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Sample records for additive genetic models

  1. Factor analysis models for structuring covariance matrices of additive genetic effects: a Bayesian implementation

    PubMed Central

    de los Campos, Gustavo; Gianola, Daniel

    2007-01-01

    Multivariate linear models are increasingly important in quantitative genetics. In high dimensional specifications, factor analysis (FA) may provide an avenue for structuring (co)variance matrices, thus reducing the number of parameters needed for describing (co)dispersion. We describe how FA can be used to model genetic effects in the context of a multivariate linear mixed model. An orthogonal common factor structure is used to model genetic effects under Gaussian assumption, so that the marginal likelihood is multivariate normal with a structured genetic (co)variance matrix. Under standard prior assumptions, all fully conditional distributions have closed form, and samples from the joint posterior distribution can be obtained via Gibbs sampling. The model and the algorithm developed for its Bayesian implementation were used to describe five repeated records of milk yield in dairy cattle, and a one common FA model was compared with a standard multiple trait model. The Bayesian Information Criterion favored the FA model. PMID:17897592

  2. Functional Generalized Additive Models.

    PubMed

    McLean, Mathew W; Hooker, Giles; Staicu, Ana-Maria; Scheipl, Fabian; Ruppert, David

    2014-01-01

    We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F(·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X(t) is a signal from diffusion tensor imaging at position, t, along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online. PMID:24729671

  3. Additive-dominance genetic model analyses for late-maturity alpha-amylase activity in a bread wheat factorial crossing population.

    PubMed

    Rasul, Golam; Glover, Karl D; Krishnan, Padmanaban G; Wu, Jixiang; Berzonsky, William A; Ibrahim, Amir M H

    2015-12-01

    Elevated level of late maturity α-amylase activity (LMAA) can result in low falling number scores, reduced grain quality, and downgrade of wheat (Triticum aestivum L.) class. A mating population was developed by crossing parents with different levels of LMAA. The F2 and F3 hybrids and their parents were evaluated for LMAA, and data were analyzed using the R software package 'qgtools' integrated with an additive-dominance genetic model and a mixed linear model approach. Simulated results showed high testing powers for additive and additive × environment variances, and comparatively low powers for dominance and dominance × environment variances. All variance components and their proportions to the phenotypic variance for the parents and hybrids were significant except for the dominance × environment variance. The estimated narrow-sense heritability and broad-sense heritability for LMAA were 14 and 54%, respectively. High significant negative additive effects for parents suggest that spring wheat cultivars 'Lancer' and 'Chester' can serve as good general combiners, and that 'Kinsman' and 'Seri-82' had negative specific combining ability in some hybrids despite of their own significant positive additive effects, suggesting they can be used as parents to reduce LMAA levels. Seri-82 showed very good general combining ability effect when used as a male parent, indicating the importance of reciprocal effects. High significant negative dominance effects and high-parent heterosis for hybrids demonstrated that the specific hybrid combinations; Chester × Kinsman, 'Lerma52' × Lancer, Lerma52 × 'LoSprout' and 'Janz' × Seri-82 could be generated to produce cultivars with significantly reduced LMAA level. PMID:26403988

  4. Mixed additive models

    NASA Astrophysics Data System (ADS)

    Carvalho, Francisco; Covas, Ricardo

    2016-06-01

    We consider mixed models y =∑i =0 w Xiβi with V (y )=∑i =1 w θiMi Where Mi=XiXi⊤ , i = 1, . . ., w, and µ = X0β0. For these we will estimate the variance components θ1, . . ., θw, aswell estimable vectors through the decomposition of the initial model into sub-models y(h), h ∈ Γ, with V (y (h ))=γ (h )Ig (h )h ∈Γ . Moreover we will consider L extensions of these models, i.e., y˚=Ly+ɛ, where L=D (1n1, . . ., 1nw) and ɛ, independent of y, has null mean vector and variance covariance matrix θw+1Iw, where w =∑i =1 n wi .

  5. Explaining additional genetic variation in complex traits

    PubMed Central

    Robinson, Matthew R.; Wray, Naomi R.; Visscher, Peter M.

    2015-01-01

    Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of complex traits, discovering >6000 variants associated with >500 quantitative traits and common complex diseases in humans. The associations identified so far represent only a fraction of those which influence phenotype, as there are likely to be very many variants across the entire frequency spectrum, each of which influences multiple traits, with only a small average contribution to the phenotypic variance. This presents a considerable challenge to further dissection of the remaining unexplained genetic variance within populations, which limits our ability to predict disease risk, identify new drug targets, improve and maintain food sources, and understand natural diversity. This challenge will be met within the current framework through larger sample size, better phenotyping including recording of non-genetic risk factors, focused study designs, and an integration of multiple sources of phenotypic and genetic information. The current evidence supports the application of quantitative genetic approaches, and we argue that one should retain simpler theories until simplicity can be traded for greater explanatory power. PMID:24629526

  6. Unnatural reactive amino acid genetic code additions

    SciTech Connect

    Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.

    2011-08-09

    This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNAsyn-thetases, pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

  7. Unnatural reactive amino acid genetic code additions

    SciTech Connect

    Deiters, Alexander; Cropp, Ashton T; Chin, Jason W; Anderson, Christopher J; Schultz, Peter G

    2013-05-21

    This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

  8. Unnatural reactive amino acid genetic code additions

    SciTech Connect

    Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.

    2014-08-26

    This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

  9. Unnatural reactive amino acid genetic code additions

    SciTech Connect

    Deiters, Alexander; Cropp, T. Ashton; Chin, Jason W.; Anderson, J. Christopher; Schultz, Peter G.

    2011-02-15

    This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

  10. Genetic risks and genetic model specification.

    PubMed

    Zheng, Gang; Zhang, Wei; Xu, Jinfeng; Yuan, Ao; Li, Qizhai; Gastwirth, Joseph L

    2016-08-21

    Genetic risks and genetic models are often used in design and analysis of genetic epidemiology studies. A genetic model is defined in terms of two genetic risk measures: genotype relative risk and odds ratio. The impacts of choosing a risk measure on the resulting genetic models are studied in the power to detect association and deviation from Hardy-Weinberg equilibrium in cases using genetic relative risk. Extensive simulations demonstrate that the power of a study to detect associations using odds ratio is lower than that using relative risk with the same value when other parameters are fixed. When the Hardy-Weinberg equilibrium holds in the general population, the genetic model can be inferred by the deviation from Hardy-Weinberg equilibrium in only cases. Furthermore, it is more efficient than that based on the deviation from Hardy-Weinberg equilibrium in all cases and controls. PMID:27181372

  11. Modeling Interference in Genetic Recombination

    PubMed Central

    McPeek, M. S.; Speed, T. P.

    1995-01-01

    In analyzing genetic linkage data it is common to assume that the locations of crossovers along a chromosome follow a Poisson process, whereas it has long been known that this assumption does not fit the data. In many organisms it appears that the presence of a crossover inhibits the formation of another nearby, a phenomenon known as ``interference.'' We discuss several point process models for recombination that incorporate position interference but assume no chromatid interference. Using stochastic simulation, we are able to fit the models to a multilocus Drosophila dataset by the method of maximum likelihood. We find that some biologically inspired point process models incorporating one or two additional parameters provide a dramatically better fit to the data than the usual ``no-interference'' Poisson model. PMID:7713406

  12. Efficient Improvement of Silage Additives by Using Genetic Algorithms

    PubMed Central

    Davies, Zoe S.; Gilbert, Richard J.; Merry, Roger J.; Kell, Douglas B.; Theodorou, Michael K.; Griffith, Gareth W.

    2000-01-01

    The enormous variety of substances which may be added to forage in order to manipulate and improve the ensilage process presents an empirical, combinatorial optimization problem of great complexity. To investigate the utility of genetic algorithms for designing effective silage additive combinations, a series of small-scale proof of principle silage experiments were performed with fresh ryegrass. Having established that significant biochemical changes occur over an ensilage period as short as 2 days, we performed a series of experiments in which we used 50 silage additive combinations (prepared by using eight bacterial and other additives, each of which was added at six different levels, including zero [i.e., no additive]). The decrease in pH, the increase in lactate concentration, and the free amino acid concentration were measured after 2 days and used to calculate a “fitness” value that indicated the quality of the silage (compared to a control silage made without additives). This analysis also included a “cost” element to account for different total additive levels. In the initial experiment additive levels were selected randomly, but subsequently a genetic algorithm program was used to suggest new additive combinations based on the fitness values determined in the preceding experiments. The result was very efficient selection for silages in which large decreases in pH and high levels of lactate occurred along with low levels of free amino acids. During the series of five experiments, each of which comprised 50 treatments, there was a steady increase in the amount of lactate that accumulated; the best treatment combination was that used in the last experiment, which produced 4.6 times more lactate than the untreated silage. The additive combinations that were found to yield the highest fitness values in the final (fifth) experiment were assessed to determine a range of biochemical and microbiological quality parameters during full-term silage

  13. Additive genetic effect of APOE and BDNF on hippocampus activity.

    PubMed

    Kauppi, Karolina; Nilsson, Lars-Göran; Persson, Jonas; Nyberg, Lars

    2014-04-01

    Human memory is a highly heritable polygenic trait with complex inheritance patterns. To study the genetics of memory and memory-related diseases, hippocampal functioning has served as an intermediate phenotype. The importance of investigating gene-gene effects on complex phenotypes has been emphasized, but most imaging studies still focus on single polymorphisms. APOE ε4 and BDNF Met, two of the most studied gene variants for variability in memory performance and neuropsychiatric disorders, have both separately been related to poorer episodic memory and altered hippocampal functioning. Here, we investigated the combined effect of APOE and BDNF on hippocampal activation (N=151). No non-additive interaction effects were seen. Instead, the results revealed decreased activation in bilateral hippocampus and parahippocampus as a function of the number of APOE ε4 and BDNF Met alleles present (neither, one, or both). The combined effect was stronger than either of the individual effects, and both gene variables explained significant proportions of variance in BOLD signal change. Thus, there was an additive gene-gene effect of APOE and BDNF on medial temporal lobe (MTL) activation, showing that a larger proportion of variance in brain activation attributed to genetics can be explained by considering more than one gene variant. This effect might be relevant for the understanding of normal variability in memory function as well as memory-related disorders associated with APOE and BDNF. PMID:24321557

  14. Common genetic variants, acting additively, are a major source of risk for autism

    PubMed Central

    2012-01-01

    Background Autism spectrum disorders (ASD) are early onset neurodevelopmental syndromes typified by impairments in reciprocal social interaction and communication, accompanied by restricted and repetitive behaviors. While rare and especially de novo genetic variation are known to affect liability, whether common genetic polymorphism plays a substantial role is an open question and the relative contribution of genes and environment is contentious. It is probable that the relative contributions of rare and common variation, as well as environment, differs between ASD families having only a single affected individual (simplex) versus multiplex families who have two or more affected individuals. Methods By using quantitative genetics techniques and the contrast of ASD subjects to controls, we estimate what portion of liability can be explained by additive genetic effects, known as narrow-sense heritability. We evaluate relatives of ASD subjects using the same methods to evaluate the assumptions of the additive model and partition families by simplex/multiplex status to determine how heritability changes with status. Results By analyzing common variation throughout the genome, we show that common genetic polymorphism exerts substantial additive genetic effects on ASD liability and that simplex/multiplex family status has an impact on the identified composition of that risk. As a fraction of the total variation in liability, the estimated narrow-sense heritability exceeds 60% for ASD individuals from multiplex families and is approximately 40% for simplex families. By analyzing parents, unaffected siblings and alleles not transmitted from parents to their affected children, we conclude that the data for simplex ASD families follow the expectation for additive models closely. The data from multiplex families deviate somewhat from an additive model, possibly due to parental assortative mating. Conclusions Our results, when viewed in the context of results from genome

  15. Simultaneous Estimation of Additive and Mutational Genetic Variance in an Outbred Population of Drosophila serrata.

    PubMed

    McGuigan, Katrina; Aguirre, J David; Blows, Mark W

    2015-11-01

    How new mutations contribute to genetic variation is a key question in biology. Although the evolutionary fate of an allele is largely determined by its heterozygous effect, most estimates of mutational variance and mutational effects derive from highly inbred lines, where new mutations are present in homozygous form. In an attempt to overcome this limitation, middle-class neighborhood (MCN) experiments have been used to assess the fitness effect of new mutations in heterozygous form. However, because MCN populations harbor substantial standing genetic variance, estimates of mutational variance have not typically been available from such experiments. Here we employ a modification of the animal model to analyze data from 22 generations of Drosophila serrata bred in an MCN design. Mutational heritability, measured for eight cuticular hydrocarbons, 10 wing-shape traits, and wing size in this outbred genetic background, ranged from 0.0006 to 0.006 (with one exception), a similar range to that reported from studies employing inbred lines. Simultaneously partitioning the additive and mutational variance in the same outbred population allowed us to quantitatively test the ability of mutation-selection balance models to explain the observed levels of additive and mutational genetic variance. The Gaussian allelic approximation and house-of-cards models, which assume real stabilizing selection on single traits, both overestimated the genetic variance maintained at equilibrium, but the house-of-cards model was a closer fit to the data. This analytical approach has the potential to be broadly applied, expanding our understanding of the dynamics of genetic variance in natural populations. PMID:26384357

  16. Computational Process Modeling for Additive Manufacturing

    NASA Technical Reports Server (NTRS)

    Bagg, Stacey; Zhang, Wei

    2014-01-01

    Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

  17. Genetic assessment of additional endophenotypes from the Consortium on the Genetics of Schizophrenia Family Study.

    PubMed

    Greenwood, Tiffany A; Lazzeroni, Laura C; Calkins, Monica E; Freedman, Robert; Green, Michael F; Gur, Raquel E; Gur, Ruben C; Light, Gregory A; Nuechterlein, Keith H; Olincy, Ann; Radant, Allen D; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Stone, William S; Sugar, Catherine A; Swerdlow, Neal R; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Braff, David L

    2016-01-01

    The Consortium on the Genetics of Schizophrenia Family Study (COGS-1) has previously reported our efforts to characterize the genetic architecture of 12 primary endophenotypes for schizophrenia. We now report the characterization of 13 additional measures derived from the same endophenotype test paradigms in the COGS-1 families. Nine of the measures were found to discriminate between schizophrenia patients and controls, were significantly heritable (31 to 62%), and were sufficiently independent of previously assessed endophenotypes, demonstrating utility as additional endophenotypes. Genotyping via a custom array of 1536 SNPs from 94 candidate genes identified associations for CTNNA2, ERBB4, GRID1, GRID2, GRIK3, GRIK4, GRIN2B, NOS1AP, NRG1, and RELN across multiple endophenotypes. An experiment-wide p value of 0.003 suggested that the associations across all SNPs and endophenotypes collectively exceeded chance. Linkage analyses performed using a genome-wide SNP array further identified significant or suggestive linkage for six of the candidate endophenotypes, with several genes of interest located beneath the linkage peaks (e.g., CSMD1, DISC1, DLGAP2, GRIK2, GRIN3A, and SLC6A3). While the partial convergence of the association and linkage likely reflects differences in density of gene coverage provided by the distinct genotyping platforms, it is also likely an indication of the differential contribution of rare and common variants for some genes and methodological differences in detection ability. Still, many of the genes implicated by COGS through endophenotypes have been identified by independent studies of common, rare, and de novo variation in schizophrenia, all converging on a functional genetic network related to glutamatergic neurotransmission that warrants further investigation. PMID:26597662

  18. FEMALE AND MALE GENETIC EFFECTS ON OFFSPRING PATERNITY: ADDITIVE GENETIC (CO)VARIANCES IN FEMALE EXTRA-PAIR REPRODUCTION AND MALE PATERNITY SUCCESS IN SONG SPARROWS (MELOSPIZA MELODIA)

    PubMed Central

    Reid, Jane M; Arcese, Peter; Keller, Lukas F; Losdat, Sylvain

    2014-01-01

    Ongoing evolution of polyandry, and consequent extra-pair reproduction in socially monogamous systems, is hypothesized to be facilitated by indirect selection stemming from cross-sex genetic covariances with components of male fitness. Specifically, polyandry is hypothesized to create positive genetic covariance with male paternity success due to inevitable assortative reproduction, driving ongoing coevolution. However, it remains unclear whether such covariances could or do emerge within complex polyandrous systems. First, we illustrate that genetic covariances between female extra-pair reproduction and male within-pair paternity success might be constrained in socially monogamous systems where female and male additive genetic effects can have opposing impacts on the paternity of jointly reared offspring. Second, we demonstrate nonzero additive genetic variance in female liability for extra-pair reproduction and male liability for within-pair paternity success, modeled as direct and associative genetic effects on offspring paternity, respectively, in free-living song sparrows (Melospiza melodia). The posterior mean additive genetic covariance between these liabilities was slightly positive, but the credible interval was wide and overlapped zero. Therefore, although substantial total additive genetic variance exists, the hypothesis that ongoing evolution of female extra-pair reproduction is facilitated by genetic covariance with male within-pair paternity success cannot yet be definitively supported or rejected either conceptually or empirically. PMID:24724612

  19. Additive genetic contribution to symptom dimensions in major depressive disorder.

    PubMed

    Pearson, Rahel; Palmer, Rohan H C; Brick, Leslie A; McGeary, John E; Knopik, Valerie S; Beevers, Christopher G

    2016-05-01

    Major depressive disorder (MDD) is a phenotypically heterogeneous disorder with a complex genetic architecture. In this study, genomic-relatedness-matrix restricted maximum-likelihood analysis (GREML) was used to investigate the extent to which variance in depression symptoms/symptom dimensions can be explained by variation in common single nucleotide polymorphisms (SNPs) in a sample of individuals with MDD (N = 1,558) who participated in the National Institute of Mental Health Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. A principal components analysis of items from the Hamilton Rating Scale for Depression (HRSD) obtained prior to treatment revealed 4 depression symptom components: (a) appetite, (b) core depression symptoms (e.g., depressed mood, anhedonia), (c) insomnia, and (d) anxiety. These symptom dimensions were associated with SNP-based heritability (hSNP2) estimates of 30%, 14%, 30%, and 5%, respectively. Results indicated that the genetic contribution of common SNPs to depression symptom dimensions were not uniform. Appetite and insomnia symptoms in MDD had a relatively strong genetic contribution whereas the genetic contribution was relatively small for core depression and anxiety symptoms. While in need of replication, these results suggest that future gene discovery efforts may strongly benefit from parsing depression into its constituent parts. (PsycINFO Database Record PMID:27124715

  20. Additive genetic risk from five serotonin system polymorphisms interacts with interpersonal stress to predict depression.

    PubMed

    Vrshek-Schallhorn, Suzanne; Stroud, Catherine B; Mineka, Susan; Zinbarg, Richard E; Adam, Emma K; Redei, Eva E; Hammen, Constance; Craske, Michelle G

    2015-11-01

    Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (G×E). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a G×E predicting depression, we created an additive multilocus profile score from 5 serotonin system polymorphisms (1 each in the genes HTR1A, HTR2A, HTR2C, and 2 in TPH2). Analyses focused on 2 forms of interpersonal stress as environmental risk factors. Using 5 years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (hazard ratio [HR] = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The G×E effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the G×E effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. PMID:26595467

  1. Genetics in Non-Genetic Model Systems

    PubMed Central

    Lois, Carlos; Groves, James O

    2011-01-01

    The past few decades have seen the field of genetic engineering evolve at a rapid pace, with neuroscientists now equipped with a wide range of tools for the manipulation of an animal's genome in order to study brain function. However, the number of species to which these technologies have been applied, namely the fruit fly, C. elegans, zebrafish and mouse, remains relatively few. This review will discuss the variety of approaches to genetic modification that have been developed in such traditional ‘genetic systems’, and highlight the progress that has been made to translate these technologies to alternative species such as rats, monkeys and birds, where certain neurobiological questions may be better studied. PMID:22119141

  2. Prevalence of gene expression additivity in genetically stable wheat allohexaploids.

    PubMed

    Chelaifa, Houda; Chagué, Véronique; Chalabi, Smahane; Mestiri, Imen; Arnaud, Dominique; Deffains, Denise; Lu, Yunhai; Belcram, Harry; Huteau, Virginie; Chiquet, Julien; Coriton, Olivier; Just, Jérémy; Jahier, Joseph; Chalhoub, Boulos

    2013-02-01

    The reprogramming of gene expression appears as the major trend in synthetic and natural allopolyploids where expression of an important proportion of genes was shown to deviate from that of the parents or the average of the parents. In this study, we analyzed gene expression changes in previously reported, highly stable synthetic wheat allohexaploids that combine the D genome of Aegilops tauschii and the AB genome extracted from the natural hexaploid wheat Triticum aestivum. A comprehensive genome-wide analysis of transcriptional changes using the Affymetrix GeneChip Wheat Genome Array was conducted. Prevalence of gene expression additivity was observed where expression does not deviate from the average of the parents for 99.3% of 34,820 expressed transcripts. Moreover, nearly similar expression was observed (for 99.5% of genes) when comparing these synthetic and natural wheat allohexaploids. Such near-complete additivity has never been reported for other allopolyploids and, more interestingly, for other synthetic wheat allohexaploids that differ from the ones studied here by having the natural tetraploid Triticum turgidum as the AB genome progenitor. Our study gave insights into the dynamics of additive gene expression in the highly stable wheat allohexaploids. PMID:23278496

  3. Effect of multiplicative and additive noise on genetic transcriptional regulatory mechanism

    NASA Astrophysics Data System (ADS)

    Liu, Xue-Mei; Xie, Hui-Zhang; Liu, Liang-Gang; Li, Zhi-Bing

    2009-02-01

    A multiplicative noise and an additive noise are introduced in the kinetic model of Smolen-Baxter-Byrne [P. Smolen, D.A. Baxter, J.H. Byrne, Amer. J. Physiol. Cell. Physiol. 274 (1998) 531], in which the expression of gene is controlled by protein concentration of transcriptional activator. The Fokker-Planck equation is solved and the steady-state probability distribution is obtained numerically. It is found that the multiplicative noise converts the bistability to monostability that can be regarded as a noise-induced transition. The additive noise reduces the transcription efficiency. The correlation between the multiplicative noise and the additive noise works as a genetic switch and regulates the gene transcription effectively.

  4. Additive genetic variation and evolvability of a multivariate trait can be increased by epistatic gene action.

    PubMed

    Griswold, Cortland K

    2015-12-21

    Epistatic gene action occurs when mutations or alleles interact to produce a phenotype. Theoretically and empirically it is of interest to know whether gene interactions can facilitate the evolution of diversity. In this paper, we explore how epistatic gene action affects the additive genetic component or heritable component of multivariate trait variation, as well as how epistatic gene action affects the evolvability of multivariate traits. The analysis involves a sexually reproducing and recombining population. Our results indicate that under stabilizing selection conditions a population with a mixed additive and epistatic genetic architecture can have greater multivariate additive genetic variation and evolvability than a population with a purely additive genetic architecture. That greater multivariate additive genetic variation can occur with epistasis is in contrast to previous theory that indicated univariate additive genetic variation is decreased with epistasis under stabilizing selection conditions. In a multivariate setting, epistasis leads to less relative covariance among individuals in their genotypic, as well as their breeding values, which facilitates the maintenance of additive genetic variation and increases a population׳s evolvability. Our analysis involves linking the combinatorial nature of epistatic genetic effects to the ancestral graph structure of a population to provide insight into the consequences of epistasis on multivariate trait variation and evolution. PMID:26431770

  5. Advances on genetic rat models of epilepsy

    PubMed Central

    Serikawa, Tadao; Mashimo, Tomoji; Kuramoto, Takashi; Voigt, Birger; Ohno, Yukihiro; Sasa, Masashi

    2014-01-01

    Considering the suitability of laboratory rats in epilepsy research, we and other groups have been developing genetic models of epilepsy in this species. After epileptic rats or seizure-susceptible rats were sporadically found in outbred stocks, the epileptic traits were usually genetically-fixed by selective breeding. So far, the absence seizure models GAERS and WAG/Rij, audiogenic seizure models GEPR-3 and GEPR-9, generalized tonic-clonic seizure models IER, NER and WER, and Canavan-disease related epileptic models TRM and SER have been established. Dissection of the genetic bases including causative genes in these epileptic rat models would be a significant step toward understanding epileptogenesis. N-ethyl-N-nitrosourea (ENU) mutagenesis provides a systematic approach which allowed us to develop two novel epileptic rat models: heat-induced seizure susceptible (Hiss) rats with an Scn1a missense mutation and autosomal dominant lateral temporal epilepsy (ADLTE) model rats with an Lgi1 missense mutation. In addition, we have established episodic ataxia type 1 (EA1) model rats with a Kcna1 missense mutation derived from the ENU-induced rat mutant stock, and identified a Cacna1a missense mutation in a N-Methyl-N-nitrosourea (MNU)-induced mutant rat strain GRY, resulting in the discovery of episodic ataxia type 2 (EA2) model rats. Thus, epileptic rat models have been established on the two paths: ‘phenotype to gene’ and ‘gene to phenotype’. In the near future, development of novel epileptic rat models will be extensively promoted by the use of sophisticated genome editing technologies. PMID:25312505

  6. Advances on genetic rat models of epilepsy.

    PubMed

    Serikawa, Tadao; Mashimo, Tomoji; Kuramoro, Takashi; Voigt, Birger; Ohno, Yukihiro; Sasa, Masashi

    2015-01-01

    Considering the suitability of laboratory rats in epilepsy research, we and other groups have been developing genetic models of epilepsy in this species. After epileptic rats or seizure-susceptible rats were sporadically found in outbred stocks, the epileptic traits were usually genetically-fixed by selective breeding. So far, the absence seizure models GAERS and WAG/Rij, audiogenic seizure models GEPR-3 and GEPR-9, generalized tonic-clonic seizure models IER, NER and WER, and Canavan-disease related epileptic models TRM and SER have been established. Dissection of the genetic bases including causative genes in these epileptic rat models would be a significant step toward understanding epileptogenesis. N-ethyl-N-nitrosourea (ENU) mutagenesis provides a systematic approach which allowed us to develop two novel epileptic rat models: heat-induced seizure susceptible (Hiss) rats with an Scn1a missense mutation and autosomal dominant lateral temporal epilepsy (ADLTE) model rats with an Lgi1 missense mutation. In addition, we have established episodic ataxia type 1 (EA1) model rats with a Kcna1 missense mutation derived from the ENU-induced rat mutant stock, and identified a Cacna1a missense mutation in a N-Methyl-N-nitrosourea (MNU)-induced mutant rat strain GRY, resulting in the discovery of episodic ataxia type 2 (EA2) model rats. Thus, epileptic rat models have been established on the two paths: 'phenotype to gene' and 'gene to phenotype'. In the near future, development of novel epileptic rat models will be extensively promoted by the use of sophisticated genome editing technologies. PMID:25312505

  7. Additive and non-additive genetic components of the jack male life history in Chinook salmon (Oncorhynchus tshawytscha).

    PubMed

    Forest, Adriana R; Semeniuk, Christina A D; Heath, Daniel D; Pitcher, Trevor E

    2016-08-01

    Chinook salmon, Oncorhynchus tshawytscha, exhibit alternative reproductive tactics (ARTs) where males exist in two phenotypes: large "hooknose" males and smaller "jacks" that reach sexual maturity after only 1 year in seawater. The mechanisms that determine "jacking rate"-the rate at which males precociously sexually mature-are known to involve both genetics and differential growth rates, where individuals that become jacks exhibit higher growth earlier in life. The additive genetic components have been studied and it is known that jack sires produce significantly more jack offspring than hooknose sires, and vice versa. The current study was the first to investigate both additive and non-additive genetic components underlying jacking through the use of a full-factorial breeding design using all hooknose sires. The effect of dams and sires descendant from a marker-assisted broodstock program that identified "high performance" and "low performance" lines using growth- and survival-related gene markers was also studied. Finally, the relative growth of jack, hooknose, and female offspring was examined. No significant dam, sire, or interaction effects were observed in this study, and the maternal, additive, and non-additive components underlying jacking were small. Differences in jacking rates in this study were determined by dam performance line, where dams that originated from the low performance line produced significantly more jacks. Jack offspring in this study had a significantly larger body size than both hooknose males and females starting 1 year post-fertilization. This study provides novel information regarding the genetic architecture underlying ARTs in Chinook salmon that could have implications for the aquaculture industry, where jacks are not favoured due to their small body size and poor flesh quality. PMID:27450674

  8. Fine-mapping in the MHC region accounts for 18% additional genetic risk for celiac disease

    PubMed Central

    Gutierrez-Achury, Javier; Zhernakova, Alexandra; Pulit, Sara L.; Trynka, Gosia; Hunt, Karen A.; Romanos, Jihane; Raychaudhuri, Soumya; van Heel, David A.; Wijmenga, Cisca; de Bakker, Paul I.W.

    2015-01-01

    Although dietary gluten is the trigger, celiac disease risk is strongly influenced by genetic variation in the major histocompatibility complex (MHC) region. We fine-mapped the MHC association signal to identify additional risk factors independent of the HLA-DQ alleles and observed five novel associations that account for 18% of the genetic risk. Together with the 57 known non-MHC loci, genetic variation can now explain up to 48% of celiac disease heritability. PMID:25894500

  9. Animal models for genetic neuromuscular diseases.

    PubMed

    Vainzof, Mariz; Ayub-Guerrieri, Danielle; Onofre, Paula C G; Martins, Poliana C M; Lopes, Vanessa F; Zilberztajn, Dinorah; Maia, Lucas S; Sell, Karen; Yamamoto, Lydia U

    2008-03-01

    , both presenting significant reduction of alpha2-laminin in the muscle and a severe phenotype. The myodystrophy mouse (Large(myd)) harbors a mutation in the glycosyltransferase Large, which leads to altered glycosylation of alpha-DG, and also a severe phenotype. Other informative models for muscle proteins include the knockout mouse for myostatin, which demonstrated that this protein is a negative regulator of muscle growth. Additionally, the stress syndrome in pigs, caused by mutations in the porcine RYR1 gene, helped to localize the gene causing malignant hypertermia and Central Core myopathy in humans. The study of animal models for genetic diseases, in spite of the existence of differences in some phenotypes, can provide important clues to the understanding of the pathogenesis of these disorders and are also very valuable for testing strategies for therapeutic approaches. PMID:18202836

  10. The Evolution of Human Intelligence and the Coefficient of Additive Genetic Variance in Human Brain Size

    ERIC Educational Resources Information Center

    Miller, Geoffrey F.; Penke, Lars

    2007-01-01

    Most theories of human mental evolution assume that selection favored higher intelligence and larger brains, which should have reduced genetic variance in both. However, adult human intelligence remains highly heritable, and is genetically correlated with brain size. This conflict might be resolved by estimating the coefficient of additive genetic…

  11. Network Reconstruction Using Nonparametric Additive ODE Models

    PubMed Central

    Henderson, James; Michailidis, George

    2014-01-01

    Network representations of biological systems are widespread and reconstructing unknown networks from data is a focal problem for computational biologists. For example, the series of biochemical reactions in a metabolic pathway can be represented as a network, with nodes corresponding to metabolites and edges linking reactants to products. In a different context, regulatory relationships among genes are commonly represented as directed networks with edges pointing from influential genes to their targets. Reconstructing such networks from data is a challenging problem receiving much attention in the literature. There is a particular need for approaches tailored to time-series data and not reliant on direct intervention experiments, as the former are often more readily available. In this paper, we introduce an approach to reconstructing directed networks based on dynamic systems models. Our approach generalizes commonly used ODE models based on linear or nonlinear dynamics by extending the functional class for the functions involved from parametric to nonparametric models. Concomitantly we limit the complexity by imposing an additive structure on the estimated slope functions. Thus the submodel associated with each node is a sum of univariate functions. These univariate component functions form the basis for a novel coupling metric that we define in order to quantify the strength of proposed relationships and hence rank potential edges. We show the utility of the method by reconstructing networks using simulated data from computational models for the glycolytic pathway of Lactocaccus Lactis and a gene network regulating the pluripotency of mouse embryonic stem cells. For purposes of comparison, we also assess reconstruction performance using gene networks from the DREAM challenges. We compare our method to those that similarly rely on dynamic systems models and use the results to attempt to disentangle the distinct roles of linearity, sparsity, and derivative

  12. Computational Process Modeling for Additive Manufacturing (OSU)

    NASA Technical Reports Server (NTRS)

    Bagg, Stacey; Zhang, Wei

    2015-01-01

    Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

  13. Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

    PubMed Central

    Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

    2015-01-01

    The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

  14. Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects

    PubMed Central

    Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Porth, Ilga; Chen, Charles; El-Kassaby, Yousry A.

    2016-01-01

    The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates’ offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of “half-sibling” in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure. PMID:26801647

  15. CREATION OF THE MODEL ADDITIONAL PROTOCOL

    SciTech Connect

    Houck, F.; Rosenthal, M.; Wulf, N.

    2010-05-25

    In 1991, the international nuclear nonproliferation community was dismayed to discover that the implementation of safeguards by the International Atomic Energy Agency (IAEA) under its NPT INFCIRC/153 safeguards agreement with Iraq had failed to detect Iraq's nuclear weapon program. It was now clear that ensuring that states were fulfilling their obligations under the NPT would require not just detecting diversion but also the ability to detect undeclared materials and activities. To achieve this, the IAEA initiated what would turn out to be a five-year effort to reappraise the NPT safeguards system. The effort engaged the IAEA and its Member States and led to agreement in 1997 on a new safeguards agreement, the Model Protocol Additional to the Agreement(s) between States and the International Atomic Energy Agency for the Application of Safeguards. The Model Protocol makes explicit that one IAEA goal is to provide assurance of the absence of undeclared nuclear material and activities. The Model Protocol requires an expanded declaration that identifies a State's nuclear potential, empowers the IAEA to raise questions about the correctness and completeness of the State's declaration, and, if needed, allows IAEA access to locations. The information required and the locations available for access are much broader than those provided for under INFCIRC/153. The negotiation was completed in quite a short time because it started with a relatively complete draft of an agreement prepared by the IAEA Secretariat. This paper describes how the Model Protocol was constructed and reviews key decisions that were made both during the five-year period and in the actual negotiation.

  16. Detecting contaminated birthdates using generalized additive models

    PubMed Central

    2014-01-01

    Background Erroneous patient birthdates are common in health databases. Detection of these errors usually involves manual verification, which can be resource intensive and impractical. By identifying a frequent manifestation of birthdate errors, this paper presents a principled and statistically driven procedure to identify erroneous patient birthdates. Results Generalized additive models (GAM) enabled explicit incorporation of known demographic trends and birth patterns. With false positive rates controlled, the method identified birthdate contamination with high accuracy. In the health data set used, of the 58 actual incorrect birthdates manually identified by the domain expert, the GAM-based method identified 51, with 8 false positives (resulting in a positive predictive value of 86.0% (51/59) and a false negative rate of 12.0% (7/58)). These results outperformed linear time-series models. Conclusions The GAM-based method is an effective approach to identify systemic birthdate errors, a common data quality issue in both clinical and administrative databases, with high accuracy. PMID:24923281

  17. Lightning Climatology with a Generalized Additive Model

    NASA Astrophysics Data System (ADS)

    Simon, Thorsten; Mayr, Georg; Umlauf, Nikolaus; Zeileis, Achim

    2016-04-01

    This study present a lightning climatology on a 1km x 1km grid estimated via generalized additive models (GAM). GAMs provide a framework to account for non-linear effects in time and space and for non-linear spatial-temporal interaction terms simultaneously. The degrees of smoothness of the non-linear effects is selected automatically in our approach. Furthermore, the influence of topography is captured in the model by including a non-linear term. To illustrate our approach we use lightning data from the ALDIS networks and selected a region in Southeastern Austria, where complex terrain extends from 200 an 3800 m asl and summertime lightning activity is high compared to other parts of the Eastern Alps. The temporal effect in the GAM shows a rapid increase in lightning activity in early July and a slow decay in activity afterwards. The estimated spatial effect is not very smooth and requires approximately 225 effective degrees of freedom. It reveals that lightning is more likely in the Eastern and Southern part of the region of interest. This spatial effect only accounts for variability not already explained by the topography. The topography effect shows lightning to be more likely at higher altitudes. The effect describing the spatio-temporal interactions takes approximately 200 degrees of freedom, and reveals local deviations of the climatology.

  18. Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data

    PubMed Central

    Lopes, Marcos S.; Bastiaansen, John W. M.; Janss, Luc; Knol, Egbert F.; Bovenhuis, Henk

    2015-01-01

    Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases. PMID:26438289

  19. Large animal models of rare genetic disorders: sheep as phenotypically relevant models of human genetic disease.

    PubMed

    Pinnapureddy, Ashish R; Stayner, Cherie; McEwan, John; Baddeley, Olivia; Forman, John; Eccles, Michael R

    2015-01-01

    Animals that accurately model human disease are invaluable in medical research, allowing a critical understanding of disease mechanisms, and the opportunity to evaluate the effect of therapeutic compounds in pre-clinical studies. Many types of animal models are used world-wide, with the most common being small laboratory animals, such as mice. However, rodents often do not faithfully replicate human disease, despite their predominant use in research. This discordancy is due in part to physiological differences, such as body size and longevity. In contrast, large animal models, including sheep, provide an alternative to mice for biomedical research due to their greater physiological parallels with humans. Completion of the full genome sequences of many species, and the advent of Next Generation Sequencing (NGS) technologies, means it is now feasible to screen large populations of domesticated animals for genetic variants that resemble human genetic diseases, and generate models that more accurately model rare human pathologies. In this review, we discuss the notion of using sheep as large animal models, and their advantages in modelling human genetic disease. We exemplify several existing naturally occurring ovine variants in genes that are orthologous to human disease genes, such as the Cln6 sheep model for Batten disease. These, and other sheep models, have contributed significantly to our understanding of the relevant human disease process, in addition to providing opportunities to trial new therapies in animals with similar body and organ size to humans. Therefore sheep are a significant species with respect to the modelling of rare genetic human disease, which we summarize in this review. PMID:26329332

  20. [Food additives and genetically modified food--a risk for allergic patients?].

    PubMed

    Wüthrich, B

    1999-04-01

    Adverse reactions to food and food additives must be classified according to pathogenic criteria. It is necessary to strictly differentiate between an allergy, triggered by a substance-specific immunological mechanism, and an intolerance, in which no specific immune reaction can be established. In contrast to views expressed in the media, by laymen and patients, adverse reactions to additives are less frequent than is believed. Due to frequently "alternative" methods of examination, an allergy to food additives is often wrongly blamed as the cause of a wide variety of symptoms and illness. Diagnosing an allergy or intolerance to additives normally involves carrying out double-blind, placebo-controlled oral provocation tests with food additives. Allergic reactions to food additives occur particularly against additives which are organic in origin. In principle, it is possible that during the manufacture of genetically modified plants and food, proteins are transferred which potentially create allergies. However, legislation exists both in the USA (Federal Drug Administration, FDA) and in Switzerland (Ordinance on the approval process for GM food, GM food additives and GM accessory agents for processing) which require a careful analysis before a genetically modified product is launched, particularly where foreign genes are introduced. Products containing genetically modified organisms (GMO) as additives must be declared. In addition, the source of the foreign protein must be identified. The "Round-up ready" (RR) soya flour introduced in Switzerland is no different from natural soya flour in terms of its allergenic potential. Genetically modified food can be a blessing for allergic individuals if gene technology were to succeed in removing the allergen (e.g. such possibilities exist for rice). The same caution shown towards genetically modified food might also be advisable for foreign food in our diet. Luckily, the immune system of the digestive tract in healthy people

  1. Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

    PubMed Central

    Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

    2015-01-01

    Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

  2. Genetic coding and gene expression - new Quadruplet genetic coding model

    NASA Astrophysics Data System (ADS)

    Shankar Singh, Rama

    2012-07-01

    Successful demonstration of human genome project has opened the door not only for developing personalized medicine and cure for genetic diseases, but it may also answer the complex and difficult question of the origin of life. It may lead to making 21st century, a century of Biological Sciences as well. Based on the central dogma of Biology, genetic codons in conjunction with tRNA play a key role in translating the RNA bases forming sequence of amino acids leading to a synthesized protein. This is the most critical step in synthesizing the right protein needed for personalized medicine and curing genetic diseases. So far, only triplet codons involving three bases of RNA, transcribed from DNA bases, have been used. Since this approach has several inconsistencies and limitations, even the promise of personalized medicine has not been realized. The new Quadruplet genetic coding model proposed and developed here involves all four RNA bases which in conjunction with tRNA will synthesize the right protein. The transcription and translation process used will be the same, but the Quadruplet codons will help overcome most of the inconsistencies and limitations of the triplet codes. Details of this new Quadruplet genetic coding model and its subsequent potential applications including relevance to the origin of life will be presented.

  3. LISREL Modeling: Genetic and Environmental Influences on IQ Revisited.

    ERIC Educational Resources Information Center

    Chipuer, Heather M.; And Others

    1990-01-01

    A model-fitting analysis of the covariance structure of an intelligence quotient (IQ) data set is reported using a model that considers additive and nonadditive genetic parameters and shared and nonshared environment parameters that permit different estimates for different types of relatives. The use of LISREL for such purposes is reviewed. (SLD)

  4. Genetically Engineered Pig Models for Human Diseases

    PubMed Central

    Prather, Randall S.; Lorson, Monique; Ross, Jason W.; Whyte, Jeffrey J.; Walters, Eric

    2015-01-01

    Although pigs are used widely as models of human disease, their utility as models has been enhanced by genetic engineering. Initially, transgenes were added randomly to the genome, but with the application of homologous recombination, zinc finger nucleases, and transcription activator-like effector nuclease (TALEN) technologies, now most any genetic change that can be envisioned can be completed. To date these genetic modifications have resulted in animals that have the potential to provide new insights into human diseases for which a good animal model did not exist previously. These new animal models should provide the preclinical data for treatments that are developed for diseases such as Alzheimer's disease, cystic fibrosis, retinitis pigmentosa, spinal muscular atrophy, diabetes, and organ failure. These new models will help to uncover aspects and treatments of these diseases that were otherwise unattainable. The focus of this review is to describe genetically engineered pigs that have resulted in models of human diseases. PMID:25387017

  5. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 45 Public Welfare 1 2011-10-01 2011-10-01 false Additional requirements prohibiting discrimination based on genetic information. 146.122 Section 146.122 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS REQUIREMENTS FOR THE GROUP HEALTH INSURANCE MARKET Requirements Relating to Access...

  6. 26 CFR 54.9802-3T - Additional requirements prohibiting discrimination based on genetic information (temporary).

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 26 Internal Revenue 17 2014-04-01 2014-04-01 false Additional requirements prohibiting discrimination based on genetic information (temporary). 54.9802-3T Section 54.9802-3T Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) MISCELLANEOUS EXCISE TAXES (CONTINUED) PENSION EXCISE TAXES § 54.9802-3T...

  7. 29 CFR 2590.702-1 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 29 Labor 9 2014-07-01 2014-07-01 false Additional requirements prohibiting discrimination based on genetic information. 2590.702-1 Section 2590.702-1 Labor Regulations Relating to Labor (Continued) EMPLOYEE BENEFITS SECURITY ADMINISTRATION, DEPARTMENT OF LABOR GROUP HEALTH PLANS RULES AND REGULATIONS FOR GROUP HEALTH PLANS Health...

  8. 26 CFR 54.9802-3T - Additional requirements prohibiting discrimination based on genetic information (temporary).

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 26 Internal Revenue 17 2012-04-01 2012-04-01 false Additional requirements prohibiting discrimination based on genetic information (temporary). 54.9802-3T Section 54.9802-3T Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) MISCELLANEOUS EXCISE TAXES (CONTINUED) PENSION EXCISE TAXES § 54.9802-3T...

  9. 26 CFR 54.9802-3T - Additional requirements prohibiting discrimination based on genetic information (temporary).

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 26 Internal Revenue 17 2013-04-01 2013-04-01 false Additional requirements prohibiting discrimination based on genetic information (temporary). 54.9802-3T Section 54.9802-3T Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) MISCELLANEOUS EXCISE TAXES (CONTINUED) PENSION EXCISE TAXES § 54.9802-3T...

  10. Additives

    NASA Technical Reports Server (NTRS)

    Smalheer, C. V.

    1973-01-01

    The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.

  11. Joint Modeling of Imaging and Genetics

    PubMed Central

    Batmanghelich, Nematollah K.; Dalca, Adrian V.; Sabuncu, Mert R.; Golland, Polina

    2014-01-01

    We propose a unified Bayesian framework for detecting genetic variants associated with a disease while exploiting image-based features as an intermediate phenotype. Traditionally, imaging genetics methods comprise two separate steps. First, image features are selected based on their relevance to the disease phenotype. Second, a set of genetic variants are identified to explain the selected features. In contrast, our method performs these tasks simultaneously to ultimately assign probabilistic measures of relevance to both genetic and imaging markers. We derive an efficient approximate inference algorithm that handles high dimensionality of imaging genetic data. We evaluate the algorithm on synthetic data and show that it outperforms traditional models. We also illustrate the application of the method on ADNI data. PMID:24684016

  12. Modeling techniques for gaining additional urban space

    NASA Astrophysics Data System (ADS)

    Thunig, Holger; Naumann, Simone; Siegmund, Alexander

    2009-09-01

    One of the major accompaniments of the globalization is the rapid growing of urban areas. Urban sprawl is the main environmental problem affecting those cities across different characteristics and continents. Various reasons for the increase in urban sprawl in the last 10 to 30 years have been proposed [1], and often depend on the socio-economic situation of cities. The quantitative reduction and the sustainable handling of land should be performed by inner urban development instead of expanding urban regions. Following the principal "spare the urban fringe, develop the inner suburbs first" requires differentiated tools allowing for quantitative and qualitative appraisals of current building potentials. Using spatial high resolution remote sensing data within an object-based approach enables the detection of potential areas while GIS-data provides information for the quantitative valuation. This paper presents techniques for modeling urban environment and opportunities of utilization of the retrieved information for urban planners and their special needs.

  13. Genetic and environmental melanoma models in fish

    PubMed Central

    Patton, E Elizabeth; Mitchell, David L; Nairn, Rodney S

    2010-01-01

    Experimental animal models are extremely valuable for the study of human diseases, especially those with underlying genetic components. The exploitation of various animal models, from fruitflies to mice, has led to major advances in our understanding of the etiologies of many diseases, including cancer. Cutaneous malignant melanoma is a form of cancer for which both environmental insult (i.e., UV) and hereditary predisposition are major causative factors. Fish melanoma models have been used in studies of both spontaneous and induced melanoma formation. Genetic hybrids between platyfish and swordtails, different species of the genus Xiphophorus, have been studied since the 1920s to identify genetic determinants of pigmentation and melanoma formation. Recently, transgenesis has been used to develop zebrafish and medaka models for melanoma research. This review will provide a historical perspective on the use of fish models in melanoma research, and an updated summary of current and prospective studies using these unique experimental systems. PMID:20230482

  14. Planning additional drilling campaign using two-space genetic algorithm: A game theoretical approach

    NASA Astrophysics Data System (ADS)

    Kumral, Mustafa; Ozer, Umit

    2013-03-01

    Grade and tonnage are the most important technical uncertainties in mining ventures because of the use of estimations/simulations, which are mostly generated from drill data. Open pit mines are planned and designed on the basis of the blocks representing the entire orebody. Each block has different estimation/simulation variance reflecting uncertainty to some extent. The estimation/simulation realizations are submitted to mine production scheduling process. However, the use of a block model with varying estimation/simulation variances will lead to serious risk in the scheduling. In the medium of multiple simulations, the dispersion variances of blocks can be thought to regard technical uncertainties. However, the dispersion variance cannot handle uncertainty associated with varying estimation/simulation variances of blocks. This paper proposes an approach that generates the configuration of the best additional drilling campaign to generate more homogenous estimation/simulation variances of blocks. In other words, the objective is to find the best drilling configuration in such a way as to minimize grade uncertainty under budget constraint. Uncertainty measure of the optimization process in this paper is interpolation variance, which considers data locations and grades. The problem is expressed as a minmax problem, which focuses on finding the best worst-case performance i.e., minimizing interpolation variance of the block generating maximum interpolation variance. Since the optimization model requires computing the interpolation variances of blocks being simulated/estimated in each iteration, the problem cannot be solved by standard optimization tools. This motivates to use two-space genetic algorithm (GA) approach to solve the problem. The technique has two spaces: feasible drill hole configuration with minimization of interpolation variance and drill hole simulations with maximization of interpolation variance. Two-space interacts to find a minmax solution

  15. Genetic and non-genetic animal models for autism spectrum disorders (ASD).

    PubMed

    Ergaz, Zivanit; Weinstein-Fudim, Liza; Ornoy, Asher

    2016-09-01

    Autism spectrum disorder (ASD) is associated, in addition to complex genetic factors, with a variety of prenatal, perinatal and postnatal etiologies. We discuss the known animal models, mostly in mice and rats, of ASD that helps us to understand the etiology, pathogenesis and treatment of human ASD. We describe only models where behavioral testing has shown autistic like behaviors. Some genetic models mimic known human syndromes like fragile X where ASD is part of the clinical picture, and others are without defined human syndromes. Among the environmentally induced ASD models in rodents, the most common model is the one induced by valproic acid (VPA) either prenatally or early postnatally. VPA induces autism-like behaviors following single exposure during different phases of brain development, implying that the mechanism of action is via a general biological mechanism like epigenetic changes. Maternal infection and inflammation are also associated with ASD in man and animal models. PMID:27142188

  16. Pattern of inbreeding depression, condition dependence, and additive genetic variance in Trinidadian guppy ejaculate traits

    PubMed Central

    Gasparini, Clelia; Devigili, Alessandro; Dosselli, Ryan; Pilastro, Andrea

    2013-01-01

    In polyandrous species, a male's reproductive success depends on his fertilization capability and traits enhancing competitive fertilization success will be under strong, directional selection. This leads to the prediction that these traits should show stronger condition dependence and larger genetic variance than other traits subject to weaker or stabilizing selection. While empirical evidence of condition dependence in postcopulatory traits is increasing, the comparison between sexually selected and ‘control’ traits is often based on untested assumption concerning the different strength of selection acting on these traits. Furthermore, information on selection in the past is essential, as both condition dependence and genetic variance of a trait are likely to be influenced by the pattern of selection acting historically on it. Using the guppy (Poecilia reticulata), a livebearing fish with high levels of multiple paternity, we performed three independent experiments on three ejaculate quality traits, sperm number, velocity, and size, which have been previously shown to be subject to strong, intermediate, and weak directional postcopulatory selection, respectively. First, we conducted an inbreeding experiment to determine the pattern of selection in the past. Second, we used a diet restriction experiment to estimate their level of condition dependence. Third, we used a half-sib/full-sib mating design to estimate the coefficients of additive genetic variance (CVA) underlying these traits. Additionally, using a simulated predator evasion test, we showed that both inbreeding and diet restriction significantly reduced condition. According to predictions, sperm number showed higher inbreeding depression, stronger condition dependence, and larger CVA than sperm velocity and sperm size. The lack of significant genetic correlation between sperm number and velocity suggests that the former may respond to selection independently one from other ejaculate quality traits

  17. Predicting genetic interactions from Boolean models of biological networks.

    PubMed

    Calzone, Laurence; Barillot, Emmanuel; Zinovyev, Andrei

    2015-08-01

    Genetic interaction can be defined as a deviation of the phenotypic quantitative effect of a double gene mutation from the effect predicted from single mutations using a simple (e.g., multiplicative or linear additive) statistical model. Experimentally characterized genetic interaction networks in model organisms provide important insights into relationships between different biological functions. We describe a computational methodology allowing us to systematically and quantitatively characterize a Boolean mathematical model of a biological network in terms of genetic interactions between all loss of function and gain of function mutations with respect to all model phenotypes or outputs. We use the probabilistic framework defined in MaBoSS software, based on continuous time Markov chains and stochastic simulations. In addition, we suggest several computational tools for studying the distribution of double mutants in the space of model phenotype probabilities. We demonstrate this methodology on three published models for each of which we derive the genetic interaction networks and analyze their properties. We classify the obtained interactions according to their class of epistasis, dependence on the chosen initial conditions and the phenotype. The use of this methodology for validating mathematical models from experimental data and designing new experiments is discussed. PMID:25958956

  18. Genetically modified pig models for neurodegenerative disorders.

    PubMed

    Holm, Ida E; Alstrup, Aage Kristian Olsen; Luo, Yonglun

    2016-01-01

    Increasing incidence of neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease has become one of the most challenging health issues in ageing humans. One approach to combat this is to generate genetically modified animal models of neurodegenerative disorders for studying pathogenesis, prognosis, diagnosis, treatment, and prevention. Owing to the genetic, anatomic, physiologic, pathologic, and neurologic similarities between pigs and humans, genetically modified pig models of neurodegenerative disorders have been attractive large animal models to bridge the gap of preclinical investigations between rodents and humans. In this review, we provide a neuroanatomical overview in pigs and summarize and discuss the generation of genetically modified pig models of neurodegenerative disorders including Alzheimer's diseases, Huntington's disease, Parkinson's disease, amyotrophic lateral sclerosis, spinal muscular atrophy, and ataxia-telangiectasia. We also highlight how non-invasive bioimaging technologies such as positron emission tomography (PET), computer tomography (CT), and magnetic resonance imaging (MRI), and behavioural testing have been applied to characterize neurodegenerative pig models. We further propose a multiplex genome editing and preterm recloning (MAP) approach by using the rapid growth of the ground-breaking precision genome editing technology CRISPR/Cas9 and somatic cell nuclear transfer (SCNT). With this approach, we hope to shorten the temporal requirement in generating multiple transgenic pigs, increase the survival rate of founder pigs, and generate genetically modified pigs that will more closely resemble the disease-causing mutations and recapitulate pathological features of human conditions. PMID:26446984

  19. Genetic models of homosexuality: generating testable predictions

    PubMed Central

    Gavrilets, Sergey; Rice, William R

    2006-01-01

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism. PMID:17015344

  20. Additive Genetic Variation in Schizophrenia Risk Is Shared by Populations of African and European Descent

    PubMed Central

    de Candia, Teresa R.; Lee, S. Hong; Yang, Jian; Browning, Brian L.; Gejman, Pablo V.; Levinson, Douglas F.; Mowry, Bryan J.; Hewitt, John K.; Goddard, Michael E.; O’Donovan, Michael C.; Purcell, Shaun M.; Posthuma, Danielle; Visscher, Peter M.; Wray, Naomi R.; Keller, Matthew C.

    2013-01-01

    To investigate the extent to which the proportion of schizophrenia’s additive genetic variation tagged by SNPs is shared by populations of European and African descent, we analyzed the largest combined African descent (AD [n = 2,142]) and European descent (ED [n = 4,990]) schizophrenia case-control genome-wide association study (GWAS) data set available, the Molecular Genetics of Schizophrenia (MGS) data set. We show how a method that uses genomic similarities at measured SNPs to estimate the additive genetic correlation (SNP correlation [SNP-rg]) between traits can be extended to estimate SNP-rg for the same trait between ethnicities. We estimated SNP-rg for schizophrenia between the MGS ED and MGS AD samples to be 0.66 (SE = 0.23), which is significantly different from 0 (p(SNP-rg = 0) = 0.0003), but not 1 (p(SNP-rg = 1) = 0.26). We re-estimated SNP-rg between an independent ED data set (n = 6,665) and the MGS AD sample to be 0.61 (SE = 0.21, p(SNP-rg = 0) = 0.0003, p(SNP-rg = 1) = 0.16). These results suggest that many schizophrenia risk alleles are shared across ethnic groups and predate African-European divergence. PMID:23954163

  1. The transport exponent in percolation models with additional loops

    NASA Astrophysics Data System (ADS)

    Babalievski, F.

    1994-10-01

    Several percolation models with additional loops were studied. The transport exponents for these models were estimated numerically by means of a transfer-matrix approach. It was found that the transport exponent has a drastically changed value for some of the models. This result supports some previous numerical studies on the vibrational properties of similar models (with additional loops).

  2. Searching for additional endocrine functions of the skeleton: genetic approaches and implications for therapeutics

    PubMed Central

    Wei, Jianwen; Flaherty, Stephen; Karsenty, Gerard

    2016-01-01

    Our knowledge of whole organism physiology has greatly advanced in the past decades through mouse genetics. In particular, genetic studies have revealed that most organs interact with one another through hormones in order to maintain normal physiological functions and the homeostasis of the entire organism. Remarkably, through these studies many unexpected novel endocrine means to regulate physiological functions have been uncovered. The skeletal system is one example. In this article, we review a series of studies that over the years have identified bone as an endocrine organ. The mechanism of action, pathological relevance, and therapeutic implications of the functions of the bone-derived hormone osteocalcin are discussed. In the last part of this review we discuss the possibility that additional endocrine functions of the skeleton may exist.

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

    PubMed

    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 subject to IGEs have been developed within two frameworks; a trait-based framework in which IGEs are specified as a direct consequence of individual trait values, and a variance-component framework in which phenotypic variance is decomposed into a direct and an indirect additive genetic component. This work is a selective review of the quantitative genetics of traits affected by IGEs, with a focus on modelling, estimation and interpretation issues. It includes a discussion on variance-component vs trait-based models of IGEs, a review of issues related to the estimation of IGEs from field data, including the estimation of the interaction coefficient Ψ (psi), and a discussion on the relevance of IGEs for response to selection in cases where the strength of interaction varies among pairs of individuals. An investigation of the trait-based model shows that the interaction coefficient Ψ may deviate considerably from the corresponding regression coefficient when feedback occurs. The increasing research effort devoted to IGEs suggests that they are a widespread phenomenon, probably particularly in natural populations and plants. Further work in this field should considerably broaden our understanding of the quantitative genetics of inheritance and response to selection in relation to the social organisation of populations. PMID:23512010

  4. Exponential family models and statistical genetics.

    PubMed

    Palmgren, J

    2000-02-01

    This article describes the evolution of applied exponential family models, starting at 1972, the year of publication of the seminal papers on generalized linear models and on Cox regression, and leading to multivariate (i) marginal models and inference based on estimating equations and (ii) random effects models and Bayesian simulation-based posterior inference. By referring to recent work in genetic epidemiology, on semiparametric methods for linkage analysis and on transmission/disequilibrium tests for haplotype transmission this paper illustrates the potential for the recent advances in applied probability and statistics to contribute to new and unified tools for statistical genetics. Finally, it is emphasized that there is a need for well-defined postgraduate education paths in medical statistics in the year 2000 and thereafter. PMID:10826159

  5. Modeling a magnetostrictive transducer using genetic algorithm

    NASA Astrophysics Data System (ADS)

    Almeida, L. A. L.; Deep, G. S.; Lima, A. M. N.; Neff, H.

    2001-05-01

    This work reports on the applicability of the genetic algorithm (GA) to the problem of parameter determination of magnetostrictive transducers. A combination of the Jiles-Atherton hysteresis model with a quadratic moment rotation model is simulated using known parameters of a sensor. The simulated sensor data are then used as input data for the GA parameter calculation method. Taking the previously known parameters, the accuracy of the GA parameter calculation method can be evaluated.

  6. Additive genetic variance and developmental plasticity in growth trajectories in a wild cooperative mammal.

    PubMed

    Huchard, E; Charmantier, A; English, S; Bateman, A; Nielsen, J F; Clutton-Brock, T

    2014-09-01

    Individual variation in growth is high in cooperative breeders and may reflect plastic divergence in developmental trajectories leading to breeding vs. helping phenotypes. However, the relative importance of additive genetic variance and developmental plasticity in shaping growth trajectories is largely unknown in cooperative vertebrates. This study exploits weekly sequences of body mass from birth to adulthood to investigate sources of variance in, and covariance between, early and later growth in wild meerkats (Suricata suricatta), a cooperative mongoose. Our results indicate that (i) the correlation between early growth (prior to nutritional independence) and adult mass is positive but weak, and there are frequent changes (compensatory growth) in post-independence growth trajectories; (ii) among parameters describing growth trajectories, those describing growth rate (prior to and at nutritional independence) show undetectable heritability while associated size parameters (mass at nutritional independence and asymptotic mass) are moderately heritable (0.09 ≤ h(2) < 0.3); and (iii) additive genetic effects, rather than early environmental effects, mediate the covariance between early growth and adult mass. These results reveal that meerkat growth trajectories remain plastic throughout development, rather than showing early and irreversible divergence, and that the weak effects of early growth on adult mass, an important determinant of breeding success, are partly genetic. In contrast to most cooperative invertebrates, the acquisition of breeding status is often determined after sexual maturity and strongly impacted by chance in many cooperative vertebrates, who may therefore retain the ability to adjust their morphology to environmental changes and social opportunities arising throughout their development, rather than specializing early. PMID:24962704

  7. Animal Models of Parkinson's Disease: Vertebrate Genetics

    PubMed Central

    Lee, Yunjong; Dawson, Valina L.; Dawson, Ted M.

