Sztepanacz, Jacqueline L; Rundle, Howard D
2012-10-01
Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low- compared to high-fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high- and low-fitness individuals and was greater among the low-fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.
Evolution of Genetic Variance during Adaptive Radiation.
Walter, Greg M; Aguirre, J David; Blows, Mark W; Ortiz-Barrientos, Daniel
2018-04-01
Genetic correlations between traits can concentrate genetic variance into fewer phenotypic dimensions that can bias evolutionary trajectories along the axis of greatest genetic variance and away from optimal phenotypes, constraining the rate of evolution. If genetic correlations limit adaptation, rapid adaptive divergence between multiple contrasting environments may be difficult. However, if natural selection increases the frequency of rare alleles after colonization of new environments, an increase in genetic variance in the direction of selection can accelerate adaptive divergence. Here, we explored adaptive divergence of an Australian native wildflower by examining the alignment between divergence in phenotype mean and divergence in genetic variance among four contrasting ecotypes. We found divergence in mean multivariate phenotype along two major axes represented by different combinations of plant architecture and leaf traits. Ecotypes also showed divergence in the level of genetic variance in individual traits and the multivariate distribution of genetic variance among traits. Divergence in multivariate phenotypic mean aligned with divergence in genetic variance, with much of the divergence in phenotype among ecotypes associated with changes in trait combinations containing substantial levels of genetic variance. Overall, our results suggest that natural selection can alter the distribution of genetic variance underlying phenotypic traits, increasing the amount of genetic variance in the direction of natural selection and potentially facilitating rapid adaptive divergence during an adaptive radiation.
Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.
Yang, Ye; Christensen, Ole F; Sorensen, Daniel
2011-02-01
Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.
Genetic variants influencing phenotypic variance heterogeneity.
Ek, Weronica E; Rask-Andersen, Mathias; Karlsson, Torgny; Enroth, Stefan; Gyllensten, Ulf; Johansson, Åsa
2018-03-01
Most genetic studies identify genetic variants associated with disease risk or with the mean value of a quantitative trait. More rarely, genetic variants associated with variance heterogeneity are considered. In this study, we have identified such variance single-nucleotide polymorphisms (vSNPs) and examined if these represent biological gene × gene or gene × environment interactions or statistical artifacts caused by multiple linked genetic variants influencing the same phenotype. We have performed a genome-wide study, to identify vSNPs associated with variance heterogeneity in DNA methylation levels. Genotype data from over 10 million single-nucleotide polymorphisms (SNPs), and DNA methylation levels at over 430 000 CpG sites, were analyzed in 729 individuals. We identified vSNPs for 7195 CpG sites (P mean DNA methylation levels. We further showed that variance heterogeneity between genotypes mainly represents additional, often rare, SNPs in linkage disequilibrium (LD) with the respective vSNP and for some vSNPs, multiple low frequency variants co-segregating with one of the vSNP alleles. Therefore, our results suggest that variance heterogeneity of DNA methylation mainly represents phenotypic effects by multiple SNPs, rather than biological interactions. Such effects may also be important for interpreting variance heterogeneity of more complex clinical phenotypes.
Analysis of conditional genetic effects and variance components in developmental genetics.
Zhu, J
1995-12-01
A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.
Comparing estimates of genetic variance across different relationship models.
Legarra, Andres
2016-02-01
Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.
Dominance genetic variance for traits under directional selection in Drosophila serrata.
Sztepanacz, Jacqueline L; Blows, Mark W
2015-05-01
In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.
Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.
Zapko-Willmes, Alexandra; Kandler, Christian
2018-01-01
The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.
Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L
2017-10-01
Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.
Genetic control of residual variance of yearling weight in Nellore beef cattle.
Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R
2017-04-01
There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting
variance components and genetic parameters for live weight
African Journals Online (AJOL)
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Against this background the present study estimated the (co)variance .... Starting values for the (co)variance components of two-trait models were ..... Estimates of genetic parameters for weaning weight of beef accounting for direct-maternal.
Genetic and environmental variance in content dimensions of the MMPI.
Rose, R J
1988-08-01
To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.
Heritability, variance components and genetic advance of some ...
African Journals Online (AJOL)
Heritability, variance components and genetic advance of some yield and yield related traits in Ethiopian ... African Journal of Biotechnology ... randomized complete block design at Adet Agricultural Research Station in 2008 cropping season.
Genetic factors explain half of all variance in serum eosinophil cationic protein
DEFF Research Database (Denmark)
Elmose, Camilla; Sverrild, Asger; van der Sluis, Sophie
2014-01-01
with variation in serum ECP and to determine the relative proportion of the variation in ECP due to genetic and non-genetic factors, in an adult twin sample. METHODS: A sample of 575 twins, selected through a proband with self-reported asthma, had serum ECP, lung function, airway responsiveness to methacholine......, exhaled nitric oxide, and skin test reactivity, measured. Linear regression analysis and variance component models were used to study factors associated with variation in ECP and the relative genetic influence on ECP levels. RESULTS: Sex (regression coefficient = -0.107, P ... was statistically non-significant (r = -0.11, P = 0.50). CONCLUSION: Around half of all variance in serum ECP is explained by genetic factors. Serum ECP is influenced by sex, BMI, and airway responsiveness. Serum ECP and airway responsiveness seem not to share genetic variance....
Genetic variance components for residual feed intake and feed ...
African Journals Online (AJOL)
Feeding costs of animals is a major determinant of profitability in livestock production enterprises. Genetic selection to improve feed efficiency aims to reduce feeding cost in beef cattle and thereby improve profitability. This study estimated genetic (co)variances between weaning weight and other production, reproduction ...
Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar).
Sonesson, Anna K; Odegård, Jørgen; Rönnegård, Lars
2013-10-17
Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro
Mulder, H.A.; Bijma, P.; Hill, W.G.
2007-01-01
There is empirical evidence that genotypes differ not only in mean, but also in environmental variance of the traits they affect. Genetic heterogeneity of environmental variance may indicate genetic differences in environmental sensitivity. The aim of this study was to develop a general framework
Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation
DEFF Research Database (Denmark)
Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel
2011-01-01
of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box–Cox transformations. Litter size data in rabbits and pigs that had previously been analysed...... in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box–Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis...... in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected...
Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank
2018-03-22
Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.
