propose the novel pooling based evaluation metric, motivated by information retrieval community, to avoid the lack of ground-truth binary image. Experimental results show that our genetic algorithm based binarization approach is effective and efficiency in the strip steel defect images and our quantitative evaluation metric on image binarization via pooling is also feasible and practical.

  17. The quantitative genetics of incipient speciation: heritability and genetic correlations of skeletal traits in populations of diverging Favia fragum ecomorphs.

    Science.gov (United States)

    Carlon, David B; Budd, Ann F; Lippé, Catherine; Andrew, Rose L

    2011-12-01

    Recent speciation events provide potential opportunities to understand the microevolution of reproductive isolation. We used a marker-based approach and a common garden to estimate the additive genetic variation in skeletal traits in a system of two ecomorphs within the coral species Favia fragum: a Tall ecomorph that is a seagrass specialist, and a Short ecomorph that is most abundant on coral reefs. Considering both ecomorphs, we found significant narrow-sense heritability (h(2) ) in a suite of measurements that define corallite architecture, and could partition additive and nonadditive variation for some traits. We found positive genetic correlations for homologous height and length measurements among different types of vertical plates (costosepta) within corallites, but negative correlations between height and length within, as well as between costosepta. Within ecomorphs, h(2) estimates were generally lower, compared to the combined ecomorph analysis. Marker-based estimates of h(2) were comparable to broad-sense heritability (H) obtained from parent-offspring regressions in a common garden for most traits, and similar genetic co-variance matrices for common garden and wild populations may indicate relatively small G × E interactions. The patterns of additive genetic variation in this system invite hypotheses of divergent selection or genetic drift as potential evolutionary drivers of reproductive isolation.

  18. Quantitative analysis of genomic element interactions by molecular colony technique.

    Science.gov (United States)

    Gavrilov, Alexey A; Chetverina, Helena V; Chermnykh, Elina S; Razin, Sergey V; Chetverin, Alexander B

    2014-03-01

    Distant genomic elements were found to interact within the folded eukaryotic genome. However, the used experimental approach (chromosome conformation capture, 3C) enables neither determination of the percentage of cells in which the interactions occur nor demonstration of simultaneous interaction of >2 genomic elements. Each of the above can be done using in-gel replication of interacting DNA segments, the technique reported here. Chromatin fragments released from formaldehyde-cross-linked cells by sodium dodecyl sulfate extraction and sonication are distributed in a polyacrylamide gel layer followed by amplification of selected test regions directly in the gel by multiplex polymerase chain reaction. The fragments that have been cross-linked and separate fragments give rise to multi- and monocomponent molecular colonies, respectively, which can be distinguished and counted. Using in-gel replication of interacting DNA segments, we demonstrate that in the material from mouse erythroid cells, the majority of fragments containing the promoters of active β-globin genes and their remote enhancers do not form complexes stable enough to survive sodium dodecyl sulfate extraction and sonication. This indicates that either these elements do not interact directly in the majority of cells at a given time moment, or the formed DNA-protein complex cannot be stabilized by formaldehyde cross-linking.

  19. Neurodegenerative diseases: quantitative predictions of protein-RNA interactions.

    Science.gov (United States)

    Cirillo, Davide; Agostini, Federico; Klus, Petr; Marchese, Domenica; Rodriguez, Silvia; Bolognesi, Benedetta; Tartaglia, Gian Gaetano

    2013-02-01

    Increasing evidence indicates that RNA plays an active role in a number of neurodegenerative diseases. We recently introduced a theoretical framework, catRAPID, to predict the binding ability of protein and RNA molecules. Here, we use catRAPID to investigate ribonucleoprotein interactions linked to inherited intellectual disability, amyotrophic lateral sclerosis, Creutzfeuld-Jakob, Alzheimer's, and Parkinson's diseases. We specifically focus on (1) RNA interactions with fragile X mental retardation protein FMRP; (2) protein sequestration caused by CGG repeats; (3) noncoding transcripts regulated by TAR DNA-binding protein 43 TDP-43; (4) autogenous regulation of TDP-43 and FMRP; (5) iron-mediated expression of amyloid precursor protein APP and α-synuclein; (6) interactions between prions and RNA aptamers. Our results are in striking agreement with experimental evidence and provide new insights in processes associated with neuronal function and misfunction.

  20. Validation of PCR methods for quantitation of genetically modified plants in food.

    Science.gov (United States)

    Hübner, P; Waiblinger, H U; Pietsch, K; Brodmann, P

    2001-01-01

    For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

  1. A Novel Approach for Discovery Quantitative Fuzzy Multi-Level Association Rules Mining Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Saad M. Darwish

    2016-10-01

    Full Text Available Quantitative multilevel association rules mining is a central field to realize motivating associations among data components with multiple levels abstractions. The problem of expanding procedures to handle quantitative data has been attracting the attention of many researchers. The algorithms regularly discretize the attribute fields into sharp intervals, and then implement uncomplicated algorithms established for Boolean attributes. Fuzzy association rules mining approaches are intended to defeat such shortcomings based on the fuzzy set theory. Furthermore, most of the current algorithms in the direction of this topic are based on very tiring search methods to govern the ideal support and confidence thresholds that agonize from risky computational cost in searching association rules. To accelerate quantitative multilevel association rules searching and escape the extreme computation, in this paper, we propose a new genetic-based method with significant innovation to determine threshold values for frequent item sets. In this approach, a sophisticated coding method is settled, and the qualified confidence is employed as the fitness function. With the genetic algorithm, a comprehensive search can be achieved and system automation is applied, because our model does not need the user-specified threshold of minimum support. Experiment results indicate that the recommended algorithm can powerfully generate non-redundant fuzzy multilevel association rules.

  2. The Flowering Repressor SVP Underlies a Novel Arabidopsis thaliana QTL Interacting with the Genetic Background

    Science.gov (United States)

    Méndez-Vigo, Belén; Martínez-Zapater, José M.; Alonso-Blanco, Carlos

    2013-01-01

    The timing of flowering initiation is a fundamental trait for the adaptation of annual plants to different environments. Large amounts of intraspecific quantitative variation have been described for it among natural accessions of many species, but the molecular and evolutionary mechanisms underlying this genetic variation are mainly being determined in the model plant Arabidopsis thaliana. To find novel A. thaliana flowering QTL, we developed introgression lines from the Japanese accession Fuk, which was selected based on the substantial transgression observed in an F2 population with the reference strain Ler. Analysis of an early flowering line carrying a single Fuk introgression identified Flowering Arabidopsis QTL1 (FAQ1). We fine-mapped FAQ1 in an 11 kb genomic region containing the MADS transcription factor gene SHORT VEGETATIVE PHASE (SVP). Complementation of the early flowering phenotype of FAQ1-Fuk with a SVP-Ler transgen demonstrated that FAQ1 is SVP. We further proved by directed mutagenesis and transgenesis that a single amino acid substitution in SVP causes the loss-of-function and early flowering of Fuk allele. Analysis of a worldwide collection of accessions detected FAQ1/SVP-Fuk allele only in Asia, with the highest frequency appearing in Japan, where we could also detect a potential ancestral genotype of FAQ1/SVP-Fuk. In addition, we evaluated allelic and epistatic interactions of SVP natural alleles by analysing more than one hundred transgenic lines carrying Ler or Fuk SVP alleles in five genetic backgrounds. Quantitative analyses of these lines showed that FAQ1/SVP effects vary from large to small depending on the genetic background. These results support that the flowering repressor SVP has been recently selected in A. thaliana as a target for early flowering, and evidence the relevance of genetic interactions for the intraspecific evolution of FAQ1/SVP and flowering time. PMID:23382706

  3. The flowering repressor SVP underlies a novel Arabidopsis thaliana QTL interacting with the genetic background.

    Directory of Open Access Journals (Sweden)

    Belén Méndez-Vigo

    Full Text Available The timing of flowering initiation is a fundamental trait for the adaptation of annual plants to different environments. Large amounts of intraspecific quantitative variation have been described for it among natural accessions of many species, but the molecular and evolutionary mechanisms underlying this genetic variation are mainly being determined in the model plant Arabidopsis thaliana. To find novel A. thaliana flowering QTL, we developed introgression lines from the Japanese accession Fuk, which was selected based on the substantial transgression observed in an F(2 population with the reference strain Ler. Analysis of an early flowering line carrying a single Fuk introgression identified Flowering Arabidopsis QTL1 (FAQ1. We fine-mapped FAQ1 in an 11 kb genomic region containing the MADS transcription factor gene SHORT VEGETATIVE PHASE (SVP. Complementation of the early flowering phenotype of FAQ1-Fuk with a SVP-Ler transgen demonstrated that FAQ1 is SVP. We further proved by directed mutagenesis and transgenesis that a single amino acid substitution in SVP causes the loss-of-function and early flowering of Fuk allele. Analysis of a worldwide collection of accessions detected FAQ1/SVP-Fuk allele only in Asia, with the highest frequency appearing in Japan, where we could also detect a potential ancestral genotype of FAQ1/SVP-Fuk. In addition, we evaluated allelic and epistatic interactions of SVP natural alleles by analysing more than one hundred transgenic lines carrying Ler or Fuk SVP alleles in five genetic backgrounds. Quantitative analyses of these lines showed that FAQ1/SVP effects vary from large to small depending on the genetic background. These results support that the flowering repressor SVP has been recently selected in A. thaliana as a target for early flowering, and evidence the relevance of genetic interactions for the intraspecific evolution of FAQ1/SVP and flowering time.

  4. The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

    Directory of Open Access Journals (Sweden)

    Ronald de Vlaming

    2015-01-01

    Full Text Available In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i the theoretical foundations of ridge regression, (ii its link to commonly used methods in animal breeding, (iii the computational feasibility, and (iv the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis. Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N<10,000 the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP. However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

  5. The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics.

    Science.gov (United States)

    de Vlaming, Ronald; Groenen, Patrick J F

    2015-01-01

    In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i) the theoretical foundations of ridge regression, (ii) its link to commonly used methods in animal breeding, (iii) the computational feasibility, and (iv) the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis). Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N < 10,000) the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP). However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

  6. 59. Cold Spring Harbor symposium on quantitative biology: Molecular genetics of cancer

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    Investigation of the mechanistic aspects of cancer has its roots in the studies on tumor viruses and their effects on cell proliferation, function, and growth. This outstanding progress was well documented in previous Cold Spring Harbor Symposia on Quantitative Biology. In the early to mid 1980s, progress on the development of chromosome mapping strategies and the accumulation of DNA probes that identified polymorphisms, encouraged by the international Human Genome Project, enabled the identification of other genes that contributed to familial inheritance of high susceptibility to specific cancers. This approach was very successful and led to a degree of optimism that one aspect of cancer, the multistep genetic process from early neoplasia to metastatic tumors, was beginning to be understood. It therefore seemed appropriate that the 59th Symposium on Quantitative Biology focus attention on the Molecular Genetics of Cancer. The concept was to combine the exciting progress on the identification of new genetic alterations in human tumor cells with studies on the function of the cancer gene products and how they go awry in tumor cells.

  7. Quantitative visualization of droplet hot-surface interaction

    Science.gov (United States)

    Erkan, Nejdet; Okamoto, Koji

    2013-11-01

    Up to this date liquid droplet impingement phenomenon onto hot surfaces has drawn massive attention from a broad spectrum of research fields, since its hydrodynamic and thermodynamic characteristics has profound importance for various industrial applications Although tremendous experimental and computational work exist in the literature, thermal-hydraulic mechanism of droplet impingement boiling on hot surfaces received several contradictory approaches due to the parametric sensitivity of the problem. To understand and to predict the physical mechanism, an experimental database including large amount of spatio-temporal data, which is formed by the tests performed under well-controlled BCs and high sensitive devices, is still a necessity. This study investigates the parametric variation of droplet boiling regimes due to the experimental BCs (e.g surface roughness, ambient pressure) by performing separate effect tests employing high-speed visualization system. Differences in the impingement boiling characteristics of water droplets on solid (with surface roughness) and liquid metal (without surface roughness) in film boiling regime are investigated. A unique quantitative velocity data inside the droplet at several surface temperatures including (Leidenfrost temperatures) captured by Particle Tracking Velocimetry (PTV). This data is a unique component for the validation of CFD simulations which are performed to resolve the phenomena.

  8. Interaction of quantitative PCR components with polymeric surfaces.

    Science.gov (United States)

    Gonzalez, Asensio; Grimes, Ronan; Walsh, Edmond J; Dalton, Tara; Davies, Mark

    2007-04-01

    This study investigated the effect of exposing a polymerase chain reaction (PCR) mixture to capillary tubing of different materials and lengths, at different contact times and flow rates and the adsorption of major reaction components into the tubing wall. Using 0.5 mm ID tubing, lengths of 40 cm and residence times up to 45 min, none of the tested polymeric materials was found to affect subsequent PCR amplification. However, after exposure of the mixture to tubing lengths of 3 m or reduction of sample volume, PCR inhibition occurred, increasing with the volume to length ratio. Different flow velocities did not affect PCR yield. When the adsorption of individual PCR components was studied, significant DNA adsorption and even more significant adsorption of the fluorescent dye Sybr Green I was found. The results indicate that PCR inhibition in polymeric tubing results from adsorption of reaction components to wall surfaces, increasing substantially with tubing length or sample volume reduction, but not with contact time or flow velocities typical in dynamic PCR amplification. The data also highlight that chemical compatibility of polymeric capillaries with DNA dyes should be carefully considered for the design of quantitative microfluidic devices.

  9. Quantitative analysis of TALE-DNA interactions suggests polarity effects.

    Science.gov (United States)

    Meckler, Joshua F; Bhakta, Mital S; Kim, Moon-Soo; Ovadia, Robert; Habrian, Chris H; Zykovich, Artem; Yu, Abigail; Lockwood, Sarah H; Morbitzer, Robert; Elsäesser, Janett; Lahaye, Thomas; Segal, David J; Baldwin, Enoch P

    2013-04-01

    Transcription activator-like effectors (TALEs) have revolutionized the field of genome engineering. We present here a systematic assessment of TALE DNA recognition, using quantitative electrophoretic mobility shift assays and reporter gene activation assays. Within TALE proteins, tandem 34-amino acid repeats recognize one base pair each and direct sequence-specific DNA binding through repeat variable di-residues (RVDs). We found that RVD choice can affect affinity by four orders of magnitude, with the relative RVD contribution in the order NG > HD ≈ NN > NI > NK. The NN repeat preferred the base G over A, whereas the NK repeat bound G with 10(3)-fold lower affinity. We compared AvrBs3, a naturally occurring TALE that recognizes its target using some atypical RVD-base combinations, with a designed TALE that precisely matches 'standard' RVDs with the target bases. This comparison revealed unexpected differences in sensitivity to substitutions of the invariant 5'-T. Another surprising observation was that base mismatches at the 5' end of the target site had more disruptive effects on affinity than those at the 3' end, particularly in designed TALEs. These results provide evidence that TALE-DNA recognition exhibits a hitherto un-described polarity effect, in which the N-terminal repeats contribute more to affinity than C-terminal ones.

  10. Mapping the genetic basis of symbiotic variation in legume-rhizobium interactions in Medicago truncatula.

    Science.gov (United States)

    Gorton, Amanda J; Heath, Katy D; Pilet-Nayel, Marie-Laure; Baranger, Alain; Stinchcombe, John R

    2012-11-01

    Mutualisms are known to be genetically variable, where the genotypes differ in the fitness benefits they gain from the interaction. To date, little is known about the loci that underlie such genetic variation in fitness or whether the loci influencing fitness are partner specific, and depend on the genotype of the interaction partner. In the legume-rhizobium mutualism, one set of potential candidate genes that may influence the fitness benefits of the symbiosis are the plant genes involved in the initiation of the signaling pathway between the two partners. Here we performed quantitative trait loci (QTL) mapping in Medicago truncatula in two different rhizobium strain treatments to locate regions of the genome influencing plant traits, assess whether such regions are dependent on the genotype of the rhizobial mutualist (QTL × rhizobium strain), and evaluate the contribution of sequence variation at known symbiosis signaling genes. Two of the symbiotic signaling genes, NFP and DMI3, colocalized with two QTL affecting average fruit weight and leaf number, suggesting that natural variation in nodulation genes may potentially influence plant fitness. In both rhizobium strain treatments, there were QTL that influenced multiple traits, indicative of either tight linkage between loci or pleiotropy, including one QTL with opposing effects on growth and reproduction. There was no evidence for QTL × rhizobium strain or genotype × genotype interactions, suggesting either that such interactions are due to small-effect loci or that more genotype-genotype combinations need to be tested in future mapping studies.

  11. Genetic Interactions of STAT3 and Anticancer Drug Development

    Directory of Open Access Journals (Sweden)

    Bingliang Fang

    2014-03-01

    Full Text Available Signal transducer and activator of transcription 3 (STAT3 plays critical roles in tumorigenesis and malignant evolution and has been intensively studied as a therapeutic target for cancer. A number of STAT3 inhibitors have been evaluated for their antitumor activity in vitro and in vivo in experimental tumor models and several approved therapeutic agents have been reported to function as STAT3 inhibitors. Nevertheless, most STAT3 inhibitors have yet to be translated to clinical evaluation for cancer treatment, presumably because of pharmacokinetic, efficacy, and safety issues. In fact, a major cause of failure of anticancer drug development is lack of efficacy. Genetic interactions among various cancer-related pathways often provide redundant input from parallel and/or cooperative pathways that drives and maintains survival environments for cancer cells, leading to low efficacy of single-target agents. Exploiting genetic interactions of STAT3 with other cancer-related pathways may provide molecular insight into mechanisms of cancer resistance to pathway-targeted therapies and strategies for development of more effective anticancer agents and treatment regimens. This review focuses on functional regulation of STAT3 activity; possible interactions of the STAT3, RAS, epidermal growth factor receptor, and reduction-oxidation pathways; and molecular mechanisms that modulate therapeutic efficacies of STAT3 inhibitors.

  12. Genetic Interactions of STAT3 and Anticancer Drug Development

    Energy Technology Data Exchange (ETDEWEB)

    Fang, Bingliang [Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030 (United States)

    2014-03-06

    Signal transducer and activator of transcription 3 (STAT3) plays critical roles in tumorigenesis and malignant evolution and has been intensively studied as a therapeutic target for cancer. A number of STAT3 inhibitors have been evaluated for their antitumor activity in vitro and in vivo in experimental tumor models and several approved therapeutic agents have been reported to function as STAT3 inhibitors. Nevertheless, most STAT3 inhibitors have yet to be translated to clinical evaluation for cancer treatment, presumably because of pharmacokinetic, efficacy, and safety issues. In fact, a major cause of failure of anticancer drug development is lack of efficacy. Genetic interactions among various cancer-related pathways often provide redundant input from parallel and/or cooperative pathways that drives and maintains survival environments for cancer cells, leading to low efficacy of single-target agents. Exploiting genetic interactions of STAT3 with other cancer-related pathways may provide molecular insight into mechanisms of cancer resistance to pathway-targeted therapies and strategies for development of more effective anticancer agents and treatment regimens. This review focuses on functional regulation of STAT3 activity; possible interactions of the STAT3, RAS, epidermal growth factor receptor, and reduction-oxidation pathways; and molecular mechanisms that modulate therapeutic efficacies of STAT3 inhibitors.

  13. Quantitative analysis of terahertz spectra for illicit drugs using adaptive-range micro-genetic algorithm

    Science.gov (United States)

    Chen, Yi; Ma, Yong; Lu, Zheng; Peng, Bei; Chen, Qin

    2011-08-01

    In the field of anti-illicit drug applications, many suspicious mixture samples might consist of various drug components—for example, a mixture of methamphetamine, heroin, and amoxicillin—which makes spectral identification very difficult. A terahertz spectroscopic quantitative analysis method using an adaptive range micro-genetic algorithm with a variable internal population (ARVIPɛμGA) has been proposed. Five mixture cases are discussed using ARVIPɛμGA driven quantitative terahertz spectroscopic analysis in this paper. The devised simulation results show agreement with the previous experimental results, which suggested that the proposed technique has potential applications for terahertz spectral identifications of drug mixture components. The results show agreement with the results obtained using other experimental and numerical techniques.

  14. Quantitative estimation of activity and quality for collections of functional genetic elements.

    Science.gov (United States)

    Mutalik, Vivek K; Guimaraes, Joao C; Cambray, Guillaume; Mai, Quynh-Anh; Christoffersen, Marc Juul; Martin, Lance; Yu, Ayumi; Lam, Colin; Rodriguez, Cesar; Bennett, Gaymon; Keasling, Jay D; Endy, Drew; Arkin, Adam P

    2013-04-01

    The practice of engineering biology now depends on the ad hoc reuse of genetic elements whose precise activities vary across changing contexts. Methods are lacking for researchers to affordably coordinate the quantification and analysis of part performance across varied environments, as needed to identify, evaluate and improve problematic part types. We developed an easy-to-use analysis of variance (ANOVA) framework for quantifying the performance of genetic elements. For proof of concept, we assembled and analyzed combinations of prokaryotic transcription and translation initiation elements in Escherichia coli. We determined how estimation of part activity relates to the number of unique element combinations tested, and we show how to estimate expected ensemble-wide part activity from just one or two measurements. We propose a new statistic, biomolecular part 'quality', for tracking quantitative variation in part performance across changing contexts.

  15. Genes and quantitative genetic variation involved with senescence in cells, organs and the whole plant

    Directory of Open Access Journals (Sweden)

    Benoit ePujol

    2015-02-01

    Full Text Available Senescence, the deterioration of morphological, physiological and reproductive functions with age that ends with the death of the organism, was widely studied in plants. Genes were identified that are linked to the deterioration of cells, organs and the whole plant. It is however unclear whether those genes are the source of age dependent deterioration or get activated to regulate such deterioration. Furthermore, it is also unclear whether such genes are active as a direct consequence of age or because they are specifically involved in some developmental stages. At the individual level, it is the relationship between quantitative genetic variation and age that can be used to detect the genetic signature of senescence. Surprisingly, the latter approach was only scarcely applied to plants. This may be the consequence of the demanding requirements for such approaches and/or the fact that most research interest was directed towards plants that avoid senescence. Here, I review those aspects in turn and call for an integrative genetic theory of senescence in plants. Such conceptual development would have implications for the management of plant genetic resources and generate progress on fundamental questions raised by ageing research.

  16. Quantitative genetics of functional characters in Drosophila melanogaster populations subjected to laboratory selection

    Indian Academy of Sciences (India)

    Henrique Teotónio; Margarida Matos; Michael R. Rose

    2004-12-01

    What are the genetics of phenotypes other than fitness, in outbred populations? To answer this question, the quantitative-genetic basis of divergence was characterized for outbred Drosophila melanogaster populations that had previously undergone selection to enhance characters related to fitness. Line-cross analysis using first-generation and second-generation hybrids from reciprocal crosses was conducted for two types of cross, each replicated fivefold. One type of cross was between representatives of the ancestral population, a set of five populations maintained for several hundred generations on a two-week discrete-generation life cycle and a set of five populations adapted to starvation stress. The other type of cross was between the same set of ancestral-representative populations and another set of five populations selected for accelerated development from egg to egg. Developmental time from egg to eclosion, starvation resistance, dry body weight and fecundity at day 14 from egg were fit to regression models estimating single-locus additive and dominant effects, maternal and paternal effects, and digenic additive and dominance epistatic effects. Additive genetic variation explained most of the differences between populations, with additive maternal and cytoplasmic effects also commonly found. Both within-locus and between-locus dominance effects were inferred in some cases, as well as one instance of additive epistasis. Some of these effects may have been caused by linkage disequilibrium. We conclude with a brief discussion concerning the relationship of the genetics of population differentiation to adaptation.

  17. Quantitative Model of microRNA-mRNA interaction

    Science.gov (United States)

    Noorbakhsh, Javad; Lang, Alex; Mehta, Pankaj

    2012-02-01

    MicroRNAs are short RNA sequences that regulate gene expression and protein translation by binding to mRNA. Experimental data reveals the existence of a threshold linear output of protein based on the expression level of microRNA. To understand this behavior, we propose a mathematical model of the chemical kinetics of the interaction between mRNA and microRNA. Using this model we have been able to quantify the threshold linear behavior. Furthermore, we have studied the effect of internal noise, showing the existence of an intermediary regime where the expression level of mRNA and microRNA has the same order of magnitude. In this crossover regime the mRNA translation becomes sensitive to small changes in the level of microRNA, resulting in large fluctuations in protein levels. Our work shows that chemical kinetics parameters can be quantified by studying protein fluctuations. In the future, studying protein levels and their fluctuations can provide a powerful tool to study the competing endogenous RNA hypothesis (ceRNA), in which mRNA crosstalk occurs due to competition over a limited pool of microRNAs.

  18. Genetic interactions between neurofibromin and endothelin receptor B in mice.

    Directory of Open Access Journals (Sweden)

    Mugdha Deo

    Full Text Available When mutations in two different genes produce the same mutant phenotype, it suggests that the encoded proteins either interact with each other, or act in parallel to fulfill a similar purpose. Haploinsufficiency of Neurofibromin and over-expression of Endothelin 3 both cause increased numbers of melanocytes to populate the dermis during mouse development, and thus we are interested in how these two signaling pathways might intersect. Neurofibromin is mutated in the human genetic disease, neurofibromatosis type 1, which is characterized by the development of Schwann cell based tumors and skin hyper-pigmentation. Neurofibromin is a GTPase activating protein, while the Endothelin 3 ligand activates Endothelin receptor B, a G protein coupled receptor. In order to study the genetic interactions between endothelin and neurofibromin, we defined the deletion breakpoints of the classical Ednrb piebald lethal allele (Ednrb(s-l and crossed these mice to mice with a loss-of-function mutation in neurofibromin, Dark skin 9 (Dsk9. We found that Neurofibromin haploinsufficiency requires Endothelin receptor B to darken the tail dermis. In contrast, Neurofibromin haploinsufficiency increases the area of the coat that is pigmented in Endothelin receptor B null mice. We also found an oncogenic mutation in the G protein alpha subunit, GNAQ, which couples to Endothelin receptor B, in a uveal melanoma from a patient with neurofibromatosis type 1. Thus, this data suggests that there is a complex relationship between Neurofibromin and Endothelin receptor B.

  19. Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

    Science.gov (United States)

    Dilworth, David; Nelson, Christopher J.

    2015-01-01

    Determining the mode of action of bioactive chemicals is of interest to a broad range of academic, pharmaceutical, and industrial scientists. Saccharomyces cerevisiae, or budding yeast, is a model eukaryote for which a complete collection of ~6,000 gene deletion mutants and hypomorphic essential gene mutants are commercially available. These collections of mutants can be used to systematically detect chemical-gene interactions, i.e. genes necessary to tolerate a chemical. This information, in turn, reports on the likely mode of action of the compound. Here we describe a protocol for the rapid identification of chemical-genetic interactions in budding yeast. We demonstrate the method using the chemotherapeutic agent 5-fluorouracil (5-FU), which has a well-defined mechanism of action. Our results show that the nuclear TRAMP RNA exosome and DNA repair enzymes are needed for proliferation in the presence of 5-FU, which is consistent with previous microarray based bar-coding chemical genetic approaches and the knowledge that 5-FU adversely affects both RNA and DNA metabolism. The required validation protocols of these high-throughput screens are also described. PMID:25867090

  20. Determination of Mycotoxin Production of Fusarium Species in Genetically Modified Maize Varieties by Quantitative Flow Immunocytometry

    Science.gov (United States)

    Bánáti, Hajnalka; Darvas, Béla; Fehér-Tóth, Szilvia; Czéh, Árpád; Székács, András

    2017-01-01

    Levels of mycotoxins produced by Fusarium species in genetically modified (GM) and near-isogenic maize, were determined using multi-analyte, microbead-based flow immunocytometry with fluorescence detection, for the parallel quantitative determination of fumonisin B1, deoxynivalenol, zearalenone, T-2, ochratoxin A, and aflatoxin B1. Maize varieties included the genetic events MON 810 and DAS-59122-7, and their isogenic counterparts. Cobs were artificially infested by F. verticillioides and F. proliferatum conidia, and contained F. graminearum and F. sporotrichoides natural infestation. The production of fumonisin B1 and deoxynivalenol was substantially affected in GM maize lines: F. verticillioides, with the addition of F. graminearum and F. sporotrichoides, produced significantly lower levels of fumonisin B1 (~300 mg·kg−1) in DAS-59122-7 than in its isogenic line (~580 mg·kg−1), while F. proliferatum, in addition to F. graminearum and F. sporotrichoides, produced significantly higher levels of deoxynivalenol (~18 mg·kg−1) in MON 810 than in its isogenic line (~5 mg·kg−1). Fusarium verticillioides, with F. graminearum and F. sporotrichoides, produced lower amounts of deoxynivalenol and zearalenone than F. proliferatum, with F. graminearum and F. sporotrichoides. T-2 toxin production remained unchanged when considering the maize variety. The results demonstrate the utility of the Fungi-Plex™ quantitative flow immunocytometry method, applied for the high throughput parallel determination of the target mycotoxins. PMID:28241411

  1. The genetic architecture of heterochronsy as a quantitative trait: lessons from a computational model.

    Science.gov (United States)

    Sun, Lidan; Sang, Mengmeng; Zheng, Chenfei; Wang, Dongyang; Shi, Hexin; Liu, Kaiyue; Guo, Yanfang; Cheng, Tangren; Zhang, Qixiang; Wu, Rongling

    2017-05-30

    Heterochrony is known as a developmental change in the timing or rate of ontogenetic events across phylogenetic lineages. It is a key concept synthesizing development into ecology and evolution to explore the mechanisms of how developmental processes impact on phenotypic novelties. A number of molecular experiments using contrasting organisms in developmental timing have identified specific genes involved in heterochronic variation. Beyond these classic approaches that can only identify single genes or pathways, quantitative models derived from current next-generation sequencing data serve as a more powerful tool to precisely capture heterochronic variation and systematically map a complete set of genes that contribute to heterochronic processes. In this opinion note, we discuss a computational framework of genetic mapping that can characterize heterochronic quantitative trait loci that determine the pattern and process of development. We propose a unifying model that charts the genetic architecture of heterochrony that perceives and responds to environmental perturbations and evolves over geologic time. The new model may potentially enhance our understanding of the adaptive value of heterochrony and its evolutionary origins, providing a useful context for designing new organisms that can best use future resources. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  2. FRET-based genetically-encoded sensors for quantitative monitoring of metabolites.

    Science.gov (United States)

    Mohsin, Mohd; Ahmad, Altaf; Iqbal, Muhammad

    2015-10-01

    Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.

  3. Quantitative trait loci mapping of phenotypic plasticity and genotype-environment interactions in plant and insect performance.

    Science.gov (United States)

    Tétard-Jones, C; Kertesz, M A; Preziosi, R F

    2011-05-12

    Community genetic studies generally ignore the plasticity of the functional traits through which the effect is passed from individuals to the associated community. However, the ability of organisms to be phenotypically plastic allows them to rapidly adapt to changing environments and plasticity is commonly observed across all taxa. Owing to the fitness benefits of phenotypic plasticity, evolutionary biologists are interested in its genetic basis, which could explain how phenotypic plasticity is involved in the evolution of species interactions. Two current ideas exist: (i) phenotypic plasticity is caused by environmentally sensitive loci associated with a phenotype; (ii) phenotypic plasticity is caused by regulatory genes that simply influence the plasticity of a phenotype. Here, we designed a quantitative trait loci (QTL) mapping experiment to locate QTL on the barley genome associated with barley performance when the environment varies in the presence of aphids, and the composition of the rhizosphere. We simultaneously mapped aphid performance across variable rhizosphere environments. We mapped main effects, QTL × environment interaction (QTL×E), and phenotypic plasticity (measured as the difference in mean trait values) for barley and aphid performance onto the barley genome using an interval mapping procedure. We found that QTL associated with phenotypic plasticity were co-located with main effect QTL and QTL×E. We also located phenotypic plasticity QTL that were located separately from main effect QTL. These results support both of the current ideas of how phenotypic plasticity is genetically based and provide an initial insight into the functional genetic basis of how phenotypically plastic traits may still be important sources of community genetic effects.

  4. Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling.

    Science.gov (United States)

    Ozer, Abdullah; Tome, Jacob M; Friedman, Robin C; Gheba, Dan; Schroth, Gary P; Lis, John T

    2015-08-01

    Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

  5. Genetic mapping of social interaction behavior in B6/MSM consomic mouse strains.

    Science.gov (United States)

    Takahashi, Aki; Tomihara, Kazuya; Shiroishi, Toshihiko; Koide, Tsuyoshi

    2010-05-01

    Genetic studies are indispensable for understanding the mechanisms by which individuals develop differences in social behavior. We report genetic mapping of social interaction behavior using inter-subspecific consomic strains established from MSM/Ms (MSM) and C57BL/6J (B6) mice. Two animals of the same strain and sex, aged 10 weeks, were introduced into a novel open-field for 10 min. Social contact was detected by an automated system when the distance between the centers of the two animals became less than approximately 12 cm. In addition, detailed behavioral observations were made of the males. The wild-derived mouse strain MSM showed significantly longer social contact as compared to B6. Analysis of the consomic panel identified two chromosomes (Chr 6 and Chr 17) with quantitative trait loci (QTL) responsible for lengthened social contact in MSM mice and two chromosomes (Chr 9 and Chr X) with QTL that inhibited social contact. Detailed behavioral analysis of males identified four additional chromosomes associated with social interaction behavior. B6 mice that contained Chr 13 from MSM showed more genital grooming and following than the parental B6 strain, whereas the presence of Chr 8 and Chr 12 from MSM resulted in a reduction of those behaviors. Longer social sniffing was observed in Chr 4 consomic strain than in B6 mice. Although the frequency was low, aggressive behavior was observed in a few pairs from consomic strains for Chrs 4, 13, 15 and 17, as well as from MSM. The social interaction test has been used as a model to measure anxiety, but genetic correlation analysis suggested that social interaction involves different aspects of anxiety than are measured by open-field test.

  6. Systems genetics of liver fibrosis: identification of fibrogenic and expression quantitative trait loci in the BXD murine reference population.

    Directory of Open Access Journals (Sweden)

    Rabea A Hall

    Full Text Available The progression of liver fibrosis in response to chronic injury varies considerably among individual patients. The underlying genetics is highly complex due to large numbers of potential genes, environmental factors and cell types involved. Here, we provide the first toxicogenomic analysis of liver fibrosis induced by carbon tetrachloride in the murine 'genetic reference panel' of recombinant inbred BXD lines. Our aim was to define the core of risk genes and gene interaction networks that control fibrosis progression. Liver fibrosis phenotypes and gene expression profiles were determined in 35 BXD lines. Quantitative trait locus (QTL analysis identified seven genomic loci influencing fibrosis phenotypes (pQTLs with genome-wide significance on chromosomes 4, 5, 7, 12, and 17. Stepwise refinement was based on expression QTL mapping with stringent selection criteria, reducing the number of 1,351 candidate genes located in the pQTLs to a final list of 11 cis-regulated genes. Our findings demonstrate that the BXD reference population represents a powerful experimental resource for shortlisting the genes within a regulatory network that determine the liver's vulnerability to chronic injury.

  7. Quantitative genetics theory for non-inbred populations in linkage disequilibrium

    Directory of Open Access Journals (Sweden)

    José Marcelo Soriano Viana

    2004-01-01

    Full Text Available Although linkage disequilibrium, epistasis and inbreeding are common phenomena in genetic systems that control quantitative traits, theory development and analysis are very complex, especially when they are considered together. The objective of this study is to offer additional quantitative genetics theory to define and analyze, in relation to non-inbred cross pollinating populations, components of genotypic variance, heritabilities and predicted gains, assuming linkage disequilibrium and absence of epistasis. The genotypic variance and its components, additive and due to dominance genetic variances, are invariant over the generations only in regard to completely linked genes and to those in equilibrium. When the population is structured in half-sib families, the additive variance in the parents' generation and the genotypic variance in the population can be estimated. When the population is structured in full-sib families, none of the components of genotypic variance can be estimated. The narrow sense heritability level at plant level can be estimated from the parent-offspring or mid parent-offspring regression. When there is dominance, the narrow sense heritability estimate in the in F2 is biased due to linkage disequilibrium when estimated by the Warner method, but not when estimated by means of the plant F2-family F3 regression. The bias is proportional to the number of pairs of linked genes, without independent assortment, and to the degree of dominance, and tends to be positive when genes in the coupling phase predominate or negative and of higher value when genes in the repulsion phase predominate. Linkage disequilibrium is also cause of bias in estimates of the narrow sense heritabilities at full-sib family mean and at plant within half-sib and full-sib families levels. Generally, the magnitude of the bias is proportional to the number of pairs of genes in disequilibrium and to the frequency of recombining gametes.

  8. Quantitative resistance against Bemisia tabaci in Solanum pennellii:Genetics and metabolomics

    Institute of Scientific and Technical Information of China (English)

    Alejandro F Lucatti; Sjaak van Heusden; Colette Broekgaarden; Roland Mumm; Marcel Dicke; Ben Vosman

    2016-01-01

    The whitefly Bemisia tabaci is a serious threat in tomato cultivation worldwide as all varieties grown today are highly susceptible to this devastating herbivorous insect. Many accessions of the tomato wild relative Solanum pennellii show a high resistance towards B. tabaci. A mapping approach was used to elucidate the genetic background of whitefly-resistance related traits and associated biochemical traits in this species. Minor quantitative trait loci (QTLs) for whitefly adult survival (AS) and oviposition rate (OR) were identified and some were confirmed in an F2BC1 population, where they showed increased percentages of explained variance (more than 30%). Bulked segregant analyses on pools of whitefly-resistant and-susceptible F2 plants enabled the identification of metabolites that correlate either with resistance or susceptibility. Genetic mapping of these metabolites showed that a large number of them co-localize with whitefly-resistance QTLs. Some of these whitefly-resistance QTLs are hotspots for metabolite QTLs. Although a large number of metabolite QTLs correlated to whitefly resistance or suscepti-bility, most of them are yet unknown compounds and further studies are needed to identify the metabolic pathways and genes involved. The results indicate a direct genetic correla-tion between biochemical-based resistance characteristics and reduced whitefly incidence in S. pennellii.

  9. Pooled-matrix protein interaction screens using Barcode Fusion Genetics.

    Science.gov (United States)

    Yachie, Nozomu; Petsalaki, Evangelia; Mellor, Joseph C; Weile, Jochen; Jacob, Yves; Verby, Marta; Ozturk, Sedide B; Li, Siyang; Cote, Atina G; Mosca, Roberto; Knapp, Jennifer J; Ko, Minjeong; Yu, Analyn; Gebbia, Marinella; Sahni, Nidhi; Yi, Song; Tyagi, Tanya; Sheykhkarimli, Dayag; Roth, Jonathan F; Wong, Cassandra; Musa, Louai; Snider, Jamie; Liu, Yi-Chun; Yu, Haiyuan; Braun, Pascal; Stagljar, Igor; Hao, Tong; Calderwood, Michael A; Pelletier, Laurence; Aloy, Patrick; Hill, David E; Vidal, Marc; Roth, Frederick P

    2016-04-22

    High-throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome-scale interaction mapping. Here, we report Barcode Fusion Genetics-Yeast Two-Hybrid (BFG-Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG-Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein-pair barcodes that can be quantified via next-generation sequencing. We applied BFG-Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG-Y2H increases the efficiency of protein matrix screening, with quality that is on par with state-of-the-art Y2H methods.

  10. Protein complexes predictions within protein interaction networks using genetic algorithms.

    Science.gov (United States)

    Ramadan, Emad; Naef, Ahmed; Ahmed, Moataz

    2016-07-25

    Protein-protein interaction networks are receiving increased attention due to their importance in understanding life at the cellular level. A major challenge in systems biology is to understand the modular structure of such biological networks. Although clustering techniques have been proposed for clustering protein-protein interaction networks, those techniques suffer from some drawbacks. The application of earlier clustering techniques to protein-protein interaction networks in order to predict protein complexes within the networks does not yield good results due to the small-world and power-law properties of these networks. In this paper, we construct a new clustering algorithm for predicting protein complexes through the use of genetic algorithms. We design an objective function for exclusive clustering and overlapping clustering. We assess the quality of our proposed clustering algorithm using two gold-standard data sets. Our algorithm can identify protein complexes that are significantly enriched in the gold-standard data sets. Furthermore, our method surpasses three competing methods: MCL, ClusterOne, and MCODE in terms of the quality of the predicted complexes. The source code and accompanying examples are freely available at http://faculty.kfupm.edu.sa/ics/eramadan/GACluster.zip .

  11. High-resolution profiling of stationary-phase survival reveals yeast longevity factors and their genetic interactions.

    Directory of Open Access Journals (Sweden)

    Erika Garay

    2014-02-01

    Full Text Available Lifespan is influenced by a large number of conserved proteins and gene-regulatory pathways. Here, we introduce a strategy for systematically finding such longevity factors in Saccharomyces cerevisiae and scoring the genetic interactions (epistasis among these factors. Specifically, we developed an automated competition-based assay for chronological lifespan, defined as stationary-phase survival of yeast populations, and used it to phenotype over 5,600 single- or double-gene knockouts at unprecedented quantitative resolution. We found that 14% of the viable yeast mutant strains were affected in their stationary-phase survival; the extent of true-positive chronological lifespan factors was estimated by accounting for the effects of culture aeration and adaptive regrowth. We show that lifespan extension by dietary restriction depends on the Swr1 histone-exchange complex and that a functional link between autophagy and the lipid-homeostasis factor Arv1 has an impact on cellular lifespan. Importantly, we describe the first genetic interaction network based on aging phenotypes, which successfully recapitulated the core-autophagy machinery and confirmed a role of the human tumor suppressor PTEN homologue in yeast lifespan and phosphatidylinositol phosphate metabolism. Our quantitative analysis of longevity factors and their genetic interactions provides insights into the gene-network interactions of aging cells.

  12. High-resolution profiling of stationary-phase survival reveals yeast longevity factors and their genetic interactions.

    Science.gov (United States)

    Garay, Erika; Campos, Sergio E; González de la Cruz, Jorge; Gaspar, Ana P; Jinich, Adrian; Deluna, Alexander

    2014-02-01

    Lifespan is influenced by a large number of conserved proteins and gene-regulatory pathways. Here, we introduce a strategy for systematically finding such longevity factors in Saccharomyces cerevisiae and scoring the genetic interactions (epistasis) among these factors. Specifically, we developed an automated competition-based assay for chronological lifespan, defined as stationary-phase survival of yeast populations, and used it to phenotype over 5,600 single- or double-gene knockouts at unprecedented quantitative resolution. We found that 14% of the viable yeast mutant strains were affected in their stationary-phase survival; the extent of true-positive chronological lifespan factors was estimated by accounting for the effects of culture aeration and adaptive regrowth. We show that lifespan extension by dietary restriction depends on the Swr1 histone-exchange complex and that a functional link between autophagy and the lipid-homeostasis factor Arv1 has an impact on cellular lifespan. Importantly, we describe the first genetic interaction network based on aging phenotypes, which successfully recapitulated the core-autophagy machinery and confirmed a role of the human tumor suppressor PTEN homologue in yeast lifespan and phosphatidylinositol phosphate metabolism. Our quantitative analysis of longevity factors and their genetic interactions provides insights into the gene-network interactions of aging cells.

  13. Impact of measurement error on testing genetic association with quantitative traits.

    Directory of Open Access Journals (Sweden)

    Jiemin Liao

    Full Text Available Measurement error of a phenotypic trait reduces the power to detect genetic associations. We examined the impact of sample size, allele frequency and effect size in presence of measurement error for quantitative traits. The statistical power to detect genetic association with phenotype mean and variability was investigated analytically. The non-centrality parameter for a non-central F distribution was derived and verified using computer simulations. We obtained equivalent formulas for the cost of phenotype measurement error. Effects of differences in measurements were examined in a genome-wide association study (GWAS of two grading scales for cataract and a replication study of genetic variants influencing blood pressure. The mean absolute difference between the analytic power and simulation power for comparison of phenotypic means and variances was less than 0.005, and the absolute difference did not exceed 0.02. To maintain the same power, a one standard deviation (SD in measurement error of a standard normal distributed trait required a one-fold increase in sample size for comparison of means, and a three-fold increase in sample size for comparison of variances. GWAS results revealed almost no overlap in the significant SNPs (p<10(-5 for the two cataract grading scales while replication results in genetic variants of blood pressure displayed no significant differences between averaged blood pressure measurements and single blood pressure measurements. We have developed a framework for researchers to quantify power in the presence of measurement error, which will be applicable to studies of phenotypes in which the measurement is highly variable.

  14. A bivariate quantitative genetic model for a threshold trait and a survival trait

    Directory of Open Access Journals (Sweden)

    Damgaard Lars

    2006-11-01

    Full Text Available Abstract Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.

  15. A bivariate quantitative genetic model for a threshold trait and a survival trait.

    Science.gov (United States)

    Damgaard, Lars Holm; Korsgaard, Inge Riis

    2006-01-01

    Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.

  16. Dissection of Genetic Effects of Quantitative Trait Loci (QTL) in Transgenic Cotton

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yong-shan

    2008-01-01

    @@ When alien DNA inserts into cotton genome in multi-copy manner,several QTL in cotton genome are disrupted,which are called dQTL in this study.Transgenic mutant line is near-isogenic to its recipient which is divergent for the dQTL from remaining QTL.So,a set of data from a transgenic QTL mutant line produced by Agrobacterium-mediated transformation,30074,its recipient,their F1 hybrids between them,and three elite lines were analyzed under a modified additive-dominance model with genotype by environment interactions in three different environments to dissect the genetic effects due to dQTL from the whole genome based genetic effects.

  17. Counting statistics for genetic switches based on effective interaction approximation

    Science.gov (United States)

    Ohkubo, Jun

    2012-09-01

    Applicability of counting statistics for a system with an infinite number of states is investigated. The counting statistics has been studied a lot for a system with a finite number of states. While it is possible to use the scheme in order to count specific transitions in a system with an infinite number of states in principle, we have non-closed equations in general. A simple genetic switch can be described by a master equation with an infinite number of states, and we use the counting statistics in order to count the number of transitions from inactive to active states in the gene. To avoid having the non-closed equations, an effective interaction approximation is employed. As a result, it is shown that the switching problem can be treated as a simple two-state model approximately, which immediately indicates that the switching obeys non-Poisson statistics.

  18. Counting statistics for genetic switches based on effective interaction approximation

    CERN Document Server

    Ohkubo, Jun

    2012-01-01

    Applicability of counting statistics for a system with an infinite number of states is investigated. The counting statistics has been studied a lot for a system with a finite number of states. While it is possible to use the scheme in order to count specific transitions in a system with an infinite number of states in principle, we have non-closed equations in general. A simple genetic switch can be described by a master equation with an infinite number of states, and we use the counting statistics in order to count the number of transitions from inactive to active states in the gene. To avoid to have the non-closed equations, an effective interaction approximation is employed. As a result, it is shown that the switching problem can be treated as a simple two-state model approximately, which immediately indicates that the switching obeys non-Poisson statistics.

  19. Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

    Science.gov (United States)

    Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

    2013-01-01

    Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

  20. The genetics of phenotypic plasticity. XIII. Interactions with developmental instability.

    Science.gov (United States)

    Scheiner, Samuel M

    2014-04-01

    In a heterogeneous environment, natural selection on a trait can lead to a variety of outcomes, including phenotypic plasticity and bet-hedging through developmental instability. These outcomes depend on the magnitude and pattern of that heterogeneity and the spatial and temporal distribution of individuals. However, we do not know if and how those two outcomes might interact with each other. I examined the joint evolution of plasticity and instability through the use of an individual-based simulation in which each could be genetically independent or pleiotropically linked. When plasticity and instability were determined by different loci, the only effect on the evolution of plasticity was the elimination of plasticity as a bet-hedging strategy. In contrast, the effects on the evolution of instability were more substantial. If conditions were such that the population was likely to evolve to the optimal reaction norm, then instability was disfavored. Instability was favored only when the lack of a reliable environmental cue disfavored plasticity. When plasticity and instability were determined by the same loci, instability acted as a strong limitation on the evolution of plasticity. Under some conditions, selection for instability resulted in maladaptive plasticity. Therefore, before testing any models of plasticity or instability evolution, or interpreting empirical patterns, it is important to know the ecological, life history, developmental, and genetic contexts of trait phenotypic plasticity and developmental instability.

  1. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Institute of Scientific and Technical Information of China (English)

    Frank M. You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier

    2016-01-01

    The type 2 modified augmented design (MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters. Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline (http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html).