    2012-01-01

    Parkinson's disease (PD) is a complex genetic disorder that is associated with environmental risk factors and aging. Vertebrate genetic models, especially mice, have aided the study of autosomal-dominant and autosomal-recessive PD. Mice are capable of showing a broad range of phenotypes and, coupled with their conserved genetic and anatomical structures, provide unparalleled molecular and pathological tools to model human disease. These models used in combination with aging and PD-associated toxins have expanded our understanding of PD pathogenesis. Attempts to refine PD animal models using conditional approaches have yielded in vivo nigrostriatal degeneration that is instructive in ordering pathogenic signaling and in developing therapeutic strategies to cure or halt the disease. Here, we provide an overview of the generation and characterization of transgenic and knockout mice used to study PD followed by a review of the molecular insights that have been gleaned from current PD mouse models. Finally, potential approaches to refine and improve current models are discussed. PMID:22960626

  8. Genomic prediction of growth in pigs based on a model including additive and dominance effects.

    PubMed

    Lopes, M S; Bastiaansen, J W M; Janss, L; Knol, E F; Bovenhuis, H

    2016-06-01

    Independent of whether prediction is based on pedigree or genomic information, the focus of animal breeders has been on additive genetic effects or 'breeding values'. However, when predicting phenotypes rather than breeding values of an animal, models that account for both additive and dominance effects might be more accurate. Our aim with this study was to compare the accuracy of predicting phenotypes using a model that accounts for only additive effects (MA) and a model that accounts for both additive and dominance effects simultaneously (MAD). Lifetime daily gain (DG) was evaluated in three pig populations (1424 Pietrain, 2023 Landrace, and 2157 Large White). Animals were genotyped using the Illumina SNP60K Beadchip and assigned to either a training data set to estimate the genetic parameters and SNP effects, or to a validation data set to assess the prediction accuracy. Models MA and MAD applied random regression on SNP genotypes and were implemented in the program Bayz. The additive heritability of DG across the three populations and the two models was very similar at approximately 0.26. The proportion of phenotypic variance explained by dominance effects ranged from 0.04 (Large White) to 0.11 (Pietrain), indicating that importance of dominance might be breed-specific. Prediction accuracies were higher when predicting phenotypes using total genetic values (sum of breeding values and dominance deviations) from the MAD model compared to using breeding values from both MA and MAD models. The highest increase in accuracy (from 0.195 to 0.222) was observed in the Pietrain, and the lowest in Large White (from 0.354 to 0.359). Predicting phenotypes using total genetic values instead of breeding values in purebred data improved prediction accuracy and reduced the bias of genomic predictions. Additional benefit of the method is expected when applied to predict crossbred phenotypes, where dominance levels are expected to be higher. PMID:26676611

  9. Probabilistic Modeling of Imaging, Genetics and Diagnosis.

    PubMed

    Batmanghelich, Nematollah K; Dalca, Adrian; Quon, Gerald; Sabuncu, Mert; Golland, Polina

    2016-07-01

    We propose a unified Bayesian framework for detecting genetic variants associated with disease by exploiting image-based features as an intermediate phenotype. The use of imaging data for examining genetic associations promises new directions of analysis, but currently the most widely used methods make sub-optimal use of the richness that these data types can offer. Currently, image features are most commonly selected based on their relevance to the disease phenotype. Then, in a separate step, a set of genetic variants is identified to explain the selected features. In contrast, our method performs these tasks simultaneously in order to jointly exploit information in both data types. The analysis yields probabilistic measures of clinical relevance for both imaging and genetic markers. We derive an efficient approximate inference algorithm that handles the high dimensionality of image and genetic data. We evaluate the algorithm on synthetic data and demonstrate that it outperforms traditional models. We also illustrate our method on Alzheimer's Disease Neuroimaging Initiative data. PMID:26886973

  10. Modeling of Nonlinear Systems using Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Hayashi, Kayoko; Yamamoto, Toru; Kawada, Kazuo

    In this paper, a newly modeling system by using Genetic Algorithm (GA) is proposed. The GA is an evolutionary computational method that simulates the mechanisms of heredity or evolution of living things, and it is utilized in optimization and in searching for optimized solutions. Most process systems have nonlinearities, so it is necessary to anticipate exactly such systems. However, it is difficult to make a suitable model for nonlinear systems, because most nonlinear systems have a complex structure. Therefore the newly proposed method of modeling for nonlinear systems uses GA. Then, according to the newly proposed scheme, the optimal structure and parameters of the nonlinear model are automatically generated.

  11. Efficient Markov Chain Monte Carlo Implementation of Bayesian Analysis of Additive and Dominance Genetic Variances in Noninbred Pedigrees

    PubMed Central

    Waldmann, Patrik; Hallander, Jon; Hoti, Fabian; Sillanpää, Mikko J.

    2008-01-01

    Accurate and fast computation of quantitative genetic variance parameters is of great importance in both natural and breeding populations. For experimental designs with complex relationship structures it can be important to include both additive and dominance variance components in the statistical model. In this study, we introduce a Bayesian Gibbs sampling approach for estimation of additive and dominance genetic variances in the traditional infinitesimal model. The method can handle general pedigrees without inbreeding. To optimize between computational time and good mixing of the Markov chain Monte Carlo (MCMC) chains, we used a hybrid Gibbs sampler that combines a single site and a blocked Gibbs sampler. The speed of the hybrid sampler and the mixing of the single-site sampler were further improved by the use of pretransformed variables. Two traits (height and trunk diameter) from a previously published diallel progeny test of Scots pine (Pinus sylvestris L.) and two large simulated data sets with different levels of dominance variance were analyzed. We also performed Bayesian model comparison on the basis of the posterior predictive loss approach. Results showed that models with both additive and dominance components had the best fit for both height and diameter and for the simulated data with high dominance. For the simulated data with low dominance, we needed an informative prior to avoid the dominance variance component becoming overestimated. The narrow-sense heritability estimates in the Scots pine data were lower compared to the earlier results, which is not surprising because the level of dominance variance was rather high, especially for diameter. In general, the hybrid sampler was considerably faster than the blocked sampler and displayed better mixing properties than the single-site sampler. PMID:18558655

  12. Efficient Markov chain Monte Carlo implementation of Bayesian analysis of additive and dominance genetic variances in noninbred pedigrees.

    PubMed

    Waldmann, Patrik; Hallander, Jon; Hoti, Fabian; Sillanpää, Mikko J

    2008-06-01

    Accurate and fast computation of quantitative genetic variance parameters is of great importance in both natural and breeding populations. For experimental designs with complex relationship structures it can be important to include both additive and dominance variance components in the statistical model. In this study, we introduce a Bayesian Gibbs sampling approach for estimation of additive and dominance genetic variances in the traditional infinitesimal model. The method can handle general pedigrees without inbreeding. To optimize between computational time and good mixing of the Markov chain Monte Carlo (MCMC) chains, we used a hybrid Gibbs sampler that combines a single site and a blocked Gibbs sampler. The speed of the hybrid sampler and the mixing of the single-site sampler were further improved by the use of pretransformed variables. Two traits (height and trunk diameter) from a previously published diallel progeny test of Scots pine (Pinus sylvestris L.) and two large simulated data sets with different levels of dominance variance were analyzed. We also performed Bayesian model comparison on the basis of the posterior predictive loss approach. Results showed that models with both additive and dominance components had the best fit for both height and diameter and for the simulated data with high dominance. For the simulated data with low dominance, we needed an informative prior to avoid the dominance variance component becoming overestimated. The narrow-sense heritability estimates in the Scots pine data were lower compared to the earlier results, which is not surprising because the level of dominance variance was rather high, especially for diameter. In general, the hybrid sampler was considerably faster than the blocked sampler and displayed better mixing properties than the single-site sampler. PMID:18558655

  13. Criteria for deviation from predictions by the concentration addition model.

    PubMed

    Takeshita, Jun-Ichi; Seki, Masanori; Kamo, Masashi

    2016-07-01

    Loewe's additivity (concentration addition) is a well-known model for predicting the toxic effects of chemical mixtures under the additivity assumption of toxicity. However, from the perspective of chemical risk assessment and/or management, it is important to identify chemicals whose toxicities are additive when present concurrently, that is, it should be established whether there are chemical mixtures to which the concentration addition predictive model can be applied. The objective of the present study was to develop criteria for judging test results that deviated from the predictions by the concentration addition chemical mixture model. These criteria were based on the confidence interval of the concentration addition model's prediction and on estimation of errors of the predicted concentration-effect curves by toxicity tests after exposure to single chemicals. A log-logit model with 2 parameters was assumed for the concentration-effect curve of each individual chemical. These parameters were determined by the maximum-likelihood method, and the criteria were defined using the variances and the covariance of the parameters. In addition, the criteria were applied to a toxicity test of a binary mixture of p-n-nonylphenol and p-n-octylphenol using the Japanese killifish, medaka (Oryzias latipes). Consequently, the concentration addition model using confidence interval was capable of predicting the test results at any level, and no reason for rejecting the concentration addition was found. Environ Toxicol Chem 2016;35:1806-1814. © 2015 SETAC. PMID:26660330

  14. Genetic Rearrangements of Six Wheat–Agropyron cristatum 6P Addition Lines Revealed by Molecular Markers

    PubMed Central

    Su, Junji; Zhang, Jinpeng; Song, Liqiang; Gao, Ainong; Yang, Xinming; Li, Xiuquan; Liu, Weihua; Li, Lihui

    2014-01-01

    Agropyron cristatum (L.) Gaertn. (2n = 4x = 28, PPPP) not only is cultivated as pasture fodder but also could provide many desirable genes for wheat improvement. It is critical to obtain common wheat–A. cristatum alien disomic addition lines to locate the desired genes on the P genome chromosomes. Comparative analysis of the homoeologous relationships between the P genome chromosome and wheat genome chromosomes is a key step in transferring different desirable genes into common wheat and producing the desired alien translocation line while compensating for the loss of wheat chromatin. In this study, six common wheat–A. cristatum disomic addition lines were produced and analyzed by phenotypic examination, genomic in situ hybridization (GISH), SSR markers from the ABD genomes and STS markers from the P genome. Comparative maps, six in total, were generated and demonstrated that all six addition lines belonged to homoeologous group 6. However, chromosome 6P had undergone obvious rearrangements in different addition lines compared with the wheat chromosome, indicating that to obtain a genetic compensating alien translocation line, one should recombine alien chromosomal regions with homoeologous wheat chromosomes. Indeed, these addition lines were classified into four types based on the comparative mapping: 6PI, 6PII, 6PIII, and 6PIV. The different types of chromosome 6P possessed different desirable genes. For example, the 6PI type, containing three addition lines, carried genes conferring high numbers of kernels per spike and resistance to powdery mildew, important traits for wheat improvement. These results may prove valuable for promoting the development of conventional chromosome engineering techniques toward molecular chromosome engineering. PMID:24595330

  15. Heritability of heterozygosity offers a new way of understanding why dominant gene action contributes to additive genetic variance.

    PubMed

    Nietlisbach, Pirmin; Hadfield, Jarrod D

    2015-07-01

    Whenever allele frequencies are unequal, nonadditive gene action contributes to additive genetic variance and therefore the resemblance between parents and offspring. The reason for this has not been easy to understand. Here, we present a new single-locus decomposition of additive genetic variance that may give greater intuition about this important result. We show that the contribution of dominant gene action to parent-offspring resemblance only depends on the degree to which the heterozygosity of parents and offspring covary. Thus, dominant gene action only contributes to additive genetic variance when heterozygosity is heritable. Under most circumstances this is the case because individuals with rare alleles are more likely to be heterozygous, and because they pass rare alleles to their offspring they also tend to have heterozygous offspring. When segregating alleles are at equal frequency there are no rare alleles, the heterozygosities of parents and offspring are uncorrelated and dominant gene action does not contribute to additive genetic variance. PMID:26100570

  16. Canalization, genetic assimilation and preadaptation. A quantitative genetic model.

    PubMed Central

    Eshel, I; Matessi, C

    1998-01-01

    We propose a mathematical model to analyze the evolution of canalization for a trait under stabilizing selection, where each individual in the population is randomly exposed to different environmental conditions, independently of its genotype. Without canalization, our trait (primary phenotype) is affected by both genetic variation and environmental perturbations (morphogenic environment). Selection of the trait depends on individually varying environmental conditions (selecting environment). Assuming no plasticity initially, morphogenic effects are not correlated with the direction of selection in individual environments. Under quite plausible assumptions we show that natural selection favors a system of canalization that tends to repress deviations from the phenotype that is optimal in the most common selecting environment. However, many experimental results, dating back to Waddington and others, indicate that natural canalization systems may fail under extreme environments. While this can be explained as an impossibility of the system to cope with extreme morphogenic pressure, we show that a canalization system that tends to be inactivated in extreme environments is even more advantageous than rigid canalization. Moreover, once this adaptive canalization is established, the resulting evolution of primary phenotype enables substantial preadaptation to permanent environmental changes resembling extreme niches of the previous environment. PMID:9691063

  17. Additive genetic variance in polyandry enables its evolution, but polyandry is unlikely to evolve through sexy or good sperm processes.

    PubMed

    Travers, L M; Simmons, L W; Garcia-Gonzalez, F

    2016-05-01

    Polyandry is widespread despite its costs. The sexually selected sperm hypotheses ('sexy' and 'good' sperm) posit that sperm competition plays a role in the evolution of polyandry. Two poorly studied assumptions of these hypotheses are the presence of additive genetic variance in polyandry and sperm competitiveness. Using a quantitative genetic breeding design in a natural population of Drosophila melanogaster, we first established the potential for polyandry to respond to selection. We then investigated whether polyandry can evolve through sexually selected sperm processes. We measured lifetime polyandry and offensive sperm competitiveness (P2 ) while controlling for sampling variance due to male × male × female interactions. We also measured additive genetic variance in egg-to-adult viability and controlled for its effect on P2 estimates. Female lifetime polyandry showed significant and substantial additive genetic variance and evolvability. In contrast, we found little genetic variance or evolvability in P2 or egg-to-adult viability. Additive genetic variance in polyandry highlights its potential to respond to selection. However, the low levels of genetic variance in sperm competitiveness suggest that the evolution of polyandry may not be driven by sexy sperm or good sperm processes. PMID:26801640

  18. Very low levels of direct additive genetic variance in fitness and fitness components in a red squirrel population

    PubMed Central

    McFarlane, S Eryn; Gorrell, Jamieson C; Coltman, David W; Humphries, Murray M; Boutin, Stan; McAdam, Andrew G

    2014-01-01

    A trait must genetically correlate with fitness in order to evolve in response to natural selection, but theory suggests that strong directional selection should erode additive genetic variance in fitness and limit future evolutionary potential. Balancing selection has been proposed as a mechanism that could maintain genetic variance if fitness components trade off with one another and has been invoked to account for empirical observations of higher levels of additive genetic variance in fitness components than would be expected from mutation–selection balance. Here, we used a long-term study of an individually marked population of North American red squirrels (Tamiasciurus hudsonicus) to look for evidence of (1) additive genetic variance in lifetime reproductive success and (2) fitness trade-offs between fitness components, such as male and female fitness or fitness in high- and low-resource environments. “Animal model” analyses of a multigenerational pedigree revealed modest maternal effects on fitness, but very low levels of additive genetic variance in lifetime reproductive success overall as well as fitness measures within each sex and environment. It therefore appears that there are very low levels of direct genetic variance in fitness and fitness components in red squirrels to facilitate contemporary adaptation in this population. PMID:24963372

  19. Identifying genetically driven clinical phenotypes using linear mixed models.

    PubMed

    Mosley, Jonathan D; Witte, John S; Larkin, Emma K; Bastarache, Lisa; Shaffer, Christian M; Karnes, Jason H; Stein, C Michael; Phillips, Elizabeth; Hebbring, Scott J; Brilliant, Murray H; Mayer, John; Ye, Zhan; Roden, Dan M; Denny, Joshua C

    2016-01-01

    We hypothesized that generalized linear mixed models (GLMMs), which estimate the additive genetic variance underlying phenotype variability, would facilitate rapid characterization of clinical phenotypes from an electronic health record. We evaluated 1,288 phenotypes in 29,349 subjects of European ancestry with single-nucleotide polymorphism (SNP) genotyping on the Illumina Exome Beadchip. We show that genetic liability estimates are primarily driven by SNPs identified by prior genome-wide association studies and SNPs within the human leukocyte antigen (HLA) region. We identify 44 (false discovery rate q<0.05) phenotypes associated with HLA SNP variation and show that hypothyroidism is genetically correlated with Type I diabetes (rG=0.31, s.e. 0.12, P=0.003). We also report novel SNP associations for hypothyroidism near HLA-DQA1/HLA-DQB1 at rs6906021 (combined odds ratio (OR)=1.2 (95% confidence interval (CI): 1.1-1.2), P=9.8 × 10(-11)) and for polymyalgia rheumatica near C6orf10 at rs6910071 (OR=1.5 (95% CI: 1.3-1.6), P=1.3 × 10(-10)). Phenome-wide application of GLMMs identifies phenotypes with important genetic drivers, and focusing on these phenotypes can identify novel genetic associations. PMID:27109359

  20. Identifying genetically driven clinical phenotypes using linear mixed models

    PubMed Central

    Mosley, Jonathan D.; Witte, John S.; Larkin, Emma K.; Bastarache, Lisa; Shaffer, Christian M.; Karnes, Jason H.; Stein, C. Michael; Phillips, Elizabeth; Hebbring, Scott J.; Brilliant, Murray H.; Mayer, John; Ye, Zhan; Roden, Dan M.; Denny, Joshua C.

    2016-01-01

    We hypothesized that generalized linear mixed models (GLMMs), which estimate the additive genetic variance underlying phenotype variability, would facilitate rapid characterization of clinical phenotypes from an electronic health record. We evaluated 1,288 phenotypes in 29,349 subjects of European ancestry with single-nucleotide polymorphism (SNP) genotyping on the Illumina Exome Beadchip. We show that genetic liability estimates are primarily driven by SNPs identified by prior genome-wide association studies and SNPs within the human leukocyte antigen (HLA) region. We identify 44 (false discovery rate q<0.05) phenotypes associated with HLA SNP variation and show that hypothyroidism is genetically correlated with Type I diabetes (rG=0.31, s.e. 0.12, P=0.003). We also report novel SNP associations for hypothyroidism near HLA-DQA1/HLA-DQB1 at rs6906021 (combined odds ratio (OR)=1.2 (95% confidence interval (CI): 1.1–1.2), P=9.8 × 10−11) and for polymyalgia rheumatica near C6orf10 at rs6910071 (OR=1.5 (95% CI: 1.3–1.6), P=1.3 × 10−10). Phenome-wide application of GLMMs identifies phenotypes with important genetic drivers, and focusing on these phenotypes can identify novel genetic associations. PMID:27109359

  1. Complex Modelling Scheme Of An Additive Manufacturing Centre

    NASA Astrophysics Data System (ADS)

    Popescu, Liliana Georgeta

    2015-09-01

    This paper presents a modelling scheme sustaining the development of an additive manufacturing research centre model and its processes. This modelling is performed using IDEF0, the resulting model process representing the basic processes required in developing such a centre in any university. While the activities presented in this study are those recommended in general, changes may occur in specific existing situations in a research centre.

  2. An animal model of differential genetic risk for methamphetamine intake

    PubMed Central

    Phillips, Tamara J.; Shabani, Shkelzen

    2015-01-01

    The question of whether genetic factors contribute to risk for methamphetamine (MA) use and dependence has not been intensively investigated. Compared to human populations, genetic animal models offer the advantages of control over genetic family history and drug exposure. Using selective breeding, we created lines of mice that differ in genetic risk for voluntary MA intake and identified the chromosomal addresses of contributory genes. A quantitative trait locus was identified on chromosome 10 that accounts for more than 50% of the genetic variance in MA intake in the selected mouse lines. In addition, behavioral and physiological screening identified differences corresponding with risk for MA intake that have generated hypotheses that are testable in humans. Heightened sensitivity to aversive and certain physiological effects of MA, such as MA-induced reduction in body temperature, are hallmarks of mice bred for low MA intake. Furthermore, unlike MA-avoiding mice, MA-preferring mice are sensitive to rewarding and reinforcing MA effects, and to MA-induced increases in brain extracellular dopamine levels. Gene expression analyses implicate the importance of a network enriched in transcription factor genes, some of which regulate the mu opioid receptor gene, Oprm1, in risk for MA use. Neuroimmune factors appear to play a role in differential response to MA between the mice bred for high and low intake. In addition, chromosome 10 candidate gene studies provide strong support for a trace amine-associated receptor 1 gene, Taar1, polymorphism in risk for MA intake. MA is a trace amine-associated receptor 1 (TAAR1) agonist, and a non-functional Taar1 allele segregates with high MA consumption. Thus, reduced TAAR1 function has the potential to increase risk for MA use. Overall, existing findings support the MA drinking lines as a powerful model for identifying genetic factors involved in determining risk for harmful MA use. Future directions include the development of a

  3. Comprehensive European dietary exposure model (CEDEM) for food additives.

    PubMed

    Tennant, David R

    2016-05-01

    European methods for assessing dietary exposures to nutrients, additives and other substances in food are limited by the availability of detailed food consumption data for all member states. A proposed comprehensive European dietary exposure model (CEDEM) applies summary data published by the European Food Safety Authority (EFSA) in a deterministic model based on an algorithm from the EFSA intake method for food additives. The proposed approach can predict estimates of food additive exposure provided in previous EFSA scientific opinions that were based on the full European food consumption database. PMID:26987377

  4. Genetic demixing and evolution in linear stepping stone models

    NASA Astrophysics Data System (ADS)

    Korolev, K. S.; Avlund, Mikkel; Hallatschek, Oskar; Nelson, David R.

    2010-04-01

    Results for mutation, selection, genetic drift, and migration in a one-dimensional continuous population are reviewed and extended. The population is described by a continuous limit of the stepping stone model, which leads to the stochastic Fisher-Kolmogorov-Petrovsky-Piscounov equation with additional terms describing mutations. Although the stepping stone model was first proposed for population genetics, it is closely related to “voter models” of interest in nonequilibrium statistical mechanics. The stepping stone model can also be regarded as an approximation to the dynamics of a thin layer of actively growing pioneers at the frontier of a colony of micro-organisms undergoing a range expansion on a Petri dish. The population tends to segregate into monoallelic domains. This segregation slows down genetic drift and selection because these two evolutionary forces can only act at the boundaries between the domains; the effects of mutation, however, are not significantly affected by the segregation. Although fixation in the neutral well-mixed (or “zero-dimensional”) model occurs exponentially in time, it occurs only algebraically fast in the one-dimensional model. An unusual sublinear increase is also found in the variance of the spatially averaged allele frequency with time. If selection is weak, selective sweeps occur exponentially fast in both well-mixed and one-dimensional populations, but the time constants are different. The relatively unexplored problem of evolutionary dynamics at the edge of an expanding circular colony is studied as well. Also reviewed are how the observed patterns of genetic diversity can be used for statistical inference and the differences are highlighted between the well-mixed and one-dimensional models. Although the focus is on two alleles or variants, q -allele Potts-like models of gene segregation are considered as well. Most of the analytical results are checked with simulations and could be tested against recent spatial

  5. Evolutionary model with genetics, aging, and knowledge

    NASA Astrophysics Data System (ADS)

    Bustillos, Armando Ticona; de Oliveira, Paulo Murilo

    2004-02-01

    We represent a process of learning by using bit strings, where 1 bits represent the knowledge acquired by individuals. Two ways of learning are considered: individual learning by trial and error, and social learning by copying knowledge from other individuals or from parents in the case of species with parental care. The age-structured bit string allows us to study how knowledge is accumulated during life and its influence over the genetic pool of a population after many generations. We use the Penna model to represent the genetic inheritance of each individual. In order to study how the accumulated knowledge influences the survival process, we include it to help individuals to avoid the various death situations. Modifications in the Verhulst factor do not show any special feature due to its random nature. However, by adding years to life as a function of the accumulated knowledge, we observe an improvement of the survival rates while the genetic fitness of the population becomes worse. In this latter case, knowledge becomes more important in the last years of life where individuals are threatened by diseases. Effects of offspring overprotection and differences between individual and social learning can also be observed. Sexual selection as a function of knowledge shows some effects when fidelity is imposed.

  6. On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis

    PubMed Central

    Li, Bing; Chun, Hyonho; Zhao, Hongyu

    2014-01-01

    We introduce a nonparametric method for estimating non-gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis. PMID:26401064

  7. Mouse Genetic Models of Human Brain Disorders.

    PubMed

    Leung, Celeste; Jia, Zhengping

    2016-01-01

    Over the past three decades, genetic manipulations in mice have been used in neuroscience as a major approach to investigate the in vivo function of genes and their alterations. In particular, gene targeting techniques using embryonic stem cells have revolutionized the field of mammalian genetics and have been at the forefront in the generation of numerous mouse models of human brain disorders. In this review, we will first examine childhood developmental disorders such as autism, intellectual disability, Fragile X syndrome, and Williams-Beuren syndrome. We will then explore psychiatric disorders such as schizophrenia and lastly, neurodegenerative disorders including Alzheimer's disease and Parkinson's disease. We will outline the creation of these mouse models that range from single gene deletions, subtle point mutations to multi-gene manipulations, and discuss the key behavioral phenotypes of these mice. Ultimately, the analysis of the models outlined in this review will enhance our understanding of the in vivo role and underlying mechanisms of disease-related genes in both normal brain function and brain disorders, and provide potential therapeutic targets and strategies to prevent and treat these diseases. PMID:27047540

  8. Mouse Genetic Models of Human Brain Disorders

    PubMed Central

    Leung, Celeste; Jia, Zhengping

    2016-01-01

    Over the past three decades, genetic manipulations in mice have been used in neuroscience as a major approach to investigate the in vivo function of genes and their alterations. In particular, gene targeting techniques using embryonic stem cells have revolutionized the field of mammalian genetics and have been at the forefront in the generation of numerous mouse models of human brain disorders. In this review, we will first examine childhood developmental disorders such as autism, intellectual disability, Fragile X syndrome, and Williams-Beuren syndrome. We will then explore psychiatric disorders such as schizophrenia and lastly, neurodegenerative disorders including Alzheimer’s disease and Parkinson’s disease. We will outline the creation of these mouse models that range from single gene deletions, subtle point mutations to multi-gene manipulations, and discuss the key behavioral phenotypes of these mice. Ultimately, the analysis of the models outlined in this review will enhance our understanding of the in vivo role and underlying mechanisms of disease-related genes in both normal brain function and brain disorders, and provide potential therapeutic targets and strategies to prevent and treat these diseases. PMID:27047540

  9. Additive-multiplicative rates model for recurrent events.

    PubMed

    Liu, Yanyan; Wu, Yuanshan; Cai, Jianwen; Zhou, Haibo

    2010-07-01

    Recurrent events are frequently encountered in biomedical studies. Evaluating the covariates effects on the marginal recurrent event rate is of practical interest. There are mainly two types of rate models for the recurrent event data: the multiplicative rates model and the additive rates model. We consider a more flexible additive-multiplicative rates model for analysis of recurrent event data, wherein some covariate effects are additive while others are multiplicative. We formulate estimating equations for estimating the regression parameters. The estimators for these regression parameters are shown to be consistent and asymptotically normally distributed under appropriate regularity conditions. Moreover, the estimator of the baseline mean function is proposed and its large sample properties are investigated. We also conduct simulation studies to evaluate the finite sample behavior of the proposed estimators. A medical study of patients with cystic fibrosis suffered from recurrent pulmonary exacerbations is provided for illustration of the proposed method. PMID:20229314

  10. Automatic reactor model synthesis with genetic programming.

    PubMed

    Dürrenmatt, David J; Gujer, Willi

    2012-01-01

    Successful modeling of wastewater treatment plant (WWTP) processes requires an accurate description of the plant hydraulics. Common methods such as tracer experiments are difficult and costly and thus have limited applicability in practice; engineers are often forced to rely on their experience only. An implementation of grammar-based genetic programming with an encoding to represent hydraulic reactor models as program trees should fill this gap: The encoding enables the algorithm to construct arbitrary reactor models compatible with common software used for WWTP modeling by linking building blocks, such as continuous stirred-tank reactors. Discharge measurements and influent and effluent concentrations are the only required inputs. As shown in a synthetic example, the technique can be used to identify a set of reactor models that perform equally well. Instead of being guided by experience, the most suitable model can now be chosen by the engineer from the set. In a second example, temperature measurements at the influent and effluent of a primary clarifier are used to generate a reactor model. A virtual tracer experiment performed on the reactor model has good agreement with a tracer experiment performed on-site. PMID:22277238

  11. Explanatory Models of Genetics and Genetic Risk among a Selected Group of Students.

    PubMed

    Goltz, Heather Honoré; Bergman, Margo; Goodson, Patricia

    2016-01-01

    This exploratory qualitative study focuses on how college students conceptualize genetics and genetic risk, concepts essential for genetic literacy (GL) and genetic numeracy (GN), components of overall health literacy (HL). HL is dependent on both the background knowledge and culture of a patient, and lower HL is linked to increased morbidity and mortality for a number of chronic health conditions (e.g., diabetes and cancer). A purposive sample of 86 students from three Southwestern universities participated in eight focus groups. The sample ranged in age from 18 to 54 years, and comprised primarily of female (67.4%), single (74.4%), and non-White (57%) participants, none of whom were genetics/biology majors. A holistic-content approach revealed broad categories concerning participants' explanatory models (EMs) of genetics and genetic risk. Participants' EMs were grounded in highly contextualized narratives that only partially overlapped with biomedical models. While higher education levels should be associated with predominately knowledge-based EM of genetic risk, this study shows that even in well-educated populations cultural factors can dominate. Study findings reveal gaps in how this sample of young adults obtains, processes, and understands genetic/genomic concepts. Future studies should assess how individuals with low GL and GN obtain and process genetics and genetic risk information and incorporate this information into health decision making. Future work should also address the interaction of communication between health educators, providers, and genetic counselors, to increase patient understanding of genetic risk. PMID:27376052

  12. Explanatory Models of Genetics and Genetic Risk among a Selected Group of Students

    PubMed Central

    Goltz, Heather Honoré; Bergman, Margo; Goodson, Patricia

    2016-01-01

    This exploratory qualitative study focuses on how college students conceptualize genetics and genetic risk, concepts essential for genetic literacy (GL) and genetic numeracy (GN), components of overall health literacy (HL). HL is dependent on both the background knowledge and culture of a patient, and lower HL is linked to increased morbidity and mortality for a number of chronic health conditions (e.g., diabetes and cancer). A purposive sample of 86 students from three Southwestern universities participated in eight focus groups. The sample ranged in age from 18 to 54 years, and comprised primarily of female (67.4%), single (74.4%), and non-White (57%) participants, none of whom were genetics/biology majors. A holistic-content approach revealed broad categories concerning participants’ explanatory models (EMs) of genetics and genetic risk. Participants’ EMs were grounded in highly contextualized narratives that only partially overlapped with biomedical models. While higher education levels should be associated with predominately knowledge-based EM of genetic risk, this study shows that even in well-educated populations cultural factors can dominate. Study findings reveal gaps in how this sample of young adults obtains, processes, and understands genetic/genomic concepts. Future studies should assess how individuals with low GL and GN obtain and process genetics and genetic risk information and incorporate this information into health decision making. Future work should also address the interaction of communication between health educators, providers, and genetic counselors, to increase patient understanding of genetic risk. PMID:27376052

  13. Genetically engineered livestock for biomedical models.

    PubMed

    Rogers, Christopher S

    2016-06-01

    To commemorate Transgenic Animal Research Conference X, this review summarizes the recent progress in developing genetically engineered livestock species as biomedical models. The first of these conferences was held in 1997, which turned out to be a watershed year for the field, with two significant events occurring. One was the publication of the first transgenic livestock animal disease model, a pig with retinitis pigmentosa. Before that, the use of livestock species in biomedical research had been limited to wild-type animals or disease models that had been induced or were naturally occurring. The second event was the report of Dolly, a cloned sheep produced by somatic cell nuclear transfer. Cloning subsequently became an essential part of the process for most of the models developed in the last 18 years and is stilled used prominently today. This review is intended to highlight the biomedical modeling achievements that followed those key events, many of which were first reported at one of the previous nine Transgenic Animal Research Conferences. Also discussed are the practical challenges of utilizing livestock disease models now that the technical hurdles of model development have been largely overcome. PMID:26820410

  14. Accelerated Nucleation Due to Trace Additives: A Fluctuating Coverage Model.

    PubMed

    Poon, Geoffrey G; Peters, Baron

    2016-03-01

    We develop a theory to account for variable coverage of trace additives that lower the interfacial free energy for nucleation. The free energy landscape is based on classical nucleation theory and a statistical mechanical model for Langmuir adsorption. Dynamics are modeled by diffusion-controlled attachment and detachment of solutes and adsorbing additives. We compare the mechanism and kinetics from a mean-field model, a projection of the dynamics and free energy surface onto nucleus size, and a full two-dimensional calculation using Kramers-Langer-Berezhkovskii-Szabo theory. The fluctuating coverage model predicts rates more accurately than mean-field models of the same process primarily because it more accurately estimates the potential of mean force along the size coordinate. PMID:26485064

  15. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... individual has a genetic variant associated with hereditary nonpolyposis colorectal cancer is a genetic test... manifested with respect to A. Example 2. (i) Facts. Individual B has several family members with colon cancer... hereditary nonpolyposis colorectal cancer (HNPCC). B's physician, a health care professional with...

  16. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... individual has a genetic variant associated with hereditary nonpolyposis colorectal cancer is a genetic test... manifested with respect to A. Example 2. (i) Facts. Individual B has several family members with colon cancer... hereditary nonpolyposis colorectal cancer (HNPCC). B's physician, a health care professional with...

  17. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... individual has a genetic variant associated with hereditary nonpolyposis colorectal cancer is a genetic test... manifested with respect to A. Example 2. (i) Facts. Individual B has several family members with colon cancer... hereditary nonpolyposis colorectal cancer (HNPCC). B's physician, a health care professional with...

  18. 45 CFR 146.122 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... individual has a genetic variant associated with hereditary nonpolyposis colorectal cancer is a genetic test... manifested with respect to A. Example 2. (i) Facts. Individual B has several family members with colon cancer... hereditary nonpolyposis colorectal cancer (HNPCC). B's physician, a health care professional with...

  19. The system-resonance approach in modeling genetic structures.

    PubMed

    Petoukhov, Sergey V

    2016-01-01

    The founder of the theory of resonance in structural chemistry Linus Pauling established the importance of resonance patterns in organization of living systems. Any living organism is a great chorus of coordinated oscillatory processes. From the formal point of view, biological organism is an oscillatory system with a great number of degrees of freedom. Such systems are studied in the theory of oscillations using matrix mathematics of their resonance characteristics. This study is devoted to a new approach for modeling genetically inherited structures and processes in living organisms using mathematical tools of the theory of resonances. This approach reveals hidden relationships in a number of genetic phenomena and gives rise to a new class of bio-mathematical models, which contribute to a convergence of biology with physics and informatics. In addition some relationships of molecular-genetic ensembles with mathematics of noise-immunity coding of information in modern communications technology are shown. Perspectives of applications of the phenomena of vibrational mechanics for modeling in biology are discussed. PMID:26545937

  20. Genetically engineered livestock: ethical use for food and medical models.

    PubMed

    Garas, Lydia C; Murray, James D; Maga, Elizabeth A

    2015-01-01

    Recent advances in the production of genetically engineered (GE) livestock have resulted in a variety of new transgenic animals with desirable production and composition changes. GE animals have been generated to improve growth efficiency, food composition, and disease resistance in domesticated livestock species. GE animals are also used to produce pharmaceuticals and as medical models for human diseases. The potential use of these food animals for human consumption has prompted an intense debate about food safety and animal welfare concerns with the GE approach. Additionally, public perception and ethical concerns about their use have caused delays in establishing a clear and efficient regulatory approval process. Ethically, there are far-reaching implications of not using genetically engineered livestock, at a detriment to both producers and consumers, as use of this technology can improve both human and animal health and welfare. PMID:25387117

  1. Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

    NASA Technical Reports Server (NTRS)

    Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

    2013-01-01

    The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

  2. Modelling the behaviour of additives in gun barrels

    NASA Astrophysics Data System (ADS)

    Rhodes, N.; Ludwig, J. C.

    1986-01-01

    A mathematical model which predicts the flow and heat transfer in a gun barrel is described. The model is transient, two-dimensional and equations are solved for velocities and enthalpies of a gas phase, which arises from the combustion of propellant and cartridge case, for particle additives which are released from the case; volume fractions of the gas and particles. Closure of the equations is obtained using a two-equation turbulence model. Preliminary calculations are described in which the proportions of particle additives in the cartridge case was altered. The model gives a good prediction of the ballistic performance and the gas to wall heat transfer. However, the expected magnitude of reduction in heat transfer when particles are present is not predicted. The predictions of gas flow invalidate some of the assumptions made regarding case and propellant behavior during combustion and further work is required to investigate these effects and other possible interactions, both chemical and physical, between gas and particles.

  3. An Additional Symmetry in the Weinberg-Salam Model

    SciTech Connect

    Bakker, B.L.G.; Veselov, A.I.; Zubkov, M.A.

    2005-06-01

    An additional Z{sub 6} symmetry hidden in the fermion and Higgs sectors of the Standard Model has been found recently. It has a singular nature and is connected to the centers of the SU(3) and SU(2) subgroups of the gauge group. A lattice regularization of the Standard Model was constructed that possesses this symmetry. In this paper, we report our results on the numerical simulation of its electroweak sector.

  4. Modeling uranium transport in acidic contaminated groundwater with base addition

    SciTech Connect

    Zhang, Fan; Luo, Wensui; Parker, Jack C.; Brooks, Scott C; Watson, David B; Jardine, Philip; Gu, Baohua

    2011-01-01

    This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO{sub 3}{sup -}, SO{sub 4}{sup 2-}, U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.

  5. Perceptions of Latinas on the Traditional Prenatal Genetic Counseling Model.

    PubMed

    Thompson, Stephanie; Noblin, Sarah Jane; Lemons, Jennifer; Peterson, Susan K; Carreno, Carlos; Harbison, Andrea

    2015-08-01

    The traditional genetic counseling model encompasses an individualized counseling session that includes the presentation of information about genes, chromosomes, personalized risk assessment, and genetic testing and screening options. Counselors are challenged to balance the provision of enough basic genetic information to ensure clients' understanding of the genetic condition in question with a personalized discussion of what this information means to them. This study explored the perceptions Latinas have about prenatal genetic counseling sessions and aimed to determine if they had preferences about the delivery of care. Data were collected through focus groups and one-on-one, semi-structured interviews of 25 Spanish speaking Latinas who received genetic counseling during their current pregnancy. We implemented grounded theory to evaluate participant responses, and were able to identify common emergent themes. Several themes were identified including an overall satisfaction with their prenatal genetic counseling appointment, desire for a healthy baby, peace of mind following their appointment, lack of desire for invasive testing, and faith in God. Several participants stated a preference for group genetic counseling over the traditional individual genetic counseling model. Our data indicate that Latinas value the information presented at prenatal genetic counseling appointments despite disinterest in pursuing genetic testing or screening and suggest that group prenatal genetic counseling may be an effective alternative to the traditional genetic counseling model in the Latina population. PMID:25475921

  6. Genetic variation and prediction of additive and nonadditive genetic effects for six carcass traits in an Angus-Brahman multibreed herd.

    PubMed

    Elzo, M A; West, R L; Johnson, D D; Wakeman, D L

    1998-07-01

    Estimates of covariances and sire expected progeny differences of additive and nonadditive genetic effects for six carcass traits were obtained using records from 486 straightbred and crossbred steers from 121 sires born between 1989 and 1995 in the Angus-Brahman multibreed herd of the University of Florida. Steers were slaughtered at a similar carcass composition end point. Covariances were estimated by REML procedures, using a generalized expectation-maximization algorithm applied to multibreed populations. Straightbred and crossbred estimates of heritabilities and additive genetic correlations were within ranges found in the literature for steers slaughtered on an age- or weight-constant basis for hot carcass weight, longissimus muscle area, and shear force but equal to or less than the lower bound of these ranges for fat-related traits. Maximum values of interactibilities (i.e., ratios of nonadditive variances to phenotypic variances in the F1) and nonadditive genetic correlations were smaller than heritabilities and additive genetic correlations in straightbreds and crossbred groups. Sire additive and total direct genetic predictions for longissimus muscle area, marbling, and shear force tended to decrease with the fraction of Brahman alleles, whereas those for hot carcass weight and fat thickness over the longissimus were higher, and those for kidney fat were lower in straightbreds and F1 than in other crossbred groups. Nonadditive genetic predictions were similar across sire groups of all Angus and Brahman fractions. These results suggest that slaughtering steers on a similar carcass composition basis reduces variability of fat-related traits while retaining variability for non-fat-related traits comparable to slaughtering steers on a similar age or weight basis. Selection for carcass traits within desirable (narrow) ranges and slaughter of steers at similar compositional end point seems to be a good combination to help produce meat products of consistent

  7. Estimation and interpretation of genetic effects with epistasis using the NOIA model.

    PubMed

    Alvarez-Castro, José M; Carlborg, Orjan; Rönnegård, Lars

    2012-01-01

    We introduce this communication with a brief outline of the historical landmarks in genetic modeling, especially concerning epistasis. Then, we present methods for the use of genetic modeling in QTL analyses. In particular, we summarize the essential expressions of the natural and orthogonal interactions (NOIA) model of genetic effects. Our motivation for reviewing that theory here is twofold. First, this review presents a digest of the expressions for the application of the NOIA model, which are often mixed with intermediate and additional formulae in the original articles. Second, we make the required theory handy for the reader to relate the genetic concepts to the particular mathematical expressions underlying them. We illustrate those relations by providing graphical interpretations and a diagram summarizing the key features for applying genetic modeling with epistasis in comprehensive QTL analyses. Finally, we briefly review some examples of the application of NOIA to real data and the way it improves the interpretability of the results. PMID:22565838

  8. Using Set Model for Learning Addition of Integers

    ERIC Educational Resources Information Center

    Lestari, Umi Puji; Putri, Ratu Ilma Indra; Hartono, Yusuf

    2015-01-01

    This study aims to investigate how set model can help students' understanding of addition of integers in fourth grade. The study has been carried out to 23 students and a teacher of IVC SD Iba Palembang in January 2015. This study is a design research that also promotes PMRI as the underlying design context and activity. Results showed that the…

  9. Genetic predisposition to coronary heart disease and stroke using an additive genetic risk score: a population-based study in Greece

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Objective: To determine the extent to which the risk for incident coronary heart disease (CHD) increases in relation to a genetic risk score (GRS) that additively integrates the influence of high-risk alleles in nine documented single nucleotide polymorphisms (SNPs) for CHD, and to examine whether t...

  10. Generating Effective Models and Parameters for RNA Genetic Circuits.

    PubMed

    Hu, Chelsea Y; Varner, Jeffrey D; Lucks, Julius B

    2015-08-21

    RNA genetic circuitry is emerging as a powerful tool to control gene expression. However, little work has been done to create a theoretical foundation for RNA circuit design. A prerequisite to this is a quantitative modeling framework that accurately describes the dynamics of RNA circuits. In this work, we develop an ordinary differential equation model of transcriptional RNA genetic circuitry, using an RNA cascade as a test case. We show that parameter sensitivity analysis can be used to design a set of four simple experiments that can be performed in parallel using rapid cell-free transcription-translation (TX-TL) reactions to determine the 13 parameters of the model. The resulting model accurately recapitulates the dynamic behavior of the cascade, and can be easily extended to predict the function of new cascade variants that utilize new elements with limited additional characterization experiments. Interestingly, we show that inconsistencies between model predictions and experiments led to the model-guided discovery of a previously unknown maturation step required for RNA regulator function. We also determine circuit parameters in two different batches of TX-TL, and show that batch-to-batch variation can be attributed to differences in parameters that are directly related to the concentrations of core gene expression machinery. We anticipate the RNA circuit models developed here will inform the creation of computer aided genetic circuit design tools that can incorporate the growing number of RNA regulators, and that the parametrization method will find use in determining functional parameters of a broad array of natural and synthetic regulatory systems. PMID:26046393

  11. Genetic Algorithm Approaches to Prebiobiotic Chemistry Modeling

    NASA Technical Reports Server (NTRS)

    Lohn, Jason; Colombano, Silvano

    1997-01-01

    We model an artificial chemistry comprised of interacting polymers by specifying two initial conditions: a distribution of polymers and a fixed set of reversible catalytic reactions. A genetic algorithm is used to find a set of reactions that exhibit a desired dynamical behavior. Such a technique is useful because it allows an investigator to determine whether a specific pattern of dynamics can be produced, and if it can, the reaction network found can be then analyzed. We present our results in the context of studying simplified chemical dynamics in theorized protocells - hypothesized precursors of the first living organisms. Our results show that given a small sample of plausible protocell reaction dynamics, catalytic reaction sets can be found. We present cases where this is not possible and also analyze the evolved reaction sets.

  12. Competitive speciation in quantitative genetic models.

    PubMed

    Drossel, B; Mckane, A

    2000-06-01

    We study sympatric speciation due to competition in an environment with a broad distribution of resources. We assume that the trait under selection is a quantitative trait, and that mating is assortative with respect to this trait. Our model alternates selection according to Lotka-Volterra-type competition equations, with reproduction using the ideas of quantitative genetics. The recurrence relations defined by these equations are studied numerically and analytically. We find that when a population enters a new environment, with a broad distribution of unexploited food sources, the population distribution broadens under a variety of conditions, with peaks at the edge of the distribution indicating the formation of subpopulations. After a long enough time period, the population can split into several subpopulations with little gene flow between them. PMID:10816369

  13. Experimental Population Genetics in the Introductory Genetics Laboratory Using "Drosophila" as a Model Organism

    ERIC Educational Resources Information Center

    Johnson, Ronald; Kennon, Tillman

    2009-01-01

    Hypotheses of population genetics are derived and tested by students in the introductory genetics laboratory classroom as they explore the effects of biotic variables (physical traits of fruit flies) and abiotic variables (island size and distance) on fruit fly populations. In addition to this hypothesis-driven experiment, the development of…

  14. Genetic models of poljes in Sicily

    NASA Astrophysics Data System (ADS)

    Di Maggio, Cipriano; Madonia, Giuliana; Vattano, Marco; De Waele, Jo

    2016-04-01

    Geomorphological and geological studies have been carried out to contribute to the recognition of controlling causes and to the definition of genetic models for poljes of Sicily. A polje is a kilometric closed depression developed mainly on karst rocks, with a conspicuously flat and alluviated bottom affected by intermittent flooding. A polje is usually characterised by relatively steep slopes enclosing an almost perfectly horizontal floor, caused by lateral solution planation related to flooding events. The origin of a polje is due to dissolution of the land surface, although geological structure generally influences its genesis. These large depressions are often elongated according to the direction of main faults, in consequence of a control due to tectonics or to differential erosion. The performed researches have shown the existence of at least seven poljes located along the north-western (chain zone) and the southern (deformed foredeep zone) areas of Sicily. These large karst depressions are developed on Mesozoic limestone/dolomitic rocks within the chain zone and on Messinian gypsum rocks within the deformed foredeep zone. They are up to 4 km in length, can reach surfaces of 3-8 km2 and are around hundred metres deep, with steep slopes and a flat bottom. Generally, they are open, occasionally active depressions and their genesis seems to be strongly controlled by structure. In particular, the studied poljes occur in two different geological/geomorphological settings: a) in graben-like tectonic depressions, where important fault slopes/scarps border the flat bottom; b) in complex depressions controlled by structure, where wide fault line slopes/scarps or large inclined degraded structural surfaces mark the poljes. Finally, landscape analysis leads to the proposition of two main genetic models in which the development of poljes is primarily due to tectonics or differential erosion followed by dissolution.

  15. The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance

    PubMed Central

    Forsberg, Simon K. G.; Andreatta, Matthew E.; Huang, Xin-Yuan; Danku, John; Salt, David E.; Carlborg, Örjan

    2015-01-01

    Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations. PMID:26599497

  16. A Tri-part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning About Authentic Genetics Dilemmas

    NASA Astrophysics Data System (ADS)

    Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

    2015-08-01

    Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational features of a reasoning task may influence how students apply content knowledge as they generate and support arguments. Understanding how students apply content knowledge to reason about authentic and complex issues is important for considering instructional practices that best support student thinking and reasoning. In this conceptual report, we present a tri-part model for genetics literacy that embodies the relationships between content knowledge use, argumentation quality, and the role of situational features in reasoning to support genetics literacy. Using illustrative examples from an interview study with early career undergraduate students majoring in the biological sciences and late career undergraduate students majoring in genetics, we provide insights into undergraduate student reasoning about complex genetics issues and discuss implications for teaching and learning. We further discuss the need for research about how the tri-part model of genetics literacy can be used to explore students' thinking and reasoning abilities in genetics.

  17. Estimating soil water retention using soil component additivity model

    NASA Astrophysics Data System (ADS)

    Zeiliger, A.; Ermolaeva, O.; Semenov, V.

    2009-04-01

    Soil water retention is a major soil hydraulic property that governs soil functioning in ecosystems and greatly affects soil management. Data on soil water retention are used in research and applications in hydrology, agronomy, meteorology, ecology, environmental protection, and many other soil-related fields. Soil organic matter content and composition affect both soil structure and adsorption properties; therefore water retention may be affected by changes in soil organic matter that occur because of both climate change and modifications of management practices. Thus, effects of organic matter on soil water retention should be understood and quantified. Measurement of soil water retention is relatively time-consuming, and become impractical when soil hydrologic estimates are needed for large areas. One approach to soil water retention estimation from readily available data is based on the hypothesis that soil water retention may be estimated as an additive function obtained by summing up water retention of pore subspaces associated with soil textural and/or structural components and organic matter. The additivity model and was tested with 550 soil samples from the international database UNSODA and 2667 soil samples from the European database HYPRES containing all textural soil classes after USDA soil texture classification. The root mean square errors (RMSEs) of the volumetric water content estimates for UNSODA vary from 0.021 m3m-3 for coarse sandy loam to 0.075 m3m-3 for sandy clay. Obtained RMSEs are at the lower end of the RMSE range for regression-based water retention estimates found in literature. Including retention estimates of organic matter significantly improved RMSEs. The attained accuracy warrants testing the 'additivity' model with additional soil data and improving this model to accommodate various types of soil structure. Keywords: soil water retention, soil components, additive model, soil texture, organic matter.

  18. Genetically engineered mouse models for lung cancer.

    PubMed

    Kwak, I; Tsai, S Y; DeMayo, F J

    2004-01-01

    The lung is a complex organ consisting of numerous cell types that function to ensure sufficient gas exchange to oxygenate the blood. In order to accomplish this function, the lung must be exposed to the external environment and at the same time maintain a homeostatic balance between its function in gas exchange and the maintenance of inflammatory balance. During the past two decades, as molecular methodologies have evolved with the sequencing of entire genomes, the use of in vivo models to elucidate the molecular mechanisms involved in pulmonary physiology and disease have increased. The mouse has emerged as a potent model to investigate pulmonary physiology due to the explosion in molecular methods that now allow for the developmental and tissue-specific regulation of gene transcription. Initial efforts to manipulate gene expression in the mouse genome resulted in the generation of transgenic mice characterized by the constitutive expression of a specific gene and knockout mice characterized by the ablation of a specific gene. The utility of these original mouse models was limited, in many cases, by phenotypes resulting in embryonic or neonatal lethality that prevented analysis of the impact of the genetic manipulation on pulmonary biology. Second-generation transgenic mouse models employ multiple strategies that can either activate or silence gene expression thereby providing extensive temporal and spatial control of the experimental parameters of gene expression. These highly regulated mouse models are intended to serve as a foundation for further investigation of the molecular basis of human disease such as tumorigenesis. This review describes the principles, progress, and application of systems that are currently employed in the conditional regulation of gene expression in the investigation of lung cancer. PMID:14977417

  19. Mining functional modules in genetic networks with decomposable graphical models.

    PubMed

    Dejori, Mathäus; Schwaighofer, Anton; Tresp, Volker; Stetter, Martin

    2004-01-01

    In recent years, graphical models have become an increasingly important tool for the structural analysis of genome-wide expression profiles at the systems level. Here we present a new graphical modelling technique, which is based on decomposable graphical models, and apply it to a set of gene expression profiles from acute lymphoblastic leukemia (ALL). The new method explains probabilistic dependencies of expression levels in terms of the concerted action of underlying genetic functional modules, which are represented as so-called "cliques" in the graph. In addition, the method uses continuous-valued (instead of discretized) expression levels, and makes no particular assumption about their probability distribution. We show that the method successfully groups members of known functional modules to cliques. Our method allows the evaluation of the importance of genes for global cellular functions based on both link count and the clique membership count. PMID:15268775

  20. Additions to Mars Global Reference Atmospheric Model (Mars-GRAM)

    NASA Technical Reports Server (NTRS)

    Justus, C. G.

    1991-01-01

    Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification has also been made which allows heights to go below local terrain height and return realistic pressure, density, and temperature (not the surface values) as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local valley areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch version of Mars-GRAM are presented.

  1. Additions to Mars Global Reference Atmospheric Model (MARS-GRAM)

    NASA Technical Reports Server (NTRS)

    Justus, C. G.; James, Bonnie

    1992-01-01

    Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification was also made which allows heights to go 'below' local terrain height and return 'realistic' pressure, density, and temperature, and not the surface values, as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local 'valley' areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch versions of Mars-GRAM are presented.

  2. Comprehensive Neurocognitive Endophenotyping Strategies for Mouse Models of Genetic Disorders

    PubMed Central

    Hunsaker, Michael R.

    2012-01-01

    There is a need for refinement of the current behavioral phenotyping methods for mouse models of genetic disorders. The current approach is to perform a behavioral screen using standardized tasks to define a broad phenotype of the model. This phenotype is then compared to what is known concerning the disorder being modeled. The weakness inherent in this approach is twofold: First, the tasks that make up these standard behavioral screens do not model specific behaviors associated with a given genetic mutation but rather phenotypes affected in various genetic disorders; secondly, these behavioral tasks are insufficiently sensitive to identify subtle phenotypes. An alternate phenotyping strategy is to determine the core behavioral phenotypes of the genetic disorder being studied and develop behavioral tasks to evaluate specific hypotheses concerning the behavioral consequences of the genetic mutation. This approach emphasizes direct comparisons between the mouse and human that facilitate the development of neurobehavioral biomarkers or quantitative outcome measures for studies of genetic disorders across species. PMID:22266125

  3. Understanding Rasch Measurement: The Rasch Model, Additive Conjoint Measurement, and New Models of Probabilistic Measurement Theory.

    ERIC Educational Resources Information Center

    Karabatsos, George

    2001-01-01

    Describes similarities and differences between additive conjoint measurement and the Rasch model, and formalizes some new nonparametric item response models that are, in a sense, probabilistic measurement theory models. Applies these new models to published and simulated data. (SLD)

  4. Backbone additivity in the transfer model of protein solvation

    PubMed Central

    Hu, Char Y; Kokubo, Hironori; Lynch, Gillian C; Bolen, D Wayne; Pettitt, B Montgomery

    2010-01-01

    The transfer model implying additivity of the peptide backbone free energy of transfer is computationally tested. Molecular dynamics simulations are used to determine the extent of change in transfer free energy (ΔGtr) with increase in chain length of oligoglycine with capped end groups. Solvation free energies of oligoglycine models of varying lengths in pure water and in the osmolyte solutions, 2M urea and 2M trimethylamine N-oxide (TMAO), were calculated from simulations of all atom models, and ΔGtr values for peptide backbone transfer from water to the osmolyte solutions were determined. The results show that the transfer free energies change linearly with increasing chain length, demonstrating the principle of additivity, and provide values in reasonable agreement with experiment. The peptide backbone transfer free energy contributions arise from van der Waals interactions in the case of transfer to urea, but from electrostatics on transfer to TMAO solution. The simulations used here allow for the calculation of the solvation and transfer free energy of longer oligoglycine models to be evaluated than is currently possible through experiment. The peptide backbone unit computed transfer free energy of −54 cal/mol/M compares quite favorably with −43 cal/mol/M determined experimentally. PMID:20306490

  5. Backbone Additivity in the Transfer Model of Protein Solvation

    SciTech Connect

    Hu, Char Y.; Kokubo, Hironori; Lynch, Gillian C.; Bolen, D Wayne; Pettitt, Bernard M.

    2010-05-01

    The transfer model implying additivity of the peptide backbone free energy of transfer is computationally tested. Molecular dynamics simulations are used to determine the extent of change in transfer free energy (ΔGtr) with increase in chain length of oligoglycine with capped end groups. Solvation free energies of oligoglycine models of varying lengths in pure water and in the osmolyte solutions, 2M urea and 2M trimethylamine N-oxide (TMAO), were calculated from simulations of all atom models, and ΔGtr values for peptide backbone transfer from water to the osmolyte solutions were determined. The results show that the transfer free energies change linearly with increasing chain length, demonstrating the principle of additivity, and provide values in reasonable agreement with experiment. The peptide backbone transfer free energy contributions arise from van der Waals interactions in the case of transfer to urea, but from electrostatics on transfer to TMAO solution. The simulations used here allow for the calculation of the solvation and transfer free energy of longer oligoglycine models to be evaluated than is currently possible through experiment. The peptide backbone unit computed transfer free energy of –54 cal/mol/Mcompares quite favorably with –43 cal/mol/M determined experimentally.

  6. Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

    NASA Technical Reports Server (NTRS)

    Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar

    2015-01-01

    The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition

  7. A Developmental-Genetic Model of Alcoholism: Implications for Genetic Research.

    ERIC Educational Resources Information Center

    Devor, Eric J.

    1994-01-01

    Research for biological-genetic markers of alcoholism is discussed in context of a multifactorial, heterogeneous, developmental model. Suggested that strategies used in linkage and association studies will require modification. Also suggested several extant associations of genetic markers represent true secondary interactive phenomena that alter…

  8. Genetic and Environmental Bases of Reading and Spelling: A Unified Genetic Dual Route Model

    ERIC Educational Resources Information Center

    Bates, Timothy C.; Castles, Anne; Luciano, Michelle; Wright, Margaret J.; Coltheart, Max; Martin, Nicholas G.

    2007-01-01

    We develop and test a dual-route model of genetic effects on reading aloud and spelling, based on irregular and non-word reading and spelling performance assessed in 1382 monozygotic and dizygotic twins. As in earlier research, most of the variance in reading was due to genetic effects. However, there were three more specific conclusions: the…

  9. Addition Table of Colours: Additive and Subtractive Mixtures Described Using a Single Reasoning Model

    ERIC Educational Resources Information Center

    Mota, A. R.; Lopes dos Santos, J. M. B.