Vandenplas, J; Bastin, C; Gengler, N; Mulder, H A
2013-09-01
Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed to be homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of 2 groups of milk fatty acids (i.e., saturated and unsaturated fatty acids), and the content in milk of one individual fatty acid (i.e., oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least 3 records and a known sire. These sires had at least 10 cows with records and each herd × test-day had at least 5 cows. The 5 traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively expectation maximization-REML algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01×10(-3) and 4.17×10(-3) for all traits. The genetic standard deviation in residual variance (i.e., approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the 5 studied traits. The standard deviations due to herd × test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd × test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, nongenetic effects also
Stock, Amanda J; Campitelli, Brandon E; Stinchcombe, John R
2014-08-19
Clinal variation is commonly interpreted as evidence of adaptive differentiation, although clines can also be produced by stochastic forces. Understanding whether clines are adaptive therefore requires comparing clinal variation to background patterns of genetic differentiation at presumably neutral markers. Although this approach has frequently been applied to single traits at a time, we have comparatively fewer examples of how multiple correlated traits vary clinally. Here, we characterize multivariate clines in the Ivyleaf morning glory, examining how suites of traits vary with latitude, with the goal of testing for divergence in trait means that would indicate past evolutionary responses. We couple this with analysis of genetic variance in clinally varying traits in 20 populations to test whether past evolutionary responses have depleted genetic variance, or whether genetic variance declines approaching the range margin. We find evidence of clinal differentiation in five quantitative traits, with little evidence of isolation by distance at neutral loci that would suggest non-adaptive or stochastic mechanisms. Within and across populations, the traits that contribute most to population differentiation and clinal trends in the multivariate phenotype are genetically variable as well, suggesting that a lack of genetic variance will not cause absolute evolutionary constraints. Our data are broadly consistent theoretical predictions of polygenic clines in response to shallow environmental gradients. Ecologically, our results are consistent with past findings of natural selection on flowering phenology, presumably due to season-length variation across the range. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Holmes, John B; Dodds, Ken G; Lee, Michael A
2017-03-02
An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.
Genetic variance for uniformity of harvest weight in Nile tilapia (Oreochromis niloticus)
Khaw, H.L.; Ponzoni, R.W.; Yee, H.Y.; Aziz, M.A.; Mulder, H.A.; Marjanovic, J.; Bijma, P.
2016-01-01
Competition for resources is common in aquaculture, which inflates the variability of fish body weight. Selective breeding is one of the effective approaches that may enable a reduction of size variability (or increase in uniformity) for body weight by genetic means. The genetic variance of
Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance
Mulder, H.A.; Veerkamp, R.F.; Vereijken, A.; Bijma, P.; Hill, W.G.
2008-01-01
some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters,
Selection for uniformity in livestock by exploiting genetic heterogeneity of environmental variance
Mulder, H.A.; Bijma, P.; Hill, W.G.
2008-01-01
In some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters,
Directory of Open Access Journals (Sweden)
Guosheng Su
Full Text Available Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1 a simple additive genetic model (MA, 2 a model including both additive and additive by additive epistatic genetic effects (MAE, 3 a model including both additive and dominance genetic effects (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.
Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig
2018-05-01
As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.
Bjørnerem, Åshild; Bui, Minh; Wang, Xiaofang; Ghasem-Zadeh, Ali; Hopper, John L; Zebaze, Roger; Seeman, Ego
2015-03-01
All genetic and environmental factors contributing to differences in bone structure between individuals mediate their effects through the final common cellular pathway of bone modeling and remodeling. We hypothesized that genetic factors account for most of the population variance of cortical and trabecular microstructure, in particular intracortical porosity and medullary size - void volumes (porosity), which establish the internal bone surface areas or interfaces upon which modeling and remodeling deposit or remove bone to configure bone microarchitecture. Microarchitecture of the distal tibia and distal radius and remodeling markers were measured for 95 monozygotic (MZ) and 66 dizygotic (DZ) white female twin pairs aged 40 to 61 years. Images obtained using high-resolution peripheral quantitative computed tomography were analyzed using StrAx1.0, a nonthreshold-based software that quantifies cortical matrix and porosity. Genetic and environmental components of variance were estimated under the assumptions of the classic twin model. The data were consistent with the proportion of variance accounted for by genetic factors being: 72% to 81% (standard errors ∼18%) for the distal tibial total, cortical, and medullary cross-sectional area (CSA); 67% and 61% for total cortical porosity, before and after adjusting for total CSA, respectively; 51% for trabecular volumetric bone mineral density (vBMD; all p accounted for 47% to 68% of the variance (all p ≤ 0.001). Cross-twin cross-trait correlations between tibial cortical porosity and medullary CSA were higher for MZ (rMZ = 0.49) than DZ (rDZ = 0.27) pairs before (p = 0.024), but not after (p = 0.258), adjusting for total CSA. For the remodeling markers, the data were consistent with genetic factors accounting for 55% to 62% of the variance. We infer that middle-aged women differ in their bone microarchitecture and remodeling markers more because of differences in their genetic factors than
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. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.
Use of genomic models to study genetic control of environmental variance
DEFF Research Database (Denmark)
Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel
2011-01-01
. The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...... of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted...... to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm...
Increasing the genetic variance of rice protein through mutation breeding techniques
International Nuclear Information System (INIS)
Ismachin, M.
1975-01-01
Recommended rice variety in Indonesia, Pelita I/1 was treated with gamma rays at the doses of 20 krad, 30 krad, and 40 krad. The seeds were also treated with EMS 1%. In M 2 generation, the protein content of seeds from the visible mutants and from the normal looking plants were analyzed by DBC method. No significant increase in the genetic variance was found on the samples treated with 20 krad gamma, and on the normal looking plants treated by EMS 1%. The mean value of the treated samples were mostly significant decrease compared with the mean value of the protein distribution in untreated samples (control). Since significant increase in genetic variance was also found in M 2 normal looking plants - treated with gamma at the doses of 30 krad and 40 krad -selection of protein among these materials could be more valuable. (author)
Lehermeier, Christina; Teyssèdre, Simon; Schön, Chris-Carolin
2017-12-01
A crucial step in plant breeding is the selection and combination of parents to form new crosses. Genome-based prediction guides the selection of high-performing parental lines in many crop breeding programs which ensures a high mean performance of progeny. To warrant maximum selection progress, a new cross should also provide a large progeny variance. The usefulness concept as measure of the gain that can be obtained from a specific cross accounts for variation in progeny variance. Here, it is shown that genetic gain can be considerably increased when crosses are selected based on their genomic usefulness criterion compared to selection based on mean genomic estimated breeding values. An efficient and improved method to predict the genetic variance of a cross based on Markov chain Monte Carlo samples of marker effects from a whole-genome regression model is suggested. In simulations representing selection procedures in crop breeding programs, the performance of this novel approach is compared with existing methods, like selection based on mean genomic estimated breeding values and optimal haploid values. In all cases, higher genetic gain was obtained compared with previously suggested methods. When 1% of progenies per cross were selected, the genetic gain based on the estimated usefulness criterion increased by 0.14 genetic standard deviation compared to a selection based on mean genomic estimated breeding values. Analytical derivations of the progeny genotypic variance-covariance matrix based on parental genotypes and genetic map information make simulations of progeny dispensable, and allow fast implementation in large-scale breeding programs. Copyright © 2017 by the Genetics Society of America.