  2. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Institute of Scientific and Technical Information of China (English)

    Frank M.You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier

    2016-01-01

    The type 2 modified augmented design(MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters.Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline(http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html).

  3. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Directory of Open Access Journals (Sweden)

    Frank M. You

    2016-04-01

    Full Text Available The type 2 modified augmented design (MAD2 is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters. Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline (http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html.

  4. Identification of Quantitative Trait Loci and Water Environmental Interactions for Developmental Behaviors of Leaf greenness in Wheat

    Directory of Open Access Journals (Sweden)

    Delong eYang

    2016-03-01

    Full Text Available The maintenance of leaf greenness in wheat, highly responsible for yield potential and resistance to drought stress, has been proved to be quantitatively inherited and susceptible to interact with environments by traditional genetic analysis. In order to further dissect the developmental genetic behaviors of flag leaf greenness under terminal drought, unconditional and conditional QTL mapping strategies were performed with a mixed linear model in a 120 F8-derived recombinant inbred lines (RILs from two Chinese common wheat cultivars (Longjian 19 × Q9086 in different water environments. A total of 65 additive QTLs (A-QTLs and 42 pairs of epistatic QTLs (AA-QTLs were identified as distribution on almost all 21 chromosomes except 5A, explaining from 0.24 to 3.29 % of the phenotypic variation. Of these, 22 A-QTLs and 25 pairs of AA-QTLs were common in two sets of mapping methods but the others differed. These putative QTLs were essentially characteristic of time- and environmentally-dependent expression patterns. Indeed some loci were expressed at two or more stages, while no single QTL was continually active through whole measuring duration. More loci were detected in early growth periods but most of QTL × water environment interactions (QEIs happened in mid-anaphase, where drought stress was more conducted with negative regulation on QTL expressions. Compared to other genetic components, epistatic effects and additive QEIs effects could be predominant in regulating phenotypic variations during the ontogeny of leaf greenness. Several QTL cluster regions were suggestive of tight linkage or expression pleiotropy in the inheritance of these traits. Some reproducibly-expressed QTLs or common loci consistent with previously detected would be useful to the genetic improvement of staygreen types in wheat through MAS, especially in water-deficit environments.

  5. Genetic programming:  a novel method for the quantitative analysis of pyrolysis mass spectral data.

    Science.gov (United States)

    Gilbert, R J; Goodacre, R; Woodward, A M; Kell, D B

    1997-11-01

    A technique for the analysis of multivariate data by genetic programming (GP) is described, with particular reference to the quantitative analysis of orange juice adulteration data collected by pyrolysis mass spectrometry (PyMS). The dimensionality of the input space was reduced by ranking variables according to product moment correlation or mutual information with the outputs. The GP technique as described gives predictive errors equivalent to, if not better than, more widespread methods such as partial least squares and artificial neural networks but additionally can provide a means for easing the interpretation of the correlation between input and output variables. The described application demonstrates that by using the GP method for analyzing PyMS data the adulteration of orange juice with 10% sucrose solution can be quantified reliably over a 0-20% range with an RMS error in the estimate of ∼1%.

  6. Parameter estimation using the genetic algorithm and its impact on quantitative precipitation forecast

    Directory of Open Access Journals (Sweden)

    Y. H. Lee

    2006-12-01

    Full Text Available In this study, optimal parameter estimations are performed for both physical and computational parameters in a mesoscale meteorological model, and their impacts on the quantitative precipitation forecasting (QPF are assessed for a heavy rainfall case occurred at the Korean Peninsula in June 2005. Experiments are carried out using the PSU/NCAR MM5 model and the genetic algorithm (GA for two parameters: the reduction rate of the convective available potential energy in the Kain-Fritsch (KF scheme for cumulus parameterization, and the Asselin filter parameter for numerical stability. The fitness function is defined based on a QPF skill score. It turns out that each optimized parameter significantly improves the QPF skill. Such improvement is maximized when the two optimized parameters are used simultaneously. Our results indicate that optimizations of computational parameters as well as physical parameters and their adequate applications are essential in improving model performance.

  7. Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk

    DEFF Research Database (Denmark)

    Buitenhuis, Albert Johannes; Sundekilde, Ulrik; Poulsen, Nina Aagaard;

    2013-01-01

    Small components and metabolites in milk are significant for the utilization of milk, not only in dairy food production but also as disease predictors in dairy cattle. This study focused on estimation of genetic parameters and detection of quantitative trait loci for metabolites in bovine milk....... For this purpose, milk samples were collected in mid lactation from 371 Danish Holstein cows in first to third parity. A total of 31 metabolites were detected and identified in bovine milk by using 1H nuclear magnetic resonance (NMR) spectroscopy. Cows were genotyped using a bovine high-density single nucleotide...... polymorphism (SNP) chip. Based on the SNP data, a genomic relationship matrix was calculated and used as a random factor in a model together with 2 fixed factors (herd and lactation stage) to estimate the heritability and breeding value for individual metabolites in the milk. Heritability was in the range of 0...

  8. Partial least squares modeling and genetic algorithm optimization in quantitative structure-activity relationships.

    Science.gov (United States)

    Hasegawa, K; Funatsu, K

    2000-01-01

    Quantitative structure-activity relationship (QSAR) studies based on chemometric techniques are reviewed. Partial least squares (PLS) is introduced as a novel robust method to replace classical methods such as multiple linear regression (MLR). Advantages of PLS compared to MLR are illustrated with typical applications. Genetic algorithm (GA) is a novel optimization technique which can be used as a search engine in variable selection. A novel hybrid approach comprising GA and PLS for variable selection developed in our group (GAPLS) is described. The more advanced method for comparative molecular field analysis (CoMFA) modeling called GA-based region selection (GARGS) is described as well. Applications of GAPLS and GARGS to QSAR and 3D-QSAR problems are shown with some representative examples. GA can be hybridized with nonlinear modeling methods such as artificial neural networks (ANN) for providing useful tools in chemometric and QSAR.

  9. Quantitative Recognizing Dissolved Hydrocarbons with Genetic Algorithm-Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Qu Zhou

    2013-09-01

    Full Text Available Online monitoring of dissolved fault characteristic hydrocarbon gases, such as methane, ethane, ethylene and acetylene in power transformer oil has significant meaning for condition assessment of transformer. Recently, semiconductor tin oxide based gas sensor array has been widely applied in online monitoring apparatus, while cross sensitivity of the gas sensor array is inevitable due to same compositions and similar structures among the four hydrocarbon gases. Based on support vector regression (SVR with genetic algorithm (GA, a new pattern recognition method was proposed to reduce the cross sensitivity of the gas sensor array and further quantitatively recognize the concentration of dissolved hydrocarbon gases. The experimental data from a certain online monitoring device in China is used to illustrate the performance of the proposed GA-SVR model. Experimental results indicate that the GA-SVR method can effectively decrease the cross sensitivity and the regressed data is much more closed to the real values.

  10. Current progress on genetic interactions of rice with rice blast and sheath blight fungi

    Institute of Scientific and Technical Information of China (English)

    Yulin JIA; Guangjie LIU; Stefano COSTANZO; Seonghee LEE; Yuntao DAI

    2009-01-01

    Analysis of genetic interactions between rice and its pathogenic fungi Magnaporthe oryzae and Rhizoctonia solani should lead to a better understanding of molecular mechanisms of host resistance, and the improvement of strategies to manage rice blast and sheath blight diseases. Currently, dozens office resistance (R) genes against specific races of the blast fungus have been described. Among them, ten were molecularly characterized and some were widely used for breeding for genetic resistance. The Pi-ta gene was one of the best characterized rice R genes. Following the elucidation of its molecular structure, interaction, distribution, and evolution, user friendly DNA markers were developed from portions of the cloned genes to facilitate the incorporations of the Pi-ta mediated resistance into improved rice varieties using marker assisted selection (MAS). However, rice blast is still a major threat for stable rice production because of race change mutations occurring in rice fields, which often overcome added resistance based on single R genes, and these virulent races of M. oryzae pose a continued challenge for blast control. For sheath blight, progress has been made on the exploration of novel sources of resistance from wild rice relatives and indica rice cultivars. A major quantitative trait locus (QTL), named qSB9-2, was recently verified in several mapping populations with different phenotyping methods, including greenhouse methods. The ability to identify qSB9-2 using greenhouse methods should accelerate the efforts on the qSB9-2 fine mapping and positional cloning.

  11. Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

    NARCIS (Netherlands)

    Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.; Acha, Moshe Ray; Newton-Cheh, Christopher; Pfeufer, Arne; Lyneh, Stacey N.; Olesen, Soren-Peter; Brunak, Soren; Ellinor, Patrick T.; Jukema, J. Wouter; Trompet, Stella; Ford, Ian; Macfarlane, Peter W.; Krijthe, Bouwe P.; Hofman, Albert; Uitterlinden, Andre G.; Stricker, Bruno H.; Nathoe, Hendrik M.; Spiering, Wilko; Daly, Mark J.; Asselbergs, Ikea W.; van der Harst, Pim; Milan, David J.; de Bakker, Paul I. W.; Lage, Kasper; Olsen, Jesper V.

    2014-01-01

    Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes

  12. Quantitative Trait Locus Analysis of Seed Germination and Seedling Vigor in Brassica rapa Reveals QTL Hotspots and Epistatic Interactions.

    Science.gov (United States)

    Basnet, Ram K; Duwal, Anita; Tiwari, Dev N; Xiao, Dong; Monakhos, Sokrat; Bucher, Johan; Visser, Richard G F; Groot, Steven P C; Bonnema, Guusje; Maliepaard, Chris

    2015-01-01

    The genetic basis of seed germination and seedling vigor is largely unknown in Brassica species. We performed a study to evaluate the genetic basis of these important traits in a B. rapa doubled haploid population from a cross of a yellow-seeded oil-type yellow sarson and a black-seeded vegetable-type pak choi. We identified 26 QTL regions across all 10 linkage groups for traits related to seed weight, seed germination and seedling vigor under non-stress and salt stress conditions illustrating the polygenic nature of these traits. QTLs for multiple traits co-localized and we identified eight hotspots for quantitative trait loci (QTL) of seed weight, seed germination, and root and shoot lengths. A QTL hotspot for seed germination on A02 mapped at the B. rapa Flowering Locus C (BrFLC2). Another hotspot on A05 with salt stress specific QTLs co-located with the B. rapa Fatty acid desaturase 2 (BrFAD2) locus. Epistatic interactions were observed between QTL hotspots for seed germination on A02 and A10 and with a salt tolerance QTL on A05. These results contribute to the understanding of the genetics of seed quality and seeding vigor in B. rapa and can offer tools for Brassica breeding.

  13. Crossover Method for Interactive Genetic Algorithms to Estimate Multimodal Preferences

    Directory of Open Access Journals (Sweden)

    Misato Tanaka

    2013-01-01

    Full Text Available We apply an interactive genetic algorithm (iGA to generate product recommendations. iGAs search for a single optimum point based on a user’s Kansei through the interaction between the user and machine. However, especially in the domain of product recommendations, there may be numerous optimum points. Therefore, the purpose of this study is to develop a new iGA crossover method that concurrently searches for multiple optimum points for multiple user preferences. The proposed method estimates the locations of the optimum area by a clustering method and then searches for the maximum values of the area by a probabilistic model. To confirm the effectiveness of this method, two experiments were performed. In the first experiment, a pseudouser operated an experiment system that implemented the proposed and conventional methods and the solutions obtained were evaluated using a set of pseudomultiple preferences. With this experiment, we proved that when there are multiple preferences, the proposed method searches faster and more diversely than the conventional one. The second experiment was a subjective experiment. This experiment showed that the proposed method was able to search concurrently for more preferences when subjects had multiple preferences.

  14. Quantitative genetic analysis of chlorophyll a fluorescence parameters in maize in the field environments

    Institute of Scientific and Technical Information of China (English)

    Domagojimi; Hrvoje Lepedu; Vlatka Jurkovi; Jasenka Antunovi; Vera Cesar

    2014-01-01

    Chlorophyl fluorescence transient from initial to maximum fluorescence (“P”step) throughout two intermedi-ate steps (“J”and“I”) (JIP-test) is considered a reliable early quantitative indicator of stress in plants. The JIP-test is particularly useful for crop plants when applied in variable field environments. The aim of the present study was to conduct a quantitative trait loci (QTL) analysis for nine JIP-test parameters in maize during flowering in four field environ-ments differing in weather conditions. QTL analysis and identification of putative candidate genes might help to explain the genetic relationship between photosynthesis and different field scenarios in maize plants. The JIP-test param-eters were analyzed in the intermated B73 ? Mo17 (IBM) maize population of 205 recombinant inbred lines. A set of 2,178 molecular markers across the whole maize genome was used for QTL analysis revealing 10 significant QTLs for seven JIP-test parameters, of which five were co-localized when combined over the four environments indicating polygenic inheritance and pleiotropy. Our results demonstrate that QTL analysis of chlorophyl fluorescence parameters was capable of detecting one pleiotropic locus on chromosome 7, coinciding with the gene gst23 that may be associated with efficient photosynthe-sis under different field scenarios.

  15. Genetic heterogeneity, modifier genes, and quantitative phenotypes in psychiatric illness: searching for a framework.

    Science.gov (United States)

    Fanous, A H; Kendler, K S

    2005-01-01

    Schizophrenia has long been thought to be clinically heterogeneous. A range of studies suggests that this is due to genetic heterogeneity. Some clinical features, such as negative symptoms, are associated with a greater risk of illness in relatives. Affected sibling pairs are correlated for clinical and course features as well as subforms of illness, and twin studies suggest that this is due to genetic factors. This is further supported by findings that subjects from families linked to some chromosomal regions may differ clinically from those from unlinked families. Moreover, some genes may affect clinical features without altering susceptibility (ie are modifier genes). High-risk genotypes may have quantitative, rather than categorical effects, and may influence milder or subclinical phenotypes. Another recent finding is that nonpsychotic relatives may have personality features that resemble those of their affected relatives. These findings taken together suggest that there may be several classes of gene action in schizophrenia: some genes may influence susceptibility only, others may influence clinical features only, and still others may have a mixed effect. Furthermore, subsets of these classes may affect personality and other traits in nonpsychotic relatives. Understanding these classes of gene action may help guide the design of linkage and association studies that have increased power. We describe five classes of genes and their predictions of the outcomes of family, twin, and several types of linkage studies. We go on to explore how these predictions can in turn be used to aid in the design of linkage studies.

  16. The Evaluation Criteria of Some Botanical Quantitative Characters of Peach Genetic Resources

    Institute of Scientific and Technical Information of China (English)

    WANG Li-rong; ZHU Geng-rui; FANG Wei-chao

    2006-01-01

    There were two peach descriptors systems: one from IPRGI in 1980 and the other from China in 1990. The former had only reference cultivars without quantity grades; the latter had only a list of some characteristics. This makes it difficult sharing of genetic resource information for breeders. To describe the main quantitative characteristics, a new system was established. Ten characteristics of 346-476 peach cultivars were investigated from 1986 to 2002 in the National Peach Genetic Collection in Zhengzhou City, China. These characteristics and their coefficients of variation were as follows: flower diameter 19.55%, vertical diameter of fruit 14.24%, cheek diameter of fruit 10.36%, suture diameter of fruit 11.44%, stone length 19.04%, stone width 10.86%, stone thickness 11.19%, leaf length 7.9%, leaf width 10.55%, and leaf stalk length 19.03%, respectively. Grade index and reference cultivars were given by statistical data for peach description.These grade indexes were recorded on 1-5 grades, and the third grade as a middle one occupied 39% or more of the distribution. In general, two reference cultivars for each grade were chosen, one is USA cultivar and the other is Chinese cultivar. This paper tried to use them as the reference cultivars, which are planted or used widely by Chinese breeders.

  17. EvolQG - An R package for evolutionary quantitative genetics [version 2; referees: 1 approved, 2 approved with reservations

    Directory of Open Access Journals (Sweden)

    Diogo Melo

    2016-06-01

    Full Text Available We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the EvolQG package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification.

  18. The quantitative genetic basis of adaptive divergence in the moor frog (Rana arvalis) and its implications for gene flow.

    Science.gov (United States)

    Hangartner, S; Laurila, A; Räsänen, K

    2012-08-01

    Knowledge on the relative contribution of direct genetic, maternal and environmental effects to adaptive divergence is important for understanding the drivers of biological diversification. The moor frog (Rana arvalis) shows adaptive divergence in embryonic and larval fitness traits along an acidification gradient in south-western Sweden. To understand the quantitative genetic basis of this divergence, we performed reciprocal crosses between three divergent population pairs and reared embryos and larvae at acid and neutral pH in the laboratory. Divergence in embryonic acid tolerance (survival) was mainly determined by maternal effects, whereas the relative contributions of maternal, additive and nonadditive genetic effects in larval life-history traits differed between traits, population pairs and rearing environments. These results emphasize the need to investigate the quantitative genetic basis of adaptive divergence in multiple populations and traits, as well as different environments. We discuss the implications of our findings for maintenance of local adaptation in the context of migrant and hybrid fitness.

  19. Fine mapping of multiple interacting quantitative trait loci using combined linkage disequilibrium and linkage information

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Quantitative trait loci (QTL) and their additive, dominance and epistatic effects play a critical role in complex trait variation. It is often infeasible to detect multiple interacting QTL due to main effects often being confounded by interaction effects.Positioning interacting QTL within a small region is even more difficult. We present a variance component approach nested in an empirical Bayesian method, which simultaneously takes into account additive, dominance and epistatic effects due to multiple interacting QTL. The covariance structure used in the variance component approach is based on combined linkage disequilibrium and linkage (LDL) information. In a simulation study where there are complex epistatic interactions between QTL, it is possible to simultaneously fine map interacting QTL using the proposed approach. The present method combined with LDL information can efficiently detect QTL and their dominance and epistatic effects, making it possible to simultaneously fine map main and epistatic QTL.

  20. Genetic parameters and mapping quantitative trait loci associated with tibia traits in broilers.

    Science.gov (United States)

    Ragognetti, B N N; Stafuzza, N B; Silva, T B R; Chud, T C S; Grupioni, N V; Cruz, V A R; Peixoto, J O; Nones, K; Ledur, M C; Munari, D P

    2015-12-21

    Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 ± 0.18 (between tibia length and BW42) to 0.89 ± 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

  1. Genetic Studies of Quantitative MCI and AD Phenotypes in ADNI: Progress, Opportunities, and Plans

    Science.gov (United States)

    Saykin, Andrew J.; Shen, Li; Yao, Xiaohui; Kim, Sungeun; Nho, Kwangsik; Risacher, Shannon L.; Ramanan, Vijay K.; Foroud, Tatiana M.; Faber, Kelly M.; Sarwar, Nadeem; Munsie, Leanne M.; Hu, Xiaolan; Soares, Holly D.; Potkin, Steven G.; Thompson, Paul M.; Kauwe, John S.K.; Kaddurah-Daouk, Rima; Green, Robert C.; Toga, Arthur W.; Weiner, Michael W.

    2015-01-01

    INTRODUCTION Genetic data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) has been crucial in advancing the understanding of AD pathophysiology. Here we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. METHODS Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing (WES, WGS) data have been obtained and disseminated. RESULTS ADNI genetic data have been downloaded thousands of times and over 300 publications have resulted, including reports of large scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies employed ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first WES and WGS data sets and reports in healthy controls, MCI, and AD. DISCUSSION Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data, and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multi-omics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological

  2. Quantitative genetic analysis of retinal degeneration in the blind cavefish Astyanax mexicanus.

    Directory of Open Access Journals (Sweden)

    Kelly E O'Quin

    Full Text Available The retina is the light-sensitive tissue of the eye that facilitates vision. Mutations within genes affecting eye development and retinal function cause a host of degenerative visual diseases, including retinitis pigmentosa and anophthalmia/microphthalmia. The characin fish Astyanax mexicanus includes both eyed (surface fish and eyeless (cavefish morphs that initially develop eyes with normal retina; however, early in development, the eyes of cavefish degenerate. Since both surface and cave morphs are members of the same species, they serve as excellent evolutionary mutant models with which to identify genes causing retinal degeneration. In this study, we crossed the eyed and eyeless forms of A. mexicanus and quantified the thickness of individual retinal layers among 115 F(2 hybrid progeny. We used next generation sequencing (RAD-seq and microsatellite mapping to construct a dense genetic map of the Astyanax genome, scan for quantitative trait loci (QTL affecting retinal thickness, and identify candidate genes within these QTL regions. The map we constructed for Astyanax includes nearly 700 markers assembled into 25 linkage groups. Based on our scans with this map, we identified four QTL, one each associated with the thickness of the ganglion, inner nuclear, outer plexiform, and outer nuclear layers of the retina. For all but one QTL, cavefish alleles resulted in a clear reduction in the thickness of the affected layer. Comparative mapping of genetic markers within each QTL revealed that each QTL corresponds to an approximately 35 Mb region of the zebrafish genome. Within each region, we identified several candidate genes associated with the function of each affected retinal layer. Our study is the first to examine Astyanax retinal degeneration in the context of QTL mapping. The regions we identify serve as a starting point for future studies on the genetics of retinal degeneration and eye disease using the evolutionary mutant model Astyanax.

  3. Quantitative structure-interaction relationship analysis of 1,4-dihydropyridine drugs in concomitant administration with grapefruit juice.

    Science.gov (United States)

    Uesawa, Y; Mohri, K

    2012-03-01

    Quantitative structure-interaction relationship (QSIR) analyses of 1,4-dihydropyridine drugs were performed on grapefruit juice interaction potentials to characterize the interaction and evaluate drugs not yet tested in clinical research. AUC ratios of drugs with and without grapefruit juice ingestion were estimated as grapefruit juice interaction potentials from clinical studies on dihydropyridine drugs such as amlodipine, azelnidipine, benidipine, cilnidipine, felodipine, manidipine, nicardipine, nifedipine, nimodipine, nisoldipine, and pranidipine. The minimal energy conformation in each dihydropyridine drug was searched for using Merck Molecular Force Field (MMFFaq), and then geometry optimization was performed by density-functional-theory (DFT) calculation (B3LYP/6-31G**). The geometric, electronic, and physicochemical features including molecular size, dipole moment, total energy, HOMO/LUMO energies, and logP values were then obtained. Dragon descriptors were also calculated by optimized 3D-structures. The relation between the potentials and over 1000 of the molecular properties was investigated using statistical techniques including partial least squares analysis with genetic algorithm (GA-PLS) to a variable subset selection. Some PLS regression equations including logP values and dragon descriptors as explanatory variables were constructed in which the maximal contribution coefficient was 94%. These models could be applied to estimate the interaction potentials of other dihydropyridine drugs that have gone unreported in interactions with drugs such as aranidipine, barnidipine, clevidipine, lemildipine, lercanidipine, niguldipine, niludipine, and nilvadipine. In the assessment of major dihydropyridines, amlodipine was found to be the safest drug to avoid interactions among the drugs investigated in the present study.

  4. Genotype by environment interaction of quantitative traits: a case study in barley.

    Science.gov (United States)

    Zhao, Fuping; Xu, Shizhong

    2012-07-01

    Genotype by environment interaction is a phenomenon that a better genotype in one environment may perform poorly in another environment. When the genotype refers to a quantitative trait locus (QTL), this phenomenon is called QTL by environment interaction, denoted by Q×E. Using a recently developed new Bayesian method and genome-wide marker information, we estimated and tested QTL main effects and Q×E interactions for a well-known barley dataset produced by the North American Barley Genome Mapping Project. This dataset contained seven quantitative traits collected from 145 doubled-haploid (DH) lines evaluated in multiple environments, which derived from a cross between two Canadian two-row barley lines, Harrington and TR306. Numerous main effects and Q×E interaction effects have been detected for all seven quantitative traits. However, main effects seem to be more important than the Q×E interaction effects for all seven traits examined. The number of main effects detected varied from 26 for the maturity trait to 75 for the heading trait, with an average of 61.86. The heading trait has the most detected effects, with a total of 98 (75 main, 29 Q×E). Among the 98 effects, 6 loci had both the main and Q×E effects. Among the total number of detected loci, on average, 78.5% of the loci show the main effects whereas 34.9% of the loci show Q×E interactions. Overall, we detected many loci with either the main or the Q×E effects, and the main effects appear to be more important than the Q×E interaction effects for all the seven traits. This means that most detected loci have a constant effect across environments. Another discovery from this analysis is that Q×E interaction occurs independently, regardless whether the locus has main effects.

  5. Photon-tissue interaction model for quantitative assessment of biological tissues

    Science.gov (United States)

    Lee, Seung Yup; Lloyd, William R.; Wilson, Robert H.; Chandra, Malavika; McKenna, Barbara; Simeone, Diane; Scheiman, James; Mycek, Mary-Ann

    2014-02-01

    In this study, we describe a direct fit photon-tissue interaction model to quantitatively analyze reflectance spectra of biological tissue samples. The model rapidly extracts biologically-relevant parameters associated with tissue optical scattering and absorption. This model was employed to analyze reflectance spectra acquired from freshly excised human pancreatic pre-cancerous tissues (intraductal papillary mucinous neoplasm (IPMN), a common precursor lesion to pancreatic cancer). Compared to previously reported models, the direct fit model improved fit accuracy and speed. Thus, these results suggest that such models could serve as real-time, quantitative tools to characterize biological tissues assessed with reflectance spectroscopy.

  6. A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

    National Research Council Canada - National Science Library

    Vizeacoumar, Franco J; Arnold, Roland; Vizeacoumar, Frederick S; Chandrashekhar, Megha; Buzina, Alla; Young, Jordan T F; Kwan, Julian H M; Sayad, Azin; Mero, Patricia; Lawo, Steffen; Tanaka, Hiromasa; Brown, Kevin R; Baryshnikova, Anastasia; Mak, Anthony B; Fedyshyn, Yaroslav; Wang, Yadong; Brito, Glauber C; Kasimer, Dahlia; Makhnevych, Taras; Ketela, Troy; Datti, Alessandro; Babu, Mohan; Emili, Andrew; Pelletier, Laurence; Wrana, Jeff; Wainberg, Zev; Kim, Philip M; Rottapel, Robert; O‧Brien, Catherine A; Andrews, Brenda; Boone, Charles; Moffat, Jason

    ...‐scale sequencing efforts. Using genome‐scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co...

  7. QTL IciMapping:Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations

    Institute of Scientific and Technical Information of China (English)

    Lei; Meng; Huihui; Li; Luyan; Zhang; Jiankang; Wang

    2015-01-01

    QTL Ici Mapping is freely available public software capable of building high-density linkage maps and mapping quantitative trait loci(QTL) in biparental populations. Eight functionalities are integrated in this software package:(1) BIN: binning of redundant markers;(2) MAP: construction of linkage maps in biparental populations;(3) CMP: consensus map construction from multiple linkage maps sharing common markers;(4) SDL: mapping of segregation distortion loci;(5) BIP: mapping of additive, dominant, and digenic epistasis genes;(6) MET: QTL-by-environment interaction analysis;(7) CSL: mapping of additive and digenic epistasis genes with chromosome segment substitution lines; and(8) NAM: QTL mapping in NAM populations. Input files can be arranged in plain text, MS Excel 2003, or MS Excel 2007 formats. Output files have the same prefix name as the input but with different extensions. As examples, there are two output files in BIN, one for summarizing the identified bin groups and deleted markers in each bin, and the other for using the MAP functionality. Eight output files are generated by MAP, including summary of the completed linkage maps, Mendelian ratio test of individual markers, estimates of recombination frequencies, LOD scores, and genetic distances, and the input files for using the BIP, SDL,and MET functionalities. More than 30 output files are generated by BIP, including results at all scanning positions, identified QTL, permutation tests, and detection powers for up to six mapping methods. Three supplementary tools have also been developed to display completed genetic linkage maps, to estimate recombination frequency between two loci,and to perform analysis of variance for multi-environmental trials.

  8. QTL IciMapping:Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations

    Institute of Scientific and Technical Information of China (English)

    Lei Meng; Huihui Li; Luyan Zhang; Jiankang Wang

    2015-01-01

    QTL IciMapping is freely available public software capable of building high-density linkage maps and mapping quantitative trait loci (QTL) in biparental populations. Eight func-tionalities are integrated in this software package: (1) BIN:binning of redundant markers;(2) MAP: construction of linkage maps in biparental populations; (3) CMP: consensus map construction from multiple linkage maps sharing common markers; (4) SDL: mapping of segregation distortion loci;(5) BIP:mapping of additive, dominant, and digenic epistasis genes;(6) MET:QTL-by-environment interaction analysis;(7) CSL:mapping of additive and digenic epistasis genes with chromosome segment substitution lines; and (8) NAM: QTL mapping in NAM populations. Input files can be arranged in plain text, MS Excel 2003, or MS Excel 2007 formats. Output files have the same prefix name as the input but with different extensions. As examples, there are two output files in BIN, one for summarizing the identified bin groups and deleted markers in each bin, and the other for using the MAP functionality. Eight output files are generated by MAP, including summary of the completed linkage maps, Mendelian ratio test of individual markers, estimates of recombination frequencies, LOD scores, and genetic distances, and the input files for using the BIP, SDL, and MET functionalities. More than 30 output files are generated by BIP, including results at all scanning positions, identified QTL, permutation tests, and detection powers for up to six mapping methods. Three supplementary tools have also been developed to display completed genetic linkage maps, to estimate recombination frequency between two loci, and to perform analysis of variance for multi-environmental trials.

  9. QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations

    Directory of Open Access Journals (Sweden)

    Lei Meng

    2015-06-01

    Full Text Available QTL IciMapping is freely available public software capable of building high-density linkage maps and mapping quantitative trait loci (QTL in biparental populations. Eight functionalities are integrated in this software package: (1 BIN: binning of redundant markers; (2 MAP: construction of linkage maps in biparental populations; (3 CMP: consensus map construction from multiple linkage maps sharing common markers; (4 SDL: mapping of segregation distortion loci; (5 BIP: mapping of additive, dominant, and digenic epistasis genes; (6 MET: QTL-by-environment interaction analysis; (7 CSL: mapping of additive and digenic epistasis genes with chromosome segment substitution lines; and (8 NAM: QTL mapping in NAM populations. Input files can be arranged in plain text, MS Excel 2003, or MS Excel 2007 formats. Output files have the same prefix name as the input but with different extensions. As examples, there are two output files in BIN, one for summarizing the identified bin groups and deleted markers in each bin, and the other for using the MAP functionality. Eight output files are generated by MAP, including summary of the completed linkage maps, Mendelian ratio test of individual markers, estimates of recombination frequencies, LOD scores, and genetic distances, and the input files for using the BIP, SDL, and MET functionalities. More than 30 output files are generated by BIP, including results at all scanning positions, identified QTL, permutation tests, and detection powers for up to six mapping methods. Three supplementary tools have also been developed to display completed genetic linkage maps, to estimate recombination frequency between two loci, and to perform analysis of variance for multi-environmental trials.

  10. Gene interactions and genetics for yield and its attributes in grass pea (Lathyrus sativus L.)

    Indian Academy of Sciences (India)

    A. K. PARIHAR; G. P. DIXIT; DEEPAK SINGH

    2016-12-01

    Grain yield is a complex character representing a multiplicative end product of many yield attributes. However, understanding the genetics and inheritance that underlies yield and its component characters pose a prerequisite to attain the actual yieldpotential of any crop species. The knowledge pertaining to gene actions and interactions is likely to direct and strengthen the crop breeding programmes. With this objective, the present investigation was undertaken by using six generations derived from three different crosses in grass pea. The study underscores the significance of additive–dominance model, gene action involved in inheritance of quantitative characters and heritability. Of note, nonallelic interactions influencing the traits were detected by both scaling test and joint scaling test, indicating the inadequacy of the additive–dominance model alone in explaining the manifestation of complex traits such as yield. Besides, additive (d) and dominance (h) gene effects, different types of interallelic interactions (i, j, l) contributed towards the inheritance of traits in the given crosses. Nevertheless, predominanceof additive variance suggests a difference between homozygotes at a locus with positive and negative alleles being distributed between the parents. Duplicate epistasis was prevalent in most of the cases for traits like plant height, seeds/pod,100-seed weight and pod width. In view of the diverse gene actions, i.e. additive, dominant and epistasis, playing important roles in the manifestation of complex traits like yield, we advocate implementation of population improvement techniques inparticular reciprocal recurrent selection to improve productivity gains in grass pea.

  11. Genetic programming-based approach to elucidate biochemical interaction networks from data.

    Science.gov (United States)

    Kandpal, Manoj; Kalyan, Chakravarthy Mynampati; Samavedham, Lakshminarayanan

    2013-02-01

    Biochemical systems are characterised by cyclic/reversible reciprocal actions, non-linear interactions and a mixed relationship structures (linear and non-linear; static and dynamic). Deciphering the architecture of such systems using measured data to provide quantitative information regarding the nature of relationships that exist between the measured variables is a challenging proposition. Causality detection is one of the methodologies that are applied to elucidate biochemical networks from such data. Autoregressive-based modelling approach such as granger causality, partial directed coherence, directed transfer function and canonical variate analysis have been applied on different systems for deciphering such interactions, but with limited success. In this study, the authors propose a genetic programming-based causality detection (GPCD) methodology which blends evolutionary computation-based procedures along with parameter estimation methods to derive a mathematical model of the system. Application of the GPCD methodology on five data sets that contained the different challenges mentioned above indicated that GPCD performs better than the other methods in uncovering the exact structure with less false positives. On a glycolysis data set, GPCD was able to fill the 'interaction gaps' which were missed by other methods.

  12. Effects of long-term averaging of quantitative blood pressure traits on the detection of genetic associations

    NARCIS (Netherlands)

    S.K. Ganesh (Santhi); D.I. Chasman (Daniel); M.G. Larson (Martin); X. Guo (Xiuqing); G.C. Verwoert (Germaine); J.C. Bis (Joshua); X. Gu (Xiangjun); G.D. Smith; M.-L. Yang (Min-Lee); Y. Zhang (Yan); G.B. Ehret (Georg); L.M. Rose (Lynda); S.J. Hwang; G.J. Papanicolau (George); E.J.G. Sijbrands (Eric); K. Rice (Kenneth); G. Eiriksdottir (Gudny); V. Pihur (Vasyl); P.M. Ridker (Paul); R.S. Vasan (Ramachandran Srini); C. Newton-Cheh (Christopher); L.J. Raffel (Leslie); N. Amin (Najaf); J.I. Rotter (Jerome); K. Liu (Kiang); L.J. Launer (Lenore); M. Xu (Ming); M. Caulfield (Mark); A.C. Morrison (Alanna); A.D. Johnson (Andrew); D. Vaidya (Dhananjay); A. Dehghan (Abbas); G. Li (Guo); C. Bouchard (Claude); T.B. Harris (Tamara); H. Zhang (He); E.A. Boerwinkle (Eric); D.S. Siscovick (David); W. Gao (Wei); A.G. Uitterlinden (André); F. Rivadeneira Ramirez (Fernando); A. Hofman (Albert); E.M. Schmidt (Ellen); O.H. Franco (Oscar); Y. Huo (Yong); J.C.M. Witteman (Jacqueline); P. Munroe (Patricia); V. Gudnason (Vilmundur); W. Palmas (Walter); C.M. van Duijn (Cock); M. Fornage (Myriam); D. Levy (Daniel); B.M. Psaty (Bruce); A. Chakravarti (Aravinda)

    2014-01-01

    textabstractBlood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that ave

  13. Study of quantitative genetics of gum arabic production complicated by variability in ploidy level of Acacia senegal (L.) Willd

    DEFF Research Database (Denmark)

    Diallo, Adja Madjiguene; Nielsen, Lene Rostgaard; Hansen, Jon Kehlet

    2015-01-01

    Gum arabic is an important international commodity produced by trees of Acacia senegal across Sahelian Africa, but documented results of breeding activities are limited. The objective of this study was to provide reliable estimates of quantitative genetic parameters in order to shed light...

  14. Chemical Genetic Dissection of Brassinosteroid-Ethylene Interaction

    Institute of Scientific and Technical Information of China (English)

    Joshua M.Gendron; Asif Haque; Nathan Gendron; Timothy Chang; Tadao Asami; Zhi-Yong Wang

    2008-01-01

    We undertook a chemical genetics screen to identify chemical inhibitors of brassinosteroid (BR) action.From a chemical library of 10,000 small molecules,one compound was found to inhibit hypocotyl length and activate the expression of a BR-repressed reporter gene (CPD::GUS) in Arabidopsis,and it was named brassinopride (BRP).These effects of BRP could be reversed by co-treatment with brassinolide,suggesting that BRP either directly or indirectly inhibits BR biosynthesis.Interestingly,the compound causes exaggerated apical hooks,similar to that caused by ethylene treatment.The BRP-induced apical hook phenotype can be blocked by a chemical inhibitor of ethylene perception or an ethylene-insensitive mutant,suggesting that,in addition to inhibiting BR,BRP activates ethylene response.Analysis of BRP analogs provided clues about structural features important for its effects on two separate targets in the BR and ethylene pathways.Analyses of the responses of various BR and ethylene mutants to BRP,ethylene,and BR treatments revealed modes of cross-talk between ethylene and BR in dark-grown seedlings.Our results suggest that active downstream BR signaling,but not BR synthesis or a BR gradient,is required for ethylene-induced apical hook formation.The BRP-related compounds can be useful tools for manipulating plant growth and studying hormone interactions.

  15. A Creative Helicobacter pylori Diagnosis Scheme Based on Multiple Genetic Analysis System: Qualification and Quantitation.

    Science.gov (United States)

    Zhou, Lifang; Zhao, Fuju; Hu, Binjie; Fang, Yi; Miao, Yingxin; Huang, Yiqin; Ji, Da'nian; Zhang, Jinghao; Xu, Lingli; Zhang, Yanmei; Bao, Zhijun; Zhao, Hu

    2015-10-01

    Currently, several diagnostic assays for Helicobacter pylori (H. pylori) are available, but each has some limitations. Further, a high-flux quantitative assay is required to assist clinical diagnosis and monitor the effectiveness of therapy and novel vaccine candidates. Three hundred and eighty-seven adult patients [nonulcer dyspepsia (NUD) 295, peptic ulcer disease (PUD) 77, gastric cancer (GC) 15] were enrolled for gastrointestinal endoscopies. Three biopsy samples from gastric antrum were collected for the following tests: culture, rapid urease test (RUT), histopathology, conventional polymerase chain reaction (PCR), and Multiple Genetic Analysis System (MGAS). The diagnostic capability of H. pylori for all methods was evaluated through the receiver operating characteristic (ROC) curves. Based on the gold standard, the sensitivity and specificity of MGAS were 92.9 and 92.4%, and positive predict value (PPV) and negative predict value (NPV) were 96.0 and 87.1%, respectively. All the above parameters of MGAS were higher than that of culture (except its specificity), RUT and histopathology, and nearly closed to that of conventional PCR. The area under curve (AUC) was 0.7575 (Culture), 0.8870 (RUT), 0.9000 (Histopathology), 0.9496 (Conventional PCR), and 0.9277 (MGAS). No significant statistical difference was observed for the H. pylori DNA load in different disease groups (p = .067). In contrast, a statistically significant difference in the H. pylori DNA copy number was observed based on age (p = .043) and gender (p = .021). The data showed that MGAS performed well in detecting H. pylori infection. Furthermore, the quantitative analysis showed that the load of H. pylori was significantly different within both age and gender groups. These results suggested that MGAS could be a potential alternative method for clinical detection and monitoring of the effectiveness of H. pylori therapy. © 2015 John Wiley & Sons Ltd.

  16. Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

    Science.gov (United States)

    Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

    2015-11-13

    The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science.

  17. Quantitative genetics approaches to study evolutionary processes in ecotoxicology; a perspective from research on the evolution of resistance.

    Science.gov (United States)

    Klerks, Paul L; Xie, Lingtian; Levinton, Jeffrey S

    2011-05-01

    Quantitative genetic approaches are often used to study evolutionary processes in ecotoxicology. This paper focuses on the evolution of resistance to environmental contaminants-an important evolutionary process in ecotoxicology. Three approaches are commonly employed to study the evolution of resistance: (1) Assessing whether a contaminant-exposed population has an increased resistance relative to a control population, using either spatial or temporal comparisons. (2) Estimating a population's heritability of resistance. (3) Investigating responses in a laboratory selection experiment. All three approaches provide valuable information on the potential for contaminants to affect a population's evolutionary trajectory via natural selection. However, all three approaches have inherent limitations, including difficulty in separating the various genetic and environmental variance components, responses being dependent on specific population and testing conditions, and inability to fully capture natural conditions in the laboratory. In order to maximize insights into the long-term consequences of adaptation, it is important to not just look at resistance itself, but also at the fitness consequences and at correlated responses in characteristics other than resistance. The rapid development of molecular genetics has yielded alternatives to the "black box" approach of quantitative genetics, but the presence of different limitations and strengths in the two fields means that they should be viewed as complementary rather than exchangeable. Quantitative genetics is benefiting from the incorporation of molecular tools and remains an important field for studying evolutionary toxicology.

  18. Genome evolution predicts genetic interactions in protein complexes and reveals cancer drug targets

    NARCIS (Netherlands)

    Lu, X.; Kensche, P.R.; Huynen, M.A.; Notebaart, R.A.

    2013-01-01

    Genetic interactions reveal insights into cellular function and can be used to identify drug targets. Here we construct a new model to predict negative genetic interactions in protein complexes by exploiting the evolutionary history of genes in parallel converging pathways in metabolism. We evaluate

  19. Genetic Risk by Experience Interaction for Childhood Internalizing Problems: Converging Evidence across Multiple Methods

    Science.gov (United States)

    Vendlinski, Matthew K.; Lemery-Chalfant, Kathryn; Essex, Marilyn J.; Goldsmith, H. Hill

    2011-01-01

    Background: Identifying how genetic risk interacts with experience to predict psychopathology is an important step toward understanding the etiology of mental health problems. Few studies have examined genetic risk by experience interaction (GxE) in the development of childhood psychopathology. Methods: We used both co-twin and parent mental…

  20. Genetic Risk by Experience Interaction for Childhood Internalizing Problems: Converging Evidence across Multiple Methods

    Science.gov (United States)

    Vendlinski, Matthew K.; Lemery-Chalfant, Kathryn; Essex, Marilyn J.; Goldsmith, H. Hill

    2011-01-01

    Background: Identifying how genetic risk interacts with experience to predict psychopathology is an important step toward understanding the etiology of mental health problems. Few studies have examined genetic risk by experience interaction (GxE) in the development of childhood psychopathology. Methods: We used both co-twin and parent mental…

  1. Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

    DEFF Research Database (Denmark)

    Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.;

    2014-01-01

    Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes...... involved in the Mendelian disorder long QT syndrome (LOTS). We integrated the LOTS network with GWAS loci from the corresponding common complex trait, QT-interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LOTS protein...... to propose candidates in GWAS loci for functional studies and to systematically filter subtle association signals using tissue-specific quantitative interaction proteomics....

  2. Clarifying CLARITY: Quantitative Optimization of the Diffusion Based Delipidation Protocol for Genetically Labeled Tissue.

    Science.gov (United States)

    Magliaro, Chiara; Callara, Alejandro L; Mattei, Giorgio; Morcinelli, Marco; Viaggi, Cristina; Vaglini, Francesca; Ahluwalia, Arti

    2016-01-01

    Tissue clarification has been recently proposed to allow deep tissue imaging without light scattering. The clarification parameters are somewhat arbitrary and dependent on tissue type, source and dimension: every laboratory has its own protocol, but a quantitative approach to determine the optimum clearing time is still lacking. Since the use of transgenic mouse lines that express fluorescent proteins to visualize specific cell populations is widespread, a quantitative approach to determine the optimum clearing time for genetically labeled neurons from thick murine brain slices using CLARITY2 is described. In particular, as the main objective of the delipidation treatment is to clarify tissues, while limiting loss of fluorescent signal, the "goodness" of clarification was evaluated by considering the bulk tissue clarification index (BTCi) and the fraction of the fluorescent marker retained in the slice as easily quantifiable macroscale parameters. Here we describe the approach, illustrating an example of how it can be used to determine the optimum clearing time for 1 mm-thick cerebellar slice from transgenic L7GFP mice, in which Purkinje neurons express the GFP (green fluorescent protein) tag. To validate the method, we evaluated confocal stacks of our samples using standard image processing indices (i.e., the mean pixel intensity of neurons and the contrast-to-noise ratio) as figures of merit for image quality. The results show that detergent-based delipidation for more than 5 days does not increase tissue clarity but the fraction of GFP in the tissue continues to diminish. The optimum clearing time for 1 mm-thick slices was thus identified as 5 days, which is the best compromise between the increase in light penetration depth due to removal of lipids and a decrease in fluorescent signal as a consequence of protein loss: further clearing does not improve tissue transparency, but only leads to more protein removal or degradation. The rigorous quantitative approach

  3. Quantitative genetic insights into the coevolutionary dynamics of male and female genitalia.

    Science.gov (United States)

    Evans, Jonathan P; van Lieshout, Emile; Gasparini, Clelia

    2013-07-22

    The spectacular variability that typically characterizes male genital traits has largely been attributed to the role of sexual selection. Among the evolutionary mechanisms proposed to account for this diversity, two processes in particular have generated considerable interest. On the one hand, females may exploit postcopulatory mechanisms of selection to favour males with preferred genital traits (cryptic female choice; CFC), while on the other hand females may evolve structures or behaviours that mitigate the direct costs imposed by male genitalia (sexual conflict; SC). A critical but rarely explored assumption underlying both processes is that male and female reproductive traits coevolve, either via the classic Fisherian model of preference-trait coevolution (CFC) or through sexually antagonistic selection (SC). Here, we provide evidence for this prediction in the guppy (Poecilia reticulata), a polyandrous livebearing fish in which males transfer sperm internally to females via consensual and forced matings. Our results from a paternal half-sibling breeding design reveal substantial levels of additive genetic variation underlying male genital size and morphology-two traits known to predict mating success during non-consensual matings. Our subsequent finding that physically interacting female genital traits exhibit corresponding levels of genetic (co)variation reveals the potential intersexual coevolutionary dynamics of male and female genitalia, thereby fulfilling a fundamental assumption underlying CFC and SC theory.

  4. Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

    Directory of Open Access Journals (Sweden)

    Dowling Damian K

    2011-07-01

    Full Text Available Abstract Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass, and each trait harboured significant additive genetic variance in the standard temperature (27°C only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass. Of the female traits measured, only ovary mass for crickets

  5. Dissociative conceptual and quantitative problem solving outcomes across interactive engagement and traditional format introductory physics

    Science.gov (United States)

    McDaniel, Mark A.; Stoen, Siera M.; Frey, Regina F.; Markow, Zachary E.; Hynes, K. Mairin; Zhao, Jiuqing; Cahill, Michael J.

    2016-12-01

    The existing literature indicates that interactive-engagement (IE) based general physics classes improve conceptual learning relative to more traditional lecture-oriented classrooms. Very little research, however, has examined quantitative problem-solving outcomes from IE based relative to traditional lecture-based physics classes. The present study included both pre- and post-course conceptual-learning assessments and a new quantitative physics problem-solving assessment that included three representative conservation of energy problems from a first-semester calculus-based college physics course. Scores for problem translation, plan coherence, solution execution, and evaluation of solution plausibility were extracted for each problem. Over 450 students in three IE-based sections and two traditional lecture sections taught at the same university during the same semester participated. As expected, the IE-based course produced more robust gains on a Force Concept Inventory than did the lecture course. By contrast, when the full sample was considered, gains in quantitative problem solving were significantly greater for lecture than IE-based physics; when students were matched on pre-test scores, there was still no advantage for IE-based physics on gains in quantitative problem solving. Further, the association between performance on the concept inventory and quantitative problem solving was minimal. These results highlight that improved conceptual understanding does not necessarily support improved quantitative physics problem solving, and that the instructional method appears to have less bearing on gains in quantitative problem solving than does the kinds of problems emphasized in the courses and homework and the overlap of these problems to those on the assessment.

  6. Establishment of a quantitative ELISA capable of determining peptide - MHC class I interaction

    DEFF Research Database (Denmark)

    Sylvester-Hvid, C; Kristensen, N; Blicher, T;

    2002-01-01

    Many different assays for measuring peptide-MHC interactions have been suggested over the years. Yet, there is no generally accepted standard method available. We have recently generated preoxidized recombinant MHC class I molecules (MHC-I) which can be purified to homogeneity under denaturing...... dependent manner. Here, we exploit the availability of these molecules to generate a quantitative ELISA-based assay capable of measuring the affinity of the interaction between peptide and MHC-I. This assay is simple and sensitive, and one can easily envisage that the necessary reagents, standards...