    2014-01-01

    Students' misconceptions concerning colour phenomena and the apparent complexity of the underlying concepts--due to the different domains of knowledge involved--make its teaching very difficult. We have developed and tested a teaching device, the addition table of colours (ATC), that encompasses additive and subtractive mixtures in a single…

  10. Sensitivity analysis of geometric errors in additive manufacturing medical models.

    PubMed

    Pinto, Jose Miguel; Arrieta, Cristobal; Andia, Marcelo E; Uribe, Sergio; Ramos-Grez, Jorge; Vargas, Alex; Irarrazaval, Pablo; Tejos, Cristian

    2015-03-01

    Additive manufacturing (AM) models are used in medical applications for surgical planning, prosthesis design and teaching. For these applications, the accuracy of the AM models is essential. Unfortunately, this accuracy is compromised due to errors introduced by each of the building steps: image acquisition, segmentation, triangulation, printing and infiltration. However, the contribution of each step to the final error remains unclear. We performed a sensitivity analysis comparing errors obtained from a reference with those obtained modifying parameters of each building step. Our analysis considered global indexes to evaluate the overall error, and local indexes to show how this error is distributed along the surface of the AM models. Our results show that the standard building process tends to overestimate the AM models, i.e. models are larger than the original structures. They also show that the triangulation resolution and the segmentation threshold are critical factors, and that the errors are concentrated at regions with high curvatures. Errors could be reduced choosing better triangulation and printing resolutions, but there is an important need for modifying some of the standard building processes, particularly the segmentation algorithms. PMID:25649961

  11. Additive Manufacturing of Medical Models--Applications in Rhinology.

    PubMed

    Raos, Pero; Klapan, Ivica; Galeta, Tomislav

    2015-09-01

    In the paper we are introducing guidelines and suggestions for use of 3D image processing SW in head pathology diagnostic and procedures for obtaining physical medical model by additive manufacturing/rapid prototyping techniques, bearing in mind the improvement of surgery performance, its maximum security and faster postoperative recovery of patients. This approach has been verified in two case reports. In the treatment we used intelligent classifier-schemes for abnormal patterns using computer-based system for 3D-virtual and endoscopic assistance in rhinology, with appropriate visualization of anatomy and pathology within the nose, paranasal sinuses, and scull base area. PMID:26898064

  12. Computer Center: BASIC String Models of Genetic Information Transfer.

    ERIC Educational Resources Information Center

    Spain, James D., Ed.

    1984-01-01

    Discusses some of the major genetic information processes which may be modeled by computer program string manipulation, focusing on replication and transcription. Also discusses instructional applications of using string models. (JN)

  13. Multiscale Modeling of Powder Bed–Based Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Markl, Matthias; Körner, Carolin

    2016-07-01

    Powder bed fusion processes are additive manufacturing technologies that are expected to induce the third industrial revolution. Components are built up layer by layer in a powder bed by selectively melting confined areas, according to sliced 3D model data. This technique allows for manufacturing of highly complex geometries hardly machinable with conventional technologies. However, the underlying physical phenomena are sparsely understood and difficult to observe during processing. Therefore, an intensive and expensive trial-and-error principle is applied to produce components with the desired dimensional accuracy, material characteristics, and mechanical properties. This review presents numerical modeling approaches on multiple length scales and timescales to describe different aspects of powder bed fusion processes. In combination with tailored experiments, the numerical results enlarge the process understanding of the underlying physical mechanisms and support the development of suitable process strategies and component topologies.

  14. Toward Developing Genetic Algorithms to Aid in Critical Infrastructure Modeling

    SciTech Connect

    Not Available

    2007-05-01

    Today’s society relies upon an array of complex national and international infrastructure networks such as transportation, telecommunication, financial and energy. Understanding these interdependencies is necessary in order to protect our critical infrastructure. The Critical Infrastructure Modeling System, CIMS©, examines the interrelationships between infrastructure networks. CIMS© development is sponsored by the National Security Division at the Idaho National Laboratory (INL) in its ongoing mission for providing critical infrastructure protection and preparedness. A genetic algorithm (GA) is an optimization technique based on Darwin’s theory of evolution. A GA can be coupled with CIMS© to search for optimum ways to protect infrastructure assets. This includes identifying optimum assets to enforce or protect, testing the addition of or change to infrastructure before implementation, or finding the optimum response to an emergency for response planning. This paper describes the addition of a GA to infrastructure modeling for infrastructure planning. It first introduces the CIMS© infrastructure modeling software used as the modeling engine to support the GA. Next, the GA techniques and parameters are defined. Then a test scenario illustrates the integration with CIMS© and the preliminary results.

  15. Additive genetic variation for tolerance to estrogen pollution in natural populations of Alpine whitefish (Coregonus sp., Salmonidae)

    PubMed Central

    Brazzola, Gregory; Chèvre, Nathalie; Wedekind, Claus

    2014-01-01

    The evolutionary potential of natural populations to adapt to anthropogenic threats critically depends on whether there exists additive genetic variation for tolerance to the threat. A major problem for water-dwelling organisms is chemical pollution, and among the most common pollutants is 17α-ethinylestradiol (EE2), the synthetic estrogen that is used in oral contraceptives and that can affect fish at various developmental stages, including embryogenesis. We tested whether there is variation in the tolerance to EE2 within Alpine whitefish. We sampled spawners from two species of different lakes, bred them in vitro in a full-factorial design each, and studied growth and mortality of embryos. Exposure to EE2 turned out to be toxic in all concentrations we tested (≥1 ng/L). It reduced embryo viability and slowed down embryogenesis. We found significant additive genetic variation in EE2-induced mortality in both species, that is, genotypes differed in their tolerance to estrogen pollution. We also found maternal effects on embryo development to be influenced by EE2, that is, some maternal sib groups were more susceptible to EE2 than others. In conclusion, the toxic effects of EE2 were strong, but both species demonstrated the kind of additive genetic variation that is necessary for an evolutionary response to this type of pollution. PMID:25553069

  16. Additive genetic variation for tolerance to estrogen pollution in natural populations of Alpine whitefish (Coregonus sp., Salmonidae).

    PubMed

    Brazzola, Gregory; Chèvre, Nathalie; Wedekind, Claus

    2014-11-01

    The evolutionary potential of natural populations to adapt to anthropogenic threats critically depends on whether there exists additive genetic variation for tolerance to the threat. A major problem for water-dwelling organisms is chemical pollution, and among the most common pollutants is 17α-ethinylestradiol (EE2), the synthetic estrogen that is used in oral contraceptives and that can affect fish at various developmental stages, including embryogenesis. We tested whether there is variation in the tolerance to EE2 within Alpine whitefish. We sampled spawners from two species of different lakes, bred them in vitro in a full-factorial design each, and studied growth and mortality of embryos. Exposure to EE2 turned out to be toxic in all concentrations we tested (≥1 ng/L). It reduced embryo viability and slowed down embryogenesis. We found significant additive genetic variation in EE2-induced mortality in both species, that is, genotypes differed in their tolerance to estrogen pollution. We also found maternal effects on embryo development to be influenced by EE2, that is, some maternal sib groups were more susceptible to EE2 than others. In conclusion, the toxic effects of EE2 were strong, but both species demonstrated the kind of additive genetic variation that is necessary for an evolutionary response to this type of pollution. PMID:25553069

  17. [Critical of the additive model of the randomized controlled trial].

    PubMed

    Boussageon, Rémy; Gueyffier, François; Bejan-Angoulvant, Theodora; Felden-Dominiak, Géraldine

    2008-01-01

    Randomized, double-blind, placebo-controlled clinical trials are currently the best way to demonstrate the clinical effectiveness of drugs. Its methodology relies on the method of difference (John Stuart Mill), through which the observed difference between two groups (drug vs placebo) can be attributed to the pharmacological effect of the drug being tested. However, this additive model can be questioned in the event of statistical interactions between the pharmacological and the placebo effects. Evidence in different domains has shown that the placebo effect can influence the effect of the active principle. This article evaluates the methodological, clinical and epistemological consequences of this phenomenon. Topics treated include extrapolating results, accounting for heterogeneous results, demonstrating the existence of several factors in the placebo effect, the necessity to take these factors into account for given symptoms or pathologies, as well as the problem of the "specific" effect. PMID:18387273

  18. Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle

    PubMed Central

    Canaza-Cayo, Ali William; Lopes, Paulo Sávio; da Silva, Marcos Vinicius Gualberto Barbosa; de Almeida Torres, Robledo; Martins, Marta Fonseca; Arbex, Wagner Antonio; Cobuci, Jaime Araujo

    2015-01-01

    A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre’s polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used indicated RRM employing the Legendre’s polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from −0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from −0.98 to 1.00, respectively. The use of PS7 would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits. PMID:26323397

  19. Developing robotic behavior using a genetic programming model

    SciTech Connect

    Pryor, R.J.

    1998-01-01

    This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle`s on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study.

  20. Calculation of exact p-values when SNPs are tested using multiple genetic models

    PubMed Central

    2014-01-01

    Background Several methods have been proposed to account for multiple comparisons in genetic association studies. However, investigators typically test each of the SNPs using multiple genetic models. Association testing using the Cochran-Armitage test for trend assuming an additive, dominant, or recessive genetic model, is commonly performed. Thus, each SNP is tested three times. Some investigators report the smallest p-value obtained from the three tests corresponding to the three genetic models, but such an approach inherently leads to inflated type 1 errors. Because of the small number of tests (three) and high correlation (functional dependence) among these tests, the procedures available for accounting for multiple tests are either too conservative or fail to meet the underlying assumptions (e.g., asymptotic multivariate normality or independence among the tests). Results We propose a method to calculate the exact p-value for each SNP using different genetic models. We performed simulations, which demonstrated the control of type 1 error and power gains using the proposed approach. We applied the proposed method to compute p-value for a polymorphism eNOS -786T>C which was shown to be associated with breast cancer risk. Conclusions Our findings indicate that the proposed method should be used to maximize power and control type 1 errors when analyzing genetic data using additive, dominant, and recessive models. PMID:24950707

  1. Genetically Engineered Mouse Models for Studying Inflammatory Bowel Disease

    PubMed Central

    Mizoguchi, Atsushi; Takeuchi, Takahito; Himuro, Hidetomo; Okada, Toshiyuki; Mizoguchi, Emiko

    2015-01-01

    Inflammatory bowel disease (IBD) is a chronic intestinal inflammatory condition that is mediated by very complex mechanisms controlled by genetic, immune, and environmental factors. More than 74 kinds of genetically engineered mouse strains have been established since 1993 for studying IBD. Although mouse models cannot fully reflect human IBD, they have provided significant contributions for not only understanding the mechanism, but also developing new therapeutic means for IBD. Indeed, 20 kinds of genetically engineered mouse models carry the susceptibility genes identified in human IBD, and the functions of some other IBD susceptibility genes have also been dissected out using mouse models. Cutting-edge technologies such as cell-specific and inducible knockout systems, which were recently employed to mouse IBD models, have further enhanced the ability of investigators to provide important and unexpected rationales for developing new therapeutic strategies for IBD. In this review article, we briefly introduce 74 kinds of genetically engineered mouse models that spontaneously develop intestinal inflammation. PMID:26387641

  2. Genetic and Epigenetic Changes in Oilseed Rape (Brassica napus L.) Extracted from Intergeneric Allopolyploid and Additions with Orychophragmus.

    PubMed

    Gautam, Mayank; Dang, Yanwei; Ge, Xianhong; Shao, Yujiao; Li, Zaiyun

    2016-01-01

    Allopolyploidization with the merger of the genomes from different species has been shown to be associated with genetic and epigenetic changes. But the maintenance of such alterations related to one parental species after the genome is extracted from the allopolyploid remains to be detected. In this study, the genome of Brassica napus L. (2n = 38, genomes AACC) was extracted from its intergeneric allohexaploid (2n = 62, genomes AACCOO) with another crucifer Orychophragmus violaceus (2n = 24, genome OO), by backcrossing and development of alien addition lines. B. napus-type plants identified in the self-pollinated progenies of nine monosomic additions were analyzed by the methods of amplified fragment length polymorphism, sequence-specific amplified polymorphism, and methylation-sensitive amplified polymorphism. They showed modifications to certain extents in genomic components (loss and gain of DNA segments and transposons, introgression of alien DNA segments) and DNA methylation, compared with B. napus donor. The significant differences in the changes between the B. napus types extracted from these additions likely resulted from the different effects of individual alien chromosomes. Particularly, the additions which harbored the O. violaceus chromosome carrying dominant rRNA genes over those of B. napus tended to result in the development of plants which showed fewer changes, suggesting a role of the expression levels of alien rRNA genes in genomic stability. These results provided new cues for the genetic alterations in one parental genome that are maintained even after the genome becomes independent. PMID:27148282

  3. Genetic and Epigenetic Changes in Oilseed Rape (Brassica napus L.) Extracted from Intergeneric Allopolyploid and Additions with Orychophragmus

    PubMed Central

    Gautam, Mayank; Dang, Yanwei; Ge, Xianhong; Shao, Yujiao; Li, Zaiyun

    2016-01-01

    Allopolyploidization with the merger of the genomes from different species has been shown to be associated with genetic and epigenetic changes. But the maintenance of such alterations related to one parental species after the genome is extracted from the allopolyploid remains to be detected. In this study, the genome of Brassica napus L. (2n = 38, genomes AACC) was extracted from its intergeneric allohexaploid (2n = 62, genomes AACCOO) with another crucifer Orychophragmus violaceus (2n = 24, genome OO), by backcrossing and development of alien addition lines. B. napus-type plants identified in the self-pollinated progenies of nine monosomic additions were analyzed by the methods of amplified fragment length polymorphism, sequence-specific amplified polymorphism, and methylation-sensitive amplified polymorphism. They showed modifications to certain extents in genomic components (loss and gain of DNA segments and transposons, introgression of alien DNA segments) and DNA methylation, compared with B. napus donor. The significant differences in the changes between the B. napus types extracted from these additions likely resulted from the different effects of individual alien chromosomes. Particularly, the additions which harbored the O. violaceus chromosome carrying dominant rRNA genes over those of B. napus tended to result in the development of plants which showed fewer changes, suggesting a role of the expression levels of alien rRNA genes in genomic stability. These results provided new cues for the genetic alterations in one parental genome that are maintained even after the genome becomes independent. PMID:27148282

  4. Complete nucleotide sequence of a Spanish isolate of alfalfa mosaic virus: evidence for additional genetic variability.

    PubMed

    Parrella, Giuseppe; Acanfora, Nadia; Orílio, Anelise F; Navas-Castillo, Jesús

    2011-06-01

    Alfalfa mosaic virus (AMV) is a plant virus that is distributed worldwide and can induce necrosis and/or yellow mosaic on a large variety of plant species, including commercially important crops. It is the only virus of the genus Alfamovirus in the family Bromoviridae. AMV isolates can be clustered into two genetic groups that correlate with their geographic origin. Here, we report for the first time the complete nucleotide sequence of a Spanish isolate of AMV found infecting Cape honeysuckle (Tecoma capensis) and named Tec-1. The tripartite genome of Tec-1 is composed of 3643 nucleotides (nt) for RNA1, 2594 nt for RNA2 and 2037 nt for RNA3. Comparative sequence analysis of the coat protein gene revealed that the isolate Tec-1 is distantly related to subgroup I of AMV and more closely related to subgroup II, although forming a distinct phylogenetic clade. Therefore, we propose to split subgroup II of AMV into two subgroups, namely IIA, comprising isolates previously included in subgroup II, and IIB, including the novel Spanish isolate Tec-1. PMID:21327783

  5. Additional records of metazoan parasites from Caribbean marine mammals, including genetically identified anisakid nematodes.

    PubMed

    Colón-Llavina, Marlene M; Mignucci-Giannoni, Antonio A; Mattiucci, Simonetta; Paoletti, Michela; Nascetti, Giuseppe; Williams, Ernest H

    2009-10-01

    Studies of marine mammal parasites in the Caribbean are scarce. An assessment for marine mammal endo- and ectoparasites from Puerto Rico and the Virgin Islands, but extending to other areas of the Caribbean, was conducted between 1989 and 1994. The present study complements the latter and enhances identification of anisakid nematodes using molecular markers. Parasites were collected from 59 carcasses of stranded cetaceans and manatees from 1994 to 2006, including Globicephala macrorhynchus, Kogia breviceps, Kogia sima, Lagenodelphis hosei, Mesoplodon densirostris, Peponocephala electra, Stenella longirostris, Steno bredanensis, Trichechus manatus. Tursiops truncatus, and Ziphius cavirostris. Sixteen species of endoparasitic helminthes were morphologically identified, including two species of acanthocephalans (Bolbosoma capitatum, Bolbosoma vasculosum), nine species of nematodes (Anisakis sp., Anisakis brevispiculata, Anisakis paggiae, Anisakis simplex, Anisakis typica, Anisakis ziphidarium, Crassicauda anthonyi, Heterocheilus tunicatus, Pseudoterranova ceticola), two species of cestodes (Monorygma grimaldi, Phyllobothrium delphini), and three species of trematodes (Chiorchis groschafti, Pulmonicola cochleotrema, Monoligerum blairi). The nematodes belonging to the genus Anisakis recovered in some stranded animals were genetically identified to species level based on their sequence analysis of mitochondrial DNA (629 bp of mtDNA cox 2). A total of five new host records and six new geographic records are presented. PMID:19582477

  6. A Genetic Model of Substrate Reduction Therapy for Mucopolysaccharidosis*

    PubMed Central

    Lamanna, William C.; Lawrence, Roger; Sarrazin, Stéphane; Lameda-Diaz, Carlos; Gordts, Philip L. S. M.; Moremen, Kelley W.; Esko, Jeffrey D.

    2012-01-01

    Inherited defects in the ability to catabolize glycosaminoglycans result in lysosomal storage disorders known as mucopolysaccharidoses (MPS), causing severe pathology, particularly in the brain. Enzyme replacement therapy has been used to treat mucopolysaccharidoses; however, neuropathology has remained refractory to this approach. To test directly whether substrate reduction might be feasible for treating MPS disease, we developed a genetic model for substrate reduction therapy by crossing MPS IIIa mice with animals partially deficient in heparan sulfate biosynthesis due to heterozygosity in Ext1 and Ext2, genes that encode the copolymerase required for heparan sulfate chain assembly. Reduction of heparan sulfate by 30–50% using this genetic strategy ameliorated the amount of disease-specific biomarker and pathology in multiple tissues, including the brain. In addition, we were able to demonstrate that substrate reduction therapy can improve the efficacy of enzyme replacement therapy in cell culture and in mice. These results provide proof of principle that targeted inhibition of heparan sulfate biosynthetic enzymes together with enzyme replacement might prove beneficial for treating mucopolysaccharidoses. PMID:22952226

  7. Genetic drift in an infinite population. The pseudohitchhiking model.

    PubMed Central

    Gillespie, J H

    2000-01-01

    Selected substitutions at one locus can induce stochastic dynamics that resemble genetic drift at a closely linked neutral locus. The pseudohitchhiking model is a one-locus model that approximates these effects and can be used to describe the major consequences of linked selection. As the changes in neutral allele frequencies when hitchhiking are rapid, diffusion theory is not appropriate for studying neutral dynamics. A stationary distribution and some results on substitution processes are presented that use the theory of continuous-time Markov processes with discontinuous sample paths. The coalescent of the pseudohitchhiking model is shown to have a random number of branches at each node, which leads to a frequency spectrum that is different from that of the equilibrium neutral model. If genetic draft, the name given to these induced stochastic effects, is a more important stochastic force than genetic drift, then a number of paradoxes that have plagued population genetics disappear. PMID:10835409

  8. Multiple Comparisons in Genetic Association Studies: A Hierarchical Modeling Approach

    PubMed Central

    Yi, Nengjun; Xu, Shizhong; Lou, Xiang-Yang; Mallick, Himel

    2016-01-01

    Multiple comparisons or multiple testing has been viewed as a thorny issue in genetic association studies aiming to detect disease-associated genetic variants from a large number of genotyped variants. We alleviate the problem of multiple comparisons by proposing a hierarchical modeling approach that is fundamentally different from the existing methods. The proposed hierarchical models simultaneously fit as many variables as possible and shrink unimportant effects towards zero. Thus, the hierarchical models yield more efficient estimates of parameters than the traditional methods that analyze genetic variants separately, and also coherently address the multiple comparisons problem due to largely reducing the effective number of genetic effects and the number of statistically ‘significant’ effects. We develop a method for computing the effective number of genetic effects in hierarchical generalized linear models, and propose a new adjustment for multiple comparisons, the hierarchical Bonferroni correction, based on the effective number of genetic effects. Our approach not only increases the power to detect disease-associated variants but also controls the Type I error. We illustrate and evaluate our method with real and simulated data sets from genetic association studies. The method has been implemented in our freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). PMID:24259248

  9. Behavioral phenotypes of genetic mouse models of autism

    PubMed Central

    Kazdoba, T. M.; Leach, P. T.; Crawley, J. N.

    2016-01-01

    More than a hundred de novo single gene mutations and copy-number variants have been implicated in autism, each occurring in a small subset of cases. Mutant mouse models with syntenic mutations offer research tools to gain an understanding of the role of each gene in modulating biological and behavioral phenotypes relevant to autism. Knockout, knockin and transgenic mice incorporating risk gene mutations detected in autism spectrum disorder and comorbid neurodevelopmental disorders are now widely available. At present, autism spectrum disorder is diagnosed solely by behavioral criteria. We developed a constellation of mouse behavioral assays designed to maximize face validity to the types of social deficits and repetitive behaviors that are central to an autism diagnosis. Mouse behavioral assays for associated symptoms of autism, which include cognitive inflexibility, anxiety, hyperactivity, and unusual reactivity to sensory stimuli, are frequently included in the phenotypic analyses. Over the past 10 years, we and many other laboratories around the world have employed these and additional behavioral tests to phenotype a large number of mutant mouse models of autism. In this review, we highlight mouse models with mutations in genes that have been identified as risk genes for autism, which work through synaptic mechanisms and through the mTOR signaling pathway. Robust, replicated autism-relevant behavioral outcomes in a genetic mouse model lend credence to a causal role for specific gene contributions and downstream biological mechanisms in the etiology of autism. PMID:26403076

  10. Replication of a Gene-Environment Interaction via Multimodel Inference: Additive-Genetic Variance in Adolescents’ General Cognitive Ability Increases with Family-of-Origin Socioeconomic Status

    PubMed Central

    Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.

    2015-01-01

    The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

  11. Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

    PubMed

    Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

    2015-03-01

    The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

  12. Models to explore genetics of human aging.

    PubMed

    Karasik, David; Newman, Anne

    2015-01-01

    Genetic studies have bestowed insight into the biological mechanisms underlying inter-individual differences in susceptibility to (or resistance to) organisms’ aging. Recent advances in molecular and genetic epidemiology provide tools to explore the genetic sources of the variability in biological aging in humans. To be successful, the genetic study of a complex condition such as aging requires the clear definition of essential traits that can characterize the aging process phenotypically. Phenotypes of human aging have long relied on mortality rate or exceptional longevity. Genome-wide association studies (GWAS) have been shown to present an unbiased approach to the identification of new candidate genes for human diseases. The GWAS approach can also be used for positive health phenotypes such as longevity or a delay in age-related chronic disease, as well as for other age related changes such as loss of telomere length or lens transparency. Sequencing, either in targeted regions or across the whole genome can further identify rare variation that may contribute to the biological aging mechanisms. To date, the results of the GWAS for longevity are rather disappointing, possibly in part due to the small number of individuals with GWAS data who have reached advanced old age.Human aging phenotypes are needed that can be assessed prior to death, and should be both heritable and validated as predictors of longevity. Potentially, phenotypes that focus on “successful” or “healthy” aging will be more powerful as they can be measured in large numbers of people and also are clinically relevant.We postulate that construction of an integrated phenotype of aging can be achieved capitalizing on multiple traits that may have weak correlations, but a shared underlying genetic architecture. This is based on a hypothesis that convergent results from multiple individual aging-related traits will point out the pleiotropic signals responsible for the overall rate of aging of

  13. How Pupils Use a Model for Abstract Concepts in Genetics

    ERIC Educational Resources Information Center

    Venville, Grady; Donovan, Jenny

    2008-01-01

    The purpose of this research was to explore the way pupils of different age groups use a model to understand abstract concepts in genetics. Pupils from early childhood to late adolescence were taught about genes and DNA using an analogical model (the wool model) during their regular biology classes. Changing conceptual understandings of the…

  14. Percolation model with an additional source of disorder.

    PubMed

    Kundu, Sumanta; Manna, S S

    2016-06-01

    The ranges of transmission of the mobiles in a mobile ad hoc network are not uniform in reality. They are affected by the temperature fluctuation in air, obstruction due to the solid objects, even the humidity difference in the environment, etc. How the varying range of transmission of the individual active elements affects the global connectivity in the network may be an important practical question to ask. Here a model of percolation phenomena, with an additional source of disorder, is introduced for a theoretical understanding of this problem. As in ordinary percolation, sites of a square lattice are occupied randomly with probability p. Each occupied site is then assigned a circular disk of random value R for its radius. A bond is defined to be occupied if and only if the radii R_{1} and R_{2} of the disks centered at the ends satisfy a certain predefined condition. In a very general formulation, one divides the R_{1}-R_{2} plane into two regions by an arbitrary closed curve. One defines a point within one region as representing an occupied bond; otherwise it is a vacant bond. The study of three different rules under this general formulation indicates that the percolation threshold always varies continuously. This threshold has two limiting values, one is p_{c}(sq), the percolation threshold for the ordinary site percolation on the square lattice, and the other is unity. The approach of the percolation threshold to its limiting values are characterized by two exponents. In a special case, all lattice sites are occupied by disks of random radii R∈{0,R_{0}} and a percolation transition is observed with R_{0} as the control variable, similar to the site occupation probability. PMID:27415234

  15. Percolation model with an additional source of disorder

    NASA Astrophysics Data System (ADS)

    Kundu, Sumanta; Manna, S. S.

    2016-06-01

    The ranges of transmission of the mobiles in a mobile ad hoc network are not uniform in reality. They are affected by the temperature fluctuation in air, obstruction due to the solid objects, even the humidity difference in the environment, etc. How the varying range of transmission of the individual active elements affects the global connectivity in the network may be an important practical question to ask. Here a model of percolation phenomena, with an additional source of disorder, is introduced for a theoretical understanding of this problem. As in ordinary percolation, sites of a square lattice are occupied randomly with probability p . Each occupied site is then assigned a circular disk of random value R for its radius. A bond is defined to be occupied if and only if the radii R1 and R2 of the disks centered at the ends satisfy a certain predefined condition. In a very general formulation, one divides the R1-R2 plane into two regions by an arbitrary closed curve. One defines a point within one region as representing an occupied bond; otherwise it is a vacant bond. The study of three different rules under this general formulation indicates that the percolation threshold always varies continuously. This threshold has two limiting values, one is pc(sq) , the percolation threshold for the ordinary site percolation on the square lattice, and the other is unity. The approach of the percolation threshold to its limiting values are characterized by two exponents. In a special case, all lattice sites are occupied by disks of random radii R ∈{0 ,R0} and a percolation transition is observed with R0 as the control variable, similar to the site occupation probability.

  16. Tetrahymena as a Unicellular Model Eukaryote: Genetic and Genomic Tools.

    PubMed

    Ruehle, Marisa D; Orias, Eduardo; Pearson, Chad G

    2016-06-01

    Tetrahymena thermophila is a ciliate model organism whose study has led to important discoveries and insights into both conserved and divergent biological processes. In this review, we describe the tools for the use of Tetrahymena as a model eukaryote, including an overview of its life cycle, orientation to its evolutionary roots, and methodological approaches to forward and reverse genetics. Recent genomic tools have expanded Tetrahymena's utility as a genetic model system. With the unique advantages that Tetrahymena provide, we argue that it will continue to be a model organism of choice. PMID:27270699

  17. Genetic algorithms for modelling and optimisation

    NASA Astrophysics Data System (ADS)

    McCall, John

    2005-12-01

    Genetic algorithms (GAs) are a heuristic search and optimisation technique inspired by natural evolution. They have been successfully applied to a wide range of real-world problems of significant complexity. This paper is intended as an introduction to GAs aimed at immunologists and mathematicians interested in immunology. We describe how to construct a GA and the main strands of GA theory before speculatively identifying possible applications of GAs to the study of immunology. An illustrative example of using a GA for a medical optimal control problem is provided. The paper also includes a brief account of the related area of artificial immune systems.

  18. Generalized population models and the nature of genetic drift.

    PubMed

    Der, Ricky; Epstein, Charles L; Plotkin, Joshua B

    2011-09-01

    The Wright-Fisher model of allele dynamics forms the basis for most theoretical and applied research in population genetics. Our understanding of genetic drift, and its role in suppressing the deterministic forces of Darwinian selection has relied on the specific form of sampling inherent to the Wright-Fisher model and its diffusion limit. Here we introduce and analyze a broad class of forward-time population models that share the same mean and variance as the Wright-Fisher model, but may otherwise differ. The proposed class unifies and further generalizes a number of population-genetic processes of recent interest, including the Λ and Cannings processes. Even though these models all have the same variance effective population size, they encode a rich diversity of alternative forms of genetic drift, with significant consequences for allele dynamics. We characterize in detail the behavior of standard population-genetic quantities across this family of generalized models. Some quantities, such as heterozygosity, remain unchanged; but others, such as neutral absorption times and fixation probabilities under selection, deviate by orders of magnitude from the Wright-Fisher model. We show that generalized population models can produce startling phenomena that differ qualitatively from classical behavior - such as assured fixation of a new mutant despite the presence of genetic drift. We derive the forward-time continuum limits of the generalized processes, analogous to Kimura's diffusion limit of the Wright-Fisher process, and we discuss their relationships to the Kingman and non-Kingman coalescents. Finally, we demonstrate that some non-diffusive, generalized models are more likely, in certain respects, than the Wright-Fisher model itself, given empirical data from Drosophila populations. PMID:21718713

  19. Testing Departure from Additivity in Tukey’s Model using Shrinkage: Application to a Longitudinal Setting

    PubMed Central

    Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A.; Park, Sung Kyun; Kardia, Sharon L.R.; Allison, Matthew A.; Vokonas, Pantel S.; Chen, Jinbo; Diez-Roux, Ana V.

    2014-01-01

    While there has been extensive research developing gene-environment interaction (GEI) methods in case-control studies, little attention has been given to sparse and efficient modeling of GEI in longitudinal studies. In a two-way table for GEI with rows and columns as categorical variables, a conventional saturated interaction model involves estimation of a specific parameter for each cell, with constraints ensuring identifiability. The estimates are unbiased but are potentially inefficient because the number of parameters to be estimated can grow quickly with increasing categories of row/column factors. On the other hand, Tukey’s one degree of freedom (df) model for non-additivity treats the interaction term as a scaled product of row and column main effects. Due to the parsimonious form of interaction, the interaction estimate leads to enhanced efficiency and the corresponding test could lead to increased power. Unfortunately, Tukey’s model gives biased estimates and low power if the model is misspecified. When screening multiple GEIs where each genetic and environmental marker may exhibit a distinct interaction pattern, a robust estimator for interaction is important for GEI detection. We propose a shrinkage estimator for interaction effects that combines estimates from both Tukey’s and saturated interaction models and use the corresponding Wald test for testing interaction in a longitudinal setting. The proposed estimator is robust to misspecification of interaction structure. We illustrate the proposed methods using two longitudinal studies — the Normative Aging Study and the Multi-Ethnic Study of Atherosclerosis. PMID:25112650

  20. The Ising Model in Physics and Statistical Genetics

    PubMed Central

    Majewski, Jacek; Li, Hao; Ott, Jurg

    2001-01-01

    Interdisciplinary communication is becoming a crucial component of the present scientific environment. Theoretical models developed in diverse disciplines often may be successfully employed in solving seemingly unrelated problems that can be reduced to similar mathematical formulation. The Ising model has been proposed in statistical physics as a simplified model for analysis of magnetic interactions and structures of ferromagnetic substances. Here, we present an application of the one-dimensional, linear Ising model to affected-sib-pair (ASP) analysis in genetics. By analyzing simulated genetics data, we show that the simplified Ising model with only nearest-neighbor interactions between genetic markers has statistical properties comparable to much more complex algorithms from genetics analysis, such as those implemented in the Allegro and Mapmaker-Sibs programs. We also adapt the model to include epistatic interactions and to demonstrate its usefulness in detecting modifier loci with weak individual genetic contributions. A reanalysis of data on type 1 diabetes detects several susceptibility loci not previously found by other methods of analysis. PMID:11517425

  1. Population genetics of Setaria viridis, a new model system.

    PubMed

    Huang, Pu; Feldman, Maximilian; Schroder, Stephan; Bahri, Bochra A; Diao, Xianmin; Zhi, Hui; Estep, Matt; Baxter, Ivan; Devos, Katrien M; Kellogg, Elizabeth A

    2014-10-01

    An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new model system for C4 grasses and bioenergy crops, due to its rapid life cycle, large amount of seed production and small diploid genome, among other characters. However, remarkably little is known about the genetic diversity in natural populations of this species. In this study, we survey the genetic diversity of a worldwide sample of more than 200 S. viridis accessions, using the genotyping-by-sequencing technique. Two distinct genetic groups in S. viridis and a third group resembling S. italica were identified, with considerable admixture among the three groups. We find the genetic variation of North American S. viridis correlates with both geography and climate and is representative of the total genetic diversity in this species. This pattern may reflect several introduction/dispersal events of S. viridis into North America. We also modelled demographic history and show signal of recent population decline in one subgroup. Finally, we show linkage disequilibrium decay is rapid (<45 kb) in our total sample and slow in genetic subgroups. These results together provide an in-depth understanding of the pattern of genetic diversity of this new model species on a broad geographic scale. They also provide key guidelines for on-going and future work including germplasm preservation, local adaptation, crossing designs and genomewide association studies. PMID:25185718

  2. Multi-locus models of genetic risk of disease

    PubMed Central

    2010-01-01

    Background Evidence for genetic contribution to complex diseases is described by recurrence risks to relatives of diseased individuals. Genome-wide association studies allow a description of the genetics of the same diseases in terms of risk loci, their effects and allele frequencies. To reconcile the two descriptions requires a model of how risks from individual loci combine to determine an individual's overall risk. Methods We derive predictions of risk to relatives from risks at individual loci under a number of models and compare them with published data on disease risk. Results The model in which risks are multiplicative on the risk scale implies equality between the recurrence risk to monozygotic twins and the square of the recurrence risk to sibs, a relationship often not observed, especially for low prevalence diseases. We show that this theoretical equality is achieved by allowing impossible probabilities of disease. Other models, in which probabilities of disease are constrained to a maximum of one, generate results more consistent with empirical estimates for a range of diseases. Conclusions The unconstrained multiplicative model, often used in theoretical studies because of its mathematical tractability, is not a realistic model. We find three models, the constrained multiplicative, Odds (or Logit) and Probit (or liability threshold) models, all fit the data on risk to relatives. Currently, in practice it would be difficult to differentiate between these models, but this may become possible if genetic variants that explain the majority of the genetic variance are identified. PMID:20181060

  3. Genetics

    MedlinePlus

    Homozygous; 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 ...

  4. Genetics

    MedlinePlus

    ... 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 ...

  5. 'NEANTHES ARENACEODENTATA', A CYTOGENETIC MODEL FOR MARINE GENETIC TOXICOLOGY

    EPA Science Inventory

    Genetic toxicants are present in polluted marine environments and may represent a long-term threat to populations of marine organisms. A cytogenetic model is useful to study the effects of these toxicants. The polychaeta, Neanthes arenaceodentata, was chosen as such a model becau...

  6. Practical implications for genetic modeling in the genomics era

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, incl...

  7. Using Generalized Additive Models to Analyze Single-Case Designs

    ERIC Educational Resources Information Center

    Shadish, William; Sullivan, Kristynn

    2013-01-01

    Many analyses for single-case designs (SCDs)--including nearly all the effect size indicators-- currently assume no trend in the data. Regression and multilevel models allow for trend, but usually test only linear trend and have no principled way of knowing if higher order trends should be represented in the model. This paper shows how Generalized…

  8. Evolution of the additive genetic variance-covariance matrix under continuous directional selection on a complex behavioural phenotype.

    PubMed

    Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

    2015-11-22

    Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance-covariance matrix ( G: ). Yet knowledge of G: in a population experiencing new or altered selection is not sufficient to predict selection response because G: itself evolves in ways that are poorly understood. We experimentally evaluated changes in G: when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G: induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G: induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G: and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. PMID:26582016

  9. Selection for increased desiccation resistance in Drosophila melanogaster: Additive genetic control and correlated responses for other stresses

    SciTech Connect

    Hoffmann, A.A.; Parsons, P.A. )

    1989-08-01

    Previously we found that Drosophila melanogaster lines selected for increased desiccation resistance have lowered metabolic rate and behavioral activity levels, and show correlated responses for resistance to starvation and a toxic ethanol level. These results were consistent with a prediction that increased resistance to many environmental stresses may be genetically correlated because of a reduction in metabolic energy expenditure. Here we present experiments on the genetic basis of the selection response and extend the study of correlated responses to other stresses. The response to selection was not sex-specific and involved X-linked and autosomal genes acting additively. Activity differences contributed little to differences in desiccation resistance between selected and control lines. Selected lines had lower metabolic rates than controls in darkness when activity was inhibited. Adults from selected lines showed increased resistance to a heat shock, {sup 60}Co-gamma-radiation, and acute ethanol and acetic acid stress. The desiccation, ethanol and starvation resistance of isofemale lines set up from the F2s of a cross between one of the selected and one of the control lines were correlated. Selected and control lines did not differ in ether-extractable lipid content or in resistance to acetone, ether or a cold shock.

  10. A model for monitoring of Hsp90-buffered genetic variations

    NASA Astrophysics Data System (ADS)

    Kozeko, Liudmyla

    Genetic material of terrestrial organisms can be considerably injured by cosmic rays and UV-radiation in the space environment. Organisms onboard are also exposed to the entire complex of negative physical factors which can generate genetic variations and affect morphogenesis. However, species phenotypes must be robust to genetic variation, requiring "buffering" systems to ensure normal development. The molecular chaperone Hsp90 can serve as such "a buffer". It is important in the maturation and conformational regulation of a diverse set of signal transducers. The requirement of many principal regulatory proteins for Hsp90 renders entire metabolic pathways sensitive to impairment of its function. So inhibition of Hsp90 function can open cryptic genetic variations and produce morphological changes. In this paper, we present a model for monitoring of cryptic Hsp90-buffered genetic variations arising during exposure to space and spaceflight factors. This model has been developed with Arabidopsis thaliana seeds gathered in natural habitats with high anthropogenic pressure and wild type (Col-0) seeds subjected to negative influences (UV, heavy metals) experimentally. The phenotypic traits of early seedlings grown under reduction of Hsp90 activity were characterized to estimate Hsp90-buffered genetic variations. Geldanamycin was used as an inhibitor of Hsp90 function.

  11. How much additional model complexity do the use of catchment hydrological signatures, additional data and expert knowledge warrant?

    NASA Astrophysics Data System (ADS)

    Hrachowitz, M.; Fovet, O.; RUIZ, L.; Gascuel-odoux, C.; Savenije, H.

    2013-12-01

    In the frequent absence of sufficient suitable data to constrain hydrological models, it is not uncommon to represent catchments at a range of scales by lumped model set-ups. Although process heterogeneity can average out on the catchment scale to generate simple catchment integrated responses whose general flow features can frequently be reproduced by lumped models, these models often fail to get details of the flow pattern as well as catchment internal dynamics, such as groundwater level changes, right to a sufficient degree, resulting in considerable predictive uncertainty. Traditionally, models are constrained by only one or two objectives functions, which does not warrant more than a handful of parameters to avoid elevated predictive uncertainty, thereby preventing more complex model set-ups accounting for increased process heterogeneity. In this study it was tested how much additional process heterogeneity is warranted in models when optimizing the model calibration strategy, using additional data and expert knowledge. Long-term timeseries of flow and groundwater levels for small nested experimental catchments in French Brittany with considerable differences in geology, topography and flow regime were used in this study to test which degree of model process heterogeneity is warranted with increased availability of information. In a first step, as a benchmark, the system was treated as one lumped entity and the model was trained based only on its ability to reproduce the hydrograph. Although it was found that the overall modelled flow generally reflects the observed flow response quite well, the internal system dynamics could not be reproduced. In further steps the complexity of this model was gradually increased, first by adding a separate riparian reservoir to the lumped set-up and then by a semi-distributed set-up, allowing for independent, parallel model structures, representing the contrasting nested catchments. Although calibration performance increased

  12. Additive Manufacturing of Anatomical Models from Computed Tomography Scan Data.

    PubMed

    Gür, Y

    2014-12-01

    The purpose of the study presented here was to investigate the manufacturability of human anatomical models from Computed Tomography (CT) scan data via a 3D desktop printer which uses fused deposition modelling (FDM) technology. First, Digital Imaging and Communications in Medicine (DICOM) CT scan data were converted to 3D Standard Triangle Language (STL) format by using In Vaselius digital imaging program. Once this STL file is obtained, a 3D physical version of the anatomical model can be fabricated by a desktop 3D FDM printer. As a case study, a patient's skull CT scan data was considered, and a tangible version of the skull was manufactured by a 3D FDM desktop printer. During the 3D printing process, the skull was built using acrylonitrile-butadiene-styrene (ABS) co-polymer plastic. The printed model showed that the 3D FDM printing technology is able to fabricate anatomical models with high accuracy. As a result, the skull model can be used for preoperative surgical planning, medical training activities, implant design and simulation to show the potential of the FDM technology in medical field. It will also improve communication between medical stuff and patients. Current result indicates that a 3D desktop printer which uses FDM technology can be used to obtain accurate anatomical models. PMID:26336695

  13. Genetic Animal Models of Parkinson’s Disease

    PubMed Central

    Dawson, Ted M.; Ko, Han Seok; Dawson, Valina L.

    2010-01-01

    Parkinson’s disease (PD) is a progressive neurodegenerative disorder that is characterized by the degeneration of dopamine (DA) and non-DA neurons, the almost uniform presence of Lewy bodies, and motor deficits. Although the majority of PD is sporadic, specific genetic defects in rare familial cases have provided unique insights into the pathogenesis of PD. Through the creation of animal and cellular models of mutations in LRRK2 and α-synuclein, which are linked to autosomal dominant PD, and mutations in parkin, DJ-1, and PINK1, which are responsible for autosomal recessive PD, insight into the molecular mechanisms of this disorder are leading to new ideas about the pathogenesis of PD. In this review, we discuss the animal models for these genetic causes of PD, their limitations and value. Moreover, we discuss future directions and potential strategies for optimization of the genetic models. PMID:20547124

  14. Oxidative Stress in Genetic Mouse Models of Parkinson's Disease

    PubMed Central

    Varçin, Mustafa; Bentea, Eduard; Michotte, Yvette; Sarre, Sophie

    2012-01-01

    There is extensive evidence in Parkinson's disease of a link between oxidative stress and some of the monogenically inherited Parkinson's disease-associated genes. This paper focuses on the importance of this link and potential impact on neuronal function. Basic mechanisms of oxidative stress, the cellular antioxidant machinery, and the main sources of cellular oxidative stress are reviewed. Moreover, attention is given to the complex interaction between oxidative stress and other prominent pathogenic pathways in Parkinson's disease, such as mitochondrial dysfunction and neuroinflammation. Furthermore, an overview of the existing genetic mouse models of Parkinson's disease is given and the evidence of oxidative stress in these models highlighted. Taken into consideration the importance of ageing and environmental factors as a risk for developing Parkinson's disease, gene-environment interactions in genetically engineered mouse models of Parkinson's disease are also discussed, highlighting the role of oxidative damage in the interplay between genetic makeup, environmental stress, and ageing in Parkinson's disease. PMID:22829959

  15. Zebrafish: A Model for the Study of Addiction Genetics

    PubMed Central

    Klee, Eric W; Schneider, Henning; Clark, Karl; Cousin, Margot; Ebbert, Jon; Hooten, Michael; Karpyak, Victor; Warner, David; Ekker, Stephen

    2013-01-01

    Drug abuse and dependence are multifaceted disorders with complex genetic underpinnings. Identifying specific genetic correlates is challenging and may be more readily accomplished by defining endophenotypes specific for addictive disorders. Symptoms and syndromes, including acute drug response, consumption, preference, and withdrawal, are potential endophenotypes characterizing addiction that have been investigated using model organisms. We present a review of major genes involved in serotonergic, dopaminergic, GABAergic, and adrenoreceptor signaling that are considered to be directly involved in nicotine, opioid, cannabinoid, and ethanol use and dependence. The zebrafish genome encodes likely homologs of the vast majority of these loci. We also review the known expression patterns of these genes in zebrafish. The information presented in this review provides support for the use of zebrafish as a viable model for studying genetic factors related to drug addiction. Expansion of investigations into drug response using model organisms holds the potential to advance our understanding of drug response and addiction in humans. PMID:22207143

  16. Modeling the MagnetoencephaloGram (MEG) Of Epileptic Patients Using Genetic Programming and Minimizing the Derived Models Using Genetic Algorithms

    NASA Astrophysics Data System (ADS)

    Theofilatos, Konstantinos; Georgopoulos, Efstratios; Likothanassis, Spiridon

    2009-09-01

    In this paper, a variation of traditional Genetic Programming(GP) is used to model the MagnetoencephaloGram(MEG) of Epileptic Patients. This variation is Linear Genetic Programming(LGP). LGP is a particular subset of GP wherein computer programs in population are represented as a sequence of instructions from imperative programming language or machine language. The derived models from this method were simplified using genetic algorithms. The proposed method was used to model the MEG signal of epileptic patients using 6 different datasets. Each dataset uses different number of previous values of MEG to predict the next value. The models were tested in datasets different from the ones which were used to produce them and the results were very promising.

  17. Model-free Estimation of Recent Genetic Relatedness

    PubMed Central

    Conomos, Matthew P.; Reiner, Alexander P.; Weir, Bruce S.; Thornton, Timothy A.

    2016-01-01

    Genealogical inference from genetic data is essential for a variety of applications in human genetics. In genome-wide and sequencing association studies, for example, accurate inference on both recent genetic relatedness, such as family structure, and more distant genetic relatedness, such as population structure, is necessary for protection against spurious associations. Distinguishing familial relatedness from population structure with genotype data, however, is difficult because both manifest as genetic similarity through the sharing of alleles. Existing approaches for inference on recent genetic relatedness have limitations in the presence of population structure, where they either (1) make strong and simplifying assumptions about population structure, which are often untenable, or (2) require correct specification of and appropriate reference population panels for the ancestries in the sample, which might be unknown or not well defined. Here, we propose PC-Relate, a model-free approach for estimating commonly used measures of recent genetic relatedness, such as kinship coefficients and IBD sharing probabilities, in the presence of unspecified structure. PC-Relate uses principal components calculated from genome-screen data to partition genetic correlations among sampled individuals due to the sharing of recent ancestors and more distant common ancestry into two separate components, without requiring specification of the ancestral populations or reference population panels. In simulation studies with population structure, including admixture, we demonstrate that PC-Relate provides accurate estimates of genetic relatedness and improved relationship classification over widely used approaches. We further demonstrate the utility of PC-Relate in applications to three ancestrally diverse samples that vary in both size and genealogical complexity. PMID:26748516

  18. Ghrelin and eating behavior: evidence and insights from genetically-modified mouse models

    PubMed Central

    Uchida, Aki; Zigman, Jeffrey M.; Perelló, Mario

    2013-01-01

    Ghrelin is an octanoylated peptide hormone, produced by endocrine cells of the stomach, which acts in the brain to increase food intake and body weight. Our understanding of the mechanisms underlying ghrelin's effects on eating behaviors has been greatly improved by the generation and study of several genetically manipulated mouse models. These models include mice overexpressing ghrelin and also mice with genetic deletion of ghrelin, the ghrelin receptor [the growth hormone secretagogue receptor (GHSR)] or the enzyme that post-translationally modifies ghrelin [ghrelin O-acyltransferase (GOAT)]. In addition, a GHSR-null mouse model in which GHSR transcription is globally blocked but can be cell-specifically reactivated in a Cre recombinase-mediated fashion has been generated. Here, we summarize findings obtained with these genetically manipulated mice, with the aim to highlight the significance of the ghrelin system in the regulation of both homeostatic and hedonic eating, including that occurring in the setting of chronic psychosocial stress. PMID:23882175

  19. Addition of Diffusion Model to MELCOR and Comparison with Data

    SciTech Connect

    Brad Merrill; Richard Moore; Chang Oh

    2004-06-01

    A chemical diffusion model was incorporated into the thermal-hydraulics package of the MELCOR Severe Accident code (Reference 1) for analyzing air ingress events for a very high temperature gas-cooled reactor.

  20. Modelling dissimilarity: generalizing ultrametric and additive tree representations.

    PubMed

    Hubert, L; Arabie, P; Meulman, J

    2001-05-01

    Methods for the hierarchical clustering of an object set produce a sequence of nested partitions such that object classes within each successive partition are constructed from the union of object classes present at the previous level. Any such sequence of nested partitions can in turn be characterized by an ultrametric. An approach to generalizing an (ultrametric) representation is proposed in which the nested character of the partition sequence is relaxed and replaced by the weaker requirement that the classes within each partition contain objects consecutive with respect to a fixed ordering of the objects. A method for fitting such a structure to a given proximity matrix is discussed, along with several alternative strategies for graphical representation. Using this same ultrametric extension, additive tree representations can also be generalized by replacing the ultrametric component in the decomposition of an additive tree (into an ultrametric and a centroid metric). A common numerical illustration is developed and maintained throughout the paper. PMID:11393895

  1. The modified ultrasound pattern sum score mUPSS as additional diagnostic tool for genetically distinct hereditary neuropathies.

    PubMed

    Grimm, Alexander; Rasenack, Maria; Athanasopoulou, Ioanna M; Dammeier, Nele Maria; Lipski, Christina; Wolking, Stefan; Vittore, Debora; Décard, Bernhard F; Axer, Hubertus

    2016-02-01

    The objective of this study is to evaluate the nerve ultrasound characteristics in genetically distinct inherited neuropathies, the value of the modified ultrasound pattern sum score (mUPSS) to differentiate between the subtypes and the correlation of ultrasound with nerve conduction studies (NCS), disease duration and severity. All patients underwent a standardized neurological examination, ultrasound, and NCS. In addition, genetic testing was performed. Consequently, mUPSS was applied, which is a sum-score of cross-sectional areas (CSA) at predefined anatomical points in different nerves. 31 patients were included (10xCharcot-Marie-Tooth (CMT)1a, 3xCMT1b, 3xCMTX, 9xCMT2, 6xHNPP [Hereditary neuropathy with liability to pressure palsies]). Generalized, homogeneous nerve enlargement and significantly increased UPS scores emphasized the diagnosis of demyelinating neuropathy, particularly CMT1a and CMT1b. The amount of enlargement did not depend on disease duration, symptom severity, height and weight. In CMTX the nerves were enlarged, as well, however, only in the roots and lower limbs, most prominent in men. In CMT2 no significant enlargement was detectable. In HNPP the CSA values were increased at entrapped sites, and not elsewhere. However, a distinction from CMT1, which also showed enlarged CSA values at entrapment sites, was only possible by calculating the entrapment ratios and entrapment score. The mUPSS allowed distinction between CMT1a (increased UPS scores, entrapment ratios <1.0) and HNPP (low UPS scores, entrapment ratios >1.4), while CMT1b and CMTX showed intermediate UPS types and entrapment ratios <1.0. Although based on few cases, ultrasound revealed consistent and homogeneous nerve alteration in certain inherited neuropathies. The modified UPSS is a quantitative tool, which may provide useful information for diagnosis, differentiation and follow-up evaluation in addition to NCS and molecular testing. PMID:26559821

  2. Additional Research Needs to Support the GENII Biosphere Models

    SciTech Connect

    Napier, Bruce A.; Snyder, Sandra F.; Arimescu, Carmen

    2013-11-30

    In the course of evaluating the current parameter needs for the GENII Version 2 code (Snyder et al. 2013), areas of possible improvement for both the data and the underlying models have been identified. As the data review was implemented, PNNL staff identified areas where the models can be improved both to accommodate the locally significant pathways identified and also to incorporate newer models. The areas are general data needs for the existing models and improved formulations for the pathway models. It is recommended that priorities be set by NRC staff to guide selection of the most useful improvements in a cost-effective manner. Suggestions are made based on relatively easy and inexpensive changes, and longer-term more costly studies. In the short term, there are several improved model formulations that could be applied to the GENII suite of codes to make them more generally useful. • Implementation of the separation of the translocation and weathering processes • Implementation of an improved model for carbon-14 from non-atmospheric sources • Implementation of radon exposure pathways models • Development of a KML processor for the output report generator module data that are calculated on a grid that could be superimposed upon digital maps for easier presentation and display • Implementation of marine mammal models (manatees, seals, walrus, whales, etc.). Data needs in the longer term require extensive (and potentially expensive) research. Before picking any one radionuclide or food type, NRC staff should perform an in-house review of current and anticipated environmental analyses to select “dominant” radionuclides of interest to allow setting of cost-effective priorities for radionuclide- and pathway-specific research. These include • soil-to-plant uptake studies for oranges and other citrus fruits, and • Development of models for evaluation of radionuclide concentration in highly-processed foods such as oils and sugars. Finally, renewed

  3. Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops

    PubMed Central

    Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

    2016-01-01

    Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an “island model” inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of

  4. Concentration Addition, Independent Action and Generalized Concentration Addition Models for Mixture Effect Prediction of Sex Hormone Synthesis In Vitro

    PubMed Central

    Hadrup, Niels; Taxvig, Camilla; Pedersen, Mikael; Nellemann, Christine; Hass, Ulla; Vinggaard, Anne Marie

    2013-01-01

    Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be

  5. Rapid SAR target modeling through genetic inheritance mechanism

    NASA Astrophysics Data System (ADS)

    Bala, Jerzy; Pachowicz, Peter W.; Vafaie, Halleh

    1997-07-01

    The paper presents a methodology and GETP experimental system for rapid SAR target signature generation from limited initial sensory data. The methodology exploits and integrates the following four processes: (1) analysis of initial SAR image signatures and their transformation into higher-level blob representation, (2) blob modeling, (3) genetic inheritance modeling to generate new instances of a target model in blob representation, and (4) synthesis of new SAR signatures from genetically evolved blob data. The GETP system takes several SAR signatures of the target and transforms each signature into more general scattered blob graphs, where each blob represents local energy cluster. A single graph node is describe by blob relative position, confidence, and iconic data. Graph data is forwarded to the genetic modeling process while blob image is stored in a catalog. Genetic inheritance is applied to the initial population of graph data. New graph models of the target are generated and evaluated. Selected graph variations are forwarded to the synthesis process. The synthesis process restores target signature from a given graph and a catalog of blobs. The background is synthesized to complement the signature. Initial experimental results are illustrated with 64 X 32 image sections of a tank.

  6. Dissecting genetic and environmental mutation signatures with model organisms.

    PubMed

    Segovia, Romulo; Tam, Annie S; Stirling, Peter C

    2015-08-01

    Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon. PMID:25940384

  7. The addition of algebraic turbulence modeling to program LAURA

    NASA Technical Reports Server (NTRS)

    Cheatwood, F. Mcneil; Thompson, R. A.

    1993-01-01

    The Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) is modified to allow the calculation of turbulent flows. This is accomplished using the Cebeci-Smith and Baldwin-Lomax eddy-viscosity models in conjunction with the thin-layer Navier-Stokes options of the program. Turbulent calculations can be performed for both perfect-gas and equilibrium flows. However, a requirement of the models is that the flow be attached. It is seen that for slender bodies, adequate resolution of the boundary-layer gradients may require more cells in the normal direction than a laminar solution, even when grid stretching is employed. Results for axisymmetric and three-dimensional flows are presented. Comparison with experimental data and other numerical results reveal generally good agreement, except in the regions of detached flow.

  8. Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models.

    PubMed

    Forutan, M; Ansari Mahyari, S; Sargolzaei, M

    2015-02-01

    Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49,583 female calves born during 1998 and 2009 were considered in five age periods as days 1-30, 31-180, 181-365, 366-760 and full period (day 1-760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd-year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82-0.95 and 0.61-0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31-180 and 181-365 (r(g) = 0.59), 31-180 and 366-760 (r(g) = 0.52), and 181-365 and 366-760 (r(g) = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection. PMID:25100295

  9. Translating Therapies for Huntington’s Disease from Genetic Animal Models to Clinical Trials

    PubMed Central

    Hersch, Steven M.; Ferrante, Robert J.

    2004-01-01

    Summary: Genetic animal models of inherited neurological diseases provide an opportunity to test potential treatments and explore their promise for translation to humans experiencing these diseases. Therapeutic trials conducted in mouse models of Huntington’s disease have identified a growing number of potential therapies that are candidates for clinical trials. Although it is very exciting to have these candidates, there has been increasing concern about the feasibility and desirability of taking all of the compounds that may work in mice and testing them in patients with HD. There is a need to begin to prioritize leads emerging from transgenic mouse studies; however, it is difficult to compare results between compounds and laboratories, and there are also many additional factors that can affect translation to humans. Among the important issues are what constitutes an informative genetic model, what principals should be followed in designing and conducting experiments using genetic animal models, how can results from different laboratories and in different models be compared, what body of evidence is desirable to fully inform clinical decision making, and what factors contribute to the equipoise in determining whether preclinical information about a therapy makes clinical study warranted. In the context of Huntington’s disease, we will review the current state of genetic models and their successes in putting forward therapeutic leads, provide a guide to assessing studies in mouse models, and discuss some of the salient issues related to translation from mice to humans. PMID:15717031

  10. Population genetics of Setaria viridis, a new model system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new mod...

  11. Software reliability: Additional investigations into modeling with replicated experiments

    NASA Technical Reports Server (NTRS)

    Nagel, P. M.; Schotz, F. M.; Skirvan, J. A.

    1984-01-01

    The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

  12. Genetically engineered mouse models to study prostate cancer.

    PubMed

    Brzezinska, Elspeth A; Nixon, Colin; Patel, Rachana; Leung, Hing Y

    2015-01-01

    Genetically engineered mouse models have become fundamental tools in the basic and translational research of prostate cancer. There is a plethora of models available to dissect the genetic alterations and aberrant signaling events associated with human prostate cancer and, furthermore, to investigate new and "personalized" therapies to treat the disease. In this chapter, we discuss some of the models recently and currently used to study prostate cancer in vivo, and some considerations when selecting an appropriate model to investigate particular aspects of the disease. We describe the methods required to isolate prostate tumors and conduct basic characterization of the tumor to determine tumor load and histopathology. We also discuss important aspects to be considered when processing samples for further analysis. PMID:25636465

  13. Rodent Models of Genetic Contributions to Motivation to Abuse Alcohol

    PubMed Central

    Crabbe, John C.

    2016-01-01

    The distinction between alcohol use (normative) and abuse (unfortunately common) implies dysregulation of motivation directed toward the drug. Genetic contributions to abuse risk are mediated through personality differences, other predispositions to drink excessively, and differences in sensitivity to the acute and chronic consequences of the drug. How to assess motivation in laboratory animals is not straightforward but risk factors for and consequences of alcohol abuse can be modeled with reasonable fidelity in laboratory rodents. Remarkably few rodent studies focus on the genetic contributions to alcohol’s reinforcing value: almost all examine preferential drinking of unflavored alcohol over water. Such studies will likely never avoid the confounding role of taste preferences and most often yield intake levels insufficient to yield a pharmacologically significant blood alcohol level. Genotypes that avoid alcohol probably do so based on pre-ingestive sensory cues; however, post-ingestive consequences are also important. Thus, the quest for improved measures of reinforcing value continues. We have genetic differences aplenty, but still lack evidence that any genotype will readily self-administer alcohol to the devastating extent that many alcoholics will. Encouraging results that are emerging include improved behavioral methods for elevating alcohol intake and inferring alcohol reinforcement, as well as new genetic animal models. Several ingenious assays to index alcohol’s motivational effects have been used extensively. Alcoholic drinking that attempts to prevent or to alleviate withdrawal symptoms has been modeled. Another characteristic of alcoholic drinking is its persistence despite abundant evidence to the drinker of the damaging effects of the excessive drinking on work, relationships, and/or health. Modeling such persistence in rodents has been uncommon to date. New genetic animal models include lines of mice selectively bred for chronic high drinking

  14. Mapping and Cracking Sensorimotor Circuits in Genetic Model Organisms

    PubMed Central

    Clark, Damon A.; Freifeld, Limor; Clandinin, Thomas R.