Argentine Population Genetic Structure: Large Variance in Amerindian Contribution
Seldin, Michael F.; Tian, Chao; Shigeta, Russell; Scherbarth, Hugo R.; Silva, Gabriel; Belmont, John W.; Kittles, Rick; Gamron, Susana; Allevi, Alberto; Palatnik, Simon A.; Alvarellos, Alejandro; Paira, Sergio; Caprarulo, Cesar; Guillerón, Carolina; Catoggio, Luis J.; Prigione, Cristina; Berbotto, Guillermo A.; García, Mercedes A.; Perandones, Carlos E.; Pons-Estel, Bernardo A.; Alarcon-Riquelme, Marta E.
2011-01-01
Argentine population genetic structure was examined using a set of 78 ancestry informative markers (AIMs) to assess the contributions of European, Amerindian, and African ancestry in 94 individuals members of this population. Using the Bayesian clustering algorithm STRUCTURE, the mean European contribution was 78%, the Amerindian contribution was 19.4%, and the African contribution was 2.5%. Similar results were found using weighted least mean square method: European, 80.2%; Amerindian, 18.1%; and African, 1.7%. Consistent with previous studies the current results showed very few individuals (four of 94) with greater than 10% African admixture. Notably, when individual admixture was examined, the Amerindian and European admixture showed a very large variance and individual Amerindian contribution ranged from 1.5 to 84.5% in the 94 individual Argentine subjects. These results indicate that admixture must be considered when clinical epidemiology or case control genetic analyses are studied in this population. Moreover, the current study provides a set of informative SNPs that can be used to ascertain or control for this potentially hidden stratification. In addition, the large variance in admixture proportions in individual Argentine subjects shown by this study suggests that this population is appropriate for future admixture mapping studies. PMID:17177183
Ramakers, J.J.C.; Culina, A.; Visser, M.E.; Gienapp, P.
2017-01-01
Additive genetic variance and selection are the key ingredients for evolution. In wild populations, however, predicting evolutionary trajectories is difficult, potentially by an unrecognised underlying environment dependency of both (additive) genetic variance and selection (i.e. G×E and S×E).
Genetic control of residual variance of yearling weight in nellore beef cattle
Iung, L.H.S.; Neves, H.H.R.; Mulder, H.A.; Carvalheiro, R.
2017-01-01
There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between
Mulder, H A; Crump, R E; Calus, M P L; Veerkamp, R F
2013-01-01
In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean and environmental variance of somatic cell score (SCS) by identifying genome-wide associations for mean and environmental variance of SCS in dairy cows and by quantifying the accuracy of genome-wide breeding values. Somatic cell score was used because previous research has shown that the environmental variance of SCS is partly under genetic control and reduction of the variance of SCS by selection is desirable. In this study, we used 37,590 single nucleotide polymorphism (SNP) genotypes and 46,353 test-day records of 1,642 cows at experimental research farms in 4 countries in Europe. We used a genomic relationship matrix in a double hierarchical generalized linear model to estimate genome-wide breeding values and genetic parameters. The estimated mean and environmental variance per cow was used in a Bayesian multi-locus model to identify SNP associated with either the mean or the environmental variance of SCS. Based on the obtained accuracy of genome-wide breeding values, 985 and 541 independent chromosome segments affecting the mean and environmental variance of SCS, respectively, were identified. Using a genomic relationship matrix increased the accuracy of breeding values relative to using a pedigree relationship matrix. In total, 43 SNP were significantly associated with either the mean (22) or the environmental variance of SCS (21). The SNP with the highest Bayes factor was on chromosome 9 (Hapmap31053-BTA-111664) explaining approximately 3% of the genetic variance of the environmental variance of SCS. Other significant SNP explained less than 1% of the genetic variance. It can be concluded that fewer genomic regions affect the environmental variance of SCS than the
Validation of consistency of Mendelian sampling variance.
Tyrisevä, A-M; Fikse, W F; Mäntysaari, E A; Jakobsen, J; Aamand, G P; Dürr, J; Lidauer, M H
2018-03-01
Experiences from international sire evaluation indicate that the multiple-trait across-country evaluation method is sensitive to changes in genetic variance over time. Top bulls from birth year classes with inflated genetic variance will benefit, hampering reliable ranking of bulls. However, none of the methods available today enable countries to validate their national evaluation models for heterogeneity of genetic variance. We describe a new validation method to fill this gap comprising the following steps: estimating within-year genetic variances using Mendelian sampling and its prediction error variance, fitting a weighted linear regression between the estimates and the years under study, identifying possible outliers, and defining a 95% empirical confidence interval for a possible trend in the estimates. We tested the specificity and sensitivity of the proposed validation method with simulated data using a real data structure. Moderate (M) and small (S) size populations were simulated under 3 scenarios: a control with homogeneous variance and 2 scenarios with yearly increases in phenotypic variance of 2 and 10%, respectively. Results showed that the new method was able to estimate genetic variance accurately enough to detect bias in genetic variance. Under the control scenario, the trend in genetic variance was practically zero in setting M. Testing cows with an average birth year class size of more than 43,000 in setting M showed that tolerance values are needed for both the trend and the outlier tests to detect only cases with a practical effect in larger data sets. Regardless of the magnitude (yearly increases in phenotypic variance of 2 or 10%) of the generated trend, it deviated statistically significantly from zero in all data replicates for both cows and bulls in setting M. In setting S with a mean of 27 bulls in a year class, the sampling error and thus the probability of a false-positive result clearly increased. Still, overall estimated genetic
Strategies for MCMC computation inquantitative genetics
DEFF Research Database (Denmark)
Waagepetersen, Rasmus; Ibánēz-Escriche, Noelia; Sorensen, Daniel
another extension of the linear mixed model introducing genetic random effects influencing the log residual variances of the observations thereby producing a genetically structured variance heterogeneity. Considerable computational problems arise when abandoning the standard linear mixed model. Maximum...... the various algorithms in the context of the heterogeneous variance model. Apart from being a model of great interest in its own right, this model has proven to be a hard test for MCMC methods. We compare the performances of the different algorithms when applied to three real datasets which differ markedly...... results of applying two MCMC schemes to data sets with pig litter sizes, rabbit litter sizes, and snail weights. Some concluding remarks are given in Section 5....