  7. Genetic mapping of quantitative trait loci for milk production in sheep.

    Science.gov (United States)

    Mateescu, R G; Thonney, M L

    2010-10-01

    A backcross pedigree using dairy East Friesian rams and non-dairy Dorset ewes was established specifically to map quantitative trait loci (QTL) affecting milk production in sheep. Ninety nine microsatellite markers of an initial set of 120 were successfully genotyped and informative on 188 animals of this backcross pedigree. Test-day milk records on individual ewes were used to estimate several milk yield related traits, including peak milk yield and cumulative milk yield to 50 (MY50), 100 (MY100) and 250 days (MY250). These traits, as well as estimated breeding value of backcross ewes extracted from the genetic evaluation file of the entire flock, were used in interval mapping. Ovine chromosomes 2, 12, 18, 20 and 24 were identified to harbour putative QTL for different measures of milk production. The QTL on Ovis aries chromosomes (OAR) 2 and 20 mapped to locations where similar trait QTL have already been mapped in other studies, whereas QTL on OAR 12, 18 and 24 were unique to our backcross pedigree and have not been reported previously. In addition, all identified QTL regions were syntenic with bovine chromosomal segments revealed to harbour QTL affecting milk production traits, providing supporting evidence for the QTL identified here.

  8. Genetic modifier loci of mouse Mfrp(rd6) identified by quantitative trait locus analysis.

    Science.gov (United States)

    Won, Jungyeon; Charette, Jeremy R; Philip, Vivek M; Stearns, Timothy M; Zhang, Weidong; Naggert, Jürgen K; Krebs, Mark P; Nishina, Patsy M

    2014-01-01

    The identification of genes that modify pathological ocular phenotypes in mouse models may improve our understanding of disease mechanisms and lead to new treatment strategies. Here, we identify modifier loci affecting photoreceptor cell loss in homozygous Mfrp(rd6) mice, which exhibit a slowly progressive photoreceptor degeneration. A cohort of 63 F2 homozygous Mfrp(rd6) mice from a (B6.C3Ga-Mfrp(rd6)/J × CAST/EiJ) F1 intercross exhibited a variable number of cell bodies in the retinal outer nuclear layer at 20 weeks of age. Mice were genotyped with a panel of single nucleotide polymorphism markers, and genotypes were correlated with phenotype by quantitative trait locus (QTL) analysis to map modifier loci. A genome-wide scan revealed a statistically significant, protective candidate locus on CAST/EiJ Chromosome 1 and suggestive modifier loci on Chromosomes 6 and 11. Multiple regression analysis of a three-QTL model indicated that the modifier loci on Chromosomes 1 and 6 together account for 26% of the observed phenotypic variation, while the modifier locus on Chromosome 11 explains only an additional 4%. Our findings indicate that the severity of the Mfrp(rd6) retinal degenerative phenotype in mice depends on the strain genetic background and that a significant modifier locus on CAST/EiJ Chromosome 1 protects against Mfrp(rd6)-associated photoreceptor loss.

  9. The first genetic map of the American cranberry: exploration of synteny conservation and quantitative trait loci.

    Science.gov (United States)

    Georgi, Laura; Johnson-Cicalese, Jennifer; Honig, Josh; Das, Sushma Parankush; Rajah, Veeran D; Bhattacharya, Debashish; Bassil, Nahla; Rowland, Lisa J; Polashock, James; Vorsa, Nicholi

    2013-03-01

    The first genetic map of cranberry (Vaccinium macrocarpon) has been constructed, comprising 14 linkage groups totaling 879.9 cM with an estimated coverage of 82.2 %. This map, based on four mapping populations segregating for field fruit-rot resistance, contains 136 distinct loci. Mapped markers include blueberry-derived simple sequence repeat (SSR) and cranberry-derived sequence-characterized amplified region markers previously used for fingerprinting cranberry cultivars. In addition, SSR markers were developed near cranberry sequences resembling genes involved in flavonoid biosynthesis or defense against necrotrophic pathogens, or conserved orthologous set (COS) sequences. The cranberry SSRs were developed from next-generation cranberry genomic sequence assemblies; thus, the positions of these SSRs on the genomic map provide information about the genomic location of the sequence scaffold from which they were derived. The use of SSR markers near COS and other functional sequences, plus 33 SSR markers from blueberry, facilitates comparisons of this map with maps of other plant species. Regions of the cranberry map were identified that showed conservation of synteny with Vitis vinifera and Arabidopsis thaliana. Positioned on this map are quantitative trait loci (QTL) for field fruit-rot resistance (FFRR), fruit weight, titratable acidity, and sound fruit yield (SFY). The SFY QTL is adjacent to one of the fruit weight QTL and may reflect pleiotropy. Two of the FFRR QTL are in regions of conserved synteny with grape and span defense gene markers, and the third FFRR QTL spans a flavonoid biosynthetic gene.

  10. Quantitative genetics model as the unifying model for defining genomic relationship and inbreeding coefficient.

    Science.gov (United States)

    Wang, Chunkao; Da, Yang

    2014-01-01

    The traditional quantitative genetics model was used as the unifying approach to derive six existing and new definitions of genomic additive and dominance relationships. The theoretical differences of these definitions were in the assumptions of equal SNP effects (equivalent to across-SNP standardization), equal SNP variances (equivalent to within-SNP standardization), and expected or sample SNP additive and dominance variances. The six definitions of genomic additive and dominance relationships on average were consistent with the pedigree relationships, but had individual genomic specificity and large variations not observed from pedigree relationships. These large variations may allow finding least related genomes even within the same family for minimizing genomic relatedness among breeding individuals. The six definitions of genomic relationships generally had similar numerical results in genomic best linear unbiased predictions of additive effects (GBLUP) and similar genomic REML (GREML) estimates of additive heritability. Predicted SNP dominance effects and GREML estimates of dominance heritability were similar within definitions assuming equal SNP effects or within definitions assuming equal SNP variance, but had differences between these two groups of definitions. We proposed a new measure of genomic inbreeding coefficient based on parental genomic co-ancestry coefficient and genomic additive correlation as a genomic approach for predicting offspring inbreeding level. This genomic inbreeding coefficient had the highest correlation with pedigree inbreeding coefficient among the four methods evaluated for calculating genomic inbreeding coefficient in a Holstein sample and a swine sample.

  11. Use of the BioGRID Database for Analysis of Yeast Protein and Genetic Interactions.

    Science.gov (United States)

    Oughtred, Rose; Chatr-aryamontri, Andrew; Breitkreutz, Bobby-Joe; Chang, Christie S; Rust, Jennifer M; Theesfeld, Chandra L; Heinicke, Sven; Breitkreutz, Ashton; Chen, Daici; Hirschman, Jodi; Kolas, Nadine; Livstone, Michael S; Nixon, Julie; O'Donnell, Lara; Ramage, Lindsay; Winter, Andrew; Reguly, Teresa; Sellam, Adnane; Stark, Chris; Boucher, Lorrie; Dolinski, Kara; Tyers, Mike

    2016-01-04

    The BioGRID database is an extensive repository of curated genetic and protein interactions for the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe, and the yeast Candida albicans SC5314, as well as for several other model organisms and humans. This protocol describes how to use the BioGRID website to query genetic or protein interactions for any gene of interest, how to visualize the associated interactions using an embedded interactive network viewer, and how to download data files for either selected interactions or the entire BioGRID interaction data set. © 2016 Cold Spring Harbor Laboratory Press.

  12. Determinants of Neurotransmitters in Cerebrospinal Fluid and Plasma : from Seasonality to Quantitative Genetics

    NARCIS (Netherlands)

    Luykx, J.J.

    2013-01-01

    Most psychiatric conditions are complex genetic as the largest proportion of genetic variance is likely to derive from many genetic variants of small effect. Nonetheless, given the intricacies of the human brain and the heterogeneous nature of psychiatric disease entities, dissecting the genetic mec

  13. Genome-wide association data reveal a global map of genetic interactions among protein complexes.

    Directory of Open Access Journals (Sweden)

    Gregory Hannum

    2009-12-01

    Full Text Available This work demonstrates how gene association studies can be analyzed to map a global landscape of genetic interactions among protein complexes and pathways. Despite the immense potential of gene association studies, they have been challenging to analyze because most traits are complex, involving the combined effect of mutations at many different genes. Due to lack of statistical power, only the strongest single markers are typically identified. Here, we present an integrative approach that greatly increases power through marker clustering and projection of marker interactions within and across protein complexes. Applied to a recent gene association study in yeast, this approach identifies 2,023 genetic interactions which map to 208 functional interactions among protein complexes. We show that such interactions are analogous to interactions derived through reverse genetic screens and that they provide coverage in areas not yet tested by reverse genetic analysis. This work has the potential to transform gene association studies, by elevating the analysis from the level of individual markers to global maps of genetic interactions. As proof of principle, we use synthetic genetic screens to confirm numerous novel genetic interactions for the INO80 chromatin remodeling complex.

  14. Mapping genetic factors controlling potato/cyst nematode interactions.

    NARCIS (Netherlands)

    Rouppe van der Voort, J.N.A.M.

    1998-01-01

    The thesis describes strategies for genetic mapping of the genomes of the potato cyst nematode and potato. Mapping in cyst nematodes was achieved by AFLP genotyping of single cysts and subsequent segregation analysis in a family of sibling populations. The genetic map of Globodera rostochiensis comp

  15. Quantitative assessment of target dependence of pion fluctuation in hadronic interactions – estimation through erraticity

    Indian Academy of Sciences (India)

    Dipak Ghosh; Argha Deb; Mitali Mondal; Arindam Mondal; Sitram Pal

    2012-12-01

    Event-to-event fluctuation pattern of pions produced by proton and pion beams is studied in terms of the newly defined erraticity measures $ (p, q)$, $_{q}^{'}$ and $_{q}^{'}$ proposed by Cao and Hwa. The analysis reveals the erratic behaviour of the produced pions signifying the chaotic multiparticle production in high-energy hadron–nucleus interactions (- –AgBr interactions at 350 GeV/c and –AgBr interactions at 400 GeV/c). However, the chaoticity does not depend on whether the projectile is proton or pion. The results are compared with the results of the VENUS-generated data for the above interactions which suggests that VENUS event generator is unable to reproduce the event-to-event fluctuations of spatial patterns of final states. A comparative study of –AgBr interactions and - collisions at 400 GeV/c from NA27, with the help of a quantitative parameter for the assessment of pion fluctuation, indicates conclusively that particle production process is more chaotic for hadron–nucleus interactions than for hadron–hadron interactions.

  16. Quantitative bioassay to identify antimicrobial drugs through drug interaction fingerprint analysis.

    Science.gov (United States)

    Weinstein, Zohar B; Zaman, Muhammad H

    2017-02-16

    Drug interaction analysis, which reports the extent to which the presence of one drug affects the efficacy of another, is a powerful tool to select potent combinatorial therapies and predict connectivity between cellular components. Combinatorial effects of drug pairs often vary even for drugs with similar mechanism of actions. Therefore, drug interaction fingerprinting may be harnessed to differentiate drug identities. We developed a method to analyze drug interactions for the application of identifying active pharmaceutical ingredients, an essential step to assess drug quality. We developed a novel approach towards the identification of active pharmaceutical ingredients by comparing drug interaction fingerprint similarity metrics such as correlation and Euclidean distance. To expedite this method, we used bioluminescent E. coli in a simplified checkerboard assay to generate unique drug interaction fingerprints of antimicrobial drugs. Of 30 antibiotics studied, 29 could be identified based on their drug interaction fingerprints. We present drug interaction fingerprint analysis as a cheap, sensitive and quantitative method towards substandard and counterfeit drug detection.

  17. Retrospective analysis of main and interaction effects in genetic association studies of human complex traits

    DEFF Research Database (Denmark)

    Tan, Qihua; Christiansen, Lene; Brasch-Andersen, Charlotte;

    2007-01-01

    BACKGROUND: The etiology of multifactorial human diseases involves complex interactions between numerous environmental factors and alleles of many genes. Efficient statistical tools are demanded in identifying the genetic and environmental variants that affect the risk of disease development....... This paper introduces a retrospective polytomous logistic regression model to measure both the main and interaction effects in genetic association studies of human discrete and continuous complex traits. In this model, combinations of genotypes at two interacting loci or of environmental exposure...... regression model can be used as a convenient tool for assessing both main and interaction effects in genetic association studies of human multifactorial diseases involving genetic and non-genetic factors as well as categorical or continuous traits....

  18. Genetic variations and miRNA-target interactions contribute to natural phenotypic variations in Populus.

    Science.gov (United States)

    Chen, Jinhui; Xie, Jianbo; Chen, Beibei; Quan, Mingyang; Li, Ying; Li, Bailian; Zhang, Deqiang

    2016-10-01

    Variation in regulatory factors, including microRNAs (miRNAs), contributes to variation in quantitative and complex traits. However, in plants, variants in miRNAs and their target genes that contribute to natural phenotypic variation, and the underlying regulatory networks, remain poorly characterized. We investigated the associations and interactions of single-nucleotide polymorphisms (SNPs) in miRNAs and their target genes with phenotypes in 435 individuals from a natural population of Populus. We used RNA-seq to identify 217 miRNAs differentially expressed in a tension wood system, and identified 1196 candidate target genes; degradome sequencing confirmed 60 of the target sites. In addition, 72 miRNA-target pairs showed significant co-expression. Gene ontology (GO) term analysis showed that most of the genes in the co-regulated pairs participate in biological regulation. Genome resequencing found 5383 common SNPs (frequency ≥ 0.05) in 139 miRNAs and 31 037 SNPs in 819 target genes. Single-SNP association analyses identified 232 significant associations between wood traits (P ≤ 0.05) and SNPs in 102 miRNAs and 1387 associations with 478 target genes. Among these, 102 miRNA-target pairs associated with the same traits. Multi-SNP associations found 102 epistatic pairs associated with traits. Furthermore, a reconstructed regulatory network contained 12 significantly co-expressed pairs, including eight miRNAs and nine targets associated with traits. Lastly, both expression and genetic association showed that miR156i, miR156j, miR396a and miR6445b were involved in the formation of tension wood. This study shows that variants in miRNAs and target genes contribute to natural phenotypic variation and annotated roles and interactions of miRNAs and their target genes by genetic association analysis. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

  19. Quantitative analysis of protein-protein interactions by split firefly luciferase complementation in plant protoplasts.

    Science.gov (United States)

    Li, Jian-Feng; Zhang, Dandan

    2014-07-01

    This unit describes the split firefly luciferase complementation (SFLC) assay, a high-throughput quantitative method that can be used to investigate protein-protein interactions (PPIs) in plant mesophyll protoplasts. In SFLC, the two proteins to be tested for interaction are expressed as chimeric proteins, each fused to a different half of firefly luciferase. If the proteins interact, a functional luciferase can be transitorily reconstituted, and is detected using the cell-permeable substrate D-luciferin. An advantage of the SFLC assay is that dynamic changes in PPIs in a cell can be detected in a near real-time manner. Another advantage is the unusually high DNA co-transfection and protein expression efficiencies that can be achieved in plant protoplasts, thereby enhancing the throughput of the method.

  20. Effect of dietary phosphorus and its interaction with genetic background on global gene expression in porcine muscle.

    Science.gov (United States)

    Qu, A; Rothschild, M F; Stahl, C H

    2007-08-01

    Environmental concerns and costs associated with dietary phosphorus (P) supplementation have lead to attempts to minimize the amount of P added to swine diets. In addition to its requirement for bone growth, dietary P is also necessary for muscular growth. To examine the effects of genetic background and dietary P on global gene expression in the muscle of young pigs, we utilized muscle tissue from 36 gilts sired from two different sire lines. These animals were fed either a P adequate, P deficient or P repletion diets for 14 days and showed differences in growth performance and bone integrity in response to the interaction of genetic background and dietary P. Total RNA from the loin muscle of these animals was obtained for microarray analysis. Significant differences (p<0.01) in gene expression were seen based on the effect of sire line (339 genes), dietary P (18 genes) and the interaction between sire line and dietary P (31 genes). The microarray data were validated by semi-quantitative real-time PCR. These results support our hypothesis that genetic background and dietary P treatment can affect the homeorhetic control of P metabolism in pigs. Genes identified as differentially expressed in this study may be excellent candidate genes for additional work to elucidate genotype specific P requirements as well as to identify a genetic background that can maintain superior growth in a more environmentally friendly manner.

  1. A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification

    Science.gov (United States)

    Malvezzi, Alex J; Murray, Christopher S; Feldheim, Kevin A; DiBattista, Joseph D; Garant, Dany; Gobler, Christopher J; Chapman, Demian D; Baumann, Hannes

    2015-01-01

    Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (∼2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent–offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection. PMID:25926880

  2. A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification.

    Science.gov (United States)

    Malvezzi, Alex J; Murray, Christopher S; Feldheim, Kevin A; DiBattista, Joseph D; Garant, Dany; Gobler, Christopher J; Chapman, Demian D; Baumann, Hannes

    2015-04-01

    Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (∼2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent-offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection.

  3. A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification

    KAUST Repository

    Malvezzi, Alex J.

    2015-02-01

    Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (~2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent-offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection.

  4. Quantitative evaluation of interaction force between functional groups in protein and polymer brush surfaces.

    Science.gov (United States)

    Sakata, Sho; Inoue, Yuuki; Ishihara, Kazuhiko

    2014-03-18

    To understand interactions between polymer surfaces and different functional groups in proteins, interaction forces were quantitatively evaluated by force-versus-distance curve measurements using atomic force microscopy with a functional-group-functionalized cantilever. Various polymer brush surfaces were systematically prepared by surface-initiated atom transfer radical polymerization as well-defined model surfaces to understand protein adsorption behavior. The polymer brush layers consisted of phosphorylcholine groups (zwitterionic/hydrophilic), trimethylammonium groups (cationic/hydrophilic), sulfonate groups (anionic/hydrophilic), hydroxyl groups (nonionic/hydrophilic), and n-butyl groups (nonionic/hydrophobic) in their side chains. The interaction forces between these polymer brush surfaces and different functional groups (carboxyl groups, amino groups, and methyl groups, which are typical functional groups existing in proteins) were quantitatively evaluated by force-versus-distance curve measurements using atomic force microscopy with a functional-group-functionalized cantilever. Furthermore, the amount of adsorbed protein on the polymer brush surfaces was quantified by surface plasmon resonance using albumin with a negative net charge and lysozyme with a positive net charge under physiological conditions. The amount of proteins adsorbed on the polymer brush surfaces corresponded to the interaction forces generated between the functional groups on the cantilever and the polymer brush surfaces. The weakest interaction force and least amount of protein adsorbed were observed in the case of the polymer brush surface with phosphorylcholine groups in the side chain. On the other hand, positive and negative surfaces generated strong forces against the oppositely charged functional groups. In addition, they showed significant adsorption with albumin and lysozyme, respectively. These results indicated that the interaction force at the functional group level might be

  5. Challenges and prospects in genome-wide quantitative trait loci mapping of standing genetic variation in natural populations.

    Science.gov (United States)

    Schielzeth, Holger; Husby, Arild

    2014-07-01

    A considerable challenge in evolutionary genetics is to understand the genetic mechanisms that facilitate or impede evolutionary adaptation in natural populations. For this, we must understand the genetic loci contributing to trait variation and the selective forces acting on them. The decreased costs and increased feasibility of obtaining genotypic data on a large number of individuals have greatly facilitated gene mapping in natural populations, particularly because organisms whose genetics have been historically difficult to study are now within reach. Here we review the methods available to evolutionary ecologists interested in dissecting the genetic basis of traits in natural populations. Our focus lies on standing genetic variation in outbred populations. We present an overview of the current state of research in the field, covering studies on both plants and animals. We also draw attention to particular challenges associated with the discovery of quantitative trait loci and discuss parallels to studies on crops, livestock, and humans. Finally, we point to some likely future developments in genetic mapping studies.

  6. Establishment of Quantitative Analysis Method for Genetically Modified Maize Using a Reference Plasmid and Novel Primers

    Science.gov (United States)

    Moon, Gi-Seong; Shin, Weon-Sun

    2012-01-01

    For the quantitative analysis of genetically modified (GM) maize in processed foods, primer sets and probes based on the 35S promoter (p35S), nopaline synthase terminator (tNOS), p35S-hsp70 intron, and zSSIIb gene encoding starch synthase II for intrinsic control were designed. Polymerase chain reaction (PCR) products (80~101 bp) were specifically amplified and the primer sets targeting the smaller regions (80 or 81 bp) were more sensitive than those targeting the larger regions (94 or 101 bp). Particularly, the primer set 35F1-R1 for p35S targeting 81 bp of sequence was even more sensitive than that targeting 101 bp of sequence by a 3-log scale. The target DNA fragments were also specifically amplified from all GM labeled food samples except for one item we tested when 35F1-R1 primer set was applied. A reference plasmid pGMmaize (3 kb) including the smaller PCR products for p35S, tNOS, p35S-hsp70 intron, and the zSSIIb gene was constructed for real-time PCR (RT-PCR). The linearity of standard curves was confirmed by using diluents ranging from 2×101~105 copies of pGMmaize and the R2 values ranged from 0.999~1.000. In the RT-PCR, the detection limit using the novel primer/probe sets was 5 pg of genomic DNA from MON810 line indicating that the primer sets targeting the smaller regions (80 or 81 bp) could be used for highly sensitive detection of foreign DNA fragments from GM maize in processed foods. PMID:24471096

  7. Physiologically Based Pharmacokinetic Modeling Framework for Quantitative Prediction of an Herb–Drug Interaction

    Science.gov (United States)

    Brantley, S J; Gufford, B T; Dua, R; Fediuk, D J; Graf, T N; Scarlett, Y V; Frederick, K S; Fisher, M B; Oberlies, N H; Paine, M F

    2014-01-01

    Herb–drug interaction predictions remain challenging. Physiologically based pharmacokinetic (PBPK) modeling was used to improve prediction accuracy of potential herb–drug interactions using the semipurified milk thistle preparation, silibinin, as an exemplar herbal product. Interactions between silibinin constituents and the probe substrates warfarin (CYP2C9) and midazolam (CYP3A) were simulated. A low silibinin dose (160 mg/day × 14 days) was predicted to increase midazolam area under the curve (AUC) by 1%, which was corroborated with external data; a higher dose (1,650 mg/day × 7 days) was predicted to increase midazolam and (S)-warfarin AUC by 5% and 4%, respectively. A proof-of-concept clinical study confirmed minimal interaction between high-dose silibinin and both midazolam and (S)-warfarin (9 and 13% increase in AUC, respectively). Unexpectedly, (R)-warfarin AUC decreased (by 15%), but this is unlikely to be clinically important. Application of this PBPK modeling framework to other herb–drug interactions could facilitate development of guidelines for quantitative prediction of clinically relevant interactions. PMID:24670388

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

    Science.gov (United States)

    Bogdan, Malgorzata; Ghosh, Jayanta K; Doerge, R W

    2004-06-01

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

  9. Engineering genetic circuit interactions within and between synthetic minimal cells

    Science.gov (United States)

    Adamala, Katarzyna P.; Martin-Alarcon, Daniel A.; Guthrie-Honea, Katriona R.; Boyden, Edward S.

    2017-05-01

    Genetic circuits and reaction cascades are of great importance for synthetic biology, biochemistry and bioengineering. An open question is how to maximize the modularity of their design to enable the integration of different reaction networks and to optimize their scalability and flexibility. One option is encapsulation within liposomes, which enables chemical reactions to proceed in well-isolated environments. Here we adapt liposome encapsulation to enable the modular, controlled compartmentalization of genetic circuits and cascades. We demonstrate that it is possible to engineer genetic circuit-containing synthetic minimal cells (synells) to contain multiple-part genetic cascades, and that these cascades can be controlled by external signals as well as inter-liposomal communication without crosstalk. We also show that liposomes that contain different cascades can be fused in a controlled way so that the products of incompatible reactions can be brought together. Synells thus enable a more modular creation of synthetic biology cascades, an essential step towards their ultimate programmability.

  10. Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers

    Science.gov (United States)

    Crossa, José; Campos, Gustavo de los; Pérez, Paulino; Gianola, Daniel; Burgueño, Juan; Araus, José Luis; Makumbi, Dan; Singh, Ravi P.; Dreisigacker, Susanne; Yan, Jianbing; Arief, Vivi; Banziger, Marianne; Braun, Hans-Joachim

    2010-01-01

    The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed. PMID:20813882

  11. Quantitative Trait Locus and Genetical Genomics Analysis Identifies Putatively Causal Genes for Fecundity and Brooding in the Chicken

    Directory of Open Access Journals (Sweden)

    Martin Johnsson

    2016-02-01

    Full Text Available Life history traits such as fecundity are important to evolution because they make up components of lifetime fitness. Due to their polygenic architectures, such traits are difficult to investigate with genetic mapping. Therefore, little is known about their molecular basis. One possible way toward finding the underlying genes is to map intermediary molecular phenotypes, such as gene expression traits. We set out to map candidate quantitative trait genes for egg fecundity in the chicken by combining quantitative trait locus mapping in an advanced intercross of wild by domestic chickens with expression quantitative trait locus mapping in the same birds. We measured individual egg fecundity in 232 intercross chickens in two consecutive trials, the second one aimed at measuring brooding. We found 12 loci for different aspects of egg fecundity. We then combined the genomic confidence intervals of these loci with expression quantitative trait loci from bone and hypothalamus in the same intercross. Overlaps between egg loci and expression loci, and trait–gene expression correlations identify 29 candidates from bone and five from hypothalamus. The candidate quantitative trait genes include fibroblast growth factor 1, and mitochondrial ribosomal proteins L42 and L32. In summary, we found putative quantitative trait genes for egg traits in the chicken that may have been affected by regulatory variants under chicken domestication. These represent, to the best of our knowledge, some of the first candidate genes identified by genome-wide mapping for life history traits in an avian species.

  12. Quantitative Trait Locus and Genetical Genomics Analysis Identifies Putatively Causal Genes for Fecundity and Brooding in the Chicken.

    Science.gov (United States)

    Johnsson, Martin; Jonsson, Kenneth B; Andersson, Leif; Jensen, Per; Wright, Dominic

    2015-12-04

    Life history traits such as fecundity are important to evolution because they make up components of lifetime fitness. Due to their polygenic architectures, such traits are difficult to investigate with genetic mapping. Therefore, little is known about their molecular basis. One possible way toward finding the underlying genes is to map intermediary molecular phenotypes, such as gene expression traits. We set out to map candidate quantitative trait genes for egg fecundity in the chicken by combining quantitative trait locus mapping in an advanced intercross of wild by domestic chickens with expression quantitative trait locus mapping in the same birds. We measured individual egg fecundity in 232 intercross chickens in two consecutive trials, the second one aimed at measuring brooding. We found 12 loci for different aspects of egg fecundity. We then combined the genomic confidence intervals of these loci with expression quantitative trait loci from bone and hypothalamus in the same intercross. Overlaps between egg loci and expression loci, and trait-gene expression correlations identify 29 candidates from bone and five from hypothalamus. The candidate quantitative trait genes include fibroblast growth factor 1, and mitochondrial ribosomal proteins L42 and L32. In summary, we found putative quantitative trait genes for egg traits in the chicken that may have been affected by regulatory variants under chicken domestication. These represent, to the best of our knowledge, some of the first candidate genes identified by genome-wide mapping for life history traits in an avian species.

  13. Peer Observed Interaction and Structured Evaluation (POISE): a Canadian experience with peer supervision for genetic counselors.

    Science.gov (United States)

    Goldsmith, Claire; Honeywell, Christina; Mettler, Gabrielle

    2011-04-01

    Peer observation, while often used in other professions, has not been formally applied in genetic counseling. The objective of this study was to pilot a method of peer evaluation whereby genetic counselors observed, and were observed by, each other during patient interaction. All of the available genetic counselors participated in both rounds of the pilot study (six in round one, seven in round two). The genetic counselors that observed the session used an observation room. Most participants reported learning a new skill. Sensitivity to, and comfort with, the feedback process improved. We conclude that Peer-Observed Interaction and Structured Evaluation (POISE) provides an opportunity to refresh counseling approaches and develop feedback skills without causing undue team discord. This new approach to peer supervision in genetic counselling offers a live observation approach for genetic counsellor supervision.

  14. Quantitative analysis of weak interactions by Lattice energy calculation, Hirshfeld surface and DFT studies of sulfamonomethoxine

    Science.gov (United States)

    Patel, Kinjal D.; Patel, Urmila H.

    2017-01-01

    Sulfamonomethoxine, 4-Amino-N-(6-methoxy-4-pyrimidinyl) benzenesulfonamide (C11H12N4O3S), is investigated by single crystal X-ray diffraction technique. Pair of N-H⋯N and C-H⋯O intermolecular interactions along with π···π interaction are responsible for the stability of the molecular packing of the structure. In order to understand the nature of the interactions and their quantitative contributions towards the crystal packing, the 3D Hirshfeld surface and 2D fingerprint plot analysis are carried out. PIXEL calculations are performed to determine the lattice energies correspond to intermolecular interactions in the crystal structure. Ab initio quantum chemical calculations of sulfamonomethoxine (SMM) have been performed by B3LYP method, using 6-31G** basis set with the help of Schrodinger software. The computed geometrical parameters are in good agreement with the experimental data. The Mulliken charge distribution, calculated using B3LYP method to confirm the presence of electron acceptor and electron donor atoms, responsible for intermolecular hydrogen bond interactions hence the molecular stability.

  15. Calculation of measurement uncertainty in quantitative analysis of genetically modified organisms using intermediate precision--a practical approach.

    Science.gov (United States)

    Zel, Jana; Gruden, Kristina; Cankar, Katarina; Stebih, Dejan; Blejec, Andrej

    2007-01-01

    Quantitative characterization of nucleic acids is becoming a frequently used method in routine analysis of biological samples, one use being the detection of genetically modified organisms (GMOs). Measurement uncertainty is an important factor to be considered in these analyses, especially where precise thresholds are set in regulations. Intermediate precision, defined as a measure between repeatability and reproducibility, is a parameter describing the real situation in laboratories dealing with quantitative aspects of molecular biology methods. In this paper, we describe the top-down approach to calculating measurement uncertainty, using intermediate precision, in routine GMO testing of food and feed samples. We illustrate its practicability in defining compliance of results with regulations. The method described is also applicable to other molecular methods for a variety of laboratory diagnostics where quantitative characterization of nucleic acids is needed.

  16. A molecular-genetic approach to studying source-sink interactions in Arabidopsis thalian. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Gibson, S. I.

    2000-06-01

    This is a final report describing the results of the research funded by the DOE Energy Biosciences Program grant entitled ''A Molecular-Genetic Approach to Studying Source-Sink Interactions in Arabidiopsis thaliana''.

  17. WOMBAT——A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML)

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model;estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses.Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from http://agbu.une.edu.au/~kmeyer/wombat.html

  18. Genetic Vulnerability Interacts with Parenting and Early Care and Education to Predict Increasing Externalizing Behavior

    Science.gov (United States)

    Lipscomb, Shannon T.; Laurent, Heidemarie; Neiderhiser, Jenae M.; Shaw, Daniel S.; Natsuaki, Misaki N.; Reiss, David; Leve, Leslie D.

    2014-01-01

    The current study examined interactions among genetic influences and children's early environments on the development of externalizing behaviors from 18 months to 6 years of age. Participants included 233 families linked through adoption (birth parents and adoptive families). Genetic influences were assessed by birth parent temperamental…

  19. Effects of genotype x environment interaction on genetic gain in breeding programs

    NARCIS (Netherlands)

    Mulder, H.A.; Bijma, P.

    2005-01-01

    Genotype x environment interaction (G x E) is increasingly important, because breeding programs tend to be more internationally oriented. The aim of this theoretical study was to investigate the effects of G x E on genetic gain in sib-testing and progeny-testing schemes. Loss of genetic gain due to

  20. Identification of new genetic susceptibility loci for breast cancer through consideration of gene-environment interactions

    DEFF Research Database (Denmark)

    Schoeps, Anja; Rudolph, Anja; Seibold, Petra

    2014-01-01

    Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,47...

  1. Weak interactions from 1950-1960: a quantitative bibliometric study of the formation of a field

    Energy Technology Data Exchange (ETDEWEB)

    White, D.H.; Sullivan, D.

    1986-01-01

    A quantitative technique is illustrated which uses publication statistics from a bibliography of citations in the area of weak interactions to provide a view of trends and patterns in the development of the field during the period from 1950 to 1960. An overview is given of what the physicists working in weak interactions during this period were doing as indicated by an analysis of the subjects of their papers. The dominant problems and concerns are discussed. Focus is then turned to the events surrounding the emergence of the tau/theta particle puzzle, the discovery of parity nonconservation, and the resolution offered by the V-A theory. Displaying the data from the citation index in unusual ways highlights dominant issues of the period, especially the close relationship between theory and experiment in the latter half of the decade. 64 refs., 14 figs. (LEW)

  2. Quantitative Genetic Analysis for Yield and Yield Components in Boro Rice (Oryza sativa L.

    Directory of Open Access Journals (Sweden)

    Supriyo CHAKRABORTY

    2010-03-01

    Full Text Available Twenty-nine genotypes of boro rice (Oryza sativa L. were grown in a randomized block design with three replications in plots of 4m x 1m with a crop geometry of 20 cm x 20 cm between November-April, in Regional Agricultural Research Station, Nagaon, India. Quantitative data were collected on five randomly selected plants of each genotype per replication for yield/plant, and six other yield components, namely plant height, panicles/plant, panicle length, effective grains/panicle, 100 grain weight and harvest index. Mean values of the characters for each genotype were used for analysis of variance and covariance to obtain information on genotypic and phenotypic correlation along with coheritability between two characters. Path analyses were carried out to estimate the direct and indirect effects of boro rice�s yield components. The objective of the study was to identify the characters that mostly influence the yield for increasing boro rice productivity through breeding program. Correlation analysis revealed significant positive genotypic correlation of yield/plant with plant height (0.21, panicles/plant (0.53, panicle length (0.53, effective grains/panicle (0.57 and harvest index (0.86. Path analysis based on genotypic correlation coefficients elucidated high positive direct effect of harvest index (0.8631, panicle length (0.2560 and 100 grain weight (0.1632 on yield/plant with a residual effect of 0.33. Plant height and panicles/plant recorded high positive indirect effect on yield/plant via harvest index whereas effective grains/panicle on yield/plant via harvest index and panicle length. Results of the present study suggested that five component characters, namely harvest index, effective grains/plant, panicle length, panicles/plant and plant height influenced the yield of boro rice. A genotype with higher magnitude of these component characters could be either selected from the existing genotypes or evolved by breeding program for genetic

  3. Interaction between 5 genetic variants and allergy in glioma risk

    DEFF Research Database (Denmark)

    Schoemaker, Minouk J; Robertson, Lindsay; Wigertz, Annette

    2010-01-01

    The etiology of glioma is barely known. Epidemiologic studies have provided evidence for an inverse relation between glioma risk and allergic disease. Genome-wide association data have identified common genetic variants at 5p15.33 (rs2736100, TERT), 8q24.21 (rs4295627, CCDC26), 9p21.3 (rs4977756...

  4. Diffusion interaction and quantitative analysis of zinc dialkyldithiophosphate content in lube base oils in terahertz regime

    Institute of Scientific and Technical Information of China (English)

    Lu Tian; Kun Zhao; Qingli Zhou; Yulei Shi; Dongmei Zhao; Cunlin Zhang; Songqing Zhao

    2011-01-01

    We investigate the diffusion interaction and quantitative analysis of zinc dialkyldithiophosphate (ZDDP) mixed with lube base oil (LBO) at different concentrations using terahertz time-domain spectroscopy (THz-TDS). When the concentration exceeds 6.78%, the characteristic absorption peaks exhibit significantly shift, and the absorption coefficient peak value is nonlinear against concentration. Moreover, the absorption coefficients of mixed samples follow the Beer's law at a concentration below 6.78%. The quantitative analysis enables a strategy for monitoring the formulation of lubricating oil in real time.%Zinc dialkyldithiophosphate (ZDDP),as a multifunctional additive and inhibitor in petroleum industry,works mainly as antiwear,antioxidant,and anticorrosion agent[1,2].ZDDP mixed with lube base oils (LBOs)has been used to study the effect of concentration on lubrication boundary and tribological properties[3].The concentration of ZDDP in LBOs plays a crucial role in formulation,which is a balance of many different aspects of performance.Lubricating formulation generally results from a molecular diffusion mechanism due to the relative motion of molecules.Molecular diffusion in a steady-state and nonequilibrium system is divided into molecular motion and interaction.Molecular motion,containing the electronic motion,molecular vibration,and molecular rotation,is complicated and multibody.

  5. Genome-wide gene-environment interactions on quantitative traits using family data.

    Science.gov (United States)

    Sitlani, Colleen M; Dupuis, Josée; Rice, Kenneth M; Sun, Fangui; Pitsillides, Achilleas N; Cupples, L Adrienne; Psaty, Bruce M

    2016-07-01

    Gene-environment interactions may provide a mechanism for targeting interventions to those individuals who would gain the most benefit from them. Searching for interactions agnostically on a genome-wide scale requires large sample sizes, often achieved through collaboration among multiple studies in a consortium. Family studies can contribute to consortia, but to do so they must account for correlation within families by using specialized analytic methods. In this paper, we investigate the performance of methods that account for within-family correlation, in the context of gene-environment interactions with binary exposures and quantitative outcomes. We simulate both cross-sectional and longitudinal measurements, and analyze the simulated data taking family structure into account, via generalized estimating equations (GEE) and linear mixed-effects models. With sufficient exposure prevalence and correct model specification, all methods perform well. However, when models are misspecified, mixed modeling approaches have seriously inflated type I error rates. GEE methods with robust variance estimates are less sensitive to model misspecification; however, when exposures are infrequent, GEE methods require modifications to preserve type I error rate. We illustrate the practical use of these methods by evaluating gene-drug interactions on fasting glucose levels in data from the Framingham Heart Study, a cohort that includes related individuals.

  6. Quantitative causal-comparative relationship between interactive whiteboard instruction and student science proficiency

    Science.gov (United States)

    Danelczyk, Ewa Krystyna

    The purpose of this quantitative causal-comparative study was to investigate the relationship between the instructional effects of the interactive whiteboard and students' proficiency levels in eighth-grade science as evidenced by the state FCAT scores. A total of 46 eighth-grade science teachers in a South Florida public school district completed a survey via the Internet. Data were analyzed using descriptive statistics, t tests, Pearson's product moment correlation, and Spearman's rank order correlation. Results revealed a significant difference in mean between eighth-grade students' proficiency percentages reported by participating teachers and the statewide results for the years 2008-2012 (p .05). The significant results were not found between use of the interactive whiteboard for science instruction and students' science proficiency levels as evidenced by FCAT (p > .05), and teachers' professional experience and students' proficiency levels (p > .05). The recommendation from the current study is to continue research pertaining to instructional effectiveness of the interactive whiteboard in relationship to standardized tests because existing findings on similar topics are contradictory. There is a need for more empirical evidence on the long-term impact of the interactive whiteboard on students' achievement in science.

  7. Genetic architecture of zinc hyperaccumulation in Arabidopsis halleri: the essential role of QTL x environment interactions.

    Science.gov (United States)

    Frérot, Hélène; Faucon, Michel-Pierre; Willems, Glenda; Godé, Cécile; Courseaux, Adeline; Darracq, Aude; Verbruggen, Nathalie; Saumitou-Laprade, Pierre

    2010-07-01

    This study sought to determine the main genomic regions that control zinc (Zn) hyperaccumulation in Arabidopsis halleri and to examine genotype x environment effects on phenotypic variance. To do so, quantitative trait loci (QTLs) were mapped using an interspecific A. halleri x Arabidopsis lyrata petraea F(2) population. *The F(2) progeny as well as representatives of the parental populations were cultivated on soils at two different Zn concentrations. A linkage map was constructed using 70 markers. *In both low and high pollution treatments, zinc hyperaccumulation showed high broad-sense heritability (81.9 and 74.7%, respectively). Five significant QTLs were detected: two QTLs specific to the low pollution treatment (chromosomes 1 and 4), and three QTLs identified at both treatments (chromosomes 3, 6 and 7). These QTLs explained 50.1 and 36.5% of the phenotypic variance in low and high pollution treatments, respectively. Two QTLs identified at both treatments (chromosomes 3 and 6) showed significant QTL x environment interactions. *The QTL on chromosome 3 largely colocalized with a major QTL previously identified for Zn and cadmium (Cd) tolerance. This suggests that Zn tolerance and hyperaccumulation share, at least partially, a common genetic basis and may have simultaneously evolved on heavy metal-contaminated soils.

  8. Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes

    NARCIS (Netherlands)

    Pillai, S. G.; Tang, Y.; van den Oord, E.; Klotsman, M.; Barnes, K.; Carlsen, K.; Gerritsen, J.; Lenney, W.; Silverman, M.; Sly, P.; Sundy, J.; Tsanakas, J.; von Berg, A.; Whyte, M.; Ortega, H. G.; Anderson, W. H.; Helms, P. J.

    2008-01-01

    Background Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the

  9. Discovering Pair-Wise Genetic Interactions: An Information Theory-Based Approach

    Science.gov (United States)

    Ignac, Tomasz M.; Skupin, Alexander; Sakhanenko, Nikita A.; Galas, David J.

    2014-01-01

    Phenotypic variation, including that which underlies health and disease in humans, results in part from multiple interactions among both genetic variation and environmental factors. While diseases or phenotypes caused by single gene variants can be identified by established association methods and family-based approaches, complex phenotypic traits resulting from multi-gene interactions remain very difficult to characterize. Here we describe a new method based on information theory, and demonstrate how it improves on previous approaches to identifying genetic interactions, including both synthetic and modifier kinds of interactions. We apply our measure, called interaction distance, to previously analyzed data sets of yeast sporulation efficiency, lipid related mouse data and several human disease models to characterize the method. We show how the interaction distance can reveal novel gene interaction candidates in experimental and simulated data sets, and outperforms other measures in several circumstances. The method also allows us to optimize case/control sample composition for clinical studies. PMID:24670935

  10. Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism.

    Science.gov (United States)

    Corominas, Roser; Yang, Xinping; Lin, Guan Ning; Kang, Shuli; Shen, Yun; Ghamsari, Lila; Broly, Martin; Rodriguez, Maria; Tam, Stanley; Trigg, Shelly A; Fan, Changyu; Yi, Song; Tasan, Murat; Lemmens, Irma; Kuang, Xingyan; Zhao, Nan; Malhotra, Dheeraj; Michaelson, Jacob J; Vacic, Vladimir; Calderwood, Michael A; Roth, Frederick P; Tavernier, Jan; Horvath, Steve; Salehi-Ashtiani, Kourosh; Korkin, Dmitry; Sebat, Jonathan; Hill, David E; Hao, Tong; Vidal, Marc; Iakoucheva, Lilia M

    2014-04-11

    Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.

  11. Uncovering the genetic architecture of Colletotrichum lindemuthianum resistance through QTL mapping and epistatic interaction analysis in common bean

    Directory of Open Access Journals (Sweden)

    Ana M. eGonzález

    2015-03-01

    Full Text Available Colletotrichum lindemuthianum is a hemibiotrophic fungal pathogen that causes anthracnose disease in common bean. Despite the genetics of anthracnose resistance has been studied for a long time, few quantitative trait loci (QTLs studies have been conducted on this species. The present work examines the genetic basis of quantitative resistance to races 23 and 1545 of C. lindemuthianum in different organs (stem, leaf and petiole. A population of 185 recombinant inbred lines (RIL derived from the cross PMB0225 x PHA1037 was evaluated for anthracnose resistance under natural and artificial photoperiod growth conditions. Using multi-environment QTL mapping approach, 10 and 16 main effect QTLs were identified for resistance to anthracnose races 23 and 1545, respectively. The homologous genomic regions corresponding to 17 of the 26 main effect QTLs detected were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL proteins. Among them, it is worth noting that the main effect QTLs detected on linkage group 05 for resistance to race 1545 in stem, petiole and leaf were located within a 1.2 Mb region. The NL gene Phvul.005G117900 is located in this region, which can be considered an important candidate gene for the non-organ-specific QTL identified here. Furthermore, a total of 39 epistatic QTL (E-QTLs (21 for resistance to race 23 and 18 for resistance to race 1545 involved in 20 epistatic interactions (eleven and nine interactions for resistance to races 23 and 1545, respectively were identified. None of the main and epistatic QTLs detected displayed significant environment interaction effects. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for anthracnose resistance improvement in common bean through application of marker-assisted selection (MAS.

  12. Uncovering the genetic architecture of Colletotrichum lindemuthianum resistance through QTL mapping and epistatic interaction analysis in common bean.

    Science.gov (United States)

    González, Ana M; Yuste-Lisbona, Fernando J; Rodiño, A Paula; De Ron, Antonio M; Capel, Carmen; García-Alcázar, Manuel; Lozano, Rafael; Santalla, Marta

    2015-01-01

    Colletotrichum lindemuthianum is a hemibiotrophic fungal pathogen that causes anthracnose disease in common bean. Despite the genetics of anthracnose resistance has been studied for a long time, few quantitative trait loci (QTLs) studies have been conducted on this species. The present work examines the genetic basis of quantitative resistance to races 23 and 1545 of C. lindemuthianum in different organs (stem, leaf and petiole). A population of 185 recombinant inbred lines (RIL) derived from the cross PMB0225 × PHA1037 was evaluated for anthracnose resistance under natural and artificial photoperiod growth conditions. Using multi-environment QTL mapping approach, 10 and 16 main effect QTLs were identified for resistance to anthracnose races 23 and 1545, respectively. The homologous genomic regions corresponding to 17 of the 26 main effect QTLs detected were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins. Among them, it is worth noting that the main effect QTLs detected on linkage group 05 for resistance to race 1545 in stem, petiole and leaf were located within a 1.2 Mb region. The NL gene Phvul.005G117900 is located in this region, which can be considered an important candidate gene for the non-organ-specific QTL identified here. Furthermore, a total of 39 epistatic QTL (E-QTLs) (21 for resistance to race 23 and 18 for resistance to race 1545) involved in 20 epistatic interactions (eleven and nine interactions for resistance to races 23 and 1545, respectively) were identified. None of the main and epistatic QTLs detected displayed significant environment interaction effects. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for anthracnose resistance improvement in common bean through application of marker-assisted selection (MAS).

  13. The genetic variance for multiple linked quantitative trait loci conditional on marker information in a crossed population.

    Science.gov (United States)

    Matsuda, H; Iwaisaki, H

    2002-01-01

    In the prediction of genetic values and quantitative trait loci (QTLs) mapping via the mixed model method incorporating marker information in animal populations, it is important to model the genetic variance for individuals with an arbitrary pedigree structure. In this study, for a crossed population originated from different genetic groups such as breeds or outbred strains, the variance of additive genetic values for multiple linked QTLs that are contained in a chromosome segment, especially the segregation variance, is investigated assuming the use of marker data. The variance for a finite number of QTLs in one chromosomal segment is first examined for the crossed population with the general pedigree. Then, applying the concept of the expectation of identity-by-descent proportion, an approximation to the mean of the conditional probabilities for the linked QTLs over all loci is obtained, and using it an expression for the variance in the case of an infinite number of linked QTLs marked by flanking markers is derived. It appears that the approach presented can be useful in the segment mapping using, and in the genetic evaluation of, crosses with general pedigrees in the population of concern. The calculation of the segregation variance through the current approach is illustrated numerically, using a small data-set.

  14. Genetic Background, Maternal Age, and Interaction Effects Mediate Rates of Crossing Over in Drosophila melanogaster Females.

    Science.gov (United States)

    Hunter, Chad M; Robinson, Matthew C; Aylor, David L; Singh, Nadia D

    2016-05-03

    Meiotic recombination is a genetic process that is critical for proper chromosome segregation in many organisms. Despite being fundamental for organismal fitness, rates of crossing over vary greatly between taxa. Both genetic and environmental factors contribute to phenotypic variation in crossover frequency, as do genotype-environment interactions. Here, we test the hypothesis that maternal age influences rates of crossing over in a genotypic-specific manner. Using classical genetic techniques, we estimated rates of crossing over for individual Drosophila melanogaster females from five strains over their lifetime from a single mating event. We find that both age and genetic background significantly contribute to observed variation in recombination frequency, as do genotype-age interactions. We further find differences in the effect of age on recombination frequency in the two genomic regions surveyed. Our results highlight the complexity of recombination rate variation and reveal a new role of genotype by maternal age interactions in mediating recombination rate.