    2013-01-01

    One central goal of systems neuroscience is to understand how neural circuits implement the computations that link sensory inputs to behavior. Work combining electrophysiological and imaging-based approaches to measure neural activity with pharmacological and electrophysiological manipulations has provided fundamental insights. More recently, genetic approaches have been used to monitor and manipulate neural activity, opening up new experimental opportunities and challenges. Here, we discuss issues associated with applying genetic approaches to circuit dissection in sensorimotor transformations, outlining important considerations for experimental design and considering how modeling can complement experimental approaches. PMID:23719159

  15. A model of the holographic principle: Randomness and additional dimension

    NASA Astrophysics Data System (ADS)

    Boyarsky, Abraham; Góra, Paweł; Proppe, Harald

    2010-01-01

    In recent years an idea has emerged that a system in a 3-dimensional space can be described from an information point of view by a system on its 2-dimensional boundary. This mysterious correspondence is called the Holographic Principle and has had profound effects in string theory and our perception of space-time. In this note we describe a purely mathematical model of the Holographic Principle using ideas from nonlinear dynamical systems theory. We show that a random map on the surface S of a 3-dimensional open ball B has a natural counterpart in B, and the two maps acting in different dimensional spaces have the same entropy. We can reverse this construction if we start with a special 3-dimensional map in B called a skew product. The key idea is to use the randomness, as imbedded in the parameter of the 2-dimensional random map, to define a third dimension. The main result shows that if we start with an arbitrary dynamical system in B with entropy E we can construct a random map on S whose entropy is arbitrarily close to E.

  16. Additional Developments in Atmosphere Revitalization Modeling and Simulation

    NASA Technical Reports Server (NTRS)

    Coker, Robert F.; Knox, James C.; Cummings, Ramona; Brooks, Thomas; Schunk, Richard G.

    2013-01-01

    NASA's Advanced Exploration Systems (AES) program is developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond Earth orbit. These forays beyond the confines of earth's gravity will place unprecedented demands on launch systems. They must launch the supplies needed to sustain a crew over longer periods for exploration missions beyond earth's moon. Thus all spacecraft systems, including those for the separation of metabolic carbon dioxide and water from a crewed vehicle, must be minimized with respect to mass, power, and volume. Emphasis is also placed on system robustness both to minimize replacement parts and ensure crew safety when a quick return to earth is not possible. Current efforts are focused on improving the current state-of-the-art systems utilizing fixed beds of sorbent pellets by evaluating structured sorbents, seeking more robust pelletized sorbents, and examining alternate bed configurations to improve system efficiency and reliability. These development efforts combine testing of sub-scale systems and multi-physics computer simulations to evaluate candidate approaches, select the best performing options, and optimize the configuration of the selected approach. This paper describes the continuing development of atmosphere revitalization models and simulations in support of the Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM)

  17. Additional Developments in Atmosphere Revitalization Modeling and Simulation

    NASA Technical Reports Server (NTRS)

    Coker, Robert F.; Knox, James C.; Cummings, Ramona; Brooks, Thomas; Schunk, Richard G.; Gomez, Carlos

    2013-01-01

    NASA's Advanced Exploration Systems (AES) program is developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond Earth orbit. These forays beyond the confines of earth's gravity will place unprecedented demands on launch systems. They must launch the supplies needed to sustain a crew over longer periods for exploration missions beyond earth's moon. Thus all spacecraft systems, including those for the separation of metabolic carbon dioxide and water from a crewed vehicle, must be minimized with respect to mass, power, and volume. Emphasis is also placed on system robustness both to minimize replacement parts and ensure crew safety when a quick return to earth is not possible. Current efforts are focused on improving the current state-of-the-art systems utilizing fixed beds of sorbent pellets by evaluating structured sorbents, seeking more robust pelletized sorbents, and examining alternate bed configurations to improve system efficiency and reliability. These development efforts combine testing of sub-scale systems and multi-physics computer simulations to evaluate candidate approaches, select the best performing options, and optimize the configuration of the selected approach. This paper describes the continuing development of atmosphere revitalization models and simulations in support of the Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM) project within the AES program.

  18. Phenotype profile of a genetic mouse model for Muenke syndrome

    PubMed Central

    Koyama, Eiki; Agochukwu, Nneamaka B.; Bartlett, Scott P.; Muenke, Maximilian

    2014-01-01

    Purpose The Muenke syndrome mutation (FGFR3P250R), which was discovered 15 years ago, represents the single most common craniosynostosis mutation. Muenke syndrome is characterized by coronal suture synostosis, mid-face hypoplasia, subtle limb anomalies, and hearing loss. However, the spectrum of clinical presentation continues to expand. To better understand the pathophysiology of the Muenke syndrome, we present collective findings from several recent studies that have characterized a genetically equivalent mouse model for Muenke syndrome (FgfR3P244R) and compare them with human phenotypes. Conclusions FgfR3P244R mutant mice show premature fusion of facial sutures, premaxillary and/or zygomatic sutures, but rarely the coronal suture. The mice also lack the typical limb phenotype. On the other hand, the mutant mice display maxillary retrusion in association with a shortening of the anterior cranial base and a premature closure of intersphenoidal and spheno-occipital synchondroses, resembling human midface hypoplasia. In addition, sensorineural hearing loss is detected in all FgfR3P244R mutant mice as in the majority of Muenke syndrome patients. It is caused by a defect in the mechanism of cell fate determination in the organ of Corti. The mice also express phenotypes that have not been previously described in humans, such as reduced cortical bone thickness, hypoplastic trabecular bone, and defective temporomandibular joint structure. Therefore, the FgfR3P244R mouse provides an excellent opportunity to study disease mechanisms of some classical phenotypes of Muenke syndrome and to test novel therapeutic strategies. The mouse model can also be further explored to discover previously unreported yet potentially significant phenotypes of Muenke syndrome. PMID:22872265

  19. Quantitative genetic models for describing simultaneous and recursive relationships between phenotypes.

    PubMed Central

    Gianola, Daniel; Sorensen, Daniel

    2004-01-01

    Multivariate models are of great importance in theoretical and applied quantitative genetics. We extend quantitative genetic theory to accommodate situations in which there is linear feedback or recursiveness between the phenotypes involved in a multivariate system, assuming an infinitesimal, additive, model of inheritance. It is shown that structural parameters defining a simultaneous or recursive system have a bearing on the interpretation of quantitative genetic parameter estimates (e.g., heritability, offspring-parent regression, genetic correlation) when such features are ignored. Matrix representations are given for treating a plethora of feedback-recursive situations. The likelihood function is derived, assuming multivariate normality, and results from econometric theory for parameter identification are adapted to a quantitative genetic setting. A Bayesian treatment with a Markov chain Monte Carlo implementation is suggested for inference and developed. When the system is fully recursive, all conditional posterior distributions are in closed form, so Gibbs sampling is straightforward. If there is feedback, a Metropolis step may be embedded for sampling the structural parameters, since their conditional distributions are unknown. Extensions of the model to discrete random variables and to nonlinear relationships between phenotypes are discussed. PMID:15280252

  20. Genetic animal models of dystonia: common features and diversities.

    PubMed

    Richter, Franziska; Richter, Angelika

    2014-10-01

    Animal models are pivotal for studies of pathogenesis and treatment of disorders of the central nervous system which in its complexity cannot yet be modeled in vitro or using computer simulations. The choice of a specific model to test novel therapeutic strategies for a human disease should be based on validity of the model for the approach: does the model reflect symptoms, pathogenesis and treatment response present in human patients? In the movement disorder dystonia, prior to the availability of genetically engineered mice, spontaneous mutants were chosen based on expression of dystonic features, including abnormal muscle contraction, movements and postures. Recent discovery of a number of genes and gene products involved in dystonia initiated research on pathogenesis of the disorder, and the creation of novel models based on gene mutations. Here we present a review of current models of dystonia, with a focus on genetic rodent models, which will likely be first choice in the future either for pathophysiological or for preclinical drug testing or both. In order to help selection of a model depending on expression of a specific feature of dystonia, this review is organized by symptoms and current knowledge of pathogenesis of dystonia. We conclude that albeit there is increasing need for research on pathogenesis of the disease and development of improved models, current models do replicate features of dystonia and are useful tools to develop urgently demanded treatment for this debilitating disorder. PMID:25034123

  1. Transferability of regional permafrost disturbance susceptibility modelling using generalized linear and generalized additive models

    NASA Astrophysics Data System (ADS)

    Rudy, Ashley C. A.; Lamoureux, Scott F.; Treitz, Paul; van Ewijk, Karin Y.

    2016-07-01

    To effectively assess and mitigate risk of permafrost disturbance, disturbance-prone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape characteristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Peninsula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed locations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) > 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Additionally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results indicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of disturbances were

  2. The Analysis of Quantitative Traits for Simple Genetic Models from Parental, F1 and Backcross Data

    PubMed Central

    Elston, R. C.; Stewart, John

    1973-01-01

    The following models are considered for the genetic determination of quantitative traits: segregation at one locus, at two linked loci, at any number of equal and additive unlinked loci, and at one major locus and an indefinite number of equal and additive loci. In each case an appropriate likelihood is given for data on parental, F1 and backcross individuals, assuming that the environmental variation is normally distributed. Methods of testing and comparing the various models are presented, and methods are suggested for the simultaneous analysis of two or more traits. PMID:4711900

  3. Metabolic Profiles and Genetic Diversity of Denitrifying Communities in Activated Sludge after Addition of Methanol or Ethanol†

    PubMed Central

    Hallin, Sara; Throbäck, Ingela Noredal; Dicksved, Johan; Pell, Mikael

    2006-01-01

    External carbon sources can enhance denitrification rates and thus improve nitrogen removal in wastewater treatment plants. The effects of adding methanol and ethanol on the genetic and metabolic diversity of denitrifying communities in activated sludge were compared using a pilot-scale plant with two parallel lines. A full-scale plant receiving the same municipal wastewater, but without external carbon source addition, was the reference. Metabolic profiles obtained from potential denitrification rates with 10 electron donors showed that the denitrifying communities altered their preferences for certain compounds after supplementation with methanol or ethanol and that methanol had the greater impact. Clone libraries of nirK and nirS genes, encoding the two different nitrite reductases in denitrifiers, revealed that methanol also increased the diversity of denitrifiers of the nirS type, which indicates that denitrifiers favored by methanol were on the rise in the community. This suggests that there might be a niche differentiation between nirS and nirK genotypes during activated sludge processes. The composition of nirS genotypes also varied greatly among all samples, whereas the nirK communities were more stable. The latter was confirmed by denaturing gradient gel electrophoresis of nirK communities on all sampling occasions. Our results support earlier hypotheses that the compositions of denitrifier communities change during predenitrification processes when external carbon sources are added, although no severe effect could be observed from an operational point of view. PMID:16885297

  4. Stress models of depression: forming genetically vulnerable strains.

    PubMed

    Henn, Fritz A; Vollmayr, Barbara

    2005-01-01

    Among the most useful models for depressive disorders are those, which involve a stress induced change in behaviour. Learned helplessness is one such model and is induced through exposure to uncontrollable and unpredictable aversive events. Learned helplessness as induced in rats using foot shock is well characterized and has good face validity and predictive validity as a model of depression, including alterations in HPA axis activity and REM sleep characteristic of depression. The data concerning the validity will be briefly reviewed. The model can also be used to look at the role of genetics through selective breeding. These studies will be reviewed and the utility of the genetic strains for understanding the interaction of stress and affect will be examined. A second model of depression using exposure to chronic stress also has high face and predictive validity. A new form of this approach, recently described, also is suitable for the examination of genetic factors leading to depressive like behaviour and this will be presented. PMID:15925700

  5. Genetic implanted fuzzy model for water saturation determination

    NASA Astrophysics Data System (ADS)

    Bagheripour, Parisa; Asoodeh, Mojtaba

    2014-04-01

    The portion of rock pore volume occupied with non-hydrocarbon fluids is called water saturation, which plays a significant role in reservoir description and management. Accurate water saturation, directly measured from special core analysis is highly expensive and time consuming. Furthermore, indirect measurements of water saturation from well log interpretation such as empirical correlations or statistical methods do not provide satisfying results. Recent works showed that fuzzy logic is a robust tool for handling geosciences problems which provide more reliable results compared with empirical correlations or statistical methods. This study goes further to improve fuzzy logic for enhancing accuracy of final prediction. It employs hybrid genetic algorithm-pattern search technique instead of widely held subtractive clustering approach for setting up fuzzy rules and for extracting optimal parameters involved in computational structure of fuzzy model. The proposed strategy, called genetic implanted fuzzy model, was used to formulate conventional well log data, including sonic transit time, neutron porosity, formation bulk density, true resistivity, and gamma ray into water saturation, obtained from subtractive clustering approach. Results indicated genetic implanted fuzzy model performed more satisfyingly compared with traditional fuzzy logic model. The propounded model was successfully applied to one of Iranian carbonate reservoir rocks.

  6. A Tri-Part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning about Authentic Genetics Dilemmas

    ERIC Educational Resources Information Center

    Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

    2015-01-01

    Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational…

  7. Current Progress of Genetically Engineered Pig Models for Biomedical Research

    PubMed Central

    Gün, Gökhan

    2014-01-01

    Abstract The first transgenic pigs were generated for agricultural purposes about three decades ago. Since then, the micromanipulation techniques of pig oocytes and embryos expanded from pronuclear injection of foreign DNA to somatic cell nuclear transfer, intracytoplasmic sperm injection-mediated gene transfer, lentiviral transduction, and cytoplasmic injection. Mechanistically, the passive transgenesis approach based on random integration of foreign DNA was developed to active genetic engineering techniques based on the transient activity of ectopic enzymes, such as transposases, recombinases, and programmable nucleases. Whole-genome sequencing and annotation of advanced genome maps of the pig complemented these developments. The full implementation of these tools promises to immensely increase the efficiency and, in parallel, to reduce the costs for the generation of genetically engineered pigs. Today, the major application of genetically engineered pigs is found in the field of biomedical disease modeling. It is anticipated that genetically engineered pigs will increasingly be used in biomedical research, since this model shows several similarities to humans with regard to physiology, metabolism, genome organization, pathology, and aging. PMID:25469311

  8. Monthly pan evaporation modeling using linear genetic programming

    NASA Astrophysics Data System (ADS)

    Guven, Aytac; Kisi, Ozgur

    2013-10-01

    This study compares the accuracy of linear genetic programming (LGP), fuzzy genetic (FG), adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANN) and Stephens-Stewart (SS) methods in modeling pan evaporations. Monthly climatic data including solar radiation, air temperature, relative humidity, wind speed and pan evaporation from Antalya and Mersin stations, in Turkey are used in the study. The study composed of two parts. First part of the study focuses the comparison of LGP models with those of the FG, ANFIS, ANN and SS models in estimating pan evaporations of Antalya and Mersin stations, separately. From the comparison results, the LGP models are found to be better than the other models. Comparison of LGP models with the other models in estimating pan evaporations of the Mersin Station by using both stations' inputs is focused in the second part of the study. The results indicate that the LGP models better accuracy than the FG, ANFIS, ANN and SS models. It is seen that the pan evaporations can be successfully estimated by the LGP method.

  9. Estimates of genetic parameters for growth traits in Brahman cattle using random regression and multitrait models.

    PubMed

    Bertipaglia, T S; Carreño, L O D; Aspilcueta-Borquis, R R; Boligon, A A; Farah, M M; Gomes, F J; Machado, C H C; Rey, F S B; da Fonseca, R

    2015-08-01

    Random regression models (RRM) and multitrait models (MTM) were used to estimate genetic parameters for growth traits in Brazilian Brahman cattle and to compare the estimated breeding values obtained by these 2 methodologies. For RRM, 78,641 weight records taken between 60 and 550 d of age from 16,204 cattle were analyzed, and for MTM, the analysis consisted of 17,385 weight records taken at the same ages from 12,925 cattle. All models included the fixed effects of contemporary group and the additive genetic, maternal genetic, and animal permanent environmental effects and the quadratic effect of age at calving (AAC) as covariate. For RRM, the AAC was nested in the animal's age class. The best RRM considered cubic polynomials and the residual variance heterogeneity (5 levels). For MTM, the weights were adjusted for standard ages. For RRM, additive heritability estimates ranged from 0.42 to 0.75, and for MTM, the estimates ranged from 0.44 to 0.72 for both models at 60, 120, 205, 365, and 550 d of age. The maximum maternal heritability estimate (0.08) was at 140 d for RRM, but for MTM, it was highest at weaning (0.09). The magnitude of the genetic correlations was generally from moderate to high. The RRM adequately modeled changes in variance or covariance with age, and provided there was sufficient number of samples, increased accuracy in the estimation of the genetic parameters can be expected. Correlation of bull classifications were different in both methods and at all the ages evaluated, especially at high selection intensities, which could affect the response to selection. PMID:26440161

  10. Dominant Genetic Variation and Missing Heritability for Human Complex Traits: Insights from Twin versus Genome-wide Common SNP Models

    PubMed Central

    Chen, Xu; Kuja-Halkola, Ralf; Rahman, Iffat; Arpegård, Johannes; Viktorin, Alexander; Karlsson, Robert; Hägg, Sara; Svensson, Per; Pedersen, Nancy L.; Magnusson, Patrik K.E.

    2015-01-01

    In order to further illuminate the potential role of dominant genetic variation in the “missing heritability” debate, we investigated the additive (narrow-sense heritability, h2) and dominant (δ2) genetic variance for 18 human complex traits. Within the same study base (10,682 Swedish twins), we calculated and compared the estimates from classic twin-based structural equation model with SNP-based genomic-relatedness-matrix restricted maximum likelihood [GREML(d)] method. Contributions of δ2 were evident for 14 traits in twin models (average δ2twin = 0.25, range 0.14–0.49), two of which also displayed significant δ2 in the GREMLd analyses (triglycerides δ2SNP = 0.28 and waist circumference δ2SNP = 0.19). On average, the proportion of h2SNP/h2twin was 70% for ADE-fitted traits (for which the best-fitting model included additive and dominant genetic and unique environmental components) and 31% for AE-fitted traits (for which the best-fitting model included additive genetic and unique environmental components). Independent evidence for contribution from shared environment, also in ADE-fitted traits, was obtained from self-reported within-pair contact frequency and age at separation. We conclude that despite the fact that additive genetics appear to constitute the bulk of genetic influences for most complex traits, dominant genetic variation might often be masked by shared environment in twin and family studies and might therefore have a more prominent role than what family-based estimates often suggest. The risk of erroneously attributing all inherited genetic influences (additive and dominant) to the h2 in too-small twin studies might also lead to exaggerated “missing heritability” (the proportion of h2 that remains unexplained by SNPs). PMID:26544805

  11. Additive transgene expression and genetic introgression in multiple green-fluorescent protein transgenic crop x weed hybrid generations.

    PubMed

    Halfhill, M D; Millwood, R J; Weissinger, A K; Warwick, S I; Stewart, C N

    2003-11-01

    The level of transgene expression in crop x weed hybrids and the degree to which crop-specific genes are integrated into hybrid populations are important factors in assessing the potential ecological and agricultural risks of gene flow associated with genetic engineering. The average transgene zygosity and genetic structure of transgenic hybrid populations change with the progression of generations, and the green fluorescent protein (GFP) transgene is an ideal marker to quantify transgene expression in advancing populations. The homozygous T(1) single-locus insert GFP/ Bacillus thuringiensis (Bt) transgenic canola ( Brassica napus, cv Westar) with two copies of the transgene fluoresced twice as much as hemizygous individuals with only one copy of the transgene. These data indicate that the expression of the GFP gene was additive, and fluorescence could be used to determine zygosity status. Several hybrid generations (BC(1)F(1), BC(2)F(1)) were produced by backcrossing various GFP/Bt transgenic canola ( B. napus, cv Westar) and birdseed rape ( Brassica rapa) hybrid generations onto B. rapa. Intercrossed generations (BC(2)F(2) Bulk) were generated by crossing BC(2)F(1) individuals in the presence of a pollinating insect ( Musca domestica L.). The ploidy of plants in the BC(2)F(2) Bulk hybrid generation was identical to the weedy parental species, B. rapa. AFLP analysis was used to quantify the degree of B. napus introgression into multiple backcross hybrid generations with B. rapa. The F(1) hybrid generations contained 95-97% of the B. napus-specific AFLP markers, and each successive backcross generation demonstrated a reduction of markers resulting in the 15-29% presence in the BC(2)F(2) Bulk population. Average fluorescence of each successive hybrid generation was analyzed, and homozygous canola lines and hybrid populations that contained individuals homozygous for GFP (BC(2)F(2) Bulk) demonstrated significantly higher fluorescence than hemizygous hybrid

  12. Modeling the cardiovascular system using a nonlinear additive autoregressive model with exogenous input

    NASA Astrophysics Data System (ADS)

    Riedl, M.; Suhrbier, A.; Malberg, H.; Penzel, T.; Bretthauer, G.; Kurths, J.; Wessel, N.

    2008-07-01

    The parameters of heart rate variability and blood pressure variability have proved to be useful analytical tools in cardiovascular physics and medicine. Model-based analysis of these variabilities additionally leads to new prognostic information about mechanisms behind regulations in the cardiovascular system. In this paper, we analyze the complex interaction between heart rate, systolic blood pressure, and respiration by nonparametric fitted nonlinear additive autoregressive models with external inputs. Therefore, we consider measurements of healthy persons and patients suffering from obstructive sleep apnea syndrome (OSAS), with and without hypertension. It is shown that the proposed nonlinear models are capable of describing short-term fluctuations in heart rate as well as systolic blood pressure significantly better than similar linear ones, which confirms the assumption of nonlinear controlled heart rate and blood pressure. Furthermore, the comparison of the nonlinear and linear approaches reveals that the heart rate and blood pressure variability in healthy subjects is caused by a higher level of noise as well as nonlinearity than in patients suffering from OSAS. The residue analysis points at a further source of heart rate and blood pressure variability in healthy subjects, in addition to heart rate, systolic blood pressure, and respiration. Comparison of the nonlinear models within and among the different groups of subjects suggests the ability to discriminate the cohorts that could lead to a stratification of hypertension risk in OSAS patients.

  13. Influence of mom and dad: quantitative genetic models for maternal effects and genomic imprinting.

    PubMed

    Santure, Anna W; Spencer, Hamish G

    2006-08-01

    The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components. PMID:16751674

  14. Genetic variants associated with neurodegenerative Alzheimer disease in natural models.

    PubMed

    Salazar, Claudia; Valdivia, Gonzalo; Ardiles, Álvaro O; Ewer, John; Palacios, Adrián G

    2016-01-01

    The use of transgenic models for the study of neurodegenerative diseases has made valuable contributions to the field. However, some important limitations, including protein overexpression and general systemic compensation for the missing genes, has caused researchers to seek natural models that show the main biomarkers of neurodegenerative diseases during aging. Here we review some of these models-most of them rodents, focusing especially on the genetic variations in biomarkers for Alzheimer diseases, in order to explain their relationships with variants associated with the occurrence of the disease in humans. PMID:26919851

  15. Genetic "code": representations and dynamical models of genetic components and networks.

    PubMed

    Gilman, Alex; Arkin, Adam P

    2002-01-01

    Dynamical modeling of biological systems is becoming increasingly widespread as people attempt to grasp biological phenomena in their full complexity and make sense of an accelerating stream of experimental data. We review a number of recent modeling studies that focus on systems specifically involving gene expression and regulation. These systems include bacterial metabolic operons and phase-variable piliation, bacteriophages T7 and lambda, and interacting networks of eukaryotic developmental genes. A wide range of conceptual and mathematical representations of genetic components and phenomena appears in these works. We discuss these representations in depth and give an overview of the tools currently available for creating and exploring dynamical models. We argue that for modeling to realize its full potential as a mainstream biological research technique the tools must become more general and flexible, and formal, standardized representations of biological knowledge and data must be developed. PMID:12142360

  16. Genetic animal models of malformations of cortical development and epilepsy.

    PubMed

    Wong, Michael; Roper, Steven N

    2016-02-15

    Malformations of cortical development constitute a variety of pathological brain abnormalities that commonly cause severe, medically-refractory epilepsy, including focal lesions, such as focal cortical dysplasia, heterotopias, and tubers of tuberous sclerosis complex, and diffuse malformations, such as lissencephaly. Although some cortical malformations result from environmental insults during cortical development in utero, genetic factors are increasingly recognized as primary pathogenic factors across the entire spectrum of malformations. Genes implicated in causing different cortical malformations are involved in a variety of physiological functions, but many are focused on regulation of cell proliferation, differentiation, and neuronal migration. Advances in molecular genetic methods have allowed the engineering of increasingly sophisticated animal models of cortical malformations and associated epilepsy. These animal models have identified some common mechanistic themes shared by a number of different cortical malformations, but also revealed the diversity and complexity of cellular and molecular mechanisms that lead to the development of the pathological lesions and resulting epileptogenesis. PMID:25911067

  17. Sleep and Development in Genetically Tractable Model Organisms.

    PubMed

    Kayser, Matthew S; Biron, David

    2016-05-01

    Sleep is widely recognized as essential, but without a clear singular function. Inadequate sleep impairs cognition, metabolism, immune function, and many other processes. Work in genetic model systems has greatly expanded our understanding of basic sleep neurobiology as well as introduced new concepts for why we sleep. Among these is an idea with its roots in human work nearly 50 years old: sleep in early life is crucial for normal brain maturation. Nearly all known species that sleep do so more while immature, and this increased sleep coincides with a period of exuberant synaptogenesis and massive neural circuit remodeling. Adequate sleep also appears critical for normal neurodevelopmental progression. This article describes recent findings regarding molecular and circuit mechanisms of sleep, with a focus on development and the insights garnered from models amenable to detailed genetic analyses. PMID:27183564

  18. Evidence of Shared Genome-Wide Additive Genetic Effects on Interpersonal Trauma Exposure and Generalized Vulnerability to Drug Dependence in a Population of Substance Users.

    PubMed

    Palmer, Rohan H C; Nugent, Nicole R; Brick, Leslie A; Bidwell, Cinnamon L; McGeary, John E; Keller, Matthew C; Knopik, Valerie S

    2016-06-01

    Exposure to traumatic experiences is associated with an increased risk for drug dependence and poorer response to substance abuse treatment (Claus & Kindleberger, 2002; Jaycox, Ebener, Damesek, & Becker, 2004). Despite this evidence, the reasons for the observed associations of trauma and the general tendency to be dependent upon drugs of abuse remain unclear. Data (N = 2,596) from the Study of Addiction: Genetics and Environment were used to analyze (a) the degree to which commonly occurring single nucleotide polymorphisms (SNPs; minor allele frequency > 1%) in the human genome explains exposure to interpersonal traumatic experiences, and (b) the extent to which additive genetic effects on trauma are shared with additive genetic effects on drug dependence. Our results suggested moderate additive genetic influences on interpersonal trauma, h(2) SNP-Interpersonal = .47, 95% confidence interval (CI) [.10, .85], that are partially shared with additive genetic effects on generalized vulnerability to drug dependence, h(2) SNP-DD = .36, 95% CI [.11, .61]; rG-SNP = .49, 95% CI [.02, .96]. Although the design/technique does not exclude the possibility that substance abuse causally increases risk for traumatic experiences (or vice versa), these findings raise the possibility that commonly occurring SNPs influence both the general tendency towards drug dependence and interpersonal trauma. PMID:27214850

  19. A Family-Centered Model for Sharing Genetic Risk.

    PubMed

    Daly, Mary B

    2015-01-01

    The successes of the Human Genome Project have ushered in a new era of genomic science. To effectively translate these discoveries, it will be critical to improve the communication of genetic risk within families. This will require a systematic approach that accounts for the nature of family relationships and sociocultural beliefs. This paper proposes the application of the Family Systems Illness Model, used in the setting of cancer care, to the evolving field of genomics. PMID:26479564

  20. A pathway-based analysis provides additional support for an immune-related genetic susceptibility to Parkinson's disease

    PubMed Central

    Holmans, Peter; Moskvina, Valentina; Jones, Lesley; Sharma, Manu; Vedernikov, Alexey; Buchel, Finja; Sadd, Mohamad; Bras, Jose M.; Bettella, Francesco; Nicolaou, Nayia; Simón-Sánchez, Javier; Mittag, Florian; Gibbs, J. Raphael; Schulte, Claudia; Durr, Alexandra; Guerreiro, Rita; Hernandez, Dena; Brice, Alexis; Stefánsson, Hreinn; Majamaa, Kari; Gasser, Thomas; Heutink, Peter; Wood, Nicholas W.; Martinez, Maria; Singleton, Andrew B.; Nalls, Michael A.; Hardy, John; Morris, Huw R.; Williams, Nigel M.; Arepalli, Sampath; Barker, Roger; Barrett, Jeffrey; Ben-Shlomo, Yoav; Berendse, Henk W.; Berg, Daniela; Bhatia, Kailash; de Bie, Rob M.A.; Biffi, Alessandro; Bloem, Bas; Brice, Alexis; Bochdanovits, Zoltan; Bonin, Michael; Bras, Jose M.; Brockmann, Kathrin; Brooks, Janet; Burn, David J.; Charlesworth, Gavin; Chen, Honglei; Chinnery, Patrick F.; Chong, Sean; Clarke, Carl E.; Cookson, Mark R.; Cooper, Jonathan M.; Corvol, Jen-Christophe; Counsell, Carl; Damier, Philippe; Dartigues, Jean Francois; Deloukas, Panagiotis; Deuschl, Günther; Dexter, David T.; van Dijk, Karin D.; Dillman, Allissa; Durif, Frank; Durr, Alexandra; Edkins, Sarah; Evans, Jonathan R.; Foltynie, Thomas; Gao, Jianjun; Gardner, Michelle; Gasser, Thomas; Gibbs, J. Raphael; Goate, Alison; Gray, Emma; Guerreiro, Rita; Gústafsson, Ómar; Hardy, John; Harris, Clare; Hernandez, Dena G.; Heutink, Peter; van Hilten, Jacobus J.; Hofman, Albert; Hollenbeck, Albert; Holmans, Peter; Holton, Janice; Hu, Michele; Huber, Heiko; Hudson, Gavin; Hunt, Sarah E.; Huttenlocher, Johanna; Illig, Thomas; Langford, Cordelia; Lees, Andrew; Lesage, Suzanne; Lichtner, Peter; Limousin, Patricia; Lopez, Grisel; Lorenz, Delia; Martinez, Maria; McNeill, Alisdair; Moorby, Catriona; Moore, Matthew; Morris, Huw; Morrison, Karen E.; Moskvina, Valentina; Mudanohwo, Ese; Nalls, Michael A.; Pearson, Justin; Perlmutter, Joel S.; Pétursson, Hjörvar; Plagnol, Vincent; Pollak, Pierre; Post, Bart; Potter, Simon; Ravina, Bernard; Revesz, Tamas; Riess, Olaf; Rivadeneira, Fernando; Rizzu, Patrizia; Ryten, Mina; Saad, Mohamad; Sawcer, Stephen; Schapira, Anthony; Scheffer, Hans; Sharma, Manu; Shaw, Karen; Sheerin, Una-Marie; Shoulson, Ira; Schulte, Claudia; Sidransky, Ellen; Simón-Sánchez, Javier; Singleton, Andrew B.; Smith, Colin; Stefánsson, Hreinn; Stefánsson, Kári; Steinberg, Stacy; Stockton, Joanna D.; Sveinbjornsdottir, Sigurlaug; Talbot, Kevin; Tanner, Carlie M.; Tashakkori-Ghanbaria, Avazeh; Tison, François; Trabzuni, Daniah; Traynor, Bryan J.; Uitterlinden, André G.; Velseboer, Daan; Vidailhet, Marie; Walker, Robert; van de Warrenburg, Bart; Wickremaratchi, Mirdhu; Williams, Nigel; Williams-Gray, Caroline H.; Winder-Rhodes, Sophie; Wood, Nicholas

    2013-01-01

    Parkinson's disease (PD) is the second most common neurodegenerative disease affecting 1–2% in people >60 and 3–4% in people >80. Genome-wide association (GWA) studies have now implicated significant evidence for association in at least 18 genomic regions. We have studied a large PD-meta analysis and identified a significant excess of SNPs (P < 1 × 10−16) that are associated with PD but fall short of the genome-wide significance threshold. This result was independent of variants at the 18 previously implicated regions and implies the presence of additional polygenic risk alleles. To understand how these loci increase risk of PD, we applied a pathway-based analysis, testing for biological functions that were significantly enriched for genes containing variants associated with PD. Analysing two independent GWA studies, we identified that both had a significant excess in the number of functional categories enriched for PD-associated genes (minimum P = 0.014 and P = 0.006, respectively). Moreover, 58 categories were significantly enriched for associated genes in both GWA studies (P < 0.001), implicating genes involved in the ‘regulation of leucocyte/lymphocyte activity’ and also ‘cytokine-mediated signalling’ as conferring an increased susceptibility to PD. These results were unaltered by the exclusion of all 178 genes that were present at the 18 genomic regions previously reported to be strongly associated with PD (including the HLA locus). Our findings, therefore, provide independent support to the strong association signal at the HLA locus and imply that the immune-related genetic susceptibility to PD is likely to be more widespread in the genome than previously appreciated. PMID:23223016

  1. Influence of a Dopamine Pathway Additive Genetic Efficacy Score on Smoking Cessation: Results from Two Randomized Clinical Trials of Bupropion

    PubMed Central

    David, Sean P.; Strong, David R.; Leventhal, Adam M.; Lancaster, Molly A.; McGeary, John E.; Munafò, Marcus R.; Bergen, Andrew W.; Swan, Gary E.; Benowitz, Neal L.; Tyndale, Rachel F.; Conti, David V.; Brown, Richard A.; Lerman, Caryn; Niaura, Raymond

    2013-01-01

    Aims To evaluate associations of treatment and an ‘additive genetic efficacy score’ (AGES) based on dopamine functional polymorphisms with time to first smoking lapse and point prevalence abstinence at end of treatment among participants enrolled in two randomized clinical trials of smoking cessation therapies. Design Double-blind pharmacogenetic efficacy trials randomizing participants to active or placebo bupropion. Study 1 also randomized participants to cognitive-behavioral smoking cessation treatment (CBT) or this treatment with CBT for depression. Study 2 provided standardized behavioural support. Setting Two Hospital-affiliated clinics (Study 1), and two University-affiliated clinics (Study 2). Participants N=792 self-identified white treatment-seeking smokers aged ≥18 years smoking ≥10 cigarettes per day over the last year. Measurements Age, gender, Fagerström Test for Nicotine Dependence, dopamine pathway genotypes (rs1800497 [ANKK1 E713K], rs4680 [COMT V158M], DRD4 exon 3 Variable Number of Tandem Repeats polymorphism [DRD4 VNTR], SLC6A3 3' VNTR) analyzed both separately and as part of an AGES, time to first lapse, and point prevalence abstinence at end of treatment. Findings Significant associations of the AGES (hazard ratio = 1.10, 95% Confidence Interval [CI] = 1.06–1.14], p=0.0099) and of the DRD4 VNTR (HR = 1.29, 95%CI 1.17–1.41, p=0.0073) were observed with time to first lapse. A significant AGES by pharmacotherapy interaction was observed (β [SE]=−0.18 [0.07], p=0.016), such that AGES predicted risk for time to first lapse only for individuals randomized to placebo. Conclusions A score based on functional polymorphisms relating to dopamine pathways appears to predict lapse to smoking following a quit attempt, and the association is mitigated in smokers using bupropion. PMID:23941313

  2. A model agreement for genetic research in socially identifiable populations.

    PubMed

    Foster, M W; Bernsten, D; Carter, T H

    1998-09-01

    Genetic research increasingly focuses on population-specific human genetic diversity. However, the naming of a human population in public databases and scientific publications entails collective risks for its members. Those collective risks can be evaluated and protections can be put in place by the establishment of a dialogue with the subject population, before a research study is initiated. Here we describe an agreement to undertake genetic research with a Native American tribe. We identified the culturally appropriate public and private social units within which community members are accustomed to make decisions about health. We then engaged those units in a process of communal discourse. In their discourses about our proposed study, community members expressed most concern about culturally specific implications. We also found that, in this population, private social units were more influential in communal decision making than were public authorities. An agreement was reached that defined the scope of research, provided options for naming the population in publications (including anonymity), and addressed the distribution of royalties from intellectual property, the future use of archival samples, and specific cultural concerns. We found that informed consent by individuals could not fully address these collective issues. This approach may serve as a general model for the undertaking of population-specific genetic studies. PMID:9718343

  3. The genetics of speciation: Insights from Fisher's geometric model.

    PubMed

    Fraïsse, Christelle; Gunnarsson, P Alexander; Roze, Denis; Bierne, Nicolas; Welch, John J

    2016-07-01

    Research in speciation genetics has uncovered many robust patterns in intrinsic reproductive isolation, and fitness landscape models have been useful in interpreting these patterns. Here, we examine fitness landscapes based on Fisher's geometric model. Such landscapes are analogous to models of optimizing selection acting on quantitative traits, and have been widely used to study adaptation and the distribution of mutational effects. We show that, with a few modifications, Fisher's model can generate all of the major findings of introgression studies (including "speciation genes" with strong deleterious effects, complex epistasis and asymmetry), and the major patterns in overall hybrid fitnesses (including Haldane's Rule, the speciation clock, heterosis, hybrid breakdown, and male-female asymmetry in the F1). We compare our approach to alternative modeling frameworks that assign fitnesses to genotypes by identifying combinations of incompatible alleles. In some cases, the predictions are importantly different. For example, Fisher's model can explain conflicting empirical results about the rate at which incompatibilities accumulate with genetic divergence. In other cases, the predictions are identical. For example, the quality of reproductive isolation is little affected by the manner in which populations diverge. PMID:27252049

  4. Genetic analysis of carcass traits in beef cattle using random regression models.

    PubMed

    Englishby, T M; Banos, G; Moore, K L; Coffey, M P; Evans, R D; Berry, D P

    2016-04-01

    Livestock mature at different rates depending, in part, on their genetic merit; therefore, the optimal age at slaughter for progeny of certain sires may differ. The objective of the present study was to examine sire-level genetic profiles for carcass weight, carcass conformation, and carcass fat in cattle of multiple beef and dairy breeds, including crossbreeds. Slaughter records from 126,214 heifers and 124,641 steers aged between 360 and 1,200 d and from 86,089 young bulls aged between 360 and 720 d were used in the analysis; animals were from 15,127 sires. Variance components for each trait across age at slaughter were generated using sire random regression models that included quadratic polynomials for fixed and random effects; heterogeneous residual variances were assumed across ages. Heritability estimates across genders ranged from 0.08 (±0.02) to 0.34 (±0.02) for carcass weight, from 0.24 (±0.02) to 0.42 (±0.01) for conformation, and from 0.16 (±0.03) to 0.40 (±0.02) for fat score. Genetic correlations within each trait across ages weakened as the interval between ages compared lengthened but were all >0.64, suggesting a similar genetic background for each trait across different ages. Eigenvalues and eigenfunctions of the additive genetic covariance matrix revealed genetic variability among animals in their growth profiles for carcass traits, although most of the genetic variability was associated with the height of the growth profile. At the same age, a positive genetic correlation (0.60 to 0.78; SE ranged from 0.01 to 0.04) existed between carcass weight and conformation, whereas negative genetic correlations existed between fatness and both conformation (-0.46 to 0.08; SE ranged from 0.02 to 0.09) and carcass weight (-0.48 to -0.16; SE ranged from 0.02 to 0.14) at the same age. The estimated genetic parameters in the present study indicate genetic variability in the growth trajectory in cattle, which can be exploited through breeding programs and

  5. Self similarity in a model of genetic microevolution

    NASA Astrophysics Data System (ADS)

    Strier, Damián E.; Zanette, Damián H.

    A mathematical model of genetic microevolution is presented. The model stands for a population of genotypes evolving in the genotypic space. Its dynamics is governed by a master evolution equation which takes into account both the presence of a fluctuating fitness landscape and genotypic variations of the offspring with respect to the parents. We found that, under rather general conditions, the population growth rate exhibits self-similarity. This result provides a clue to universal scaling features of evolution in the large-time scale, as observed from paleobiological evidence.

  6. Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation

    PubMed Central

    Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara

    2016-01-01

    Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother’s old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother’s old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington’s genetic

  7. Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation.

    PubMed

    Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara

    2016-01-01

    Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington's genetic assimilation

  8. Identification of response surface models using genetic programming

    NASA Astrophysics Data System (ADS)

    Lew, T. L.; Spencer, A. B.; Scarpa, F.; Worden, K.; Rutherford, A.; Hemez, F.

    2006-11-01

    There is a move in modern research in Structural Dynamics towards analysing the inherent uncertainty in a given problem. This may be quantifying or fusing uncertainty models, or can be propagation of uncertainty through a system or calculation. If the system of interest is represented by, e.g. a large Finite Element (FE) model the large number of computations involved can rule out many approaches due to the expense of carrying out many runs. One way of circumnavigating this problem is to replace the true system by an approximate surrogate/replacement model, which is fast-running compared to the original. In traditional approaches using response surfaces a simple least-squares multinomial model is often adopted. The objective of this paper is to extend the class of possible models considerably by carrying out a general symbolic regression using a Genetic Programming approach. The approach is demonstrated on both univariate and multivariate problems with both computational and experimental data.

  9. The evolution of menstruation: A new model for genetic assimilation

    PubMed Central

    Emera, D.; Romero, R.; Wagner, G.

    2012-01-01

    Why do humans menstruate while most mammals do not? Here, we present our answer to this long-debated question, arguing that (i) menstruation occurs as a mechanistic consequence of hormone-induced differentiation of the endometrium (referred to as spontaneous decidualization, or SD); (ii) SD evolved because of maternal-fetal conflict; and (iii) SD evolved by genetic assimilation of the decidualization reaction, which is induced by the fetus in non-menstruating species. The idea that menstruation occurs as a consequence of SD has been proposed in the past, but here we present a novel hypothesis on how SD evolved. We argue that decidualization became genetically stabilized in menstruating lineages, allowing females to prepare for pregnancy without any signal from the fetus. We present three models for the evolution of SD by genetic assimilation, based on recent advances in our understanding of the mechanisms of endometrial differentiation and implantation. Testing these models will ultimately shed light on the evolutionary significance of menstruation, as well as on the etiology of human reproductive disorders like endometriosis and recurrent pregnancy loss. PMID:22057551

  10. Genetic parameters for racing records in trotters using linear and generalized linear models.

    PubMed

    Suontama, M; van der Werf, J H J; Juga, J; Ojala, M

    2012-09-01

    Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success

  11. GENETIC ANALYSIS OF STRUCTURAL BRAIN CONNECTIVITY USING DICCCOL MODELS OF DIFFUSION MRI IN 522 TWINS

    PubMed Central

    Zhu, Dajiang; Zhan, Liang; Faskowitz, Joshua; Daianu, Madelaine; Jahanshad, Neda; de Zubicaray, Greig I.; McMahon, Katie L.; Martin, Nicholas G.; Wright, Margaret J.; Thompson, Paul M.

    2015-01-01

    Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the “DICCCOL” framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all “DICCCOLs” as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 “heritable DICCCOLs” whose connectivity was genetically influenced (a2>1%); half of them showed significant heritability (a2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies. PMID:26413210

  12. Genetic control of soybean seed isoflavone content: importance of statistical model and epistasis in complex traits.

    PubMed

    Gutierrez-Gonzalez, Juan Jose; Wu, Xiaolei; Zhang, Juan; Lee, Jeong-Dong; Ellersieck, Mark; Shannon, J Grover; Yu, Oliver; Nguyen, Henry T; Sleper, David A

    2009-10-01

    A major objective for geneticists is to decipher genetic architecture of traits associated with agronomic importance. However, a majority of such traits are complex, and their genetic dissection has been traditionally hampered not only by the number of minor-effect quantitative trait loci (QTL) but also by genome-wide interacting loci with little or no individual effect. Soybean (Glycine max [L.] Merr.) seed isoflavonoids display a broad range of variation, even in genetically stabilized lines that grow in a fixed environment, because their synthesis and accumulation are affected by many biotic and abiotic factors. Due to this complexity, isoflavone QTL mapping has often produced conflicting results especially with variable growing conditions. Herein, we comparatively mapped soybean seed isoflavones genistein, daidzein, and glycitein by using several of the most commonly used mapping approaches: interval mapping, composite interval mapping, multiple interval mapping and a mixed-model based composite interval mapping. In total, 26 QTLs, including many novel regions, were found bearing additive main effects in a population of RILs derived from the cross between Essex and PI 437654. Our comparative approach demonstrates that statistical mapping methodologies are crucial for QTL discovery in complex traits. Despite a previous understanding of the influence of additive QTL on isoflavone production, the role of epistasis is not well established. Results indicate that epistasis, although largely dependent on the environment, is a very important genetic component underlying seed isoflavone content, and suggest epistasis as a key factor causing the observed phenotypic variability of these traits in diverse environments. PMID:19626310

  13. Additive influence of genetic predisposition and conventional risk factors in the incidence of coronary heart disease: a population-based study in Greece

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An additive genetic risk score (GRS) for coronary heart disease (CHD) has previously been associated with incident CHD in the population-based Greek European Prospective Investigation into Cancer and nutrition (EPIC) cohort. In this study, we explore GRS-‘environment’ joint actions on CHD for severa...

  14. Transgenic animal models of neurodegeneration based on human genetic studies

    PubMed Central

    Richie, Christopher T.; Hoffer, Barry J.; Airavaara, Mikko

    2011-01-01

    The identification of genes linked to neurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD) and Parkinson's disease (PD) has led to the development of animal models for studying mechanism and evaluating potential therapies. None of the transgenic models developed based on disease-associated genes have been able to fully recapitulate the behavioral and pathological features of the corresponding disease. However, there has been enormous progress made in identifying potential therapeutic targets and understanding some of the common mechanisms of neurodegeneration. In this review, we will discuss transgenic animal models for AD, ALS, HD and PD that are based on human genetic studies. All of the diseases discussed have active or complete clinical trials for experimental treatments that benefited from transgenic models of the disease. PMID:20931247

  15. Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops

    PubMed Central

    Ru, Sushan; Hardner, Craig; Carter, Patrick A; Evans, Kate; Main, Dorrie; Peace, Cameron

    2016-01-01

    Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations—known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available. PMID:27148453

  16. Modeling monthly pan evaporations using fuzzy genetic approach

    NASA Astrophysics Data System (ADS)

    Kişi, Özgür; Tombul, Mustafa

    2013-01-01

    SummaryThis study investigates the ability of fuzzy genetic (FG) approach in estimation of monthly pan evaporations. Various monthly climatic data, that are, solar radiation, air temperature, relative humidity and wind speed from two stations, Antalya and Mersin, in Mediterranean Region of Turkey, were used as inputs to the FG technique so as to estimate monthly pan evaporations. In the first part of the study, FG models were compared with neuro-fuzzy (ANFIS), artificial neural networks (ANNs) and Stephens-Stewart (SS) methods in estimating pan evaporations of Antalya and Mersin stations, separately. Comparison of the models revealed that the FG models generally performed better than the ANFIS, ANN and SS models. In the second part of the study, models were compared to each other in two different applications. In the first application the input data of Antalya Station were used as inputs to the models to estimate pan evaporation data of Mersin Station. The pan evaporation data of Mersin Station were estimated using the input data of Antalya and Mersin stations in the second application. Comparison results indicated that the FG models performed better than the ANFIS and ANN models. Comparison of the accuracy of the applied models in estimating total pan evaporations showed that the FG model provided the closest estimate. It was concluded that monthly pan evaporations could be successfully estimated by the FG approach.

  17. Random regression models to estimate genetic parameters for test-day milk yield in Brazilian Murrah buffaloes.

    PubMed

    Sesana, R C; Bignardi, A B; Borquis, R R A; El Faro, L; Baldi, F; Albuquerque, L G; Tonhati, H

    2010-10-01

    The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo's test-day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test-day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from -0.07 (second with eighth week) to -0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes. PMID:20831561

  18. Suspended sediment modeling using genetic programming and soft computing techniques

    NASA Astrophysics Data System (ADS)

    Kisi, Ozgur; Dailr, Ali Hosseinzadeh; Cimen, Mesut; Shiri, Jalal

    2012-07-01

    SummaryModeling suspended sediment load is an important factor in water resources engineering as it crucially affects the design and management of water resources structures. In this study the genetic programming (GP) technique was applied for estimating the daily suspended sediment load in two stations in Cumberland River in U.S. Daily flow and sediment data from 1972 to 1989 were used to train and test the applied genetic programming models. The effect of various GP operators on sediment load estimation was investigated. The optimal fitness function, operator functions, linking function and learning algorithm were obtained for modeling daily suspended sediment. The GP estimates were compared with those of the Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Networks (ANNs) and Support Vector Machine (SVM) results, in term of coefficient of determination, mean absolute error, coefficient of residual mass and variance accounted for. The comparison results indicated that the GP is superior to the ANFIS, ANN and SVM models in estimating daily suspended sediment load.

  19. Random regression models for the estimation of genetic and environmental covariance functions for growth traits in Santa Ines sheep.

    PubMed

    Sarmento, J L R; Torres, R A; Sousa, W H; Lôbo, R N B; Albuquerque, L G; Lopes, P S; Santos, N P S; Bignard, A B

    2016-01-01

    Polynomial functions of different orders were used to model random effects associated with weight of Santa Ines sheep from birth to 196 days. Fixed effects included in the models were contemporary groups, age of ewe at lambing, and fourth-order Legendre polynomials for age to represent the average growth curve. In the random part, functions of different orders were included to model variances associated with direct additive and maternal genetic effects and with permanent environmental effects of the animal and mother. Residual variance was fitted by a sixth-order ordinary polynomial for age. The higher the order of the functions, the better the model fit the data. According to the Akaike information criterion and likelihood ratio test, a continuous function of order, five, five, seven, and three for direct additive genetic, maternal genetic, animal permanent environmental, and maternal permanent environmental effects (k = 5573), respectively, was sufficient to model changes in (co)variances with age. However, a more parsimonious model of order three, three, five, and three (k = 3353) was suggested based on Schwarz's Bayesian information criterion for the same effects. Since it was a more flexible model, model k = 5573 provided inconsistent genetic parameter estimates when compared to the biologically expected result. Predicted breeding values obtained with models k = 3353 and k = 5573 differed, especially at young ages. Model k = 3353 adequately fit changes in variances and covariances with time, and may be used to describe changes in variances with age in the Santa Ines sheep studied. PMID:27323203

  20. The ontology of genetic susceptibility factors (OGSF) and its application in modeling genetic susceptibility to vaccine adverse events

    PubMed Central

    2014-01-01

    Background Due to human variations in genetic susceptibility, vaccination often triggers adverse events in a small population of vaccinees. Based on our previous work on ontological modeling of genetic susceptibility to disease, we developed an Ontology of Genetic Susceptibility Factors (OGSF), a biomedical ontology in the domain of genetic susceptibility and genetic susceptibility factors. The OGSF framework was then applied in the area of vaccine adverse events (VAEs). Results OGSF aligns with the Basic Formal Ontology (BFO). OGSF defines ‘genetic susceptibility’ as a subclass of BFO:disposition and has a material basis ‘genetic susceptibility factor’. The ‘genetic susceptibility to pathological bodily process’ is a subclasses of ‘genetic susceptibility’. A VAE is a type of pathological bodily process. OGSF represents different types of genetic susceptibility factors including various susceptibility alleles (e.g., SNP and gene). A general OGSF design pattern was developed to represent genetic susceptibility to VAE and associated genetic susceptibility factors using experimental results in genetic association studies. To test and validate the design pattern, two case studies were populated in OGSF. In the first case study, human gene allele DBR*15:01 is susceptible to influenza vaccine Pandemrix-induced Multiple Sclerosis. The second case study reports genetic susceptibility polymorphisms associated with systemic smallpox VAEs. After the data of the Case Study 2 were represented using OGSF-based axioms, SPARQL was successfully developed to retrieve the susceptibility factors stored in the populated OGSF. A network of data from the Case Study 2 was constructed by using ontology terms and individuals as nodes and ontology relations as edges. Different social network analys is (SNA) methods were then applied to verify core OGSF terms. Interestingly, a SNA hub analysis verified all susceptibility alleles of SNPs and a SNA closeness analysis verified

  1. Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: comparing meta and mega analytical approaches for data pooling

    PubMed Central

    Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E.; Mandl, René C.; Almasy, Laura; Booth, Tom; Brouwer, Rachel M.; Curran, Joanne E.; de Zubicaray, Greig I.; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T.; Hong, L. Elliot; Landman, Bennett A.; Lemaitre, Hervé; Lopez, Lorna; Martin, Nicholas G.; McMahon, Katie L.; Mitchell, Braxton D.; Olvera, Rene L.; Peterson, Charles P.; Starr, John M.; Sussmann, Jessika E.; Toga, Arthur W.; Wardlaw, Joanna M.; Wright, Margaret J.; Wright, Susan N.; Bastin, Mark E.; McIntosh, Andrew M.; Boomsma, Dorret I.; Kahn, René S.; den Braber, Anouk; de Geus, Eco JC; Deary, Ian J.; Hulshoff Pol, Hilleke E.; Williamson, Douglas E.; Blangero, John; van ’t Ent, Dennis; Thompson, Paul M.; Glahn, David C.

    2014-01-01

    Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9–85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large “mega-family”. We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. PMID:24657781

  2. Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling.

    PubMed

    Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E; Mandl, René C; Almasy, Laura; Booth, Tom; Brouwer, Rachel M; Curran, Joanne E; de Zubicaray, Greig I; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T; Hong, L Elliot; Landman, Bennett A; Lemaitre, Hervé; Lopez, Lorna M; Martin, Nicholas G; McMahon, Katie L; Mitchell, Braxton D; Olvera, Rene L; Peterson, Charles P; Starr, John M; Sussmann, Jessika E; Toga, Arthur W; Wardlaw, Joanna M; Wright, Margaret J; Wright, Susan N; Bastin, Mark E; McIntosh, Andrew M; Boomsma, Dorret I; Kahn, René S; den Braber, Anouk; de Geus, Eco J C; Deary, Ian J; Hulshoff Pol, Hilleke E; Williamson, Douglas E; Blangero, John; van 't Ent, Dennis; Thompson, Paul M; Glahn, David C

    2014-07-15

    Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. PMID:24657781

  3. Additive Manufacturing Modeling and Simulation A Literature Review for Electron Beam Free Form Fabrication

    NASA Technical Reports Server (NTRS)

    Seufzer, William J.

    2014-01-01

    Additive manufacturing is coming into industrial use and has several desirable attributes. Control of the deposition remains a complex challenge, and so this literature review was initiated to capture current modeling efforts in the field of additive manufacturing. This paper summarizes about 10 years of modeling and simulation related to both welding and additive manufacturing. The goals were to learn who is doing what in modeling and simulation, to summarize various approaches taken to create models, and to identify research gaps. Later sections in the report summarize implications for closed-loop-control of the process, implications for local research efforts, and implications for local modeling efforts.

  4. Landscape models for nuclear genetic diversity and genetic structure in white-footed mice (Peromyscus leucopus)

    PubMed Central

    Taylor, Z S; Hoffman, S M G

    2014-01-01

    Dramatic changes in the North American landscape over the last 12 000 years have shaped the genomes of the small mammals, such as the white-footed mouse (Peromyscus leucopus), which currently inhabit the region. However, very recent interactions of populations with each other and the environment are expected to leave the most pronounced signature on rapidly evolving nuclear microsatellite loci. We analyzed landscape characteristics and microsatellite markers of P. leucopus populations along a transect from southern Ohio to northern Michigan, in order to evaluate hypotheses about the spatial distribution of genetic heterogeneity. Genetic diversity increased to the north and was best approximated by a single-variable model based on habitat availability within a 0.5-km radius of trapping sites. Interpopulation differentiation measured by clustering analysis was highly variable and not significantly related to latitude or habitat availability. Interpopulation differentiation measured as FST values and chord distance was correlated with the proportion of habitat intervening, but was best explained by agricultural distance and by latitude. The observed gradients in diversity and interpopulation differentiation were consistent with recent habitat availability being the major constraint on effective population size in this system, and contradicted the predictions of both the postglacial expansion and core-periphery hypotheses. PMID:24448564

  5. Simplifying clinical use of the genetic risk prediction model BRCAPRO.

    PubMed

    Biswas, Swati; Atienza, Philamer; Chipman, Jonathan; Hughes, Kevin; Barrera, Angelica M Gutierrez; Amos, Christopher I; Arun, Banu; Parmigiani, Giovanni

    2013-06-01

    Health care providers need simple tools to identify patients at genetic risk of breast and ovarian cancers. Genetic risk prediction models such as BRCAPRO could fill this gap if incorporated into Electronic Medical Records or other Health Information Technology solutions. However, BRCAPRO requires potentially extensive information on the counselee and her family history. Thus, it may be useful to provide simplified version(s) of BRCAPRO for use in settings that do not require exhaustive genetic counseling. We explore four simplified versions of BRCAPRO, each using less complete information than the original model. BRCAPROLYTE uses information on affected relatives only up to second degree. It is in clinical use but has not been evaluated. BRCAPROLYTE-Plus extends BRCAPROLYTE by imputing the ages of unaffected relatives. BRCAPROLYTE-Simple reduces the data collection burden associated with BRCAPROLYTE and BRCAPROLYTE-Plus by not collecting the family structure. BRCAPRO-1Degree only uses first-degree affected relatives. We use data on 2,713 individuals from seven sites of the Cancer Genetics Network and MD Anderson Cancer Center to compare these simplified tools with the Family History Assessment Tool (FHAT) and BRCAPRO, with the latter serving as the benchmark. BRCAPROLYTE retains high discrimination; however, because it ignores information on unaffected relatives, it overestimates carrier probabilities. BRCAPROLYTE-Plus and BRCAPROLYTE-Simple provide better calibration than BRCAPROLYTE, so they have higher specificity for similar values of sensitivity. BRCAPROLYTE-Plus performs slightly better than BRCAPROLYTE-Simple. The Areas Under the ROC curve are 0.783 (BRCAPRO), 0.763 (BRCAPROLYTE), 0.772 (BRCAPROLYTE-Plus), 0.773 (BRCAPROLYTE-Simple), 0.728 (BRCAPRO-1Degree), and 0.745 (FHAT). The simpler versions, especially BRCAPROLYTE-Plus and BRCAPROLYTE-Simple, lead to only modest loss in overall discrimination compared to BRCAPRO in this dataset. Thus, we conclude that

  6. Accelerating Cancer Modeling with RNAi and Nongermline Genetically Engineered Mouse Models

    PubMed Central

    Livshits, Geulah; Lowe, Scott W.

    2014-01-01

    For more than two decades, genetically engineered mouse models have been key to our mechanistic understanding of tumorigenesis and cancer progression. Recently, the massive quantity of data emerging from cancer genomics studies has demanded a corresponding increase in the efficiency and throughput of in vivo models for functional testing of putative cancer genes. Already a mainstay of cancer research, recent innovations in RNA interference (RNAi) technology have extended its utility for studying gene function and genetic interactions, enabling tissue-specific, inducible and reversible gene silencing in vivo. Concurrent advances in embryonic stem cell (ESC) culture and genome engineering have accelerated several steps of genetically engineered mouse model production and have facilitated the incorporation of RNAi technology into these models. Here, we review the current state of these technologies and examine how their integration has the potential to dramatically enhance the throughput and capabilities of animal models for cancer. PMID:24184755

  7. A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection

    PubMed Central

    Sale, Mark; Sherer, Eric A

    2015-01-01

    The current algorithm for selecting a population pharmacokinetic/pharmacodynamic model is based on the well-established forward addition/backward elimination method. A central strength of this approach is the opportunity for a modeller to continuously examine the data and postulate new hypotheses to explain observed biases. This algorithm has served the modelling community well, but the model selection process has essentially remained unchanged for the last 30 years. During this time, more robust approaches to model selection have been made feasible by new technology and dramatic increases in computation speed. We review these methods, with emphasis on genetic algorithm approaches and discuss the role these methods may play in population pharmacokinetic/pharmacodynamic model selection. PMID:23772792

  8. Modeling AEC-New approaches to study rare genetic disorders.

    PubMed

    Koch, Peter J; Dinella, Jason; Fete, Mary; Siegfried, Elaine C; Koster, Maranke I

    2014-10-01

    Ankyloblepharon-ectodermal defects-cleft lip/palate (AEC) syndrome is a rare monogenetic disorder that is characterized by severe abnormalities in ectoderm-derived tissues, such as skin and its appendages. A major cause of morbidity among affected infants is severe and chronic skin erosions. Currently, supportive care is the only available treatment option for AEC patients. Mutations in TP63, a gene that encodes key regulators of epidermal development, are the genetic cause of AEC. However, it is currently not clear how mutations in TP63 lead to the various defects seen in the patients' skin. In this review, we will discuss current knowledge of the AEC disease mechanism obtained by studying patient tissue and genetically engineered mouse models designed to mimic aspects of the disorder. We will then focus on new approaches to model AEC, including the use of patient cells and stem cell technology to replicate the disease in a human tissue culture model. The latter approach will advance our understanding of the disease and will allow for the development of new in vitro systems to identify drugs for the treatment of skin erosions in AEC patients. Further, the use of stem cell technology, in particular induced pluripotent stem cells (iPSC), will enable researchers to develop new therapeutic approaches to treat the disease using the patient's own cells (autologous keratinocyte transplantation) after correction of the disease-causing mutations. PMID:24665072

  9. A Review of Modeling Techniques for Genetic Regulatory Networks

    PubMed Central

    Yaghoobi, Hanif; Haghipour, Siyamak; Hamzeiy, Hossein; Asadi-Khiavi, Masoud

    2012-01-01

    Understanding the genetic regulatory networks, the discovery of interactions between genes and understanding regulatory processes in a cell at the gene level are the major goals of system biology and computational biology. Modeling gene regulatory networks and describing the actions of the cells at the molecular level are used in medicine and molecular biology applications such as metabolic pathways and drug discovery. Modeling these networks is also one of the important issues in genomic signal processing. After the advent of microarray technology, it is possible to model these networks using time–series data. In this paper, we provide an extensive review of methods that have been used on time–series data and represent the features, advantages and disadvantages of each. Also, we classify these methods according to their nature. A parallel study of these methods can lead to the discovery of new synthetic methods or improve previous methods. PMID:23493097

  10. Modelling of Genetically Engineered Microorganisms Introduction in Closed Artificial Microcosms

    NASA Astrophysics Data System (ADS)

    Pechurkin, N. S.; Brilkov, A. V.; Ganusov, V. V.; Kargatova, T. V.; Maksimova, E. E.; Popova, L. Yu.