Mäki, K.; Groen, A.F.; Liinamo, A.E.; Ojala, M.
2002-01-01
The aims of this study were to assess genetic variances, trends and mode of inheritance for hip and elbow dysplasia in Finnish dog populations. The influence of time-dependent fixed effects in the model when estimating the genetic trends was also studied. Official hip and elbow dysplasia screening
Mulder, H.A.; Crump, R.E.; Calus, M.P.L.; Veerkamp, R.F.
2013-01-01
In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean
Directory of Open Access Journals (Sweden)
Matheus Costa dos Reis
2014-01-01
Full Text Available This study was carried out to obtain the estimates of genetic variance and covariance components related to intra- and interpopulation in the original populations (C0 and in the third cycle (C3 of reciprocal recurrent selection (RRS which allows breeders to define the best breeding strategy. For that purpose, the half-sib progenies of intrapopulation (P11 and P22 and interpopulation (P12 and P21 from populations 1 and 2 derived from single-cross hybrids in the 0 and 3 cycles of the reciprocal recurrent selection program were used. The intra- and interpopulation progenies were evaluated in a 10×10 triple lattice design in two separate locations. The data for unhusked ear weight (ear weight without husk and plant height were collected. All genetic variance and covariance components were estimated from the expected mean squares. The breakdown of additive variance into intrapopulation and interpopulation additive deviations (στ2 and the covariance between these and their intrapopulation additive effects (CovAτ found predominance of the dominance effect for unhusked ear weight. Plant height for these components shows that the intrapopulation additive effect explains most of the variation. Estimates for intrapopulation and interpopulation additive genetic variances confirm that populations derived from single-cross hybrids have potential for recurrent selection programs.
Influence of Family Structure on Variance Decomposition
DEFF Research Database (Denmark)
Edwards, Stefan McKinnon; Sarup, Pernille Merete; Sørensen, Peter
Partitioning genetic variance by sets of randomly sampled genes for complex traits in D. melanogaster and B. taurus, has revealed that population structure can affect variance decomposition. In fruit flies, we found that a high likelihood ratio is correlated with a high proportion of explained ge...... capturing pure noise. Therefore it is necessary to use both criteria, high likelihood ratio in favor of a more complex genetic model and proportion of genetic variance explained, to identify biologically important gene groups...
Ontogeny of additive and maternal genetic effects: lessons from domestic mammals.
Wilson, Alastair J; Reale, Denis
2006-01-01
Evolution of size and growth depends on heritable variation arising from additive and maternal genetic effects. Levels of heritable (and nonheritable) variation might change over ontogeny, increasing through "variance compounding" or decreasing through "compensatory growth." We test for these processes using a meta-analysis of age-specific weight traits in domestic ungulates. Generally, mean standardized variance components decrease with age, consistent with compensatory growth. Phenotypic convergence among adult sheep occurs through decreasing environmental and maternal genetic variation. Maternal variation similarly declines in cattle. Maternal genetic effects are thus reduced with age (both in absolute and relative terms). Significant trends in heritability (decreasing in cattle, increasing in sheep) result from declining maternal and environmental components rather than from changing additive variation. There was no evidence for increasing standardized variance components. Any compounding must therefore be masked by more important compensatory processes. While extrapolation of these patterns to processes in natural population is difficult, our results highlight the inadequacy of assuming constancy in genetic parameters over ontogeny. Negative covariance between direct and maternal genetic effects was common. Negative correlations with additive and maternal genetic variances indicate that antagonistic pleiotropy (between additive and maternal genetic effects) may maintain genetic variance and limit responses to selection.
Genotypic-specific variance in Caenorhabditis elegans lifetime fecundity.
Diaz, S Anaid; Viney, Mark
2014-06-01
Organisms live in heterogeneous environments, so strategies that maximze fitness in such environments will evolve. Variation in traits is important because it is the raw material on which natural selection acts during evolution. Phenotypic variation is usually thought to be due to genetic variation and/or environmentally induced effects. Therefore, genetically identical individuals in a constant environment should have invariant traits. Clearly, genetically identical individuals do differ phenotypically, usually thought to be due to stochastic processes. It is now becoming clear, especially from studies of unicellular species, that phenotypic variance among genetically identical individuals in a constant environment can be genetically controlled and that therefore, in principle, this can be subject to selection. However, there has been little investigation of these phenomena in multicellular species. Here, we have studied the mean lifetime fecundity (thus a trait likely to be relevant to reproductive success), and variance in lifetime fecundity, in recently-wild isolates of the model nematode Caenorhabditis elegans. We found that these genotypes differed in their variance in lifetime fecundity: some had high variance in fecundity, others very low variance. We find that this variance in lifetime fecundity was negatively related to the mean lifetime fecundity of the lines, and that the variance of the lines was positively correlated between environments. We suggest that the variance in lifetime fecundity may be a bet-hedging strategy used by this species.
DEFF Research Database (Denmark)
Fé, Dario; Greve-Pedersen, Morten; Jensen, Christian Sig
2013-01-01
In the joint project “FORAGESELECT”, we aim to implement Genome Wide Selection (GWS) in breeding of perennial ryegrass (Lolium perenne L.), in order to increase genetic response in important agronomic traits such as yield, seed production, stress tolerance and disease resistance, while decreasing...... of this study was to estimate the genetic and environmental variance in the training set composed of F2 families selected from a ten year breeding period. Variance components were estimated on 1193 of those families, sown in 2001, 2003 and 2005 in five locations around Europe. Families were tested together...
DEFF Research Database (Denmark)
Ødegård, Jørgen; Meuwissen, Theo HE; Heringstad, Bjørg
2010-01-01
Background In the genetic analysis of binary traits with one observation per animal, animal threshold models frequently give biased heritability estimates. In some cases, this problem can be circumvented by fitting sire- or sire-dam models. However, these models are not appropriate in cases where...... records exist for the parents). Furthermore, the new algorithm showed much faster Markov chain mixing properties for genetic parameters (similar to the sire-dam model). Conclusions The new algorithm to estimate genetic parameters via Gibbs sampling solves the bias problems typically occurring in animal...... individual records exist on parents. Therefore, the aim of our study was to develop a new Gibbs sampling algorithm for a proper estimation of genetic (co)variance components within an animal threshold model framework. Methods In the proposed algorithm, individuals are classified as either "informative...