  15. Genetic Background, Maternal Age, and Interaction Effects Mediate Rates of Crossing Over in Drosophila melanogaster Females

    Directory of Open Access Journals (Sweden)

    Chad M. Hunter

    2016-05-01

    Full Text Available Meiotic recombination is a genetic process that is critical for proper chromosome segregation in many organisms. Despite being fundamental for organismal fitness, rates of crossing over vary greatly between taxa. Both genetic and environmental factors contribute to phenotypic variation in crossover frequency, as do genotype–environment interactions. Here, we test the hypothesis that maternal age influences rates of crossing over in a genotypic-specific manner. Using classical genetic techniques, we estimated rates of crossing over for individual Drosophila melanogaster females from five strains over their lifetime from a single mating event. We find that both age and genetic background significantly contribute to observed variation in recombination frequency, as do genotype–age interactions. We further find differences in the effect of age on recombination frequency in the two genomic regions surveyed. Our results highlight the complexity of recombination rate variation and reveal a new role of genotype by maternal age interactions in mediating recombination rate.

  16. Mouse Social Interaction Test (MoST): a quantitative computer automated analysis of behavior.

    Science.gov (United States)

    Thanos, Panayotis K; Restif, Christophe; O'Rourke, Joseph R; Lam, Chiu Yin; Metaxas, Dimitris

    2017-01-01

    Rodents are the most commonly used preclinical model of human disease assessing the mechanism(s) involved as well as the role of genetics, epigenetics, and pharmacotherapy on this disease as well as identifying vulnerability factors and risk assessment for disease critical in the development of improved treatment strategies. Unfortunately, the majority of rodent preclinical studies utilize single housed approaches where animals are either entirely housed and tested in solitary environments or group housed but tested in solitary environments. This approach, however, ignores the important contribution of social interaction and social behavior. Social interaction in rodents is found to be a major criterion for the ethological validity of rodent species-specific behavioral characteristics (Zurn et al. 2007; Analysis 2011). It is also well established that there is significant and growing number of reports, which illustrates the important role of social environment and social interaction in all diseases, with particularly significance in all neuropsychiatric diseases. Thus, it is imperative that research studies be able to add large-scale evaluations of social interaction and behavior in mice and benefit from automated tracking of behaviors and measurements by removing user bias and by quantifying aspects of behaviors that cannot be assessed by a human observer. Single mouse setups have been used routinely, but cannot be easily extended to multiple-animal studies where social behavior is key, e.g., autism, depression, anxiety, substance and non-substance addictive disorders, aggression, sexual behavior, or parenting. While recent efforts are focusing on multiple-animal tracking alone, a significant limitation remains the lack of insightful measures of social interactions. We present a novel, non-invasive single camera-based automated tracking method described as Mouse Social Test (MoST) and set of measures designed for estimating the interactions of multiple mice at the

  17. Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations

    Directory of Open Access Journals (Sweden)

    José Marcelo Soriano Viana

    2016-06-01

    Full Text Available ABSTRACT To date, the quantitative genetics theory for genomic selection has focused mainly on the relationship between marker and additive variances assuming one marker and one quantitative trait locus (QTL. This study extends the quantitative genetics theory to genomic selection in order to prove that prediction of breeding values based on thousands of single nucleotide polymorphisms (SNPs depends on linkage disequilibrium (LD between markers and QTLs, assuming dominance. We also assessed the efficiency of genomic selection in relation to phenotypic selection, assuming mass selection in an open-pollinated population, all QTLs of lower effect, and reduced sample size, based on simulated data. We show that the average effect of a SNP substitution is proportional to LD measure and to average effect of a gene substitution for each QTL that is in LD with the marker. Weighted (by SNP frequencies and unweighted breeding value predictors have the same accuracy. Efficiency of genomic selection in relation to phenotypic selection is inversely proportional to heritability. Accuracy of breeding value prediction is not affected by the dominance degree and the method of analysis, however, it is influenced by LD extent and magnitude of additive variance. The increase in the number of markers asymptotically improved accuracy of breeding value prediction. The decrease in the sample size from 500 to 200 did not reduce considerably accuracy of breeding value prediction.

  18. Capturing the spectrum of interaction effects in genetic association studies by simulated evaporative cooling network analysis.

    Directory of Open Access Journals (Sweden)

    Brett A McKinney

    2009-03-01

    Full Text Available Evidence from human genetic studies of several disorders suggests that interactions between alleles at multiple genes play an important role in influencing phenotypic expression. Analytical methods for identifying Mendelian disease genes are not appropriate when applied to common multigenic diseases, because such methods investigate association with the phenotype only one genetic locus at a time. New strategies are needed that can capture the spectrum of genetic effects, from Mendelian to multifactorial epistasis. Random Forests (RF and Relief-F are two powerful machine-learning methods that have been studied as filters for genetic case-control data due to their ability to account for the context of alleles at multiple genes when scoring the relevance of individual genetic variants to the phenotype. However, when variants interact strongly, the independence assumption of RF in the tree node-splitting criterion leads to diminished importance scores for relevant variants. Relief-F, on the other hand, was designed to detect strong interactions but is sensitive to large backgrounds of variants that are irrelevant to classification of the phenotype, which is an acute problem in genome-wide association studies. To overcome the weaknesses of these data mining approaches, we develop Evaporative Cooling (EC feature selection, a flexible machine learning method that can integrate multiple importance scores while removing irrelevant genetic variants. To characterize detailed interactions, we construct a genetic-association interaction network (GAIN, whose edges quantify the synergy between variants with respect to the phenotype. We use simulation analysis to show that EC is able to identify a wide range of interaction effects in genetic association data. We apply the EC filter to a smallpox vaccine cohort study of single nucleotide polymorphisms (SNPs and infer a GAIN for a collection of SNPs associated with adverse events. Our results suggest an important

  19. Mapping of the interaction sites of galanthamine: a quantitative analysis through pairwise potentials and quantum chemistry

    Science.gov (United States)

    Galland, Nicolas; Kone, Soleymane; Le Questel, Jean-Yves

    2012-10-01

    A quantitative analysis of the interaction sites of the anti-Alzheimer drug galanthamine with molecular probes (water and benzene molecules) representative of its surroundings in the binding site of acetylcholinesterase (AChE) has been realized through pairwise potentials calculations and quantum chemistry. This strategy allows a full and accurate exploration of the galanthamine potential energy surface of interaction. Significantly different results are obtained according to the distances of approaches between the various molecular fragments and the conformation of the galanthamine N-methyl substituent. The geometry of the most relevant complexes has then been fully optimized through MPWB1K/6-31 + G(d,p) calculations, final energies being recomputed at the LMP2/aug-cc-pVTZ(-f) level of theory. Unexpectedly, galanthamine is found to interact mainly from its hydrogen-bond donor groups. Among those, CH groups in the vicinity of the ammonium group are prominent. The trends obtained provide rationales to the predilection of the equatorial orientation of the galanthamine N-methyl substituent for binding to AChE. The analysis of the interaction energies pointed out the independence between the various interaction sites and the rigid character of galanthamine. The comparison between the cluster calculations and the crystallographic observations in galanthamine-AChE co-crystals allows the validation of the theoretical methodology. In particular, the positions of several water molecules appearing as strongly conserved in galanthamine-AChE co-crystals are predicted by the calculations. Moreover, the experimental position and orientation of lateral chains of functionally important aminoacid residues are in close agreement with the ones predicted theoretically. Our study provides relevant information for a rational drug design of galanthamine based AChE inhibitors.

  20. Mapping of the interaction sites of galanthamine: a quantitative analysis through pairwise potentials and quantum chemistry.

    Science.gov (United States)

    Galland, Nicolas; Kone, Soleymane; Le Questel, Jean-Yves

    2012-10-01

    A quantitative analysis of the interaction sites of the anti-Alzheimer drug galanthamine with molecular probes (water and benzene molecules) representative of its surroundings in the binding site of acetylcholinesterase (AChE) has been realized through pairwise potentials calculations and quantum chemistry. This strategy allows a full and accurate exploration of the galanthamine potential energy surface of interaction. Significantly different results are obtained according to the distances of approaches between the various molecular fragments and the conformation of the galanthamine N-methyl substituent. The geometry of the most relevant complexes has then been fully optimized through MPWB1K/6-31 + G(d,p) calculations, final energies being recomputed at the LMP2/aug-cc-pVTZ(-f) level of theory. Unexpectedly, galanthamine is found to interact mainly from its hydrogen-bond donor groups. Among those, CH groups in the vicinity of the ammonium group are prominent. The trends obtained provide rationales to the predilection of the equatorial orientation of the galanthamine N-methyl substituent for binding to AChE. The analysis of the interaction energies pointed out the independence between the various interaction sites and the rigid character of galanthamine. The comparison between the cluster calculations and the crystallographic observations in galanthamine-AChE co-crystals allows the validation of the theoretical methodology. In particular, the positions of several water molecules appearing as strongly conserved in galanthamine-AChE co-crystals are predicted by the calculations. Moreover, the experimental position and orientation of lateral chains of functionally important aminoacid residues are in close agreement with the ones predicted theoretically. Our study provides relevant information for a rational drug design of galanthamine based AChE inhibitors.

  1. Expression Profiling of Human Genetic and Protein Interaction Networks in Type 1 Diabetes

    DEFF Research Database (Denmark)

    Brunak, Søren; Bergholdt, R; Brorsson, C

    2009-01-01

    Proteins contributing to a complex disease are often members of the same functional pathways. Elucidation of such pathways may provide increased knowledge about functional mechanisms underlying disease. By combining genetic interactions in Type 1 Diabetes (T1D) with protein interaction data we have...

  2. Understanding rice adaptation to varying agro-ecosystems: trait interactions and quantitative trait loci.

    Science.gov (United States)

    Dixit, Shalabh; Grondin, Alexandre; Lee, Cheng-Ruei; Henry, Amelia; Olds, Thomas-Mitchell; Kumar, Arvind

    2015-08-05

    Interaction and genetic control for traits influencing the adaptation of the rice crop to varying environments was studied in a mapping population derived from parents (Moroberekan and Swarna) contrasting for drought tolerance, yield potential, lodging resistance, and adaptation to dry direct seeding. A BC2F3-derived mapping population for traits related to these four trait groups was phenotyped to understand the interactions among traits and to map and align QTLs using composite interval mapping (CIM). The study also aimed to identify QTLs for the four trait groups as composite traits using multivariate least square interval mapping (MLSIM) to further understand the genetic control of these traits. Significant correlations between drought- and yield-related traits at seedling and reproductive stages respectively with traits for adaptation to dry direct-seeded conditions were observed. CIM and MLSIM methods were applied to identify QTLs for univariate and composite traits. QTL clusters showing alignment of QTLs for several traits within and across trait groups were detected at chromosomes 3, 4, and 7 through CIM. The largest number of QTLs related to traits belonging to all four trait groups were identified on chromosome 3 close to the qDTY 3.2 locus. These included QTLs for traits such as bleeding rate, shoot biomass, stem strength, and spikelet fertility. Multivariate QTLs were identified at loci supported by univariate QTLs such as on chromosomes 3 and 4 as well as at distinctly different loci on chromosome 8 which were undetected through CIM. Rice requires better adaptation across a wide range of environments and cultivation practices to adjust to climate change. Understanding the genetics and trade-offs related to each of these environments and cultivation practices thus becomes highly important to develop varieties with stability of yield across them. This study provides a wider picture of the genetics and physiology of adaptation of rice to wide range of

  3. Identification of Cell Cycle Dependent Interaction Partners of the Septins by Quantitative Mass Spectrometry.

    Directory of Open Access Journals (Sweden)

    Christian Renz

    Full Text Available The septins are a conserved family of GTP-binding proteins that, in the baker's yeast, assemble into a highly ordered array of filaments at the mother bud neck. These filaments undergo significant structural rearrangements during the cell cycle. We aimed at identifying key components that are involved in or regulate the transitions of the septins. By combining cell synchronization and quantitative affinity-purification mass-spectrometry, we performed a screen for specific interaction partners of the septins at three distinct stages of the cell cycle. A total of 83 interaction partners of the septins were assigned. Surprisingly, we detected DNA-interacting/nuclear proteins and proteins involved in ribosome biogenesis and protein synthesis predominantly present in alpha-factor arrested that do not display an assembled septin structure. Furthermore, two distinct sets of regulatory proteins that are specific for cells at S-phase with a stable septin collar or at mitosis with split septin rings were identified. Complementary methods like SPLIFF and immunoprecipitation allowed us to more exactly define the spatial and temporal characteristics of selected hits of the AP-MS screen.

  4. Understanding protein–protein interactions by genetic suppression

    Indian Academy of Sciences (India)

    Sitaraman Sujatha; Dipankar Chatterji

    2000-01-01

    Protein–protein interactions influence many cellular processes and it is increasingly being felt that even a weak and remote interplay between two subunits of a protein or between two proteins in a complex may govern the fate of a particular biochemical pathway. In a bacterial system where the complete genome sequence is available, it is an arduous task to assign function to a large number of proteins. It is possible that many of them are peripherally associated with a cellular event and it is very difficult to probe such interaction. However, mutations in the genes that encode such proteins (primary mutations) are useful in these studies. Isolation of a suppressor or a second-site mutation that restores the phenotype abolished by the primary mutation could be an elegant yet simple way to follow a set of interacting proteins. Such a reversion site need not necessarily be geometrically close to the primary mutation site.

  5. Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions*

    Science.gov (United States)

    Shatsky, Maxim; Dong, Ming; Liu, Haichuan; Yang, Lee Lisheng; Choi, Megan; Singer, Mary E.; Geller, Jil T.; Fisher, Susan J.; Hall, Steven C.; Hazen, Terry C.; Brenner, Steven E.; Butland, Gareth; Jin, Jian; Witkowska, H. Ewa; Chandonia, John-Marc; Biggin, Mark D.

    2016-01-01

    Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification of endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR. PMID:27099342

  6. Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

    Energy Technology Data Exchange (ETDEWEB)

    YANG, CHIN-RANG [NHLBI, NIH

    2013-12-11

    Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complement Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.

  7. Genotype X environment interactions. II. Some genetical considerations.

    Science.gov (United States)

    Mather, K

    1975-08-01

    An algebraic formulation, alternative to that of Mather and Jones (1958) and hierarchial rather than factorial in nauture, is presented for describing the differences among the phenotypes produced by a number of genotypes each grown in each of a number of environments. This formuationdoes not include terms representing statistical interactions between genotypes and environments: it depends instead on comparisons between the different genotypes in their variation over the relevant ranges of environemnts. The two-line case is considered ant eht condition established for linearity of the regress ion of genotype X enviroment interaction (g in Mather and Jones' formulation) on overall effect of the envirronment (e in Mather and Jones' formulation)...

  8. Quantitative characterization of biomolecular assemblies and interactions using atomic force microscopy.

    Science.gov (United States)

    Yang, Yong; Wang, Hong; Erie, Dorothy A

    2003-02-01

    Atomic force microscopy (AFM) has been applied in many biological investigations in the past 15 years. This review focuses on the application of AFM for quantitatively characterizing the structural and thermodynamic properties of protein-protein and protein-nucleic acid complexes. AFM can be used to determine the stoichiometries and association constants of multiprotein assemblies and to quantify changes in conformations of proteins and protein-nucleic acid complexes. In addition, AFM in solution permits the observation of the dynamic properties of biomolecular complexes and the measurement of intermolecular forces between biomolecules. Recent advances in cryogenic AFM, AFM on two-dimensional crystals, carbon nanotube probes, solution imaging, high-speed AFM, and manipulation capabilities enhance these applications by improving AFM resolution and the dynamic and operative capabilities of the AFM. These developments make AFM a powerful tool for investigating the biomolecular assemblies and interactions that govern gene regulation.

  9. Formation of chitosan-fucoidan nanoparticles and their electrostatic interactions: Quantitative analysis.

    Science.gov (United States)

    Lee, Eun Ju; Lim, Kwang-Hee

    2016-01-01

    The stoichiometric distributions of both positive amino groups and negative sulfate ions loaded in chitosan-fucoidan nanoparticles (CFNs) were predicted quantitatively by correlating the separate yields of loaded chitosan and fucoidan, and a proposed relative charge density model (case 1). In addition, those distributions of both positive amino groups and negative sulfate ions loaded in CFNs were obtained by deriving the expression of their loaded concentrations directly from the experimental data (case 2). Both the model-prediction and experimental derivations were remarkably consistent with each other except at pH 2. The discrepancy between cases 1 and 2 at pH 2 was explained by an increase in the sulfate group loading because of the most intensive electrostatic (specific ion) interactions at pH 2. The ratio of the CFN-free net charge density shielded by counter-ions in the solution entrapped in CFNs to their counter-ion-crosslinking charge density was suggested to be a quantitative criterion for determining the size distribution of CFNs. The formation of CFNs ranked according to size was predicted well and explained reasonably by the suggested criterion, considering both the ionic strength of the entrapped solution in CFNs and the nonspecific binding (interaction) of the positive amino groups among the chitosan molecules. Furthermore, the fraction of nonspecifically-bound positive amino groups causing hysteresis was quantified from the positive net charged amino groups per unit-mass CFN. Thus, its magnitude was predicted to have a strong correlation with the CFN-preparation conditions, such as pH and fucoidan to chitosan mass ratio.

  10. PCR-free quantitative detection of genetically modified organism from raw materials. An electrochemiluminescence-based bio bar code method.

    Science.gov (United States)

    Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R

    2008-05-15

    A bio bar code assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio bar code assay requires lengthy experimental procedures including the preparation and release of bar code DNA probes from the target-nanoparticle complex and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio bar code assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2,2'-bipyridyl) ruthenium (TBR)-labeled bar code DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products.

  11. Class II HLA interactions modulate genetic risk for multiple sclerosis

    DEFF Research Database (Denmark)

    Moutsianas, Loukas; Jostins, Luke; Beecham, Ashley H;

    2015-01-01

    Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on ...

  12. Study of quantitative genetics of gum arabic production complicated by variability in ploidy level of Acacia senegal (L.) Willd

    DEFF Research Database (Denmark)

    Diallo, Adja Madjiguene; Nielsen, Lene Rostgaard; Hansen, Jon Kehlet;

    2015-01-01

    sibs, while the open-pollinated families of polyploids showed low variation within families. The difference in sibling relationship observed between ploidy levels complicated estimation of genetic parameters. However, based on the diploid trees, we conclude that heritability in gum arabic production......Gum arabic is an important international commodity produced by trees of Acacia senegal across Sahelian Africa, but documented results of breeding activities are limited. The objective of this study was to provide reliable estimates of quantitative genetic parameters in order to shed light...... on the breeding potential for improvement of gum yield and quality. For this purpose, we measured growth on 617 offspring from 60 open-pollinated trees after 18 years, and gum yield and quality based on two seasons, 18 and 19 years after establishment. Genotyping with eight microsatellite markers revealed...

  13. Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites

    KAUST Repository

    Abkallo, Hussein M.

    2016-10-01

    Identifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.

  14. High-Density Genetic Linkage Map Construction and Quantitative Trait Locus Mapping for Hawthorn (Crataegus pinnatifida Bunge).

    Science.gov (United States)

    Zhao, Yuhui; Su, Kai; Wang, Gang; Zhang, Liping; Zhang, Jijun; Li, Junpeng; Guo, Yinshan

    2017-07-14

    Genetic linkage maps are an important tool in genetic and genomic research. In this study, two hawthorn cultivars, Qiujinxing and Damianqiu, and 107 progenies from a cross between them were used for constructing a high-density genetic linkage map using the 2b-restriction site-associated DNA (2b-RAD) sequencing method, as well as for mapping quantitative trait loci (QTL) for flavonoid content. In total, 206,411,693 single-end reads were obtained, with an average sequencing depth of 57× in the parents and 23× in the progeny. After quality trimming, 117,896 high-quality 2b-RAD tags were retained, of which 42,279 were polymorphic; of these, 12,951 markers were used for constructing the genetic linkage map. The map contained 17 linkage groups and 3,894 markers, with a total map length of 1,551.97 cM and an average marker interval of 0.40 cM. QTL mapping identified 21 QTLs associated with flavonoid content in 10 linkage groups, which explained 16.30-59.00% of the variance. This is the first high-density linkage map for hawthorn, which will serve as a basis for fine-scale QTL mapping and marker-assisted selection of important traits in hawthorn germplasm and will facilitate chromosome assignment for hawthorn whole-genome assemblies in the future.

  15. Quantitative genetic analysis indicates natural selection on leaf phenotypes across wild tomato species (Solanum sect. Lycopersicon; Solanaceae).

    Science.gov (United States)

    Muir, Christopher D; Pease, James B; Moyle, Leonie C

    2014-12-01

    Adaptive evolution requires both raw genetic material and an accessible path of high fitness from one fitness peak to another. In this study, we used an introgression line (IL) population to map quantitative trait loci (QTL) for leaf traits thought to be associated with adaptation to precipitation in wild tomatoes (Solanum sect. Lycopersicon; Solanaceae). A QTL sign test showed that several traits likely evolved under directional natural selection. Leaf traits correlated across species do not share a common genetic basis, consistent with a scenario in which selection maintains trait covariation unconstrained by pleiotropy or linkage disequilibrium. Two large effect QTL for stomatal distribution colocalized with key genes in the stomatal development pathway, suggesting promising candidates for the molecular bases of adaptation in these species. Furthermore, macroevolutionary transitions between vastly different stomatal distributions may not be constrained when such large-effect mutations are available. Finally, genetic correlations between stomatal traits measured in this study and data on carbon isotope discrimination from the same ILs support a functional hypothesis that the distribution of stomata affects the resistance to CO2 diffusion inside the leaf, a trait implicated in climatic adaptation in wild tomatoes. Along with evidence from previous comparative and experimental studies, this analysis indicates that leaf traits are an important component of climatic niche adaptation in wild tomatoes and demonstrates that some trait transitions between species could have involved few, large-effect genetic changes, allowing rapid responses to new environmental conditions.

  16. [Genetic and environmental interactions on the development of rheumatoid arthritis].

    Science.gov (United States)

    Malaise, O; von Frenckell, C; Malaise, M G

    2012-01-01

    Rheumatoid arthritis (RA) more and more becomes a syndrome, rather than a disease, with genetic, hormonal and environmental influences, among which smoking and the microbiota generate focused interest. The shared epitope and PTPN22 loci are associated with RA, and, particularly, with the "classical" form with anti-citrullinated peptide antibodies (ACPA) and IgM-rheumatoid factor (IgM-RF) positivity. Pregnancy is associated with a--temporary--remission of RA. Epidemiological studies have shown that oral contraception, parity and hormonal replacement therapy influence the severity of RA, and, this is still discussed, its incidence. Smoking is the first environmental factor strongly associated with RA, specifically with the shared epitope and with ACPA. The study of the microbiota is a novel emerging field that will help us to better understand patterns and evolution of RA.

  17. The genetic basis of adaptive population differentiation: A quantitative trait locus analysis of fitness traits in two wild barley populations from contrasting habitats

    NARCIS (Netherlands)

    Verhoeven, K.J.F.; Vanhala, T.K.; Biere, A.; Nevo, E.; Damme, van J.M.M.

    2004-01-01

    We used a quantitative trait locus (QTL) approach to study the genetic basis of population differentiation in wild barley, Hordeum spontaneum. Several ecotypes are recognized in this model species, and population genetic studies and reciprocal transplant experiments have indicated the role of local

  18. Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in "Brassica rapa" Fast Plants

    Science.gov (United States)

    Batzli, Janet M.; Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dosa, Katalin; Pfammatter, Jesse

    2014-01-01

    Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory…

  19. Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in "Brassica rapa" Fast Plants

    Science.gov (United States)

    Batzli, Janet M.; Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dosa, Katalin; Pfammatter, Jesse

    2014-01-01

    Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory…

  20. Quantitative determination of casein genetic variants in goat milk: Application in Girgentana dairy goat breed.

    Science.gov (United States)

    Montalbano, Maria; Segreto, Roberta; Di Gerlando, Rosalia; Mastrangelo, Salvatore; Sardina, Maria Teresa

    2016-02-01

    The study was conducted to develop a high-performance liquid chromatographic (HPLC) method to quantify casein genetic variants (αs2-, β-, and κ-casein) in milk of homozygous individuals of Girgentana goat breed. For calibration experiments, pure genetic variants were extracted from individual milk samples of animals with known genotypes. The described HPLC approach was precise, accurate and highly suitable for quantification of goat casein genetic variants of homozygous individuals. The amount of each casein per allele was: αs2-casein A = 2.9 ± 0.8 g/L and F = 1.8 ± 0.4 g/L; β-casein C = 3.0 ± 0.8 g/L and C1 = 2.0 ± 0.7 g/L and κ-casein A = 1.6 ± 0.3 g/L and B = 1.1 ± 0.2 g/L. A good correlation was found between the quantities of αs2-casein genetic variants A and F, and β-casein C and C1 with other previously described method. The main important result was obtained for κ-casein because, till now, no data were available on quantification of single genetic variants for this protein.

  1. Quantitative genetics of migration syndromes: a study of two barn swallow populations.

    Science.gov (United States)

    Teplitsky, C; Mouawad, N G; Balbontin, J; De Lope, F; Møller, A P

    2011-09-01

    Migration is a complex trait although little is known about genetic correlations between traits involved in such migration syndromes. To assess the migratory responses to climate change, we need information on genetic constraints on evolutionary potential of arrival dates in migratory birds. Using two long-term data sets on barn swallows Hirundo rustica (from Spain and Denmark), we show for the first time in wild populations that spring arrival dates are phenotypically and genetically correlated with morphological and life history traits. In the Danish population, length of outermost tail feathers and wing length were negatively genetically correlated with arrival date. In the Spanish population, we found a negative genetic correlation between arrival date and time elapsed between arrival date and laying date, constraining response to selection that favours both early arrival and shorter delays. This results in a decreased rate of adaptation, not because of constraints on arrival date, but constraints on delay before breeding, that is, a trait that can be equally important in the context of climate change.

  2. Nanoparticle interactions with live cells: Quantitative fluorescence microscopy of nanoparticle size effects

    Directory of Open Access Journals (Sweden)

    Li Shang

    2014-12-01

    Full Text Available Engineered nanomaterials are known to enter human cells, often via active endocytosis. Mechanistic details of the interactions between nanoparticles (NPs with cells are still not well enough understood. NP size is a key parameter that controls the endocytic mechanism and affects the cellular uptake yield. Therefore, we have systematically analyzed the cellular uptake of fluorescent NPs in the size range of 3.3–100 nm (diameter by live cells. By using spinning disk confocal microscopy in combination with quantitative image analysis, we studied the time courses of NP association with the cell membrane and subsequent internalization. NPs with diameters of less than 10 nm were observed to accumulate at the plasma membrane before being internalized by the cells. In contrast, larger NPs (100 nm were directly internalized without prior accumulation at the plasma membrane, regardless of their surface charges. We attribute this distinct size dependence to the requirement of a sufficiently strong local interaction of the NPs with the endocytic machinery in order to trigger the subsequent internalization.

  3. Quantitative receptor radioautography in the study of receptor-receptor interactions in the nucleus tractus solitarii

    Directory of Open Access Journals (Sweden)

    Fior-Chadi D.R.

    1998-01-01

    Full Text Available The nucleus tractus solitarii (NTS in the dorsomedial medulla comprises a wide range of neuropeptides and biogenic amines. Several of them are related to mechanisms of central blood pressure control. Angiotensin II (Ang II, neuropeptide Y (NPY and noradrenaline (NA are found in the NTS cells, as well as their receptors. Based on this observation we have evaluated the modulatory effect of these peptide receptors on a2-adrenoceptors in the NTS. Using quantitative receptor radioautography, we observed that NPY and Ang II receptors decreased the affinity of a2-adrenoceptors for their agonists in the NTS of the rat. Cardiovascular experiments agreed with the in vitro data. Coinjection of a threshold dose of Ang II or of the NPY agonists together with an ED50 dose of adrenergic agonists such as NA, adrenaline and clonidine counteracted the depressor effect produced by the a2-agonist in the NTS. The results provide evidence for the existence of an antagonistic interaction between Ang II at1 receptors and NPY receptor subtypes with the a2-adrenoceptors in the NTS. This receptor interaction may reduce the transduction over the a2-adrenoceptors which can be important in central cardiovascular regulation and in the development of hypertension

  4. Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

    Science.gov (United States)

    Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John

    2016-01-01

    The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886

  5. Genome-wide genetic interaction analysis of glaucoma using expert knowledge derived from human phenotype networks.

    Science.gov (United States)

    Hu, Ting; Darabos, Christian; Cricco, Maria E; Kong, Emily; Moore, Jason H

    2015-01-01

    The large volume of GWAS data poses great computational challenges for analyzing genetic interactions associated with common human diseases. We propose a computational framework for characterizing epistatic interactions among large sets of genetic attributes in GWAS data. We build the human phenotype network (HPN) and focus around a disease of interest. In this study, we use the GLAUGEN glaucoma GWAS dataset and apply the HPN as a biological knowledge-based filter to prioritize genetic variants. Then, we use the statistical epistasis network (SEN) to identify a significant connected network of pairwise epistatic interactions among the prioritized SNPs. These clearly highlight the complex genetic basis of glaucoma. Furthermore, we identify key SNPs by quantifying structural network characteristics. Through functional annotation of these key SNPs using Biofilter, a software accessing multiple publicly available human genetic data sources, we find supporting biomedical evidences linking glaucoma to an array of genetic diseases, proving our concept. We conclude by suggesting hypotheses for a better understanding of the disease.

  6. Quantitative determination of pairing interactions for high-temperature superconductivity in cuprates.

    Science.gov (United States)

    Bok, Jin Mo; Bae, Jong Ju; Choi, Han-Yong; Varma, Chandra M; Zhang, Wentao; He, Junfeng; Zhang, Yuxiao; Yu, Li; Zhou, X J

    2016-03-01

    A profound problem in modern condensed matter physics is discovering and understanding the nature of fluctuations and their coupling to fermions in cuprates, which lead to high-temperature superconductivity and the invariably associated strange metal state. We report the quantitative determination of normal and pairing self-energies, made possible by laser-based angle-resolved photoemission measurements of unprecedented accuracy and stability. Through a precise inversion procedure, both the effective interactions in the attractive d-wave symmetry and the repulsive part in the full symmetry are determined. The latter is nearly angle-independent. Near T c, both interactions are nearly independent of frequency and have almost the same magnitude over the complete energy range of up to about 0.4 eV, except for a low-energy feature at around 50 meV that is present only in the repulsive part, which has less than 10% of the total spectral weight. Well below T c, they both change similarly, with superconductivity-induced features at low energies. Besides finding the pairing self-energy and the attractive interactions for the first time, these results expose the central paradox of the problem of high T c: how the same frequency-independent fluctuations can dominantly scatter at angles ±π/2 in the attractive channel to give d-wave pairing and lead to angle-independent repulsive scattering. The experimental results are compared with available theoretical calculations based on antiferromagnetic fluctuations, the Hubbard model, and quantum-critical fluctuations of the loop-current order.

  7. Worming forward: amyotrophic lateral sclerosis toxicity mechanisms and genetic interactions in Caenorhabditis elegans

    Directory of Open Access Journals (Sweden)

    Martine eTherrien

    2014-04-01

    Full Text Available Neurodegenerative diseases share pathogenic mechanisms at the cellular level including protein misfolding, excitotoxicity and altered RNA homeostasis among others. Recent advances have shown that the genetic causes underlying these pathologies overlap, hinting at the existence of a genetic network for neurodegeneration. This is perhaps best illustrated by the recent discoveries of causative mutations for amyotrophic lateral sclerosis (ALS and frontotemporal degeneration (FTD. Once thought to be distinct entities, it is now recognized that these diseases exist along a genetic spectrum. With this wealth of discoveries comes the need to develop new genetic models of ALS and FTD to investigate not only pathogenic mechanisms linked to causative mutations, but to uncover potential genetic interactions that may point to new therapeutic targets. Given the conservation of many disease genes across evolution, Caenorhabditis elegans is an ideal system to investigate genetic interactions amongst these genes. Here we review the use of C. elegans to model ALS and investigate a putative genetic network for ALS/FTD that may extend to other neurological disorders.

  8. Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

    Science.gov (United States)

    The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...

  9. [Attempt at quantitative estimation of genetic effects of chemical pollution of atmospheric air in urban populations].

    Science.gov (United States)

    Antypenko, Ie M; Kohut, N M; Oleksiienko, P L

    1992-01-01

    Epidemiological investigation of spontaneous abortions and congenital anomalies in three towns of Ukraine has shown that mutation rate in Mariupol, the most contaminated town, as compared with relatively clean town is essentially higher. Genetical consequences due to environmental chemical pollution in Mariupol proved to be equivalent to the chronic influence of ionizing radiation for 30 years in the dose of 230 REM.

  10. Genetic analysis identifies quantitative trait loci controlling rosette mineral concentrations in Arabidopsis thaliana under drought

    NARCIS (Netherlands)

    Ghandilyan, A.; Barboza, L.; Tisne, S.; Granier, C.; Reymond, M.; Koornneef, M.; Schat, H.; Aarts, M.G.M.

    2009-01-01

    • Rosettes of 25 Arabidopsis thaliana accessions and an Antwerp-1 (An-1) × Landsberg erecta (Ler) population of recombinant inbred lines (RILs) grown in optimal watering conditions (OWC) and water deficit conditions (WDC) were analysed for mineral concentrations to identify genetic loci involved in

  11. Genetic interaction network of the Saccharomyces cerevisiae type 1 phosphatase Glc7

    Directory of Open Access Journals (Sweden)

    Neszt Michael

    2008-07-01

    Full Text Available Abstract Background Protein kinases and phosphatases regulate protein phosphorylation, a critical means of modulating protein function, stability and localization. The identification of functional networks for protein phosphatases has been slow due to their redundant nature and the lack of large-scale analyses. We hypothesized that a genome-scale analysis of genetic interactions using the Synthetic Genetic Array could reveal protein phosphatase functional networks. We apply this approach to the conserved type 1 protein phosphatase Glc7, which regulates numerous cellular processes in budding yeast. Results We created a novel glc7 catalytic mutant (glc7-E101Q. Phenotypic analysis indicates that this novel allele exhibits slow growth and defects in glucose metabolism but normal cell cycle progression and chromosome segregation. This suggests that glc7-E101Q is a hypomorphic glc7 mutant. Synthetic Genetic Array analysis of glc7-E101Q revealed a broad network of 245 synthetic sick/lethal interactions reflecting that many processes are required when Glc7 function is compromised such as histone modification, chromosome segregation and cytokinesis, nutrient sensing and DNA damage. In addition, mitochondrial activity and inheritance and lipid metabolism were identified as new processes involved in buffering Glc7 function. An interaction network among 95 genes genetically interacting with GLC7 was constructed by integration of genetic and physical interaction data. The obtained network has a modular architecture, and the interconnection among the modules reflects the cooperation of the processes buffering Glc7 function. Conclusion We found 245 genes required for the normal growth of the glc7-E101Q mutant. Functional grouping of these genes and analysis of their physical and genetic interaction patterns bring new information on Glc7-regulated processes.

  12. Effects of long-term averaging of quantitative blood pressure traits on the detection of genetic associations.

    Science.gov (United States)

    Ganesh, Santhi K; Chasman, Daniel I; Larson, Martin G; Guo, Xiuqing; Verwoert, Germain; Bis, Joshua C; Gu, Xiangjun; Smith, Albert V; Yang, Min-Lee; Zhang, Yan; Ehret, Georg; Rose, Lynda M; Hwang, Shih-Jen; Papanicolau, George J; Sijbrands, Eric J; Rice, Kenneth; Eiriksdottir, Gudny; Pihur, Vasyl; Ridker, Paul M; Vasan, Ramachandran S; Newton-Cheh, Christopher; Raffel, Leslie J; Amin, Najaf; Rotter, Jerome I; Liu, Kiang; Launer, Lenore J; Xu, Ming; Caulfield, Mark; Morrison, Alanna C; Johnson, Andrew D; Vaidya, Dhananjay; Dehghan, Abbas; Li, Guo; Bouchard, Claude; Harris, Tamara B; Zhang, He; Boerwinkle, Eric; Siscovick, David S; Gao, Wei; Uitterlinden, Andre G; Rivadeneira, Fernando; Hofman, Albert; Willer, Cristen J; Franco, Oscar H; Huo, Yong; Witteman, Jacqueline C M; Munroe, Patricia B; Gudnason, Vilmundur; Palmas, Walter; van Duijn, Cornelia; Fornage, Myriam; Levy, Daniel; Psaty, Bruce M; Chakravarti, Aravinda

    2014-07-03

    Blood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that averaging BP measured across time would improve phenotypic accuracy and thereby increase statistical power to detect genetic associations. We studied systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) averaged over multiple years in 46,629 individuals of European ancestry. We identified 39 trait-variant associations across 19 independent loci (p < 5 × 10(-8)); five associations (in four loci) uniquely identified by our LTA analyses included those of SBP and MAP at 2p23 (rs1275988, near KCNK3), DBP at 2q11.2 (rs7599598, in FER1L5), and PP at 6p21 (rs10948071, near CRIP3) and 7p13 (rs2949837, near IGFBP3). Replication analyses conducted in cohorts with single-visit BP data showed positive replication of associations and a nominal association (p < 0.05). We estimated a 20% gain in statistical power with long-term average (LTA) as compared to single-visit BP association studies. Using LTA analysis, we identified genetic loci influencing BP. LTA might be one way of increasing the power of genetic associations for continuous traits in extant samples for other phenotypes that are measured serially over time. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  13. Quantitative genetics, version 3.0: where have we gone since 1987 and where are we headed?

    Science.gov (United States)

    Walsh, Bruce

    2009-06-01

    The last 20 years since the previous World Congress have seen tremendous advancements in quantitative genetics, in large part due to the advancements in genomics, computation, and statistics. One central theme of this last 20 years has been the exploitation of the vast harvest of molecular markers--examples include QTL and association mapping, marker-assisted selection and introgression, scans for loci under selection, and methods to infer degree of coancestry, population membership, and past demographic history. One consequence of this harvest is that phenotyping, rather than genotyping, is now the bottleneck in molecular quantitative genetics studies. Equally important have been advances in statistics, many developed to effectively use this treasure trove of markers. Computational improvements in statistics, and in particular Markov Chain Monte Carlo (MCMC) methods, have facilitated many of these methods, as have significantly improved computational abilities for mixed models. Indeed, one could argue that mixed models have had at least as great an impact in quantitative genetics as have molecular markers. A final important theme over the past 20 years has been the fusion of population and quantitative genetics, in particular the importance of coalescence theory with its applications for association mapping, scans for loci under selection, and estimation of the demography history of a population. What are the future directions of the field? While obviously important surprises await us, the general trend seems to be moving into higher and higher dimensional traits and, in general, dimensional considerations. We have methods to deal with infinite-dimensional traits indexed by a single variable (such as a trait varying over time), but the future will require us to treat much more complex objects, such as infinite-dimensional traits indexed over several variables and with graphs and dynamical networks. A second important direction is the interfacing of quantitative

  14. An information-gain approach to detecting three-way epistatic interactions in genetic association studies

    DEFF Research Database (Denmark)

    Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W;

    2013-01-01

    Background Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying epistasis....... In the tuberculosis data, we found a statistically significant pure three-way epistatic interaction effect that was stronger than any lower-order associations. Conclusion Our study provides a methodological basis for detecting and characterizing high-order gene-gene interactions in genetic association studies....

  15. Transgene x environment interactions in genetically modified wheat.

    Directory of Open Access Journals (Sweden)

    Simon L Zeller

    Full Text Available BACKGROUND: The introduction of transgenes into plants may cause unintended phenotypic effects which could have an impact on the plant itself and the environment. Little is published in the scientific literature about the interrelation of environmental factors and possible unintended effects in genetically modified (GM plants. METHODS AND FINDINGS: We studied transgenic bread wheat Triticum aestivum lines expressing the wheat Pm3b gene against the fungus powdery mildew Blumeria graminis f.sp. tritici. Four independent offspring pairs, each consisting of a GM line and its corresponding non-GM control line, were grown under different soil nutrient conditions and with and without fungicide treatment in the glasshouse. Furthermore, we performed a field experiment with a similar design to validate our glasshouse results. The transgene increased the resistance to powdery mildew in all environments. However, GM plants reacted sensitive to fungicide spraying in the glasshouse. Without fungicide treatment, in the glasshouse GM lines had increased vegetative biomass and seed number and a twofold yield compared with control lines. In the field these results were reversed. Fertilization generally increased GM/control differences in the glasshouse but not in the field. Two of four GM lines showed up to 56% yield reduction and a 40-fold increase of infection with ergot disease Claviceps purpurea compared with their control lines in the field experiment; one GM line was very similar to its control. CONCLUSIONS: Our results demonstrate that, depending on the insertion event, a particular transgene can have large effects on the entire phenotype of a plant and that these effects can sometimes be reversed when plants are moved from the glasshouse to the field. However, it remains unclear which mechanisms underlie these effects and how they may affect concepts in molecular plant breeding and plant evolutionary ecology.

  16. Development and evaluation of event-specific quantitative PCR method for genetically modified soybean A2704-12.

    Science.gov (United States)

    Takabatake, Reona; Akiyama, Hiroshi; Sakata, Kozue; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Teshima, Reiko; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

    2011-01-01

    A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event; A2704-12. During the plant transformation, DNA fragments derived from pUC19 plasmid were integrated in A2704-12, and the region was found to be A2704-12 specific. The pUC19-derived DNA sequences were used as primers for the specific detection of A2704-12. We first tried to construct a standard plasmid for A2704-12 quantification using pUC19. However, non-specific signals appeared with both qualitative and quantitative PCR analyses using the specific primers with pUC19 as a template, and we then constructed a plasmid using pBR322. The conversion factor (C(f)), which is required to calculate the amount of the genetically modified organism (GMO), was experimentally determined with two real-time PCR instruments, the Applied Biosystems 7900HT and the Applied Biosystems 7500. The determined C(f) values were both 0.98. The quantitative method was evaluated by means of blind tests in multi-laboratory trials using the two real-time PCR instruments. The limit of quantitation for the method was estimated to be 0.1%. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSD(R)), and the determined bias and RSD(R) values for the method were each less than 20%. These results suggest that the developed method would be suitable for practical analyses for the detection and quantification of A2704-12.

  17. Cancer genetics education in a low- to middle-income country: evaluation of an interactive workshop for clinicians in Kenya.

    Directory of Open Access Journals (Sweden)

    Jessica A Hill

    Full Text Available Clinical genetic testing is becoming an integral part of medical care for inherited disorders. While genetic testing and counseling are readily available in high-income countries, in low- and middle-income countries like Kenya genetic testing is limited and genetic counseling is virtually non-existent. Genetic testing is likely to become widespread in Kenya within the next decade, yet there has not been a concomitant increase in genetic counseling resources. To address this gap, we designed an interactive workshop for clinicians in Kenya focused on the genetics of the childhood eye cancer retinoblastoma. The objectives were to increase retinoblastoma genetics knowledge, build genetic counseling skills and increase confidence in those skills.The workshop was conducted at the 2013 Kenyan National Retinoblastoma Strategy meeting. It included a retinoblastoma genetics presentation, small group discussion of case studies and genetic counseling role-play. Knowledge was assessed by standardized test, and genetic counseling skills and confidence by questionnaire.Knowledge increased significantly post-workshop, driven by increased knowledge of retinoblastoma causative genetics. One-year post-workshop, participant knowledge had returned to baseline, indicating that knowledge retention requires more frequent reinforcement. Participants reported feeling more confident discussing genetics with patients, and had integrated more genetic counseling into patient interactions.A comprehensive retinoblastoma genetics workshop can increase the knowledge and skills necessary for effective retinoblastoma genetic counseling.

  18. [Development and validation of event-specific quantitative PCR method for genetically modified maize LY038].

    Science.gov (United States)

    Mano, Junichi; Masubuchi, Tomoko; Hatano, Shuko; Futo, Satoshi; Koiwa, Tomohiro; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Akiyama, Hiroshi; Teshima, Reiko; Kurashima, Takeyo; Takabatake, Reona; Kitta, Kazumi

    2013-01-01

    In this article, we report a novel real-time PCR-based analytical method for quantitation of the GM maize event LY038. We designed LY038-specific and maize endogenous reference DNA-specific PCR amplifications. After confirming the specificity and linearity of the LY038-specific PCR amplification, we determined the conversion factor required to calculate the weight-based content of GM organism (GMO) in a multilaboratory evaluation. Finally, in order to validate the developed method, an interlaboratory collaborative trial according to the internationally harmonized guidelines was performed with blind DNA samples containing LY038 at the mixing levels of 0, 0.5, 1.0, 5.0 and 10.0%. The precision of the method was evaluated as the RSD of reproducibility (RSDR), and the values obtained were all less than 25%. The limit of quantitation of the method was judged to be 0.5% based on the definition of ISO 24276 guideline. The results from the collaborative trial suggested that the developed quantitative method would be suitable for practical testing of LY038 maize.

  19. Genetic Analysis of Embryo, Cytoplasm and Maternal Effects and Their Environment Interactions for Isoflavone Content in Soybean [Glycine max(L.) Merr.

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Soybean seed products contain isoflavones (genistein, daidzein, and glycitein) that display biological effects when ingested by humans and animals. These effects are species, dose and age dependent. Therefore, the content and quality of isoflavones in soybeans is a key factor to the biological effect. Our objective was to identify the genetic effects that underlie the isoflavone content in soybean seeds. A genetic model for quantitative traits of seeds in diploid plants was applied to estimate the genetic main effects and genotype × environment (GE) interaction effects for the isoflavone content (IC) of soybean seeds by using two years experimental data with an incomplete diallel mating design of six parents. Results showed that the IC of soybean seeds was simultaneously controlled by the genetic effects of maternal,embryo, and cytoplasm, of which maternal genetic effects were most important, followed by embryo and cytoplasmic genetic effects. The main effects of different genetic systems on IC trait were more important than environment interaction effects. The strong dominance effects on isoflavone from residual was made easily by environment conditions. Therefore,the improvement of the IC of soybean seeds would be more efficient when selection is based on maternal plants than that on the single seed. Maternal heritability (65.73%) was most important for IC, followed by embryo heritability (25.87%) and cytoplasmic heritability (8.39%). Based on predicated genetic effects, Yudou 29 and Zheng 90007 were better than other parents for increasing IC in the progeny and improving the quality of soybean. The significant effects of maternal and embryo dominance effects in variance show that the embryo heterosis and maternal heterosis are existent and uninfluenced by environment interaction effects.

  20. A quantitative genetic study of starvation resistance at different geographic scales in natural populations of Drosophila melanogaster.

    Science.gov (United States)

    Goenaga, Julieta; José Fanara, Juan; Hasson, Esteban

    2010-08-01

    Food shortage is a stress factor that commonly affects organisms in nature. Resistance to food shortage or starvation resistance (SR) is a complex quantitative trait with direct implications on fitness. However, surveys of natural genetic variation in SR at different geographic scales are scarce. Here, we have measured variation in SR in sets of lines derived from nine natural populations of Drosophila melanogaster collected in western Argentina. Our study shows that within population variation explained a larger proportion of overall phenotypic variance (80%) than among populations (7·2%). We also noticed that an important fraction of variation was sex-specific. Overall females were more resistant to starvation than males; however, the magnitude of the sexual dimorphism (SD) in SR varied among lines and explained a significant fraction of phenotypic variance in all populations. Estimates of cross-sex genetic correlations suggest that the genetic architecture of SR is only partially shared between sexes in the populations examined, thus, facilitating further evolution of the SD.

  1. Genetic diversity of upland rice germplasm in Malaysia based on quantitative traits.

    Science.gov (United States)

    Sohrabi, M; Rafii, M Y; Hanafi, M M; Siti Nor Akmar, A; Latif, M A

    2012-01-01

    Genetic diversity is prerequisite for any crop improvement program as it helps in the development of superior recombinants. Fifty Malaysian upland rice accessions were evaluated for 12 growth traits, yield and yield components. All of the traits were significant and highly significant among the accessions. The higher magnitudes of genotypic and phenotypic coefficients of variation were recorded for flag leaf length-to-width ratio, spikelet fertility, and days to flowering. High heritability along with high genetic advance was registered for yield of plant, days to flowering, and flag leaf length-to-width ratio suggesting preponderance of additive gene action in the gene expression of these characters. Plant height showed highly significant positive correlation with most of the traits. According to UPGMA cluster analysis all accessions were clustered into six groups. Twelve morphological traits provided around 77% of total variation among the accessions.