    1999-01-01

    The possibility of introducing genetically engineered microorganisms (GEM) into simple biotic cycles of laboratory water microcosms was investigated. The survival of the recombinant strain Escherichia coli Z905 (Apr, Lux+) in microcosms depends on the type of model ecosystems. During the absence of algae blooming in the model ecosystem, the part of plasmid-containing cells E. coli decreased fast, and the structure of the plasmid was also modified. In conditions of algae blooming (Ankistrodesmus sp.) an almost total maintenance of plasmid-containing cells was observed in E.coli population. A mathematics model of GEM's behavior in water ecosystems with different level of complexity has been formulated. Mechanisms causing the difference in luminescent exhibition of different species are discussed, and attempts are made to forecast the GEM's behavior in water ecosystems.

  11. Genetic Diseases and Genetic Determinism Models in French Secondary School Biology Textbooks

    ERIC Educational Resources Information Center

    Castera, Jeremy; Bruguiere, Catherine; Clement, Pierre

    2008-01-01

    The presentation of genetic diseases in French secondary school biology textbooks is analysed to determine the major conceptions taught in the field of human genetics. References to genetic diseases, and the processes by which they are explained (monogeny, polygeny, chromosomal anomaly and environmental influence) are studied in recent French…

  12. Relationship between obesity phenotypes and genetic determinants in a mouse model for juvenile obesity.

    PubMed

    Brockmann, Gudrun A; Schäfer, Nadine; Hesse, Claudia; Heise, Sebastian; Neuschl, Christina; Wagener, Asja; Churchill, Gary A; Li, Renhua

    2013-09-16

    Obesity, a state of imbalance between lean mass and fat mass, is important for the etiology of diseases affected by the interplay of multiple genetic and environmental factors. Although genome-wide association studies have repeatedly associated genes with obesity and body weight, the mechanisms underlying the interaction between the muscle and adipose tissues remain unknown. Using 351 mice (at 10 wk of age) of an intercross population between Berlin Fat Mouse Inbred (BFMI) and C57BL/6NCrl (B6N) mice, we examined the causal relationships between genetic variations and multiple traits: body lean mass and fat mass, adipokines, and bone mineral density. Furthermore, evidence from structural equation modeling suggests causality among these traits. In the BFMI model, juvenile obesity affects lean mass and impairs bone mineral density via adipokines secreted from the white adipose tissues. While previous studies have indicated that lean mass has a causative effect on adiposity, in the Berlin Fat Mouse model that has been selected for juvenile obesity (at 9 wk of age) for >90 generations, however, the causality is switched from fat mass to lean mass. In addition, linkage studies and statistical modeling have indicated that quantitative trait loci on chromosomes 5 and 6 affect both lean mass and fat mass. These lines of evidence indicate that the muscle and adipose tissues interact with one another and the interaction is modulated by genetic variations that are shaped by selections. Experimental examinations are necessary to verify the biological role of the inferred causalities. PMID:23922126

  13. Using Epidemiological Models and Genetic Selection to Identify Theoretical Opportunities to Reduce Disease Impact

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Selection for disease resistance is a contemporary topic with developing approaches for genetic improvement. Merging the sciences of genetic selection and epidemiology is essential to identify selection schemes to enhance disease resistance. Epidemiological models can identify theoretical opportuni...

  14. Multiprocessing and Correction Algorithm of 3D-models for Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Anamova, R. R.; Zelenov, S. V.; Kuprikov, M. U.; Ripetskiy, A. V.

    2016-07-01

    This article addresses matters related to additive manufacturing preparation. A layer-by-layer model presentation was developed on the basis of a routing method. Methods for correction of errors in the layer-by-layer model presentation were developed. A multiprocessing algorithm for forming an additive manufacturing batch file was realized.

  15. Validation analysis of probabilistic models of dietary exposure to food additives.

    PubMed

    Gilsenan, M B; Thompson, R L; Lambe, J; Gibney, M J

    2003-10-01

    The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above 'true' additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (2(3)) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above 'true' intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty. PMID:14555358

  16. Practical implications for genetic modeling in the genomics era.

    PubMed

    VanRaden, P M

    2016-03-01

    Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, including genetic by environmental interactions and correlations among traits, and accounting for nonadditive inheritance or nonnormal distributions. Data include phenotypes and pedigrees during the last century and genotypes within the last decade. The genomic data can include single nucleotide polymorphisms, quantitative trait loci, insertions, deletions, and haplotypes. Subsets must be selected to reduce computation because total numbers of variants that can be imputed have increased rapidly from thousands to millions. Current computation using 60,671 markers takes just a few days. Nonlinear models can account for the nonnormal distribution of genomic effects, but reliability is usually better than that of linear models only for traits influenced by major genes. Numbers of genotyped animals have also increased rapidly in the joint North American database from a few thousand in 2009 to over 1 million in 2015. Most are young females and will contribute to estimating allele effects in the future, but only about 150,000 have phenotypes so far. Genomic preselection can bias traditional animal models because Mendelian sampling of phenotyped progeny and mates is no longer expected to average zero; however, estimates of bias are small in current US data. Single-step models that combine pedigree and genomic relationships can account for preselection, but approximations are required for affordable computation. Traditional animal models may include all breeds and crossbreds, but most genomic evaluations are still computed within breed. Models that include inbreeding, heterosis, dominance, and interactions can improve predictions for individual matings. Multitrait genomic models may

  17. Genetics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The genus Capsicum represents one of several well characterized Solanaceous genera. A wealth of classical and molecular genetics research is available for the genus. Information gleaned from its cultivated relatives, tomato and potato, provide further insight for basic and applied studies. Early ...

  18. Genetics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Maintaining genetic variation in wild populations of Arctic organisms is fundamental to the long-term persistence of high latitude biodiversity. Variability is important because it provides options for species to respond to changing environmental conditions and novel challenges such as emerging path...

  19. Tackling intraspecific genetic structure in distribution models better reflects species geographical range.

    PubMed

    Marcer, Arnald; Méndez-Vigo, Belén; Alonso-Blanco, Carlos; Picó, F Xavier

    2016-04-01

    Genetic diversity provides insight into heterogeneous demographic and adaptive history across organisms' distribution ranges. For this reason, decomposing single species into genetic units may represent a powerful tool to better understand biogeographical patterns as well as improve predictions of the effects of GCC (global climate change) on biodiversity loss. Using 279 georeferenced Iberian accessions, we used classes of three intraspecific genetic units of the annual plant Arabidopsis thaliana obtained from the genetic analyses of nuclear SNPs (single nucleotide polymorphisms), chloroplast SNPs, and the vernalization requirement for flowering. We used SDM (species distribution models), including climate, vegetation, and soil data, at the whole-species and genetic-unit levels. We compared model outputs for present environmental conditions and with a particularly severe GCC scenario. SDM accuracy was high for genetic units with smaller distribution ranges. Kernel density plots identified the environmental variables underpinning potential distribution ranges of genetic units. Combinations of environmental variables accounted for potential distribution ranges of genetic units, which shrank dramatically with GCC at almost all levels. Only two genetic clusters increased their potential distribution ranges with GCC. The application of SDM to intraspecific genetic units provides a detailed picture on the biogeographical patterns of distinct genetic groups based on different genetic criteria. Our approach also allowed us to pinpoint the genetic changes, in terms of genetic background and physiological requirements for flowering, that Iberian A. thaliana may experience with a GCC scenario applying SDM to intraspecific genetic units. PMID:27066224

  20. Intrauterine diabetic environment confers risks for type 2 diabetes mellitus and obesity in the offspring, in addition to genetic susceptibility.

    PubMed

    Dabelea, D; Pettitt, D J

    2001-01-01

    Numerous studies have reported that offspring whose mothers had type 2 diabetes mellitus (DM) are more likely to develop type 2 DM, impaired glucose tolerance, and obesity at an early age than offspring whose fathers had DM. Exposure to the diabetic intrauterine environment has been shown to be an important risk factor for all these conditions. To what extent transmission of type 2 DM from mother to offspring is the effect of genetic inheritance and to what extent it is the long-term consequence of exposure to maternal hyperglycemia is still uncertain. There are, of course, interactions between the diabetic intrauterine environment and genetics. Several data in experimental animals as well as in humans suggest, however, that exposure of the fetus to the mother's DM confers a risk for type 2 DM and obesity that is above any genetically transmitted susceptibility. In the Pima Indian population much of the increase in childhood type 2 DM can be attributed to the diabetic intrauterine environment. This suggests that intensive glucose control during pregnancy might have extended beneficial effects, contributing to a decrease in the prevalence of childhood type 2 DM. PMID:11592564

  1. Calibration of Uncertainty Analysis of the SWAT Model Using Genetic Algorithms and Bayesian Model Averaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this paper, the Genetic Algorithms (GA) and Bayesian model averaging (BMA) were combined to simultaneously conduct calibration and uncertainty analysis for the Soil and Water Assessment Tool (SWAT). In this hybrid method, several SWAT models with different structures are first selected; next GA i...

  2. Exploring Middle School Students' Understanding of Three Conceptual Models in Genetics

    NASA Astrophysics Data System (ADS)

    Bresler Freidenreich, Hava; Golan Duncan, Ravit; Shea, Nicole

    2011-11-01

    Genetics is the cornerstone of modern biology and a critical aspect of scientific literacy. Research has shown, however, that many high school graduates lack fundamental understandings in genetics necessary to make informed decisions about issues and emerging technologies in this domain, such as genetic screening, genetically modified foods, etc. Genetic literacy entails understanding three interrelated models: a genetic model that describes patterns of genetic inheritance, a meiotic model that describes the process by which genes are segregated into sex cells, and a molecular model that describes the mechanisms that link genotypes to phenotypes within an individual. Currently, much of genetics instruction, especially in terms of the molecular model, occurs at the high school level, and we know little about the ways in which middle school students can reason about these models. Furthermore, we do not know the extent to which carefully designed instruction can help younger students develop coherent and interrelated understandings in genetics. In this paper, we discuss a research study aimed at elucidating middle school students' abilities to reason about the three genetic models. As part of our research, we designed an eight-week inquiry unit that was implemented in a combined sixth- to eighth-grade science classroom. We describe our instructional design and report results based on an analysis of written assessments, clinical interviews, and artifacts of the unit. Our findings suggest that middle school students are able to successfully reason about all three genetic models.

  3. An Intelligent Model for Pairs Trading Using Genetic Algorithms

    PubMed Central

    Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

    2015-01-01

    Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice. PMID:26339236

  4. An Intelligent Model for Pairs Trading Using Genetic Algorithms.

    PubMed

    Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

    2015-01-01

    Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice. PMID:26339236

  5. An uncertain revolution: why the rise of a genetic model of mental illness has not increased tolerance.

    PubMed

    Schnittker, Jason

    2008-11-01

    This study uses the 2006 replication of the 1996 General Social Survey Mental Health Module to explore trends in public beliefs about mental illness in the USA. Drawing on three models related to the framing of genetic arguments in popular media, the study attempts to address why tolerance of the mentally ill has not increased, despite the growing popularity of a biomedical view. The key to resolving this paradox lies in understanding how genetic arguments interact with other beliefs about mental illness, as well as the complex ideational implications of genetic frameworks. Genetic arguments have contingent relationships with tolerance. When applied to schizophrenia, genetic arguments are positively associated with fears regarding violence. Indeed, in this regard, attributing schizophrenia to genes is no different from attributing schizophrenia to bad character. However, when applied to depression, genetic arguments are positively associated with social acceptance. In addition to these contingencies, genetic explanations have discontinuous relationships with beliefs regarding treatment. Although genetic arguments are positively associated with recommending medical treatment, they are not associated with the perceived likelihood of improvement. The net result of these assorted relationships is little change in overall levels of tolerance over time. Because of the blunt nature of the forces propelling a biomedical view--including the growing popularity of psychiatric medications--altering beliefs about the etiology of mental illness is unlikely, on its own, to increase tolerance. PMID:18703264

  6. An introduction to modeling longitudinal data with generalized additive models: applications to single-case designs.

    PubMed

    Sullivan, Kristynn J; Shadish, William R; Steiner, Peter M

    2015-03-01

    Single-case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time in both the presence and absence of treatment. This article introduces a statistical technique for analyzing SCD data that has not been much used in psychological and educational research: generalized additive models (GAMs). In parametric regression, the researcher must choose a functional form to impose on the data, for example, that trend over time is linear. GAMs reverse this process by letting the data inform the choice of functional form. In this article we review the problem that trend poses in SCDs, discuss how current SCD analytic methods approach trend, describe GAMs as a possible solution, suggest a GAM model testing procedure for examining the presence of trend in SCDs, present a small simulation to show the statistical properties of GAMs, and illustrate the procedure on 3 examples of different lengths. Results suggest that GAMs may be very useful both as a form of sensitivity analysis for checking the plausibility of assumptions about trend and as a primary data analysis strategy for testing treatment effects. We conclude with a discussion of some problems with GAMs and some future directions for research on the application of GAMs to SCDs. PMID:24885341

  7. Modeling variation in early life mortality in the western lowland gorilla: Genetic, maternal and other effects.

    PubMed

    Ahsan, Monica H; Blomquist, Gregory E

    2015-06-01

    Uncovering sources of variation in gorilla infant mortality informs conservation and life history research efforts. The international studbook for the western lowland gorilla provides information on a sample of captive gorillas large enough for which to analyze genetic, maternal, and various other effects on early life mortality in this critically endangered species. We assess the importance of variables such as sex, maternal parity, paternal age, and hand rearing with regard to infant survival. We also quantify the proportions of variation in mortality influenced by heritable variation and maternal effects from these pedigree and survival data using variance component estimation. Markov chain Monte Carlo simulations of generalized linear mixed models produce variance component distributions in an animal model framework that employs all pedigree information. Two models, one with a maternal identity component and one with both additive genetic and maternal identity components, estimate variance components for different age classes during the first 2 years of life. This is informative of the extent to which mortality risk factors change over time during gorilla infancy. Our results indicate that gorilla mortality is moderately heritable with the strongest genetic influence just after birth. Maternal effects are most important during the first 6 months of life. Interestingly, hand-reared infants have lower mortality for the first 6 months of life. Aside from hand rearing, we found other predictors commonly used in studies of primate infant mortality to have little influence in these gorilla data. PMID:25809396

  8. Quantitative genetic analysis of brain size variation in sticklebacks: support for the mosaic model of brain evolution

    PubMed Central

    Noreikiene, Kristina; Herczeg, Gábor; Gonda, Abigél; Balázs, Gergely; Husby, Arild; Merilä, Juha

    2015-01-01

    The mosaic model of brain evolution postulates that different brain regions are relatively free to evolve independently from each other. Such independent evolution is possible only if genetic correlations among the different brain regions are less than unity. We estimated heritabilities, evolvabilities and genetic correlations of relative size of the brain, and its different regions in the three-spined stickleback (Gasterosteus aculeatus). We found that heritabilities were low (average h2 = 0.24), suggesting a large plastic component to brain architecture. However, evolvabilities of different brain parts were moderate, suggesting the presence of additive genetic variance to sustain a response to selection in the long term. Genetic correlations among different brain regions were low (average rG = 0.40) and significantly less than unity. These results, along with those from analyses of phenotypic and genetic integration, indicate a high degree of independence between different brain regions, suggesting that responses to selection are unlikely to be severely constrained by genetic and phenotypic correlations. Hence, the results give strong support for the mosaic model of brain evolution. However, the genetic correlation between brain and body size was high (rG = 0.89), suggesting a constraint for independent evolution of brain and body size in sticklebacks. PMID:26108633

  9. Effect of keishibukuryogan on genetic and dietary obesity models.

    PubMed

    Gao, Fengying; Yokoyama, Satoru; Fujimoto, Makoto; Tsuneyama, Koichi; Saiki, Ikuo; Shimada, Yutaka; Hayakawa, Yoshihiro

    2015-01-01

    Obesity has been recognized as one of the most important risk factors for a variety of chronic diseases, such as diabetes, hypertension/cardiovascular diseases, steatosis/hepatitis, and cancer. Keishibukuryogan (KBG, Gui Zhi Fu Ling Wan in Chinese) is a traditional Chinese/Japanese (Kampo) medicine that has been known to improve blood circulation and is also known for its anti-inflammatory or scavenging effect. In this study, we evaluated the effect of KBG in two distinct rodent models of obesity driven by either a genetic (SHR/NDmcr-cp rat model) or dietary (high-fat diet-induced mouse obesity model) mechanism. Although there was no significant effect on the body composition in either the SHR rat or the DIO mouse models, KBG treatment significantly decreased the serum level of leptin and liver TG level in the DIO mouse, but not in the SHR rat model. Furthermore, a lower fat deposition in liver and a smaller size of adipocytes in white adipose tissue were observed in the DIO mice treated with KBG. Importantly, we further found downregulation of genes involved in lipid metabolism in the KBG-treated liver, along with decreased liver TG and cholesterol level. Our present data experimentally support in fact that KBG can be an attractive Kampo medicine to improve obese status through a regulation of systemic leptin level and/or lipid metabolism. PMID:25793003

  10. The severity of retinal pathology in homozygous Crb1rd8/rd8 mice is dependent on additional genetic factors

    PubMed Central

    Luhmann, Ulrich F.O.; Carvalho, Livia S.; Holthaus, Sophia-Martha kleine; Cowing, Jill A.; Greenaway, Simon; Chu, Colin J.; Herrmann, Philipp; Smith, Alexander J.; Munro, Peter M.G.; Potter, Paul; Bainbridge, James W.B.; Ali, Robin R.

    2015-01-01

    Understanding phenotype–genotype correlations in retinal degeneration is a major challenge. Mutations in CRB1 lead to a spectrum of autosomal recessive retinal dystrophies with variable phenotypes suggesting the influence of modifying factors. To establish the contribution of the genetic background to phenotypic variability associated with the Crb1rd8/rd8 mutation, we compared the retinal pathology of Crb1rd8/rd8/J inbred mice with that of two Crb1rd8/rd8 lines backcrossed with C57BL/6JOlaHsd mice. Topical endoscopic fundal imaging and scanning laser ophthalmoscopy fundus images of all three Crb1rd8/rd8 lines showed a significant increase in the number of inferior retinal lesions that was strikingly variable between the lines. Optical coherence tomography, semithin, ultrastructural morphology and assessment of inflammatory and vascular marker by immunohistochemistry and quantitative reverse transcriptase-polymerase chain reaction revealed that the lesions were associated with photoreceptor death, Müller and microglia activation and telangiectasia-like vascular remodelling—features that were stable in the inbred, variable in the second, but virtually absent in the third Crb1rd8/rd8 line, even at 12 months of age. This suggests that the Crb1rd8/rd8 mutation is necessary, but not sufficient for the development of these degenerative features. By whole-genome SNP analysis of the genotype–phenotype correlation, a candidate region on chromosome 15 was identified. This may carry one or more genetic modifiers for the manifestation of the retinal pathology associated with mutations in Crb1. This study also provides insight into the nature of the retinal vascular lesions that likely represent a clinical correlate for the formation of retinal telangiectasia or Coats-like vasculopathy in patients with CRB1 mutations that are thought to depend on such genetic modifiers. PMID:25147295

  11. The severity of retinal pathology in homozygous Crb1rd8/rd8 mice is dependent on additional genetic factors.

    PubMed

    Luhmann, Ulrich F O; Carvalho, Livia S; Holthaus, Sophia-Martha Kleine; Cowing, Jill A; Greenaway, Simon; Chu, Colin J; Herrmann, Philipp; Smith, Alexander J; Munro, Peter M G; Potter, Paul; Bainbridge, James W B; Ali, Robin R

    2015-01-01

    Understanding phenotype-genotype correlations in retinal degeneration is a major challenge. Mutations in CRB1 lead to a spectrum of autosomal recessive retinal dystrophies with variable phenotypes suggesting the influence of modifying factors. To establish the contribution of the genetic background to phenotypic variability associated with the Crb1(rd8/rd8) mutation, we compared the retinal pathology of Crb1(rd8/rd8)/J inbred mice with that of two Crb1(rd8/rd8) lines backcrossed with C57BL/6JOlaHsd mice. Topical endoscopic fundal imaging and scanning laser ophthalmoscopy fundus images of all three Crb1(rd8/rd8) lines showed a significant increase in the number of inferior retinal lesions that was strikingly variable between the lines. Optical coherence tomography, semithin, ultrastructural morphology and assessment of inflammatory and vascular marker by immunohistochemistry and quantitative reverse transcriptase-polymerase chain reaction revealed that the lesions were associated with photoreceptor death, Müller and microglia activation and telangiectasia-like vascular remodelling-features that were stable in the inbred, variable in the second, but virtually absent in the third Crb1(rd8/rd8) line, even at 12 months of age. This suggests that the Crb1(rd8/rd8) mutation is necessary, but not sufficient for the development of these degenerative features. By whole-genome SNP analysis of the genotype-phenotype correlation, a candidate region on chromosome 15 was identified. This may carry one or more genetic modifiers for the manifestation of the retinal pathology associated with mutations in Crb1. This study also provides insight into the nature of the retinal vascular lesions that likely represent a clinical correlate for the formation of retinal telangiectasia or Coats-like vasculopathy in patients with CRB1 mutations that are thought to depend on such genetic modifiers. PMID:25147295

  12. Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

    PubMed

    Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

    2016-09-01

    Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that

  13. A new perspective on dark energy modeling via genetic algorithms

    SciTech Connect

    Nesseris, Savvas; García-Bellido, Juan E-mail: juan.garciabellido@uam.es

    2012-11-01

    We use Genetic Algorithms to extract information from several cosmological probes, such as the type Ia supernovae (SnIa), the Baryon Acoustic Oscillations (BAO) and the growth rate of matter perturbations. This is done by implementing a model independent and bias-free reconstruction of the various scales and distances that characterize the data, like the luminosity d{sub L}(z) and the angular diameter distance d{sub A}(z) in the SnIa and BAO data, respectively, or the dependence with redshift of the matter density Ω{sub m}(a) in the growth rate data, fσ{sub 8}(z). These quantities can then be used to reconstruct the expansion history of the Universe, and the resulting Dark Energy (DE) equation of state w(z) in the context of FRW models, or the mass radial function Ω{sub M}(r) in LTB models. In this way, the reconstruction is completely independent of our prior bias. Furthermore, we use this method to test the Etherington relation, ie the well-known relation between the luminosity and the angular diameter distance, η≡d{sub L}(z)/(1+z){sup 2}d{sub A}(z), which is equal to 1 in metric theories of gravity. We find that the present data seem to suggest a 3-σ deviation from one at redshifts z ∼ 0.5. Finally, we present a novel way, within the Genetic Algorithm paradigm, to analytically estimate the errors on the reconstructed quantities by calculating a Path Integral over all possible functions that may contribute to the likelihood. We show that this can be done regardless of the data being correlated or uncorrelated with each other and we also explicitly demonstrate that our approach is in good agreement with other error estimation techniques like the Fisher Matrix approach and the Bootstrap Monte Carlo.

  14. Recent Enhancements to the Genetic Risk Prediction Model BRCAPRO

    PubMed Central

    Mazzola, Emanuele; Blackford, Amanda; Parmigiani, Giovanni; Biswas, Swati

    2015-01-01

    BRCAPRO is a widely used model for genetic risk prediction of breast cancer. It is a function within the R package BayesMendel and is used to calculate the probabilities of being a carrier of a deleterious mutation in one or both of the BRCA genes, as well as the probability of being affected with breast and ovarian cancer within a defined time window. Both predictions are based on information contained in the counselee’s family history of cancer. During the last decade, BRCAPRO has undergone several rounds of successive refinements: the current version is part of release 2.1 of BayesMendel. In this review, we showcase some of the most notable features of the software resulting from these recent changes. We provide examples highlighting each feature, using artificial pedigrees motivated by complex clinical examples. We illustrate how BRCAPRO is a comprehensive software for genetic risk prediction with many useful features that allow users the flexibility to incorporate varying amounts of available information. PMID:25983549

  15. Genetic programming for evolving due-date assignment models in job shop environments.

    PubMed

    Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

    2014-01-01

    Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines. PMID:23614773

  16. Fitting additive hazards models for case-cohort studies: a multiple imputation approach.

    PubMed

    Jung, Jinhyouk; Harel, Ofer; Kang, Sangwook

    2016-07-30

    In this paper, we consider fitting semiparametric additive hazards models for case-cohort studies using a multiple imputation approach. In a case-cohort study, main exposure variables are measured only on some selected subjects, but other covariates are often available for the whole cohort. We consider this as a special case of a missing covariate by design. We propose to employ a popular incomplete data method, multiple imputation, for estimation of the regression parameters in additive hazards models. For imputation models, an imputation modeling procedure based on a rejection sampling is developed. A simple imputation modeling that can naturally be applied to a general missing-at-random situation is also considered and compared with the rejection sampling method via extensive simulation studies. In addition, a misspecification aspect in imputation modeling is investigated. The proposed procedures are illustrated using a cancer data example. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26194861

  17. Genetic structure and bio-climatic modeling support allopatric over parapatric speciation along a latitudinal gradient

    PubMed Central

    2012-01-01

    clusters corresponding to the four recognised species with the additional division of T. speciosissima into populations north and south of the Shoalhaven River valley. Unexpectedly, the northern disjunct population of T. oreades grouped with T. mongaensis and was identified as a hybrid swarm by the Bayesian assignment test implemented in NewHybrids. Present day and LGM environmental niche models differed dramatically, suggesting that distributions of all species had repeatedly expanded and contracted in response to Pleistocene climatic oscillations and confirming strongly marked historical distributional gaps among taxes. Conclusions Genetic structure and bio-climatic modeling results are more consistent with a history of allopatric speciation followed by repeated episodes of secondary contact and localised hybridisation, rather than with parapatric speciation. This study on Telopea shows that the evidence for temporal exclusion of gene flow can be found even outside obvious geographical contexts, and that it is possible to make significant progress towards excluding parapatric speciation as a contributing evolutionary process. PMID:22906180

  18. Sphingolipids and Membrane Biology as Determined from Genetic Models

    PubMed Central

    Rao, Raghavendra Pralhada; Acharya, Jairaj K

    2008-01-01

    The importance of sphingolipids in membrane biology was appreciated early in the twentieth century when several human inborn errors of metabolism were linked to defects in sphingolipid degradation. The past two decades have seen an explosion of information linking sphingolipids with cellular processes. Studies have unraveled mechanistic details of the sphingolipid metabolic pathways, and these findings are being exploited in the development of novel therapies, some now in clinical trials. Pioneering work in yeast has laid the foundation for identifying genes encoding the enzymes of the pathways. The advent of the era of genomics and bioinformatics has led to the identification of homologous genes in other species and the subsequent creation of animal knock-out lines for these genes. Discoveries from these efforts have re-kindled interest in the role of sphingolipids in membrane biology. This review highlights some of the recent advances in understanding sphingolipids’ roles in membrane biology as determined from genetic models. PMID:18035569

  19. Genetic regulation of bone strength: a review of animal model studies

    PubMed Central

    Adams, Douglas J; Ackert-Bicknell, Cheryl L

    2015-01-01

    Population- and family-based studies have established that fragility fracture risk is heritable; yet, the genome-wide association studies published to date have only accounted for a small fraction of the known variation for fracture risk of either the femur or the lumbar spine. Much work has been carried out using animal models toward finding genetic loci that are associated with bone strength. Studies using animal models overcome some of the issues associated with using patient data, but caution is needed when interpreting the results. In this review, we examine the types of tests that have been used for forward genetics mapping in animal models to identify loci and/or genes that regulate bone strength and discuss the limitations of these test methods. In addition, we present a summary of the quantitative trait loci that have been mapped for bone strength in mice, rats and chickens. The majority of these loci co-map with loci for bone size and/or geometry and thus likely dictate strength via modulating bone size. Differences in bone matrix composition have been demonstrated when comparing inbred strains of mice, and these matrix differences may be associated with differences in bone strength. However, additional work is needed to identify loci that act on bone strength at the materials level. PMID:26157577

  20. Uncovering Local Trends in Genetic Effects of Multiple Phenotypes via Functional Linear Models.

    PubMed

    Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Barondess, David A; Tong, Xiaoren; Jadhav, Sneha; Lu, Qing

    2016-04-01

    Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear model approach. In this work we extend previous developments to allow inclusion of multiple traits and adjustment for additional covariates. Our functional approach is unique in that it provides a nuanced depiction of effects and interactions for the variables in the model by representing them as curves varying over a genetic region. We demonstrate flexibility and competitive power of our approach by contrasting its performance with commonly used statistical tools and illustrate its potential for discovery and characterization of genetic architecture of complex traits using sequencing data from the Dallas Heart Study. PMID:27027515

  1. Model suicide vector for containment of genetically engineered microorganisms.

    PubMed

    Bej, A K; Perlin, M H; Atlas, R M

    1988-10-01

    A model suicide vector (pBAP19h), designed for the potential containment of genetically engineered microorganisms, was made by constructing a plasmid with the hok gene, which codes for a lethal polypeptide, under the control of the lac promoter. The vector plasmid also codes for carbenicillin resistance. In the absence of carbenicillin, induction of the hok gene in vitro caused elimination of all detectable cells containing the suicide vector; pBAP19h-free cells of the culture survived and grew exponentially. In the presence of carbenicillin, however, the number of cells containing pBAP19h initially declined after induction of hok but then multiplied exponentially. The surviving cells still had a fully functional hok gene and had apparently developed resistance to the action of the Hok polypeptide. Thus, high selective pressure against the loss of the suicide vector led to a failure of the system. Soil microcosm experiments confirmed the ability of a suicide vector to restrict the growth of a genetically engineered microorganism in the absence of selective pressure against the loss of the plasmid, with 90 to 99% elimination of hok-bearing cells within 24 h of hok induction. However, some pBAP19h-bearing cells survived in the soil microcosms after hok induction. The surviving cells contained an active hok gene but were not capable of normal growth even after elimination of the hok gene; it appears that a mutation that made them Hok resistant also reduced their capacity for membrane functions needed for energy generation and exponential cell growth. Thus, the model suicide vector was shown to be functional in soil as well as in vitro.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:3060017

  2. Nature and nurture: environmental influences on a genetic rat model of depression.

    PubMed

    Mehta-Raghavan, N S; Wert, S L; Morley, C; Graf, E N; Redei, E E

    2016-01-01

    In this study, we sought to learn whether adverse events such as chronic restraint stress (CRS), or 'nurture' in the form of environmental enrichment (EE), could modify depression-like behavior and blood biomarker transcript levels in a genetic rat model of depression. The Wistar Kyoto More Immobile (WMI) is a genetic model of depression that aided in the identification of blood transcriptomic markers, which successfully distinguished adolescent and adult subjects with major depressive disorders from their matched no-disorder controls. Here, we followed the effects of CRS and EE in adult male WMIs and their genetically similar control strain, the Wistar Kyoto Less Immobile (WLI), that does not show depression-like behavior, by measuring the levels of these transcripts in the blood and hippocampus. In WLIs, increased depression-like behavior and transcriptomic changes were present in response to CRS, but in WMIs no behavioral or additive transcriptomic changes occurred. Environmental enrichment decreased both the inherent depression-like behavior in the WMIs and the behavioral difference between WMIs and WLIs, but did not reverse basal transcript level differences between the strains. The inverse behavioral change induced by CRS and EE in the WLIs did not result in parallel inverse expression changes of the transcriptomic markers, suggesting that these behavioral responses to the environment work via separate molecular pathways. In contrast, 'trait' transcriptomic markers with expression differences inherent and unchanging between the strains regardless of the environment suggest that in our model, environmental and genetic etiologies of depression work through independent molecular mechanisms. PMID:27023176

  3. Hcn1 Is a Tremorgenic Genetic Component in a Rat Model of Essential Tremor

    PubMed Central

    Ohno, Yukihiro; Shimizu, Saki; Tatara, Ayaka; Imaoku, Takuji; Ishii, Takahiro; Sasa, Masashi; Serikawa, Tadao; Kuramoto, Takashi

    2015-01-01

    Genetic factors are thought to play a major role in the etiology of essential tremor (ET); however, few genetic changes that induce ET have been identified to date. In the present study, to find genes responsible for the development of ET, we employed a rat model system consisting of a tremulous mutant strain, TRM/Kyo (TRM), and its substrain TRMR/Kyo (TRMR). The TRM rat is homozygous for the tremor (tm) mutation and shows spontaneous tremors resembling human ET. The TRMR rat also carries a homozygous tm mutation but shows no tremor, leading us to hypothesize that TRM rats carry one or more genes implicated in the development of ET in addition to the tm mutation. We used a positional cloning approach and found a missense mutation (c. 1061 C>T, p. A354V) in the hyperpolarization-activated cyclic nucleotide-gated 1 channel (Hcn1) gene. The A354V HCN1 failed to conduct hyperpolarization-activated currents in vitro, implicating it as a loss-of-function mutation. Blocking HCN1 channels with ZD7288 in vivo evoked kinetic tremors in nontremulous TRMR rats. We also found neuronal activation of the inferior olive (IO) in both ZD7288-treated TRMR and non-treated TRM rats and a reduced incidence of tremor in the IO-lesioned TRM rats, suggesting a critical role of the IO in tremorgenesis. A rat strain carrying the A354V mutation alone on a genetic background identical to that of the TRM rats showed no tremor. Together, these data indicate that body tremors emerge when the two mutant loci, tm and Hcn1A354V, are combined in a rat model of ET. In this model, HCN1 channels play an important role in the tremorgenesis of ET. We propose that oligogenic, most probably digenic, inheritance is responsible for the genetic heterogeneity of ET. PMID:25970616

  4. Nature and nurture: environmental influences on a genetic rat model of depression

    PubMed Central

    Mehta-Raghavan, N S; Wert, S L; Morley, C; Graf, E N; Redei, E E

    2016-01-01

    In this study, we sought to learn whether adverse events such as chronic restraint stress (CRS), or ‘nurture' in the form of environmental enrichment (EE), could modify depression-like behavior and blood biomarker transcript levels in a genetic rat model of depression. The Wistar Kyoto More Immobile (WMI) is a genetic model of depression that aided in the identification of blood transcriptomic markers, which successfully distinguished adolescent and adult subjects with major depressive disorders from their matched no-disorder controls. Here, we followed the effects of CRS and EE in adult male WMIs and their genetically similar control strain, the Wistar Kyoto Less Immobile (WLI), that does not show depression-like behavior, by measuring the levels of these transcripts in the blood and hippocampus. In WLIs, increased depression-like behavior and transcriptomic changes were present in response to CRS, but in WMIs no behavioral or additive transcriptomic changes occurred. Environmental enrichment decreased both the inherent depression-like behavior in the WMIs and the behavioral difference between WMIs and WLIs, but did not reverse basal transcript level differences between the strains. The inverse behavioral change induced by CRS and EE in the WLIs did not result in parallel inverse expression changes of the transcriptomic markers, suggesting that these behavioral responses to the environment work via separate molecular pathways. In contrast, ‘trait' transcriptomic markers with expression differences inherent and unchanging between the strains regardless of the environment suggest that in our model, environmental and genetic etiologies of depression work through independent molecular mechanisms. PMID:27023176

  5. A genetic algorithm based molecular modeling technique for RNA stem-loop structures.

    PubMed Central

    Ogata, H; Akiyama, Y; Kanehisa, M

    1995-01-01

    A new modeling technique for arriving at the three dimensional (3-D) structure of an RNA stem-loop has been developed based on a conformational search by a genetic algorithm and the following refinement by energy minimization. The genetic algorithm simultaneously optimizes a population of conformations in the predefined conformational space and generates 3-D models of RNA. The fitness function to be optimized by the algorithm has been defined to reflect the satisfaction of known conformational constraints. In addition to a term for distance constraints, the fitness function contains a term to constrain each local conformation near to a prepared template conformation. The technique has been applied to the two loops of tRNA, the anticodon loop and the T-loop, and has found good models with small root mean square deviations from the crystal structure. Slightly different models have also been found for the anticodon loop. The analysis of a collection of alternative models obtained has revealed statistical features of local variations at each base position. Images PMID:7533901

  6. Teaching Human Genetics with Mustard: Rapid Cycling "Brassica rapa" (Fast Plants Type) as a Model for Human Genetics in the Classroom Laboratory

    ERIC Educational Resources Information Center

    Wendell, Douglas L.; Pickard, Dawn

    2007-01-01

    We have developed experiments and materials to model human genetics using rapid cycling "Brassica rapa", also known as Fast Plants. Because of their self-incompatibility for pollination and the genetic diversity within strains, "B. rapa" can serve as a relevant model for human genetics in teaching laboratory experiments. The experiment presented…

  7. Present-Day Genetic Structure of Atlantic Salmon (Salmo salar) in Icelandic Rivers and Ice-Cap Retreat Models

    PubMed Central

    Olafsson, Kristinn; Pampoulie, Christophe; Hjorleifsdottir, Sigridur; Gudjonsson, Sigurdur; Hreggvidsson, Gudmundur O.

    2014-01-01

    Due to an improved understanding of past climatological conditions, it has now become possible to study the potential concordance between former climatological models and present-day genetic structure. Genetic variability was assessed in 26 samples from different rivers of Atlantic salmon in Iceland (total of 2,352 individuals), using 15 microsatellite loci. F-statistics revealed significant differences between the majority of the populations that were sampled. Bayesian cluster analyses using both prior information and no prior information on sampling location revealed the presence of two distinguishable genetic pools - namely, the Northern (Group 1) and Southern (Group 2) regions of Iceland. Furthermore, the random permutation of different allele sizes among allelic states revealed a significant mutational component to the genetic differentiation at four microsatellite loci (SsaD144, Ssa171, SSsp2201 and SsaF3), and supported the proposition of a historical origin behind the observed variation. The estimated time of divergence, using two different ABC methods, suggested that the observed genetic pattern originated from between the Last Glacial Maximum to the Younger Dryas, which serves as additional evidence of the relative immaturity of Icelandic fish populations, on account of the re-colonisation of this young environment following the Last Glacial Maximum. Additional analyses suggested the presence of several genetic entities which were likely to originate from the original groups detected. PMID:24498283

  8. Genetic Models for the Study of Luteinizing Hormone Receptor Function

    PubMed Central

    Narayan, Prema

    2015-01-01

    The luteinizing hormone/chorionic gonadotropin receptor (LHCGR) is essential for fertility in men and women. LHCGR binds luteinizing hormone (LH) as well as the highly homologous chorionic gonadotropin. Signaling from LHCGR is required for steroidogenesis and gametogenesis in males and females and for sexual differentiation in the male. The importance of LHCGR in reproductive physiology is underscored by the large number of naturally occurring inactivating and activating mutations in the receptor that result in reproductive disorders. Consequently, several genetically modified mouse models have been developed for the study of LHCGR function. They include targeted deletion of LH and LHCGR that mimic inactivating mutations in hormone and receptor, expression of a constitutively active mutant in LHCGR that mimics activating mutations associated with familial male-limited precocious puberty and transgenic models of LH and hCG overexpression. This review summarizes the salient findings from these models and their utility in understanding the physiological and pathological consequences of loss and gain of function in LHCGR signaling. PMID:26483755

  9. GRAVITATIONAL LENS MODELING WITH GENETIC ALGORITHMS AND PARTICLE SWARM OPTIMIZERS

    SciTech Connect

    Rogers, Adam; Fiege, Jason D.

    2011-02-01

    Strong gravitational lensing of an extended object is described by a mapping from source to image coordinates that is nonlinear and cannot generally be inverted analytically. Determining the structure of the source intensity distribution also requires a description of the blurring effect due to a point-spread function. This initial study uses an iterative gravitational lens modeling scheme based on the semilinear method to determine the linear parameters (source intensity profile) of a strongly lensed system. Our 'matrix-free' approach avoids construction of the lens and blurring operators while retaining the least-squares formulation of the problem. The parameters of an analytical lens model are found through nonlinear optimization by an advanced genetic algorithm (GA) and particle swarm optimizer (PSO). These global optimization routines are designed to explore the parameter space thoroughly, mapping model degeneracies in detail. We develop a novel method that determines the L-curve for each solution automatically, which represents the trade-off between the image {chi}{sup 2} and regularization effects, and allows an estimate of the optimally regularized solution for each lens parameter set. In the final step of the optimization procedure, the lens model with the lowest {chi}{sup 2} is used while the global optimizer solves for the source intensity distribution directly. This allows us to accurately determine the number of degrees of freedom in the problem to facilitate comparison between lens models and enforce positivity on the source profile. In practice, we find that the GA conducts a more thorough search of the parameter space than the PSO.

  10. The use of genetic algorithms to model protoplanetary discs

    NASA Astrophysics Data System (ADS)

    Hetem, Annibal; Gregorio-Hetem, Jane

    2007-12-01

    The protoplanetary discs of T Tauri and Herbig Ae/Be stars have previously been studied using geometric disc models to fit their spectral energy distribution (SED). The simulations provide a means to reproduce the signatures of various circumstellar structures, which are related to different levels of infrared excess. With the aim of improving our previous model, which assumed a simple flat-disc configuration, we adopt here a reprocessing flared-disc model that assumes hydrostatic, radiative equilibrium. We have developed a method to optimize the parameter estimation based on genetic algorithms (GAs). This paper describes the implementation of the new code, which has been applied to Herbig stars from the Pico dos Dias Survey catalogue, in order to illustrate the quality of the fitting for a variety of SED shapes. The star AB Aur was used as a test of the GA parameter estimation, and demonstrates that the new code reproduces successfully a canonical example of the flared-disc model. The GA method gives a good quality of fit, but the range of input parameters must be chosen with caution, as unrealistic disc parameters can be derived. It is confirmed that the flared-disc model fits the flattened SEDs typical of Herbig stars; however, embedded objects (increasing SED slope) and debris discs (steeply decreasing SED slope) are not well fitted with this configuration. Even considering the limitation of the derived parameters, the automatic process of SED fitting provides an interesting tool for the statistical analysis of the circumstellar luminosity of large samples of young stars.

  11. Testing a Gender Additive Model: The Role of Body Image in Adolescent Depression

    ERIC Educational Resources Information Center

    Bearman, Sarah Kate; Stice, Eric

    2008-01-01

    Despite consistent evidence that adolescent girls are at greater risk of developing depression than adolescent boys, risk factor models that account for this difference have been elusive. The objective of this research was to examine risk factors proposed by the "gender additive" model of depression that attempts to partially explain the increased…

  12. Toward a genetically-informed model of borderline personality disorder.

    PubMed

    Livesley, John

    2008-02-01

    This article describes a conceptual framework for describing borderline personality disorder (BPD) based on empirical studies of the phenotypic structure and genetic architecture of personality. The proposed phenotype has 2 components: (1) a description of core self and interpersonal pathology-the defining features of personality disorder-as these features are expressed in the disorder; and (2) a set of traits based on the anxious-dependent or emotional dysregulation factor of the four-factor model of PD. Four kinds of traits are described: emotional (anxiousness, emotional reactivity, emotional intensity, and pessimistic-anhedonia), interpersonal (submissiveness, insecure attachment, social apprehensiveness, and need for approval), cognitive (cognitive dysregulation), and self-harm (behaviors and ideas). Formulation of the phenotype was guided by the conceptualization of personality as a system of interrelated sub-systems. The psychopathology associated with BPD involves most components of the system. The trait structure of the disorder is assumed to reflect the genetic architecture of personality and individual traits are assumed to be based on adaptive mechanisms. It is suggested that borderline traits are organized around the trait of anxiousness and that an important feature of BPD is dysregulation of the threat management system leading to pervasive fearfulness and unstable emotions. The interpersonal traits are assumed to be heritable characteristics that evolved to deal with interpersonal threats that arose as a result of social living. The potential for unstable and conflicted interpersonal relationships that is inherent to the disorder is assumed to result from the interplay between the adaptive structure of personality and psychosocial adversity. The etiology of the disorder is discussed in terms of biological and environmental factors associated with each component of the phenotype. PMID:18312122

  13. Smooth-Threshold Multivariate Genetic Prediction with Unbiased Model Selection.

    PubMed

    Ueki, Masao; Tamiya, Gen

    2016-04-01

    We develop a new genetic prediction method, smooth-threshold multivariate genetic prediction, using single nucleotide polymorphisms (SNPs) data in genome-wide association studies (GWASs). Our method consists of two stages. At the first stage, unlike the usual discontinuous SNP screening as used in the gene score method, our method continuously screens SNPs based on the output from standard univariate analysis for marginal association of each SNP. At the second stage, the predictive model is built by a generalized ridge regression simultaneously using the screened SNPs with SNP weight determined by the strength of marginal association. Continuous SNP screening by the smooth thresholding not only makes prediction stable but also leads to a closed form expression of generalized degrees of freedom (GDF). The GDF leads to the Stein's unbiased risk estimation (SURE), which enables data-dependent choice of optimal SNP screening cutoff without using cross-validation. Our method is very rapid because computationally expensive genome-wide scan is required only once in contrast to the penalized regression methods including lasso and elastic net. Simulation studies that mimic real GWAS data with quantitative and binary traits demonstrate that the proposed method outperforms the gene score method and genomic best linear unbiased prediction (GBLUP), and also shows comparable or sometimes improved performance with the lasso and elastic net being known to have good predictive ability but with heavy computational cost. Application to whole-genome sequencing (WGS) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) exhibits that the proposed method shows higher predictive power than the gene score and GBLUP methods. PMID:26947266

  14. Additive genetic variation in resistance traits of an exotic pine species: little evidence for constraints on evolution of resistance against native herbivores

    PubMed Central

    Moreira, X; Zas, R; Sampedro, L

    2013-01-01

    The apparent failure of invasions by alien pines in Europe has been explained by the co-occurrence of native pine congeners supporting herbivores that might easily recognize the new plants as hosts. Previous studies have reported that exotic pines show reduced tolerance and capacity to induce resistance to those native herbivores. We hypothesize that limited genetic variation in resistance to native herbivores and the existence of evolutionary trade-offs between growth and resistance could represent additional potential constraints on the evolution of invasiveness of exotic pines outside their natural range. In this paper, we examined genetic variation for constitutive and induced chemical defences (measured as non-volatile resin in the stem and total phenolics in the needles) and resistance to two major native generalist herbivores of pines in cafeteria bioassays (the phloem-feeder Hylobius abietis and the defoliator Thaumetopoea pityocampa) using half-sib families drawn from a sample of the population of Pinus radiata introduced to Spain in the mid-19th century. We found (i) significant genetic variation, with moderate-to-high narrow-sense heritabilities for both the production of constitutive non-volatile resin and induced total phenolics, and for constitutive resistance against T. pityocampa in bioassays, (ii) no evolutionary trade-offs between plant resistance and growth traits or between the production of different quantitative chemical defences and (iii) a positive genetic correlation between constitutive resistance to the two studied herbivores. Overall, results of our study indicate that the exotic pine P. radiata has limited genetic constraints on the evolution of resistance against herbivores in its introduced range, suggesting that, at least in terms of interactions with these enemies, this pine species has potential to become invasive in the future. PMID:23232833

  15. Additive genetic variation in resistance traits of an exotic pine species: little evidence for constraints on evolution of resistance against native herbivores.

    PubMed

    Moreira, X; Zas, R; Sampedro, L

    2013-05-01

    The apparent failure of invasions by alien pines in Europe has been explained by the co-occurrence of native pine congeners supporting herbivores that might easily recognize the new plants as hosts. Previous studies have reported that exotic pines show reduced tolerance and capacity to induce resistance to those native herbivores. We hypothesize that limited genetic variation in resistance to native herbivores and the existence of evolutionary trade-offs between growth and resistance could represent additional potential constraints on the evolution of invasiveness of exotic pines outside their natural range. In this paper, we examined genetic variation for constitutive and induced chemical defences (measured as non-volatile resin in the stem and total phenolics in the needles) and resistance to two major native generalist herbivores of pines in cafeteria bioassays (the phloem-feeder Hylobius abietis and the defoliator Thaumetopoea pityocampa) using half-sib families drawn from a sample of the population of Pinus radiata introduced to Spain in the mid-19th century. We found (i) significant genetic variation, with moderate-to-high narrow-sense heritabilities for both the production of constitutive non-volatile resin and induced total phenolics, and for constitutive resistance against T. pityocampa in bioassays, (ii) no evolutionary trade-offs between plant resistance and growth traits or between the production of different quantitative chemical defences and (iii) a positive genetic correlation between constitutive resistance to the two studied herbivores. Overall, results of our study indicate that the exotic pine P. radiata has limited genetic constraints on the evolution of resistance against herbivores in its introduced range, suggesting that, at least in terms of interactions with these enemies, this pine species has potential to become invasive in the future. PMID:23232833

  16. Genetic education to diverse communities employing a community empowerment model.

    PubMed

    Mittman, I S

    1998-01-01

    Lack of equity in access to health care, in general, and genetic services in particular, places communities of color at a distinct disadvantage when considering the rapidly evolving genetic technology. Much of this disparity is owed to lack of trust and credibility in the genetic care system as well as multiple ethnocultural barriers to services. This paper presents a 3-year community outreach demonstration project in genetic education. The project employed the premise that the empowerment of the target communities to take active part in their genetic education, with attention to a wide array of the community's health care needs, is the most efficacious manner in which to provide genetic education to underserved communities. PMID:15178975

  17. A Two-Stage Approximation for Analysis of Mixture Genetic Models in Large Pedigrees

    PubMed Central

    Habier, D.; Totir, L. R.; Fernando, R. L.

    2010-01-01

    Information from cosegregation of marker and QTL alleles, in addition to linkage disequilibrium (LD), can improve genomic selection. Variance components linear models have been proposed for this purpose, but accommodating dominance and epistasis is not straightforward with them. A full-Bayesian analysis of a mixture genetic model is favorable in this respect, but is computationally infeasible for whole-genome analyses. Thus, we propose an approximate two-step approach that neglects information from trait phenotypes in inferring ordered genotypes and segregation indicators of markers. Quantitative trait loci (QTL) fine-mapping scenarios, using high-density markers and pedigrees of five generations without genotyped females, were simulated to test this strategy against an exact full-Bayesian approach. The latter performed better in estimating QTL genotypes, but precision of QTL location and accuracy of genomic breeding values (GEBVs) did not differ for the two methods at realistically low LD. If, however, LD was higher, the exact approach resulted in a slightly higher accuracy of GEBVs. In conclusion, the two-step approach makes mixture genetic models computationally feasible for high-density markers and large pedigrees. Furthermore, markers need to be sampled only once and results can be used for the analysis of all traits. Further research is needed to evaluate the two-step approach for complex pedigrees and to analyze alternative strategies for modeling LD between QTL and markers. PMID:20382829

  18. Three-dimensional inverse modelling of magnetic anomaly sources based on a genetic algorithm

    NASA Astrophysics Data System (ADS)

    Montesinos, Fuensanta G.; Blanco-Montenegro, Isabel; Arnoso, José

    2016-04-01

    We present a modelling method to estimate the 3-D geometry and location of homogeneously magnetized sources from magnetic anomaly data. As input information, the procedure needs the parameters defining the magnetization vector (intensity, inclination and declination) and the Earth's magnetic field direction. When these two vectors are expected to be different in direction, we propose to estimate the magnetization direction from the magnetic map. Then, using this information, we apply an inversion approach based on a genetic algorithm which finds the geometry of the sources by seeking the optimum solution from an initial population of models in successive iterations through an evolutionary process. The evolution consists of three genetic operators (selection, crossover and mutation), which act on each generation, and a smoothing operator, which looks for the best fit to the observed data and a solution consisting of plausible compact sources. The method allows the use of non-gridded, non-planar and inaccurate anomaly data and non-regular subsurface partitions. In addition, neither constraints for the depth to the top of the sources nor an initial model are necessary, although previous models can be incorporated into the process. We show the results of a test using two complex synthetic anomalies to demonstrate the efficiency of our inversion method. The application to real data is illustrated with aeromagnetic data of the volcanic island of Gran Canaria (Canary Islands).

  19. Form Follows Function: A Model for Clinical Supervision of Genetic Counseling Students.

    PubMed

    Wherley, Colleen; Veach, Patricia McCarthy; Martyr, Meredith A; LeRoy, Bonnie S

    2015-10-01

    Supervision plays a vital role in genetic counselor training, yet models describing genetic counseling supervision processes and outcomes are lacking. This paper describes a proposed supervision model intended to provide a framework to promote comprehensive and consistent clinical supervision training for genetic counseling students. Based on the principle "form follows function," the model reflects and reinforces McCarthy Veach et al.'s empirically derived model of genetic counseling practice - the "Reciprocal Engagement Model" (REM). The REM consists of mutually interactive educational, relational, and psychosocial components. The Reciprocal Engagement Model of Supervision (REM-S) has similar components and corresponding tenets, goals, and outcomes. The 5 REM-S tenets are: Learning and applying genetic information are key; Relationship is integral to genetic counseling supervision; Student autonomy must be supported; Students are capable; and Student emotions matter. The REM-S outcomes are: Student understands and applies information to independently provide effective services, develop professionally, and engage in self-reflective practice. The 16 REM-S goals are informed by the REM of genetic counseling practice and supported by prior literature. A review of models in medicine and psychology confirms the REM-S contains supervision elements common in healthcare fields, while remaining unique to genetic counseling. The REM-S shows promise for enhancing genetic counselor supervision training and practice and for promoting research on clinical supervision. The REM-S is presented in detail along with specific examples and training and research suggestions. PMID:25956951

  20. Description and Validation of a Dynamical Systems Model of Presynaptic Serotonin Function: Genetic Variation, Brain Activation and Impulsivity

    PubMed Central

    Stoltenberg, Scott F.; Nag, Parthasarathi

    2010-01-01

    Despite more than a decade of empirical work on the role of genetic polymorphisms in the serotonin system on behavior, the details across levels of analysis are not well understood. We describe a mathematical model of the genetic control of presynaptic serotonergic function that is based on control theory, implemented using systems of differential equations, and focused on better characterizing pathways from genes to behavior. We present the results of model validation tests that include the comparison of simulation outcomes with empirical data on genetic effects on brain response to affective stimuli and on impulsivity. Patterns of simulated neural firing were consistent with recent findings of additive effects of serotonin transporter and tryptophan hydroxylase-2 polymorphisms on brain activation. In addition, simulated levels of cerebral spinal fluid 5-hydroxyindoleacetic acid (CSF 5-HIAA) were negatively correlated with Barratt Impulsiveness Scale (Version 11) Total scores in college students (r = −.22, p = .002, N = 187), which is consistent with the well-established negative correlation between CSF 5-HIAA and impulsivity. The results of the validation tests suggest that the model captures important aspects of the genetic control of presynaptic serotonergic function and behavior via brain activation. The proposed model can be: (1) extended to include other system components, neurotransmitter systems, behaviors and environmental influences; (2) used to generate testable hypotheses. PMID:20111992

  1. Genetic parameters for various random regression models to describe total sperm cells per ejaculate over the reproductive lifetime of boars.

    PubMed

    Oh, S H; See, M T; Long, T E; Galvin, J M

    2006-03-01

    The objective of this study was to model the variances and covariances of total sperm cells per ejaculate (TSC) over the reproductive lifetime of AI boars. Data from boars (n = 834) selected for AI were provided by Smithfield Premium Genetics. The total numbers of records and animals were 19,629 and 1,736, respectively. Parameters were estimated for TSC by age of boar classification with a random regression model using the Simplex method and DxMRR procedures. The model included breed, collector, and year-season as fixed effects. Random effects were additive genetic, permanent environmental effect of boar, and residual. Observations were removed when the number of data at a given age of boar classification was < 10 records. Preliminary evaluations showed the best fit with fifth-order polynomials, indicating that the best model would have fifth-order fixed regression and fifth-order random regressions for animal and permanent environmental effects. Random regression models were fitted to evaluate all combinations of first- through seventh-order polynomial covariance functions. Goodness of fit for the models was tested using Akaike's Information Criterion and the Schwarz Criterion. The maximum log likelihood value was observed for sixth-, fifth-, and seventh-order polynomials for fixed, additive genetic, and permanent environmental effects, respectively. However, the best fit as determined by Akaike's Information Criterion and the Schwarz Criterion was by fitting sixth-, fourth-, and seventh-order polynomials; and fourth-, second-, and seventh-order polynomials for fixed, additive genetic, and permanent environmental effects, respectively. Heritability estimates for TSC ranged from 0.27 to 0.48 across age of boar classifications. In addition, heritability for TSC tended to increase with age of boar classification. PMID:16478945

  2. Placing Neuroanatomical Models of Executive Function in a Developmental Context Imaging and Imaging–Genetic Strategies

    PubMed Central

    Brocki, Karin; Fan, Jin; Fossella, John

    2009-01-01

    Children show gradual and protracted improvement in an array of behaviors involved in the conscious control of thought and emotion. Behavioral research has shown that these abilities, collectively referred to as executive functions (EF), can be dissociated into separable processes, such as inhibition and working memory. Furthermore, noninvasive neuroimaging shows that these component processes often rely on separable neural circuits involving areas of the frontal cortex and nuclei of the basal ganglia. As additional noninvasive methodologies become available, it is increasingly possible to continue to dissect and dissociate components of EF and also test predictions made by a number of theoretical neuroanatomical models. One method of late is genetics, which is noninvasive and readily used in concert with neuroimaging. The biological data obtained with neuroimaging and genetics is particularly able to inform neuroanatomical models that link specific brain systems with higher more abstract process models derived from purely behavioral work. As much progress in this area continues to occur, we seek to evaluate the age dependency and manner in which certain aspects of EF and certain anatomical circuits show changes and interactions as children develop. Some examples are taken from research on children with the developmental disability attention deficit hyperactivity disorder. A review of selected developmental research shows that current cognitive and neuroanatomical models of EF offer a great many system- and synaptic-level hypotheses that can be tested using imaging and imaging genetics in longitudinal and cross-sectional study designs. Here, we focus on age-related changes in inhibition and working memory. PMID:18591485

  3. Achieving World-Class Schools: Mastering School Improvement Using a Genetic Model.

    ERIC Educational Resources Information Center

    Kimmelman, Paul L.; Kroeze, David J.

    In providing its program for education reform, this book uses, as an analogy, the genetic model taken from the Human Genome project. In the first part, "Theoretical Underpinnings," the book explains why a genetic model can be used to improve school systems; describes the critical components of a world-class school system; and details the genetic…

  4. An SSR-Based Genetic Linkage Map of the Model Grass Brachypodium distachyon

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The grass species Brachypodium distachyon (Brachypodium) has been adopted as a model system for grasses. While many genome resources are being developed, genetic resources will be essential to make full use of this model. Here, we describe the first molecular map of diploid Brachypodium. The genetic...