Directory of Open Access Journals (Sweden)
Francisco Garcia-Gonzalez
2011-01-01
Full Text Available Whether species exhibit significant heritable variation in fitness is central for sexual selection. According to good genes models there must be genetic variation in males leading to variation in offspring fitness if females are to obtain genetic benefits from exercising mate preferences, or by mating multiply. However, sexual selection based on genetic benefits is controversial, and there is limited unambiguous support for the notion that choosy or polyandrous females can increase the chances of producing offspring with high viability. Here we examine the levels of additive genetic variance in two fitness components in the dung beetle Onthophagus taurus. We found significant sire effects on egg-to-adult viability and on son, but not daughter, survival to sexual maturity, as well as moderate coefficients of additive variance in these traits. Moreover, we do not find evidence for sexual antagonism influencing genetic variation for fitness. Our results are consistent with good genes sexual selection, and suggest that both pre- and postcopulatory mate choice, and male competition could provide indirect benefits to females.
Frank M. You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier
2016-01-01
The type 2 modified augmented design (MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic ...
The genetic variance of resistance in M3 lines of rice against leaf blight disease
International Nuclear Information System (INIS)
Mugiono
1979-01-01
Seeds of Pelita I/1 rice variety were irradiated with 20, 30, 40 and 50 krad of gamma rays from a 60 Co source. Plants of M 3 lines were inoculated with bacterial leaf blight, Xanthomonas oryzae (Uzeda and Ishiyama) Downson, using clipping method. The coefficient of genetic variability of resistance against leaf blight disease increased with increasing dose. Highly significant difference in the genetic variance of resistance were found between the treated samples and the control. Dose of 20 krad gave good probability for selection of plants resistant against leaf blight disease. (author)
Rodríguez-Clark, K M
2004-07-01
Understanding the changes in genetic variance which may occur as populations move from nature into captivity has been considered important when populations in captivity are used as models of wild ones. However, the inherent significance of these changes has not previously been appreciated in a conservation context: are the methods aimed at founding captive populations with gene diversity representative of natural populations likely also to capture representative quantitative genetic variation? Here, I investigate changes in heritability and a less traditional measure, evolvability, between nature and captivity for the large milkweed bug, Oncopeltus fasciatus, to address this question. Founders were collected from a 100-km transect across the north-eastern US, and five traits (wing colour, pronotum colour, wing length, early fecundity and later fecundity) were recorded for founders and for their offspring during two generations in captivity. Analyses reveal significant heritable variation for some life history and morphological traits in both environments, with comparable absolute levels of evolvability across all traits (0-30%). Randomization tests show that while changes in heritability and total phenotypic variance were highly variable, additive genetic variance and evolvability remained stable across the environmental transition in the three morphological traits (changing 1-2% or less), while they declined significantly in the two life-history traits (5-8%). Although it is unclear whether the declines were due to selection or gene-by-environment interactions (or both), such declines do not appear inevitable: captive populations with small numbers of founders may contain substantial amounts of the evolvability found in nature, at least for some traits.
DEFF Research Database (Denmark)
van Heerwaarden, Belinda; Willi, Yvonne; Kristensen, Torsten N
2008-01-01
for desiccation resistance in the rain forest-restricted fly Drosophila bunnanda. After one generation of single-pair mating, additive genetic variance for desiccation resistance increased to a significant level, on average higher than for the control lines. Line crosses revealed that both dominance and epistatic...
DEFF Research Database (Denmark)
Pitkänen, Timo; Mäntysaari, Esa A; Nielsen, Ulrik Sander
2013-01-01
of variance correction is developed for the same observations. As automated milking systems are becoming more popular the current evaluation model needs to be enhanced to account for the different measurement error variances of observations from automated milking systems. In this simulation study different...... models and different approaches to account for heterogeneous variance when observations have different measurement error variances were investigated. Based on the results we propose to upgrade the currently applied models and to calibrate the heterogeneous variance adjustment method to yield same genetic......The Nordic Holstein yield evaluation model describes all available milk, protein and fat test-day yields from Denmark, Finland and Sweden. In its current form all variance components are estimated from observations recorded under conventional milking systems. Also the model for heterogeneity...
Rijn, M.J. van; Schut, A.F.; Aulchenko, Y.S.; Deinum, J.; Sayed-Tabatabaei, F.A.; Yazdanpanah, M.; Isaacs, A.; Axenovich, T.I.; Zorkoltseva, I.V.; Zillikens, M.C.; Pols, H.A.; Witteman, J.C.; Oostra, B.A.; Duijn, C.M. van
2007-01-01
OBJECTIVE: To study the heritability of four blood pressure traits and the proportion of variance explained by four blood-pressure-related genes. METHODS: All participants are members of an extended pedigree from a Dutch genetically isolated population. Heritability and genetic correlations of
Variance heterogeneity in Saccharomyces cerevisiae expression data: trans-regulation and epistasis.
Nelson, Ronald M; Pettersson, Mats E; Li, Xidan; Carlborg, Örjan
2013-01-01
Here, we describe the results from the first variance heterogeneity Genome Wide Association Study (VGWAS) on yeast expression data. Using this forward genetics approach, we show that the genetic regulation of gene-expression in the budding yeast, Saccharomyces cerevisiae, includes mechanisms that can lead to variance heterogeneity in the expression between genotypes. Additionally, we performed a mean effect association study (GWAS). Comparing the mean and variance heterogeneity analyses, we find that the mean expression level is under genetic regulation from a larger absolute number of loci but that a higher proportion of the variance controlling loci were trans-regulated. Both mean and variance regulating loci cluster in regulatory hotspots that affect a large number of phenotypes; a single variance-controlling locus, mapping close to DIA2, was found to be involved in more than 10% of the significant associations. It has been suggested in the literature that variance-heterogeneity between the genotypes might be due to genetic interactions. We therefore screened the multi-locus genotype-phenotype maps for several traits where multiple associations were found, for indications of epistasis. Several examples of two and three locus genetic interactions were found to involve variance-controlling loci, with reports from the literature corroborating the functional connections between the loci. By using a new analytical approach to re-analyze a powerful existing dataset, we are thus able to both provide novel insights to the genetic mechanisms involved in the regulation of gene-expression in budding yeast and experimentally validate epistasis as an important mechanism underlying genetic variance-heterogeneity between genotypes.
Genetic selection for increased mean and reduced variance of twinning rate in Belclare ewes.