  2. Genetic Diversity of Upland Rice Germplasm in Malaysia Based on Quantitative Traits

    Directory of Open Access Journals (Sweden)

    M. Sohrabi

    2012-01-01

    Full Text Available Genetic diversity is prerequisite for any crop improvement program as it helps in the development of superior recombinants. Fifty Malaysian upland rice accessions were evaluated for 12 growth traits, yield and yield components. All of the traits were significant and highly significant among the accessions. The higher magnitudes of genotypic and phenotypic coefficients of variation were recorded for flag leaf length-to-width ratio, spikelet fertility, and days to flowering. High heritability along with high genetic advance was registered for yield of plant, days to flowering, and flag leaf length-to-width ratio suggesting preponderance of additive gene action in the gene expression of these characters. Plant height showed highly significant positive correlation with most of the traits. According to UPGMA cluster analysis all accessions were clustered into six groups. Twelve morphological traits provided around 77% of total variation among the accessions.

  3. Estimates of genetic variability and association studies in quantitative plant traits of Eruca spp. landraces

    Directory of Open Access Journals (Sweden)

    Bozokalfa Kadri Mehmet

    2010-01-01

    Full Text Available Despite the increasing of economical importance of rocket plant limited information is available on genetic variability for the agronomic traits among Eruca spp. Hence, heritability and association studies of plant properties are necessities for a successful further rocket breeding programme. The objective of this study was to examine phenotypic and genotypic variability, broad sense heritability, genetic advance, genotypic and phenotypic correlation and mean for agronomic traits of rocket plant. The magnitude of phenotypic coefficient of variation values for all the traits were higher than the corresponding values and broad sense heritability estimates exceeded 65% for all traits. Phenotypic coefficients of variability (PCV ranged from 7.60 to 34.34% and genotypic coefficients of variability (GCV ranged between 5.58% for petiole thickness and 34.30% for plant weight. The results stated that plant weight, siliqua width, seed per siliqua and seed weight could be useful character for improved Eruca spp. breeding programme.

  4. Quantitative genetic variation for oviposition preference with respect to phenylthiocarbamide in Drosophila melanogaster.

    Science.gov (United States)

    Possidente, B; Mustafa, M; Collins, L

    1999-05-01

    Seven isogenic strains of Drosophila melanogaster were assayed for oviposition preference on food with phenylthiocarbamide (PTC) versus plain food. There was significant variation among strains for the percentage of eggs oviposited on each medium, ranging from 70 +/- 4% (SE) preference for plain food to no significant preference. Reciprocal hybrid, backcross, and F2 generations derived from two extreme parent strains revealed significant additive and nonadditive genetic variation but no evidence of maternal, paternal, or sex-chromosome effects.

  5. Quantitative genetics of plumage color: lifetime effects of early nest environment on a colorful sexual signal

    Science.gov (United States)

    Hubbard, Joanna K; Jenkins, Brittany R; Safran, Rebecca J

    2015-01-01

    Phenotypic differences among individuals are often linked to differential survival and mating success. Quantifying the relative influence of genetic and environmental variation on phenotype allows evolutionary biologists to make predictions about the potential for a given trait to respond to selection and various aspects of environmental variation. In particular, the environment individuals experience during early development can have lasting effects on phenotype later in life. Here, we used a natural full-sib/half-sib design as well as within-individual longitudinal analyses to examine genetic and various environmental influences on plumage color. We find that variation in melanin-based plumage color – a trait known to influence mating success in adult North American barn swallows (Hirundo rustica erythrogaster) – is influenced by both genetics and aspects of the developmental environment, including variation due to the maternal phenotype and the nest environment. Within individuals, nestling color is predictive of adult color. Accordingly, these early environmental influences are relevant to the sexually selected plumage color variation in adults. Early environmental conditions appear to have important lifelong implications for individual reproductive performance through sexual signal development in barn swallows. Our results indicate that feather color variation conveys information about developmental conditions and maternal care alleles to potential mates in North American barn swallows. Melanin-based colors are used for sexual signaling in many organisms, and our study suggests that these signals may be more sensitive to environmental variation than previously thought. PMID:26380676

  6. Quantitative genetics of plumage color: lifetime effects of early nest environment on a colorful sexual signal.

    Science.gov (United States)

    Hubbard, Joanna K; Jenkins, Brittany R; Safran, Rebecca J

    2015-08-01

    Phenotypic differences among individuals are often linked to differential survival and mating success. Quantifying the relative influence of genetic and environmental variation on phenotype allows evolutionary biologists to make predictions about the potential for a given trait to respond to selection and various aspects of environmental variation. In particular, the environment individuals experience during early development can have lasting effects on phenotype later in life. Here, we used a natural full-sib/half-sib design as well as within-individual longitudinal analyses to examine genetic and various environmental influences on plumage color. We find that variation in melanin-based plumage color - a trait known to influence mating success in adult North American barn swallows (Hirundo rustica erythrogaster) - is influenced by both genetics and aspects of the developmental environment, including variation due to the maternal phenotype and the nest environment. Within individuals, nestling color is predictive of adult color. Accordingly, these early environmental influences are relevant to the sexually selected plumage color variation in adults. Early environmental conditions appear to have important lifelong implications for individual reproductive performance through sexual signal development in barn swallows. Our results indicate that feather color variation conveys information about developmental conditions and maternal care alleles to potential mates in North American barn swallows. Melanin-based colors are used for sexual signaling in many organisms, and our study suggests that these signals may be more sensitive to environmental variation than previously thought.

  7. Quantitative genetic modeling and inference in the presence of nonignorable missing data.

    Science.gov (United States)

    Steinsland, Ingelin; Larsen, Camilla Thorrud; Roulin, Alexandre; Jensen, Henrik

    2014-06-01

    Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

  8. Genetic counseling follow-up - a retrospective study with a quantitative approach

    Directory of Open Access Journals (Sweden)

    De Pina-Neto João M.

    1999-01-01

    Full Text Available The impact of genetic counseling (GC was evaluated in families, who were interviewed at least two and half years and at most seven years after GC at the Genetics Service of the University Hospital, Faculty of Medicine of Ribeirão Preto, University of São Paulo (HC, FMRP, USP. The 113 families interviewed in this study were asked 48 questions and all children born after GC were studied clinically. We evaluated the families for spontaneous motivation for GC and understanding of GC information, their reproductive decisions, changes in the family after GC and the health status of new children. The majority of families seen at the Hospital das Clínicas de Ribeirão Preto were not spontaneously motivated to undergo GC. They had a low level of understanding about the information they received during GC. Generally families were using contraceptive methods (even when at low genetic risk with a consequent low rate of pregnancies and children born after GC. These families also had a very low rate of child adoption and divorces when compared to other studies.

  9. Interactive decision support for risk management: a qualitative evaluation in cancer genetic counselling sessions.

    Science.gov (United States)

    Glasspool, David W; Oettinger, Ayelet; Braithwaite, Dejana; Fox, John

    2010-09-01

    Genetic counselling for inherited susceptibility to cancer involves communication of a significant amount of information about possible consequences of different interventions. This study explores counsellors' attitudes to computer software designed to aid this process. Eight genetic counsellors used the software with actors playing patients. Clinicians' rating of expected patient satisfaction, content, accuracy, timeliness, format, overall value, ease of use, effect on the patient-provider relationship and effect on clinician's performance were evaluated via qualitative and quantitative analysis of interviews, training tasks and questionnaires. Most counsellors found the software effective. Concerns related to possible impact on consultation dynamics and content. Participants suggested countering these through appropriate new counselling skills and selective use of the computer. The REACT software could provide effective support for genetic risk management counselling.

  10. How Genetic and Other Biological Factors Interact with Smoking Decisions.

    Science.gov (United States)

    Bierut, Laura; Cesarini, David

    2015-09-01

    Despite clear links between genes and smoking, effective public policy requires far richer measurement of the feedback between biological, behavioral, and environmental factors. The Kavli HUMAN Project (KHP) plans to exploit the plummeting costs of data gathering and to make creative use of new technologies to construct a longitudinal panel data set that would compare favorably to existing longitudinal surveys, both in terms of the richness of the behavioral measures and the cost-effectiveness of the data collection. By developing a more comprehensive approach to characterizing behavior than traditional methods, KHP will allow researchers to paint a much richer picture of an individual's life-cycle trajectory of smoking, alcohol, and drug use, and interactions with other choices and environmental factors. The longitudinal nature of KHP will be particularly valuable in light of the increasing evidence for how smoking behavior affects physiology and health. The KHP could have a transformative impact on the understanding of the biology of addictive behaviors such as smoking, and of a rich range of prevention and amelioration policies.

  11. Marker-assisted introgression of five QTLs controlling fruit quality traits into three tomato lines revealed interactions between QTLs and genetic backgrounds.

    Science.gov (United States)

    Lecomte, L; Duffé, P; Buret, M; Servin, B; Hospital, F; Causse, M

    2004-08-01

    The evaluation of organoleptic quality of tomato fruit requires physical, chemical and sensory analyses, which are expensive and difficult to assess. Therefore, their practical use in phenotypic selection is difficult. In a previous study, the genetic control of several traits related to organoleptic quality of fresh-market tomato fruit was investigated. Five chromosome regions strongly involved in organoleptic quality attributes were then chosen to be introgressed into three different recipient lines through marker-assisted selection. A marker-assisted backcross (MABC) strategy was performed, as all the favorable alleles for quality traits were provided by the same parental tomato line, whose fruit weight (FW) and firmness were much lower than those of the lines commonly used to develop fresh market varieties. Three improved lines were obtained after three backcrossing and two selfing generations. The implementation of the MABC scheme is described. The three improved lines were crossed together and with the recipient lines in a half-diallel mating scheme, and the simultaneous effect of the five quantitative trait locus (QTL) regions was compared in different genetic backgrounds. Significant effects of the introgressed regions and of the genetic backgrounds were shown. Additive effects were detected for soluble solid and reducing sugar content in two genetic backgrounds. A partially dominant effect on titratable acidity was detected in only one genetic background. In contrast, additive to dominant unfavorable effects of the donor alleles were detected for FW and locule number in the three genetic backgrounds. Recessive QTL effects on firmness were only detected in the two firmest genetic backgrounds. Comparison of the hybrids in the half-diallel gave complementary information on the effects of: (1) the alleles at the selected regions, (2) the genetic backgrounds and (3) their interaction. Breeding efficiency strongly varied according to the recipient parent, and

  12. Association mapping of loci controlling genetic and environmental interaction of soybean flowering time under various photo-thermal conditions.

    Science.gov (United States)

    Mao, Tingting; Li, Jinyu; Wen, Zixiang; Wu, Tingting; Wu, Cunxiang; Sun, Shi; Jiang, Bingjun; Hou, Wensheng; Li, Wenbin; Song, Qijian; Wang, Dechun; Han, Tianfu

    2017-05-26

    Soybean (Glycine max (L.) Merr.) is a short day plant. Its flowering and maturity time are controlled by genetic and environmental factors, as well the interaction between the two factors. Previous studies have shown that both genetic and environmental factors, mainly photoperiod and temperature, control flowering time of soybean. Additionally, these studies have reported gene × gene and gene × environment interactions on flowering time. However, the effects of quantitative trait loci (QTL) in response to photoperiod and temperature have not been well evaluated. The objectives of the current study were to identify the effects of loci associated with flowering time under different photo-thermal conditions and to understand the effects of interaction between loci and environment on soybean flowering. Different photoperiod and temperature combinations were obtained by adjusting sowing dates (spring sowing and summer sowing) or day-length (12 h, 16 h). Association mapping was performed on 91 soybean cultivars from different maturity groups (MG000-VIII) using 172 SSR markers and 5107 SNPs from the Illumina SoySNP6K iSelectBeadChip. The effects of the interaction between QTL and environments on flowering time were also analysed using the QTXNetwork. Large-effect loci were detected on Gm 11, Gm 16 and Gm 20 as in previous reports. Most loci associated with flowering time are sensitive to photo-thermal conditions. Number of loci associated with flowering time was more under the long day (LD) than under the short day (SD) condition. The variation of flowering time among the soybean cultivars mostly resulted from the epistasis × environment and additive × environment interactions. Among the three candidate loci, i.e. Gm04_4497001 (near GmCOL3a), Gm16_30766209 (near GmFT2a and GmFT2b) and Gm19_47514601 (E3 or GmPhyA3), the Gm04_4497001 may be the key locus interacting with other loci for controlling soybean flowering time. The effects of loci associated

  13. The conditional nature of genetic interactions: the consequences of wild-type backgrounds on mutational interactions in a genome-wide modifier screen.

    Directory of Open Access Journals (Sweden)

    Sudarshan Chari

    Full Text Available The phenotypic outcome of a mutation cannot be simply mapped onto the underlying DNA variant. Instead, the phenotype is a function of the allele, the genetic background in which it occurs and the environment where the mutational effects are expressed. While the influence of genetic background on the expressivity of individual mutations is recognized, its consequences on the interactions between genes, or the genetic network they form, is largely unknown. The description of genetic networks is essential for much of biology; yet if, and how, the topologies of such networks are influenced by background is unknown. Furthermore, a comprehensive examination of the background dependent nature of genetic interactions may lead to identification of novel modifiers of biological processes. Previous work in Drosophila melanogaster demonstrated that wild-type genetic background influences the effects of an allele of scalloped (sd, with respect to both its principal consequence on wing development and its interactions with a mutation in optomotor blind. In this study we address whether the background dependence of mutational interactions is a general property of genetic systems by performing a genome wide dominant modifier screen of the sd(E3 allele in two wild-type genetic backgrounds using molecularly defined deletions. We demonstrate that ~74% of all modifiers of the sd(E3 phenotype are background-dependent due in part to differential sensitivity to genetic perturbation. These background dependent interactions include some with qualitative differences in the phenotypic outcome, as well as instances of sign epistasis. This suggests that genetic interactions are often contingent on genetic background, with flexibility in genetic networks due to segregating variation in populations. Such background dependent effects can substantially alter conclusions about how genes influence biological processes, the potential for genetic screens in alternative wild

  14. Quantitation of malaria parasite-erythrocyte cell-cell interactions using optical tweezers.

    Science.gov (United States)

    Crick, Alex J; Theron, Michel; Tiffert, Teresa; Lew, Virgilio L; Cicuta, Pietro; Rayner, Julian C

    2014-08-19

    Erythrocyte invasion by Plasmodium falciparum merozoites is an essential step for parasite survival and hence the pathogenesis of malaria. Invasion has been studied intensively, but our cellular understanding has been limited by the fact that it occurs very rapidly: invasion is generally complete within 1 min, and shortly thereafter the merozoites, at least in in vitro culture, lose their invasive capacity. The rapid nature of the process, and hence the narrow time window in which measurements can be taken, have limited the tools available to quantitate invasion. Here we employ optical tweezers to study individual invasion events for what we believe is the first time, showing that newly released P. falciparum merozoites, delivered via optical tweezers to a target erythrocyte, retain their ability to invade. Even spent merozoites, which had lost the ability to invade, retain the ability to adhere to erythrocytes, and furthermore can still induce transient local membrane deformations in the erythrocyte membrane. We use this technology to measure the strength of the adhesive force between merozoites and erythrocytes, and to probe the cellular mode of action of known invasion inhibitory treatments. These data add to our understanding of the erythrocyte-merozoite interactions that occur during invasion, and demonstrate the power of optical tweezers technologies in unraveling the blood-stage biology of malaria. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  15. Joint genetic analysis using variant sets reveals polygenic gene-context interactions.

    Directory of Open Access Journals (Sweden)

    Francesco Paolo Casale

    2017-04-01

    Full Text Available Joint genetic models for multiple traits have helped to enhance association analyses. Most existing multi-trait models have been designed to increase power for detecting associations, whereas the analysis of interactions has received considerably less attention. Here, we propose iSet, a method based on linear mixed models to test for interactions between sets of variants and environmental states or other contexts. Our model generalizes previous interaction tests and in particular provides a test for local differences in the genetic architecture between contexts. We first use simulations to validate iSet before applying the model to the analysis of genotype-environment interactions in an eQTL study. Our model retrieves a larger number of interactions than alternative methods and reveals that up to 20% of cases show context-specific configurations of causal variants. Finally, we apply iSet to test for sub-group specific genetic effects in human lipid levels in a large human cohort, where we identify a gene-sex interaction for C-reactive protein that is missed by alternative methods.

  16. Interactions within the MHC contribute to the genetic architecture of celiac disease

    Science.gov (United States)

    Abraham, Gad; Kikianty, Eder; Wang, Qiao; Rawlinson, Dave; Shi, Fan; Haviv, Izhak; Stern, Linda

    2017-01-01

    Interaction analysis of GWAS can detect signal that would be ignored by single variant analysis, yet few robust interactions in humans have been detected. Recent work has highlighted interactions in the MHC region between known HLA risk haplotypes for various autoimmune diseases. To better understand the genetic interactions underlying celiac disease (CD), we have conducted exhaustive genome-wide scans for pairwise interactions in five independent CD case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 14 independent interaction signals within the MHC region that achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD interaction signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for statistical interaction outside the MHC was not observed. Both within and between European populations, we observed striking consistency of two-locus models and model distribution. Within the UK population, models of CD based on both interactions and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. The interactions signal detected across the five cohorts indicates the presence of novel associations in the MHC region that cannot be detected using additive models. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets. PMID:28282431

  17. Identification of quantitative genetic components of fitness variation in farmed, hybrid and native salmon in the wild.

    Science.gov (United States)

    Besnier, F; Glover, K A; Lien, S; Kent, M; Hansen, M M; Shen, X; Skaala, Ø

    2015-07-01

    Feral animals represent an important problem in many ecosystems due to interbreeding with wild conspecifics. Hybrid offspring from wild and domestic parents are often less adapted to local environment and ultimately, can reduce the fitness of the native population. This problem is an important concern in Norway, where each year, hundreds of thousands of farm Atlantic salmon escape from fish farms. Feral fish outnumber wild populations, leading to a possible loss of local adaptive genetic variation and erosion of genetic structure in wild populations. Studying the genetic factors underlying relative performance between wild and domesticated conspecific can help to better understand how domestication modifies the genetic background of populations, and how it may alter their ability to adapt to the natural environment. Here, based upon a large-scale release of wild, farm and wild x farm salmon crosses into a natural river system, a genome-wide quantitative trait locus (QTL) scan was performed on the offspring of 50 full-sib families, for traits related to fitness (length, weight, condition factor and survival). Six QTLs were detected as significant contributors to the phenotypic variation of the first three traits, explaining collectively between 9.8 and 14.8% of the phenotypic variation. The seventh QTL had a significant contribution to the variation in survival, and is regarded as a key factor to understand the fitness variability observed among salmon in the river. Interestingly, strong allelic correlation within one of the QTL regions in farmed salmon might reflect a recent selective sweep due to artificial selection.

  18. Interactions between meat intake and genetic variation in relation to colorectal cancer

    DEFF Research Database (Denmark)

    Andersen, Vibeke; Vogel, Ulla

    2015-01-01

    Meat intake is associated with the risk of colorectal cancer. The objective of this systematic review was to evaluate interactions between meat intake and genetic variation in order to identify biological pathways involved in meat carcinogenesis. We performed a literature search of Pub...... a polymorphism in XPC and meat was found in one prospective and one case-control study; however, the directions of the risk estimates were opposite. Thus, none of the findings were replicated. The results from this systematic review suggest that genetic variation in the inflammatory response and DNA repair...... pathway is involved in meat-related colorectal carcinogenesis, whereas no support for the involvement of heme and iron from meat or cooking mutagens was found. Further studies assessing interactions between meat intake and genetic variation in relation to CRC in large well-characterised prospective...

  19. The Interaction of Selective Attention and Cognitive Development on Achievement in Nigerian Secondary School Genetics

    Science.gov (United States)

    Okoye, Namdi N. S.

    2009-01-01

    The study tried to examine the interaction between two independent variables of selective attention and cognitive development on Achievement in Genetics at the Secondary School level. In looking at the problem of this study three null hypotheses were generated for testing at 0.05 level of significance. Factorial Analysis of Variance design with…

  20. Genetic interactions for heat stress and production level: predicting foreign from domestic data

    Science.gov (United States)

    Genetic by environmental interactions were estimated from U.S. national data by separately adding random regressions for heat stress (HS) and herd production level (HL) to the all-breed animal model to improve predictions of future records and rankings in other climate and production situations. Yie...

  1. Genetics of non-alcoholic fatty liver disease: From susceptibility and nutrient interactions to management

    Institute of Scientific and Technical Information of China (English)

    Vishnubhotla; Venkata; Ravi; Kanth; Mitnala; Sasikala; Mithun; Sharma; Padaki; Nagaraja; Rao; Duvvuru; Nageshwar; Reddy

    2016-01-01

    Genetics plays an important role in determining the susceptibility of an individual to develop a disease. Complex, multi factorial diseases of modern day(diabetes, cardiovascular disease, hypertension and obesity) are a result of disparity between the type of food consumed and genes, suggesting that food which does not match the host genes is probably one of the major reasons for developing life style diseases. Non-alcoholic fatty liver is becoming a global epidemic leading to substantial morbidity. While various genotyping approaches such as whole exome sequencing using next generation sequencers and genome wide association studies have identified susceptibility loci for non-alcoholic fatty liver disease(NAFLD) including variants in patatin-like phospholipase domain containing 3 and transmembrane 6 superfamily member 2 genes apart from others; nutrient based studies emphasized on a combination of vitamin D, E and omega-3 fatty acids to manage fatty liver disease. However majority of the studies were conducted independent of each other and very few studies explored the interactions between the genetic susceptibility and nutrient interactions. Identifying such interactions will aid in optimizing the nutrition tailor made to an individual’s genetic makeup, thereby aiding in delaying the onset of the disease and its progression. The present topic focuses on studies that identified the genetic susceptibility for NAFLD, nutritional recommendations, and their interactions for better management of NAFLD.

  2. Estimating interaction between genetic and environmental risk factors efficiency of sampling designs within a cohort

    Science.gov (United States)

    Large prospective cohorts originally assembled to study environmental risk factors are increasingly exploited to study gene-environment interactions. Given the cost of genetic studies in large numbers of subjects, being able to select a sub-sample for genotyping that contains most of the information...

  3. Interactions between dietary vitamin E intake and SIRT1 genetic variation influence body mass index

    NARCIS (Netherlands)

    M.C. Zillikens (Carola); J.B.J. van Meurs (Joyce); F. Rivadeneira Ramirez (Fernando); A. Hofman (Albert); B.A. Oostra (Ben); E.J.G. Sijbrands (Eric); J.C.M. Witteman (Jacqueline); H.A.P. Pols (Huib); P. Tikka-Kleemola (Päivi); A.G. Uitterlinden (André)

    2010-01-01

    textabstractBackground: Genetic variation in SIRT1 has been associated with body mass index (BMI) and risk of obesity. SIRT1 may be influenced by diet. Objective: We studied the gene-diet interaction on BMI at the SIRT1 locus. Design: In 4575 elderly men and women in the population-based Rotterdam S

  4. Interactions between dietary vitamin E intake and SIRT1 genetic variation influence body mass index

    NARCIS (Netherlands)

    M.C. Zillikens (Carola); J.B.J. van Meurs (Joyce); F. Rivadeneira Ramirez (Fernando); A. Hofman (Albert); B.A. Oostra (Ben); E.J.G. Sijbrands (Eric); J.C.M. Witteman (Jacqueline); H.A.P. Pols (Huib); P. Tikka-Kleemola (Päivi); A.G. Uitterlinden (André)

    2010-01-01

    textabstractBackground: Genetic variation in SIRT1 has been associated with body mass index (BMI) and risk of obesity. SIRT1 may be influenced by diet. Objective: We studied the gene-diet interaction on BMI at the SIRT1 locus. Design: In 4575 elderly men and women in the population-based Rotterdam

  5. Characterizing the Pyrenophora teres f. maculata – barley interaction using pathogen genetics

    Science.gov (United States)

    Pyrenophora teres f. maculata is the cause of the foliar disease spot form net blotch (SFNB) on barley. To evaluate pathogen genetics underlying the P. teres f. maculata- barley interaction, we developed a 105-progeny population by crossing two globally diverse isolates, one from North Dakota, USA a...

  6. LC-MS/MS-based targeted proteomics quantitatively detects the interaction between p53 and MDM2 in breast cancer.

    Science.gov (United States)

    Zhang, Wen; Zhong, Ting; Chen, Yun

    2017-01-30

    In breast cancer, p53 could be functionally compromised by interaction with several proteins. Among those proteins, MDM2 serves as a pivotal negative regulator and counteracts p53 activation. Thus, the ability to quantitatively and accurately monitor the changes in level of p53-MDM2 interaction with disease state can enable an improved understanding of this protein-protein interaction (PPI), provide a better insight into cancer development and allow the emergence of advanced treatments. However, rare studies have evaluated the quantitative extent of PPI including p53-MDM2 interaction so far. In this study, a LC-MS/MS-based targeted proteomics assay was developed and coupled with co-immunoprecipitation (Co-IP) for the quantification of p53-MDM2 complex. A p53 antibody with the epitope residing at 156-214 residues achieved the greatest IP efficiency. 321KPLDGEYFTLQIR333 (p53) and 327ENWLPEDK334 (MDM2) were selected as surrogate peptides in the targeted analysis. Stable isotope-labeled synthetic peptides were used as internal standards. An LOQ (limit of quantification) of 2ng/mL was obtained. Then, the assay was applied to quantitatively detect total p53, total MDM2 and p53-MDM2 in breast cells and tissue samples. Western blotting was performed for a comparison. Finally, a quantitative time-course analysis in MCF-7 cells with the treatment of nutlin-3 as a PPI inhibitor was also monitored.

  7. Development of quantitative duplex real-time PCR method for screening analysis of genetically modified maize.

    Science.gov (United States)

    Oguchi, Taichi; Onishi, Mari; Minegishi, Yasutaka; Kurosawa, Yasunori; Kasahara, Masaki; Akiyama, Hiroshi; Teshima, Reiko; Futo, Satoshi; Furui, Satoshi; Hino, Akihiro; Kitta, Kazumi

    2009-06-01

    A duplex real-time PCR method was developed for quantitative screening analysis of GM maize. The duplex real-time PCR simultaneously detected two GM-specific segments, namely the cauliflower mosaic virus (CaMV) 35S promoter (P35S) segment and an event-specific segment for GA21 maize which does not contain P35S. Calibration was performed with a plasmid calibrant specially designed for the duplex PCR. The result of an in-house evaluation suggested that the analytical precision of the developed method was almost equivalent to those of simplex real-time PCR methods, which have been adopted as ISO standard methods for the analysis of GMOs in foodstuffs and have also been employed for the analysis of GMOs in Japan. In addition, this method will reduce both the cost and time requirement of routine GMO analysis by half. The high analytical performance demonstrated in the current study would be useful for the quantitative screening analysis of GM maize. We believe the developed method will be useful for practical screening analysis of GM maize, although interlaboratory collaborative studies should be conducted to confirm this.

  8. Genetic influences on type 2 diabetes and metabolic syndrome related quantitative traits in Mauritius.

    Science.gov (United States)

    Jowett, Jeremy B; Diego, Vincent P; Kotea, Navaratnam; Kowlessur, Sudhir; Chitson, Pierrot; Dyer, Thomas D; Zimmet, Paul; Blangero, John

    2009-02-01

    Epidemiological studies report a high prevalence of type 2 diabetes and metabolic syndrome in the island nation of Mauritius. The Mauritius Family Study was initiated to examine heritable factors that contribute to these high rates of prevalence and consists of 400 individuals in 24 large extended multigenerational pedigrees. Anthropometric and biochemical measurements relating to the metabolic syndrome were undertaken in addition to family and lifestyle based information for each individual. Variance components methods were used to determine the heritability of the type 2 diabetes and metabolic syndrome related quantitative traits. The cohort was made up of 218 females (55%) and 182 males with 22% diagnosed with type 2 diabetes and a further 30% having impaired glucose tolerance or impaired fasting glucose. Notably BMI was not significantly increased in those with type 2 diabetes (P= .12), however a significant increase in waist circumference was observed in these groups (P= .02). The heritable proportion of trait variance was substantial and greater than values previously published for hip circumference, LDL and total cholesterol, diastolic and systolic blood pressure and serum creatinine. Height, weight and BMI heritabilities were all in the upper range of those previously reported. The phenotypic characteristics of the Mauritius family cohort are similar to those previously reported in the Mauritian population with a high observed prevalence rate of type 2 diabetes. A high heritability for key type 2 diabetes and metabolic syndrome related phenotypes (range 0.23 to 0.68), suggest the cohort will have utility in identifying genes that influence these quantitative traits.

  9. GENES - a software package for analysis in experimental statistics and quantitative genetics

    Directory of Open Access Journals (Sweden)

    Cosme Damião Cruz

    2013-06-01

    Full Text Available GENES is a software package used for data analysis and processing with different biometricmodels and is essential in genetic studies applied to plant and animal breeding. It allows parameterestimation to analyze biologicalphenomena and is fundamental for the decision-making process andpredictions of success and viability of selection strategies. The program can be downloaded from theInternet (http://www.ufv.br/dbg/genes/genes.htm orhttp://www.ufv.br/dbg/biodata.htm and is available inPortuguese, English and Spanish. Specific literature (http://www.livraria.ufv.br/ and a set of sample filesare also provided, making GENES easy to use. The software is integrated into the programs MS Word, MSExcel and Paint, ensuring simplicity and effectiveness indata import and export ofresults, figures and data.It is also compatible with the free software R and Matlab, through the supply of useful scripts available forcomplementary analyses in different areas, including genome wide selection, prediction of breeding valuesand use of neural networks in genetic improvement.

  10. Simulation of collaborative studies for real-time PCR-based quantitation methods for genetically modified crops.

    Science.gov (United States)

    Watanabe, Satoshi; Sawada, Hiroshi; Naito, Shigehiro; Akiyama, Hiroshi; Teshima, Reiko; Furui, Satoshi; Kitta, Kazumi; Hino, Akihiro

    2013-01-01

    To study impacts of various random effects and parameters of collaborative studies on the precision of quantitation methods of genetically modified (GM) crops, we developed a set of random effects models for cycle time values of a standard curve-based relative real-time PCR that makes use of an endogenous gene sequence as the internal standard. The models and data from a published collaborative study for six GM lines at four concentration levels were used to simulate collaborative studies under various conditions. Results suggested that by reducing the numbers of well replications from three to two, and standard levels of endogenous sequence from five to three, the number of unknown samples analyzable on a 96-well PCR plate in routine analyses could be almost doubled, and still the acceptable repeatability RSD (RSDr crops by real-time PCR and their collaborative studies.

  11. Gene set analyses of genome-wide association studies on 49 quantitative traits measured in a single genetic epidemiology dataset.

    Science.gov (United States)

    Kim, Jihye; Kwon, Ji-Sun; Kim, Sangsoo

    2013-09-01

    Gene set analysis is a powerful tool for interpreting a genome-wide association study result and is gaining popularity these days. Comparison of the gene sets obtained for a variety of traits measured from a single genetic epidemiology dataset may give insights into the biological mechanisms underlying these traits. Based on the previously published single nucleotide polymorphism (SNP) genotype data on 8,842 individuals enrolled in the Korea Association Resource project, we performed a series of systematic genome-wide association analyses for 49 quantitative traits of basic epidemiological, anthropometric, or blood chemistry parameters. Each analysis result was subjected to subsequent gene set analyses based on Gene Ontology (GO) terms using gene set analysis software, GSA-SNP, identifying a set of GO terms significantly associated to each trait (pcorr neuronal or nerve systems.

  12. [Genetic selection of mice for quantitative responsiveness of lymphocytes to phytohemagglutinin].

    Science.gov (United States)

    Stiffel, C; Liacopoulos-Briot, M; Decreusefond, C; Lambert, F

    1977-01-01

    A two-way selection was performed in mice according to the quantitative response of small lymphocytes to the mitogenic activity of phytohaemagglutinin (PHA). The response of inguinal lymph node cells of each mouse to an optimal dose of PHA was measured by 3H-thymidine incorporation using a micro-plate method. Starting from four outbred mouse strains we mated on the one hand mice getting the best response and on the other hand mice getting the poorest response. A progressive separation of the two lines was observed. At the 7th generation a 3-fold difference was found between the two lines. A similar interline difference was observed when concanavalin A (ConA) was used as mitogen. The separation of the two lines was also evident when spleen cells or thymus cells were cultured with PHA or ConA.

  13. Quantitation of Bt-176 maize genomic sequences by surface plasmon resonance-based biospecific interaction analysis of multiplex polymerase chain reaction (PCR).

    Science.gov (United States)

    Feriotto, Giordana; Gardenghi, Sara; Bianchi, Nicoletta; Gambari, Roberto

    2003-07-30

    Surface plasmon resonance (SPR) based biosensors have been described for the identification of genetically modified organisms (GMO) by biospecific interaction analysis (BIA). This paper describes the design and testing of an SPR-based BIA protocol for quantitative determinations of GMOs. Biotinylated multiplex Polymerase Chain Reaction (PCR) products from nontransgenic maize as well as maize powders containing 0.5 and 2% genetically modified Bt-176 sequences were immobilized on different flow cells of a sensor chip. After immobilization, different oligonucleotide probes recognizing maize zein and Bt-176 sequences were injected. The results obtained were compared with Southern blot analysis and with quantitative real-time PCR assays. It was demonstrated that sequential injections of Bt-176 and zein probes to sensor chip flow cells containing multiplex PCR products allow discrimination between PCR performed using maize genomic DNA containing 0.5% Bt-176 sequences and that performed using maize genomic DNA containing 2% Bt-176 sequences. The efficiency of SPR-based BIA in discriminating material containing different amounts of Bt-176 maize is comparable to real-time quantitative PCR and much more reliable than Southern blotting, which in the past has been used for semiquantitative purposes. Furthermore, the approach allows the BIA assay to be repeated several times on the same multiplex PCR product immobilized on the sensor chip, after washing and regeneration of the flow cell. Finally, it is emphasized that the presented strategy to quantify GMOs could be proposed for all of the SPR-based, commercially available biosensors. Some of these optical SPR-based biosensors use, instead of flow-based sensor chips, stirred microcuvettes, reducing the costs of the experimentation.

  14. How can we harness quantitative genetic variation in crop root systems for agricultural improvement?

    Institute of Scientific and Technical Information of China (English)

    Christopher N. Topp; Adam L. Bray

    2016-01-01

    Root systems are a black box obscuring a comprehensive understanding of plant function, from the ecosystem scale down to the individual. In particular, a lack of knowledge about the genetic mechanisms and environmental effects that condition root system growth hinders our ability to develop the next generation of crop plants for improved agricultural productivity and sustainability. We discuss how the methods and metrics we use to quantify root systems can affect our ability to understand them, how we can bridge knowledge gaps and accelerate the derivation of structure-function relationships for roots, and why a detailed mecha-nistic understanding of root growth and function will be important for future agricultural gains.

  15. Functional Divergence of Hsp90 Genetic Interactions in Biofilm and Planktonic Cellular States.

    Directory of Open Access Journals (Sweden)

    Stephanie Diezmann

    Full Text Available Candida albicans is among the most prevalent opportunistic fungal pathogens. Its capacity to cause life-threatening bloodstream infections is associated with the ability to form biofilms, which are intrinsically drug resistant reservoirs for dispersal. A key regulator of biofilm drug resistance and dispersal is the molecular chaperone Hsp90, which stabilizes many signal transducers. We previously identified 226 C. albicans Hsp90 genetic interactors under planktonic conditions, of which 56 are involved in transcriptional regulation. Six of these transcriptional regulators have previously been implicated in biofilm formation, suggesting that Hsp90 genetic interactions identified in planktonic conditions may have functional significance in biofilms. Here, we explored the relationship between Hsp90 and five of these transcription factor genetic interactors: BCR1, MIG1, TEC1, TUP1, and UPC2. We deleted each transcription factor gene in an Hsp90 conditional expression strain, and assessed biofilm formation and morphogenesis. Strikingly, depletion of Hsp90 conferred no additional biofilm defect in the mutants. An interaction was observed in which deletion of BCR1 enhanced filamentation upon reduction of Hsp90 levels. Further, although Hsp90 modulates expression of TEC1, TUP1, and UPC2 in planktonic conditions, it has no impact in biofilms. Lastly, we probed for physical interactions between Hsp90 and Tup1, whose WD40 domain suggests that it might interact with Hsp90 directly. Hsp90 and Tup1 formed a stable complex, independent of temperature or developmental state. Our results illuminate a physical interaction between Hsp90 and a key transcriptional regulator of filamentation and biofilm formation, and suggest that Hsp90 has distinct genetic interactions in planktonic and biofilm cellular states.

  16. Social Organization of Crop Genetic Diversity. The G × E × S Interaction Model

    Directory of Open Access Journals (Sweden)

    Geo Coppens d’Eeckenbrugge

    2011-12-01

    Full Text Available A better knowledge of factors organizing crop genetic diversity in situ increases the efficiency of diversity analyses and conservation strategies, and requires collaboration between social and biological disciplines. Four areas of anthropology may contribute to our understanding of the impact of social factors on crop diversity: ethnobotany, cultural, cognitive and social anthropology. So far, most collaborative studies have been based on ethnobotanical methods, focusing on farmers’ individual motivations and actions, and overlooking the effects of farmer’s social organization per se. After reviewing common shortcomings in studies on sorghum and maize, this article analyzes how social anthropology, through the analysis of intermarriage, residence and seed inheritance practices, can contribute to studies on crop genetic diversity in situ. Crop varieties are thus considered social objects and socially based sampling strategies can be developed. Such an approach is justified because seed exchange is built upon trust and as such seed systems are embedded in a pre-existing social structure and centripetally oriented as a function of farmers’ social identity. The strong analogy between farmers’ cultural differentiation and crop genetic differentiation, both submitted to the same vertical transmission processes, allows proposing a common methodological framework for social anthropology and crop population genetics, where the classical interaction between genetic and environmental factors, G × E, is replaced by a three-way interaction G × E × S, where “S” stands for the social differentiation factors.

  17. Interlaboratory validation of quantitative duplex real-time PCR method for screening analysis of genetically modified maize.

    Science.gov (United States)

    Takabatake, Reona; Koiwa, Tomohiro; Kasahara, Masaki; Takashima, Kaori; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Oguchi, Taichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

    2011-01-01

    To reduce the cost and time required to routinely perform the genetically modified organism (GMO) test, we developed a duplex quantitative real-time PCR method for a screening analysis simultaneously targeting an event-specific segment for GA21 and Cauliflower Mosaic Virus 35S promoter (P35S) segment [Oguchi et al., J. Food Hyg. Soc. Japan, 50, 117-125 (2009)]. To confirm the validity of the method, an interlaboratory collaborative study was conducted. In the collaborative study, conversion factors (Cfs), which are required to calculate the GMO amount (%), were first determined for two real-time PCR instruments, the ABI PRISM 7900HT and the ABI PRISM 7500. A blind test was then conducted. The limit of quantitation for both GA21 and P35S was estimated to be 0.5% or less. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSD(R)). The determined bias and RSD(R) were each less than 25%. We believe the developed method would be useful for the practical screening analysis of GM maize.

  18. Development and validation of an event-specific quantitative PCR method for genetically modified maize MIR162.

    Science.gov (United States)

    Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

    2014-01-01

    A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) maize event, MIR162. We first prepared a standard plasmid for MIR162 quantification. The conversion factor (Cf) required to calculate the genetically modified organism (GMO) amount was empirically determined for two real-time PCR instruments, the Applied Biosystems 7900HT (ABI7900) and the Applied Biosystems 7500 (ABI7500) for which the determined Cf values were 0.697 and 0.635, respectively. To validate the developed method, a blind test was carried out in an interlaboratory study. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr). The determined biases were less than 25% and the RSDr values were less than 20% at all evaluated concentrations. These results suggested that the limit of quantitation of the method was 0.5%, and that the developed method would thus be suitable for practical analyses for the detection and quantification of MIR162.

  19. Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

    Science.gov (United States)

    Dobata, Shigeto

    2012-12-01

    Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

  20. Construction of a genetic linkage map of Thlaspi caerulescens and quantitative trait loci analysis of zinc accumulation.

    Science.gov (United States)

    Assunção, Ana G L; Pieper, Bjorn; Vromans, Jaap; Lindhout, Pim; Aarts, Mark G M; Schat, Henk

    2006-01-01

    Zinc (Zn) hyperaccumulation seems to be a constitutive species-level trait in Thlaspi caerulescens. When compared under conditions of equal Zn availability, considerable variation in the degree of hyperaccumulation is observed among accessions originating from different soil types. This variation offers an excellent opportunity for further dissection of the genetics of this trait. A T. caerulescens intraspecific cross was made between a plant from a nonmetallicolous accession [Lellingen (LE)], characterized by relatively high Zn accumulation, and a plant from a calamine accession [La Calamine (LC)], characterized by relatively low Zn accumulation. Zinc accumulation in roots and shoots segregated in the F3 population. This population was used to construct an LE/LC amplified fragment length polymorphism (AFLP)-based genetic linkage map and to map quantitative trait loci (QTL) for Zn accumulation. Two QTL were identified for root Zn accumulation, with the trait-enhancing alleles being derived from each of the parents, and explaining 21.7 and 16.6% of the phenotypic variation observed in the mapping population. Future development of more markers, based on Arabidopsis orthologous genes localized in the QTL regions, will allow fine-mapping and map-based cloning of the genes underlying the QTL.

  1. Detection of nonauthorized genetically modified organisms using differential quantitative polymerase chain reaction: application to 35S in maize.

    Science.gov (United States)

    Cankar, Katarina; Chauvensy-Ancel, Valérie; Fortabat, Marie-Noelle; Gruden, Kristina; Kobilinsky, André; Zel, Jana; Bertheau, Yves

    2008-05-15

    Detection of nonauthorized genetically modified organisms (GMOs) has always presented an analytical challenge because the complete sequence data needed to detect them are generally unavailable although sequence similarity to known GMOs can be expected. A new approach, differential quantitative polymerase chain reaction (PCR), for detection of nonauthorized GMOs is presented here. This method is based on the presence of several common elements (e.g., promoter, genes of interest) in different GMOs. A statistical model was developed to study the difference between the number of molecules of such a common sequence and the number of molecules identifying the approved GMO (as determined by border-fragment-based PCR) and the donor organism of the common sequence. When this difference differs statistically from zero, the presence of a nonauthorized GMO can be inferred. The interest and scope of such an approach were tested on a case study of different proportions of genetically modified maize events, with the P35S promoter as the Cauliflower Mosaic Virus common sequence. The presence of a nonauthorized GMO was successfully detected in the mixtures analyzed and in the presence of (donor organism of P35S promoter). This method could be easily transposed to other common GMO sequences and other species and is applicable to other detection areas such as microbiology.

  2. A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models

    Directory of Open Access Journals (Sweden)

    Brian B. Haines

    2009-01-01

    Full Text Available Two genetically engineered, conditional mouse models of lung tumor formation, K-rasLSL-G12D and K-rasLSL-G12D/p53LSL-R270H, are commonly used to model human lung cancer. Developed by Tyler Jacks and colleagues, these models have been invaluable to study in vivo lung cancer initiation and progression in a genetically and physiologically relevant context. However, heterogeneity, multiplicity and complexity of tumor formation in these models make it challenging to monitor tumor growth in vivo and have limited the application of these models in oncology drug discovery. Here, we describe a novel analytical method to quantitatively measure total lung tumor burden in live animals using micro-computed tomography imaging. Applying this methodology, we studied the kinetics of tumor development and response to targeted therapy in vivo in K-ras and K-ras/p53 mice. Consistent with previous reports, lung tumors in both models developed in a time- and dose (Cre recombinase-dependent manner. Furthermore, the compound K-rasLSL-G12D/p53LSL-R270H mice developed tumors faster and more robustly than mice harboring a single K-rasLSL-G12D oncogene, as expected. Erlotinib, a small molecule inhibitor of the epidermal growth factor receptor, significantly inhibited tumor growth in K-rasLSL-G12D/p53LSL-R270H mice. These results demonstrate that this novel imaging technique can be used to monitor both tumor progression and response to treatment and therefore supports a broader application of these genetically engineered mouse models in oncology drug discovery and development.

  3. Quantitative trait locus mapping with background control in genetic populations of clonal F1 and double cross.

    Science.gov (United States)

    Zhang, Luyan; Li, Huihui; Ding, Junqiang; Wu, Jianyu; Wang, Jiankang

    2015-12-01

    In this study, we considered five categories of molecular markers in clonal F1 and double cross populations, based on the number of distinguishable alleles and the number of distinguishable genotypes at the marker locus. Using the completed linkage maps, incomplete and missing markers were imputed as fully informative markers in order to simplify the linkage mapping approaches of quantitative trait genes. Under the condition of fully informative markers, we demonstrated that dominance effect between the female and male parents in clonal F1 and double cross populations can cause the interactions between markers. We then developed an inclusive linear model that includes marker variables and marker interactions so as to completely control additive effects of the female and male parents, as well as the dominance effect between the female and male parents. The linear model was finally used for background control in inclusive composite interval mapping (ICIM) of quantitative trait locus (QTL). The efficiency of ICIM was demonstrated by extensive simulations and by comparisons with simple interval mapping, multiple-QTL models and composite interval mapping. Finally, ICIM was applied in one actual double cross population to identify QTL on days to silking in maize.

  4. Unraveling the environmental and genetic interactions in atherosclerosis: Central role of the gut microbiota.

    Science.gov (United States)

    Org, Elin; Mehrabian, Margarete; Lusis, Aldons J

    2015-08-01

    Recent studies have convincingly linked gut microbiota to traits relevant to atherosclerosis, such as insulin resistance, dyslipidemia and inflammation, and have revealed novel disease pathways involving microbe-derived metabolites. These results have important implications for understanding how environmental and genetic factors act together to influence cardiovascular disease (CVD) risk. Thus, dietary constituents are not only absorbed and metabolized by the host but they also perturb the gut microbiota, which in turn influence host metabolism and inflammation. It also appears that host genetics helps to shape the gut microbiota community. Here, we discuss challenges in understanding these interactions and the role they play in CVD.

  5. Unraveling the environmental and genetic interactions in atherosclerosis: Central role of the gut microbiota

    Science.gov (United States)

    Org, Elin; Mehrabian, Margarete; Lusis, Aldons J.

    2015-01-01

    Recent studies have convincingly linked gut microbiota to traits relevant to atherosclerosis, such as insulin resistance, dyslipidemia and inflammation, and have revealed novel disease pathways involving microbe-derived metabolites. These results have important implications for understanding how environmental and genetic factors act together to influence cardiovascular disease (CVD) risk. Thus, dietary constituents are not only absorbed and metabolized by the host but they also perturb the gut microbiota, which in turn influence host metabolism and inflammation. It also appears that host genetics helps to shape the gut microbiota community. Here, we discuss challenges in understanding these interactions and the role they play in CVD. PMID:26071662

  6. Genetic Identification of Quantitative Trait Loci for Contents of Mineral Nutrients in Rice Grain

    Institute of Scientific and Technical Information of China (English)

    Ana Luisa Garcia-Oliveira; Lubin Tan; Yongcai Fu; Chuanqing Sun

    2009-01-01

    In present study, Fe, Zn, Mn, Cu, Ca, Mg, P and K contents of 85 Introgression linee (ILs) derived from a cross between an elite indica cultivar Teqing and the wild rice (Oryza rufipogon) were measured by inductively coupled argon plasma (ICAP) spectrometry. Substantial variation was observed for all traits and most of the mineral elements were significantly positive correlated or independent except for Fe with Cu. A total of 31 putative quantitative trait loci (QTLs) were detected for these eight mineral elements by single point analysis. Wild rice (O. rufipogon) contributed favorable alleles for most of the QTLs (26 QTLs), and chromosomes 1, 9 and 12 exhibited 14 QTLs (45%) for these traits. One major effect of QTL for zinc content accounted for the largest proportion of phenotypic variation (11%-19%) was detected near the simple sequence repeats marker RM152 on chromosome 8. The co-locations of QTLs for some mineral elements observed in this mapping population suggested the relationship was at a molecular level among these traits and could be helpful for simultaneous improvement of these traits in rice grain by marker assisted selection.