  5. Mouse models for induced genetic instability at endogenous loci.

    PubMed

    Reliene, Ramune; Schiestl, Robert H

    2003-10-13

    Exposure to environmental factors and genetic predisposition of an individual may lead individually or in combination to various genetic diseases including cancer. These diseases may be a consequence of genetic instability resulting in large-scale genomic rearrangements, such as DNA deletions, duplications, and translocations. This review focuses on mouse assays detecting genetic instability at endogenous loci. The frequency of DNA deletions by homologous recombination at the pink-eyed unstable (p(un)) locus is elevated in mice with mutations in ATM, Trp53, Gadd45, and WRN genes and after exposure to carcinogens. Other quantitative in vivo assays detecting loss of heterozygosity events, such as the mammalian spot assay, Dlb-1 mouse and Aprt mouse assays, are also reviewed. These in vivo test systems may predict hazardous effects of an environmental agent and/or genetic predisposition to cancer. PMID:14557804

  6. Modeling oxygen dissolution and biological uptake during pulse oxygen additions in oenological fermentations.

    PubMed

    Saa, Pedro A; Moenne, M Isabel; Pérez-Correa, J Ricardo; Agosin, Eduardo

    2012-09-01

    Discrete oxygen additions during oenological fermentations can have beneficial effects both on yeast performance and on the resulting wine quality. However, the amount and time of the additions must be carefully chosen to avoid detrimental effects. So far, most oxygen additions are carried out empirically, since the oxygen dynamics in the fermenting must are not completely understood. To efficiently manage oxygen dosage, we developed a mass balance model of the kinetics of oxygen dissolution and biological uptake during wine fermentation on a laboratory scale. Model calibration was carried out employing a novel dynamic desorption-absorption cycle based on two optical sensors able to generate enough experimental data for the precise determination of oxygen uptake and volumetric mass transfer coefficients. A useful system for estimating the oxygen solubility in defined medium and musts was also developed and incorporated into the mass balance model. Results indicated that several factors, such as the fermentation phase, wine composition, mixing and carbon dioxide concentration, must be considered when performing oxygen addition during oenological fermentations. The present model will help develop better oxygen addition policies in wine fermentations on an industrial scale. PMID:22349928

  7. Genetic variation, climate models and the ecological genetics of Larix occidentalis

    SciTech Connect

    Rehfeldt, G.E.

    1995-12-31

    Provenance tests of 138 populations of Larix occidentalis revealed genetic differentiation for eight variables describing growth, phenology, tolerance to spring frosts, effects of Meria laricis needle cast, and survival. Geographic variables accounted for as much as 34% of the variance among Rocky Mountain populations. Patterns of genetic variation were dominated by the effects of latitude and elevation, with populations from the north and from high elevations having the lowest growth potential, the least tolerance to the needle cast, and the lowest survival. However, the slope of the geographic clines was relatively flat. Populations in the same geographic area, for instance, need to be separated by about 500 m in elevation before genetic differentiation can be expected.

  8. Genetic analysis of calving traits by the multi-trait individual animal model.

    PubMed

    Weller, J I; Ezra, E

    2016-01-01

    Five alternative models were applied for analysis of dystocia and stillbirth in first and second parities. Models 1 and 2 were included only to estimate the parameters required for model 4, and models 3 and 5 are included only as comparisons to the model 4 estimates. Variance components were estimated by multi-trait REML, including cows with valid calving records for both parities. For the effects of sire of calf on first and second parities, variance components were estimated including only calvings with the same sire of calf for both parities. All heritabilities for the cow effect were quite low, but higher for dystocia than for stillbirth and higher in first parity. The sire-of-calf heritabilities were higher than the cow effect heritabilities, except for stillbirth in parity 2. Unlike the effect of cow correlations, all sire of calf correlations were >0.6, and the correlations for the same trait in parities 1 and 2 were >0.9. Thus, a multi-trait analysis should yield a significant gain in accuracy with respect to the sire of calf effects for bulls not mated to virgin heifers. A multi-trait individual animal model algorithm was developed for joint analysis of dystocia and stillbirth in first and second parities. Relationships matrices were included both for the effects of cow and sire of calf. In addition, random herd-year-season and fixed sex of calf effects were included in the model. Records were preadjusted for calving month and age. A total of 899,223 Israeli Holstein cows with first calvings since 1985 were included in the complete analysis. Approximate reliabilities were computed for both sire of cow and sire of calf effects. Correlations between these reliabilities and reliabilities obtained by direct inversion of the coefficient matrix for a sire of cow-sire of calf model were all close to 0.99. Phenotypic trends for cows born from 1983 through 2007 were economically unfavorable for dystocia and favorable for stillbirth in both parities. Genetic trends

  9. Modeling Hypercalciuria in the Genetic Hypercalciuric Stone-Forming Rat

    PubMed Central

    Frick, Kevin K.; Krieger, Nancy S.; Bushinsky, David A.

    2015-01-01

    Purpose of Review In this review we discuss how the Genetic Hypercalciuric Stone-Forming (GHS) rats, which closely model idiopathic hypercalciuria and stone formation in humans, provide insights into the pathophysiology and consequences of clinical hypercalciuria. Recent Findings Hypercalciuria in the GHS rats is due to a systemic dysregulation of calcium transport, as manifest by increased intestinal calcium absorption, increased bone resorption and decreased renal tubule calcium reabsorption. Increased levels of vitamin D receptor in intestine, bone and kidney appear to mediate these changes. The excess receptors are biologically active and increase tissue sensitivity to exogenous vitamin D. Bones of GHS rats have decreased bone mineral density (BMD) as compared with Sprague Dawley rats, and exogenous 1,25(OH)2D3 exacerbates the loss of BMD. Thiazide diuretics improve the BMD in GHS rats. Summary Studying GHS rats allows direct investigation of the effects of alterations in diet and utilization of pharmacologic therapy on hypercalciuria, urine supersaturation, stone formation and bone quality in ways that are not possible in humans. PMID:26050120

  10. Vector generalized additive models for extreme rainfall data analysis (study case rainfall data in Indramayu)

    NASA Astrophysics Data System (ADS)

    Utami, Eka Putri Nur; Wigena, Aji Hamim; Djuraidah, Anik

    2016-02-01

    Rainfall pattern are good indicators for potential disasters. Global Circulation Model (GCM) contains global scale information that can be used to predict the rainfall data. Statistical downscaling (SD) utilizes the global scale information to make inferences in the local scale. Essentially, SD can be used to predict local scale variables based on global scale variables. SD requires a method to accommodate non linear effects and extreme values. Extreme value Theory (EVT) can be used to analyze the extreme value. One of methods to identify the extreme events is peak over threshold that follows Generalized Pareto Distribution (GPD). The vector generalized additive model (VGAM) is an extension of the generalized additive model. It is able to accommodate linear or nonlinear effects by involving more than one additive predictors. The advantage of VGAM is to handle multi response models. The key idea of VGAM are iteratively reweighted least square for maximum likelihood estimation, penalized smoothing, fisher scoring and additive models. This works aims to analyze extreme rainfall data in Indramayu using VGAM. The results show that the VGAM with GPD is able to predict extreme rainfall data accurately. The prediction in February is very close to the actual value at quantile 75.

  11. Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network, and pathway analyses

    PubMed Central

    Kogelman, Lisette J. A.; Pant, Sameer D.; Fredholm, Merete; Kadarmideen, Haja N.

    2014-01-01

    Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g., metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie

  12. Integrated reservoir characterization: Improvement in heterogeneities stochastic modelling by integration of additional external constraints

    SciTech Connect

    Doligez, B.; Eschard, R.; Geffroy, F.

    1997-08-01

    The classical approach to construct reservoir models is to start with a fine scale geological model which is informed with petrophysical properties. Then scaling-up techniques allow to obtain a reservoir model which is compatible with the fluid flow simulators. Geostatistical modelling techniques are widely used to build the geological models before scaling-up. These methods provide equiprobable images of the area under investigation, which honor the well data, and which variability is the same than the variability computed from the data. At an appraisal phase, when few data are available, or when the wells are insufficient to describe all the heterogeneities and the behavior of the field, additional constraints are needed to obtain a more realistic geological model. For example, seismic data or stratigraphic models can provide average reservoir information with an excellent areal coverage, but with a poor vertical resolution. New advances in modelisation techniques allow now to integrate this type of additional external information in order to constrain the simulations. In particular, 2D or 3D seismic derived information grids, or sand-shale ratios maps coming from stratigraphic models can be used as external drifts to compute the geological image of the reservoir at the fine scale. Examples are presented to illustrate the use of these new tools, their impact on the final reservoir model, and their sensitivity to some key parameters.

  13. Analysis of error-prone survival data under additive hazards models: measurement error effects and adjustments.

    PubMed

    Yan, Ying; Yi, Grace Y

    2016-07-01

    Covariate measurement error occurs commonly in survival analysis. Under the proportional hazards model, measurement error effects have been well studied, and various inference methods have been developed to correct for error effects under such a model. In contrast, error-contaminated survival data under the additive hazards model have received relatively less attention. In this paper, we investigate this problem by exploring measurement error effects on parameter estimation and the change of the hazard function. New insights of measurement error effects are revealed, as opposed to well-documented results for the Cox proportional hazards model. We propose a class of bias correction estimators that embraces certain existing estimators as special cases. In addition, we exploit the regression calibration method to reduce measurement error effects. Theoretical results for the developed methods are established, and numerical assessments are conducted to illustrate the finite sample performance of our methods. PMID:26328545

  14. Experimental model and analytic solution for real-time observation of vehicle's additional steer angle

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaolong; Li, Liang; Pan, Deng; Cao, Chengmao; Song, Jian

    2014-03-01

    The current research of real-time observation for vehicle roll steer angle and compliance steer angle(both of them comprehensively referred as the additional steer angle in this paper) mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle's roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ɛ-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system(ESC). The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model's generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal (the magnitude up to 1°), followed by the longitudinal acceleration-deceleration and the road wave amplitude (the magnitude up to 0.3°). Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC. This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.

  15. Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models.

    PubMed

    Baeder, Desiree Y; Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens; Regoes, Roland R

    2016-05-26

    Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials.This article is part of the themed issue 'Evolutionary ecology of arthropod antimicrobial peptides'. PMID:27160596

  16. Cognitive vulnerability to depression: A comparison of the weakest link, keystone and additive models

    PubMed Central

    Reilly, Laura C.; Ciesla, Jeffrey A.; Felton, Julia W.; Weitlauf, Amy S.; Anderson, Nicholas L.

    2014-01-01

    Multiple theories of cognitive vulnerability to depression have been proposed, each focusing on different aspects of negative cognition and utilising different measures of risk. Various methods of integrating such multiple indices of risk have been examined in the literature, and each demonstrates some promise. Yet little is known about the interrelations among these methods, or their incremental validity in predicting changes in depression. The present study compared three integrative models of cognitive vulnerability: the additive, weakest link, and keystone models. Support was found for each model as predictive of depression over time, but only the weakest link model demonstrated incremental utility in predicting changes in depression over the other models. We also explore the correlation between these models and each model’s unique contribution to predicting onset of depressive symptoms. PMID:21851251

  17. Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

    PubMed

    Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

    2014-04-01

    The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method. PMID:25061254

  18. Additive influence of genetic predisposition and conventional risk factors in the incidence of coronary heart disease: a population-based study in Greece

    PubMed Central

    Yiannakouris, Nikos; Katsoulis, Michail; Trichopoulou, Antonia; Ordovas, Jose M; Trichopoulos, Dimitrios

    2014-01-01

    Objectives An additive genetic risk score (GRS) for coronary heart disease (CHD) has previously been associated with incident CHD in the population-based Greek European Prospective Investigation into Cancer and nutrition (EPIC) cohort. In this study, we explore GRS-‘environment’ joint actions on CHD for several conventional cardiovascular risk factors (ConvRFs), including smoking, hypertension, type-2 diabetes mellitus (T2DM), body mass index (BMI), physical activity and adherence to the Mediterranean diet. Design A case–control study. Setting The general Greek population of the EPIC study. Participants and outcome measures 477 patients with medically confirmed incident CHD and 1271 controls participated in this study. We estimated the ORs for CHD by dividing participants at higher or lower GRS and, alternatively, at higher or lower ConvRF, and calculated the relative excess risk due to interaction (RERI) as a measure of deviation from additivity. Results The joint presence of higher GRS and higher risk ConvRF was in all instances associated with an increased risk of CHD, compared with the joint presence of lower GRS and lower risk ConvRF. The OR (95% CI) was 1.7 (1.2 to 2.4) for smoking, 2.7 (1.9 to 3.8) for hypertension, 4.1 (2.8 to 6.1) for T2DM, 1.9 (1.4 to 2.5) for lower physical activity, 2.0 (1.3 to 3.2) for high BMI and 1.5 (1.1 to 2.1) for poor adherence to the Mediterranean diet. In all instances, RERI values were fairly small and not statistically significant, suggesting that the GRS and the ConvRFs do not have effects beyond additivity. Conclusions Genetic predisposition to CHD, operationalised through a multilocus GRS, and ConvRFs have essentially additive effects on CHD risk. PMID:24500614

  19. Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data

    PubMed Central

    Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

    2012-01-01

    Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions. PMID:23645976

  20. Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes.

    PubMed

    Borquis, Rusbel Raul Aspilcueta; Neto, Francisco Ribeiro de Araujo; Baldi, Fernando; Hurtado-Lugo, Naudin; de Camargo, Gregório M F; Muñoz-Berrocal, Milthon; Tonhati, Humberto

    2013-09-01

    In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. PMID:23831097

  1. Testing the genetic predictions of a biogeographical model in a dominant endemic Eastern Pacific coral (Porites panamensis) using a genetic seascape approach.

    PubMed

    Saavedra-Sotelo, Nancy C; Calderon-Aguilera, Luis E; Reyes-Bonilla, Héctor; Paz-García, David A; López-Pérez, Ramón A; Cupul-Magaña, Amilcar; Cruz-Barraza, José A; Rocha-Olivares, Axayácatl

    2013-10-01

    The coral fauna of the Eastern Tropical Pacific (ETP) is depauperate and peripheral; hence, it has drawn attention to the factors allowing its survival. Here, we use a genetic seascape approach and ecological niche modeling to unravel the environmental factors correlating with the genetic variation of Porites panamensis, a hermatypic coral endemic to the ETP. Specifically, we test if levels of diversity and connectivity are higher among abundant than among depauperate populations, as expected by a geographically relaxed version of the Abundant Center Hypothesis (rel-ACH). Unlike the original ACH, referring to a geographical center of distribution of maximal abundance, the rel-ACH refers only to a center of maximum abundance, irrespective of its geographic position. The patterns of relative abundance of P. panamensis in the Mexican Pacific revealed that northern populations from Baja California represent its center of abundance; and southern depauperate populations along the continental margin are peripheral relative to it. Genetic patterns of diversity and structure of nuclear DNA sequences (ribosomal DNA and a single copy open reading frame) and five alloenzymatic loci partially agreed with rel-ACH predictions. We found higher diversity levels in peninsular populations and significant differentiation between peninsular and continental colonies. In addition, continental populations showed higher levels of differentiation and lower connectivity than peninsular populations in the absence of isolation by distance in each region. Some discrepancies with model expectations may relate to the influence of significant habitat discontinuities in the face of limited dispersal potential. Environmental data analyses and niche modeling allowed us to identify temperature, water clarity, and substrate availability as the main factors correlating with patterns of abundance, genetic diversity, and structure, which may hold the key to the survival of P. panamensis in the face of

  2. Testing the genetic predictions of a biogeographical model in a dominant endemic Eastern Pacific coral (Porites panamensis) using a genetic seascape approach

    PubMed Central

    Saavedra-Sotelo, Nancy C; Calderon-Aguilera, Luis E; Reyes-Bonilla, Héctor; Paz-García, David A; López-Pérez, Ramón A; Cupul-Magaña, Amilcar; Cruz-Barraza, José A; Rocha-Olivares, Axayácatl

    2013-01-01

    The coral fauna of the Eastern Tropical Pacific (ETP) is depauperate and peripheral; hence, it has drawn attention to the factors allowing its survival. Here, we use a genetic seascape approach and ecological niche modeling to unravel the environmental factors correlating with the genetic variation of Porites panamensis, a hermatypic coral endemic to the ETP. Specifically, we test if levels of diversity and connectivity are higher among abundant than among depauperate populations, as expected by a geographically relaxed version of the Abundant Center Hypothesis (rel-ACH). Unlike the original ACH, referring to a geographical center of distribution of maximal abundance, the rel-ACH refers only to a center of maximum abundance, irrespective of its geographic position. The patterns of relative abundance of P. panamensis in the Mexican Pacific revealed that northern populations from Baja California represent its center of abundance; and southern depauperate populations along the continental margin are peripheral relative to it. Genetic patterns of diversity and structure of nuclear DNA sequences (ribosomal DNA and a single copy open reading frame) and five alloenzymatic loci partially agreed with rel-ACH predictions. We found higher diversity levels in peninsular populations and significant differentiation between peninsular and continental colonies. In addition, continental populations showed higher levels of differentiation and lower connectivity than peninsular populations in the absence of isolation by distance in each region. Some discrepancies with model expectations may relate to the influence of significant habitat discontinuities in the face of limited dispersal potential. Environmental data analyses and niche modeling allowed us to identify temperature, water clarity, and substrate availability as the main factors correlating with patterns of abundance, genetic diversity, and structure, which may hold the key to the survival of P. panamensis in the face of

  3. Physiological basis of tolerance to complete submergence in rice involves genetic factors in addition to the SUB1 gene.

    PubMed

    Singh, Sudhanshu; Mackill, David J; Ismail, Abdelbagi M

    2014-01-01

    1 lines. This suggests the possibility of further improvements in submergence tolerance by incorporating additional traits present in FR13A or other similar landraces. PMID:25281725

  4. Physiological basis of tolerance to complete submergence in rice involves genetic factors in addition to the SUB1 gene

    PubMed Central

    Singh, Sudhanshu; Mackill, David J.; Ismail, Abdelbagi M.

    2014-01-01

    1 lines. This suggests the possibility of further improvements in submergence tolerance by incorporating additional traits present in FR13A or other similar landraces. PMID:25281725

  5. New Genetics

    MedlinePlus

    ... human genome, behavioral genetics, pharmacogenetics, drug resistance, biofilms, computer modeling. » more Chapter 5: 21st-Century Genetics Covers systems biology, GFP, genetic testing, privacy concerns, DNA forensics, ...

  6. DNA looping increases the range of bistability in a stochastic model of the lac genetic switch.

    PubMed

    Earnest, Tyler M; Roberts, Elijah; Assaf, Michael; Dahmen, Karin; Luthey-Schulten, Zaida

    2013-04-01

    Conditions and parameters affecting the range of bistability of the lac genetic switch in Escherichia coli are examined for a model which includes DNA looping interactions with the lac repressor and a lactose analogue. This stochastic gene-mRNA-protein model of the lac switch describes DNA looping using a third transcriptional state. We exploit the fast bursting dynamics of mRNA by combining a novel geometric burst extension with the finite state projection method. This limits the number of protein/mRNA states, allowing for an accelerated search of the model's parameter space. We evaluate how the addition of the third state changes the bistability properties of the model and find a critical region of parameter space where the phenotypic switching occurs in a range seen in single molecule fluorescence studies. Stochastic simulations show induction in the looping model is preceded by a rare complete dissociation of the loop followed by an immediate burst of mRNA rather than a slower build up of mRNA as in the two-state model. The overall effect of the looped state is to allow for faster switching times while at the same time further differentiating the uninduced and induced phenotypes. Furthermore, the kinetic parameters are consistent with free energies derived from thermodynamic studies suggesting that this minimal model of DNA looping could have a broader range of application. PMID:23406725

  7. DNA looping increases the range of bistability in a stochastic model of the lac genetic switch

    NASA Astrophysics Data System (ADS)

    Earnest, Tyler M.; Roberts, Elijah; Assaf, Michael; Dahmen, Karin; Luthey-Schulten, Zaida

    2013-04-01

    Conditions and parameters affecting the range of bistability of the lac genetic switch in Escherichia coli are examined for a model which includes DNA looping interactions with the lac repressor and a lactose analogue. This stochastic gene-mRNA-protein model of the lac switch describes DNA looping using a third transcriptional state. We exploit the fast bursting dynamics of mRNA by combining a novel geometric burst extension with the finite state projection method. This limits the number of protein/mRNA states, allowing for an accelerated search of the model's parameter space. We evaluate how the addition of the third state changes the bistability properties of the model and find a critical region of parameter space where the phenotypic switching occurs in a range seen in single molecule fluorescence studies. Stochastic simulations show induction in the looping model is preceded by a rare complete dissociation of the loop followed by an immediate burst of mRNA rather than a slower build up of mRNA as in the two-state model. The overall effect of the looped state is to allow for faster switching times while at the same time further differentiating the uninduced and induced phenotypes. Furthermore, the kinetic parameters are consistent with free energies derived from thermodynamic studies suggesting that this minimal model of DNA looping could have a broader range of application.

  8. Plasmodium falciparum genetic crosses in a humanized mouse model

    PubMed Central

    Vaughan, Ashley M.; Pinapati, Richard S.; Cheeseman, Ian H.; Camargo, Nelly; Fishbaugher, Matthew; Checkley, Lisa A.; Nair, Shalini; Hutyra, Carolyn A.; Nosten, François H.; Anderson, Timothy J. C.; Ferdig, Michael T.; Kappe, Stefan H. I.

    2015-01-01

    Genetic crosses of phenotypically distinct strains of the human malaria parasite Plasmodium falciparum are a powerful tool for identifying genes controlling drug resistance and other key phenotypes. Previous studies relied on the isolation of recombinant parasites from splenectomized chimpanzees, a research avenue that is no longer available. Here, we demonstrate that human-liver chimeric mice support recovery of recombinant progeny for the identification of genetic determinants of parasite traits and adaptations. PMID:26030447

  9. Formation and reduction of carcinogenic furan in various model systems containing food additives.

    PubMed

    Kim, Jin-Sil; Her, Jae-Young; Lee, Kwang-Geun

    2015-12-15

    The aim of this study was to analyse and reduce furan in various model systems. Furan model systems consisting of monosaccharides (0.5M glucose and ribose), amino acids (0.5M alanine and serine) and/or 1.0M ascorbic acid were heated at 121°C for 25 min. The effects of food additives (each 0.1M) such as metal ions (iron sulphate, magnesium sulphate, zinc sulphate and calcium sulphate), antioxidants (BHT and BHA), and sodium sulphite on the formation of furan were measured. The level of furan formed in the model systems was 6.8-527.3 ng/ml. The level of furan in the model systems of glucose/serine and glucose/alanine increased 7-674% when food additives were added. In contrast, the level of furan decreased by 18-51% in the Maillard reaction model systems that included ribose and alanine/serine with food additives except zinc sulphate. PMID:26190608

  10. Random regression test day models to estimate genetic parameters for milk yield and milk components in Philippine dairy buffaloes.

    PubMed

    Flores, E B; van der Werf, J

    2015-08-01

    Heritabilities and genetic correlations for milk production traits were estimated from first-parity test day records on 1022 Philippine dairy buffalo cows. Traits analysed included milk (MY), fat (FY) and protein (PY) yields, and fat (Fat%) and protein (Prot%) concentrations. Varying orders of Legendre polynomials (Leg(m)) as well as the Wilmink function (Wil) were used in random regression models. These various models were compared based on log likelihood, Akaike's information criterion, Bayesian information criterion and genetic variance estimates. Six residual variance classes were sufficient for MY, FY, PY and Fat%, while seven residual classes for Prot%. Multivariate analysis gave higher estimates of genetic variance and heritability compared with univariate analysis for all traits. Heritability estimates ranged from 0.25 to 0.44, 0.13 to 0.31 and 0.21 to 0.36 for MY, FY and PY, respectively. Wilmink's function was the better fitting function for additive genetic effects for all traits. It was also the preferred function for permanent environment effects for Fat% and Prot%, but for MY, FY and PY, the Legm was the appropriate function. Genetic correlations of MY with FY and PY were high and they were moderately negative with Fat% and Prot%. To prevent deterioration in Fat% and Prot% and improve milk quality, more weight should be applied to milk component traits. PMID:25727642

  11. Modeling Longitudinal Data with Generalized Additive Models: Applications to Single-Case Designs

    ERIC Educational Resources Information Center

    Sullivan, Kristynn J.; Shadish, William R.

    2013-01-01

    Single case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time both in the presence and absence of treatment. For a variety of reasons, interest in the statistical analysis and meta-analysis of these designs has been growing in recent years. This paper proposes modeling SCD data with…

  12. NB-PLC channel modelling with cyclostationary noise addition & OFDM implementation for smart grid

    NASA Astrophysics Data System (ADS)

    Thomas, Togis; Gupta, K. K.

    2016-03-01

    Power line communication (PLC) technology can be a viable solution for the future ubiquitous networks because it provides a cheaper alternative to other wired technology currently being used for communication. In smart grid Power Line Communication (PLC) is used to support communication with low rate on low voltage (LV) distribution network. In this paper, we propose the channel modelling of narrowband (NB) PLC in the frequency range 5 KHz to 500 KHz by using ABCD parameter with cyclostationary noise addition. Behaviour of the channel was studied by the addition of 11KV/230V transformer, by varying load location and load. Bit error rate (BER) Vs signal to noise ratio SNR) was plotted for the proposed model by employing OFDM. Our simulation results based on the proposed channel model show an acceptable performance in terms of bit error rate versus signal to noise ratio, which enables communication required for smart grid applications.

  13. Identification of Treatment Targets in a Genetic Mouse Model of Voluntary Methamphetamine Drinking.

    PubMed

    Phillips, T J; Mootz, J R K; Reed, C

    2016-01-01

    Methamphetamine has powerful stimulant and euphoric effects that are experienced as rewarding and encourage use. Methamphetamine addiction is associated with debilitating illnesses, destroyed relationships, child neglect, violence, and crime; but after many years of research, broadly effective medications have not been identified. Individual differences that may impact not only risk for developing a methamphetamine use disorder but also affect treatment response have not been fully considered. Human studies have identified candidate genes that may be relevant, but lack of control over drug history, the common use or coabuse of multiple addictive drugs, and restrictions on the types of data that can be collected in humans are barriers to progress. To overcome some of these issues, a genetic animal model comprised of lines of mice selectively bred for high and low voluntary methamphetamine intake was developed to identify risk and protective alleles for methamphetamine consumption, and identify therapeutic targets. The mu opioid receptor gene was supported as a target for genes within a top-ranked transcription factor network associated with level of methamphetamine intake. In addition, mice that consume high levels of methamphetamine were found to possess a nonfunctional form of the trace amine-associated receptor 1 (TAAR1). The Taar1 gene is within a mouse chromosome 10 quantitative trait locus for methamphetamine consumption, and TAAR1 function determines sensitivity to aversive effects of methamphetamine that may curb intake. The genes, gene interaction partners, and protein products identified in this genetic mouse model represent treatment target candidates for methamphetamine addiction. PMID:27055611

  14. Genetic basis of hindlimb loss in a naturally occurring vertebrate model

    PubMed Central

    Don, Emily K.; de Jong-Curtain, Tanya A.; Doggett, Karen; Hall, Thomas E.; Heng, Benjamin; Badrock, Andrew P.; Winnick, Claire; Nicholson, Garth A.; Guillemin, Gilles J.; Currie, Peter D.; Hesselson, Daniel; Heath, Joan K.; Cole, Nicholas J.

    2016-01-01

    ABSTRACT Here we genetically characterise pelvic finless, a naturally occurring model of hindlimb loss in zebrafish that lacks pelvic fin structures, which are homologous to tetrapod hindlimbs, but displays no other abnormalities. Using a hybrid positional cloning and next generation sequencing approach, we identified mutations in the nuclear localisation signal (NLS) of T-box transcription factor 4 (Tbx4) that impair nuclear localisation of the protein, resulting in altered gene expression patterns during pelvic fin development and the failure of pelvic fin development. Using a TALEN-induced tbx4 knockout allele we confirm that mutations within the Tbx4 NLS (A78V; G79A) are sufficient to disrupt pelvic fin development. By combining histological, genetic, and cellular approaches we show that the hindlimb initiation gene tbx4 has an evolutionarily conserved, essential role in pelvic fin development. In addition, our novel viable model of hindlimb deficiency is likely to facilitate the elucidation of the detailed molecular mechanisms through which Tbx4 functions during pelvic fin and hindlimb development. PMID:26892237

  15. Genetic basis of hindlimb loss in a naturally occurring vertebrate model.

    PubMed

    Don, Emily K; de Jong-Curtain, Tanya A; Doggett, Karen; Hall, Thomas E; Heng, Benjamin; Badrock, Andrew P; Winnick, Claire; Nicholson, Garth A; Guillemin, Gilles J; Currie, Peter D; Hesselson, Daniel; Heath, Joan K; Cole, Nicholas J

    2016-01-01

    Here we genetically characterise pelvic finless, a naturally occurring model of hindlimb loss in zebrafish that lacks pelvic fin structures, which are homologous to tetrapod hindlimbs, but displays no other abnormalities. Using a hybrid positional cloning and next generation sequencing approach, we identified mutations in the nuclear localisation signal (NLS) of T-box transcription factor 4 (Tbx4) that impair nuclear localisation of the protein, resulting in altered gene expression patterns during pelvic fin development and the failure of pelvic fin development. Using a TALEN-induced tbx4 knockout allele we confirm that mutations within the Tbx4 NLS (A78V; G79A) are sufficient to disrupt pelvic fin development. By combining histological, genetic, and cellular approaches we show that the hindlimb initiation gene tbx4 has an evolutionarily conserved, essential role in pelvic fin development. In addition, our novel viable model of hindlimb deficiency is likely to facilitate the elucidation of the detailed molecular mechanisms through which Tbx4 functions during pelvic fin and hindlimb development. PMID:26892237

  16. Estimating heritabilities and genetic correlations: comparing the 'animal model' with parent-offspring regression using data from a natural population.

    PubMed

    Akesson, Mikael; Bensch, Staffan; Hasselquist, Dennis; Tarka, Maja; Hansson, Bengt

    2008-01-01

    Quantitative genetic parameters are nowadays more frequently estimated with restricted maximum likelihood using the 'animal model' than with traditional methods such as parent-offspring regressions. These methods have however rarely been evaluated using equivalent data sets. We compare heritabilities and genetic correlations from animal model and parent-offspring analyses, respectively, using data on eight morphological traits in the great reed warbler (Acrocephalus arundinaceus). Animal models were run using either mean trait values or individual repeated measurements to be able to separate between effects of including more extended pedigree information and effects of replicated sampling from the same individuals. We show that the inclusion of more pedigree information by the use of mean traits animal models had limited effect on the standard error and magnitude of heritabilities. In contrast, the use of repeated measures animal model generally had a positive effect on the sampling accuracy and resulted in lower heritabilities; the latter due to lower additive variance and higher phenotypic variance. For most trait combinations, both animal model methods gave genetic correlations that were lower than the parent-offspring estimates, whereas the standard errors were lower only for the mean traits animal model. We conclude that differences in heritabilities between the animal model and parent-offspring regressions were mostly due to the inclusion of individual replicates to the animal model rather than the inclusion of more extended pedigree information. Genetic correlations were, on the other hand, primarily affected by the inclusion of more pedigree information. This study is to our knowledge the most comprehensive empirical evaluation of the performance of the animal model in relation to parent-offspring regressions in a wild population. Our conclusions should be valuable for reconciliation of data obtained in earlier studies as well as for future meta

  17. Ballooning dispersal using silk: world fauna, phylogenies, genetics and models.

    PubMed

    Bell, J R; Bohan, D A; Shaw, E M; Weyman, G S

    2005-04-01

    Aerial dispersal using silk ('ballooning') has evolved in spiders (Araneae), spider mites (Acari) and in the larvae of moths (Lepidoptera). Since the 17th century, over 500 observations of ballooning behaviours have been published, yet there is an absence of any evolutionary synthesis of these data. In this paper the literature is reviewed, extensively documenting the known world fauna that balloon and the principal behaviours involved. This knowledge is then incorporated into the current evolutionary phylogenies to examine how ballooning might have arisen. Whilst it is possible that ballooning co-evolved with silk and emerged as early as the Devonian (410-355 mya), it is arguably more likely that ballooning evolved in parallel with deciduous trees, herbaceous annuals and grasses in the Cretaceous (135-65 mya). During this period, temporal (e.g. bud burst, chlorophyll thresholds) and spatial (e.g. herbivory, trampling) heterogeneities in habitat structuring predominated and intensified into the Cenozoic (65 mya to the present). It is hypothesized that from the ancestral launch mechanism known as 'suspended ballooning', widely used by individuals in plant canopies, 'tip-toe' and 'rearing' take-off behaviours were strongly selected for as habitats changed. It is contended that ballooning behaviour in all three orders can be described as a mixed Evolutionary Stable Strategy. This comprises individual bet-hedging due to habitat unpredictability, giving an underlying randomness to individual ballooning, with adjustments to the individual ballooning probability being conferred by more predictable habitat changes or colonization strategies. Finally, current methods used to study ballooning, including modelling and genetic research, are illustrated and an indication of future prospects given. PMID:15877859

  18. Different concepts and models of information for family-relevant genetic findings: comparison and ethical analysis.

    PubMed

    Lenk, Christian; Frommeld, Debora

    2015-08-01

    Genetic predispositions often concern not only individual persons, but also other family members. Advances in the development of genetic tests lead to a growing number of genetic diagnoses in medical practice and to an increasing importance of genetic counseling. In the present article, a number of ethical foundations and preconditions for this issue are discussed. Four different models for the handling of genetic information are presented and analyzed including a discussion of practical implications. The different models' ranges of content reach from a strictly autonomous position over self-governed arrangements in the practice of genetic counseling up to the involvement of official bodies and committees. The different models show a number of elements which seem to be very useful for the handling of genetic data in families from an ethical perspective. In contrast, the limitations of the standard medical attempt regarding confidentiality and personal autonomy in the context of genetic information in the family are described. Finally, recommendations for further ethical research and the development of genetic counseling in families are given. PMID:25894235

  19. Animal model integration to AutDB, a genetic database for autism

    PubMed Central

    2011-01-01

    Background In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models. Description As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future. Conclusions Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of

  20. Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models.

    PubMed

    Aspilcueta-Borquis, Rúsbel R; Araujo Neto, Francisco R; Baldi, Fernando; Santos, Daniel J A; Albuquerque, Lucia G; Tonhati, Humberto

    2012-08-01

    The test-day yields of milk, fat and protein were analysed from 1433 first lactations of buffaloes of the Murrah breed, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, born between 1985 and 2007. For the test-day yields, 10 monthly classes of lactation days were considered. The contemporary groups were defined as the herd-year-month of the test day. Random additive genetic, permanent environmental and residual effects were included in the model. The fixed effects considered were the contemporary group, number of milkings (1 or 2 milkings), linear and quadratic effects of the covariable cow age at calving and the mean lactation curve of the population (modelled by third-order Legendre orthogonal polynomials). The random additive genetic and permanent environmental effects were estimated by means of regression on third- to sixth-order Legendre orthogonal polynomials. The residual variances were modelled with a homogenous structure and various heterogeneous classes. According to the likelihood-ratio test, the best model for milk and fat production was that with four residual variance classes, while a third-order Legendre polynomial was best for the additive genetic effect for milk and fat yield, a fourth-order polynomial was best for the permanent environmental effect for milk production and a fifth-order polynomial was best for fat production. For protein yield, the best model was that with three residual variance classes and third- and fourth-order Legendre polynomials were best for the additive genetic and permanent environmental effects, respectively. The heritability estimates for the characteristics analysed were moderate, varying from 0·16±0·05 to 0·29±0·05 for milk yield, 0·20±0·05 to 0·30±0·08 for fat yield and 0·18±0·06 to 0·27±0·08 for protein yield. The estimates of the genetic correlations between the tests varied from 0·18±0·120 to 0·99±0·002; from 0·44±0·080 to 0·99±0·004; and from 0·41±0·080 to

  1. Effect of Bead and Illustrations Models on High School Students' Achievement in Molecular Genetics

    ERIC Educational Resources Information Center

    Rotbain, Yosi; Marbach-Ad, Gili; Stavy, Ruth

    2006-01-01

    Our main goal in this study was to explore whether the use of models in molecular genetics instruction in high school can contribute to students' understanding of concepts and processes in genetics. Three comparable groups of 11th and 12th graders participated: The control group (116 students) was taught in the traditional lecture format, while…

  2. An implementation of continuous genetic algorithm in parameter estimation of predator-prey model

    NASA Astrophysics Data System (ADS)

    Windarto

    2016-03-01

    Genetic algorithm is an optimization method based on the principles of genetics and natural selection in life organisms. The main components of this algorithm are chromosomes population (individuals population), parent selection, crossover to produce new offspring, and random mutation. In this paper, continuous genetic algorithm was implemented to estimate parameters in a predator-prey model of Lotka-Volterra type. For simplicity, all genetic algorithm parameters (selection rate and mutation rate) are set to be constant along implementation of the algorithm. It was found that by selecting suitable mutation rate, the algorithms can estimate these parameters well.

  3. Modelling and genetic algorithm based optimisation of inverse supply chain

    NASA Astrophysics Data System (ADS)

    Bányai, T.

    2009-04-01

    (Recycling of household appliances with emphasis on reuse options). The purpose of this paper is the presentation of a possible method for avoiding the unnecessary environmental risk and landscape use through unprovoked large supply chain of collection systems of recycling processes. In the first part of the paper the author presents the mathematical model of recycling related collection systems (applied especially for wastes of electric and electronic products) and in the second part of the work a genetic algorithm based optimisation method will be demonstrated, by the aid of which it is possible to determine the optimal structure of the inverse supply chain from the point of view economical, ecological and logistic objective functions. The model of the inverse supply chain is based on a multi-level, hierarchical collection system. In case of this static model it is assumed that technical conditions are permanent. The total costs consist of three parts: total infrastructure costs, total material handling costs and environmental risk costs. The infrastructure-related costs are dependent only on the specific fixed costs and the specific unit costs of the operation points (collection, pre-treatment, treatment, recycling and reuse plants). The costs of warehousing and transportation are represented by the material handling related costs. The most important factors determining the level of environmental risk cost are the number of out of time recycled (treated or reused) products, the number of supply chain objects and the length of transportation routes. The objective function is the minimization of the total cost taking into consideration the constraints. However a lot of research work discussed the design of supply chain [8], but most of them concentrate on linear cost functions. In the case of this model non-linear cost functions were used. The non-linear cost functions and the possible high number of objects of the inverse supply chain leaded to the problem of choosing a

  4. Generalized Additive Mixed-Models for Pharmacology Using Integrated Discrete Multiple Organ Co-Culture.

    PubMed

    Ingersoll, Thomas; Cole, Stephanie; Madren-Whalley, Janna; Booker, Lamont; Dorsey, Russell; Li, Albert; Salem, Harry

    2016-01-01

    Integrated Discrete Multiple Organ Co-culture (IDMOC) is emerging as an in-vitro alternative to in-vivo animal models for pharmacology studies. IDMOC allows dose-response relationships to be investigated at the tissue and organoid levels, yet, these relationships often exhibit responses that are far more complex than the binary responses often measured in whole animals. To accommodate departure from binary endpoints, IDMOC requires an expansion of analytic techniques beyond simple linear probit and logistic models familiar in toxicology. IDMOC dose-responses may be measured at continuous scales, exhibit significant non-linearity such as local maxima or minima, and may include non-independent measures. Generalized additive mixed-modeling (GAMM) provides an alternative description of dose-response that relaxes assumptions of independence and linearity. We compared GAMMs to traditional linear models for describing dose-response in IDMOC pharmacology studies. PMID:27110941

  5. Generalized Additive Mixed-Models for Pharmacology Using Integrated Discrete Multiple Organ Co-Culture

    PubMed Central

    Ingersoll, Thomas; Cole, Stephanie; Madren-Whalley, Janna; Booker, Lamont; Dorsey, Russell; Li, Albert; Salem, Harry

    2016-01-01

    Integrated Discrete Multiple Organ Co-culture (IDMOC) is emerging as an in-vitro alternative to in-vivo animal models for pharmacology studies. IDMOC allows dose-response relationships to be investigated at the tissue and organoid levels, yet, these relationships often exhibit responses that are far more complex than the binary responses often measured in whole animals. To accommodate departure from binary endpoints, IDMOC requires an expansion of analytic techniques beyond simple linear probit and logistic models familiar in toxicology. IDMOC dose-responses may be measured at continuous scales, exhibit significant non-linearity such as local maxima or minima, and may include non-independent measures. Generalized additive mixed-modeling (GAMM) provides an alternative description of dose-response that relaxes assumptions of independence and linearity. We compared GAMMs to traditional linear models for describing dose-response in IDMOC pharmacology studies. PMID:27110941

  6. Use of additive technologies for practical working with complex models for foundry technologies

    NASA Astrophysics Data System (ADS)

    Olkhovik, E.; Butsanets, A. A.; Ageeva, A. A.

    2016-07-01

    The article presents the results of research of additive technology (3D printing) application for developing a geometrically complex model of castings parts. Investment casting is well known and widely used technology for the production of complex parts. The work proposes the use of a 3D printing technology for manufacturing models parts, which are removed by thermal destruction. Traditional methods of equipment production for investment casting involve the use of manual labor which has problems with dimensional accuracy, and CNC technology which is less used. Such scheme is low productive and demands considerable time. We have offered an alternative method which consists in printing the main knots using a 3D printer (PLA and ABS) with a subsequent production of castings models from them. In this article, the main technological methods are considered and their problems are discussed. The dimensional accuracy of models in comparison with investment casting technology is considered as the main aspect.

  7. Genetics of PTSD: Fear Conditioning as a Model for Future Research.

    PubMed

    Amstadter, Ananda B; Nugent, Nicole R; Koenen, Karestan C

    2009-06-01

    In the last decade, the number of publications in psychiatric genetics has nearly tripled but little attention has been paid to the role of genetic factors in the etiology of posttraumatic stress disorder (PTSD). The present review summarizes the current state of genetic research on PTSD. First, we outline information regarding genetic influences provided by family investigations and by twin studies. Second, we propose the fear-conditioning model of PTSD as a framework for the nomination of candidate genes that may be related to the disorder. Third, we review lines of evidence from three neurobiological systems involved in fear conditioning, and we summarize published investigations of genetic variants studied in association with PTSD in these three systems. Finally, we review gene-by-environment interaction research, a promising novel approach to genetic research in PTSD. PMID:19779593

  8. Genetic modeling of gliomas in mice: new tools to tackle old problems

    PubMed Central

    Hambardzumyan, Dolores; Parada, Luis F.; Holland, Eric C.; Charest, Al

    2011-01-01

    The recently published comprehensive profiles of genomic alterations in glioma have led to a refinement in our understanding of the molecular events that underlie this cancer. Using state-of-the-art genomic tools, several laboratories have created and characterized accurate genetically engineered mouse models of glioma based on specific genetic alterations observed in human tumors. These in vivo brain tumor models faithfully recapitulate the histopathology, etiology, and biology of gliomas and provide an exceptional experimental system to discover novel therapeutic targets and test therapeutic agents. This review focuses on mouse models of glioma with a special emphasis on genetically engineered models developed around key genetic glioma signature mutations in the PDGFR, EGFR and NF1 genes and pathways. The resulting animal models have provided insight into many fundamental and mechanistic facets of tumor initiation, maintenance and resistance to therapeutic intervention and will continue to do so in the future. PMID:21305617

  9. State to State and Charged Particle Kinetic Modeling of Time Filtering and Cs Addition

    SciTech Connect

    Capitelli, M.; Gorse, C.; Longo, S.; Diomede, P.; Pagano, D.

    2007-08-10

    We present here an account on the progress of kinetic simulation of non equilibrium plasmas in conditions of interest for negative ion production by using the 1D Bari code for hydrogen plasma simulation. The model includes the state to state kinetics of the vibrational level population of hydrogen molecules, plus a PIC/MCC module for the multispecies dynamics of charged particles. In particular we present new results for the modeling of two issues of great interest: the time filtering and the Cs addition via surface coverage.

  10. Additional interfacial force in lattice Boltzmann models for incompressible multiphase flows.

    PubMed

    Li, Q; Luo, K H; Gao, Y J; He, Y L

    2012-02-01

    The existing lattice Boltzmann models for incompressible multiphase flows are mostly constructed with two distribution functions: one is the order parameter distribution function, which is used to track the interface between different phases, and the other is the pressure distribution function for solving the velocity field. In this paper, it is shown that in these models the recovered momentum equation is inconsistent with the target one: an additional force is included in the recovered momentum equation. The additional force has the following features. First, it is proportional to the macroscopic velocity. Second, it is zero in every single-phase region but is nonzero in the interface. Therefore it can be interpreted as an interfacial force. To investigate the effects of the additional interfacial force, numerical simulations are carried out for the problem of Rayleigh-Taylor instability, droplet splashing on a thin liquid film, and the evolution of a falling droplet under gravity. Numerical results demonstrate that, with the increase of the velocity or the Reynolds number, the additional interfacial force will gradually have an important influence on the interface and affect the numerical accuracy. PMID:22463354

  11. Model for Assembly Line Re-Balancing Considering Additional Capacity and Outsourcing to Face Demand Fluctuations

    NASA Astrophysics Data System (ADS)

    Samadhi, TMAA; Sumihartati, Atin

    2016-02-01

    The most critical stage in a garment industry is sewing process, because generally, it consists of a number of operations and a large number of sewing machines for each operation. Therefore, it requires a balancing method that can assign task to work station with balance workloads. Many studies on assembly line balancing assume a new assembly line, but in reality, due to demand fluctuation and demand increased a re-balancing is needed. To cope with those fluctuating demand changes, additional capacity can be carried out by investing in spare sewing machine and paying for sewing service through outsourcing. This study develops an assembly line balancing (ALB) model on existing line to cope with fluctuating demand change. Capacity redesign is decided if the fluctuation demand exceeds the available capacity through a combination of making investment on new machines and outsourcing while considering for minimizing the cost of idle capacity in the future. The objective of the model is to minimize the total cost of the line assembly that consists of operating costs, machine cost, adding capacity cost, losses cost due to idle capacity and outsourcing costs. The model develop is based on an integer programming model. The model is tested for a set of data of one year demand with the existing number of sewing machines of 41 units. The result shows that additional maximum capacity up to 76 units of machine required when there is an increase of 60% of the average demand, at the equal cost parameters..

  12. Border cell migration: a model system for live imaging and genetic analysis of collective cell movement.

    PubMed

    Prasad, Mohit; Wang, Xiaobo; He, Li; Montell, Denise J

    2011-01-01

    Border cell migration in the Drosophila ovary has emerged as a genetically tractable model for studying collective cell movement. Over many years border cell migration was exclusively studied in fixed samples due to the inability to culture stage 9 egg chambers in vitro. Although culturing late stage egg chambers was long feasible, stage 9 egg chambers survived only briefly outside the female body. We identified culture conditions that support stage 9 egg chamber development and sustain complete migration of border cells ex vivo. This protocol enables one to compare the dynamics of egg chamber development in wild type and mutant egg chambers using time-lapse microscopy and taking advantage of a multiposition microscope with a motorized imaging stage. In addition, this protocol has been successfully used in combination with fluorescence resonance energy transfer biosensors, photo-activatable proteins, and pharmacological agents and can be used with widefield or confocal microscopes in either an upright or inverted configuration. PMID:21748683

  13. Genome editing revolutionize the creation of genetically modified pigs for modeling human diseases.

    PubMed

    Yao, Jing; Huang, Jiaojiao; Zhao, Jianguo

    2016-09-01

    Pigs have anatomical, physiological and genomic characteristics that make them highly suitable for modeling human diseases. Genetically modified (GM) pig models of human diseases are critical for studying pathogenesis, treatment, and prevention. The emergence of nuclease-mediated genome editing technology has been successfully employed for engineering of the pig genome, which has revolutionize the creation of GM pig models with highly complex pathophysiologies and comorbidities. In this review, we summarize the progress of recently developed genome editing technologies, including zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9), which enable highly efficient and precise introduction of genome modifications into pigs, and tailored disease models that have been generated in various disciplines via genome editing technology. We also summarize the GM pig models that have been generated by conventional transgenic strategies. Additionally, perspectives regarding the application of GM pigs in biomedical research are discussed. PMID:27432159

  14. A genetic mouse model for progressive ablation and regeneration of insulin producing beta-cells

    PubMed Central

    Shamsi, Farnaz; Parlato, Rosanna; Collombat, Patrick; Mansouri, Ahmed

    2014-01-01

    The putative induction of adult β-cell regeneration represents a promising approach for the treatment of type 1 diabetes. Toward this ultimate goal, it is essential to develop an inducible model mimicking the long-lasting disease progression. In the current study, we have established a novel β-cell ablation mouse model, in which the β-cell mass progressively declines, as seen in type 1 diabetes. The model is based on the β-cell specific genetic ablation of the transcription initiation factor 1A, TIF-IA, essential for RNA Polymerase I activity (TIF-IAΔ/Δ). Using this approach, we induced a slow apoptotic response that eventually leads to a protracted β-cell death. In this model, we observed β-cell regeneration that resulted in a complete recovery of the β-cell mass and normoglycemia. In addition, we showed that adaptive proliferation of remaining β-cells is the prominent mechanism acting to compensate for the massive β-cell loss in young but also aged mice. Interestingly, at any age, we also detected β-like cells expressing the glucagon hormone, suggesting a transition between α- and β-cell identities or vice versa. Taken together, the TIF-IAΔ/Δ mouse model can be used to investigate the potential therapeutic approaches for type 1 diabetes targeting β-cell regeneration. PMID:25558832

  15. Efficacy of targeted AKT inhibition in genetically engineered mouse models of PTEN-deficient prostate cancer

    PubMed Central

    De Velasco, Marco A.; Kura, Yurie; Yoshikawa, Kazuhiro; Nishio, Kazuto; Davies, Barry R.; Uemura, Hirotsugu

    2016-01-01

    The PI3K/AKT pathway is frequently altered in advanced human prostate cancer mainly through the loss of functional PTEN, and presents as potential target for personalized therapy. Our aim was to determine the therapeutic potential of the pan-AKT inhibitor, AZD5363, in PTEN-deficient prostate cancer. Here we used a genetically engineered mouse (GEM) model of PTEN-deficient prostate cancer to evaluate the in vivo pharmacodynamic and antitumor activity of AZD5363 in castration-naïve and castration-resistant prostate cancer. An additional GEM model, based on the concomitant inactivation of PTEN and Trp53 (P53), was established as an aggressive model of advanced prostate cancer and was used to further evaluate clinically relevant endpoints after treatment with AZD5363. In vivo pharmacodynamic studies demonstrated that AZD5363 effectively inhibited downstream targets of AKT. AZD5363 monotherapy significantly reduced growth of tumors in castration-naïve and castration-resistant models of PTEN-deficient prostate cancer. More importantly, AZD5363 significantly delayed tumor growth and improved overall survival and progression-free survival in PTEN/P53 double knockout mice. Our findings demonstrate that AZD5363 is effective against GEM models of PTEN-deficient prostate cancer and provide lines of evidence to support further investigation into the development of treatment strategies targeting AKT for the treatment of PTEN-deficient prostate cancer. PMID:26910118

  16. Tau loss attenuates neuronal network hyperexcitability in mouse and Drosophila genetic models of epilepsy

    PubMed Central

    Holth, Jerrah K.; Bomben, Valerie C.; Reed, J. Graham; Inoue, Taeko; Younkin, Linda; Younkin, Steven G.; Pautler, Robia G.; Botas, Juan; Noebels, Jeffrey L.

    2013-01-01

    Neuronal network hyperexcitability underlies the pathogenesis of seizures and is a component of some degenerative neurological disorders such as Alzheimer’s disease (AD). Recently, the microtubule binding protein tau has been implicated in the regulation of network synchronization. Genetic removal of Mapt, the gene encoding tau, in AD models overexpressing amyloid-beta (Aβ) decreases hyperexcitability and normalizes the excitation/inhibition imbalance. Whether this effect of tau removal is specific to Aβ mouse models remains to be determined. Here we examined tau as an excitability modifier in the non-AD nervous system using genetic deletion of tau in mouse and Drosophila models of hyperexcitability. Kcna1−/− mice lack Kv1.1 delayed rectifier currents and exhibit severe spontaneous seizures, early lethality, and megencephaly. Young Kcna1−/− mice retained wild-type levels of Aβ, tau, and tau phospho-Thr231. Decreasing tau in Kcna1−/− mice reduced hyperexcitability and alleviated seizure-related comorbidities. Tau reduction decreased Kcna1−/− video-EEG recorded seizure frequency and duration as well as normalized Kcna1−/− hippocampal network hyperexcitability in vitro. Additionally, tau reduction increased Kcna1−/− survival and prevented megencephaly and hippocampal hypertrophy, as determined by MRI. Bang-sensitive Drosophila mutants display paralysis and seizures in response to mechanical stimulation, providing a complementary excitability assay for epistatic interactions. We found that tau reduction significantly decreased seizure sensitivity in two independent bang-sensitive mutant models, kcc and eas. Our results indicate that tau plays a general role in regulating intrinsic neuronal network hyperexcitability independently of Aβ overexpression and suggest that reducing tau function could be a viable target for therapeutic intervention in seizure disorders and antiepileptogenesis. PMID:23345237

  17. Genetic Model of an Aborted Porphyry-copper System

    NASA Astrophysics Data System (ADS)

    Papp, D. C.; Nitoi, E.; Szakacs, A.

    2009-05-01

    The Neogene Sturzii shallow intrusion from the East Carpathians (Bargau Mts., Romania), hosted by Paleogene-Miocene sediments of the Transcarpatian Flysch, developed as an immature porphyry copper structure. It consists of small volumes of dacites, andesites and related contact breccias, having a surface exposure of a few km2. Hydrothermal alteration occurred in the inner part of the intrusive body. The related mineralization consists of pyrite and chalcopyrite either as small veins or disseminated within the rock. A genetic model of the intrusive structure has been developed based on an integrated petrographic, geochemical, isotopic, fluid inclusion and geophysical study. The rapidly ascending calc-alkaline magmas that generated the intrusion are mantle-derived and contaminated with lower-crustal material. Pressure estimations for amphibole reveal significant differences between values corresponding to the crystal cores and rims, suggesting that decompression occurred during its crystallization. The occurrence of exploded fluid inclusions, as well as of primary igneous garnet, also indicate decompression regime during magma uplift and/or storage. All fluid inclusions identified in dacites are aqueous; C-N-S species were not detected. The general evolution of the fluids is toward decreasing salinity with decreasing temperature. Early high-T, high salinity fluids, most likely of magmatic origin, were subjected to a boiling event, related to a change of fluid pressure from litho- to hydrostatic, and followed by dilution with meteoric fluids as indicated by low salinities. These characteristics of the fluids suggest the tendency of the intrusion to evolve towards a porphyry copper system. We estimate that the evolution stopped due to decompression that allowed cold and dilute external fluids to enter the system and because of the small size of the intrusion that cooled down rapidly and could not induce extensive and long-lasting fluid circulation. Since there is no

  18. Modeling genetic connectivity in sticklebacks as a guideline for river restoration.

    PubMed

    Raeymaekers, Joost A M; Maes, Gregory E; Geldof, Sarah; Hontis, Ingrid; Nackaerts, Kris; Volckaert, Filip A M

    2008-08-01

    Estimating genetic connectivity in disturbed riverine landscapes is of key importance for river restoration. However, few species of the disturbed riverine fauna may provide a detailed and basin-wide picture of the human impact on the population genetics of riverine organisms. Here we used the most abundant native fish, the three-spined stickleback (Gasterosteus aculeatus L.), to detect the geographical determinants of genetic connectivity in the eastern part of the Scheldt basin in Belgium. Anthropogenic structures came out as the strongest determinant of population structure, when evaluated against a geographically well-documented baseline model accounting for natural effects. These barriers not only affected genetic diversity, but they also controlled the balance between gene flow and genetic drift, and therefore may crucially disrupt the population structure of sticklebacks. Landscape models explained a high percentage of variation (allelic richness: adjusted R (2) = 0.78; pairwise F ST: adjusted R (2) = 0.60), and likely apply to other species as well. River restoration and conservation genetics may highly benefit from riverine landscape genetics, including model building, the detection of outlier populations, and a specific test for the geographical factors controlling the balance between gene flow and genetic drift. PMID:25567729

  19. Modeling genetic connectivity in sticklebacks as a guideline for river restoration

    PubMed Central

    Raeymaekers, Joost A M; Maes, Gregory E; Geldof, Sarah; Hontis, Ingrid; Nackaerts, Kris; Volckaert, Filip A M

    2008-01-01

    Estimating genetic connectivity in disturbed riverine landscapes is of key importance for river restoration. However, few species of the disturbed riverine fauna may provide a detailed and basin-wide picture of the human impact on the population genetics of riverine organisms. Here we used the most abundant native fish, the three-spined stickleback (Gasterosteus aculeatus L.), to detect the geographical determinants of genetic connectivity in the eastern part of the Scheldt basin in Belgium. Anthropogenic structures came out as the strongest determinant of population structure, when evaluated against a geographically well-documented baseline model accounting for natural effects. These barriers not only affected genetic diversity, but they also controlled the balance between gene flow and genetic drift, and therefore may crucially disrupt the population structure of sticklebacks. Landscape models explained a high percentage of variation (allelic richness: adjusted R2 = 0.78; pairwise FST: adjusted R2 = 0.60), and likely apply to other species as well. River restoration and conservation genetics may highly benefit from riverine landscape genetics, including model building, the detection of outlier populations, and a specific test for the geographical factors controlling the balance between gene flow and genetic drift. PMID:25567729

  20. Generalized linear and generalized additive models in studies of species distributions: Setting the scene

    USGS Publications Warehouse

    Guisan, A.; Edwards, T.C., Jr.; Hastie, T.

    2002-01-01

    An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001. We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling. ?? 2002 Elsevier Science B.V. All rights reserved.

  1. A patch-based cross masking model for natural images with detail loss and additive defects

    NASA Astrophysics Data System (ADS)

    Liu, Yucheng; Allebach, Jan P.

    2015-03-01

    Visual masking is an effect that contents of the image reduce the detectability of a given target signal hidden in the image. The effect of visual masking has found its application in numerous image processing and vision tasks. In the past few decades, numerous research has been conducted on visual masking based on models optimized for artificial targets placed upon unnatural masks. Over the years, there is a tendency to apply masking model to predict natural image quality and detection threshold of distortion presented in natural images. However, to our knowledge few studies have been conducted to understand the generalizability of masking model to different types of distortion presented in natural images. In this work, we measure the ability of natural image patches in masking three different types of distortion, and analyse the performance of conventional gain control model in predicting the distortion detection threshold. We then propose a new masking model, where detail loss and additive defects are modeled in two parallel vision channels and interact with each other via a cross masking mechanism. We show that the proposed cross masking model has better adaptability to various image structures and distortions in natural scenes.

  2. Modeling the evolution of complex genetic systems: the gene network family tree.

    PubMed

    Fierst, Janna L; Phillips, Patrick C

    2015-01-01

    In 1994 and 1996, Andreas Wagner introduced a novel model in two papers addressing the evolution of genetic regulatory networks. This work, and a suite of papers that followed using similar models, helped integrate network thinking into biology and motivate research focused on the evolution of genetic networks. The Wagner network has its mathematical roots in the Ising model, a statistical physics model describing the activity of atoms on a lattice, and in neural networks. These models have given rise to two branches of applications, one in physics and biology and one in artificial intelligence and machine learning. Here, we review development along these branches, outline similarities and differences between biological models of genetic regulatory circuits and neural circuits models used in machine learning, and identify ways in which these models can provide novel insights into biological systems. PMID:25504926

  3. Linguini Models of Molecular Genetic Mapping and Fingerprinting.

    ERIC Educational Resources Information Center

    Thompson, James N., Jr.; Gray, Stanton B.; Hellack, Jenna J.

    1997-01-01

    Presents an exercise using linguini noodles to demonstrate an aspect of DNA fingerprinting. DNA maps that show genetic differences can be produced by digesting a certain piece of DNA with two or more restriction enzymes both individually and in combination. By rearranging and matching linguini fragments, students can recreate the original pattern…

  4. The case for developing a lacewing genetic model organism

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lacewings (Chrysopidae: Neuroptera) are a family of insect predators, also called aphidlions because of their voracious feeding on aphids. While lacewings have been popular with growers, gardeners, and biological control scientists, they have had little visibility in the world of genetics. Generalis...