Cottle, D J; Gilmour, A R; Pabiou, T; Amer, P R; Fahey, A G
2016-04-01
It is sometimes possible to breed for more uniform individuals by selecting animals with a greater tendency to be less variable, that is, those with a smaller environmental variance. This approach has been applied to reproduction traits in various animal species. We have evaluated fecundity in the Irish Belclare sheep breed by analyses of flocks with differing average litter size (number of lambs per ewe per year, NLB) and have estimated the genetic variance in environmental variance of lambing traits using double hierarchical generalized linear models (DHGLM). The data set comprised of 9470 litter size records from 4407 ewes collected in 56 flocks. The percentage of pedigreed lambing ewes with singles, twins and triplets was 30, 54 and 14%, respectively, in 2013 and has been relatively constant for the last 15 years. The variance of NLB increases with the mean in this data; the correlation of mean and standard deviation across sires is 0.50. The breeding goal is to increase the mean NLB without unduly increasing the incidence of triplets and higher litter sizes. The heritability estimates for lambing traits were NLB, 0.09; triplet occurrence (TRI) 0.07; and twin occurrence (TWN), 0.02. The highest and lowest twinning flocks differed by 23% (75% versus 52%) in the proportion of ewes lambing twins. Fitting bivariate sire models to NLB and the residual from the NLB model using a double hierarchical generalized linear model (DHGLM) model found a strong genetic correlation (0.88 ± 0.07) between the sire effect for the magnitude of the residual (VE ) and sire effects for NLB, confirming the general observation that increased average litter size is associated with increased variability in litter size. We propose a threshold model that may help breeders with low litter size increase the percentage of twin bearers without unduly increasing the percentage of ewes bearing triplets in Belclare sheep. © 2015 Blackwell Verlag GmbH.
GSEVM v.2: MCMC software to analyse genetically structured environmental variance models
DEFF Research Database (Denmark)
Ibáñez-Escriche, N; Garcia, M; Sorensen, D
2010-01-01
This note provides a description of software that allows to fit Bayesian genetically structured variance models using Markov chain Monte Carlo (MCMC). The gsevm v.2 program was written in Fortran 90. The DOS and Unix executable programs, the user's guide, and some example files are freely available...... for research purposes at http://www.bdporc.irta.es/estudis.jsp. The main feature of the program is to compute Monte Carlo estimates of marginal posterior distributions of parameters of interest. The program is quite flexible, allowing the user to fit a variety of linear models at the level of the mean...
Bureau, Alexandre; Duchesne, Thierry
2015-12-01
Splitting extended families into their component nuclear families to apply a genetic association method designed for nuclear families is a widespread practice in familial genetic studies. Dependence among genotypes and phenotypes of nuclear families from the same extended family arises because of genetic linkage of the tested marker with a risk variant or because of familial specificity of genetic effects due to gene-environment interaction. This raises concerns about the validity of inference conducted under the assumption of independence of the nuclear families. We indeed prove theoretically that, in a conditional logistic regression analysis applicable to disease cases and their genotyped parents, the naive model-based estimator of the variance of the coefficient estimates underestimates the true variance. However, simulations with realistic effect sizes of risk variants and variation of this effect from family to family reveal that the underestimation is negligible. The simulations also show the greater efficiency of the model-based variance estimator compared to a robust empirical estimator. Our recommendation is therefore, to use the model-based estimator of variance for inference on effects of genetic variants.
Benavente, Javiera N; Seeb, Lisa W; Seeb, James E; Arismendi, Ivan; Hernández, Cristián E; Gajardo, Gonzalo; Galleguillos, Ricardo; Cádiz, Maria I; Musleh, Selim S; Gomez-Uchida, Daniel
2015-01-01
Knowledge about the genetic underpinnings of invasions-a theme addressed by invasion genetics as a discipline-is still scarce amid well documented ecological impacts of non-native species on ecosystems of Patagonia in South America. One of the most invasive species in Patagonia's freshwater systems and elsewhere is rainbow trout (Oncorhynchus mykiss). This species was introduced to Chile during the early twentieth century for stocking and promoting recreational fishing; during the late twentieth century was reintroduced for farming purposes and is now naturalized. We used population- and individual-based inference from single nucleotide polymorphisms (SNPs) to illuminate three objectives related to the establishment and naturalization of Rainbow Trout in Lake Llanquihue. This lake has been intensively used for trout farming during the last three decades. Our results emanate from samples collected from five inlet streams over two seasons, winter and spring. First, we found that significant intra- population (temporal) genetic variance was greater than inter-population (spatial) genetic variance, downplaying the importance of spatial divergence during the process of naturalization. Allele frequency differences between cohorts, consistent with variation in fish length between spring and winter collections, might explain temporal genetic differences. Second, individual-based Bayesian clustering suggested that genetic structure within Lake Llanquihue was largely driven by putative farm propagules found at one single stream during spring, but not in winter. This suggests that farm broodstock might migrate upstream to breed during spring at that particular stream. It is unclear whether interbreeding has occurred between "pure" naturalized and farm trout in this and other streams. Third, estimates of the annual number of breeders (Nb) were below 73 in half of the collections, suggestive of genetically small and recently founded populations that might experience substantial
San-Jose, Luis M; Ducret, Valérie; Ducrest, Anne-Lyse; Simon, Céline; Roulin, Alexandre
2017-10-01
The mean phenotypic effects of a discovered variant help to predict major aspects of the evolution and inheritance of a phenotype. However, differences in the phenotypic variance associated to distinct genotypes are often overlooked despite being suggestive of processes that largely influence phenotypic evolution, such as interactions between the genotypes with the environment or the genetic background. We present empirical evidence for a mutation at the melanocortin-1-receptor gene, a major vertebrate coloration gene, affecting phenotypic variance in the barn owl, Tyto alba. The white MC1R allele, which associates with whiter plumage coloration, also associates with a pronounced phenotypic and additive genetic variance for distinct color traits. Contrarily, the rufous allele, associated with a rufous coloration, relates to a lower phenotypic and additive genetic variance, suggesting that this allele may be epistatic over other color loci. Variance differences between genotypes entailed differences in the strength of phenotypic and genetic associations between color traits, suggesting that differences in variance also alter the level of integration between traits. This study highlights that addressing variance differences of genotypes in wild populations provides interesting new insights into the evolutionary mechanisms and the genetic architecture underlying the phenotype. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
Husby, A.; Visser, M.E.; Kruuk, L.E.B.
2011-01-01
The amount of genetic variance underlying a phenotypic trait and the strength of selection acting on that trait are two key parameters that determine any evolutionary response to selection. Despite substantial evidence that, in natural populations, both parameters may vary across environmental
A study of heterogeneity of environmental variance for slaughter weight in pigs
DEFF Research Database (Denmark)
Ibánez-Escriche, N; Varona, L; Sorensen, D
2008-01-01
This work presents an analysis of heterogeneity of environmental variance for slaughter weight (175 days) in pigs. This heterogeneity is associated with systematic and additive genetic effects. The model also postulates the presence of additive genetic effects affecting the mean and environmental...... variance. The study reveals the presence of genetic variation at the level of the mean and the variance, but an absence of correlation, or a small negative correlation, between both types of additive genetic effects. In addition, we show that both, the additive genetic effects on the mean and those...... on environmental variance have an important influence upon the future economic performance of selected individuals...