  7. Genetic selection of mice for quantitative responsiveness of lymphocytes to phytohemagglutinin.

    Science.gov (United States)

    Stiffel, C; Liacopoulos-Briot, M; Decreusefond, C; Lambert, F

    1977-05-01

    A two-way selection was performed in mice according to the quantitative in vitro response of lymph node lymphocytes to the mitogenic activity of phytohemagglutinin (PHA). The foundation population was composed of outbred mice produced by reciprocal mating of equal numbers of mice from four different colonies. The selective breeding was carried out by mating of mice at each generation giving the best or the lowest response, respectively. The progressive interline separation produced by 6 generations of selective breeding demonstrates that responsiveness to PHA is submitted to polygenic regulation. The heritability of the character investigated is 0.28 +/- 0.08. The interline separation is also found with another T mitogen, concanavalin A (Con A). In spleen cells PHA and Con A produce a similar interline difference. In contrast, the purified protein derivative of tuberculin (PPD) stimulated both lines equally, and E. coli lipopolysaccharide gave only a slightly higher response in high line. This finding implies that our selection based upon response to PHA did not influence B cell function.

  8. Quantitative criteria for improving performance of buccal DNA for high-throughput genetic analysis

    Directory of Open Access Journals (Sweden)

    Woo Jessica G

    2012-08-01

    Full Text Available Abstract Background DNA from buccal brush samples is being used for high-throughput analyses in a variety of applications, but the impact of sample type on genotyping success and downstream statistical analysis remains unclear. The objective of the current study was to determine laboratory predictors of genotyping failure among buccal DNA samples, and to evaluate the successfully genotyped results with respect to analytic quality control metrics. Sample and genotyping characteristics were compared between buccal and blood samples collected in the population-based Genetic and Environmental Risk Factors for Hemorrhagic Stroke (GERFHS study (https://gerfhs.phs.wfubmc.edu/public/index.cfm. Results Seven-hundred eight (708 buccal and 142 blood DNA samples were analyzed for laboratory-based and analysis metrics. Overall genotyping failure rates were not statistically different between buccal (11.3% and blood (7.0%, p = 0.18 samples; however, both the Contrast Quality Control (cQC rate and the dynamic model (DM call rates were lower among buccal DNA samples (p  Conclusions We identified a buccal sample characteristic, a ratio of ds/total DNA

  9. Breeding maize as biogas substrate in Central Europe: I. Quantitative-genetic parameters for testcross performance.

    Science.gov (United States)

    Grieder, Christoph; Dhillon, Baldev S; Schipprack, Wolfgang; Melchinger, Albrecht E

    2012-04-01

    Biofuels have gained importance recently and the use of maize biomass as substrate in biogas plants for production of methane has increased tremendously in Germany. The objectives of our research were to (1) estimate variance components and heritability for different traits relevant to biogas production in testcrosses (TCs) of maize, (2) study correlations among traits, and (3) discuss strategies to breed maize as a substrate for biogas fermenters. We evaluated 570 TCs of 285 diverse dent maize lines crossed with two flint single-cross testers in six environments. Data were recorded on agronomic and quality traits, including dry matter yield (DMY), methane fermentation yield (MFY), and methane yield (MY), the product of DMY and MFY, as the main target trait. Estimates of variance components showed general combining ability (GCA) to be the major source of variation. Estimates of heritability exceeded 0.67 for all traits and were even much greater in most instances. Methane yield was perfectly correlated with DMY but not with MFY, indicating that variation in MY is primarily determined by DMY. Further, DMY had a larger heritability and coefficient of genetic variation than MFY. Hence, for improving MY, selection should primarily focus on DMY rather than MFY. Further, maize breeding for biogas production may diverge from that for forage production because in the former case, quality traits seem to be of much lower importance.

  10. Interactions between Gut Microbiota, Host Genetics and Diet Modulate the Predisposition to Obesity and Metabolic Syndrome.

    Science.gov (United States)

    Ussar, Siegfried; Griffin, Nicholas W; Bezy, Olivier; Fujisaka, Shiho; Vienberg, Sara; Softic, Samir; Deng, Luxue; Bry, Lynn; Gordon, Jeffrey I; Kahn, C Ronald

    2015-09-01

    Obesity, diabetes, and metabolic syndrome result from complex interactions between genetic and environmental factors, including the gut microbiota. To dissect these interactions, we utilized three commonly used inbred strains of mice-obesity/diabetes-prone C57Bl/6J mice, obesity/diabetes-resistant 129S1/SvImJ from Jackson Laboratory, and obesity-prone but diabetes-resistant 129S6/SvEvTac from Taconic-plus three derivative lines generated by breeding these strains in a new, common environment. Analysis of metabolic parameters and gut microbiota in all strains and their environmentally normalized derivatives revealed strong interactions between microbiota, diet, breeding site, and metabolic phenotype. Strain-dependent and strain-independent correlations were found between specific microbiota and phenotypes, some of which could be transferred to germ-free recipient animals by fecal transplantation. Environmental reprogramming of microbiota resulted in 129S6/SvEvTac becoming obesity resistant. Thus, development of obesity/metabolic syndrome is the result of interactions between gut microbiota, host genetics, and diet. In permissive genetic backgrounds, environmental reprograming of microbiota can ameliorate development of metabolic syndrome. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. Phosphorus and Nitrogen Interactions in Field-Grown Soybean as Related to Genetic Attributes of Root Morphological and Nodular Traits

    Institute of Scientific and Technical Information of China (English)

    Rui-Bin KUANG; Hong LIAO; Xiao-Long YAN; Ying-Shan DONG

    2005-01-01

    Two field experiments with different soybean (Glycine max L.) materials were conducted to investigate the interactions between phosphorus (P) and nitrogen (N) as related to the genetic attributes of root morphological and nodular traits. In experiment one, 13 cultivated soybean varieties were grown in a field with relatively low soil P and N availability. P application with 160 kg P/hm2 as triple superphosphate produced a significant simultaneous increase in the content of both P and N in shoot, demonstrating positive P and N interactions. The addition of P also increased root dry weight, root nodule number, nodule mass, nodule size, and nodulation index, but decreased root length and root surface area, indicating that P may affect N nutrition in soybean through a number of root morphological and nodular traits. Interestingly,like P content, N content appeared to be more correlated with root morphological traits (root weight, root length, and root surface area) than with root nodular traits (nodule number, nodule size, nodule mass, and nodulation index) at both P levels, implying that N taken up by the roots may contribute more to the plant N status than biological N2 fixation under the present experimental conditions. In experiment two, 57 soybean lines of a recombinant inbred line (RIL) population derived from a cross between a cultivated variety and a wild genotype were grown on another field site with moderately sufficient P and N levels to further characterize the genetic attributes of root morphological and nodular traits and their relationships with P and N interactions. The results indicated that all morphological and nodular traits measured continually segregated in the RIL population with a normal distribution of the phenotypic values, indicating that these traits are possibly controlled by quantitative trait loci (QTLs). Genetic analysis revealed that all these root traits had relatively low heritabilities (h2b=74.12, 70.65, 73.76, 56.34, 52.59, and 52

  12. Quantitative secretome analysis reveals the interactions between epithelia and tumor cells by in vitro modulating colon cancer microenvironment.

    Science.gov (United States)

    Zeng, Xiao; Yang, Pengbo; Chen, Bing; Jin, Xuewen; Liu, Yuling; Zhao, Xia; Liang, Shufang

    2013-08-26

    In tumor microenvironment, interactions among multiple cell types are critical for cancer progression. Secreted proteins are responsible for crosstalk among these cells within tumor microenvironment. To elucidate the interactions of tumor and epithelia, we co-cultured colon cancer cell line HT29 with normal human colon mucosal epithelial cell line NCM460 to mimic tumor microenvironment in vitro and investigated the differential expression pattern of secretome. A quantitative proteomics approach based on stable isotope labeling by amino acids in cell culture (SILAC) and LC-mass spectrometry was used for secretome analysis. Totally 45 proteins were altered over 2-fold in co-cultured cellular supernatants between equal amounts of NCM460 and HT29 cells, compared with mono-cultured conditions. These differential secreted proteins involve in multiple tumor-associated biological functions. The secretion level and acting pattern of acrogranin, IGFBP6 and vimentin were changed along with different co-cultured cell number ratios between NCM460 and HT29 cells, simulating early, middle or advanced stage of colon cancer. Therefore, a quantitative secretome profiling based on a co-culture system can track secreted protein changes and their associated biological roles between tumor and epithelia, which gives a new insight on communications between tumor and epithelia as well as cancer biotherapy by inhibiting cell interactions. Tumor microenvironment is a complex system and comprised of cancer cells and host stromal cells. The growth and progression of tumor have been recognized were affected by multidirectional interactions of secreted proteins (secretome), which were produced by the cells within tumor microenvironment. Focus on general secreted molecules of living cells via proteomic tools, is promising for investigating cell communication. Stable isotope labeling by amino acids in cell culture (SILAC) is a metabolic labeling strategy for quantitative analysis, which is gaining

  13. Genetics

    Science.gov (United States)

    ... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...

  14. Automated, quantitative cognitive/behavioral screening of mice: for genetics, pharmacology, animal cognition and undergraduate instruction.

    Science.gov (United States)

    Gallistel, C R; Balci, Fuat; Freestone, David; Kheifets, Aaron; King, Adam

    2014-02-26

    We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be

  15. Quantitative proteomic analysis of the interaction between the endophytic plant-growth-promoting bacterium Gluconacetobacter diazotrophicus and sugarcane.

    Science.gov (United States)

    Lery, Letícia M S; Hemerly, Adriana S; Nogueira, Eduardo M; von Krüger, Wanda M A; Bisch, Paulo M

    2011-05-01

    Gluconacetobacter diazotrophicus is a plant-growth-promoting bacterium that colonizes sugarcane. In order to investigate molecular aspects of the G. diazotrophicus-sugarcane interaction, we performed a quantitative mass spectrometry-based proteomic analysis by (15)N metabolic labeling of bacteria, root samples, and co-cultures. Overall, more than 400 proteins were analyzed and 78 were differentially expressed between the plant-bacterium interaction model and control cultures. A comparative analysis of the G. diazotrophicus in interaction with two distinct genotypes of sugarcane, SP70-1143 and Chunee, revealed proteins with fundamental roles in cellular recognition. G. diazotrophicus presented proteins involved in adaptation to atypical conditions and signaling systems during the interaction with both genotypes. However, SP70-1143 and Chunee, sugarcane genotypes with high and low contribution of biological nitrogen fixation, showed divergent responses in contact with G. diazotrophicus. The SP70-1143 genotype overexpressed proteins from signaling cascades and one from a lipid metabolism pathway, whereas Chunee differentially synthesized proteins involved in chromatin remodeling and protein degradation pathways. In addition, we have identified 30 bacterial proteins in the roots of the plant samples; from those, nine were specifically induced by plant signals. This is the first quantitative proteomic analysis of a bacterium-plant interaction, which generated insights into early signaling of the G. diazotrophicus-sugarcane interaction.

  16. Interactive Genetic Algorithm - An Adaptive and Interactive Decision Support Framework for Design of Optimal Groundwater Monitoring Plans

    Science.gov (United States)

    Babbar-Sebens, M.; Minsker, B. S.

    2006-12-01

    that met the DM's preference criteria, therefore allowing the expert to select among several strong candidate designs depending on her/his LTM budget, c) two of the methodologies - Case-Based Micro Interactive Genetic Algorithm (CBMIGA) and Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) - were also able to assist in controlling human fatigue and adapt to the DM's learning process.

  17. Interactive computer program for learning genetic principles of segregation and independent assortment through meiosis.

    Science.gov (United States)

    Yang, Xiaoli; Ge, Rong; Yang, Yufei; Shen, Hao; Li, Yingjie; Tseng, Charles C

    2009-01-01

    Teaching fundamental principles of genetics such as segregation and independent assortment of genes could be challenging for high school and college biology instructors. Students without thorough knowledge in meiosis often end up of frustration and failure in genetics courses. Although all textbooks and laboratory manuals have excellent graphic demonstrations and photographs of meiotic process, students may not always master the concept due to the lack of hands-on exercise. In response to the need for an effective lab exercise to understand the segregation of allelic genes and the independent assortment of the unlinked genes, we developed an interactive program for students to manually manipulate chromosome models and visualize each major step of meiosis so that these two genetic principles can be thoroughly understood.

  18. A non-parametric mixture model for genome-enabled prediction of genetic value for a quantitative trait.

    Science.gov (United States)

    Gianola, Daniel; Wu, Xiao-Lin; Manfredi, Eduardo; Simianer, Henner

    2010-10-01

    A Bayesian nonparametric form of regression based on Dirichlet process priors is adapted to the analysis of quantitative traits possibly affected by cryptic forms of gene action, and to the context of SNP-assisted genomic selection, where the main objective is to predict a genomic signal on phenotype. The procedure clusters unknown genotypes into groups with distinct genetic values, but in a setting in which the number of clusters is unknown a priori, so that standard methods for finite mixture analysis do not work. The central assumption is that genetic effects follow an unknown distribution with some "baseline" family, which is a normal process in the cases considered here. A Bayesian analysis based on the Gibbs sampler produces estimates of the number of clusters, posterior means of genetic effects, a measure of credibility in the baseline distribution, as well as estimates of parameters of the latter. The procedure is illustrated with a simulation representing two populations. In the first one, there are 3 unknown QTL, with additive, dominance and epistatic effects; in the second, there are 10 QTL with additive, dominance and additive × additive epistatic effects. In the two populations, baseline parameters are inferred correctly. The Dirichlet process model infers the number of unique genetic values correctly in the first population, but it produces an understatement in the second one; here, the true number of clusters is over 900, and the model gives a posterior mean estimate of about 140, probably because more replication of genotypes is needed for correct inference. The impact on inferences of the prior distribution of a key parameter (M), and of the extent of replication, was examined via an analysis of mean body weight in 192 paternal half-sib families of broiler chickens, where each sire was genotyped for nearly 7,000 SNPs. In this small sample, it was found that inference about the number of clusters was affected by the prior distribution of M. For a

  19. Quantitative measurements and modeling of cargo–motor interactions during fast transport in the living axon

    Science.gov (United States)

    Seamster, Pamela E; Loewenberg, Michael; Pascal, Jennifer; Chauviere, Arnaud; Gonzales, Aaron; Cristini, Vittorio; Bearer, Elaine L

    2013-01-01

    The kinesins have long been known to drive microtubule-based transport of sub-cellular components, yet the mechanisms of their attachment to cargo remain a mystery. Several different cargo-receptors have been proposed based on their in vitro binding affinities to kinesin-1. Only two of these—phosphatidyl inositol, a negatively charged lipid, and the carboxyl terminus of the amyloid precursor protein (APP-C), a trans-membrane protein—have been reported to mediate motility in living systems. A major question is how these many different cargo, receptors and motors interact to produce the complex choreography of vesicular transport within living cells. Here we describe an experimental assay that identifies cargo–motor receptors by their ability to recruit active motors and drive transport of exogenous cargo towards the synapse in living axons. Cargo is engineered by derivatizing the surface of polystyrene fluorescent nanospheres (100 nm diameter) with charged residues or with synthetic peptides derived from candidate motor receptor proteins, all designed to display a terminal COOH group. After injection into the squid giant axon, particle movements are imaged by laser-scanning confocal time-lapse microscopy. In this report we compare the motility of negatively charged beads with APP-C beads in the presence of glycine-conjugated non-motile beads using new strategies to measure bead movements. The ensuing quantitative analysis of time-lapse digital sequences reveals detailed information about bead movements: instantaneous and maximum velocities, run lengths, pause frequencies and pause durations. These measurements provide parameters for a mathematical model that predicts the spatiotemporal evolution of distribution of the two different types of bead cargo in the axon. The results reveal that negatively charged beads differ from APP-C beads in velocity and dispersion, and predict that at long time points APP-C will achieve greater progress towards the presynaptic

  20. Quantitative measurements and modeling of cargo-motor interactions during fast transport in the living axon

    Science.gov (United States)

    Seamster, Pamela E.; Loewenberg, Michael; Pascal, Jennifer; Chauviere, Arnaud; Gonzales, Aaron; Cristini, Vittorio; Bearer, Elaine L.

    2012-10-01

    The kinesins have long been known to drive microtubule-based transport of sub-cellular components, yet the mechanisms of their attachment to cargo remain a mystery. Several different cargo-receptors have been proposed based on their in vitro binding affinities to kinesin-1. Only two of these—phosphatidyl inositol, a negatively charged lipid, and the carboxyl terminus of the amyloid precursor protein (APP-C), a trans-membrane protein—have been reported to mediate motility in living systems. A major question is how these many different cargo, receptors and motors interact to produce the complex choreography of vesicular transport within living cells. Here we describe an experimental assay that identifies cargo-motor receptors by their ability to recruit active motors and drive transport of exogenous cargo towards the synapse in living axons. Cargo is engineered by derivatizing the surface of polystyrene fluorescent nanospheres (100 nm diameter) with charged residues or with synthetic peptides derived from candidate motor receptor proteins, all designed to display a terminal COOH group. After injection into the squid giant axon, particle movements are imaged by laser-scanning confocal time-lapse microscopy. In this report we compare the motility of negatively charged beads with APP-C beads in the presence of glycine-conjugated non-motile beads using new strategies to measure bead movements. The ensuing quantitative analysis of time-lapse digital sequences reveals detailed information about bead movements: instantaneous and maximum velocities, run lengths, pause frequencies and pause durations. These measurements provide parameters for a mathematical model that predicts the spatiotemporal evolution of distribution of the two different types of bead cargo in the axon. The results reveal that negatively charged beads differ from APP-C beads in velocity and dispersion, and predict that at long time points APP-C will achieve greater progress towards the presynaptic

  1. A common genetic determinism for sensitivities to soil water deficit and evaporative demand: meta-analysis of quantitative trait Loci and introgression lines of maize.

    Science.gov (United States)

    Welcker, Claude; Sadok, Walid; Dignat, Grégoire; Renault, Morgan; Salvi, Silvio; Charcosset, Alain; Tardieu, François

    2011-10-01

    Evaporative demand and soil water deficit equally contribute to water stress and to its effect on plant growth. We have compared the genetic architectures of the sensitivities of maize (Zea mays) leaf elongation rate with evaporative demand and soil water deficit. The former was measured via the response to leaf-to-air vapor pressure deficit in well-watered plants, the latter via the response to soil water potential in the absence of evaporative demand. Genetic analyses of each sensitivity were performed over 21 independent experiments with (1) three mapping populations, with temperate or tropical materials, (2) one population resulting from the introgression of a tropical drought-tolerant line in a temperate line, and (3) two introgression libraries genetically independent from mapping populations. A very large genetic variability was observed for both sensitivities. Some lines maintained leaf elongation at very high evaporative demand or water deficit, while others stopped elongation in mild conditions. A complex architecture arose from analyses of mapping populations, with 19 major meta-quantitative trait loci involving strong effects and/or more than one mapping population. A total of 68% of those quantitative trait loci affected sensitivities to both evaporative demand and soil water deficit. In introgressed lines, 73% of the tested genomic regions affected both sensitivities. To our knowledge, this study is the first genetic demonstration that hydraulic processes, which drive the response to evaporative demand, also have a large contribution to the genetic variability of plant growth under water deficit in a large range of genetic material.

  2. Interactions between Gut Microbiota, Host Genetics and Diet Modulate the Predisposition to Obesity and Metabolic Syndrome

    OpenAIRE

    Ussar, Siegfried; Griffin, Nicholas W.; Bezy, Olivier; Fujisaka, Shiho; Vienberg, Sara; Softic, Samir; Deng, Luxue; Bry, Lynn; Gordon, Jeffrey I.; Kahn, C. Ronald

    2015-01-01

    Obesity, diabetes and metabolic syndrome result from complex interactions between genetic and environmental factors, including the gut microbiota. To dissect these interactions, we utilized three commonly-used inbred strains of mice – obesity/diabetes-prone C57Bl/6J mice, obesity/diabetes-resistant 129S1/SvImJ, from Jackson Laboratory and obesity-prone, but diabetes resistant 129S6/SvEvTac from Taconic - plus three derivative lines generated by breeding these strains in a new, common environm...

  3. A mitochondrial-focused genetic interaction map reveals a scaffold-like complex required for inner membrane organization in mitochondria.

    Science.gov (United States)

    Hoppins, Suzanne; Collins, Sean R; Cassidy-Stone, Ann; Hummel, Eric; Devay, Rachel M; Lackner, Laura L; Westermann, Benedikt; Schuldiner, Maya; Weissman, Jonathan S; Nunnari, Jodi

    2011-10-17

    To broadly explore mitochondrial structure and function as well as the communication of mitochondria with other cellular pathways, we constructed a quantitative, high-density genetic interaction map (the MITO-MAP) in Saccharomyces cerevisiae. The MITO-MAP provides a comprehensive view of mitochondrial function including insights into the activity of uncharacterized mitochondrial proteins and the functional connection between mitochondria and the ER. The MITO-MAP also reveals a large inner membrane-associated complex, which we term MitOS for mitochondrial organizing structure, comprised of Fcj1/Mitofilin, a conserved inner membrane protein, and five additional components. MitOS physically and functionally interacts with both outer and inner membrane components and localizes to extended structures that wrap around the inner membrane. We show that MitOS acts in concert with ATP synthase dimers to organize the inner membrane and promote normal mitochondrial morphology. We propose that MitOS acts as a conserved mitochondrial skeletal structure that differentiates regions of the inner membrane to establish the normal internal architecture of mitochondria.

  4. Genotype × Environment Interaction in Psychiatric Genetics: Deep Truth or Thin Ice?

    Science.gov (United States)

    Eaves, Lindon

    2017-06-01

    There continues to be significant investment in the detection of genotype × environment interaction (G × E) in psychiatric genetics. The implications of the method of assessment for the genetic analysis of psychiatric disorders are examined for simulated twin data on symptom scores and environmental covariates. Additive and independent genetic and environmental risks were simulated for 10,000 monozygotic (MZ) and 10,000 dizygotic (DZ) twin pairs and the 'subjects' administered typical simulated checklists of clinical symptoms and environmental factors. A variety of standard tests for G × E were applied to the simulated additive risk scores, sum scores derived from the checklists and transformed sum scores. All analyses revealed no evidence for G × E for latent risk but marked evidence for G × E and other effects of modulation in the sum scores. These effects were all removed by transformation. An integrated genetic and psychometric model, accounting for both the causes of latent liability and a theory of measurement, was fitted to a sample of the simulated sum-score data and showed that there was no significant modulation of the parameters of the genetic model by environmental covariates (i.e., no G × E). Claims to detect G × E based on analytical methods that ignore the theory of measurement must be subjected to greater scrutiny prior to publication.

  5. The Genetic Landscape of a Cell

    Science.gov (United States)

    Bellay, Jeremy; Kim, Yungil; Spear, Eric D.; Sevier, Carolyn S.; Ding, Huiming; Koh, Judice L.Y.; Toufighi, Kiana; Mostafavi, Sara; Prinz, Jeany; St. Onge, Robert P.; VanderSluis, Benjamin; Makhnevych, Taras; Vizeacoumar, Franco J.; Alizadeh, Solmaz; Bahr, Sondra; Brost, Renee L.; Chen, Yiqun; Cokol, Murat; Deshpande, Raamesh; Li, Zhijian; Lin, Zhen-Yuan; Liang, Wendy; Marback, Michaela; Paw, Jadine; San Luis, Bryan-Joseph; Shuteriqi, Ermira; Hin Yan Tong, Amy; van Dyk, Nydia; Wallace, Iain M.; Whitney, Joseph A.; Weirauch, Matthew T.; Zhong, Guoqing; Zhu, Hongwei; Houry, Walid A.; Brudno, Michael; Ragibizadeh, Sasan; Papp, Balázs; Pál, Csaba; Roth, Frederick P.; Giaever, Guri; Nislow, Corey; Troyanskaya, Olga G.; Bussey, Howard; Bader, Gary D.; Gingras, Anne-Claude; Morris, Quaid D.; Kim, Philip M.; Kaiser, Chris A.; Myers, Chad L.; Andrews, Brenda J.; Boone, Charles

    2017-01-01

    A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification. PMID:20093466

  6. Drosophila domino Exhibits Genetic Interactions with a Wide Spectrum of Chromatin Protein-Encoding Loci.

    Science.gov (United States)

    Ellis, Kaitlyn; Friedman, Chloe; Yedvobnick, Barry

    2015-01-01

    The Drosophila domino gene encodes protein of the SWI2/SNF2 family that has widespread roles in transcription, replication, recombination and DNA repair. Here, the potential relationship of Domino protein to other chromatin-associated proteins has been investigated through a genetic interaction analysis. We scored for genetic modification of a domino wing margin phenotype through coexpression of RNAi directed against a set of previously characterized and more newly characterized chromatin-encoding loci. A set of other SWI2/SNF2 loci were also assayed for interaction with domino. Our results show that the majority of tested loci exhibit synergistic enhancement or suppression of the domino wing phenotype. Therefore, depression in domino function sensitizes the wing margin to alterations in the activity of numerous chromatin components. In several cases the genetic interactions are associated with changes in the level of cell death measured across the dorsal-ventral margin of the wing imaginal disc. These results highlight the broad realms of action of many chromatin proteins and suggest significant overlap with Domino function in fundamental cell processes, including cell proliferation, cell death and cell signaling.

  7. Genetic control of environmental variation of two quantitative traits of Drosophila melanogaster revealed by whole-genome sequencing

    DEFF Research Database (Denmark)

    Sørensen, Peter; de los Campos, Gustavo; Morgante, Fabio

    2015-01-01

    Genetic studies usually focus on quantifying and understanding the existence of genetic control on expected phenotypic outcomes. However, there is compelling evidence suggesting the existence of genetic control at the level of environmental variability, with some genotypes exhibiting more stable ...

  8. The TissueNet v.2 database: A quantitative view of protein-protein interactions across human tissues

    Science.gov (United States)

    Basha, Omer; Barshir, Ruth; Sharon, Moran; Lerman, Eugene; Kirson, Binyamin F.; Hekselman, Idan; Yeger-Lotem, Esti

    2017-01-01

    Knowledge of the molecular interactions of human proteins within tissues is important for identifying their tissue-specific roles and for shedding light on tissue phenotypes. However, many protein–protein interactions (PPIs) have no tissue-contexts. The TissueNet database bridges this gap by associating experimentally-identified PPIs with human tissues that were shown to express both pair-mates. Users can select a protein and a tissue, and obtain a network view of the query protein and its tissue-associated PPIs. TissueNet v.2 is an updated version of the TissueNet database previously featured in NAR. It includes over 40 human tissues profiled via RNA-sequencing or protein-based assays. Users can select their preferred expression data source and interactively set the expression threshold for determining tissue-association. The output of TissueNet v.2 emphasizes qualitative and quantitative features of query proteins and their PPIs. The tissue-specificity view highlights tissue-specific and globally-expressed proteins, and the quantitative view highlights proteins that were differentially expressed in the selected tissue relative to all other tissues. Together, these views allow users to quickly assess the unique versus global functionality of query proteins. Thus, TissueNet v.2 offers an extensive, quantitative and user-friendly interface to study the roles of human proteins across tissues. TissueNet v.2 is available at http://netbio.bgu.ac.il/tissuenet. PMID:27899616

  9. Genetic interactions between planar cell polarity genes cause diverse neural tube defects in mice

    Directory of Open Access Journals (Sweden)

    Jennifer N. Murdoch

    2014-10-01

    Full Text Available Neural tube defects (NTDs are among the commonest and most severe forms of developmental defect, characterized by disruption of the early embryonic events of central nervous system formation. NTDs have long been known to exhibit a strong genetic dependence, yet the identity of the genetic determinants remains largely undiscovered. Initiation of neural tube closure is disrupted in mice homozygous for mutations in planar cell polarity (PCP pathway genes, providing a strong link between NTDs and PCP signaling. Recently, missense gene variants have been identified in PCP genes in humans with NTDs, although the range of phenotypes is greater than in the mouse mutants. In addition, the sequence variants detected in affected humans are heterozygous, and can often be detected in unaffected individuals. It has been suggested that interactions between multiple heterozygous gene mutations cause the NTDs in humans. To determine the phenotypes produced in double heterozygotes, we bred mice with all three pairwise combinations of Vangl2Lp, ScribCrc and Celsr1Crsh mutations, the most intensively studied PCP mutants. The majority of double-mutant embryos had open NTDs, with the range of phenotypes including anencephaly and spina bifida, therefore reflecting the defects observed in humans. Strikingly, even on a uniform genetic background, variability in the penetrance and severity of the mutant phenotypes was observed between the different double-heterozygote combinations. Phenotypically, Celsr1Crsh;Vangl2Lp;ScribCrc triply heterozygous mutants were no more severe than doubly heterozygous or singly homozygous mutants. We propose that some of the variation between double-mutant phenotypes could be attributed to the nature of the protein disruption in each allele: whereas ScribCrc is a null mutant and produces no Scrib protein, Celsr1Crsh and Vangl2Lp homozygotes both express mutant proteins, consistent with dominant effects. The variable outcomes of these genetic

  10. Genetic interactions between planar cell polarity genes cause diverse neural tube defects in mice.

    Science.gov (United States)

    Murdoch, Jennifer N; Damrau, Christine; Paudyal, Anju; Bogani, Debora; Wells, Sara; Greene, Nicholas D E; Stanier, Philip; Copp, Andrew J

    2014-10-01

    Neural tube defects (NTDs) are among the commonest and most severe forms of developmental defect, characterized by disruption of the early embryonic events of central nervous system formation. NTDs have long been known to exhibit a strong genetic dependence, yet the identity of the genetic determinants remains largely undiscovered. Initiation of neural tube closure is disrupted in mice homozygous for mutations in planar cell polarity (PCP) pathway genes, providing a strong link between NTDs and PCP signaling. Recently, missense gene variants have been identified in PCP genes in humans with NTDs, although the range of phenotypes is greater than in the mouse mutants. In addition, the sequence variants detected in affected humans are heterozygous, and can often be detected in unaffected individuals. It has been suggested that interactions between multiple heterozygous gene mutations cause the NTDs in humans. To determine the phenotypes produced in double heterozygotes, we bred mice with all three pairwise combinations of Vangl2(Lp), Scrib(Crc) and Celsr1(Crsh) mutations, the most intensively studied PCP mutants. The majority of double-mutant embryos had open NTDs, with the range of phenotypes including anencephaly and spina bifida, therefore reflecting the defects observed in humans. Strikingly, even on a uniform genetic background, variability in the penetrance and severity of the mutant phenotypes was observed between the different double-heterozygote combinations. Phenotypically, Celsr1(Crsh);Vangl2(Lp);Scrib(Crc) triply heterozygous mutants were no more severe than doubly heterozygous or singly homozygous mutants. We propose that some of the variation between double-mutant phenotypes could be attributed to the nature of the protein disruption in each allele: whereas Scrib(Crc) is a null mutant and produces no Scrib protein, Celsr1(Crsh) and Vangl2(Lp) homozygotes both express mutant proteins, consistent with dominant effects. The variable outcomes of these genetic

  11. Influence of plant genetic diversity on interactions between higher trophic levels.

    Science.gov (United States)

    Moreira, Xoaquín; Mooney, Kailen A

    2013-06-23

    While the ecological consequences of plant diversity have received much attention, the mechanisms by which intraspecific diversity affects associated communities remains understudied. We report on a field experiment documenting the effects of patch diversity in the plant Baccharis salicifolia (genotypic monocultures versus polycultures of four genotypes), ants (presence versus absence) and their interaction on ant-tended aphids, ants and parasitic wasps, and the mechanistic pathways by which diversity influences their multi-trophic interactions. Five months after planting, polycultures (versus monocultures) had increased abundances of aphids (threefold), ants (3.2-fold) and parasitoids (1.7-fold) owing to non-additive effects of genetic diversity. The effect on aphids was direct, as plant genetic diversity did not mediate ant-aphid, parasitoid-aphid or ant-parasitoid interactions. This increase in aphid abundance occurred even though plant growth (and thus aphid resources) was not higher in polycultures. The increase in ants and parasitoids was an indirect effect, due entirely to higher aphid abundance. Ants reduced parasitoid abundance by 60 per cent, but did not affect aphid abundance or plant growth, and these top-down effects were equivalent between monocultures and polycultures. In summary, intraspecific plant diversity did not increase primary productivity, but nevertheless had strong effects across multiple trophic levels, and effects on both herbivore mutualists and enemies could be predicted entirely as an extension of plant-herbivore interactions.

  12. Construction of measurement uncertainty profiles for quantitative analysis of genetically modified organisms based on interlaboratory validation data.

    Science.gov (United States)

    Macarthur, Roy; Feinberg, Max; Bertheau, Yves

    2010-01-01

    A method is presented for estimating the size of uncertainty associated with the measurement of products derived from genetically modified organisms (GMOs). The method is based on the uncertainty profile, which is an extension, for the estimation of uncertainty, of a recent graphical statistical tool called an accuracy profile that was developed for the validation of quantitative analytical methods. The application of uncertainty profiles as an aid to decision making and assessment of fitness for purpose is also presented. Results of the measurement of the quantity of GMOs in flour by PCR-based methods collected through a number of interlaboratory studies followed the log-normal distribution. Uncertainty profiles built using the results generally give an expected range for measurement results of 50-200% of reference concentrations for materials that contain at least 1% GMO. This range is consistent with European Network of GM Laboratories and the European Union (EU) Community Reference Laboratory validation criteria and can be used as a fitness for purpose criterion for measurement methods. The effect on the enforcement of EU labeling regulations is that, in general, an individual analytical result needs to be 1.8% to demonstrate noncompliance with a labeling threshold of 0.9%.

  13. International collaborative study of the endogenous reference gene LAT52 used for qualitative and quantitative analyses of genetically modified tomato.

    Science.gov (United States)

    Yang, Litao; Zhang, Haibo; Guo, Jinchao; Pan, Liangwen; Zhang, Dabing

    2008-05-28

    One tomato ( Lycopersicon esculentum) gene, LAT52, has been proved to be a suitable endogenous reference gene for genetically modified (GM) tomato detection in a previous study. Herein are reported the results of a collaborative ring trial for international validation of the LAT52 gene as endogenous reference gene and its analytical systems; 14 GMO detection laboratories from 8 countries were invited, and results were finally received from 13. These data confirmed the species specificity by testing 10 plant genomic DNAs, less allelic variation and stable single copy number of the LAT52 gene, among 12 different tomato cultivars. Furthermore, the limit of detection of LAT52 qualitative PCR was proved to be 0.1%, which corresponded to 11 copies of haploid tomato genomic DNA, and the limit of quantification for the quantitative PCR system was about 10 copies of haploid tomato genomic DNA with acceptable PCR efficiency and linearity. Additionally, the bias between the test and true values of 8 blind samples ranged from 1.94 to 10.64%. All of these validated results indicated that the LAT52 gene is suitable for use as an endogenous reference gene for the identification and quantification of GM tomato and its derivates.

  14. A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize.

    Science.gov (United States)

    Boer, Martin P; Wright, Deanne; Feng, Lizhi; Podlich, Dean W; Luo, Lang; Cooper, Mark; van Eeuwijk, Fred A

    2007-11-01

    Complex quantitative traits of plants as measured on collections of genotypes across multiple environments are the outcome of processes that depend in intricate ways on genotype and environment simultaneously. For a better understanding of the genetic architecture of such traits as observed across environments, genotype-by-environment interaction should be modeled with statistical models that use explicit information on genotypes and environments. The modeling approach we propose explains genotype-by-environment interaction by differential quantitative trait locus (QTL) expression in relation to environmental variables. We analyzed grain yield and grain moisture for an experimental data set composed of 976 F(5) maize testcross progenies evaluated across 12 environments in the U.S. corn belt during 1994 and 1995. The strategy we used was based on mixed models and started with a phenotypic analysis of multi-environment data, modeling genotype-by-environment interactions and associated genetic correlations between environments, while taking into account intraenvironmental error structures. The phenotypic mixed models were then extended to QTL models via the incorporation of marker information as genotypic covariables. A majority of the detected QTL showed significant QTL-by-environment interactions (QEI). The QEI were further analyzed by including environmental covariates into the mixed model. Most QEI could be understood as differential QTL expression conditional on longitude or year, both consequences of temperature differences during critical stages of the growth.

  15. Quantitative interaction proteomics and genome-wide profiling of epigenetic histone marks and their readers

    DEFF Research Database (Denmark)

    Vermeulen, Michiel; Eberl, H Christian; Matarese, Filomena

    2010-01-01

    Trimethyl-lysine (me3) modifications on histones are the most stable epigenetic marks and they control chromatin-mediated regulation of gene expression. Here, we determine proteins that bind these marks by high-accuracy, quantitative mass spectrometry. These chromatin "readers" are assigned...

  16. A quantitative study to assess synergistic interactions between urotensin II and angiotensin II.

    Science.gov (United States)

    Lamarre, Neil S; Tallarida, Ronald J

    2008-05-31

    Interaction between the vasoactive peptides, urotensin II and angiotensin II, could have important implications in various disease states. We examined this interaction using isolated rat aortic rings with intact adventitia and endothelium. The fixed-ratio combination we tested produced effect levels significantly greater than predicted by additivity. Thus, the interaction was synergistic, and this is illustrated in a response surface plot that shows the predicted additive effect for all possible combinations.

  17. A high-resolution gene expression atlas of epistasis between gene-specific transcription factors exposes potential mechanisms for genetic interactions

    NARCIS (Netherlands)

    Sameith, Katrin; Amini, Saman; Groot Koerkamp, Marian J A; van Leenen, Dik|info:eu-repo/dai/nl/304817236; Brok, Mariel; Brabers, Nathalie; Lijnzaad, Philip|info:eu-repo/dai/nl/311462197; van Hooff, Sander R; Benschop, Joris J.; Lenstra, Tineke L.; Apweiler, Eva; van Wageningen, Sake; Snel, Berend; Holstege, Frank C P|info:eu-repo/dai/nl/149308035; Kemmeren, Patrick|info:eu-repo/dai/nl/304817228

    2015-01-01

    Background: Genetic interactions, or non-additive effects between genes, play a crucial role in many cellular processes and disease. Which mechanisms underlie these genetic interactions has hardly been characterized. Understanding the molecular basis of genetic interactions is crucial in deciphering

  18. GLABROUS INFLORESCENCE STEMS regulates trichome branching by genetically interacting with SIM in Arabidopsis

    Institute of Scientific and Technical Information of China (English)

    Li-li SUN; Zhong-jing ZHOU; Li-jun AN; Yan AN; Yong-qin ZHAO; Xiao-fang MENG; Clare STEELE-KING

    2013-01-01

    Arabidopsis trichomes are large branched single cells that protrude from the epidermis.The first morphological indication of trichome development is an increase in nuclear content resulting from an initial cycle of endoreduplication.Our previous study has shown that the C2H2 zinc finger protein GLABROUS INFLORESCENCE STEMS (GIS) is required for trichome initiation in the inflorescence organ and for trichome branching in response to gibberellic acid signaling,although GIS gene does not play a direct role in regulating trichome cell division.Here,we describe a novel role of GIS,controlling trichome cell division indirectly by interacting genetically with a key endoreduplication regulator SIAMESE (SIM).Our molecular and genetic studies have shown that GIS might indireclty control cell division and trichome branching by acting downstream of SIM.A loss of function mutation of SIM signficantly reduced the expression of GIS.Futhermore,the overexpression of GIS rescued the trichome cluster cell phenotypes of sim mutant.The gain or loss of function of GIS had no significant effect on the expression of SIM.These results suggest that GIS may play an indirect role in regulating trichome cell division by genetically interacting with SIM.

  19. Genetic variation changes the interactions between the parasitic plant-ecosystem engineer Rhinanthus and its hosts.

    Science.gov (United States)

    Rowntree, Jennifer K; Cameron, Duncan D; Preziosi, Richard F

    2011-05-12

    Within-species genetic variation is a potent factor influencing between-species interactions and community-level structure. Species of the hemi-parasitic plant genus Rhinanthus act as ecosystem engineers, significantly altering above- and below-ground community structure in grasslands. Here, we show the importance of genotypic variation within a single host species (barley-Hordeum vulgare), and population-level variation among two species of parasite (Rhinanthus minor and Rhinanthus angustifolius) on the outcome of parasite infection for both partners. We measured host fitness (number of seeds) and calculated parasite virulence as the difference in seed set between infected and uninfected hosts (the inverse of host tolerance). Virulence was determined by genetic variation within the host species and among the parasite species, but R. angustifolius was consistently more virulent than R. minor. The most tolerant host had the lowest inherent fitness and did not gain a fitness advantage over other infected hosts. We measured parasite size as a proxy for transmission ability (ability to infect further hosts) and host resistance. Parasite size depended on the specific combination of host genotype, parasite species and parasite population, and no species was consistently larger. We demonstrate that the outcome of infection by Rhinanthus depends not only on the host species, but also on the underlying genetics of both host and parasite. Thus, genetic variations within host and parasite are probably essential components of the ecosystem-altering effects of Rhinanthus.

  20. CSF-PR 2.0: An Interactive Literature Guide to Quantitative Cerebrospinal Fluid Mass Spectrometry Data from Neurodegenerative Disorders.

    Science.gov (United States)

    Guldbrandsen, Astrid; Farag, Yehia; Kroksveen, Ann Cathrine; Oveland, Eystein; Lereim, Ragnhild R; Opsahl, Jill A; Myhr, Kjell-Morten; Berven, Frode S; Barsnes, Harald

    2017-02-01

    The rapidly growing number of biomedical studies supported by mass spectrometry based quantitative proteomics data has made it increasingly difficult to obtain an overview of the current status of the research field. A better way of organizing the biomedical proteomics information from these studies and making it available to the research community is therefore called for. In the presented work, we have investigated scientific publications describing the analysis of the cerebrospinal fluid proteome in relation to multiple sclerosis, Parkinson's disease and Alzheimer's disease. Based on a detailed set of filtering criteria we extracted 85 data sets containing quantitative information for close to 2000 proteins. This information was made available in CSF-PR 2.0 (http://probe.uib.no/csf-pr-2.0), which includes novel approaches for filtering, visualizing and comparing quantitative proteomics information in an interactive and user-friendly environment. CSF-PR 2.0 will be an invaluable resource for anyone interested in quantitative proteomics on cerebrospinal fluid. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  1. Impact of non-linear smoking effects on the identification of gene-by-smoking interactions in COPD genetics studies

    DEFF Research Database (Denmark)

    Castaldi, P J; Demeo, D L; Hersh, C P;

    2010-01-01

    with COPD. Using data from the Alpha-1 Antitrypsin Genetic Modifiers Study, the accuracy and power of two different approaches to model smoking were compared by performing a simulation study of a genetic variant with a range of gene-by-smoking interaction effects. Results Non-linear relationships between...

  2. Meta-analysis of interaction between dietary magnesium intake and genetic risk variants on diabetes phenotypes in the charge consortium

    Science.gov (United States)

    Little is known about whether genetic variation modifies the effect of magnesium (Mg) intake on two important diabetes risk factors: fasting glucose (FG) and insulin (FI). We examined interactions between dietary Mg and genetic variants associated with glucose (16 SNPs), insulin (2 SNPs), or Mg home...

  3. Genetic dissection of milk yield traits and mastitis resistance quantitative trait loci on chromosome 20 in dairy cattle.

    Science.gov (United States)

    Kadri, Naveen K; Guldbrandtsen, Bernt; Lund, Mogens S; Sahana, Goutam

    2015-12-01

    Intense selection to increase milk yield has had negative consequences for mastitis incidence in dairy cattle. Due to low heritability of mastitis resistance and an unfavorable genetic correlation with milk yield, a reduction in mastitis through traditional breeding has been difficult to achieve. Here, we examined quantitative trait loci (QTL) that segregate for clinical mastitis and milk yield on Bos taurus autosome 20 (BTA20) to determine whether both traits are affected by a single polymorphism (pleiotropy) or by multiple closely linked polymorphisms. In the latter but not the former situation, undesirable genetic correlation could potentially be broken by selecting animals that have favorable variants for both traits. First, we performed a within-breed association study using a haplotype-based method in Danish Holstein cattle (HOL). Next, we analyzed Nordic Red dairy cattle (RDC) and Danish Jersey cattle (JER) with the goal of determining whether these QTL identified in Holsteins were segregating across breeds. Genotypes for 12,566 animals (5,966 HOL, 5,458 RDC, and 1,142 JER) were determined by using the Illumina Bovine SNP50 BeadChip (50K; Illumina, San Diego, CA), which identifies 1,568 single nucleotide polymorphisms on BTA20. Data were combined, phased, and clustered into haplotype states, followed by within- and across-breed haplotype-based association analyses using a linear mixed model. Association signals for both clinical mastitis and milk yield peaked in the 26- to 40-Mb region on BTA20 in HOL. Single-variant association analyses were carried out in the QTL region using whole sequence level variants imputed from references of 2,036 HD genotypes (BovineHD BeadChip; Illumina) and 242 whole-genome sequences. The milk QTL were also segregating in RDC and JER on the BTA20-targeted region; however, an indication of differences in the causal factor(s) was observed across breeds. A previously reported F279Y mutation (rs385640152) within the growth hormone

  4. Phosphatase and Tensin Homologue Genetic Polymorphisms and their Interactions with Viral Mutations on the Risk of Hepatocellular Carcinoma

    Institute of Scientific and Technical Information of China (English)

    Yan Du; Yu-Wei Zhang; Rui Pu; Xue Han; Jian-Ping Hu; Hong-Wei Zhang; Hong-Yang Wang

    2015-01-01

    Background:Chronic hepatitis B virus (HBV) infection is the major cause of hepatocellular carcinoma (HCC).Some HBV mutants and dysregulation of phosphatase and tensin homolog (PTEN) may promote the development of HCC synergistically.We aimed to test the effects of PTEN genetic polymorphisms and their interactions with important HBV mutations on the development of HCC in HBV-infected subjects.Methods:Quantitative polymerase chain reaction was applied to genotype PTEN polymorphisms (rs1234220,rs2299939,rs1234213) in 1012 healthy controls,302 natural clearance subjects,and 2011 chronic HBV-infected subjects including 1021 HCC patients.HBV mutations were determined by sequencing.The associations of PTEN polymorphisms and their interactions with HBV mutations with HCC risk were assessed using multivariate logistic regression analysis.Results:Rs 1234220 C allele was significantly associated with HCC risk compared to healthy controls (adjusted odds ratio [A OR] =1.35,95% confidence interval [CI] =1.07-1.69) and HCC-free HBV-infected subjects (AOR =1.27,95% CI =1.01-1.57).rs1234220 C allele was significantly associated with increased frequencies of HCC-risk A 1652G,C 1673T,and C 1730G mutations in genotype B HBV-infected subjects.Rs2299939 GT genotype was inversely associated with HCC risk in HBV-infected patients (AOR =0.75,95% CI =0.62-0.92).The interaction of rs2299939 variant genotypes (GT+TT) with A3054T mutation significantly increased HCC risk (AOR =2.41,95% CI =1.08-5.35);whereas its interaction with C3116T mutation significantly reduced HCC risk (AOR =0.34,95% CI =0.18-0.66).These significant effects were only evident in males after stratification.Conclusions:PTEN polymorphisms and their interactions with HBV mutations may contribute to hepatocarcinogenesis in males.The host-virus interactions are important in identifying HBV-infected subjects who are more likely to develop HCC.

  5. Integration of genetic virtual screening patterns and latent multivariate modeling techniques for QSAR optimization based on combinations and/or interactions between peptides and proteins

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Both the concept and the model of snug quantitative structure-activity relationship (QSAR) were pro-posed and developed for molecular design through constructing QSAR based on some known mode of receptor/ligand interactions. Many disadvantages of traditional models can be avoided by using the proposed method because the traditional models only determined upon molecular structural features in sample sets themselves. A genetic virtual screening of peptide/protein combinations (GVSPPC) is proposed for the first time by utilizing this idea to examine peptide/protein affinity activities. A genetic algorithm (GA) was developed for screening combinative targets with an interaction mode for virtual receptors. GVSPPC succeeds in disposing difficulties in rational QSAR,in order to search for the ligand/receptor interactions on conditions of unknown structures. Some bioactive oligo-/poly-peptide systems covering 58 angiotensin converting enzyme (ACE) inhibitors and 18 double site mutation residues in camel antibody protein cAb-Lys3 were investigated by GVSPPC with satisfactory results (R 2 cu>0.91,Q 2 cv > 0.86,ERMS=0.19-0.95),respectively,which demonstrates that GVSPPC is more inter-pretable in the ligand-receptor interaction than the traditional QSAR method.