  5. Resources allocation in healthcare for cancer: a case study using generalised additive mixed models.

    PubMed

    Musio, Monica; Sauleau, Erik A; Augustin, Nicole H

    2012-11-01

    Our aim is to develop a method for helping resources re-allocation in healthcare linked to cancer, in order to replan the allocation of providers. Ageing of the population has a considerable impact on the use of health resources because aged people require more specialised medical care due notably to cancer. We propose a method useful to monitor changes of cancer incidence in space and time taking into account two age categories, according to healthcar general organisation. We use generalised additive mixed models with a Poisson response, according to the methodology presented in Wood, Generalised additive models: an introduction with R. Chapman and Hall/CRC, 2006. Besides one-dimensional smooth functions accounting for non-linear effects of covariates, the space-time interaction can be modelled using scale invariant smoothers. Incidence data collected by a general cancer registry between 1992 and 2007 in a specific area of France is studied. Our best model exhibits a strong increase of the incidence of cancer along time and an obvious spatial pattern for people more than 70 years with a higher incidence in the central band of the region. This is a strong argument for re-allocating resources for old people cancer care in this sub-region. PMID:23242683

  6. A genetic rat model of cholinergic hypersensitivity: implications for chemical intolerance, chronic fatigue, and asthma.

    PubMed

    Overstreet, D H; Djuric, V

    2001-03-01

    The fact that only some individuals exposed to environmental chemicals develop chemical intolerance raises the possibility that genetic factors could be contributing factors. The present communication summarizes evidence from a genetic animal model of cholinergic supersensitivity that suggests that an abnormal cholinergic system could be one predisposing genetic factor. The Flinders Sensitive Line (FSL) rats were established by selective breeding for increased responses to an organophosphate. It was subsequently found that these FSL rats were also more sensitive to direct-acting muscarinic agonists and had elevated muscarinic receptors compared to the selectively bred parallel group, the Flinders Resistant Line (FRL) rats, or randomly bred control rats. Increased sensitivity to cholinergic agents has also been observed in several human populations, including individuals suffering from chemical intolerance. Indeed, the FSL rats exhibit certain behavioral characteristics such as abnormal sleep, activity, and appetite that are similar to those reported in these human populations. In addition, the FSL rats have been reported to exhibit increased sensitivity to a variety of other chemical agents. Peripheral tissues, such as intestinal and airway smooth muscle, appear to be more sensitive to both cholinergic agonists and an antigen, ovalbumin. Hypothermia, a centrally mediated response, is more pronounced in the FSL rats after nicotine and alcohol, as well as agents that are selective for the dopaminergic and serotonergic systems. In some cases, the increased sensitivity has been detected in the absence of any changes in the receptors with which the drugs interact (dopamine receptors), while receptor changes have been seen in other cases (nicotine receptors). Therefore, there may be multiple mechanisms underlying the multiple chemical sensitivity-chemical intolerance of the FSL rats. An elucidation of these mechanisms may provide useful clues to those involved in

  7. USE OF MODELING APPROACHES TO UNDERSTAND POTENTIAL IMPACTS OF GENETICALLY MODIFIED PLANTS ON PLANT COMMUNITIES

    EPA Science Inventory

    Model development is of interest to ecologists, regulators and developers, since it may assist theoretical understanding, decision making in experimental design, product development and risk assessment. In order to predict the potential impacts of genetically modified (GM) plants...

  8. Evaporation model for beam based additive manufacturing using free surface lattice Boltzmann methods

    NASA Astrophysics Data System (ADS)

    Klassen, Alexander; Scharowsky, Thorsten; Körner, Carolin

    2014-07-01

    Evaporation plays an important role in many technical applications including beam-based additive manufacturing processes, such as selective electron beam or selective laser melting (SEBM/SLM). In this paper, we describe an evaporation model which we employ within the framework of a two-dimensional free surface lattice Boltzmann method. With this method, we solve the hydrodynamics as well as thermodynamics of the molten material taking into account the mass and energy losses due to evaporation and the recoil pressure acting on the melt pool. Validation of the numerical model is performed by measuring maximum melt depths and evaporative losses in samples of pure titanium and Ti-6Al-4V molten by an electron beam. Finally, the model is applied to create processing maps for an SEBM process. The results predict that the penetration depth of the electron beam, which is a function of the acceleration voltage, has a significant influence on evaporation effects.

  9. Parity Symmetry and Parity Breaking in the Quantum Rabi Model with Addition of Ising Interaction

    NASA Astrophysics Data System (ADS)

    Wang, Qiong; He, Zhi; Yao, Chun-Mei

    2015-04-01

    We explore the possibility to generate new parity symmetry in the quantum Rabi model after a bias is introduced. In contrast to a mathematical treatment in a previous publication [J. Phys. A 46 (2013) 265302], we consider a physically realistic method by involving an additional spin into the quantum Rabi model to couple with the original spin by an Ising interaction, and then the parity symmetry is broken as well as the scaling behavior of the ground state by introducing a bias. The rule can be found that the parity symmetry is broken by introducing a bias and then restored by adding new degrees of freedom. Experimental feasibility of realizing the models under discussion is investigated. Supported by the National Natural Science Foundation of China under Grant Nos. 61475045 and 11347142, the Natural Science Foundation of Hunan Province, China under Grant No. 2015JJ3092

  10. Hydrophobic interactions in model enclosures from small to large length scales: non-additivity in explicit and implicit solvent models

    PubMed Central

    Wang, Lingle; Friesner, Richard A.; Berne, B. J.

    2011-01-01

    The binding affinities between a united-atom methane and various model hydrophobic enclosures were studied through high accuracy free energy perturbation methods (FEP). We investigated the non-additivity of the hydrophobic interaction in these systems, measured by the deviation of its binding affinity from that predicted by the pairwise additivity approximation. While only small non-additivity effects were previously reported in the interactions in methane trimers, we found large cooperative effects (as large as −1.14 kcal mol−1 or approximately a 25% increase in the binding affinity) and anti-cooperative effects (as large as 0.45 kcal mol−1) for these model enclosed systems. Decomposition of the total potential of mean force (PMF) into increasing orders of multi-body interactions indicates that the contributions of the higher order multi-body interactions can be either positive or negative in different systems, and increasing the order of multi-body interactions considered did not necessarily improve the accuracy. A general correlation between the sign of the non-additivity effect and the curvature of the solute molecular surface was observed. We found that implicit solvent models based on the molecular surface area (MSA) performed much better, not only in predicting binding affinities, but also in predicting the non-additivity effects, compared with models based on the solvent accessible surface area (SASA), suggesting that MSA is a better descriptor of the curvature of the solutes. We also show how the non-additivity contribution changes as the hydrophobicity of the plate is decreased from the dewetting regime to the wetting regime. PMID:21043426

  11. Drosophila melanogaster as a genetic model system to study neurotransmitter transporters

    PubMed Central

    Martin, Ciara A.; Krantz, David E.

    2014-01-01

    The model genetic organism Drosophila melanogaster, commonly known as the fruit fly, uses many of the same neurotransmitters as mammals and very similar mechanisms of neurotransmitter storage, release and recycling. This system offers a variety of powerful molecular-genetic methods for the study of transporters, many of which would be difficult in mammalian models. We review here progress made using Drosophila to understand the function and regulation of neurotransmitter transporters and discuss future directions for its use. PMID:24704795

  12. Wall-models for large eddy simulation based on a generic additive-filter formulation

    NASA Astrophysics Data System (ADS)

    Sanchez Rocha, Martin

    Based on the philosophy of only resolving the large scales of turbulent motion, Large Eddy Simulation (LES) has demonstrated potential to provide high-fidelity turbulence simulations at low computational cost. However, when the scales that control the turbulence in a particular flow are not large, LES has to increase significantly its computational cost to provide accurate predictions. This is the case in wall-bounded flows, where the grid resolution required by LES to resolve the near-wall structures is close to the requirements to resolve the smallest dissipative scales in turbulence. Therefore, to reduce this demanding requirement, it has been proposed to model the near-wall region with Reynolds-Averaged Navier-Stokes (RANS) models, in what is known as hybrid RANS/LES approach. In this work, the mathematical implications of merging two different turbulence modeling approaches are addressed by deriving the exact hybrid RANS/LES Navier-Stokes equations. These equations are derived by introducing an additive-filter, which linearly combines the RANS and LES operators with a blending function. The equations derived with the additive-filter predict additional hybrid terms, which represent the interactions between RANS and LES formulations. Theoretically, the prediction of the hybrid terms demonstrates that the hybridization of the two approaches cannot be accomplished only by the turbulence model equations, as it is claimed in current hybrid RANS/LES models. The importance of the exact hybrid RANS/LES equations is demonstrated by conducting numerical calculations on a turbulent flat-plate boundary layer. Results indicate that the hybrid terms help to maintain an equilibrated model transition when the hybrid formulation switches from RANS to LES. Results also indicate, that when the hybrid terms are not included, the accuracy of the calculations strongly relies on the blending function implemented in the additive-filter. On the other hand, if the exact equations are

  13. Genetic mouse models to study blood–brain barrier development and function

    PubMed Central

    2013-01-01

    The blood–brain barrier (BBB) is a complex physiological structure formed by the blood vessels of the central nervous system (CNS) that tightly regulates the movement of substances between the blood and the neural tissue. Recently, the generation and analysis of different genetic mouse models has allowed for greater understanding of BBB development, how the barrier is regulated during health, and its response to disease. Here we discuss: 1) Genetic mouse models that have been used to study the BBB, 2) Available mouse genetic tools that can aid in the study of the BBB, and 3) Potential tools that if generated could greatly aid in our understanding of the BBB. PMID:23305182

  14. Genetic and cultural transmission of antisocial behavior: an extended twin parent model.

    PubMed

    Maes, Hermine H; Silberg, Judy L; Neale, Michael C; Eaves, Lindon J

    2007-02-01

    Considerable evidence from twin and adoption studies indicates that both genetic and shared environmental factors play a substantial role in the liability to antisocial behavior. Although twin and adoption designs can resolve genetic and environmental influences, they do not provide information about assortative mating, parent-offspring transmission, or the contribution of these factors to trait variation. We examined the role of genetic and environmental factors for conduct disorder (CD) using a twin-parent design. This design allows the simultaneous estimation of additive genetic, shared and individual-specific environmental effects, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission. A retrospective measure of CD was obtained from twins and their parents or guardians in the Virginia Twin Study of Adolescent Behavior Development and its Young Adult Follow up sample. Both genetic and environmental factors play a significant role in the liability to CD. Major influences on individual differences appeared to be additive genetic (38%-40%) and unique environmental (39%-42%) effects, with smaller contributions from the shared environment (18%-23%), assortative mating (-2%), cultural transmission (approximately 2%) and resulting genotype-environment covariance. This study showed significant heritability, which is slightly increased by assortative mating, and significant effects of primarily nonparental shared environment on CD. PMID:17539373

  15. Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

    PubMed

    Bellucci, Michael A; Coker, David F

    2011-07-28

    We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. PMID:21806098

  16. Modelling and genetic algorithm based optimisation of inverse supply chain

    NASA Astrophysics Data System (ADS)

    Bányai, T.

    2009-04-01

    (Recycling of household appliances with emphasis on reuse options). The purpose of this paper is the presentation of a possible method for avoiding the unnecessary environmental risk and landscape use through unprovoked large supply chain of collection systems of recycling processes. In the first part of the paper the author presents the mathematical model of recycling related collection systems (applied especially for wastes of electric and electronic products) and in the second part of the work a genetic algorithm based optimisation method will be demonstrated, by the aid of which it is possible to determine the optimal structure of the inverse supply chain from the point of view economical, ecological and logistic objective functions. The model of the inverse supply chain is based on a multi-level, hierarchical collection system. In case of this static model it is assumed that technical conditions are permanent. The total costs consist of three parts: total infrastructure costs, total material handling costs and environmental risk costs. The infrastructure-related costs are dependent only on the specific fixed costs and the specific unit costs of the operation points (collection, pre-treatment, treatment, recycling and reuse plants). The costs of warehousing and transportation are represented by the material handling related costs. The most important factors determining the level of environmental risk cost are the number of out of time recycled (treated or reused) products, the number of supply chain objects and the length of transportation routes. The objective function is the minimization of the total cost taking into consideration the constraints. However a lot of research work discussed the design of supply chain [8], but most of them concentrate on linear cost functions. In the case of this model non-linear cost functions were used. The non-linear cost functions and the possible high number of objects of the inverse supply chain leaded to the problem of choosing a

  17. Discrete time spatial models arising in genetics, evolutionary game theory, and branching processes.

    PubMed

    Radcliffe, J; Rass, L

    1997-03-01

    A saddle point method is used to obtain the speed of first spread of new genotypes in genetic models and of new strategies in game theoretic models. It is also used to obtain the speed of the forward tail of the distribution of farthest spread for branching process models. The technique is applicable to a wide range of models. They include multiple allele and sex-linked models in genetics, multistrategy and bimatrix evolutionary games, and multitype and demographic branching processes. The speed of propagation has been obtained for genetics models (in simple cases only) by Weinberger and Lui, using exact analytical methods. The exact results were obtained only for two-allele, single-locus genetic models. The saddle point method agrees in these very simple cases with the results obtained by using the exact analytic methods. Of course, it can also be used in much more general situations far less tractable to exact analysis. The connection between genetic and game theoretic models is also briefly considered, as is the extent to which the exact analytic methods yield results for simple models in game theory. PMID:9046771

  18. Analysis of Time to Event Outcomes in Randomized Controlled Trials by Generalized Additive Models

    PubMed Central

    Argyropoulos, Christos; Unruh, Mark L.

    2015-01-01

    Background Randomized Controlled Trials almost invariably utilize the hazard ratio calculated with a Cox proportional hazard model as a treatment efficacy measure. Despite the widespread adoption of HRs, these provide a limited understanding of the treatment effect and may even provide a biased estimate when the assumption of proportional hazards in the Cox model is not verified by the trial data. Additional treatment effect measures on the survival probability or the time scale may be used to supplement HRs but a framework for the simultaneous generation of these measures is lacking. Methods By splitting follow-up time at the nodes of a Gauss Lobatto numerical quadrature rule, techniques for Poisson Generalized Additive Models (PGAM) can be adopted for flexible hazard modeling. Straightforward simulation post-estimation transforms PGAM estimates for the log hazard into estimates of the survival function. These in turn were used to calculate relative and absolute risks or even differences in restricted mean survival time between treatment arms. We illustrate our approach with extensive simulations and in two trials: IPASS (in which the proportionality of hazards was violated) and HEMO a long duration study conducted under evolving standards of care on a heterogeneous patient population. Findings PGAM can generate estimates of the survival function and the hazard ratio that are essentially identical to those obtained by Kaplan Meier curve analysis and the Cox model. PGAMs can simultaneously provide multiple measures of treatment efficacy after a single data pass. Furthermore, supported unadjusted (overall treatment effect) but also subgroup and adjusted analyses, while incorporating multiple time scales and accounting for non-proportional hazards in survival data. Conclusions By augmenting the HR conventionally reported, PGAMs have the potential to support the inferential goals of multiple stakeholders involved in the evaluation and appraisal of clinical trial

  19. Topsoil organic carbon content of Europe, a new map based on a generalised additive model

    NASA Astrophysics Data System (ADS)

    de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

    2014-05-01

    There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average

  20. Predicting the Survival Time for Bladder Cancer Using an Additive Hazards Model in Microarray Data

    PubMed Central

    TAPAK, Leili; MAHJUB, Hossein; SADEGHIFAR, Majid; SAIDIJAM, Massoud; POOROLAJAL, Jalal

    2016-01-01

    Background: One substantial part of microarray studies is to predict patients’ survival based on their gene expression profile. Variable selection techniques are powerful tools to handle high dimensionality in analysis of microarray data. However, these techniques have not been investigated in competing risks setting. This study aimed to investigate the performance of four sparse variable selection methods in estimating the survival time. Methods: The data included 1381 gene expression measurements and clinical information from 301 patients with bladder cancer operated in the years 1987 to 2000 in hospitals in Denmark, Sweden, Spain, France, and England. Four methods of the least absolute shrinkage and selection operator, smoothly clipped absolute deviation, the smooth integration of counting and absolute deviation and elastic net were utilized for simultaneous variable selection and estimation under an additive hazards model. The criteria of area under ROC curve, Brier score and c-index were used to compare the methods. Results: The median follow-up time for all patients was 47 months. The elastic net approach was indicated to outperform other methods. The elastic net had the lowest integrated Brier score (0.137±0.07) and the greatest median of the over-time AUC and C-index (0.803±0.06 and 0.779±0.13, respectively). Five out of 19 selected genes by the elastic net were significant (P<0.05) under an additive hazards model. It was indicated that the expression of RTN4, SON, IGF1R and CDC20 decrease the survival time, while the expression of SMARCAD1 increase it. Conclusion: The elastic net had higher capability than the other methods for the prediction of survival time in patients with bladder cancer in the presence of competing risks base on additive hazards model. PMID:27114989

  1. Comparison of prosthetic models produced by traditional and additive manufacturing methods

    PubMed Central

    Park, Jin-Young; Kim, Hae-Young; Kim, Ji-Hwan; Kim, Jae-Hong

    2015-01-01

    PURPOSE The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). MATERIALS AND METHODS Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (α=.05). RESULTS The mean marginal gaps and internal gaps showed significant differences according to tooth type (P<.001 and P<.001, respectively) and manufacturing method (P<.037 and P<.001, respectively). Micro-SLA did not show any significant difference from CLWT regarding mean marginal gap compared to the WBM and MJM methods. CONCLUSION The mean values of gaps resulting from the four different manufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing. PMID:26330976

  2. Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

    NASA Astrophysics Data System (ADS)

    Sastry, Kumara Narasimha

    2007-03-01

    Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

  3. Thermodynamic network model for predicting effects of substrate addition and other perturbations on subsurface microbial communities

    SciTech Connect

    Jack Istok; Melora Park; James McKinley; Chongxuan Liu; Lee Krumholz; Anne Spain; Aaron Peacock; Brett Baldwin

    2007-04-19

    The overall goal of this project is to develop and test a thermodynamic network model for predicting the effects of substrate additions and environmental perturbations on microbial growth, community composition and system geochemistry. The hypothesis is that a thermodynamic analysis of the energy-yielding growth reactions performed by defined groups of microorganisms can be used to make quantitative and testable predictions of the change in microbial community composition that will occur when a substrate is added to the subsurface or when environmental conditions change.

  4. Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

    USGS Publications Warehouse

    Louis, S.J.; Raines, G.L.

    2003-01-01

    We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

  5. Identifying future models for delivering genetic services: a nominal group study in primary care

    PubMed Central

    Elwyn, Glyn; Edwards, Adrian; Iredale, Rachel; Davies, Peter; Gray, Jonathon

    2005-01-01

    Background To enable primary care medical practitioners to generate a range of possible service delivery models for genetic counselling services and critically assess their suitability. Methods Modified nominal group technique using in primary care professional development workshops. Results 37 general practitioners in Wales, United Kingdom too part in the nominal group process. The practitioners who attended did not believe current systems were sufficient to meet anticipated demand for genetic services. A wide range of different service models was proposed, although no single option emerged as a clear preference. No argument was put forward for genetic assessment and counselling being central to family practice, neither was there a voice for the view that the family doctor should become skilled at advising patients about predictive genetic testing and be able to counsel patients about the wider implications of genetic testing for patients and their family members, even for areas such as common cancers. Nevertheless, all the preferred models put a high priority on providing the service in the community, and often co-located in primary care, by clinicians who had developed expertise. Conclusion There is a need for a wider debate about how healthcare systems address individual concerns about genetic concerns and risk, especially given the increasing commercial marketing of genetic tests. PMID:15831099

  6. Ocean circulation model predicts high genetic structure observed in a long-lived pelagic developer.

    PubMed

    Sunday, J M; Popovic, I; Palen, W J; Foreman, M G G; Hart, M W

    2014-10-01

    Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes and may not capture present-day connectivity between populations. Here, we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns, which tend to retain passive larvae within 20-50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks. PMID:25231198

  7. Coupling genetic and ecological-niche models to examine how past population distributions contribute to divergence.

    PubMed

    Knowles, L Lacey; Carstens, Bryan C; Keat, Marcia L

    2007-06-01

    Understanding the impact of climate-induced distributional shifts on species divergence, like those accompanying the Pleistocene glacial cycles [1, 2], requires tools that explicitly incorporate the geographic configuration of past distributions into analyses of genetic differentiation. Depending on the historical distribution of species, genetic differences may accumulate among ancestral source populations, but there is long-standing debate whether displacements into glacial refugia promoted divergence. Here we integrate coalescent-based genetic models [3, 4] with ecological-niche modeling [5, 6] to generate expectations for patterns of genetic variation based on an inferred past distribution of a species. Reconstruction of the distribution of a montane grasshopper species during the last glacial maximum suggests that Melanoplus marshalli populations from the sky islands of Colorado and Utah were likely colonized from multiple ancestral source populations. The genetic analyses provide compelling evidence that the historical distribution of M. marshalli-namely, spatial separation of multiple refugia-was conducive to genetic differentiation. The coupling of genetic and ecological-niche modeling provides a new and flexible tool for integrating paleoenvironmental details into species-specific predictions of population structure that can increase our understanding of why the glacial cycles promoted speciation in some taxa and yet inhibited diversification in others [7, 8]. PMID:17475496

  8. Transposon mouse models to elucidate the genetic mechanisms of hepatitis B viral induced hepatocellular carcinoma.

    PubMed

    Chiu, Amy P; Tschida, Barbara R; Lo, Lilian H; Moriarity, Branden S; Rowlands, Dewi K; Largaespada, David A; Keng, Vincent W

    2015-11-14

    The major type of human liver cancer is hepatocellular carcinoma (HCC), and there are currently many risk factors that contribute to this deadly disease. The majority of HCC occurrences are associated with chronic hepatitis viral infection, and hepatitis B viral (HBV) infection is currently a major health problem in Eastern Asia. Elucidating the genetic mechanisms associated with HBV-induced HCC has been difficult due to the heterogeneity and genetic complexity associated with this disease. A repertoire of animal models has been broadly used to study the pathophysiology and to develop potential treatment regimens for HBV-associated HCC. The use of these animal models has provided valuable genetic information and has been an important contributor to uncovering the factors involved in liver malignant transformation, invasion and metastasis. Recently, transposon-based mouse models are becoming more widely used in liver cancer research to interrogate the genome by forward genetics and also used to validate genes rapidly in a reverse genetic manner. Importantly, these transposon-based rapid reverse genetic mouse models could become crucial in testing potential therapeutic agents before proceeding to clinical trials in human. Therefore, this review will cover the use of transposon-based mouse models to address the problems of liver cancer, especially HBV-associated HCC occurrences in Asia. PMID:26576100

  9. Transposon mouse models to elucidate the genetic mechanisms of hepatitis B viral induced hepatocellular carcinoma

    PubMed Central

    Chiu, Amy P; Tschida, Barbara R; Lo, Lilian H; Moriarity, Branden S; Rowlands, Dewi K; Largaespada, David A; Keng, Vincent W

    2015-01-01

    The major type of human liver cancer is hepatocellular carcinoma (HCC), and there are currently many risk factors that contribute to this deadly disease. The majority of HCC occurrences are associated with chronic hepatitis viral infection, and hepatitis B viral (HBV) infection is currently a major health problem in Eastern Asia. Elucidating the genetic mechanisms associated with HBV-induced HCC has been difficult due to the heterogeneity and genetic complexity associated with this disease. A repertoire of animal models has been broadly used to study the pathophysiology and to develop potential treatment regimens for HBV-associated HCC. The use of these animal models has provided valuable genetic information and has been an important contributor to uncovering the factors involved in liver malignant transformation, invasion and metastasis. Recently, transposon-based mouse models are becoming more widely used in liver cancer research to interrogate the genome by forward genetics and also used to validate genes rapidly in a reverse genetic manner. Importantly, these transposon-based rapid reverse genetic mouse models could become crucial in testing potential therapeutic agents before proceeding to clinical trials in human. Therefore, this review will cover the use of transposon-based mouse models to address the problems of liver cancer, especially HBV-associated HCC occurrences in Asia. PMID:26576100

  10. Cycles of Exploration, Reflection, and Consolidation in Model-Based Learning of Genetics

    ERIC Educational Resources Information Center

    Kim, Beaumie; Pathak, Suneeta A.; Jacobson, Michael J.; Zhang, Baohui; Gobert, Janice D.

    2015-01-01

    Model-based reasoning has been introduced as an authentic way of learning science, and many researchers have developed technological tools for learning with models. This paper describes how a model-based tool, "BioLogica"™, was used to facilitate genetics learning in secondary 3-level biology in Singapore. The research team co-designed…

  11. Rate of evolutionary change in cranial morphology of the marsupial genus Monodelphis is constrained by the availability of additive genetic variation.

    PubMed

    Porto, A; Sebastião, H; Pavan, S E; VandeBerg, J L; Marroig, G; Cheverud, J M

    2015-04-01

    We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyse the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation. PMID:25818173

  12. Rate of evolutionary change in cranial morphology of the marsupial genus Monodelphis is constrained by the availability of additive genetic variation

    PubMed Central

    Porto, Arthur; Sebastião, Harley; Pavan, Silvia Eliza; VandeBerg, John L.; Marroig, Gabriel; Cheverud, James M.

    2015-01-01

    We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyze the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation. PMID:25818173

  13. Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

    NASA Astrophysics Data System (ADS)

    Ushijima, Timothy T.; Yeh, William W.-G.

    2013-10-01

    An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

  14. Coupling Genetic and Species Distribution Models to Examine the Response of the Hainan Partridge (Arborophila ardens) to Late Quaternary Climate

    PubMed Central

    Chang, Jiang; Chen, De; Ye, Xinping; Li, Shouhsien; Liang, Wei; Zhang, Zhengwang; Li, Ming

    2012-01-01

    Understanding the historical dynamics of animal species is critical for accurate prediction of their response to climate changes. During the late Quaternary period, Southeast Asia had a larger land area than today due to lower sea levels, and its terrestrial landscape was covered by extensive forests and savanna. To date, however, the distribution fluctuation of vegetation and its impacts on genetic structure and demographic history of local animals during the Last Glacial Maximum (LGM) are still disputed. In addition, the responses of animal species on Hainan Island, located in northern Southeast Asia, to climate changes during the LGM are poorly understood. Here, we combined phylogeographic analysis, paleoclimatic evidence, and species distribution models to examine the response of the flightless Hainan Partridge (Arborophila ardens) to climate change. We concluded that A. ardens survived through LGM climate changes, and its current distribution on Hainan Island was its in situ refuge. Range model results indicated that A. ardens once covered a much larger area than its current distribution. Demographic history described a relatively stable pattern during and following the LGM. In addition, weak population genetic structure suggests a role in promoting gene flow between populations with climate-induced elevation shifts. Human activities must be considered in conservation planning due to their impact on fragmented habitats. These first combined data for Hainan Partridge demonstrate the value of paired genetic and SDMs study. More related works that might deepen our understanding of the responses of the species in Southeast Asia to late Quaternary Climate are needed. PMID:23185599

  15. Analysis and Modeling of soil hydrology under different soil additives in artificial runoff plots

    NASA Astrophysics Data System (ADS)

    Ruidisch, M.; Arnhold, S.; Kettering, J.; Huwe, B.; Kuzyakov, Y.; Ok, Y.; Tenhunen, J. D.

    2009-12-01

    The impact of monsoon events during June and July in the Korean project region Haean Basin, which is located in the northeastern part of South Korea plays a key role for erosion, leaching and groundwater pollution risk by agrochemicals. Therefore, the project investigates the main hydrological processes in agricultural soils under field and laboratory conditions on different scales (plot, hillslope and catchment). Soil hydrological parameters were analysed depending on different soil additives, which are known for prevention of soil erosion and nutrient loss as well as increasing of water infiltration, aggregate stability and soil fertility. Hence, synthetic water-soluble Polyacrylamides (PAM), Biochar (Black Carbon mixed with organic fertilizer), both PAM and Biochar were applied in runoff plots at three agricultural field sites. Additionally, as control a subplot was set up without any additives. The field sites were selected in areas with similar hillslope gradients and with emphasis on the dominant land management form of dryland farming in Haean, which is characterised by row planting and row covering by foil. Hydrological parameters like satured water conductivity, matrix potential and water content were analysed by infiltration experiments, continuous tensiometer measurements, time domain reflectometry as well as pressure plates to indentify characteristic water retention curves of each horizon. Weather data were observed by three weather stations next to the runoff plots. Measured data also provide the input data for modeling water transport in the unsatured zone in runoff plots with HYDRUS 1D/2D/3D and SWAT (Soil & Water Assessment Tool).

  16. Guarana provides additional stimulation over caffeine alone in the planarian model.

    PubMed

    Moustakas, Dimitrios; Mezzio, Michael; Rodriguez, Branden R; Constable, Mic Andre; Mulligan, Margaret E; Voura, Evelyn B

    2015-01-01

    The stimulant effect of energy drinks is primarily attributed to the caffeine they contain. Many energy drinks also contain other ingredients that might enhance the tonic effects of these caffeinated beverages. One of these additives is guarana. Guarana is a climbing plant native to the Amazon whose seeds contain approximately four times the amount of caffeine found in coffee beans. The mix of other natural chemicals contained in guarana seeds is thought to heighten the stimulant effects of guarana over caffeine alone. Yet, despite the growing use of guarana as an additive in energy drinks, and a burgeoning market for it as a nutritional supplement, the science examining guarana and how it affects other dietary ingredients is lacking. To appreciate the stimulant effects of guarana and other natural products, a straightforward model to investigate their physiological properties is needed. The planarian provides such a system. The locomotor activity and convulsive response of planarians with substance exposure has been shown to provide an excellent system to measure the effects of drug stimulation, addiction and withdrawal. To gauge the stimulant effects of guarana we studied how it altered the locomotor activity of the planarian species Dugesia tigrina. We report evidence that guarana seeds provide additional stimulation over caffeine alone, and document the changes to this stimulation in the context of both caffeine and glucose. PMID:25880065

  17. Guarana Provides Additional Stimulation over Caffeine Alone in the Planarian Model

    PubMed Central

    Moustakas, Dimitrios; Mezzio, Michael; Rodriguez, Branden R.; Constable, Mic Andre; Mulligan, Margaret E.; Voura, Evelyn B.

    2015-01-01

    The stimulant effect of energy drinks is primarily attributed to the caffeine they contain. Many energy drinks also contain other ingredients that might enhance the tonic effects of these caffeinated beverages. One of these additives is guarana. Guarana is a climbing plant native to the Amazon whose seeds contain approximately four times the amount of caffeine found in coffee beans. The mix of other natural chemicals contained in guarana seeds is thought to heighten the stimulant effects of guarana over caffeine alone. Yet, despite the growing use of guarana as an additive in energy drinks, and a burgeoning market for it as a nutritional supplement, the science examining guarana and how it affects other dietary ingredients is lacking. To appreciate the stimulant effects of guarana and other natural products, a straightforward model to investigate their physiological properties is needed. The planarian provides such a system. The locomotor activity and convulsive response of planarians with substance exposure has been shown to provide an excellent system to measure the effects of drug stimulation, addiction and withdrawal. To gauge the stimulant effects of guarana we studied how it altered the locomotor activity of the planarian species Dugesia tigrina. We report evidence that guarana seeds provide additional stimulation over caffeine alone, and document the changes to this stimulation in the context of both caffeine and glucose. PMID:25880065

  18. Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive Models.

    PubMed

    Fan, Jianqing; Feng, Yang; Song, Rui

    2011-06-01

    A variable screening procedure via correlation learning was proposed in Fan and Lv (2008) to reduce dimensionality in sparse ultra-high dimensional models. Even when the true model is linear, the marginal regression can be highly nonlinear. To address this issue, we further extend the correlation learning to marginal nonparametric learning. Our nonparametric independence screening is called NIS, a specific member of the sure independence screening. Several closely related variable screening procedures are proposed. Under general nonparametric models, it is shown that under some mild technical conditions, the proposed independence screening methods enjoy a sure screening property. The extent to which the dimensionality can be reduced by independence screening is also explicitly quantified. As a methodological extension, a data-driven thresholding and an iterative nonparametric independence screening (INIS) are also proposed to enhance the finite sample performance for fitting sparse additive models. The simulation results and a real data analysis demonstrate that the proposed procedure works well with moderate sample size and large dimension and performs better than competing methods. PMID:22279246

  19. Creep damage in a localized load sharing fibre bundle model with additional ageing

    NASA Astrophysics Data System (ADS)

    Lennartz-Sassinek, Sabine; Danku, Zsuzsa; Main, Ian; Kun, Ferenc

    2013-04-01

    Many fields of science are interested in the damage growth in earth materials. Often the damage propagates not in big avalanches like the crack growth measured by acoustic emissions. Also "silent" damage may occur whose emissions are either to small to be detected or mix with back ground noise. These silent emissions may carry the majority of the over all damage in a system until failure. One famous model for damage growth is the fibre bundle model. Here we consider an extended version of a localized load sharing fibre bundle model which incorporates additional time dependent ageing of each fibre motivated by a chemically active environment. We present the non-trivial time dependent damage growth in this model in the low load limit representing creep damage far away from failure. We show both numerical simulations and analytical equations describing the damage rate of silent events and the corresponding amount of triggered "acoustic" damage. The analytical description is in agreement with the numerical results.

  20. Model Scramjet Inlet Unstart Induced by Mass Addition and Heat Release

    NASA Astrophysics Data System (ADS)

    Im, Seong-Kyun; Baccarella, Damiano; McGann, Brendan; Liu, Qili; Wermer, Lydiy; Do, Hyungrok

    2015-11-01

    The inlet unstart phenomena in a model scramjet are investigated at an arc-heated hypersonic wind tunnel. The unstart induced by nitrogen or ethylene jets at low or high enthalpy Mach 4.5 freestream flow conditions are compared. The jet injection pressurizes the downstream flow by mass addition and flow blockage. In case of the ethylene jet injection, heat release from combustion increases the backpressure further. Time-resolved schlieren imaging is performed at the jet and the lip of the model inlet to visualize the flow features during unstart. High frequency pressure measurements are used to provide information on pressure fluctuation at the scramjet wall. In both of the mass and heat release driven unstart cases, it is observed that there are similar flow transient and quasi-steady behaviors of unstart shockwave system during the unstart processes. Combustion driven unstart induces severe oscillatory flow motions of the jet and the unstart shock at the lip of the scramjet inlet after the completion of the unstart process, while the unstarted flow induced by solely mass addition remains relatively steady. The discrepancies between the processes of mass and heat release driven unstart are explained by flow choking mechanism.

  1. Empirical predictive model for the vmax/ amax ratio of strong ground motions using genetic programming

    NASA Astrophysics Data System (ADS)

    Jafarian, Yaser; Kermani, Elnaz; Baziar, Mohammad H.

    2010-12-01

    Earthquake-induced deformation of structures is strongly influenced by the frequency content of input motion. Nevertheless, state-of-the-practice studies commonly use the intensity measures such as peak ground acceleration ( PGA), which are not frequency dependent. The vmax/ amax ratio of strong ground motions can be used in seismic hazard studies as a parameter that captures the influence of frequency content. In the present study, genetic programming (GP) is employed to develop a new empirical predictive equation for the vmax/ amax ratio of the shallow crustal strong ground motions recorded at free field sites. The proposed model is a function of earthquake magnitude, closest distance from source to site ( Rclstd), faulting mechanism, and average shear wave velocity over the top 30 m of site ( Vs30 ). A wide-ranging database of strong ground motion released by Pacific Earthquake Engineering Research Center (PEER) was utilized. It is demonstrated that residuals of the final equation show insignificant bias against the variations of the predictive parameters. The results indicate that vmax/ amax increases through increasing earthquake magnitude and source-to-site distance while magnitude dependency is considerably more than distance dependency. In addition, the proposed model predicts higher vmax/ amax ratio at softer sites that possess higher fundamental periods. Consequently, as an instance for the application of the proposed model, its reasonable performance in liquefaction potential assessment of sands and silty sands is presented.

  2. Apoc2 loss-of-function zebrafish mutant as a genetic model of hyperlipidemia.

    PubMed

    Liu, Chao; Gates, Keith P; Fang, Longhou; Amar, Marcelo J; Schneider, Dina A; Geng, Honglian; Huang, Wei; Kim, Jungsu; Pattison, Jennifer; Zhang, Jian; Witztum, Joseph L; Remaley, Alan T; Dong, P Duc; Miller, Yury I

    2015-08-01

    Apolipoprotein C-II (APOC2) is an obligatory activator of lipoprotein lipase. Human patients with APOC2 deficiency display severe hypertriglyceridemia while consuming a normal diet, often manifesting xanthomas, lipemia retinalis and pancreatitis. Hypertriglyceridemia is also an important risk factor for development of cardiovascular disease. Animal models to study hypertriglyceridemia are limited, with no Apoc2-knockout mouse reported. To develop a genetic model of hypertriglyceridemia, we generated an apoc2 mutant zebrafish characterized by the loss of Apoc2 function. apoc2 mutants show decreased plasma lipase activity and display chylomicronemia and severe hypertriglyceridemia, which closely resemble the phenotype observed in human patients with APOC2 deficiency. The hypertriglyceridemia in apoc2 mutants is rescued by injection of plasma from wild-type zebrafish or by injection of a human APOC2 mimetic peptide. Consistent with a previous report of a transient apoc2 knockdown, apoc2 mutant larvae have a minor delay in yolk consumption and angiogenesis. Furthermore, apoc2 mutants fed a normal diet accumulate lipid and lipid-laden macrophages in the vasculature, which resemble early events in the development of human atherosclerotic lesions. In addition, apoc2 mutant embryos show ectopic overgrowth of pancreas. Taken together, our data suggest that the apoc2 mutant zebrafish is a robust and versatile animal model to study hypertriglyceridemia and the mechanisms involved in the pathogenesis of associated human diseases. PMID:26044956

  3. A Principled Approach to Deriving Approximate Conditional Sampling Distributions in Population Genetics Models with Recombination

    PubMed Central

    Paul, Joshua S.; Song, Yun S.

    2010-01-01

    The multilocus conditional sampling distribution (CSD) describes the probability that an additionally sampled DNA sequence is of a certain type, given that a collection of sequences has already been observed. The CSD has a wide range of applications in both computational biology and population genomics analysis, including phasing genotype data into haplotype data, imputing missing data, estimating recombination rates, inferring local ancestry in admixed populations, and importance sampling of coalescent genealogies. Unfortunately, the true CSD under the coalescent with recombination is not known, so approximations, formulated as hidden Markov models, have been proposed in the past. These approximations have led to a number of useful statistical tools, but it is important to recognize that they were not derived from, though were certainly motivated by, principles underlying the coalescent process. The goal of this article is to develop a principled approach to derive improved CSDs directly from the underlying population genetics model. Our approach is based on the diffusion process approximation and the resulting mathematical expressions admit intuitive genealogical interpretations, which we utilize to introduce further approximations and make our method scalable in the number of loci. The general algorithm presented here applies to an arbitrary number of loci and an arbitrary finite-alleles recurrent mutation model. Empirical results are provided to demonstrate that our new CSDs are in general substantially more accurate than previously proposed approximations. PMID:20592264

  4. Apoc2 loss-of-function zebrafish mutant as a genetic model of hyperlipidemia

    PubMed Central

    Liu, Chao; Gates, Keith P.; Fang, Longhou; Amar, Marcelo J.; Schneider, Dina A.; Geng, Honglian; Huang, Wei; Kim, Jungsu; Pattison, Jennifer; Zhang, Jian; Witztum, Joseph L.; Remaley, Alan T.; Dong, P. Duc; Miller, Yury I.

    2015-01-01

    ABSTRACT Apolipoprotein C-II (APOC2) is an obligatory activator of lipoprotein lipase. Human patients with APOC2 deficiency display severe hypertriglyceridemia while consuming a normal diet, often manifesting xanthomas, lipemia retinalis and pancreatitis. Hypertriglyceridemia is also an important risk factor for development of cardiovascular disease. Animal models to study hypertriglyceridemia are limited, with no Apoc2-knockout mouse reported. To develop a genetic model of hypertriglyceridemia, we generated an apoc2 mutant zebrafish characterized by the loss of Apoc2 function. apoc2 mutants show decreased plasma lipase activity and display chylomicronemia and severe hypertriglyceridemia, which closely resemble the phenotype observed in human patients with APOC2 deficiency. The hypertriglyceridemia in apoc2 mutants is rescued by injection of plasma from wild-type zebrafish or by injection of a human APOC2 mimetic peptide. Consistent with a previous report of a transient apoc2 knockdown, apoc2 mutant larvae have a minor delay in yolk consumption and angiogenesis. Furthermore, apoc2 mutants fed a normal diet accumulate lipid and lipid-laden macrophages in the vasculature, which resemble early events in the development of human atherosclerotic lesions. In addition, apoc2 mutant embryos show ectopic overgrowth of pancreas. Taken together, our data suggest that the apoc2 mutant zebrafish is a robust and versatile animal model to study hypertriglyceridemia and the mechanisms involved in the pathogenesis of associated human diseases. PMID:26044956

  5. Determinants of Low Birth Weight in Malawi: Bayesian Geo-Additive Modelling.

    PubMed

    Ngwira, Alfred; Stanley, Christopher C

    2015-01-01

    Studies on factors of low birth weight in Malawi have neglected the flexible approach of using smooth functions for some covariates in models. Such flexible approach reveals detailed relationship of covariates with the response. The study aimed at investigating risk factors of low birth weight in Malawi by assuming a flexible approach for continuous covariates and geographical random effect. A Bayesian geo-additive model for birth weight in kilograms and size of the child at birth (less than average or average and higher) with district as a spatial effect using the 2010 Malawi demographic and health survey data was adopted. A Gaussian model for birth weight in kilograms and a binary logistic model for the binary outcome (size of child at birth) were fitted. Continuous covariates were modelled by the penalized (p) splines and spatial effects were smoothed by the two dimensional p-spline. The study found that child birth order, mother weight and height are significant predictors of birth weight. Secondary education for mother, birth order categories 2-3 and 4-5, wealth index of richer family and mother height were significant predictors of child size at birth. The area associated with low birth weight was Chitipa and areas with increased risk to less than average size at birth were Chitipa and Mchinji. The study found support for the flexible modelling of some covariates that clearly have nonlinear influences. Nevertheless there is no strong support for inclusion of geographical spatial analysis. The spatial patterns though point to the influence of omitted variables with some spatial structure or possibly epidemiological processes that account for this spatial structure and the maps generated could be used for targeting development efforts at a glance. PMID:26114866

  6. Genetics of complex neurological disease: challenges and opportunities for modeling epilepsy in mice and rats.

    PubMed

    Frankel, Wayne N

    2009-08-01

    Currently, approximately 20 genetic variants are known to cause Mendelian forms of human epilepsy, leaving a vast heritability undefined. Rodent models for genetically complex epilepsy have been studied for many years, but only recently have strong candidate genes emerged, including Cacna1 g in the GAERS rat model of absence epilepsy and Kcnj10 in the low seizure threshold of DBA/2 mice. In parallel, a growing number of mouse mutations studied on multiple strain backgrounds reveal the impact of genetic modifiers on seizure severity, incidence or form--perhaps mimicking the complexity seen in humans. The field of experimental genetics in rodents is poised to study discrete epilepsy mutations on a diverse choice of strain backgrounds to develop better models and identify modifiers. But, it must find the right balance between embracing the strain diversity available, with the ability to detect and characterize genetic effects. Using alternative strain backgrounds when studying epilepsy mutations will enhance the modeling of epilepsy as a complex genetic disease. PMID:19665252

  7. A stochastic dynamic simulation model including multi-trait genetics to estimate genetic, technical and financial consequences of dairy farm reproduction and selection strategies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The objective of this study was to develop a daily stochastic dynamic dairy simulation model which included multi-trait genetics, and to evaluate the effects of various reproduction and selection strategies on the genetic, technical and financial performance of a dairy herd. The 12 correlated geneti...

  8. Learning genetic inquiry through the use, revision, and justification of explanatory models

    NASA Astrophysics Data System (ADS)

    Cartier, Jennifer Lorraine

    Central to the process of inquiry in science is the construction and assessment of models that can be used to explain (and in some cases, predict) natural phenomena. This dissertation is a qualitative study of student learning in a high school biology course that was designed to give students opportunities to learn about genetic inquiry in part by providing them with authentic experiences doing inquiry in the discipline. With the aid of a computer program that generates populations of "fruit flies", the students in this class worked in groups structured like scientific communities to build, revise, and defend explanatory models for various inheritance phenomena. Analysis of the ways in which the first cohort of students assessed their inheritance models revealed that all students assessed models based upon empirical fit (data/model match). However, in contrast to the practice of scientists and despite explicit instruction, students did not consistently apply conceptual assessment criteria to their models. That is, they didn't seek consistency between underlying concepts or processes in their models and those of other important genetic models, such as meiosis. This is perhaps in part because they lacked an understanding of models as conceptual rather than physical entities. Subsequently, the genetics curriculum was altered in order to create more opportunities for students to address epistemological issues associated with model assessment throughout the course. The second cohort of students' understanding of models changed over the nine-week period: initially the majority of students equated scientific models with "proof" (generally physical) of "theories"; at the end of the course, most students demonstrated understanding of the conceptual nature of scientific models and the need to justify such knowledge according to both its empirical utility and conceptual consistency. Through model construction and assessment (i.e. scientific inquiry), students were able to

  9. Optimization of Volumetric Computed Tomography for Skeletal Analysis of Model Genetic Organisms

    PubMed Central

    Vasquez, Sergio X.; Hansen, Mark S.; Bahadur, Ali N.; Hockin, Matthew F.; Kindlmann, Gordon L.; Nevell, Lisa; Wu, Isabel Q.; Grunwald, David J.; Weinstein, David M.; Jones, Greg M.; Johnson, Christopher R.; Vandeberg, John L.; Capecchi, Mario R.; Keller, Charles

    2011-01-01

    Forward and reverse genetics now allow researchers to understand embryonic and postnatal gene function in a broad range of species. Although some genetic mutations cause obvious morphological change, other mutations can be more subtle and, without adequate observation and quantification, might be overlooked. For the increasing number of genetic model organisms examined by the growing field of phenomics, standardized but sensitive methods for quantitative analysis need to be incorporated into routine practice to effectively acquire and analyze ever-increasing quantities of phenotypic data. In this study, we present platform-independent parameters for the use of microscopic x-ray computed tomography (microCT) for phenotyping species-specific skeletal morphology of a variety of different genetic model organisms. We show that microCT is suitable for phenotypic characterization for prenatal and postnatal specimens across multiple species. PMID:18286615

  10. Modeling the expected lifetime and evolution of a deme's principal genetic sequence.

    NASA Astrophysics Data System (ADS)

    Clark, Brian

    2014-03-01

    The principal genetic sequence (PGS) is the most common genetic sequence in a deme. The PGS changes over time because new genetic sequences are created by inversions, compete with the current PGS, and a small fraction become PGSs. A set of coupled difference equations provides a description of the evolution of the PGS distribution function in an ensemble of demes. Solving the set of equations produces the survival probability of a new genetic sequence and the expected lifetime of an existing PGS as a function of inversion size and rate, recombination rate, and deme size. Additionally, the PGS distribution function is used to explain the transition pathway from old to new PGSs. We compare these results to a cellular automaton based representation of a deme and the drosophila species, D. melanogaster and D. yakuba.

  11. Modeling particulate matter concentrations measured through mobile monitoring in a deletion/substitution/addition approach

    NASA Astrophysics Data System (ADS)

    Su, Jason G.; Hopke, Philip K.; Tian, Yilin; Baldwin, Nichole; Thurston, Sally W.; Evans, Kristin; Rich, David Q.

    2015-12-01

    Land use regression modeling (LUR) through local scale circular modeling domains has been used to predict traffic-related air pollution such as nitrogen oxides (NOX). LUR modeling for fine particulate matters (PM), which generally have smaller spatial gradients than NOX, has been typically applied for studies involving multiple study regions. To increase the spatial coverage for fine PM and key constituent concentrations, we designed a mobile monitoring network in Monroe County, New York to measure pollutant concentrations of black carbon (BC, wavelength at 880 nm), ultraviolet black carbon (UVBC, wavelength at 3700 nm) and Delta-C (the difference between the UVBC and BC concentrations) using the Clarkson University Mobile Air Pollution Monitoring Laboratory (MAPL). A Deletion/Substitution/Addition (D/S/A) algorithm was conducted, which used circular buffers as a basis for statistics. The algorithm maximizes the prediction accuracy for locations without measurements using the V-fold cross-validation technique, and it reduces overfitting compared to other approaches. We found that the D/S/A LUR modeling approach could achieve good results, with prediction powers of 60%, 63%, and 61%, respectively, for BC, UVBC, and Delta-C. The advantage of mobile monitoring is that it can monitor pollutant concentrations at hundreds of spatial points in a region, rather than the typical less than 100 points from a fixed site saturation monitoring network. This research indicates that a mobile saturation sampling network, when combined with proper modeling techniques, can uncover small area variations (e.g., 10 m) in particulate matter concentrations.

  12. The biobehavioral family model: testing social support as an additional exogenous variable.

    PubMed

    Woods, Sarah B; Priest, Jacob B; Roush, Tara

    2014-12-01

    This study tests the inclusion of social support as a distinct exogenous variable in the Biobehavioral Family Model (BBFM). The BBFM is a biopsychosocial approach to health that proposes that biobehavioral reactivity (anxiety and depression) mediates the relationship between family emotional climate and disease activity. Data for this study included married, English-speaking adult participants (n = 1,321; 55% female; M age = 45.2 years) from the National Comorbidity Survey Replication, a nationally representative epidemiological study of the frequency of mental disorders in the United States. Participants reported their demographics, marital functioning, social support from friends and relatives, anxiety and depression (biobehavioral reactivity), number of chronic health conditions, and number of prescription medications. Confirmatory factor analyses supported the items used in the measures of negative marital interactions, social support, and biobehavioral reactivity, as well as the use of negative marital interactions, friends' social support, and relatives' social support as distinct factors in the model. Structural equation modeling indicated a good fit of the data to the hypothesized model (χ(2)  = 846.04, p = .000, SRMR = .039, CFI = .924, TLI = .914, RMSEA = .043). Negative marital interactions predicted biobehavioral reactivity (β = .38, p < .001), as did relatives' social support, inversely (β = -.16, p < .001). Biobehavioral reactivity predicted disease activity (β = .40, p < .001) and was demonstrated to be a significant mediator through tests of indirect effects. Findings are consistent with previous tests of the BBFM with adult samples, and suggest the important addition of family social support as a predicting factor in the model. PMID:24981970

  13. A habitat suitability model for Chinese sturgeon determined using the generalized additive method

    NASA Astrophysics Data System (ADS)

    Yi, Yujun; Sun, Jie; Zhang, Shanghong

    2016-03-01

    The Chinese sturgeon is a type of large anadromous fish that migrates between the ocean and rivers. Because of the construction of dams, this sturgeon's migration path has been cut off, and this species currently is on the verge of extinction. Simulating suitable environmental conditions for spawning followed by repairing or rebuilding its spawning grounds are effective ways to protect this species. Various habitat suitability models based on expert knowledge have been used to evaluate the suitability of spawning habitat. In this study, a two-dimensional hydraulic simulation is used to inform a habitat suitability model based on the generalized additive method (GAM). The GAM is based on real data. The values of water depth and velocity are calculated first via the hydrodynamic model and later applied in the GAM. The final habitat suitability model is validated using the catch per unit effort (CPUEd) data of 1999 and 2003. The model results show that a velocity of 1.06-1.56 m/s and a depth of 13.33-20.33 m are highly suitable ranges for the Chinese sturgeon to spawn. The hydraulic habitat suitability indexes (HHSI) for seven discharges (4000; 9000; 12,000; 16,000; 20,000; 30,000; and 40,000 m3/s) are calculated to evaluate integrated habitat suitability. The results show that the integrated habitat suitability reaches its highest value at a discharge of 16,000 m3/s. This study is the first to apply a GAM to evaluate the suitability of spawning grounds for the Chinese sturgeon. The study provides a reference for the identification of potential spawning grounds in the entire basin.

  14. Generalized additive models used to predict species abundance in the Gulf of Mexico: an ecosystem modeling tool.

    PubMed

    Drexler, Michael; Ainsworth, Cameron H

    2013-01-01

    Spatially explicit ecosystem models of all types require an initial allocation of biomass, often in areas where fisheries independent abundance estimates do not exist. A generalized additive modelling (GAM) approach is used to describe the abundance of 40 species groups (i.e. functional groups) across the Gulf of Mexico (GoM) using a large fisheries independent data set (SEAMAP) and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. Despite the presence of a large number of zeros in the data, a single GAM using a negative binomial distribution was suitable to make predictions of abundance for multiple functional groups. We present an example case study using pink shrimp (Farfantepenaeus duroarum) and compare the results to known distributions. The model successfully predicts the known areas of high abundance in the GoM, including those areas where no data was inputted into the model fitting. Overall, the model reliably captures areas of high and low abundance for the large majority of functional groups observed in SEAMAP. The result of this method allows for the objective setting of spatial distributions for numerous functional groups across a modeling domain, even where abundance data may not exist. PMID:23691223

  15. Generalized Additive Models Used to Predict Species Abundance in the Gulf of Mexico: An Ecosystem Modeling Tool

    PubMed Central

    Drexler, Michael; Ainsworth, Cameron H.

    2013-01-01

    Spatially explicit ecosystem models of all types require an initial allocation of biomass, often in areas where fisheries independent abundance estimates do not exist. A generalized additive modelling (GAM) approach is used to describe the abundance of 40 species groups (i.e. functional groups) across the Gulf of Mexico (GoM) using a large fisheries independent data set (SEAMAP) and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. Despite the presence of a large number of zeros in the data, a single GAM using a negative binomial distribution was suitable to make predictions of abundance for multiple functional groups. We present an example case study using pink shrimp (Farfantepenaeus duroarum) and compare the results to known distributions. The model successfully predicts the known areas of high abundance in the GoM, including those areas where no data was inputted into the model fitting. Overall, the model reliably captures areas of high and low abundance for the large majority of functional groups observed in SEAMAP. The result of this method allows for the objective setting of spatial distributions for numerous functional groups across a modeling domain, even where abundance data may not exist. PMID:23691223

  16. Nonlinear feedback in a six-dimensional Lorenz Model: impact of an additional heating term

    NASA Astrophysics Data System (ADS)

    Shen, B.-W.

    2015-03-01

    In this study, a six-dimensional Lorenz model (6DLM) is derived, based on a recent study using a five-dimensional (5-D) Lorenz model (LM), in order to examine the impact of an additional mode and its accompanying heating term on solution stability. The new mode added to improve the representation of the steamfunction is referred to as a secondary streamfunction mode, while the two additional modes, that appear in both the 6DLM and 5DLM but not in the original LM, are referred to as secondary temperature modes. Two energy conservation relationships of the 6DLM are first derived in the dissipationless limit. The impact of three additional modes on solution stability is examined by comparing numerical solutions and ensemble Lyapunov exponents of the 6DLM and 5DLM as well as the original LM. For the onset of chaos, the critical value of the normalized Rayleigh number (rc) is determined to be 41.1. The critical value is larger than that in the 3DLM (rc ~ 24.74), but slightly smaller than the one in the 5DLM (rc ~ 42.9). A stability analysis and numerical experiments obtained using generalized LMs, with or without simplifications, suggest the following: (1) negative nonlinear feedback in association with the secondary temperature modes, as first identified using the 5DLM, plays a dominant role in providing feedback for improving the solution's stability of the 6DLM, (2) the additional heating term in association with the secondary streamfunction mode may destabilize the solution, and (3) overall feedback due to the secondary streamfunction mode is much smaller than the feedback due to the secondary temperature modes; therefore, the critical Rayleigh number of the 6DLM is comparable to that of the 5DLM. The 5DLM and 6DLM collectively suggest different roles for small-scale processes (i.e., stabilization vs. destabilization), consistent with the following statement by Lorenz (1972): If the flap of a butterfly's wings can be instrumental in generating a tornado, it can

  17. Nonlinear feedback in a six-dimensional Lorenz model: impact of an additional heating term

    NASA Astrophysics Data System (ADS)

    Shen, B.-W.

    2015-12-01

    In this study, a six-dimensional Lorenz model (6DLM) is derived, based on a recent study using a five-dimensional (5-D) Lorenz model (LM), in order to examine the impact of an additional mode and its accompanying heating term on solution stability. The new mode added to improve the representation of the streamfunction is referred to as a secondary streamfunction mode, while the two additional modes, which appear in both the 6DLM and 5DLM but not in the original LM, are referred to as secondary temperature modes. Two energy conservation relationships of the 6DLM are first derived in the dissipationless limit. The impact of three additional modes on solution stability is examined by comparing numerical solutions and ensemble Lyapunov exponents of the 6DLM and 5DLM as well as the original LM. For the onset of chaos, the critical value of the normalized Rayleigh number (rc) is determined to be 41.1. The critical value is larger than that in the 3DLM (rc ~ 24.74), but slightly smaller than the one in the 5DLM (rc ~ 42.9). A stability analysis and numerical experiments obtained using generalized LMs, with or without simplifications, suggest the following: (1) negative nonlinear feedback in association with the secondary temperature modes, as first identified using the 5DLM, plays a dominant role in providing feedback for improving the solution's stability of the 6DLM, (2) the additional heating term in association with the secondary streamfunction mode may destabilize the solution, and (3) overall feedback due to the secondary streamfunction mode is much smaller than the feedback due to the secondary temperature modes; therefore, the critical Rayleigh number of the 6DLM is comparable to that of the 5DLM. The 5DLM and 6DLM collectively suggest different roles for small-scale processes (i.e., stabilization vs. destabilization), consistent with the following statement by Lorenz (1972): "If the flap of a butterfly's wings can be instrumental in generating a tornado, it can

  18. Impact of an additional chronic BDNF reduction on learning performance in an Alzheimer mouse model

    PubMed Central

    Psotta, Laura; Rockahr, Carolin; Gruss, Michael; Kirches, Elmar; Braun, Katharina; Lessmann, Volkmar; Bock, Jörg; Endres, Thomas

    2015-01-01

    There is increasing evidence that brain-derived neurotrophic factor (BDNF) plays a crucial role in Alzheimer’s disease (AD) pathology. A number of studies demonstrated that AD patients exhibit reduced BDNF levels in the brain and the blood serum, and in addition, several animal-based studies indicated a potential protective effect of BDNF against Aβ-induced neurotoxicity. In order to further investigate the role of BDNF in the etiology of AD, we created a novel mouse model by crossing a well-established AD mouse model (APP/PS1) with a mouse exhibiting a chronic BDNF deficiency (BDNF+/−). This new triple transgenic mouse model enabled us to further analyze the role of BDNF in AD in vivo. We reasoned that in case BDNF has a protective effect against AD pathology, an AD-like phenotype in our new mouse model should occur earlier and/or in more severity than in the APP/PS1-mice. Indeed, the behavioral analysis revealed that the APP/PS1-BDNF+/−-mice show an earlier onset of learning impairments in a two-way active avoidance task in comparison to APP/PS1- and BDNF+/−-mice. However in the Morris water maze (MWM) test, we could not observe an overall aggrevated impairment in spatial learning and also short-term memory in an object recognition task remained intact in all tested mouse lines. In addition to the behavioral experiments, we analyzed the amyloid plaque pathology in the APP/PS1 and APP/PS1-BDNF+/−-mice and observed a comparable plaque density in the two genotypes. Moreover, our results revealed a higher plaque density in prefrontal cortical compared to hippocampal brain regions. Our data reveal that higher cognitive tasks requiring the recruitment of cortical networks appear to be more severely affected in our new mouse model than learning tasks requiring mainly sub-cortical networks. Furthermore, our observations of an accelerated impairment in active avoidance learning in APP/PS1-BDNF+/−-mice further supports the hypothesis that BDNF deficiency

  19. Alternate Service Delivery Models in Cancer Genetic Counseling: A Mini-Review.

    PubMed

    Buchanan, Adam Hudson; Rahm, Alanna Kulchak; Williams, Janet L

    2016-01-01

    Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care, and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models, such as telephone counseling, telegenetics, and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology. PMID:27242960

  20. Alternate Service Delivery Models in Cancer Genetic Counseling: A Mini-Review

    PubMed Central

    Buchanan, Adam Hudson; Rahm, Alanna Kulchak; Williams, Janet L.