Directory of Open Access Journals (Sweden)
Abdulqader Jighly
2018-02-01
Full Text Available Whole genome duplication (WGD is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents (Triticum turgidum; 2n = 4x = 28, AABB subgenomes with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii; 2n = 2x = 14, DD subgenome. The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy
Nonlinear Epigenetic Variance: Review and Simulations
Kan, Kees-Jan; Ploeger, Annemie; Raijmakers, Maartje E. J.; Dolan, Conor V.; van Der Maas, Han L. J.
2010-01-01
We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addition to our review, we present simulation studies…
Directory of Open Access Journals (Sweden)
Kaifeng Ma
2018-01-01
Full Text Available Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree Prunus mume. We used amplified fragment length polymorphism (AFLP and methylation-sensitive amplified polymorphism (MSAP techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits. By performing leaf sampling, the relative total methylation level (29.80% was detected in 96 accessions of P. mume. And the relative hemi-methylation level (15.77% was higher than the relative full methylation level (14.03%. The epigenetic diversity (I∗ = 0.575, h∗ = 0.393 was higher than the genetic diversity (I = 0.484, h = 0.319. The cultivated population displayed greater epigenetic diversity than the wild populations in both southwest and southeast China. We found that epigenetic variance and genetic variance, and environmental factors performed cooperative structures, respectively. In particular, leaf length, width and area were positively correlated with relative full methylation level and total methylation level, indicating that the DNA methylation level played a role in trait variation. In total, 203 AFLP and 423 MSAP associated markers were detected and 68 of them were sequenced. Homologous analysis and functional prediction suggested that the candidate marker-linked genes were essential for leaf morphology development and metabolism, implying that these markers play critical roles in the establishment of leaf length, width, area, and ratio of length to width.
Ma, Kaifeng; Sun, Lidan; Cheng, Tangren; Pan, Huitang; Wang, Jia; Zhang, Qixiang
2018-01-01
Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree Prunus mume . We used amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP) techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits. By performing leaf sampling, the relative total methylation level (29.80%) was detected in 96 accessions of P . mume . And the relative hemi-methylation level (15.77%) was higher than the relative full methylation level (14.03%). The epigenetic diversity ( I ∗ = 0.575, h ∗ = 0.393) was higher than the genetic diversity ( I = 0.484, h = 0.319). The cultivated population displayed greater epigenetic diversity than the wild populations in both southwest and southeast China. We found that epigenetic variance and genetic variance, and environmental factors performed cooperative structures, respectively. In particular, leaf length, width and area were positively correlated with relative full methylation level and total methylation level, indicating that the DNA methylation level played a role in trait variation. In total, 203 AFLP and 423 MSAP associated markers were detected and 68 of them were sequenced. Homologous analysis and functional prediction suggested that the candidate marker-linked genes were essential for leaf morphology development and metabolism, implying that these markers play critical roles in the establishment of leaf length, width, area, and ratio of length to width.
Phenotypic variance explained by local ancestry in admixed African Americans.
Shriner, Daniel; Bentley, Amy R; Doumatey, Ayo P; Chen, Guanjie; Zhou, Jie; Adeyemo, Adebowale; Rotimi, Charles N
2015-01-01
We surveyed 26 quantitative traits and disease outcomes to understand the proportion of phenotypic variance explained by local ancestry in admixed African Americans. After inferring local ancestry as the number of African-ancestry chromosomes at hundreds of thousands of genotyped loci across all autosomes, we used a linear mixed effects model to estimate the variance explained by local ancestry in two large independent samples of unrelated African Americans. We found that local ancestry at major and polygenic effect genes can explain up to 20 and 8% of phenotypic variance, respectively. These findings provide evidence that most but not all additive genetic variance is explained by genetic markers undifferentiated by ancestry. These results also inform the proportion of health disparities due to genetic risk factors and the magnitude of error in association studies not controlling for local ancestry.
International Nuclear Information System (INIS)
Moster, Benjamin P.; Rix, Hans-Walter; Somerville, Rachel S.; Newman, Jeffrey A.
2011-01-01
Deep pencil beam surveys ( 2 ) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by 'cosmic variance'. This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift z-bar and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, z-bar , Δz, and stellar mass m * . We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at z-bar =2 and with Δz = 0.5, the relative cosmic variance of galaxies with m * >10 11 M sun is ∼38%, while it is ∼27% for GEMS and ∼12% for COSMOS. For galaxies of m * ∼ 10 10 M sun , the relative cosmic variance is ∼19% for GOODS, ∼13% for GEMS, and ∼6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at z-bar =2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic
Using SNP markers to estimate additive, dominance and imprinting genetic variance
DEFF Research Database (Denmark)
Lopes, M S; Bastiaansen, J W M; Janss, Luc
The contributions of additive, dominance and imprinting effects to the variance of number of teats (NT) were evaluated in two purebred pig populations using SNP markers. Three different random regression models were evaluated, accounting for the mean and: 1) additive effects (MA), 2) additive...... and dominance effects (MAD) and 3) additive, dominance and imprinting effects (MADI). Additive heritability estimates were 0.30, 0.28 and 0.27-0.28 in both lines using MA, MAD and MADI, respectively. Dominance heritability ranged from 0.06 to 0.08 using MAD and MADI. Imprinting heritability ranged from 0.......01 to 0.02. Dominance effects make an important contribution to the genetic variation of NT in the two lines evaluated. Imprinting effects appeared less important for NT than additive and dominance effects. The SNP random regression model presented and evaluated in this study is a feasible approach...
On the multiplicity of option prices under CEV with positive elasticity of variance
Veestraeten, D.
2017-01-01
The discounted stock price under the Constant Elasticity of Variance model is not a martingale when the elasticity of variance is positive. Two expressions for the European call price then arise, namely the price for which put-call parity holds and the price that represents the lowest cost of
On the multiplicity of option prices under CEV with positive elasticity of variance
Veestraeten, D.