  6. Integration of genetic virtual screening patterns and latent multivariate modeling techniques for QSAR optimization based on combinations and/or interactions between peptides and proteins

    Institute of Scientific and Technical Information of China (English)

    LI ZhiLiang; CHEN Gang; LI GenRong; TIAN FeiFei; WU ShiRong; YANG ShanBin; YANG ShengXi; ZHOU Yuan; ZHANG QiaoXia; QIN RenHui; MEI Hu

    2008-01-01

    Both the concept and the model of snug quantitative structure-activity relationship (QSAR) were pro-posed and developed for molecular design through constructing QSAR based on some known mode of receptor/ligand interactions. Many disadvantages of traditional models can be avoided by using the proposed method because the traditional models only determined upon molecular structural features in sample sets themselves. A genetic virtual screening of peptide/protein combinations (GVSPPC) is proposed for the first time by utilizing this idea to examine peptide/protein affinity activities. A genetic algorithm (GA) was developed for screening combinative targets with an interaction mode for virtual receptors. GVSPPC succeeds in disposing difficulties in rational QSAR, in order to search for the ligand/receptor interactions on conditions of unknown structures. Some bioactive oligo-/poly-peptide systems covering 58 angiotensin converting enzyme (ACE) inhibitors and 18 double site mutation residues in camel antibody protein cAb-Lys3 were investigated by GVSPPC with satisfactory results (Rcu2 > 0.91, Qcv2 0.86, ERMS = 0.19-0.95), respectively, which demonstrates that GVSPPC is more inter-pretable in the ligand-receptor interaction than the traditional QSAR method.

  7. Genetic and childhood trauma interaction effect on age of onset in bipolar disorder: An exploratory analysis.

    Science.gov (United States)

    Anand, Amit; Koller, Daniel L; Lawson, William B; Gershon, Elliot S; Nurnberger, John I

    2015-07-01

    This study investigated whether early life trauma mediates genetic effects on the age at onset (AAO) of bipolar disorder. Data from the BiGS Consortium case samples (N=1119) were used. Childhood traumatic events were documented using the Childhood Life Events Scale (CLES). Interaction between occurrence of childhood trauma and common genetic variants throughout the genome was tested to identify single nucleotide polymorphic gene variants (SNPs) whose effects on bipolar AAO differ between individuals clearly exposed (CLES≥2) and not exposed (CLES=0) to childhood trauma. The modal response to the CLES was 0 (N=480), but an additional 276 subjects had CLES=1, and 363 subjects reported 2 or more traumatic lifetime events. The distribution of age at onset showed a broad peak between ages 12 and 18, with the majority of subjects having onset during that period, and a significant decrease in age of onset with the number of traumatic events. No single SNP showed a statistically significant interaction with the presence of traumatic events to impact bipolar age at onset. However, SNPs in or near genes coding for calcium channel activity-related proteins (Gene Ontology: 0005262) were found to be more likely than other SNPs to show evidence of interaction using the INRICH method (peffects of early life trauma with genotype may have a significant effect on the development and manifestation of bipolar disorder. These effects may be mediated in part by genes involved in calcium signaling. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Intercellular Genetic Interaction Between Irf6 and Twist1 during Craniofacial Development.

    Science.gov (United States)

    Fakhouri, Walid D; Metwalli, Kareem; Naji, Ali; Bakhiet, Sarah; Quispe-Salcedo, Angela; Nitschke, Larissa; Kousa, Youssef A; Schutte, Brian C

    2017-08-02

    Interferon Regulatory Factor 6 (IRF6) and TWIST1 are transcription factors necessary for craniofacial development. Human genetic studies showed that mutations in IRF6 lead to cleft lip and palate and mandibular abnormalities. In the mouse, we found that loss of Irf6 causes craniosynostosis and mandibular hypoplasia. Similarly, mutations in TWIST1 cause craniosynostosis, mandibular hypoplasia and cleft palate. Based on this phenotypic overlap, we asked if Irf6 and Twist1 interact genetically during craniofacial formation. While single heterozygous mice are normal, double heterozygous embryos (Irf6 (+/-) ; Twist1 (+/-) ) can have severe mandibular hypoplasia that leads to agnathia and cleft palate at birth. Analysis of spatiotemporal expression showed that Irf6 and Twist1 are found in different cell types. Consistent with the intercellular interaction, we found reduced expression of Endothelin1 (EDN1) in mandible and transcription factors that are critical for mandibular patterning including DLX5, DLX6 and HAND2, were also reduced in mesenchymal cells. Treatment of mandibular explants with exogenous EDN1 peptides partially rescued abnormalities in Meckel's cartilage. In addition, partial rescue was observed when double heterozygous embryos also carried a null allele of p53. Considering that variants in IRF6 and TWIST1 contribute to human craniofacial defects, this gene-gene interaction may have implications on craniofacial disorders.

  9. A quantitative framework for understanding complex interactions between competing interfacial processes and in situ biodegradation

    Science.gov (United States)

    Johnson, Mark A.; Song, Xin; Seagren, Eric A.

    2013-03-01

    In situ bioremediation of contaminated groundwater is made technologically challenging by the physically, chemically, and biologically heterogeneous subsurface environment. Subsurface heterogeneities are important because of influences on interfacial mass transfer processes that impact the availability of substrates to microorganisms. The goal of this study was to perform a "proof-of-concept" evaluation of the utility of a quantitative framework based on a set of dimensionless coefficients for evaluating the effects of competing physicochemical interfacial and biokinetic processes at the field scale. First, three numerical modeling experiments were completed, demonstrating how the framework can be used to identify the rate-limiting process for the overall bioremediation rate, and to predict what engineered enhancements will alleviate the rate-limiting process. Baseline conditions for each scenario were established to examine intrinsic biodegradation with a given rate-limiting process (either dispersion, biokinetics, or sorption). Then different engineering treatments were examined. In each case, the treatment predicted to be appropriate for addressing the overall rate-limiting process based on the quantitative framework alleviated the limitation more successfully, and enhanced the in situ biodegradation rate more than the alternative enhancements. Second, the quantitative framework was applied to a series of large-scale laboratory and field-scale experiments, using reported parameter estimates to calculate the relevant dimensionless coefficients and predict the rate-limiting process(es). Observations from the studies were then used to evaluate those predictions.

  10. MaGelLAn 1.0: a software to facilitate quantitative and population genetic analysis of maternal inheritance by combination of molecular and pedigree information.

    Science.gov (United States)

    Ristov, Strahil; Brajkovic, Vladimir; Cubric-Curik, Vlatka; Michieli, Ivan; Curik, Ino

    2016-09-10

    Identification of genes or even nucleotides that are responsible for quantitative and adaptive trait variation is a difficult task due to the complex interdependence between a large number of genetic and environmental factors. The polymorphism of the mitogenome is one of the factors that can contribute to quantitative trait variation. However, the effects of the mitogenome have not been comprehensively studied, since large numbers of mitogenome sequences and recorded phenotypes are required to reach the adequate power of analysis. Current research in our group focuses on acquiring the necessary mitochondria sequence information and analysing its influence on the phenotype of a quantitative trait. To facilitate these tasks we have produced software for processing pedigrees that is optimised for maternal lineage analysis. We present MaGelLAn 1.0 (maternal genealogy lineage analyser), a suite of four Python scripts (modules) that is designed to facilitate the analysis of the impact of mitogenome polymorphism on quantitative trait variation by combining molecular and pedigree information. MaGelLAn 1.0 is primarily used to: (1) optimise the sampling strategy for molecular analyses; (2) identify and correct pedigree inconsistencies; and (3) identify maternal lineages and assign the corresponding mitogenome sequences to all individuals in the pedigree, this information being used as input to any of the standard software for quantitative genetic (association) analysis. In addition, MaGelLAn 1.0 allows computing the mitogenome (maternal) effective population sizes and probability of mitogenome (maternal) identity that are useful for conservation management of small populations. MaGelLAn is the first tool for pedigree analysis that focuses on quantitative genetic analyses of mitogenome data. It is conceived with the purpose to significantly reduce the effort in handling and preparing large pedigrees for processing the information linked to maternal lines. The software source

  11. Plant genetics and interspecific competitive interactions determine ectomycorrhizal fungal community responses to climate change.

    Science.gov (United States)

    Gehring, Catherine; Flores-Rentería, Dulce; Sthultz, Christopher M; Leonard, Tierra M; Flores-Rentería, Lluvia; Whipple, Amy V; Whitham, Thomas G

    2014-03-01

    Although the importance of plant-associated microbes is increasingly recognized, little is known about the biotic and abiotic factors that determine the composition of that microbiome. We examined the influence of plant genetic variation, and two stressors, one biotic and one abiotic, on the ectomycorrhizal (EM) fungal community of a dominant tree species, Pinus edulis. During three periods across 16 years that varied in drought severity, we sampled the EM fungal communities of a wild stand of P. edulis in which genetically based resistance and susceptibility to insect herbivory was linked with drought tolerance and the abundance of competing shrubs. We found that the EM fungal communities of insect-susceptible trees remained relatively constant as climate dried, while those of insect-resistant trees shifted significantly, providing evidence of a genotype by environment interaction. Shrub removal altered the EM fungal communities of insect-resistant trees, but not insect-susceptible trees, also a genotype by environment interaction. The change in the EM fungal community of insect-resistant trees following shrub removal was associated with greater shoot growth, evidence of competitive release. However, shrub removal had a 7-fold greater positive effect on the shoot growth of insect-susceptible trees than insect-resistant trees when shrub density was taken into account. Insect-susceptible trees had higher growth than insect-resistant trees, consistent with the hypothesis that the EM fungi associated with susceptible trees were superior mutualists. These complex, genetic-based interactions among species (tree-shrub-herbivore-fungus) argue that the ultimate impacts of climate change are both ecological and evolutionary. © 2013 John Wiley & Sons Ltd.

  12. The synthetic genetic interaction network reveals small molecules that target specific pathways in Sacchromyces cerevisiae.

    Science.gov (United States)

    Tamble, Craig M; St Onge, Robert P; Giaever, Guri; Nislow, Corey; Williams, Alexander G; Stuart, Joshua M; Lokey, R Scott

    2011-06-01

    High-throughput elucidation of synthetic genetic interactions (SGIs) has contributed to a systems-level understanding of genetic robustness and fault-tolerance encoded in the genome. Pathway targets of various compounds have been predicted by comparing chemical-genetic synthetic interactions to a network of SGIs. We demonstrate that the SGI network can also be used in a powerful reverse pathway-to-drug approach for identifying compounds that target specific pathways of interest. Using the SGI network, the method identifies an indicator gene that may serve as a good candidate for screening a library of compounds. The indicator gene is selected so that compounds found to produce sensitivity in mutants deleted for the indicator gene are likely to abrogate the target pathway. We tested the utility of the SGI network for pathway-to-drug discovery using the DNA damage checkpoint as the target pathway. An analysis of the compendium of synthetic lethal interactions in yeast showed that superoxide dismutase 1 (SOD1) has significant SGI connectivity with a large subset of DNA damage checkpoint and repair (DDCR) genes in Saccharomyces cerevisiae, and minimal SGIs with non-DDCR genes. We screened a sod1Δ strain against three National Cancer Institute (NCI) compound libraries using a soft agar high-throughput halo assay. Fifteen compounds out of ∼3100 screened showed selective toxicity toward sod1Δ relative to the isogenic wild type (wt) strain. One of these, 1A08, caused a transient increase in growth in the presence of sublethal doses of DNA damaging agents, suggesting that 1A08 inhibits DDCR signaling in yeast. Genome-wide screening of 1A08 against the library of viable homozygous deletion mutants further supported DDCR as the relevant targeted pathway of 1A08. When assayed in human HCT-116 colorectal cancer cells, 1A08 caused DNA-damage resistant DNA synthesis and blocked the DNA-damage checkpoint selectively in S-phase.

  13. Array-CGH and quantitative PCR genetic analysis in a case with bilateral hypoplasia of pulmonary arteries and lungs and simultaneous unilateral renal agenesis.

    Science.gov (United States)

    Hussein, Kais; Steinemann, Doris; Scholz, Henrike; Menkhaus, Ralf; Feist, Henning; Kreipe, Hans

    2010-08-18

    We describe the clinical course and have characterised anatomically and genetically a unique case of a newborn with bilateral hypoplasia of pulmonary arteries, consecutive extremely hypoplastic lung tissue and associated unilateral renal agenesis. Intrauterine oxygenation by the placenta seemed to have allowed normotrophic body maturity but immediately after delivery, in the third trimester, progressive hypoxemia developed and the newborn succumbed to acute respiratory failure. Genetic analysis by array-based comparative genomic hybridisation and quantitative PCR revealed duplication of 1p21, which, however, might not be the disease causing aberration. This case might represent an extreme form of previously reported, rare cases with simultaneous dysorganogenesis of lungs and kidneys.

  14. The TissueNet v.2 database: A quantitative view of protein-protein interactions across human tissues.

    Science.gov (United States)

    Basha, Omer; Barshir, Ruth; Sharon, Moran; Lerman, Eugene; Kirson, Binyamin F; Hekselman, Idan; Yeger-Lotem, Esti

    2017-01-04

    Knowledge of the molecular interactions of human proteins within tissues is important for identifying their tissue-specific roles and for shedding light on tissue phenotypes. However, many protein-protein interactions (PPIs) have no tissue-contexts. The TissueNet database bridges this gap by associating experimentally-identified PPIs with human tissues that were shown to express both pair-mates. Users can select a protein and a tissue, and obtain a network view of the query protein and its tissue-associated PPIs. TissueNet v.2 is an updated version of the TissueNet database previously featured in NAR. It includes over 40 human tissues profiled via RNA-sequencing or protein-based assays. Users can select their preferred expression data source and interactively set the expression threshold for determining tissue-association. The output of TissueNet v.2 emphasizes qualitative and quantitative features of query proteins and their PPIs. The tissue-specificity view highlights tissue-specific and globally-expressed proteins, and the quantitative view highlights proteins that were differentially expressed in the selected tissue relative to all other tissues. Together, these views allow users to quickly assess the unique versus global functionality of query proteins. Thus, TissueNet v.2 offers an extensive, quantitative and user-friendly interface to study the roles of human proteins across tissues. TissueNet v.2 is available at http://netbio.bgu.ac.il/tissuenet. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. Quantitative modeling assesses the contribution of bond strengthening, rebinding and force sharing to the avidity of biomolecule interactions.

    Directory of Open Access Journals (Sweden)

    Valentina Lo Schiavo

    Full Text Available Cell adhesion is mediated by numerous membrane receptors. It is desirable to derive the outcome of a cell-surface encounter from the molecular properties of interacting receptors and ligands. However, conventional parameters such as affinity or kinetic constants are often insufficient to account for receptor efficiency. Avidity is a qualitative concept frequently used to describe biomolecule interactions: this includes incompletely defined properties such as the capacity to form multivalent attachments. The aim of this study is to produce a working description of monovalent attachments formed by a model system, then to measure and interpret the behavior of divalent attachments under force. We investigated attachments between antibody-coated microspheres and surfaces coated with sparse monomeric or dimeric ligands. When bonds were subjected to a pulling force, they exhibited both a force-dependent dissociation consistent with Bell's empirical formula and a force- and time-dependent strengthening well described by a single parameter. Divalent attachments were stronger and less dependent on forces than monovalent ones. The proportion of divalent attachments resisting a force of 30 piconewtons for at least 5 s was 3.7 fold higher than that of monovalent attachments. Quantitative modeling showed that this required rebinding, i.e. additional bond formation between surfaces linked by divalent receptors forming only one bond. Further, experimental data were compatible with but did not require stress sharing between bonds within divalent attachments. Thus many ligand-receptor interactions do not behave as single-step reactions in the millisecond to second timescale. Rather, they exhibit progressive stabilization. This explains the high efficiency of multimerized or clustered receptors even when bonds are only subjected to moderate forces. Our approach provides a quantitative way of relating binding avidity to measurable parameters including bond

  16. Evaluation of stable isotope labelling strategies for the quantitation of CP4 EPSPS in genetically modified soya

    Energy Technology Data Exchange (ETDEWEB)

    Ocana, Mireia Fernandez [Centre for Chemical and Bioanalytical Sciences, Royal Holloway, University of London, Egham TW20 0EX (United Kingdom)], E-mail: Mireia.FernandezOcana@pfizer.com; Fraser, Paul D. [Centre for Chemical and Bioanalytical Sciences, Royal Holloway, University of London, Egham TW20 0EX (United Kingdom); Patel, Raj K.P.; Halket, John M. [Specialist Bioanalytical Services Ltd., Royal Holloway, University of London, Egham TW20 0EX (United Kingdom); Bramley, Peter M. [Centre for Chemical and Bioanalytical Sciences, Royal Holloway, University of London, Egham TW20 0EX (United Kingdom)

    2009-02-16

    The introduction of genetically modified (GM) crops into the market has raised a general alertness relating to the control and safety of foods. The applicability of protein separation hyphenated to mass spectrometry to identify the bacterial enolpyruvylshikimate-3-phosphate synthase (CP4 EPSPS) protein expressed in GM crops has been previously reported [M.F. Ocana, P.D. Fraser, R.K.P. Patel, J.M. Halket, P.M. Bramley, Rapid Commun. Mass Spectrom. 21 (2007) 319.]. Herein, we investigate the suitability of two strategies that employ heavy stable isotopes, i.e. AQUA and iTRAQ, to quantify different levels of CP4 EPSPS in up to four GM preparations. Both quantification strategies showed potential to determine whether the presence of GM material is above the limits established by the European Union. The AQUA quantification procedure involved protein solubilisation/fractionation and subsequent separation using SDS-PAGE. A segment of the gel in which the protein of interest was located was excised, the stable isotope labeled peptide added at a known concentration and proteolytic digestion initiated. Following recovery of the peptides, on-line separation and detection using LC-MS was carried out. A similar approach was used for the iTRAQ workflow with the exception that proteins were digested in solution and generated tryptic peptides were chemically tagged. Both procedures demonstrated the potential for quantitative detection at 0.5% (w/w) GM soya which is a level below the current European Union's threshold for food-labelling. In this context, a comparison between the two procedures is provided within the present study.

  17. Quantitative ultrasound of the hand phalanges in a cohort of monozygotic twins: influence of genetic and environmental factors

    Energy Technology Data Exchange (ETDEWEB)

    Guglielmi, G. [Scientific Institute Hospital, Department of Radiology, San Giovanni Rotondo (Italy); Terlizzi, F. de [IGEA Biophysics Lab, Carpi (Italy); Torrente, I.; Mingarelli, R. [Mendel Institute, Rome (Italy); Dallapiccola, B. [Scientific Institute Hospital, Department of Radiology, San Giovanni Rotondo (Italy); Mendel Institute, Rome (Italy)

    2005-11-01

    Our objective was to evaluate the similarities and differences in bone mass and structure between pairs of monozygotic twins as measured by means of the quantitative ultrasound (QUS) technique. A cohort of monozygotic twins was measured by QUS of the hand phalanges using the DBM sonic bone profiler (IGEA, Carpi, Italy). The parameters studied were amplitude-dependent speed of sound (AD-SoS), ultrasound bone profile index (UBPI), signal dynamics (SDy) and bone transmission time (BTT). Linear correlation coefficients, multivariate linear analysis and the ANOVA test were used to assess intrapair associations between variables and to determine which factors influence the intrapair differences in QUS variables. One hundred and six pairs of monozygotic twins were enrolled in the study, 68 females and 38 males in the age range 5 to 71 years. Significant intrapair correlations were obtained in the whole population and separately for males and females, regarding height (r =0.98-0.99, p <0.0001), weight (r =0.95-0.96, p <0.0001), AD-SoS (r =0.90-0.92, p <0.0001), BTT (r =0.94-0.95, p <0.0001) and other QUS parameters (r >0.74, p <0.0001). Multivariate analysis revealed that intrapair differences between AD-SoS, SDy, UBPI and BTT are significantly influenced by age in the whole population and in the female population. Furthermore, the ANOVA test showed, for the female group, a significant increase in the intrapair differences in SDy and UBPI above 40 years. A relative contribution of genetic factors to skeletal status could be observed by phalangeal QUS measurement in monozygotic twins. A significant increase in the intrapair difference in QUS parameters with increasing age and onset of menopause also suggests the importance of environmental factors in the female twin population. (orig.)

  18. Novel Sessile Drop Software for Quantitative Estimation of Slag Foaming in Carbon/Slag Interactions

    Science.gov (United States)

    Khanna, Rita; Rahman, Mahfuzur; Leow, Richard; Sahajwalla, Veena

    2007-08-01

    Novel video-processing software has been developed for the sessile drop technique for a rapid and quantitative estimation of slag foaming. The data processing was carried out in two stages: the first stage involved the initial transformation of digital video/audio signals into a format compatible with computing software, and the second stage involved the computation of slag droplet volume and area of contact in a chosen video frame. Experimental results are presented on slag foaming from synthetic graphite/slag system at 1550 °C. This technique can be used for determining the extent and stability of foam as a function of time.

  19. Genetic, epigenetic, and gene-by-diet interaction effects underlie variation in serum lipids in a LG/JxSM/J murine model.

    Science.gov (United States)

    Lawson, Heather A; Zelle, Kathleen M; Fawcett, Gloria L; Wang, Bing; Pletscher, L Susan; Maxwell, Taylor J; Ehrich, Thomas H; Kenney-Hunt, Jane P; Wolf, Jason B; Semenkovich, Clay F; Cheverud, James M

    2010-10-01

    Variation in serum cholesterol, free-fatty acids, and triglycerides is associated with cardiovascular disease (CVD) risk factors. There is great interest in characterizing the underlying genetic architecture of these risk factors, because they vary greatly within and among human populations and between the sexes. We present results of a genome-wide scan for quantitative trait loci (QTL) affecting serum cholesterol, free-fatty acids, and triglycerides in an F(16) advanced intercross line of LG/J and SM/J (Wustl:LG,SM-G16). Half of the population was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. Here we examine genetic, environmental, and genetic-by-environmental interactions of QTL overlapping previously identified loci associated with CVD risk factors, and we add to the serum lipid QTL landscape by identifying new loci.

  20. A VR Based Interactive Genetic Algorithm Framework For Design of Support Schemes to Deep Excavations

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Riyu [Univ. of Queensland, Brisbane (Australia); Wu, Heng [Guangxi Univ., Nanning (China)

    2002-11-15

    An interactive genetic algorithm (IGA) framework for the design of support schemes to deep excavations is proposed in this paper, in which virtual reality (VR) is used as an aid to the evaluation of design schemes that is performed interactively. The fitness of a scheme individual is evaluated by two steps. Firstly a fitness value is automatically assigned to a scheme individual according to the the estimated construction cost of the individual. And the human evaluation is introduced to modify the fitness value by taking into account other factors, such as the feasibility factor. The design scheme is composed of four basic categories, i. e., cantilever walls, reinforced soil walls, tieback systems and bracing systems, each of which is encoded by a binary string. To assist human evaluation, 3D models of design schemes are created and visualized in a virtual reality environment, providing designers with a reality sense of various schemes.

  1. M51 revisited: a genetic algorithm approach of its interaction history

    CERN Document Server

    Theis, C; Spinneker, Ch.; Theis, Ch.

    2003-01-01

    Detailed models of observed interacting galaxies suffer from the extended parameter space. Here, we present results from our code MINGA which couples an evolutionary optimization strategy (a genetic algorithm) with a fast N-body method. MINGA allows for an automatic search of the optimal region(s) in parameter space within a few hours to a few days of CPU time on a modern PC by investigating of the order of 10^5 models. We demonstrate its applicability by modelling the HI intensity and velocity maps of the interacting system M51 and NGC 5195. We get a good fit for the HI intensity map and we can reproduce the counter-rotation feature of the HI arm. Our result corroborates the results of Salo & Laurikainen (2000) who favour a model with multiple passages through M51's disk.

  2. M51 revisited: A genetic algorithm approach of its interaction history

    Science.gov (United States)

    Theis, Christian; Spinneker, Christian

    2003-04-01

    Detailed models of observed interacting galaxies suffer from the extended parameter space. Here, we present results from our code MINGA which couples an evolutionary optimization strategy (a genetic algorithm) with a fast N-body method. MINGA allows for an automatic search of the optimal region(s) in parameter space within a few hours to a few days of CPU time on a modern PC by investigating of the order of 105 models. We demonstrate its applicability by modelling the HI intensity and velocity maps of the interacting system M51 and NGC 5195. We get a good fit for the HI intensity map and we can reproduce the counter-rotation feature of the HI arm. Our result corroborates the results of Salo and Laurikainen (2000) who favour a model with multiple passages through M51's disk.

  3. Exploitation of genetic interaction network topology for the prediction of epistatic behavior

    KAUST Repository

    Alanis Lobato, Gregorio

    2013-10-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.

  4. Exploitation of genetic interaction network topology for the prediction of epistatic behavior.

    Science.gov (United States)

    Alanis-Lobato, Gregorio; Cannistraci, Carlo Vittorio; Ravasi, Timothy

    2013-10-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks. We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks. Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab.

  5. Effect of genetic variants and traits related to glucose metabolism and their interaction with obesity on breast and colorectal cancer risk among postmenopausal women.

    Science.gov (United States)

    Jung, Su Yon; Sobel, Eric M; Papp, Jeanette C; Zhang, Zuo-Feng

    2017-04-26

    Impaired glucose metabolism-related genetic variants and traits likely interact with obesity and related lifestyle factors, influencing postmenopausal breast and colorectal cancer (CRC), but their interconnected pathways are not fully understood. By stratifying via obesity and lifestyles, we partitioned the total effect of glucose metabolism genetic variants on cancer risk into two putative mechanisms: 1) indirect (risk-associated glucose metabolism genetic variants mediated by glucose metabolism traits) and 2) direct (risk-associated glucose metabolism genetic variants through pathways other than glucose metabolism traits) effects. Using 16 single-nucleotide polymorphisms (SNPs) associated with glucose metabolism and data from 5379 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies, we retrospectively assessed the indirect and direct effects of glucose metabolism-traits (fasting glucose, insulin, and homeostatic model assessment-insulin resistance [HOMA-IR]) using two quantitative tests. Several SNPs were associated with breast cancer and CRC risk, and these SNP-cancer associations differed between non-obese and obese women. In both strata, the direct effect of cancer risk associated with the SNP accounted for the majority of the total effect for most SNPs, with roughly 10% of cancer risk due to the SNP that was from an indirect effect mediated by glucose metabolism traits. No apparent differences in the indirect (glucose metabolism-mediated) effects were seen between non-obese and obese women. It is notable that among obese women, 50% of cancer risk was mediated via glucose metabolism trait, owing to two SNPs: in breast cancer, in relation to GCKR through glucose, and in CRC, in relation to DGKB/TMEM195 through HOMA-IR. Our findings suggest that glucose metabolism genetic variants interact with obesity, resulting in altered cancer risk through pathways other than those mediated by glucose metabolism traits.

  6. Genetic analysis of ecological relevant morphological variability in Plantago lanceolata L. : 2. Localisation and organisation of quantitative trait loci.

    Science.gov (United States)

    Wolff, K

    1987-04-01

    Morphological variability was analysed in an F2-generation derived from crosses between two ecotypes of Plantago lanceolata L. Six allozyme loci, localised in five linkage groups, were used as markers. For two marker loci, Got-2 and Gpi-1, segregations did not fit monogenic ratios. In the linkage groups to which these two loci belonged, male sterility genes appeared to be present. In these crosses, male sterility (type 3, as described by Van Damme 1983) may be determined by two recessive loci located in the linkage groups of Got-2 and of Gpi-1. Many correlations of morphological and life history characters with allozyme markers were observed. The quantitative trait loci did not appear to be concentrated in major gene complexes. Often many loci were involved, sometimes with effects opposite to those expected from the population values. Main effects of the linkage groups appeared to be more important than interaction effects in determining variability. It also appeared that there is a positive correlation between the number of heterozygous allozyme loci and generative growth.

  7. Impact of non-linear smoking effects on the identification of gene-by-smoking interactions in COPD genetics studies

    DEFF Research Database (Denmark)

    Castaldi, P J; Demeo, D L; Hersh, C P

    2010-01-01

    Background The identification of gene-by-environment interactions is important for understanding the genetic basis of chronic obstructive pulmonary disease (COPD). Many COPD genetic association analyses assume a linear relationship between pack-years of smoking exposure and forced expiratory volume...... in 1 s (FEV(1)); however, this assumption has not been evaluated empirically in cohorts with a wide spectrum of COPD severity. Methods The relationship between FEV(1) and pack-years of smoking exposure was examined in four large cohorts assembled for the purpose of identifying genetic associations...... with COPD. Using data from the Alpha-1 Antitrypsin Genetic Modifiers Study, the accuracy and power of two different approaches to model smoking were compared by performing a simulation study of a genetic variant with a range of gene-by-smoking interaction effects. Results Non-linear relationships between...

  8. Syndecan 4 interacts genetically with Vangl2 to regulate neural tube closure and planar cell polarity.

    Science.gov (United States)

    Escobedo, Noelia; Contreras, Osvaldo; Muñoz, Rosana; Farías, Marjorie; Carrasco, Héctor; Hill, Charlotte; Tran, Uyen; Pryor, Sophie E; Wessely, Oliver; Copp, Andrew J; Larraín, Juan

    2013-07-01

    Syndecan 4 (Sdc4) is a cell-surface heparan sulfate proteoglycan (HSPG) that regulates gastrulation, neural tube closure and directed neural crest migration in Xenopus development. To determine whether Sdc4 participates in Wnt/PCP signaling during mouse development, we evaluated a possible interaction between a null mutation of Sdc4 and the loop-tail allele of Vangl2. Sdc4 is expressed in multiple tissues, but particularly in the non-neural ectoderm, hindgut and otic vesicles. Sdc4;Vangl2(Lp) compound mutant mice have defective spinal neural tube closure, disrupted orientation of the stereocilia bundles in the cochlea and delayed wound healing, demonstrating a strong genetic interaction. In Xenopus, co-injection of suboptimal amounts of Sdc4 and Vangl2 morpholinos resulted in a significantly greater proportion of embryos with defective neural tube closure than each individual morpholino alone. To probe the mechanism of this interaction, we overexpressed or knocked down Vangl2 function in HEK293 cells. The Sdc4 and Vangl2 proteins colocalize, and Vangl2, particularly the Vangl2(Lp) mutant form, diminishes Sdc4 protein levels. Conversely, Vangl2 knockdown enhances Sdc4 protein levels. Overall HSPG steady-state levels were regulated by Vangl2, suggesting a molecular mechanism for the genetic interaction in which Vangl2(Lp/+) enhances the Sdc4-null phenotype. This could be mediated via heparan sulfate residues, as Vangl2(Lp/+) embryos fail to initiate neural tube closure and develop craniorachischisis (usually seen only in Vangl2(Lp/Lp)) when cultured in the presence of chlorate, a sulfation inhibitor. These results demonstrate that Sdc4 can participate in the Wnt/PCP pathway, unveiling its importance during neural tube closure in mammalian embryos.

  9. Genetic and Epigenetic Contributions to Human Nutrition and Health: Managing Genome–Diet Interactions

    Science.gov (United States)

    STOVER, PATRICK J.; CAUDILL, MARIE A.

    2017-01-01

    The Institute of Medicine recently convened a workshop to review the state of the various domains of nutritional genomics research and policy and to provide guidance for further development and translation of this knowledge into nutrition practice and policy. Nutritional genomics holds the promise to revolutionize both clinical and public health nutrition practice and facilitate the establishment of (a) genome-informed nutrient and food-based dietary guidelines for disease prevention and healthful aging, (b) individualized medical nutrition therapy for disease management, and (c) better targeted public health nutrition interventions (including micronutrient fortification and supplementation) that maximize benefit and minimize adverse outcomes within genetically diverse human populations. As the field of nutritional genomics matures, which will include filling fundamental gaps in knowledge of nutrient–genome interactions in health and disease and demonstrating the potential benefits of customizing nutrition prescriptions based on genetics, registered dietitians will be faced with the opportunity of making genetically driven dietary recommendations aimed at improving human health. PMID:18755320

  10. PROSPECTIVE STUDY OF MULTIPLE GENETIC TUMOR MARKER ASSAY BY QUANTITATIVE REAL-TIME PCR TO PREDICT RECURRENCE IN COLORECTAL CANCER PATIENTS

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Objective To describe correlation between multiple genetic tumor markers,carcinoembryonic antigen (CEA),cytokeratin 20 (CK20),and Survivin,and clinicopathological features of colorectal cancer (CRC) and to assess prognostic diagnosis value in cancer recurrence and metastasis.Methods A total of 92 patients with CRC,68 patients with precancerous lesions,and 29 control volunteers were collected for the detection of CEA,CK20,and Survivin expressions by using quantitative Real-Time PCR technology.Associations am...

  11. [Cyclooxygenase 2 genetic variant interacting with tobacco smoking and the risk of lung cancer].

    Science.gov (United States)

    Zhang, Zhi; Liu, Rui; Yang, Zhao-huan; Wang, Guang-xia; Shao, Sha-sha; Song, Qin-qin; Zhang, Xue-mei

    2013-08-01

    To explore the association of -1195G > A genetic variant in the promoter region of cyclooxygenase 2 genetic (COX2) with the genetic susceptibility of lung cancer and its interaction with smoking. Totally, 956 lung cancer patients recruited between January 2000 and December 2008 at Cancer Hospital, Chinese Academy of Medical Science as the case group, and 994 frequency-matched controls were randomly selected from a pool of cancer-free subjects recruited from a nutritional survey. All subjects were ethnic Han Chinese. There was no sex, age restrictions. Case group and control group were matched. Informed consent was obtained and 2 ml peripheral blood was collected from each subject. All samples were genotyped by polymerase chain reaction-restriction fragment length polymorphism method, smoking status of the subjects was surveyed.While the OR and 95% CI were estimated by logistic regression to evaluate the relation of COX2 -1195G > A variant and the risk of lung cancer. The genetic allele COX2 -1195AA of control group and case group were 24.9% (247/994) and 28.3% (271/956) . Case-control analysis showed an increased risk of developing lung cancer for -1195AA genotype carriers (OR = 1.36, 95% CI: 1.03-1.79), compared with -1195GG carriers. When stratified by smoking status, the significant increased risk of lung cancer was found among smokers with COX2-1195AA genotype, with the OR (95%CI) was 1.56 (1.08-2.25); while among non-smokers, difference of lung cancer risk was not found among different genotypes (OR = 1.17; 95%CI: 0.77-1.61). Among heavy smokers (pack-year >20), -1195AA and -1195AG genotype carriers have significant increased risk of lung cancer with 1.85 (1.16-2.95) and 1.62(1.08-2.43) of OR (95%CI), respectively; among light smokers (pack-year ≤ 20), the OR (95%CI) of lung cancer risk in -1195AG and -1195AA genotype carriers were 0.78 (0.47-1.30) and 1.08 (0.60-1.94), respectively. Genetic polymorphism in the promoter of COX2 gene interacting with smoking

  12. Comparison and evaluation of network clustering algorithms applied to genetic interaction networks.

    Science.gov (United States)

    Hou, Lin; Wang, Lin; Berg, Arthur; Qian, Minping; Zhu, Yunping; Li, Fangting; Deng, Minghua

    2012-01-01

    The goal of network clustering algorithms detect dense clusters in a network, and provide a first step towards the understanding of large scale biological networks. With numerous recent advances in biotechnologies, large-scale genetic interactions are widely available, but there is a limited understanding of which clustering algorithms may be most effective. In order to address this problem, we conducted a systematic study to compare and evaluate six clustering algorithms in analyzing genetic interaction networks, and investigated influencing factors in choosing algorithms. The algorithms considered in this comparison include hierarchical clustering, topological overlap matrix, bi-clustering, Markov clustering, Bayesian discriminant analysis based community detection, and variational Bayes approach to modularity. Both experimentally identified and synthetically constructed networks were used in this comparison. The accuracy of the algorithms is measured by the Jaccard index in comparing predicted gene modules with benchmark gene sets. The results suggest that the choice differs according to the network topology and evaluation criteria. Hierarchical clustering showed to be best at predicting protein complexes; Bayesian discriminant analysis based community detection proved best under epistatic miniarray profile (EMAP) datasets; the variational Bayes approach to modularity was noticeably better than the other algorithms in the genome-scale networks.

  13. Frontiers of torenia research: innovative ornamental traits and study of ecological interaction networks through genetic engineering.

    Science.gov (United States)

    Nishihara, Masahiro; Shimoda, Takeshi; Nakatsuka, Takashi; Arimura, Gen-Ichiro

    2013-06-26

    Advances in research in the past few years on the ornamental plant torenia (Torenia spps.) have made it notable as a model plant on the frontier of genetic engineering aimed at studying ornamental characteristics and pest control in horticultural ecosystems. The remarkable advantage of torenia over other ornamental plant species is the availability of an easy and high-efficiency transformation system for it. Unfortunately, most of the current torenia research is still not very widespread, because this species has not become prominent as an alternative to other successful model plants such as Arabidopsis, snapdragon and petunia. However, nowadays, a more global view using not only a few selected models but also several additional species are required for creating innovative ornamental traits and studying horticultural ecosystems. We therefore introduce and discuss recent research on torenia, the family Scrophulariaceae, for secondary metabolite bioengineering, in which global insights into horticulture, agriculture and ecology have been advanced. Floral traits, in torenia particularly floral color, have been extensively studied by manipulating the flavonoid biosynthetic pathways in flower organs. Plant aroma, including volatile terpenoids, has also been genetically modulated in order to understand the complicated nature of multi-trophic interactions that affect the behavior of predators and pollinators in the ecosystem. Torenia would accordingly be of great use for investigating both the variation in ornamental plants and the infochemical-mediated interactions with arthropods.

  14. Genetic variability for iron and zinc content in common bean lines and interaction with water availability.

    Science.gov (United States)

    Pereira, H S; Del Peloso, M J; Bassinello, P Z; Guimarães, C M; Melo, L C; Faria, L C

    2014-08-28

    The common bean is an important source of iron and zinc in humans. Increases in the contents of these minerals can combat mineral deficiencies, but these contents are influenced by environmental conditions. Thus, the objectives of this study were to investigate the interaction between common bean lines and water availability on iron and zinc contents (CFe and CZn, respectively), identify superior lines with stable CFe and CZn, and test for a genetic relationship between CFe and CZn. Six crop trials were performed using a randomized block design with three replications. The trials were performed during the winter sowing period for three different combinations of year and site in Brazil. For each combination, 53 lines were evaluated across two parallel trials; one trial was irrigated according to the crop requirements, and the other trial operated under a water deficit. Interaction was detected between lines and environments, and between lines and water availability for CFe and CZn. However, some lines exhibited high CFe and CZn in both conditions. Lines G 6492 and G 6490 exhibited high mean values, stability, and adaptability for both minerals. Other lines exhibited high CFe (Xamego) or CZn (Bambuí and Iapar 65). A moderate genetic correlation (0.62) between CFe and CZn was detected. Water availability during the common bean cycle had an effect on CFe and CZn; however, lines with high CFe and CZn in different conditions of water availability and environment were detected.

  15. Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in Brassica rapa Fast Plants

    Science.gov (United States)

    Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dósa, Katalin; Pfammatter, Jesse

    2014-01-01

    Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question “What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev),” we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students’ cognitive structures before and after the unit and explanations in students’ final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on “variation” as a proposed threshold concept and primary goal for students’ explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from “plug and play,” this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. PMID:25185225

  16. Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population.

    Science.gov (United States)

    Bonnet, Timothée; Wandeler, Peter; Camenisch, Glauco; Postma, Erik

    2017-01-01

    In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called "stasis paradox" highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is

  17. Quantitative evaluation of noncovalent interactions between polyphosphate and dissolved humic acids in aqueous conditions.

    Science.gov (United States)

    Fang, Wei; Sheng, Guo-Ping; Wang, Long-Fei; Ye, Xiao-Dong; Yu, Han-Qing

    2015-12-01

    As one kind of phosphorus species, polyphosphate (poly-P) is ubiquitous in natural environments, and the potential interactions between poly-P and humic substances in the sediments or natural waters would influence the fate of poly-P in the environments. However, the mechanism of the interactions has not yet been understood clearly. In this work, the characteristics and mechanisms of the interactions between humic acids (HA) and two model poly-P compounds with various chain lengths have been investigated. Results show that a stable polyphosphate-HA complex would be formed through the noncovalent interactions, and hydrogen bond might be the main driving force for the binding process, which might be formed between the proton-accepting groups of poly-P (e.g., PO and P-O(-)) and the oxygen containing functional groups in HA. Our findings implied that the presence of humic substances in natural waters, soils and sediments would influence the potential transport and/or mobility of environmental poly-P.

  18. Quantitative Research Methods, Study Quality, and Outcomes: The Case of Interaction Research

    Science.gov (United States)

    Plonsky, Luke; Gass, Susan

    2011-01-01

    This article constitutes the first empirical assessment of methodological quality in second language acquisition (SLA). We surveyed a corpus of 174 studies (N = 7,951) within the tradition of research on second-language interaction, one of the longest and most influential traditions of inquiry in SLA. Each report was coded for methodological…

  19. Factors Mediating the Interactions between Adviser and Advisee during the Master's Thesis Project: A Quantitative Approach

    Science.gov (United States)

    Rodrigues Jr., Jose Florencio; Lehmann, Angela Valeria Levay; Fleith, Denise De Souza

    2005-01-01

    Building on previous studies centred on the interaction between adviser and advisee in masters thesis projects, in which a qualitative approach was used, the present study uses factor analysis to identify the factors that determine either a successful or unsuccessful outcome for the masters thesis project. There were five factors relating to the…

  20. Spectral study of interaction between chondroitin sulfate and nanoparticles and its application in quantitative analysis

    Science.gov (United States)

    Ma, Yi; Wei, Maojie; Zhang, Xiao; Zhao, Ting; Liu, Xiumei; Zhou, Guanglian

    2016-01-01

    In this work, the interaction between chondroitin sulfate (CS) and gold nanoparticles (GNPs) and silver nanoparticles (SNPs) was characterized for the first time. Plasma resonance scattering (PRS) and plasma resonance absorption (PRA) were used to investigate the characteristics of their spectrum. The results suggested that the CS with negative charge could interact with metal nanoparticles with negative charge and the adsorption of CS on the surface of SNPs was more regular than that of GNPs. The resonance scattering spectra also further confirmed the interaction between CS and SNPs. A new method for detection of CS based on the interaction was developed. CS concentrations in the range of 0.02-3.5 μg/mL were proportional to the decreases of absorbance of SNPs. Compared with other reported methods, the proposed method is simple and workable without complex process, high consumption and expensive equipments. The developed method was applied to the determination of the CS contents from different biological origins and the results were compared with those obtained by the method of Chinese Pharmacopeia. The effects of matrix in plasma and other glycosaminoglycans on the determination of CS were also investigated. The results showed that a small quantity of blood plasma had no effect on the determination of CS and when the concentration ratio of CS to heparin was more than 10:1, the influence of heparin on the detection of CS could be ignored. This work gave a specific research direction for the detection of CS in the presence of metal nanoparticles.

  1. Interactions Between Genetic Variants and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium

    NARCIS (Netherlands)

    Campa, Daniele; Kaaks, Rudolf; Le Marchand, Loic; Haiman, Christopher A.; Travis, Ruth C.; Berg, Christine D.; Buring, Julie E.; Chanock, Stephen J.; Diver, W. Ryan; Dostal, Lucie; Fournier, Agnes; Hankinson, Susan E.; Henderson, Brian E.; Hoover, Robert N.; Isaacs, Claudine; Johansson, Mattias; Kolonel, Laurence N.; Kraft, Peter; Lee, I-Min; McCarty, Catherine A.; Overvad, Kim; Panico, Salvatore; Peeters, Petra H. M.; Riboli, Elio; Jose Sanchez, Maria; Schumacher, Fredrick R.; Skeie, Guri; Stram, Daniel O.; Thun, Michael J.; Trichopoulos, Dimitrios; Zhang, Shumin; Ziegler, Regina G.; Hunter, David J.; Lindstroem, Sara; Canzian, Federico

    2011-01-01

    Background Recently, several genome-wide association studies have identified various genetic susceptibility loci for breast cancer. Relatively little is known about the possible interactions between these loci and the established risk factors for breast cancer. Methods To assess interactions between

  2. Genetic perspectives on forager-farmer interaction in the Luangwa valley of Zambia.

    Science.gov (United States)

    de Filippo, Cesare; Heyn, Patricia; Barham, Lawrence; Stoneking, Mark; Pakendorf, Brigitte

    2010-03-01

    The transformation from a foraging way of life to a reliance on domesticated plants and animals often led to the expansion of agropastoralist populations at the expense of hunter-gatherers (HGs). In Africa, one of these expansions involved the Niger-Congo Bantu-speaking populations that started to spread southwards from Cameroon/Nigeria approximately 4,000 years ago, bringing agricultural technologies. Genetic studies have shown different degrees of gene flow (sometimes involving sex-biased migrations) between Bantu agriculturalists and HGs. Although these studies have covered many parts of sub-Saharan Africa, the central part (e.g. Zambia) was not yet studied, and the interactions between immigrating food-producers and local HGs are still unclear. Archeological evidence from the Luangwa Valley of Zambia suggests a long period of coexistence ( approximately 1,700 years) of early food-producers and HGs. To investigate if this apparent coexistence was accompanied by genetic admixture, we analyzed the mtDNA control region, Y chromosomal unique event polymorphisms, and 12 associated Y- short tandem repeats in two food-producing groups (Bisa and Kunda) that live today in the Luangwa Valley, and compared these data with available published data on African HGs. Our results suggest that both the Bisa and Kunda experienced at most low levels of admixture with HGs, and these levels do not differ between the maternal and paternal lineages. Coalescent simulations indicate that the genetic data best fit a demographic scenario with a long divergence (62,500 years) and little or no gene flow between the ancestors of the Bisa/Kunda and existing HGs. This scenario contrasts with the archaeological evidence for a long period of coexistence between the two different communities in the Luangwa Valley, and suggests a process of sociocultural boundary maintenance may have characterized their interaction.

  3. A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

    Directory of Open Access Journals (Sweden)

    Ching Lee Koo

    2013-01-01

    Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  4. Genetic modifier screens reveal new components that interact with the Drosophila dystroglycan-dystrophin complex.

    Directory of Open Access Journals (Sweden)

    Mariya M Kucherenko

    Full Text Available The Dystroglycan-Dystrophin (Dg-Dys complex has a capacity to transmit information from the extracellular matrix to the cytoskeleton inside the cell. It is proposed that this interaction is under tight regulation; however the signaling/regulatory components of Dg-Dys complex remain elusive. Understanding the regulation of the complex is critical since defects in this complex cause muscular dystrophy in humans. To reveal new regulators of the Dg-Dys complex, we used a model organism Drosophila melanogaster and performed genetic interaction screens to identify modifiers of Dg and Dys mutants in Drosophila wing veins. These mutant screens revealed that the Dg-Dys complex interacts with genes involved in muscle function and components of Notch, TGF-beta and EGFR signaling pathways. In addition, components of pathways that are required for cellular and/or axonal migration through cytoskeletal regulation, such as Semaphorin-Plexin, Frazzled-Netrin and Slit-Robo pathways show interactions with Dys and/or Dg. These data suggest that the Dg-Dys complex and the other pathways regulating extracellular information transfer to the cytoskeletal dynamics are more intercalated than previously thought.

  5. On-Beads Digestion in Conjunction with Data-Dependent Mass Spectrometry: A Shortcut to Quantitative and Dynamic Interaction Proteomics

    Directory of Open Access Journals (Sweden)

    Benedetta Turriziani

    2014-04-01

    Full Text Available With the advent of the “-omics” era, biological research has shifted from functionally analyzing single proteins to understanding how entire protein networks connect and adapt to environmental cues. Frequently, pathological processes are initiated by a malfunctioning protein network rather than a single protein. It is therefore crucial to investigate the regulation of proteins in the context of a pathway first and signaling network second. In this study, we demonstrate that a quantitative interaction proteomic approach, combining immunoprecipitation, in-solution digestion and label-free quantification mass spectrometry, provides data of high accuracy and depth. This protocol is applicable, both to tagged, exogenous and untagged, endogenous proteins. Furthermore, it is fast, reliable and, due to a label-free quantitation approach, allows the comparison of multiple conditions. We further show that we are able to generate data in a medium throughput fashion and that we can quantify dynamic interaction changes in signaling pathways in response to mitogenic stimuli, making our approach a suitable method to generate data for system biology approaches.