    2016-01-01

    Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care, and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models, such as telephone counseling, telegenetics, and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology. PMID:27242960

  1. Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

    PubMed Central

    Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.

    2013-01-01

    Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933

  2. Investigating the genetic architecture of conditional strategies using the environmental threshold model.

    PubMed

    Buzatto, Bruno A; Buoro, Mathieu; Hazel, Wade N; Tomkins, Joseph L

    2015-12-22

    The threshold expression of dichotomous phenotypes that are environmentally cued or induced comprise the vast majority of phenotypic dimorphisms in colour, morphology, behaviour and life history. Modelled as conditional strategies under the framework of evolutionary game theory, the quantitative genetic basis of these traits is a challenge to estimate. The challenge exists firstly because the phenotypic expression of the trait is dichotomous and secondly because the apparent environmental cue is separate from the biological signal pathway that induces the switch between phenotypes. It is the cryptic variation underlying the translation of cue to phenotype that we address here. With a 'half-sib common environment' and a 'family-level split environment' experiment, we examine the environmental and genetic influences that underlie male dimorphism in the earwig Forficula auricularia. From the conceptual framework of the latent environmental threshold (LET) model, we use pedigree information to dissect the genetic architecture of the threshold expression of forceps length. We investigate for the first time the strength of the correlation between observable and cryptic 'proximate' cues. Furthermore, in support of the environmental threshold model, we found no evidence for a genetic correlation between cue and the threshold between phenotypes. Our results show strong correlations between observable and proximate cues and less genetic variation for thresholds than previous studies have suggested. We discuss the importance of generating better estimates of the genetic variation for thresholds when investigating the genetic architecture and heritability of threshold traits. By investigating genetic architecture by means of the LET model, our study supports several key evolutionary ideas related to conditional strategies and improves our understanding of environmentally cued decisions. PMID:26674955

  3. Protein folding simulations of the hydrophobic-hydrophilic model by combining tabu search with genetic algorithms

    NASA Astrophysics Data System (ADS)

    Jiang, Tianzi; Cui, Qinghua; Shi, Guihua; Ma, Songde

    2003-08-01

    In this paper, a novel hybrid algorithm combining genetic algorithms and tabu search is presented. In the proposed hybrid algorithm, the idea of tabu search is applied to the crossover operator. We demonstrate that the hybrid algorithm can be applied successfully to the protein folding problem based on a hydrophobic-hydrophilic lattice model. The results show that in all cases the hybrid algorithm works better than a genetic algorithm alone. A comparison with other methods is also made.

  4. Toward improving the reliability of hydrologic prediction: Model structure uncertainty and its quantification using ensemble-based genetic programming framework

    NASA Astrophysics Data System (ADS)

    Parasuraman, Kamban; Elshorbagy, Amin

    2008-12-01

    Uncertainty analysis is starting to be widely acknowledged as an integral part of hydrological modeling. The conventional treatment of uncertainty analysis in hydrologic modeling is to assume a deterministic model structure, and treat its associated parameters as imperfectly known, thereby neglecting the uncertainty associated with the model structure. In this paper, a modeling framework that can explicitly account for the effect of model structure uncertainty has been proposed. The modeling framework is based on initially generating different realizations of the original data set using a non-parametric bootstrap method, and then exploiting the ability of the self-organizing algorithms, namely genetic programming, to evolve their own model structure for each of the resampled data sets. The resulting ensemble of models is then used to quantify the uncertainty associated with the model structure. The performance of the proposed modeling framework is analyzed with regards to its ability in characterizing the evapotranspiration process at the Southwest Sand Storage facility, located near Ft. McMurray, Alberta. Eddy-covariance-measured actual evapotranspiration is modeled as a function of net radiation, air temperature, ground temperature, relative humidity, and wind speed. Investigating the relation between model complexity, prediction accuracy, and uncertainty, two sets of experiments were carried out by varying the level of mathematical operators that can be used to define the predictand-predictor relationship. While the first set uses just the additive operators, the second set uses both the additive and the multiplicative operators to define the predictand-predictor relationship. The results suggest that increasing the model complexity may lead to better prediction accuracy but at an expense of increasing uncertainty. Compared to the model parameter uncertainty, the relative contribution of model structure uncertainty to the predictive uncertainty of a model is

  5. Thermal Stability of Nanocrystalline Alloys by Solute Additions and A Thermodynamic Modeling

    NASA Astrophysics Data System (ADS)

    Saber, Mostafa

    and alpha → gamma phase transformation in Fe-Ni-Zr alloys. In addition to the experimental study of thermal stabilization of nanocrystalline Fe-Cr-Zr or Fe-Ni-Zr alloys, the thesis presented here developed a new predictive model, applicable to strongly segregating solutes, for thermodynamic stabilization of binary alloys. This model can serve as a benchmark for selecting solute and evaluating the possible contribution of stabilization. Following a regular solution model, both the chemical and elastic strain energy contributions are combined to obtain the mixing enthalpy. The total Gibbs free energy of mixing is then minimized with respect to simultaneous variations in the grain boundary volume fraction and the solute concentration in the grain boundary and the grain interior. The Lagrange multiplier method was used to obtained numerical solutions. Application are given for the temperature dependence of the grain size and the grain boundary solute excess for selected binary system where experimental results imply that thermodynamic stabilization could be operative. This thesis also extends the binary model to a new model for thermodynamic stabilization of ternary nanocrystalline alloys. It is applicable to strongly segregating size-misfit solutes and uses input data available in the literature. In a same manner as the binary model, this model is based on a regular solution approach such that the chemical and elastic strain energy contributions are incorporated into the mixing enthalpy DeltaHmix, and the mixing entropy DeltaSmix is obtained using the ideal solution approximation. The Gibbs mixing free energy Delta Gmix is then minimized with respect to simultaneous variations in grain growth and solute segregation parameters. The Lagrange multiplier method is similarly used to obtain numerical solutions for the minimum Delta Gmix. The temperature dependence of the nanocrystalline grain size and interfacial solute excess can be obtained for selected ternary systems. As

  6. Semiparametric regression of multidimensional genetic pathway data: least-squares kernel machines and linear mixed models.

    PubMed

    Liu, Dawei; Lin, Xihong; Ghosh, Debashis

    2007-12-01

    We consider a semiparametric regression model that relates a normal outcome to covariates and a genetic pathway, where the covariate effects are modeled parametrically and the pathway effect of multiple gene expressions is modeled parametrically or nonparametrically using least-squares kernel machines (LSKMs). This unified framework allows a flexible function for the joint effect of multiple genes within a pathway by specifying a kernel function and allows for the possibility that each gene expression effect might be nonlinear and the genes within the same pathway are likely to interact with each other in a complicated way. This semiparametric model also makes it possible to test for the overall genetic pathway effect. We show that the LSKM semiparametric regression can be formulated using a linear mixed model. Estimation and inference hence can proceed within the linear mixed model framework using standard mixed model software. Both the regression coefficients of the covariate effects and the LSKM estimator of the genetic pathway effect can be obtained using the best linear unbiased predictor in the corresponding linear mixed model formulation. The smoothing parameter and the kernel parameter can be estimated as variance components using restricted maximum likelihood. A score test is developed to test for the genetic pathway effect. Model/variable selection within the LSKM framework is discussed. The methods are illustrated using a prostate cancer data set and evaluated using simulations. PMID:18078480

  7. Physical Model for the Evolution of the Genetic Code

    NASA Astrophysics Data System (ADS)

    Yamashita, Tatsuro; Narikiyo, Osamu

    2011-12-01

    Using the shape space of codons and tRNAs we give a physical description of the genetic code evolution on the basis of the codon capture and ambiguous intermediate scenarios in a consistent manner. In the lowest dimensional version of our description, a physical quantity, codon level is introduced. In terms of the codon levels two scenarios are typically classified into two different routes of the evolutional process. In the case of the ambiguous intermediate scenario we perform an evolutional simulation implemented cost selection of amino acids and confirm a rapid transition of the code change. Such rapidness reduces uncomfortableness of the non-unique translation of the code at intermediate state that is the weakness of the scenario. In the case of the codon capture scenario the survival against mutations under the mutational pressure minimizing GC content in genomes is simulated and it is demonstrated that cells which experience only neutral mutations survive.

  8. Design and tuning of standard additive model based fuzzy PID controllers for multivariable process systems.

    PubMed

    Harinath, Eranda; Mann, George K I

    2008-06-01

    This paper describes a design and two-level tuning method for fuzzy proportional-integral derivative (FPID) controllers for a multivariable process where the fuzzy inference uses the inference of standard additive model. The proposed method can be used for any n x n multi-input-multi-output process and guarantees closed-loop stability. In the two-level tuning scheme, the tuning follows two steps: low-level tuning followed by high-level tuning. The low-level tuning adjusts apparent linear gains, whereas the high-level tuning changes the nonlinearity in the normalized fuzzy output. In this paper, two types of FPID configurations are considered, and their performances are evaluated by using a real-time multizone temperature control problem having a 3 x 3 process system. PMID:18558531

  9. Optimization of simulation models with GADELO: a multi-population genetic algorithm.

    PubMed

    Elketroussi, M; Fan, D P

    1994-02-01

    In this paper, a new Genetic Algorithm based on the Dynamic Exploration of Local Optima (GADELO) was used to estimate the parameters of the MRD (Micro-population model of Risk-group Dynamics) micro-population model for smoking cessation by minimizing a deviation function between the model's predictions and the smoking cessation data of the Multiple Risk Factor Intervention Trial (MRFIT). The efficiency and accuracy of the GADELO estimations were consistently superior to those obtained using the standard genetic algorithm or the simplex algorithm of Nelder-Mead. PMID:8175209

  10. 2015 Guidelines for Establishing Genetically Modified Rat Models for Cardiovascular Research

    PubMed Central

    Flister, Michael J.; Prokop, Jeremy W.; Lazar, Jozef; Shimoyama, Mary; Dwinell, Melinda; Geurts, Aron

    2015-01-01

    The rat has long been a key physiological model for cardiovascular research; most of the inbred strains having been previously selected for susceptibility or resistance to various cardiovascular diseases (CVD). These CVD rat models offer a physiologically relevant background on which candidates of human CVD can be tested in a more clinically translatable experimental setting. However, a diverse toolbox for genetically modifying the rat genome to test molecular mechanisms has only recently become available. Here, we provide a high-level description of several strategies for developing genetically modified rat models of CVD. PMID:25920443

  11. Use of generalised additive models to categorise continuous variables in clinical prediction

    PubMed Central

    2013-01-01

    Background In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind. Methods We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the outcome. The proposed method consists of creating at least one average-risk category along with high- and low-risk categories based on the GAM smooth function. We applied this methodology to a prospective cohort of patients with exacerbated chronic obstructive pulmonary disease. The predictors selected were respiratory rate and partial pressure of carbon dioxide in the blood (PCO2), and the response variable was poor evolution. An additive logistic regression model was used to show the relationship between the covariates and the dichotomous response variable. The proposed categorisation was compared to the continuous predictor as the best option, using the AIC and AUC evaluation parameters. The sample was divided into a derivation (60%) and validation (40%) samples. The first was used to obtain the cut points while the second was used to validate the proposed methodology. Results The three-category proposal for the respiratory rate was ≤ 20;(20,24];> 24, for which the following values were obtained: AIC=314.5 and AUC=0.638. The respective values for the continuous predictor were AIC=317.1 and AUC=0.634, with no statistically

  12. Estimation of the lag time in a subsequent monomer addition model for fibril elongation.

    PubMed

    Shoffner, Suzanne K; Schnell, Santiago

    2016-08-01

    Fibrillogenesis, the production or development of protein fibers, has been linked to protein folding diseases. The progress curve of fibrils or aggregates typically takes on a sigmoidal shape with a lag phase, a rapid growth phase, and a final plateau regime. The study of the lag phase and the estimation of its critical timescale provide insight into the factors regulating the fibrillation process. However, methods to estimate a quantitative expression for the lag time rely on empirical expressions, which cannot connect the lag time to kinetic parameters associated with the reaction mechanisms of protein fibrillation. Here we introduce an approach for the estimation of the lag time using the governing rate equations of the elementary reactions of a subsequent monomer addition model for protein fibrillation as a case study. We show that the lag time is given by the sum of the critical timescales for each fibril intermediate in the subsequent monomer addition mechanism and therefore reveals causal connectivity between intermediate species. Furthermore, we find that single-molecule assays of protein fibrillation can exhibit a lag phase without a nucleation process, while dyes and extrinsic fluorescent probe bulk assays of protein fibrillation do not exhibit an observable lag phase during template-dependent elongation. Our approach could be valuable for investigating the effects of intrinsic and extrinsic factors to the protein fibrillation reaction mechanism and provides physicochemical insights into parameters regulating the lag phase. PMID:27250246

  13. Supra-additive effects of tramadol and acetaminophen in a human pain model.

    PubMed

    Filitz, Jörg; Ihmsen, Harald; Günther, Werner; Tröster, Andreas; Schwilden, Helmut; Schüttler, Jürgen; Koppert, Wolfgang

    2008-06-01

    The combination of analgesic drugs with different pharmacological properties may show better efficacy with less side effects. Aim of this study was to examine the analgesic and antihyperalgesic properties of the weak opioid tramadol and the non-opioid acetaminophen, alone as well as in combination, in an experimental pain model in humans. After approval of the local Ethics Committee, 17 healthy volunteers were enrolled in this double-blind and placebo-controlled study in a cross-over design. Transcutaneous electrical stimulation at high current densities (29.6+/-16.2 mA) induced spontaneous acute pain (NRS=6 of 10) and distinct areas of hyperalgesia for painful mechanical stimuli (pinprick-hyperalgesia). Pain intensities as well as the extent of the areas of hyperalgesia were assessed before, during and 150 min after a 15 min lasting intravenous infusion of acetaminophen (650 mg), tramadol (75 mg), a combination of both (325 mg acetaminophen and 37.5mg tramadol), or saline 0.9%. Tramadol led to a maximum pain reduction of 11.7+/-4.2% with negligible antihyperalgesic properties. In contrast, acetaminophen led to a similar pain reduction (9.8+/-4.4%), but a sustained antihyperalgesic effect (34.5+/-14.0% reduction of hyperalgesic area). The combination of both analgesics at half doses led to a supra-additive pain reduction of 15.2+/-5.7% and an enhanced antihyperalgesic effect (41.1+/-14.3% reduction of hyperalgesic areas) as compared to single administration of acetaminophen. Our study provides first results on interactions of tramadol and acetaminophen on experimental pain and hyperalgesia in humans. Pharmacodynamic modeling combined with the isobolographic technique showed supra-additive effects of the combination of acetaminophen and tramadol concerning both, analgesia and antihyperalgesia. The results might act as a rationale for combining both analgesics. PMID:17709207

  14. Initial assessment of a model relating intratumoral genetic heterogeneity to radiological morphology

    PubMed Central

    Noterdaeme, O; Kelly, M; Friend, P; Soonowalla, Z; Steers, G; Brady, M

    2010-01-01

    Tumour heterogeneity has major implications for tumour development and response to therapy. Tumour heterogeneity results from mutations in the genes responsible for mismatch repair or maintenance of chromosomal stability. Cells with different genetic properties may grow at different rates and exhibit different resistance to therapeutic interventions. To date, there exists no approach to non-invasively assess tumour heterogeneity. Here we present a biologically inspired model of tumour growth, which relates intratumoral genetic heterogeneity to gross morphology visible on radiological images. The model represents the development of a tumour as a set of expanding spheres, each sphere representing a distinct clonal centre, with the sprouting of new spheres corresponding to new clonal centres. Each clonal centre may possess different characteristics relating to genetic composition, growth rate and response to treatment. We present a clinical example for which the model accurately tracks tumour growth and shows the correspondence to genetic variation (as determined by array comparative genomic hybridisation). One clinical implication of our work is that the assessment of heterogeneous tumours using Response Evaluation Criteria In Solid Tumours (RECIST) or volume measurements may not accurately reflect tumour growth, stability or the response to treatment. We believe that this is the first model linking the macro-scale appearance of tumours to their genetic composition. We anticipate that our model will provide a more informative way to assess the response of heterogeneous tumours to treatment, which is of increasing importance with the development of novel targeted anti-cancer treatments. PMID:19690073

  15. Genetic Algorithm Based Framework for Automation of Stochastic Modeling of Multi-Season Streamflows

    NASA Astrophysics Data System (ADS)

    Srivastav, R. K.; Srinivasan, K.; Sudheer, K.

    2009-05-01

    bootstrap (MABB) ) based on the explicit objective functions of minimizing the relative bias and relative root mean square error in estimating the storage capacity of the reservoir. The optimal parameter set of the hybrid model is obtained based on the search over a multi- dimensional parameter space (involving simultaneous exploration of the parametric (PAR(1)) as well as the non-parametric (MABB) components). This is achieved using the efficient evolutionary search based optimization tool namely, non-dominated sorting genetic algorithm - II (NSGA-II). This approach helps in reducing the drudgery involved in the process of manual selection of the hybrid model, in addition to predicting the basic summary statistics dependence structure, marginal distribution and water-use characteristics accurately. The proposed optimization framework is used to model the multi-season streamflows of River Beaver and River Weber of USA. In case of both the rivers, the proposed GA-based hybrid model yields a much better prediction of the storage capacity (where simultaneous exploration of both parametric and non-parametric components is done) when compared with the MLE-based hybrid models (where the hybrid model selection is done in two stages, thus probably resulting in a sub-optimal model). This framework can be further extended to include different linear/non-linear hybrid stochastic models at other temporal and spatial scales as well.

  16. A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem

    NASA Astrophysics Data System (ADS)

    Moradgholi, Mostafa; Paydar, Mohammad Mahdi; Mahdavi, Iraj; Jouzdani, Javid

    2016-05-01

    Nowadays, with the increasing pressure of the competitive business environment and demand for diverse products, manufacturers are force to seek for solutions that reduce production costs and rise product quality. Cellular manufacturing system (CMS), as a means to this end, has been a point of attraction to both researchers and practitioners. Limitations of cell formation problem (CFP), as one of important topics in CMS, have led to the introduction of virtual CMS (VCMS). This research addresses a bi-objective dynamic virtual cell formation problem (DVCFP) with the objective of finding the optimal formation of cells, considering the material handling costs, fixed machine installation costs and variable production costs of machines and workforce. Furthermore, we consider different skills on different machines in workforce assignment in a multi-period planning horizon. The bi-objective model is transformed to a single-objective fuzzy goal programming model and to show its performance; numerical examples are solved using the LINGO software. In addition, genetic algorithm (GA) is customized to tackle large-scale instances of the problems to show the performance of the solution method.

  17. Testing the limits of the 'joint account' model of genetic information: a legal thought experiment.

    PubMed

    Foster, Charles; Herring, Jonathan; Boyd, Magnus

    2015-05-01

    We examine the likely reception in the courtroom of the 'joint account' model of genetic confidentiality. We conclude that the model, as modified by Gilbar and others, is workable and reflects, better than more conventional legal approaches, both the biological and psychological realities and the obligations owed under Articles 8 and 10 of the European Convention on Human Rights (ECHR). PMID:24965717

  18. Effect of bead and illustrations models on high school students' achievement in molecular genetics

    NASA Astrophysics Data System (ADS)

    Rotbain, Yosi; Marbach-Ad, Gili; Stavy, Ruth

    2006-05-01

    Our main goal in this study was to explore whether the use of models in molecular genetics instruction in high school can contribute to students' understanding of concepts and processes in genetics. Three comparable groups of 11th and 12th graders participated: The control group (116 students) was taught in the traditional lecture format, while the others received instructions which integrated a bead model (71 students), or an illustration model (71 students). Similar instructions and the same guiding questions accompanied the two models. We used three instruments: a multiple-choice and an open-ended written questionnaire, as well as personal interviews. Five of the multiple-choice questions were also given to students before receiving their genetics instruction (pretest). We found that students who used one of the two types of models improved their knowledge in molecular genetics compared to the control group. However, the open-ended questions revealed that bead model activity was significantly more effective than illustration activity. On the basis of these findings we conclude that, though it is advisable to use a three-dimensional model, such as the bead model, engaging students in activities with illustrations can still improve their achievement in comparison to traditional instruction.

  19. Practical implications for genetic modeling in the genomics era for the dairy industry

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, incl...

  20. Recent developments in computer modeling add ecological realism to landscape genetics

    EPA Science Inventory

    Background / Question / Methods A factor limiting the rate of progress in landscape genetics has been the shortage of spatial models capable of linking life history attributes such as dispersal behavior to complex dynamic landscape features. The recent development of new models...

  1. Giftedness and Genetics: The Emergenic-Epigenetic Model and Its Implications

    ERIC Educational Resources Information Center

    Simonton, Dean Keith

    2005-01-01

    The genetic endowment underlying giftedness may operate in a far more complex manner than often expressed in most theoretical accounts of the phenomenon. First, an endowment may be emergenic. That is, a gift may consist of multiple traits (multidimensional) that are inherited in a multiplicative (configurational), rather than an additive (simple)…

  2. Evaluation of the Performance of Smoothing Functions in Generalized Additive Models for Spatial Variation in Disease

    PubMed Central

    Siangphoe, Umaporn; Wheeler, David C.

    2015-01-01

    Generalized additive models (GAMs) with bivariate smoothing functions have been applied to estimate spatial variation in risk for many types of cancers. Only a handful of studies have evaluated the performance of smoothing functions applied in GAMs with regard to different geographical areas of elevated risk and different risk levels. This study evaluates the ability of different smoothing functions to detect overall spatial variation of risk and elevated risk in diverse geographical areas at various risk levels using a simulation study. We created five scenarios with different true risk area shapes (circle, triangle, linear) in a square study region. We applied four different smoothing functions in the GAMs, including two types of thin plate regression splines (TPRS) and two versions of locally weighted scatterplot smoothing (loess). We tested the null hypothesis of constant risk and detected areas of elevated risk using analysis of deviance with permutation methods and assessed the performance of the smoothing methods based on the spatial detection rate, sensitivity, accuracy, precision, power, and false-positive rate. The results showed that all methods had a higher sensitivity and a consistently moderate-to-high accuracy rate when the true disease risk was higher. The models generally performed better in detecting elevated risk areas than detecting overall spatial variation. One of the loess methods had the highest precision in detecting overall spatial variation across scenarios and outperformed the other methods in detecting a linear elevated risk area. The TPRS methods outperformed loess in detecting elevated risk in two circular areas. PMID:25983545

  3. Modeling and additive manufacturing of bio-inspired composites with tunable fracture mechanical properties.

    PubMed

    Dimas, Leon S; Buehler, Markus J

    2014-07-01

    Flaws, imperfections and cracks are ubiquitous in material systems and are commonly the catalysts of catastrophic material failure. As stresses and strains tend to concentrate around cracks and imperfections, structures tend to fail far before large regions of material have ever been subjected to significant loading. Therefore, a major challenge in material design is to engineer systems that perform on par with pristine structures despite the presence of imperfections. In this work we integrate knowledge of biological systems with computational modeling and state of the art additive manufacturing to synthesize advanced composites with tunable fracture mechanical properties. Supported by extensive mesoscale computer simulations, we demonstrate the design and manufacturing of composites that exhibit deformation mechanisms characteristic of pristine systems, featuring flaw-tolerant properties. We analyze the results by directly comparing strain fields for the synthesized composites, obtained through digital image correlation (DIC), and the computationally tested composites. Moreover, we plot Ashby diagrams for the range of simulated and experimental composites. Our findings show good agreement between simulation and experiment, confirming that the proposed mechanisms have a significant potential for vastly improving the fracture response of composite materials. We elucidate the role of stiffness ratio variations of composite constituents as an important feature in determining the composite properties. Moreover, our work validates the predictive ability of our models, presenting them as useful tools for guiding further material design. This work enables the tailored design and manufacturing of composites assembled from inferior building blocks, that obtain optimal combinations of stiffness and toughness. PMID:24700202

  4. Effects of Mn addition on dislocation loop formation in A533B and model alloys

    NASA Astrophysics Data System (ADS)

    Watanabe, H.; Masaki, S.; Masubuchi, S.; Yoshida, N.; Dohi, K.

    2013-08-01

    It is well known that the radiation hardening or embrittlement of pressure vessel steels is very sensitive to the contents of minor solutes. To study the effect of dislocation loop formation on radiation hardening in these steels, in situ observation using a high-voltage electron microscope was conducted for the reference pressure vessel steel JRQ and Fe-based model alloys containing Mn, Si, and Ni. In the Fe-based model alloys, the addition of Mn was most effective for increasing dislocation loop density at 290 °C. Based on the assumption that a di-interstitial was adopted as the nucleus for the formation of an interstitial loop, a binding energy of 0.22 eV was obtained for the interaction of a Mn atom and an interstitial. The formation of Mn clusters detected by three-dimensional atom probe and interstitial-type loops at room temperature clearly showed that the oversized Mn atoms migrate through an interstitial mechanism. The temperature and flux dependence of loop density in pressure vessel steels was very weak up to 290 °C. This suggests that interstitial atoms are deeply trapped by the radiation-induced solute clusters in pressure vessel steels.

  5. Modeling of trophospheric ozone concentrations using genetically trained multi-level cellular neural networks

    NASA Astrophysics Data System (ADS)

    Ozcan, H. Kurtulus; Bilgili, Erdem; Sahin, Ulku; Ucan, O. Nuri; Bayat, Cuma

    2007-09-01

    Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.

  6. The Parasitoid Wasp Nasonia: An Emerging Model System With Haploid Male Genetics

    PubMed Central

    Werren, John H.; Loehlin, David W.

    2010-01-01

    Nasonia is a complex of four closely related species that is rapidly emerging as a model for evolutionary and developmental genetics. It has several features that make it an excellent genetic system, including a short generation time, ease of rearing, interfertile species, visible and molecular markers, and a sequenced genome. The form of sex determination, called haplodiploidy, makes Nasonia particularly suited as a genetic tool. Females are diploid and develop from fertilized eggs, whereas males are haploid and develop from unfertilized eggs. This allows geneticists to exploit many of the advantages of haploid genetics in an otherwise complex eukaryotic organism. Nasonia readily inbreeds, permitting production of isogenic lines, and the four species in the genus are inter-fertile (after removal of the endosymbiont Wolbachia), facilitating movement of genes between the species for efficient positional cloning of quantitative trait loci (QTL). Genome sequencing of the genetic model N. vitripennis and two interfertile species N. giraulti and N. longicornis is now completed. This genome project provides a wealth of interspecies polymorphisms (SNPs, indels, microsatellites) to facilitate positional cloning of genes involved in species differences in behavior, morphology and development. Advances in the genetics of this system also open a path for improvement of parasitoid insects as agents of pest control. PMID:20147035

  7. A test of genetic models for the evolutionary maintenance of same-sex sexual behaviour

    PubMed Central

    Hoskins, Jessica L.; Ritchie, Michael G.; Bailey, Nathan W.

    2015-01-01

    The evolutionary maintenance of same-sex sexual behaviour (SSB) has received increasing attention because it is perceived to be an evolutionary paradox. The genetic basis of SSB is almost wholly unknown in non-human animals, though this is key to understanding its persistence. Recent theoretical work has yielded broadly applicable predictions centred on two genetic models for SSB: overdominance and sexual antagonism. Using Drosophila melanogaster, we assayed natural genetic variation for male SSB and empirically tested predictions about the mode of inheritance and fitness consequences of alleles influencing its expression. We screened 50 inbred lines derived from a wild population for male–male courtship and copulation behaviour, and examined crosses between the lines for evidence of overdominance and antagonistic fecundity selection. Consistent variation among lines revealed heritable genetic variation for SSB, but the nature of the genetic variation was complex. Phenotypic and fitness variation was consistent with expectations under overdominance, although predictions of the sexual antagonism model were also supported. We found an unexpected and strong paternal effect on the expression of SSB, suggesting possible Y-linkage of the trait. Our results inform evolutionary genetic mechanisms that might maintain low but persistently observed levels of male SSB in D. melanogaster, but highlight a need for broader taxonomic representation in studies of its evolutionary causes. PMID:26019160

  8. S2M: A Stochastic Simulation Model of Poliovirus Genetic State Transition

    PubMed Central

    Ecale Zhou, Carol L.

    2016-01-01

    Modeling the molecular mechanisms that govern genetic variation can be useful in understanding the dynamics that drive genetic state transition in quasispecies viruses. For example, there is considerable interest in understanding how the relatively benign vaccine strains of poliovirus eventually revert to forms that confer neurovirulence and cause disease (ie, vaccine-derived poliovirus). This report describes a stochastic simulation model, S2M, which can be used to generate hypothetical outcomes based on known mechanisms of genetic diversity. S2M begins with predefined genotypes based on the Sabin-1 and Mahoney wild-type sequences, constructs a set of independent cell-based populations, and performs in-cell replication and cell-to-cell infection cycles while quantifying genetic changes that track the transition from Sabin-1 toward Mahoney. Realism is incorporated into the model by assigning defaults for variables that constrain mechanisms of genetic variability based roughly on metrics reported in the literature, yet these values can be modified at the command line in order to generate hypothetical outcomes driven by these parameters. To demonstrate the utility of S2M, simulations were performed to examine the effects of the rates of replication error and recombination and the presence or absence of defective interfering particles, upon reaching the end states of Mahoney resemblance (semblance of a vaccine-derived state), neurovirulence, genome fitness, and cloud diversity. Simulations provide insight into how modeled biological features may drive hypothetical outcomes, independently or in combination, in ways that are not always intuitively obvious. PMID:27385911

  9. Progress and Prospects for Genetic Modification of Nonhuman Primate Models in Biomedical Research

    PubMed Central

    Chan, Anthony W. S.

    2013-01-01

    The growing interest of modeling human diseases using genetically modified (transgenic) nonhuman primates (NHPs) is a direct result of NHPs (rhesus macaque, etc.) close relation to humans. NHPs share similar developmental paths with humans in their anatomy, physiology, genetics, and neural functions; and in their cognition, emotion, and social behavior. The NHP model within biomedical research has played an important role in the development of vaccines, assisted reproductive technologies, and new therapies for many diseases. Biomedical research has not been the primary role of NHPs. They have mainly been used for safety evaluation and pharmacokinetics studies, rather than determining therapeutic efficacy. The development of the first transgenic rhesus macaque (2001) revolutionized the role of NHP models in biomedicine. Development of the transgenic NHP model of Huntington's disease (2008), with distinctive clinical features, further suggested the uniqueness of the model system; and the potential role of the NHP model for human genetic disorders. Modeling human genetic diseases using NHPs will continue to thrive because of the latest advances in molecular, genetic, and embryo technologies. NHPs rising role in biomedical research, specifically pre-clinical studies, is foreseeable. The path toward the development of transgenic NHPs and the prospect of transgenic NHPs in their new role in future biomedicine needs to be reviewed. This article will focus on the advancement of transgenic NHPs in the past decade, including transgenic technologies and disease modeling. It will outline new technologies that may have significant impact in future NHP modeling and will conclude with a discussion of the future prospects of the transgenic NHP model. PMID:24174443

  10. Entering the second century of maize quantitative genetics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  11. An F2 Pig Resource Population as a Model for Genetic Studies of Obesity and Obesity-Related Diseases in Humans: Design and Genetic Parameters

    PubMed Central

    Kogelman, Lisette J. A.; Kadarmideen, Haja N.; Mark, Thomas; Karlskov-Mortensen, Peter; Bruun, Camilla S.; Cirera, Susanna; Jacobsen, Mette J.; Jørgensen, Claus B.; Fredholm, Merete

    2013-01-01

    Obesity is a rising worldwide public health problem. Difficulties to precisely measure various obesity traits and the genetic heterogeneity in human have been major impediments to completely disentangle genetic factors causing obesity. The pig is a relevant model for studying human obesity and obesity-related (OOR) traits. Using founder breeds divergent with respect to obesity traits we have created an F2 pig resource population (454 pigs), which has been intensively phenotyped for 36 OOR traits. The main rationale for our study is to characterize the genetic architecture of OOR traits in the F2 pig design, by estimating heritabilities, genetic, and phenotypic correlations using mixed- and multi-trait BLUP animal models. Our analyses revealed high coefficients of variation (15–42%) and moderate to high heritabilities (0.22–0.81) in fatness traits, showing large phenotypic and genetic variation in the F2 population, respectively. This fulfills the purpose of creating a resource population divergent for OOR traits. Strong genetic correlations were found between weight and lean mass at dual-energy x-ray absorptiometry scanning (0.56–0.97). Weight and conformation also showed strong genetic correlations with slaughter traits (e.g., rg between abdominal circumference and leaf fat at slaughtering: 0.66). Genetic correlations between fat-related traits and the glucose level vary between 0.35 and 0.74 and show a strong correlation between adipose tissue and impaired glucose metabolism. Our power calculations showed a minimum of 80% power for QTL detection for all phenotypes. We revealed genetic correlations at population level, for the first time, for several difficult to measure and novel OOR traits and diseases. The results underpin the potential of the established F2 pig resource population for further genomic, systems genetics, and functional investigations to unravel the genetic background of OOR traits. PMID:23515185

  12. A Genetic Animal Model of Alcoholism for Screening Medications to Treat Addiction

    PubMed Central

    Bell, Richard L.; Hauser, Sheketha; Rodd, Zachary A.; Liang, Tiebing; Sari, Youssef; McClintick, Jeanette; Rahman, Shafiqur; Engleman, Eric A.

    2016-01-01

    The purpose of this review is to present up-to-date pharmacological, genetic and behavioral findings from the alcohol-preferring P rat and summarize similar past work. Behaviorally, the focus will be on how the P rat meets criteria put forth for a valid animal model of alcoholism with a highlight on its use as an animal model of polysubstance abuse, including alcohol, nicotine and psychostimulants. Pharmacologically and genetically, the focus will be on the neurotransmitter and neuropeptide systems that have received the most attention: cholinergic, dopaminergic, GABAergic, glutamatergic, serotonergic, noradrenergic, corticotrophin releasing hormone, opioid, and neuropeptide Y. Herein we sought to place the P rat’s behavioral and neurochemical phenotypes, and to some extent its genotype, in the context of the clinical literature. After reviewing the findings thus far, this paper discusses future directions for expanding the use of this genetic animal model of alcoholism to identify molecular targets for treating drug addiction in general. PMID:27055615

  13. A Genetic Animal Model of Alcoholism for Screening Medications to Treat Addiction.

    PubMed

    Bell, R L; Hauser, S; Rodd, Z A; Liang, T; Sari, Y; McClintick, J; Rahman, S; Engleman, E A

    2016-01-01

    The purpose of this review is to present up-to-date pharmacological, genetic, and behavioral findings from the alcohol-preferring P rat and summarize similar past work. Behaviorally, the focus will be on how the P rat meets criteria put forth for a valid animal model of alcoholism with a highlight on its use as an animal model of polysubstance abuse, including alcohol, nicotine, and psychostimulants. Pharmacologically and genetically, the focus will be on the neurotransmitter and neuropeptide systems that have received the most attention: cholinergic, dopaminergic, GABAergic, glutamatergic, serotonergic, noradrenergic, corticotrophin releasing hormone, opioid, and neuropeptide Y. Herein, we sought to place the P rat's behavioral and neurochemical phenotypes, and to some extent its genotype, in the context of the clinical literature. After reviewing the findings thus far, this chapter discusses future directions for expanding the use of this genetic animal model of alcoholism to identify molecular targets for treating drug addiction in general. PMID:27055615

  14. Mouse Models of Cancer: Sleeping Beauty Transposons for Insertional Mutagenesis Screens and Reverse Genetic Studies

    PubMed Central

    Tschida, Barbara R.; Largaespada, David A.; Keng, Vincent W.

    2014-01-01

    The genetic complexity and heterogeneity of cancer has posed a problem in designing rationally targeted therapies effective in a large proportion of human cancer. Genomic characterization of many cancer types has provided a staggering amount of data that needs to be interpreted to further our understanding of this disease. Forward genetic screening in mice using Sleeping Beauty (SB) based insertional mutagenesis is an effective method for candidate cancer gene discovery that can aid in distinguishing driver from passenger mutations in human cancer. This system has been adapted for unbiased screens to identify drivers of multiple cancer types. These screens have already identified hundreds of candidate cancer-promoting mutations. These can be used to develop new mouse models for further study, which may prove useful for therapeutic testing. SB technology may also hold the key for rapid generation of reverse genetic mouse models of cancer, and has already been used to model glioblastoma and liver cancer. PMID:24468652

  15. Learning to Fish with Genetics: A Primer on the Vertebrate Model Danio rerio.

    PubMed

    Holtzman, Nathalia G; Iovine, M Kathryn; Liang, Jennifer O; Morris, Jacqueline

    2016-07-01

    In the last 30 years, the zebrafish has become a widely used model organism for research on vertebrate development and disease. Through a powerful combination of genetics and experimental embryology, significant inroads have been made into the regulation of embryonic axis formation, organogenesis, and the development of neural networks. Research with this model has also expanded into other areas, including the genetic regulation of aging, regeneration, and animal behavior. Zebrafish are a popular model because of the ease with which they can be maintained, their small size and low cost, the ability to obtain hundreds of embryos on a daily basis, and the accessibility, translucency, and rapidity of early developmental stages. This primer describes the swift progress of genetic approaches in zebrafish and highlights recent advances that have led to new insights into vertebrate biology. PMID:27384027

  16. A model-based approach for analysis of spatial structure in genetic data.

    PubMed

    Yang, Wen-Yun; Novembre, John; Eskin, Eleazar; Halperin, Eran

    2012-06-01

    Characterizing genetic diversity within and between populations has broad applications in studies of human disease and evolution. We propose a new approach, spatial ancestry analysis, for the modeling of genotypes in two- or three-dimensional space. In spatial ancestry analysis (SPA), we explicitly model the spatial distribution of each SNP by assigning an allele frequency as a continuous function in geographic space. We show that the explicit modeling of the allele frequency allows individuals to be localized on the map on the basis of their genetic information alone. We apply our SPA method to a European and a worldwide population genetic variation data set and identify SNPs showing large gradients in allele frequency, and we suggest these as candidate regions under selection. These regions include SNPs in the well-characterized LCT region, as well as at loci including FOXP2, OCA2 and LRP1B. PMID:22610118

  17. Xiphophorus interspecies hybrids as genetic models of induced neoplasia.

    PubMed

    Walter, R B; Kazianis, S

    2001-01-01

    Fishes of the genus Xiphophorus (platyfishes and swordtails) are small, internally fertilizing, livebearing, and derived from freshwater habitats in Mexico, Guatemala, Belize, and Honduras. Scientists have used these fishes in cancer research studies for more than 70 yr. The genus is presently composed of 22 species that are quite divergent in their external morphology. Most cancer studies using Xiphophorus use hybrids, which can be easily produced by artificial insemination. Phenotypic traits, such as macromelanophore pigment patterns, are often drastically altered as a result of lack of gene regulation within hybrid fishes. These fish can develop large exophytic melanomas as a result of upregulated expression of these pigment patterns. Because backcross hybrid fish are susceptible to the development of melanoma and other neoplasms, they can be subjected to potentially deleterious chemical and physical agents. It is thus possible to use gene mapping and cloning methodologies to identify and characterize oncogenes and tumor suppressors implicated in spontaneous or induced neoplasia. This article reviews the history of cancer research using Xiphophorus and recent developments regarding DNA repair capabilities, mapping, and cloning of candidate genes involved in neoplastic phenotypes. The particular genetic complexity of melanoma in these fishes is analyzed and reviewed. PMID:11581522

  18. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle.

    PubMed

    Singh, Ajay; Singh, Avtar; Singh, Manvendra; Prakash, Ved; Ambhore, G S; Sahoo, S K; Dash, Soumya

    2016-06-01

    A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields. PMID:26954137

  19. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

    PubMed Central

    Singh, Ajay; Singh, Avtar; Singh, Manvendra; Prakash, Ved; Ambhore, G. S.; Sahoo, S. K.; Dash, Soumya

    2016-01-01

    A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields. PMID:26954137

  20. Genetic and Functional Studies of the Intervertebral Disc: A Novel Murine Intervertebral Disc Model

    PubMed Central

    Pelle, Dominic W.; Peacock, Jacqueline D.; Schmidt, Courtney L.; Kampfschulte, Kevin; Scholten, Donald J.; Russo, Scott S.; Easton, Kenneth J.; Steensma, Matthew R.

    2014-01-01

    Intervertebral disc (IVD) homeostasis is mediated through a combination of micro-environmental and biomechanical factors, all of which are subject to genetic influences. The aim of this study is to develop and characterize a genetically tractable, ex vivo organ culture model that can be used to further elucidate mechanisms of intervertebral disc disease. Specifically, we demonstrate that IVD disc explants (1) maintain their native phenotype in prolonged culture, (2) are responsive to exogenous stimuli, and (3) that relevant homeostatic regulatory mechanisms can be modulated through ex-vivo genetic recombination. We present a novel technique for isolation of murine IVD explants with demonstration of explant viability (CMFDA/propidium iodide staining), disc anatomy (H&E), maintenance of extracellular matrix (ECM) (Alcian Blue staining), and native expression profile (qRT-PCR) as well as ex vivo genetic recombination (mT/mG reporter mice; AdCre) following 14 days of culture in DMEM media containing 10% fetal bovine serum, 1% L-glutamine, and 1% penicillin/streptomycin. IVD explants maintained their micro-anatomic integrity, ECM proteoglycan content, viability, and gene expression profile consistent with a homeostatic drive in culture. Treatment of genetically engineered explants with cre-expressing adenovirus efficaciously induced ex vivo genetic recombination in a variety of genetically engineered mouse models. Exogenous administration of IL-1ß and TGF-ß3 resulted in predicted catabolic and anabolic responses, respectively. Genetic recombination of TGFBR1fl/fl explants resulted in constitutively active TGF-ß signaling that matched that of exogenously administered TGF-ß3. Our results illustrate the utility of the murine intervertebral disc explant to investigate mechanisms of intervertebral disc degeneration. PMID:25474689

  1. Do clones degenerate over time? Explaining the genetic variability of asexuals through population genetic models

    PubMed Central

    2011-01-01

    Background Quest for understanding the nature of mechanisms governing the life span of clonal organisms lasts for several decades. Phylogenetic evidence for recent origins of most clones is usually interpreted as proof that clones suffer from gradual age-dependent fitness decay (e.g. Muller's ratchet). However, we have shown that a neutral drift can also qualitatively explain the observed distribution of clonal ages. This finding was followed by several attempts to distinguish the effects of neutral and non-neutral processes. Most recently, Neiman et al. 2009 (Ann N Y Acad Sci.:1168:185-200.) reviewed the distribution of asexual lineage ages estimated from a diverse array of taxa and concluded that neutral processes alone may not explain the observed data. Moreover, the authors inferred that similar types of mechanisms determine maximum asexual lineage ages in all asexual taxa. In this paper we review recent methods for distinguishing the effects of neutral and non-neutral processes and point at methodological problems related with them. Results and Discussion We found that contemporary analyses based on phylogenetic data are inadequate to provide any clear-cut answer about the nature and generality of processes affecting evolution of clones. As an alternative approach, we demonstrate that sequence variability in asexual populations is suitable to detect age-dependent selection against clonal lineages. We found that asexual taxa with relatively old clonal lineages are characterised by progressively stronger deviations from neutrality. Conclusions Our results demonstrate that some type of age-dependent selection against clones is generally operational in asexual animals, which cover a wide taxonomic range spanning from flatworms to vertebrates. However, we also found a notable difference between the data distribution predicted by available models of sequence evolution and those observed in empirical data. These findings point at the possibility that processes

  2. Natural diversity in the model legume Medicago truncatula allows identifying distinct genetic mechanisms conferring partial resistance to Verticillium wilt

    PubMed Central

    Gentzbittel, Laurent

    2013-01-01

    Verticillium wilt is a major threat to alfalfa (Medicago sativa) and many other crops. The model legume Medicago truncatula was used as a host for studying resistance and susceptibility to Verticillium albo-atrum. In addition to presenting well-established genetic resources, this wild plant species enables to investigate biodiversity of the response to the pathogen and putative crosstalk between disease and symbiosis. Symptom scoring after root inoculation and modelling of disease curves allowed assessing susceptibility levels in recombinant lines of three crosses between susceptible and resistant lines, in a core collection of 32 lines, and in mutants affected in symbiosis with rhizobia. A GFP-expressing V. albo-atrum strain was used to study colonization of susceptible plants. Symptoms and colonization pattern in infected M. truncatula plants were typical of Verticillium wilt. Three distinct major quantitative trait loci were identified using a multicross, multisite design, suggesting that simple genetic mechanisms appear to control Verticillium wilt resistance in M. truncatula lines A17 and DZA45.5. The disease functional parameters varied largely in lines of the core collection. This biodiversity with regard to disease response encourages the development of association genetics and ecological approaches. Several mutants of the resistant line, impaired in different steps of rhizobial symbiosis, were affected in their response to V. albo-atrum, which suggests that mechanisms involved in the establishment of symbiosis or disease might have some common regulatory control points. PMID:23213135

  3. FITPOP, a heuristic simulation model of population dynamics and genetics with special reference to fisheries

    USGS Publications Warehouse

    McKenna, James E., Jr.

    2000-01-01

    Although, perceiving genetic differences and their effects on fish population dynamics is difficult, simulation models offer a means to explore and illustrate these effects. I partitioned the intrinsic rate of increase parameter of a simple logistic-competition model into three components, allowing specification of effects of relative differences in fitness and mortality, as well as finite rate of increase. This model was placed into an interactive, stochastic environment to allow easy manipulation of model parameters (FITPOP). Simulation results illustrated the effects of subtle differences in genetic and population parameters on total population size, overall fitness, and sensitivity of the system to variability. Several consequences of mixing genetically distinct populations were illustrated. For example, behaviors such as depression of population size after initial introgression and extirpation of native stocks due to continuous stocking of genetically inferior fish were reproduced. It also was shown that carrying capacity relative to the amount of stocking had an important influence on population dynamics. Uncertainty associated with parameter estimates reduced confidence in model projections. The FITPOP model provided a simple tool to explore population dynamics, which may assist in formulating management strategies and identifying research needs.

  4. Unraveling Additive from Nonadditive Effects Using Genomic Relationship Matrices

    PubMed Central

    Muñoz, Patricio R.; Resende, Marcio F. R.; Gezan, Salvador A.; Resende, Marcos Deon Vilela; de los Campos, Gustavo; Kirst, Matias; Huber, Dudley; Peter, Gary F.

    2014-01-01

    The application of quantitative genetics in plant and animal breeding has largely focused on additive models, which may also capture dominance and epistatic effects. Partitioning genetic variance into its additive and nonadditive components using pedigree-based models (P-genomic best linear unbiased predictor) (P-BLUP) is difficult with most commonly available family structures. However, the availability of dense panels of molecular markers makes possible the use of additive- and dominance-realized genomic relationships for the estimation of variance components and the prediction of genetic values (G-BLUP). We evaluated height data from a multifamily population of the tree species Pinus taeda with a systematic series of models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance), using either pedigree- or marker-based information. We show that, compared with the pedigree, use of realized genomic relationships in marker-based models yields a substantially more precise separation of additive and nonadditive components of genetic variance. We conclude that the marker-based relationship matrices in a model including additive and nonadditive effects performed better, improving breeding value prediction. Moreover, our results suggest that, for tree height in this population, the additive and nonadditive components of genetic variance are similar in magnitude. This novel result improves our current understanding of the genetic control and architecture of a quantitative trait and should be considered when developing breeding strategies. PMID:25324160

  5. Emerging Technologies to Create Inducible and Genetically Defined Porcine Cancer Models

    PubMed Central

    Schook, Lawrence B.; Rund, Laurie; Begnini, Karine R.; Remião, Mariana H.; Seixas, Fabiana K.; Collares, Tiago

    2016-01-01

    There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic, and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research. PMID:26973698

  6. Structured additive regression modeling of age of menarche and menopause in a breast cancer screening program.

    PubMed

    Duarte, Elisa; de Sousa, Bruno; Cadarso-Suarez, Carmen; Rodrigues, Vitor; Kneib, Thomas

    2014-05-01

    Breast cancer risk is believed to be associated with several reproductive factors, such as early menarche and late menopause. This study is based on the registries of the first time a woman enters the screening program, and presents a spatio-temporal analysis of the variables age of menarche and age of menopause along with other reproductive and socioeconomic factors. The database was provided by the Portuguese Cancer League (LPCC), a private nonprofit organization dealing with multiple issues related to oncology of which the Breast Cancer Screening Program is one of its main activities. The registry consists of 259,652 records of women who entered the screening program for the first time between 1990 and 2007 (45-69-year age group). Structured Additive Regression (STAR) models were used to explore spatial and temporal correlations with a wide range of covariates. These models are flexible enough to deal with a variety of complex datasets, allowing us to reveal possible relationships among the variables considered in this study. The analysis shows that early menarche occurs in younger women and in municipalities located in the interior of central Portugal. Women living in inland municipalities register later ages for menopause, and those born in central Portugal after 1933 show a decreasing trend in the age of menopause. Younger ages of menarche and late menopause are observed in municipalities with a higher purchasing power index. The analysis performed in this study portrays the time evolution of the age of menarche and age of menopause and their spatial characterization, adding to the identification of factors that could be of the utmost importance in future breast cancer incidence research. PMID:24615881

  7. Integrating Genetic, Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity

    PubMed Central

    Mas, Sergi; Gassó, Patricia; Morer, Astrid; Calvo, Anna; Bargalló, Nuria; Lafuente, Amalia; Lázaro, Luisa

    2016-01-01

    We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder. PMID:27093171

  8. Integrating Genetic, Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity.

    PubMed

    Mas, Sergi; Gassó, Patricia; Morer, Astrid; Calvo, Anna; Bargalló, Nuria; Lafuente, Amalia; Lázaro, Luisa

    2016-01-01

    We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder. PMID:27093171

  9. Enhancement of colour stability of anthocyanins in model beverages by gum arabic addition.

    PubMed

    Chung, Cheryl; Rojanasasithara, Thananunt; Mutilangi, William; McClements, David Julian

    2016-06-15

    This study investigated the potential of gum arabic to improve the stability of anthocyanins that are used in commercial beverages as natural colourants. The degradation of purple carrot anthocyanin in model beverage systems (pH 3.0) containing L-ascorbic acid proceeded with a first-order reaction rate during storage (40 °C for 5 days in light). The addition of gum arabic (0.05-5.0%) significantly enhanced the colour stability of anthocyanin, with the most stable systems observed at intermediate levels (1.5%). A further increase in concentration (>1.5%) reduced its efficacy due to a change in the conformation of the gum arabic molecules that hindered their exposure to the anthocyanins. Fluorescence quenching measurements showed that the anthocyanin could have interacted with the glycoprotein fractions of the gum arabic through hydrogen bonding, resulting in enhanced stability. Overall, this study provides valuable information about enhancing the stability of anthocyanins in beverage systems using natural ingredients. PMID:26868542

  10. Statistical inference for the additive hazards model under outcome-dependent sampling

    PubMed Central

    Yu, Jichang; Liu, Yanyan; Sandler, Dale P.; Zhou, Haibo

    2015-01-01

    Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer. PMID:26379363

  11. Influence of the heterogeneous reaction HCL + HOCl on an ozone hole model with hydrocarbon additions

    SciTech Connect

    Elliott, S.; Cicerone, R.J.; Turco, R.P.

    1994-02-20

    Injection of ethane or propane has been suggested as a means for reducing ozone loss within the Antarctic vortex because alkanes can convert active chlorine radicals into hydrochloric acid. In kinetic models of vortex chemistry including as heterogeneous processes only the hydrolysis and HCl reactions of ClONO{sub 2} and N{sub 2}O{sub 5}, parts per billion by volume levels of the light alkanes counteract ozone depletion by sequestering chlorine atoms. Introduction of the surface reaction of HCl with HOCl causes ethane to deepen baseline ozone holes and generally works to impede any mitigation by hydrocarbons. The increased depletion occurs because HCl + HOCl can be driven by HO{sub x} radicals released during organic oxidation. Following initial hydrogen abstraction by chlorine, alkane breakdown leads to a net hydrochloric acid activation as the remaining hydrogen atoms enter the photochemical system. Lowering the rate constant for reactions of organic peroxy radicals with ClO to 10{sup {minus}13} cm{sup 3} molecule{sup {minus}1} s{sup {minus}1} does not alter results, and the major conclusions are insensitive to the timing of the ethane additions. Ignoring the organic peroxy radical plus ClO reactions entirely restores remediation capabilities by allowing HO{sub x} removal independent of HCl. Remediation also returns if early evaporation of polar stratospheric clouds leaves hydrogen atoms trapped in aldehyde intermediates, but real ozone losses are small in such cases. 95 refs., 4 figs., 7 tabs.

  12. In vivo characterization of two additional Leishmania donovani strains using the murine and hamster model.

    PubMed

    Kauffmann, F; Dumetz, F; Hendrickx, S; Muraille, E; Dujardin, J-C; Maes, L; Magez, S; De Trez, C

    2016-05-01

    Leishmania donovani is a protozoan parasite causing the neglected tropical disease visceral leishmaniasis. One difficulty to study the immunopathology upon L. donovani infection is the limited adaptability of the strains to experimental mammalian hosts. Our knowledge about L. donovani infections relies on a restricted number of East African strains (LV9, 1S). Isolated from patients in the 1960s, these strains were described extensively in mice and Syrian hamsters and have consequently become 'reference' laboratory strains. L. donovani strains from the Indian continent display distinct clinical features compared to East African strains. Some reports describing the in vivo immunopathology of strains from the Indian continent exist. This study comprises a comprehensive immunopathological characterization upon infection with two additional strains, the Ethiopian L. donovani L82 strain and the Nepalese L. donovani BPK282 strain in both Syrian hamsters and C57BL/6 mice. Parameters that include parasitaemia levels, weight loss, hepatosplenomegaly and alterations in cellular composition of the spleen and liver, showed that the L82 strain generated an overall more virulent infection compared to the BPK282 strain. Altogether, both L. donovani strains are suitable and interesting for subsequent in vivo investigation of visceral leishmaniasis in the Syrian hamster and the C57BL/6 mouse model. PMID:27012562

  13. Random Regression Models Are Suitable to Substitute the Traditional 305-Day Lactation Model in Genetic Evaluations of Holstein Cattle in Brazil

    PubMed Central

    Padilha, Alessandro Haiduck; Cobuci, Jaime Araujo; Costa, Cláudio Napolis; Neto, José Braccini

    2016-01-01

    The aim of this study was to compare two random regression models (RRM) fitted by fourth (RRM4) and fifth-order Legendre polynomials (RRM5) with a lactation model (LM) for evaluating Holstein cattle in Brazil. Two datasets with the same animals were prepared for this study. To apply test-day RRM and LMs, 262,426 test day records and 30,228 lactation records covering 305 days were prepared, respectively. The lowest values of Akaike’s information criterion, Bayesian information criterion, and estimates of the maximum of the likelihood function (−2LogL) were for RRM4. Heritability for 305-day milk yield (305MY) was 0.23 (RRM4), 0.24 (RRM5), and 0.21 (LM). Heritability, additive genetic and permanent environmental variances of test days on days in milk was from 0.16 to 0.27, from 3.76 to 6.88 and from 11.12 to 20.21, respectively. Additive genetic correlations between test days ranged from 0.20 to 0.99. Permanent environmental correlations between test days were between 0.07 and 0.99. Standard deviations of average estimated breeding values (EBVs) for 305MY from RRM4 and RRM5 were from 11% to 30% higher for bulls and around 28% higher for cows than that in LM. Rank correlations between RRM EBVs and LM EBVs were between 0.86 to 0.96 for bulls and 0.80 to 0.87 for cows. Average percentage of gain in reliability of EBVs for 305-day yield increased from 4% to 17% for bulls and from 23% to 24% for cows when reliability of EBVs from RRM models was compared to those from LM model. Random regression model fitted by fourth order Legendre polynomials is recommended for genetic evaluations of Brazilian Holstein cattle because of the higher reliability in the estimation of breeding values. PMID:26954176

  14. Random Regression Models Are Suitable to Substitute the Traditional 305-Day Lactation Model in Genetic Evaluations of Holstein Cattle in Brazil.

    PubMed

    Padilha, Alessandro Haiduck; Cobuci, Jaime Araujo; Costa, Cláudio Napolis; Neto, José Braccini

    2016-06-01

    The aim of this study was to compare two random regression models (RRM) fitted by fourth (RRM4) and fifth-order Legendre polynomials (RRM5) with a lactation model (LM) for evaluating Holstein cattle in Brazil. Two datasets with the same animals were prepared for this study. To apply test-day RRM and LMs, 262,426 test day records and 30,228 lactation records covering 305 days were prepared, respectively. The lowest values of Akaike's information criterion, Bayesian information criterion, and estimates of the maximum of the likelihood function (-2LogL) were for RRM4. Heritability for 305-day milk yield (305MY) was 0.23 (RRM4), 0.24 (RRM5), and 0.21 (LM). Heritability, additive genetic and permanent environmental variances of test days on days in milk was from 0.16 to 0.27, from 3.76 to 6.88 and from 11.12 to 20.21, respectively. Additive genetic correlations between test days ranged from 0.20 to 0.99. Permanent environmental correlations between test days were between 0.07 and 0.99. Standard deviations of average estimated breeding values (EBVs) for 305MY from RRM4 and RRM5 were from 11% to 30% higher for bulls and around 28% higher for cows than that in LM. Rank correlations between RRM EBVs and LM EBVs were between 0.86 to 0.96 for bulls and 0.80 to 0.87 for cows. Average percentage of gain in reliability of EBVs for 305-day yield increased from 4% to 17% for bulls and from 23% to 24% for cows when reliability of EBVs from RRM models was compared to those from LM model. Random regression model fitted by fourth order Legendre polynomials is recommended for genetic evaluations of Brazilian Holstein cattle because of the higher reliability in the estimation of breeding values. PMID:26954176

  15. Analysis of Genetic Variation and Potential Applications in Genome-Scale Metabolic Modeling

    PubMed Central

    Cardoso, João G. R.; Andersen, Mikael Rørdam; Herrgård, Markus J.; Sonnenschein, Nikolaus

    2015-01-01

    Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic variation during a long term production process may lead to significant economic losses and it is important to understand how to control this type of variation. With the emergence of next-generation sequencing technologies, genetic variation in microbial strains can now be determined on an unprecedented scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function, and discuss approaches for interfacing existing bioinformatics approaches with genome-scale models of cellular processes in order to predict effects of sequence variation on cellular phenotypes. PMID:25763369

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

    PubMed

    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. PMID:26083847

  17. Two-Variance-Component Model Improves Genetic Prediction in Family Datasets

    PubMed Central

    Tucker, George; Loh, Po-Ru; MacLeod, Iona M.; Hayes, Ben J.; Goddard, Michael E.; Berger, Bonnie; Price, Alkes L.

    2015-01-01

    Genetic prediction based on either identity by state (IBS) sharing or pedigree information has been investigated extensively with best linear unbiased prediction (BLUP) methods. Such methods were pioneered in plant and animal-breeding literature and have since been applied to predict human traits, with the aim of eventual clinical utility. However, methods to combine IBS sharing and pedigree information for genetic prediction in humans have not been explored. We introduce a two-variance-component model for genetic prediction: one component for IBS sharing and one for approximate pedigree structure, both estimated with genetic markers. In simulations using real genotypes from the Candidate-gene Association Resource (CARe) and Framingham Heart Study (FHS) family cohorts, we demonstrate that the two-variance-component model achieves gains in prediction r2 over standard BLUP at current sample sizes, and we project, based on simulations, that these gains will continue to hold at larger sample sizes. Accordingly, in analyses of four quantitative phenotypes from CARe and two quantitative phenotypes from FHS, the two-variance-component model significantly improves prediction r2 in each case, with up to a 20% relative improvement. We also find that standard mixed-model association tests can produce inflated test statistics in datasets with related individuals, whereas the two-variance-component model corrects for inflation. PMID:26544803

  18. Two-Variance-Component Model Improves Genetic Prediction in Family Datasets.

    PubMed

    Tucker, George; Loh, Po-Ru; MacLeod, Iona M; Hayes, Ben J; Goddard, Michael E; Berger, Bonnie; P