  6. Genetic Parameters and Combining Ability Effects of Parents for Seed Yield and other Quantitative Traits in Black Gram [Vigna mungo (L. Hepper

    Directory of Open Access Journals (Sweden)

    Supriyo CHAKRABORTY

    2010-06-01

    Full Text Available Line x tester analysis was carried out in black gram [Vigna mungo (L. Hepper], an edible legume, to estimate the gca (general combining ability effects of parents (3 lines and 3 testers and the SCA (specific combining ability effects of 9 crosses for seed yield and other eleven quantitative traits. Though additive and nonadditive gene actions governed the expression of quantitative traits, the magnitude of nonadditive gene action was higher than that of additive gene action for each quantitative trait. Two parents viz. UG157 and DPU915 were good general combiners. Two crosses namely PDB 88-31/DPU 915 and PLU 277/KAU7 had high per se performance along with positive significant SCA effect for seed yield/plant. The degree of dominance revealed overdominance for all the traits except clusters/plant with partial dominance. The predictability ratio also revealed the predominant role of nonadditive gene action in the genetic control of quantitative traits. Narrow sense heritability was also low for each trait. Recurrent selection or biparental mating followed by selection which can exploit both additive and nonadditive gene actions would be of interest for yield improvement in black gram. Due to presence of high magnitude of nonadditive gene action, heterosis breeding could also be attempted to develop low cost hybrid variety using genetic male sterility system in black gram.

  7. Genetic Parameters and Combining Ability Effects of Parents for Seed Yield and other Quantitative Traits in Black Gram [Vigna mungo (L. Hepper

    Directory of Open Access Journals (Sweden)

    Supriyo CHAKRABORTY

    2010-06-01

    Full Text Available Line x tester analysis was carried out in black gram [Vigna mungo (L. Hepper], an edible legume, to estimate the gca (general combining ability effects of parents (3 lines and 3 testers and the SCA (specific combining ability effects of 9 crosses for seed yield and other eleven quantitative traits. Though additive and nonadditive gene actions governed the expression of quantitative traits, the magnitude of nonadditive gene action was higher than that of additive gene action for each quantitative trait. Two parents viz. �UG157� and �DPU915� were good general combiners. Two crosses namely �PDB 88-31�/�DPU 915� and �PLU 277�/�KAU7� had high per se performance along with positive significant SCA effect for seed yield/plant. The degree of dominance revealed overdominance for all the traits except clusters/plant with partial dominance. The predictability ratio also revealed the predominant role of nonadditive gene action in the genetic control of quantitative traits. Narrow sense heritability was also low for each trait. Recurrent selection or biparental mating followed by selection which can exploit both additive and nonadditive gene actions would be of interest for yield improvement in black gram. Due to presence of high magnitude of nonadditive gene action, heterosis breeding could also be attempted to develop low cost hybrid variety using genetic male sterility system in black gram.

  8. Mitochondrial morphology, topology, and membrane interactions in skeletal muscle: a quantitative three-dimensional electron microscopy study.

    Science.gov (United States)

    Picard, Martin; White, Kathryn; Turnbull, Douglass M

    2013-01-15

    Dynamic remodeling of mitochondrial morphology through membrane dynamics are linked to changes in mitochondrial and cellular function. Although mitochondrial membrane fusion/fission events are frequent in cell culture models, whether mitochondrial membranes dynamically interact in postmitotic muscle fibers in vivo remains unclear. Furthermore, a quantitative assessment of mitochondrial morphology in intact muscle is lacking. Here, using electron microscopy (EM), we provide evidence of interacting membranes from adjacent mitochondria in intact mouse skeletal muscle. Electron-dense mitochondrial contact sites consistent with events of outer mitochondrial membrane tethering are also described. These data suggest that mitochondrial membranes interact in vivo among mitochondria, possibly to induce morphology transitions, for kiss-and-run behavior, or other processes involving contact between mitochondrial membranes. Furthermore, a combination of freeze-fracture scanning EM and transmission EM in orthogonal planes was used to characterize and quantify mitochondrial morphology. Two subpopulations of mitochondria were studied: subsarcolemmal (SS) and intermyofibrillar (IMF), which exhibited significant differences in morphological descriptors, including form factor (means ± SD for SS: 1.41 ± 0.45 vs. IMF: 2.89 ± 1.76, P mitochondrial size and morphological parameters were highly skewed, suggesting the presence of mechanisms to influence mitochondrial size and shape. In addition, physical continuities between SS and IMF mitochondria indicated mixing of both subpopulations. These data provide evidence that mitochondrial membranes interact in vivo in mouse skeletal muscle and that factors may be involved in regulating skeletal muscle mitochondrial morphology.

  9. Genome-wide conserved non-coding microsatellite (CNMS) marker-based integrative genetical genomics for quantitative dissection of seed weight in chickpea

    Science.gov (United States)

    Bajaj, Deepak; Saxena, Maneesha S.; Kujur, Alice; Das, Shouvik; Badoni, Saurabh; Tripathi, Shailesh; Upadhyaya, Hari D.; Gowda, C. L. L.; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

    2015-01-01

    Phylogenetic footprinting identified 666 genome-wide paralogous and orthologous CNMS (conserved non-coding microsatellite) markers from 5′-untranslated and regulatory regions (URRs) of 603 protein-coding chickpea genes. The (CT)n and (GA)n CNMS carrying CTRMCAMV35S and GAGA8BKN3 regulatory elements, respectively, are abundant in the chickpea genome. The mapped genic CNMS markers with robust amplification efficiencies (94.7%) detected higher intraspecific polymorphic potential (37.6%) among genotypes, implying their immense utility in chickpea breeding and genetic analyses. Seventeen differentially expressed CNMS marker-associated genes showing strong preferential and seed tissue/developmental stage-specific expression in contrasting genotypes were selected to narrow down the gene targets underlying seed weight quantitative trait loci (QTLs)/eQTLs (expression QTLs) through integrative genetical genomics. The integration of transcript profiling with seed weight QTL/eQTL mapping, molecular haplotyping, and association analyses identified potential molecular tags (GAGA8BKN3 and RAV1AAT regulatory elements and alleles/haplotypes) in the LOB-domain-containing protein- and KANADI protein-encoding transcription factor genes controlling the cis-regulated expression for seed weight in the chickpea. This emphasizes the potential of CNMS marker-based integrative genetical genomics for the quantitative genetic dissection of complex seed weight in chickpea. PMID:25504138

  10. RSC Chromatography Monographs Quantitative In Silico Chromatography Computational Modelling of Molecular Interactions.

    Science.gov (United States)

    Hanai, Toshihiko

    2014-07-29

    All early chromatographic techniques, starting from the primitive "ancient" chromatography introduced by Tswett in the very early twentieth century, perfected in partition chromatography in the 1940s by Martin and Synge, and extended to a variety of additional separation mechanisms later, were first entirely experimental trial-and-error methods. The early years can also be characterized by searching for theoretical base of various separation techniques that would allow establishing relation between the structure of the analytes and their chromatographic behavior. The advent of computers followed by development of the new software then revolutionized the theoretical approaches and enabled detailed modeling instead of tedious experimentation. This book introduces the readers to the era of computational modeling in which molecular interactions are used to analyze the mechanisms of general molecular interactions with a special focus on biological applications. This article is protected by copyright. All rights reserved.

  11. A quantitative analysis of weak intermolecular interactions & quantum chemical calculations (DFT) of novel chalcone derivatives

    Science.gov (United States)

    Chavda, Bhavin R.; Gandhi, Sahaj A.; Dubey, Rahul P.; Patel, Urmila H.; Barot, Vijay M.

    2016-05-01

    The novel chalcone derivatives have widespread applications in material science and medicinal industries. The density functional theory (DFT) is used to optimized the molecular structure of the three chalcone derivatives (M-I, II, III). The observed discrepancies between the theoretical and experimental (X-ray data) results attributed to different environments of the molecules, the experimental values are of the molecule in solid state there by subjected to the intermolecular forces, like non-bonded hydrogen bond interactions, where as isolated state in gas phase for theoretical studies. The lattice energy of all the molecules have been calculated using PIXELC module in Coulomb -London -Pauli (CLP) package and is partitioned into corresponding coulombic, polarization, dispersion and repulsion contributions. Lattice energy data confirm and strengthen the finding of the X-ray results that the weak but significant intermolecular interactions like C-H…O, Π- Π and C-H… Π plays an important role in the stabilization of crystal packing.

  12. Dolphin interactions with the mullet artisanal fishing on Southern Brazil: a qualitative and quantitative approach

    Directory of Open Access Journals (Sweden)

    Paulo C. Simões-Lopes

    1998-01-01

    Full Text Available A detailed analysis of the interactions between Tursiops truncatus (Montagu, 1821 and the artisanal fishing of mullets (Mugil spp. is presented at two localities in the south of Brazil: Laguna (Santa Catarina and Inibé/Tramandaí (Rio Grande do Sul. Its behavioral strategies and the advantages of their association are re-described and quantified based on the success of the capture and on the selectivity of the prey sizes. The mullets are the main resource involved (92% to 75% both at numerical level and as biomass. Twenty individuals of Tursiops truncatus participated in the interactions in Laguna and 9 in Imbé/Tramandaí. The participation and learning of calves is also reported.

  13. Quantitative characterization of Tob interactions provides the thermodynamic basis for translation termination-coupled deadenylase regulation.

    Science.gov (United States)

    Ruan, Lin; Osawa, Masanori; Hosoda, Nao; Imai, Shunsuke; Machiyama, Asako; Katada, Toshiaki; Hoshino, Shin-ichi; Shimada, Ichio

    2010-09-03

    Translation termination-coupled deadenylation is the first and often the rate-limiting step of eukaryotic mRNA decay in which two deadenylases, Ccr4-Caf1 and Pan2, play key roles. One of the deadenylases, Caf1, associates with Tob, which recruits Caf1 to the poly(A) tail through interactions with a cytoplasmic poly(A)-binding protein 1 (PABPC1). We previously proposed that the competition between Tob and eRF3 (a translation termination factor that interacts with PABPC1) is responsible for the regulation of deadenylase activity. However, the molecular mechanism of the regulation should be addressed by investigating the binding affinity and the cellular levels of these proteins. In this work, we characterized the human Tob interactions with Caf1 and a C-terminal domain of PABPC1 (PABC). Nuclear magnetic resonance (NMR) and Western blot analyses revealed that Tob consists of a structured N-terminal BTG-Tob domain and an unstructured C-terminal region with two conserved PAM2 (PABPC1-interacting motif 2) motifs. The BTG-TOB domain associates with Caf1, whereas the C-terminal PAM2 motif binds to PABC, with a K(d) value of 20 microM. Furthermore, we demonstrated that the levels of eRF3 and Tob in HeLa cells are 4-5 microM and less than 0.2 microM, respectively. On the basis of these results, we propose a thermodynamic mechanism for the translation termination-coupled deadenylation mediated by the Tob-Caf1 complex.

  14. Quantitative analysis of the fusion cross sections using different microscopic nucleus-nucleus interactions

    Science.gov (United States)

    Adel, A.; Alharbi, T.

    2017-01-01

    The fusion cross sections for reactions involving medium and heavy nucleus-nucleus systems are investigated near and above the Coulomb barrier using the one-dimensional barrier penetration model. The microscopic nuclear interaction potential is computed by four methods, namely: the double-folding model based on a realistic density-dependent M3Y NN interaction with a finite-range exchange part, the Skyrme energy density functional in the semiclassical extended Thomas-Fermi approximation, the generalized Proximity potential, and the Akyüz-Winther interaction. The comparison between the calculated and the measured values of the fusion excitation functions indicates that the calculations of the DFM give quite satisfactory agreement with the experimental data, being much better than the other methods. New parameterized forms for the fusion barrier heights and positions are presented. Furthermore, the effects of deformation and orientation degrees of freedom on the distribution of the Coulomb barrier characteristics as well as the fusion cross sections are studied for the reactions 16 O + 70 Ge and 28 Si + 100 Mo. The calculated values of the total fusion cross sections are compared with coupled channel calculations using the code CCFULL and compared with the experimental data. Our results reveal that the inclusion of deformations and orientation degrees of freedom improves the comparison with the experimental data.

  15. A quantitative approach to study indirect effects among disease proteins in the human protein interaction network

    Directory of Open Access Journals (Sweden)

    Jordán Ferenc

    2010-07-01

    Full Text Available Abstract Background Systems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lead to diseases. Novel tools in network analysis provide the possibility to quantify the key interacting proteins in large networks as well as proteins that connect them. Here we suggest a new method to study the relationships between topology and functionality of the protein-protein interaction network, by identifying key mediator proteins possibly maintaining indirect relationships among proteins causing various diseases. Results Based on the i2d and OMIM databases, we have constructed (i a network of proteins causing five selected diseases (DP, disease proteins plus their interacting partners (IP, non-disease proteins, the DPIP network and (ii a protein network showing only these IPs and their interactions, the IP network. The five investigated diseases were (1 various cancers, (2 heart diseases, (3 obesity, (4 diabetes and (5 autism. We have quantified the number and strength of IP-mediated indirect effects between the five groups of disease proteins and hypothetically identified the most important mediator proteins linking heart disease to obesity or diabetes in the IP network. The results present the relationship between mediator role and centrality, as well as between mediator role and functional properties of these proteins. Conclusions We show that a protein which plays an important indirect mediator role between two diseases is not necessarily a hub in the PPI network. This may suggest that, even if hub proteins and disease proteins are trivially of great interest, mediators may also deserve more attention, especially if disease-disease associations are to be understood. Identifying the hubs may not be sufficient to understand

  16. Indirect genetic effects influence antipredator behavior in guppies: estimates of the coefficient of interaction psi and the inheritance of reciprocity.

    Science.gov (United States)

    Bleakley, Bronwyn H; Brodie, Edmund D

    2009-07-01

    How and why cooperation evolves, particularly among nonrelatives, remains a major paradox for evolutionary biologists and behavioral ecologists. Although much attention has focused on fitness consequences associated with cooperating, relatively little is known about the second component of evolutionary change, the inheritance of cooperation or reciprocity. The genetics of behaviors that can only be expressed in the context of interactions are particularly difficult to describe because the relevant genes reside in multiple social partners. Indirect genetic effects (IGEs) describe the influence of genes carried in social partners on the phenotype of a focal individual and thus provide a novel approach to quantifying the genetics underlying interactions such as reciprocal cooperation. We used inbred lines of guppies and a novel application of IGE theory to describe the dual genetic control of predator inspection and social behavior, both classic models of reciprocity. We identified effects of focal strain, social group strain, and interactions between focal and group strains on variation in focal behavior. We measured psi, the coefficient of the interaction, which describes the degree to which an individual's phenotype is influenced by the phenotype of its social partners. The genetic identity of social partners substantially influences inspection behavior, measures of threat assessment, and schooling and does so in positively reinforcing manner. We therefore demonstrate strong IGEs for antipredator behavior that represent the genetic variation necessary for the evolution of reciprocity.

  17. Quantitative micro-CT based coronary artery profiling using interactive local thresholding and cylindrical coordinates.

    Science.gov (United States)

    Panetta, Daniele; Pelosi, Gualtiero; Viglione, Federica; Kusmic, Claudia; Terreni, Marianna; Belcari, Nicola; Guerra, Alberto Del; Athanasiou, Lambros; Exarchos, Themistoklis; Fotiadis, Dimitrios I; Filipovic, Nenad; Trivella, Maria Giovanna; Salvadori, Piero A; Parodi, Oberdan

    2015-01-01

    Micro-CT is an established imaging technique for high-resolution non-destructive assessment of vascular samples, which is gaining growing interest for investigations of atherosclerotic arteries both in humans and in animal models. However, there is still a lack in the definition of micro-CT image metrics suitable for comprehensive evaluation and quantification of features of interest in the field of experimental atherosclerosis (ATS). A novel approach to micro-CT image processing for profiling of coronary ATS is described, providing comprehensive visualization and quantification of contrast agent-free 3D high-resolution reconstruction of full-length artery walls. Accelerated coronary ATS has been induced by high fat cholesterol-enriched diet in swine and left coronary artery (LCA) harvested en bloc for micro-CT scanning and histologic processing. A cylindrical coordinate system has been defined on the image space after curved multiplanar reformation of the coronary vessel for the comprehensive visualization of the main vessel features such as wall thickening and calcium content. A novel semi-automatic segmentation procedure based on 2D histograms has been implemented and the quantitative results validated by histology. The potentiality of attenuation-based micro-CT at low kV to reliably separate arterial wall layers from adjacent tissue as well as identify wall and plaque contours and major tissue components has been validated by histology. Morphometric indexes from histological data corresponding to several micro-CT slices have been derived (double observer evaluation at different coronary ATS stages) and highly significant correlations (R2 > 0.90) evidenced. Semi-automatic morphometry has been validated by double observer manual morphometry of micro-CT slices and highly significant correlations were found (R2 > 0.92). The micro-CT methodology described represents a handy and reliable tool for quantitative high resolution and contrast agent free full length

  18. A quantitative analysis of hydraulic interaction processes in stream-aquifer systems.

    Science.gov (United States)

    Wang, Wenke; Dai, Zhenxue; Zhao, Yaqian; Li, Junting; Duan, Lei; Wang, Zhoufeng; Zhu, Lin

    2016-01-28

    The hydraulic relationship between the stream and aquifer can be altered from hydraulic connection to disconnection when the pumping rate exceeds the maximum seepage flux of the streambed. This study proposes to quantitatively analyze the physical processes of stream-aquifer systems from connection to disconnection. A free water table equation is adopted to clarify under what conditions a stream starts to separate hydraulically from an aquifer. Both the theoretical analysis and laboratory tests have demonstrated that the hydraulic connectedness of the stream-aquifer system can reach a critical disconnection state when the horizontal hydraulic gradient at the free water surface is equal to zero and the vertical is equal to 1. A boundary-value problem for movement of the critical point of disconnection is established for an analytical solution of the inverted water table movement beneath the stream. The result indicates that the maximum distance or thickness of the inverted water table is equal to the water depth in the stream, and at a steady state of disconnection, the maximum hydraulic gradient at the streambed center is 2. This study helps us to understand the hydraulic phenomena of water flow near streams and accurately assess surface water and groundwater resources.

  19. Interactions of Indole Derivatives with β-Cyclodextrin: A Quantitative Structure-Property Relationship Study.

    Directory of Open Access Journals (Sweden)

    Milan Šoškić

    Full Text Available Retention factors for 31 indole derivatives, most of them with auxin activity, were determined by high-performance liquid chromatography, using bonded β-cyclodextrin as a stationary phase. A three-parameter QSPR (quantitative structure-property relationship model, based on physico-chemical and structural descriptors was derived, which accounted for about 98% variations in the retention factors. The model suggests that the indole nucleus occupies the relatively apolar cavity of β-cyclodextrin while the carboxyl group of the indole -3-carboxylic acids makes hydrogen bonds with the hydroxyl groups of β-cyclodextrin. The length and flexibility of the side chain containing carboxyl group strongly affect the binding of these compounds to β-cyclodextrin. Non-acidic derivatives, unlike the indole-3-carboxylic acids, are poorly retained on the column. A reasonably well correlation was found between the retention factors of the indole-3-acetic acids and their relative binding affinities for human serum albumin, a carrier protein in the blood plasma. A less satisfactory correlation was obtained when the retention factors of the indole derivatives were compared with their affinities for auxin-binding protein 1, a plant auxin receptor.

  20. Interactions of Indole Derivatives with β-Cyclodextrin: A Quantitative Structure-Property Relationship Study.

    Science.gov (United States)

    Šoškić, Milan; Porobić, Ivana

    2016-01-01

    Retention factors for 31 indole derivatives, most of them with auxin activity, were determined by high-performance liquid chromatography, using bonded β-cyclodextrin as a stationary phase. A three-parameter QSPR (quantitative structure-property relationship) model, based on physico-chemical and structural descriptors was derived, which accounted for about 98% variations in the retention factors. The model suggests that the indole nucleus occupies the relatively apolar cavity of β-cyclodextrin while the carboxyl group of the indole -3-carboxylic acids makes hydrogen bonds with the hydroxyl groups of β-cyclodextrin. The length and flexibility of the side chain containing carboxyl group strongly affect the binding of these compounds to β-cyclodextrin. Non-acidic derivatives, unlike the indole-3-carboxylic acids, are poorly retained on the column. A reasonably well correlation was found between the retention factors of the indole-3-acetic acids and their relative binding affinities for human serum albumin, a carrier protein in the blood plasma. A less satisfactory correlation was obtained when the retention factors of the indole derivatives were compared with their affinities for auxin-binding protein 1, a plant auxin receptor.

  1. Genetic and physical interaction of Meis2, Pax3 and Pax7 during dorsal midbrain development

    Directory of Open Access Journals (Sweden)

    Agoston Zsuzsa

    2012-03-01

    Full Text Available Abstract Background During early stages of brain development, secreted molecules, components of intracellular signaling pathways and transcriptional regulators act in positive and negative feed-back or feed-forward loops at the mid-hindbrain boundary. These genetic interactions are of central importance for the specification and subsequent development of the adjacent mid- and hindbrain. Much less, however, is known about the regulatory relationship and functional interaction of molecules that are expressed in the tectal anlage after tectal fate specification has taken place and tectal development has commenced. Results Here, we provide experimental evidence for reciprocal regulation and subsequent cooperation of the paired-type transcription factors Pax3, Pax7 and the TALE-homeodomain protein Meis2 in the tectal anlage. Using in ovo electroporation of the mesencephalic vesicle of chick embryos we show that (i Pax3 and Pax7 mutually regulate each other's expression in the mesencephalic vesicle, (ii Meis2 acts downstream of Pax3/7 and requires balanced expression levels of both proteins, and (iii Meis2 physically interacts with Pax3 and Pax7. These results extend our previous observation that Meis2 cooperates with Otx2 in tectal development to include Pax3 and Pax7 as Meis2 interacting proteins in the tectal anlage. Conclusion The results described here suggest a model in which interdependent regulatory loops involving Pax3 and Pax7 in the dorsal mesencephalic vesicle modulate Meis2 expression. Physical interaction with Meis2 may then confer tectal specificity to a wide range of otherwise broadly expressed transcriptional regulators, including Otx2, Pax3 and Pax7.

  2. The Interaction between Pesticide Use and Genetic Variants Involved in Lipid Metabolism on Prostate Cancer Risk

    Directory of Open Access Journals (Sweden)

    Gabriella Andreotti

    2012-01-01

    Full Text Available Background. Lipid metabolism processes have been implicated in prostate carcinogenesis. Since several pesticides are lipophilic or are metabolized via lipid-related mechanisms, they may interact with variants of genes in the lipid metabolism pathway. Methods. In a nested case-control study of 776 cases and 1444 controls from the Agricultural Health Study (AHS, a prospective cohort study of pesticide applicators, we examined the interactions between 39 pesticides (none, low, and high exposure and 220 single nucleotide polymorphisms (SNPs in 59 genes. The false discovery rate (FDR was used to account for multiple comparisons. Results. We found 17 interactions that displayed a significant monotonic increase in prostate cancer risk with pesticide exposure in one genotype and no significant association in the other genotype. The most noteworthy association was for ALOXE3 rs3027208 and terbufos, such that men carrying the T allele who were low users had an OR of 1.86 (95% CI = 1.16–2.99 and high users an OR of 2.00 (95% CI = 1.28–3.15 compared to those with no use of terbufos, while men carrying the CC genotype did not exhibit a significant association. Conclusion. Genetic variation in lipid metabolism genes may modify pesticide associations with prostate cancer; however our results require replication.

  3. Genetic identification of a network of factors that functionally interact with the nucleosome remodeling ATPase ISWI.

    Directory of Open Access Journals (Sweden)

    Giosalba Burgio

    2008-06-01

    Full Text Available Nucleosome remodeling and covalent modifications of histones play fundamental roles in chromatin structure and function. However, much remains to be learned about how the action of ATP-dependent chromatin remodeling factors and histone-modifying enzymes is coordinated to modulate chromatin organization and transcription. The evolutionarily conserved ATP-dependent chromatin-remodeling factor ISWI plays essential roles in chromosome organization, DNA replication, and transcription regulation. To gain insight into regulation and mechanism of action of ISWI, we conducted an unbiased genetic screen to identify factors with which it interacts in vivo. We found that ISWI interacts with a network of factors that escaped detection in previous biochemical analyses, including the Sin3A gene. The Sin3A protein and the histone deacetylase Rpd3 are part of a conserved histone deacetylase complex involved in transcriptional repression. ISWI and the Sin3A/Rpd3 complex co-localize at specific chromosome domains. Loss of ISWI activity causes a reduction in the binding of the Sin3A/Rpd3 complex to chromatin. Biochemical analysis showed that the ISWI physically interacts with the histone deacetylase activity of the Sin3A/Rpd3 complex. Consistent with these findings, the acetylation of histone H4 is altered when ISWI activity is perturbed in vivo. These findings suggest that ISWI associates with the Sin3A/Rpd3 complex to support its function in vivo.

  4. Probing Protein-Protein Interactions with Genetically Encoded Photoactivatable Cross-Linkers.

    Science.gov (United States)

    Cooley, Richard B; Sondermann, Holger

    2017-01-01

    Fundamental to all living organisms is the ability of proteins to interact with other biological molecules at the right time and location, with the proper affinity, and to do so reversibly. One well-established technique to study protein interactions is chemical cross-linking, a process in which proteins in close spatial proximity are covalently tethered together. An emerging technology that overcomes many limitations of traditional cross-linking methods is one in which photoactivatable cross-linking noncanonical amino acids are genetically encoded into a protein of interest using the cell's native translational machinery. These proteins can then be used to trap interacting biomolecules upon UV illumination. Here, we describe a method for the site-specific incorporation of photoactivatable cross-linking amino acids into fluorescently tagged proteins of interest in E. coli. Photo-cross-linking and analysis by SDS-PAGE using in-gel fluorescence detection, which provides rapid, highly sensitive, and specific detection of cross-linked adducts even in impure systems, are also described. An example expression and cross-linking experiment involving transmembrane signaling of a bacterial second messenger receptor system that controls biofilm formation is shown. All reagents needed to carry out these experiments are commercially available, and do not require special or unique technology to perform, making this method tractable to a broad community studying protein structure and function.

  5. A quantitative analysis of weak intermolecular interactions & quantum chemical calculations (DFT) of novel chalcone derivatives

    Energy Technology Data Exchange (ETDEWEB)

    Chavda, Bhavin R., E-mail: chavdabhavin9@gmail.com; Dubey, Rahul P.; Patel, Urmila H. [Department of Physics, Sardar Patel University, Vallabh Vidyanagar-388120, Gujarat (India); Gandhi, Sahaj A. [Bhavan’s Shri I.L. Pandya Arts-Science and Smt. J.M. shah Commerce College, Dakar, Anand -388001, Gujarat, Indian (India); Barot, Vijay M. [P. G. Center in Chemistry, Smt. S. M. Panchal Science College, Talod, Gujarat 383 215 (India)

    2016-05-06

    The novel chalcone derivatives have widespread applications in material science and medicinal industries. The density functional theory (DFT) is used to optimized the molecular structure of the three chalcone derivatives (M-I, II, III). The observed discrepancies between the theoretical and experimental (X-ray data) results attributed to different environments of the molecules, the experimental values are of the molecule in solid state there by subjected to the intermolecular forces, like non-bonded hydrogen bond interactions, where as isolated state in gas phase for theoretical studies. The lattice energy of all the molecules have been calculated using PIXELC module in Coulomb –London –Pauli (CLP) package and is partitioned into corresponding coulombic, polarization, dispersion and repulsion contributions. Lattice energy data confirm and strengthen the finding of the X-ray results that the weak but significant intermolecular interactions like C-H…O, Π- Π and C-H… Π plays an important role in the stabilization of crystal packing.

  6. Protein-nanoparticle interactions evaluation by immunomethods: Surfactants can disturb quantitative determinations.

    Science.gov (United States)

    Fornaguera, Cristina; Calderó, Gabriela; Solans, Conxita; Vauthier, Christine

    2015-08-01

    The adsorption of proteins on nanoparticle surface is one of the first events that occur when nanoparticles enter in the blood stream, which influences nanoparticles lifetime and further biodistribution. Albumin, which is the most abundant protein in serum and which has been deeply characterized, is an interesting model protein to investigate nanoparticle-protein interactions. Therefore, the interaction of nanoparticles with serum albumin has been widely studied. Immunomethods were suggested for the investigation of adsorption isotherms because of their ease to quantify the non-adsorbed bovine serum albumin without the need of applying separation methods that could modify the balance between the adsorbed and non-adsorbed proteins. The present work revealed that this method should be applied with caution. Artifacts in the determination of free protein can be generated by the presence of surfactants such as polysorbate 80, widely used in the pharmaceutical and biomedical field, that are needed to preserve the stability of nanoparticle dispersions. It was shown that the presence of traces of polysorbate 80 in the dispersion leads to an overestimation of the amount of bovine serum albumin remaining free in the dispersion medium when determined by both radial immunodiffusion and rocket immunoelectrophoresis. However, traces of poloxamer 188 did not result in clear perturbed migrations. These methods are not appropriate to perform adsorption isotherms of proteins on nanoparticle dispersions containing traces of remaining free surfactant. They should only be applied on dispersions that are free of surfactant that is not associated with nanoparticles.

  7. Quantitative ethnographic study of physician workflow and interactions with electronic health record systems.

    Science.gov (United States)

    Asan, Onur; Chiou, Erin; Montague, Enid

    2015-09-01

    This study explores the relationship between primary care physicians' interactions with health information technology and primary care workflow. Clinical encounters were recorded with high-resolution video cameras to capture physicians' workflow and interaction with two objects of interest, the electronic health record (EHR) system, and their patient. To analyze the data, a coding scheme was developed based on a validated list of primary care tasks to define the presence or absence of a task, the time spent on each task, and the sequence of tasks. Results revealed divergent workflows and significant differences between physicians' EHR use surrounding common workflow tasks: gathering information, documenting information, and recommend/discuss treatment options. These differences suggest impacts of EHR use on primary care workflow, and capture types of workflows that can be used to inform future studies with larger sample sizes for more effective designs of EHR systems in primary care clinics. Future research on this topic and design strategies for effective health information technology in primary care are discussed.

  8. The 1997 Kagoshima (Japan) Earthquake Doublet: A Quantitative Analysis of Stress Interaction

    Science.gov (United States)

    Woessner, J.; Hauksson, E.; Wiemer, S.; Neukomm, S.

    2003-12-01

    Understanding how the nucleation of earthquakes is affected by sudden changes in the state of stress in their immediate vicinity may provide insight into the elusive relationship between static stress changes and earthquake occurrence. As working hypothesis, we assume that if aftershocks are in part caused by stress changes from their mainshock, changes in their decay rate may reflect changes in the state of stress induced by nearby large earthquakes. The 1997 Kagoshima (Japan) earthquake doublet provides a unique opportunity to analyze this hypothesis for two moderate M6 events that occurred on adjacent faults with the epicenters located in a distance of about 5 km from each other. We map the Omori law parameters on an equally spaced grid for the time period between the two mainshocks (the learning period of 47.8 days) using four Omori law type models with increasing complexity. The best fitting model is found using the corrected Akaike Criterion Information. We then forecast the number of aftershocks for the next 50 days and compare it to the actual observed number. Uncertainties in the rate forecasts are obtained by a bootstrap approach, allowing us to compute a detailed map of the significance of the relative rate changes. We find four regions with highly significant relative rate changes, three negative and one positive, which are a consequence of the activation and deactivation of aftershock activity due to the second mainshock, respectively. While our results confirm a relative rate drop in the Western part of the aftershock sequence that is in agreement with the stress triggering hypothesis (Stein, 2003), the other changes cannot be readily explained. Because of the importance of rate changes for the evaluation of the stress triggering hypothesis as well as for rate and state friction models, we consider our quantitative analysis technique introduced here important and a step forward in the process of understanding the behavior of aftershocks.

  9. Quantitative analysis of chemical interaction and doping of the Si(111) native oxide surface with tetrafluorotetracyanoquinodimethane

    Energy Technology Data Exchange (ETDEWEB)

    Yoshimoto, Shinya, E-mail: yosshi@issp.u-tokyo.ac.jp; Furuhashi, Masayuki; Koitaya, Takanori; Shiozawa, Yuichiro; Fujimaki, Kazutaka; Harada, Yosuke; Mukai, Kozo; Yoshinobu, Jun [The Institute for Solid State Physics, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8581 (Japan)

    2014-04-14

    The charge-transfer states and the carrier concentration of the native oxide Si(111) surface adsorbed with 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F{sub 4}-TCNQ) were investigated by X-ray photoelectron spectroscopy (XPS) and independently driven four-probe electrical conductivity measurements. The XPS results show that F{sub 4}-TCNQ molecules are involved in charge transfer with the SiO{sub 2}/Si(111) surface. The Si 2p XPS spectra and the surface photovoltage shift provide the evidences of (i) change in the oxidation states at the SiO{sub 2}-Si(111) interface region and (ii) formation of a p-type space charge layer (SCL) with a hole concentration of 1.7 × 10{sup 10} cm{sup −2}, respectively. The four-probe I–V measurements also support the formation of the p-type SCL, and the estimated hole concentration of 2.0 × 10{sup 10} cm{sup −2} agrees well with the XPS results. The estimated SCL hole concentrations were much smaller than the excess charge density in the F{sub 4}-TCNQ layer, of the order of 10{sup 13} cm{sup −2}, suggesting that most of charges were localized as the oxidation states at the SiO{sub 2}-Si(111) interface region. The present quantitative methods ensure precise determination of the doping concentration near the surface region.

  10. Quantitative Analysis of the Microtubule Interaction of Rabies Virus P3 Protein: Roles in Immune Evasion and Pathogenesis.

    Science.gov (United States)

    Brice, Aaron; Whelan, Donna R; Ito, Naoto; Shimizu, Kenta; Wiltzer-Bach, Linda; Lo, Camden Y; Blondel, Danielle; Jans, David A; Bell, Toby D M; Moseley, Gregory W

    2016-09-21

    Although microtubules (MTs) are known to have important roles in intracellular transport of many viruses, a number of reports suggest that specific viral MT-associated proteins (MAPs) target MTs to subvert distinct MT-dependent cellular processes. The precise functional importance of these interactions and their roles in pathogenesis, however, remain largely unresolved. To assess the association with disease of the rabies virus (RABV) MAP, P3, we quantitatively compared the phenotypes of P3 from a pathogenic RABV strain, Nishigahara (Ni) and a non-pathogenic Ni-derivative strain, Ni-CE. Using confocal/live-cell imaging and dSTORM super-resolution microscopy to quantify protein interactions with the MT network and with individual MT filaments, we found that the interaction by Ni-CE-P3 is significantly impaired compared with Ni-P3. This correlated with an impaired capacity to effect association of the transcription factor STAT1 with MTs and to antagonize interferon (IFN)/STAT1-dependent antiviral signaling. Importantly, we identified a single mutation in Ni-CE-P3 that is sufficient to inhibit MT-association and IFN-antagonist function of Ni-P3, and showed that this mutation alone attenuates the pathogenicity of RABV. These data provide evidence that the viral protein-MT interface has important roles in pathogenesis, suggesting that this interface could provide targets for vaccine/antiviral drug development.

  11. Quantitative genetics of growth and development time in the burying beetle Nicrophorus pustulatus in the presence and absence of post-hatching parental care.

    Science.gov (United States)

    Rauter, Claudia M; Moore, Allen J

    2002-01-01

    Despite a growing interest in the evolutionary aspects of maternal effects, few studies have examined the genetic consequences of maternal effects associated with parental care. To begin to provide data on nonlaboratory or nondomestic animals, we compared the effect of presence and absence of parental care on phenotype expression of larval mass and development time at different life-history stages in the burying beetle Nicrophorus pustulatus. This beetle has facultative care; parents can feed their larvae through regurgitation of digested carrion or offspring can feed by themselves from previously prepared carrion. To investigate larval responses to these two levels of care, including estimates of additive genetic effects, maternal effects, and genotype-by-environment interactions, we used a half-sibling split-family breeding experiment-raising half of the offspring of a family in the presence of their mother and the other half without their mother present. Larvae reared with their mother present were on average heavier and developed faster, although some of the differences in development decreased or were eliminated by the adult stage. These results suggest that presence or absence of post-hatching maternal care plays an important role in phenotype expression early in life, whereas later the phenotype of the offspring is determined mainly by the genotype and/or unshared environmental effects. Our study also permitted us to examine the differences in genetic effects between the two care environments. Heritabilities, maternal/common environment effect, and most genetic correlations did not differ between the care treatments. Genetic analyses revealed substantial additive genetic effects for development time but small effects for measures of body mass. Maternal plus common environment effects were high for measures of mass but low for development time, suggesting that indirect genetic effects of maternal and/or common environment are less important for the evolution

  12. From beavis to beak color: a simulation study to examine how much qtl mapping can reveal about the genetic architecture of quantitative traits.

    Science.gov (United States)

    Slate, Jon

    2013-05-01

    Quantitative trait locus (QTL) mapping is frequently used in evolutionary studies to understand the genetic architecture of continuously varying traits. The majority of studies have been conducted in specially created crosses, in which genetic differences between parental lines are identified by linkage analysis. Detecting QTL segregating within populations is more problematic, especially in wild populations, because these populations typically have complicated and unbalanced multigenerational pedigrees. However, QTL mapping can still be conducted in such populations using a variance components mixed model approach, and the advent of appropriate statistical frameworks and better genotyping methods mean that the approach is gaining popularity. In this study it is shown that all studies described to date report evidence of QTL of major effect on trait variation, but that these findings are probably caused by inflated estimates of QTL effect sizes due to the Beavis effect. Using simulations I show that even the most powerful studies conducted to date are likely to give misleading descriptions of the genetic architecture of a trait. I show that an interpretation of a mapping study of beak color in the zebra finch (Taeniopygia guttata), that suggested genetic variation was determined by a small number of loci of large effect, which are possibly maintained by antagonistic pleiotropy, is likely to be incorrect. More generally, recommendations are made to how QTL mapping can be combined with other approaches to provide more accurate descriptions of a trait's genetic architecture.

  13. A quantitative approach to the free radical interaction between alpha-tocopherol or ascorbate and flavonoids.

    Science.gov (United States)

    Fujisawa, Seiichiro; Ishihara, Mariko; Atsumi, Toshiko; Kadoma, Yoshinori

    2006-01-01

    Despite numerous previous studies, the mechanism of the free radical interaction between alpha-tocopherol (VE), or ascorbate and flavonoids, as coantioxidants remains unclear. The synergistic antioxidant effects of VE or L-ascorbyl 2,6-dibutyrate (ASDB, an ascorbate derivative) with the flavonoids (-)-epicatechin (EC), (-)-epigallocatechin (EGC), (-)-epicatechin gallate (ECG) and (-)-epigallocatechin gallate (EGCG) and methyl gallate (MG), were investigated by the induction period method in the polymerization of methyl methacrylate (MMA), initiated by thermal decomposition of 2,2'-azobis(isobutyronitrile) (an alkyl radical, R *), under nearly anaerobic conditions. For VE, a synergistic antioxidant effect was observed with MG, EC, EGC and ECG, whereas this activity was decreased by the addition of EGCG. For ASDB, a synergistic antioxidant effect was observed with EGC and ECG, whereas this activity was decreased by the addition of EGCG or MG. A synergistic antioxidant effect (regeneration of VE) appears to be feasible even though the BDE (phenolic O-H bond dissociation entropy) of the coantioxidants is significantly higher than that of VE. The driving force for the regeneration process may be the removal of the semiquinone radical from the flavonoids MG, EC, EGC and ECG by the VE radical. In the ASDB/flavonoid mixture, flavonoid radicals are scavenged by ASDB. The partial regeneration of flavonoids by ASDB may follow a similar recycling mechanism to that of the well-known VE/ascorbate mixture. The free radical interaction between EGCG and VE or ASDB decreased the antioxidant effect. Such enhancement of prooxidation in EGCG/VE or EGCG/ASDB mixtures oxidized by R * may increase their cytotoxic effects.

  14. Quantitation of interaction of lipids with polymer surfaces in cell culture.

    Science.gov (United States)

    Altaras, Gina M; Eklund, Carrie; Ranucci, Colette; Maheshwari, Gargi

    2007-04-01

    As cell culture medium development efforts have progressed towards leaner, serum-free, and chemically defined formulations, it has become increasingly important to ensure that the appropriate concentrations of all nutrients are maintained and delivered at point of use. In light of concurrent efforts to progress to disposable polymeric storage and culture platforms, the characterization and control of medium component interactions with container surfaces can be a key issue in ensuring consistent delivery of these medium formulations. These studies characterize the interactions of lipids with culture surfaces typically encountered in the bioprocess industry using model systems. The extent and kinetics of lipid association with polymeric surfaces were determined using radio-labeled linoleic acid and cholesterol. The effect of methyl-beta-cyclodextrin, a component commonly used to solubilize lipids in culture media, on association kinetics was also examined. In addition, loss of lipids across a sterilizing membrane filter was quantified. We find that there is potential for significant loss of hydrophobic components due to non-specific binding to surfaces at timescales relevant to a typical cell culture process. The extent of loss is dependent on the nature of the hydrophobic component as well as the type of surface. These studies highlight the potential of the extracellular environment to modify medium composition and also emphasize the importance of medium formulation strategies, including those used in the delivery of hydrophobic components. It is noted, however, that the level of loss is very dependent on the specific system including the composition of the culture medium used. (c) 2006 Wiley Periodicals, Inc.

  15. Hybrid Genetic Algorithm Based Optimization of Coupled HMM for Complex Interacting Processes Recognition

    Institute of Scientific and Technical Information of China (English)

    Liu Jianghua(刘江华); Chen Jiapin; Cheng Junshi

    2004-01-01

    Coupled Hidden Markov Model (CHMM) is the extension of traditional HMM, which is mainly used for complex interactive process modeling such as two-hand gestures. However, the problems of finding optimal model parameter are still of great interest to the researches in this area. This paper proposes a hybrid genetic algorithm (HGA) for the CHMM training. Chaos is used to initialize GA and used as mutation operator. Experiments on Chinese TaiChi gestures show that standard GA (SGA) based CHMM training is superior to Maximum Likelihood (ML) HMM training. HGA approach has the highest recognition rate of 98.0769%, then 96.1538% for SGA. The last one is ML method, only with a recognition rate of 69.2308%.

  16. Developmental cartography: coordination via hormonal and genetic interactions during gynoecium formation.

    Science.gov (United States)

    Deb, Joyita; Bland, Heather M; Østergaard, Lars

    2017-09-26

    Development in multicellular organisms requires the establishment of tissue identity through polarity cues. The Arabidopsis gynoecium presents an excellent model to study this coordination, as it comprises a complex tissue structure which is established through multiple polarity systems. The gynoecium is derived from the fusion of two carpels and forms in the centre of the flower. Many regulators of carpel development also have roles in leaf development, emphasizing the evolutionary origin of carpels as modified leaves. The gynoecium can therefore be considered as having evolved from a simple setup followed by adjustment in tissue polarity to facilitate efficient reproduction. Here, we discuss concepts to understand how hormonal and genetic systems interact to pattern the gynoecium. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  17. Interaction of genetic and exposure factors in the prevalence of berylliosis.

    Science.gov (United States)

    Richeldi, L; Kreiss, K; Mroz, M M; Zhen, B; Tartoni, P; Saltini, C

    1997-10-01

    Prevalence of berylliosis, a lung disorder driven by the activation of beryllium-specific T cells, is associated with a major histocompatibility complex (MHC) class II marker (HLA-DPB1Glu69) and with the type of industrial exposure. We evaluated the interaction between marker and exposure in a beryllium-exposed population in which the prevalence of berylliosis was associated with machining beryllium. The presence of the marker was associated with higher prevalence (HLA-DPB1Glu69-positive machinists 25%; HLA-DPB1Glu69-negative machinists 3.2%, P = 0.05) and predicted berylliosis independent of machining history (odds ratios 11.8 and 10.1). The study shows that in berylliosis the carrier status of a genetic susceptibility factor adds to the effect of process-related risk factors.

  18. Phylogeographic Triangulation: Using Predator-Prey-Parasite Interactions to Infer Population History from Partial Genetic Information

    Science.gov (United States)

    Barbosa, A. Márcia; Thode, Guillermo; Real, Raimundo; Feliu, Carlos; Vargas, J. Mario

    2012-01-01

    Phylogeographic studies, which infer population history and dispersal movements from intra-specific spatial genetic variation, require expensive and time-consuming analyses that are not always feasible, especially in the case of rare or endangered species. On the other hand, comparative phylogeography of species involved in close biotic interactions may show congruent patterns depending on the specificity of the relationship. Consequently, the phylogeography of a parasite that needs two hosts to complete its life cycle should reflect population history traits of both hosts. Population movements evidenced by the parasite’s phylogeography that are not reflected in the phylogeography of one of these hosts may thus be attributed to the other host. Using the wild rabbit (Oryctolagus cuniculus) and a parasitic tapeworm (Taenia pisiformis) as an example, we propose comparing the phylogeography of easily available organisms such as game species and their specific heteroxenous parasites to infer population movements of definitive host/predator species, independently of performing genetic analyses on the latter. This may be an interesting approach for indirectly studying the history of species whose phylogeography is difficult to analyse directly. PMID:23209834

  19. Cuckoo search epistasis: a new method for exploring significant genetic interactions.

    Science.gov (United States)

    Aflakparast, M; Salimi, H; Gerami, A; Dubé, M-P; Visweswaran, S; Masoudi-Nejad, A

    2014-06-01

    The advent of high-throughput sequencing technology has resulted in the ability to measure millions of single-nucleotide polymorphisms (SNPs) from thousands of individuals. Although these high-dimensional data have paved the way for better understanding of the genetic architecture of common diseases, they have also given rise to challenges in developing computational methods for learning epistatic relationships among genetic markers. We propose a new method, named cuckoo search epistasis (CSE) for identifying significant epistatic interactions in population-based association studies with a case-control design. This method combines a computationally efficient Bayesian scoring function with an evolutionary-based heuristic search algorithm, and can be efficiently applied to high-dimensional genome-wide SNP data. The experimental results from synthetic data sets show that CSE outperforms existing methods including multifactorial dimensionality reduction and Bayesian epistasis association mapping. In addition, on a real genome-wide data set related to Alzheimer's disease, CSE identified SNPs that are consistent with previously reported results, and show the utility of CSE for application to genome-wide data.

  20. Genetic cross-interaction between APOE and PRNP in sporadic Alzheimer's and Creutzfeldt-Jakob diseases.

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    Olga Calero

    Full Text Available Alzheimer's disease (AD and Creutzfeldt-Jakob disease (CJD represent two distinct clinical entities belonging to a wider group, generically named as conformational disorders that share common pathophysiologic mechanisms. It is well-established that the APOE ε4 allele and homozygosity at polymorphic codon 129 in the PRNP gene are the major genetic risk factors for AD and human prion diseases, respectively. However, the roles of PRNP in AD, and APOE in CJD are controversial. In this work, we investigated for the first time, APOE and PRNP genotypes simultaneously in 474 AD and 175 sporadic CJD (sCJD patients compared to a common control population of 335 subjects. Differences in genotype distribution between patients and control subjects were studied by logistic regression analysis using age and gender as covariates. The effect size of risk association and synergy factors were calculated using the logistic odds ratio estimates. Our data confirmed that the presence of APOE ε4 allele is associated with a higher risk of developing AD, while homozygosity at PRNP gene constitutes a risk for sCJD. Opposite, we found no association for PRNP with AD, nor for APOE with sCJD. Interestingly, when AD and sCJD patients were stratified according to their respective main risk genes (APOE for AD, and PRNP for sCJD, we found statistically significant associations for the other gene in those strata at higher previous risk. Synergy factor analysis showed a synergistic age-dependent interaction between APOE and PRNP in both AD (SF = 3.59, p = 0.027, and sCJD (SF = 7.26, p = 0.005. We propose that this statistical epistasis can partially explain divergent data from different association studies. Moreover, these results suggest that the genetic interaction between APOE and PRNP may have a biological correlate that is indicative of shared neurodegenerative pathways involved in AD and sCJD.

  1. Intramolecular interactions in aminoacyl nucleotides: Implications regarding the origin of genetic coding and protein synthesis

    Science.gov (United States)

    Lacey, J. C., Jr.; Mullins, D. W., Jr.; Watkins, C. L.; Hall, L. M.

    1986-01-01

    Cellular organisms store information as sequences of nucleotides in double stranded DNA. This information is useless unless it can be converted into the active molecular species, protein. This is done in contemporary creatures first by transcription of one strand to give a complementary strand of mRNA. The sequence of nucleotides is then translated into a specific sequence of