2014-01-01
The discounted stock price under the Constant Elasticity of Variance (CEV) model is a strict local martingale when the elasticity of variance is positive. Two expressions for the European call price then arise, namely the risk-neutral call price and an alternative price that is linked to the unique
DEFF Research Database (Denmark)
Widyas, Nuzul; Jensen, Just; Nielsen, Vivi Hunnicke
Selection experiment was performed for weight gain in 13 generations of outbred mice. A total of 18 lines were included in the experiment. Nine lines were allotted to each of the two treatment diets (19.3 and 5.1 % protein). Within each diet three lines were selected upwards, three lines were...... selected downwards and three lines were kept as controls. Bayesian statistical methods are used to estimate the genetic variance components. Mixed model analysis is modified including mutation effect following the methods by Wray (1990). DIC was used to compare the model. Models including mutation effect...... have better fit compared to the model with only additive effect. Mutation as direct effect contributes 3.18% of the total phenotypic variance. While in the model with interactions between additive and mutation, it contributes 1.43% as direct effect and 1.36% as interaction effect of the total variance...
Variance components for body weight in Japanese quails (Coturnix japonica
Directory of Open Access Journals (Sweden)
RO Resende
2005-03-01
Full Text Available The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH and at 7 (BW07, 14 (BW14, 21 (BW21 and 28 days of age (BW28 of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model. Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch, 7, 14, 21 and 28 days old, respectively. These results indicate that heritability increased with age. On the other hand, after hatch there was a marked reduction in the maternal environment variance proportion of the phenotypic variance, whose estimates were 0.50; 0.11; 0.07; 0.07 and 0.08 for BWH, BW07, BW14, BW21 and BW28, respectively. The genetic correlation between weights at different ages was high, except for those estimates between BWH and weight at other ages. Changes in body weight of quails can be efficiently achieved by selection.
Minimum variance Monte Carlo importance sampling with parametric dependence
International Nuclear Information System (INIS)
Ragheb, M.M.H.; Halton, J.; Maynard, C.W.
1981-01-01
An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de
A population genetic interpretation of GWAS findings for human quantitative traits
Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy
2018-01-01
Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID
Luo, X N; Yang, M; Liang, X F; Jin, K; Lv, L Y; Tian, C X; Yuan, Y C; Sun, J
2015-09-25
In this study, 12 polymorphic microsatellites were inves-tigated to determine the genetic diversity and structure of 5 consecu-tive selected populations of golden mandarin fish (Siniperca scherzeri Steindachner). The total numbers of alleles, average heterozyosity, and average polymorphism information content showed that the genetic diversity of these breeding populations was decreasing. Additionally, pairwise fixation index FST values among populations and Da values in-creased from F1 generation to subsequent generations (FST values from 0.0221-0.1408; Da values from 0.0608-0.1951). Analysis of molecular variance indicated that most genetic variations arise from individuals within populations (about 92.05%), while variation among populations accounted for only 7.95%. The allele frequency of the loci SC75-220 and SC101-222 bp changed regularly in the 5 breeding generations. Their frequencies were gradually increased and showed an enrichment trend, indicating that there may be genetic correlations between these 2 loci and breeding traits. Our study indicated that microsatellite markers are effective for assessing the genetic variability in the golden mandarin fish breeding program.
The contribution of the mitochondrial genome to sex-specific fitness variance.
Smith, Shane R T; Connallon, Tim
2017-05-01
Maternal inheritance of mitochondrial DNA (mtDNA) facilitates the evolutionary accumulation of mutations with sex-biased fitness effects. Whereas maternal inheritance closely aligns mtDNA evolution with natural selection in females, it makes it indifferent to evolutionary changes that exclusively benefit males. The constrained response of mtDNA to selection in males can lead to asymmetries in the relative contributions of mitochondrial genes to female versus male fitness variation. Here, we examine the impact of genetic drift and the distribution of fitness effects (DFE) among mutations-including the correlation of mutant fitness effects between the sexes-on mitochondrial genetic variation for fitness. We show how drift, genetic correlations, and skewness of the DFE determine the relative contributions of mitochondrial genes to male versus female fitness variance. When mutant fitness effects are weakly correlated between the sexes, and the effective population size is large, mitochondrial genes should contribute much more to male than to female fitness variance. In contrast, high fitness correlations and small population sizes tend to equalize the contributions of mitochondrial genes to female versus male variance. We discuss implications of these results for the evolution of mitochondrial genome diversity and the genetic architecture of female and male fitness. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
DEFF Research Database (Denmark)
Bilde, T.; Friberg, U.; Maklakov, A.A.
2008-01-01
variance in F1 productivity, but lower genetic variance in egg-to-adult survival, which was strongly influenced by maternal and paternal effects. Conclusion Our results show that, in order to gain a relevant understanding of the genetic architecture of fitness, measures of offspring fitness should...... is the genetic interaction between parental genomes, as indicated by large amounts of non-additive genetic variance (dominance and/or epistasis) for F1 productivity. We discuss the processes that may maintain additive and non-additive genetic variance for fitness and how these relate to indirect selection...
New insights into how genetic disorders arise
International Nuclear Information System (INIS)
Unrau, P.
1992-01-01
One questionable assumption in genetic risk assessment is that all members of the population are equally at risk to the causative agent. The invalidity of this assumption can be demonstrated by considering data on the range of sensitivity to ionizing radiation of lymphoblastoid cell lines derived from various normal members of the population or from various disease groups associated with extreme radiosensitivity. Some 'normal' cell lines are as sensitive as those from the disease groups. A certain proportion of the normal population may be heterozygotic for many of the genes that lead to radiosensitivity. There are many cancer-facilitating genes in the population. These are made homozygotic by somatic mechanisms, or by breeding patterns. Mechanisms at the DNA level that lead to homozygosity change the risk within tissues and thus individuals. We need to measure heterozygosity, breeding effects, and molecular mechanisms to determine the causes of genetic and somatic risk. (L.L.)
MYC Amplification in Angiosarcoma Arising from an Arteriovenous Graft Site
Directory of Open Access Journals (Sweden)
Kristen M. Paral
2015-01-01
Full Text Available Angiosarcoma arising in association with an arteriovenous graft (AVG or fistula is a unique clinicopathologic scenario that appears to be gaining recognition in the literature. Among reported cases, none has described high-level MYC gene amplification, a genetic aberration that is increasingly unifying the various clinicopathologic subdivisions of angiosarcoma. We therefore report the MYC gene status in a case of angiosarcoma arising at an AVG site.
A class of multi-period semi-variance portfolio for petroleum exploration and development
Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei
2012-10-01
Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.
Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances
Deng, Wei Q; Asma, Senay; Paré, Guillaume
2014-01-01
Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis to identify the genetic basis of phenotypic variability and to prioritize single-nucleotide polymorphisms (SNPs) for gene–gene and gene–environment interactions. The use of Levene's test has several advantages, including robustness to departure from the normality assumption, freedom from the influence of the main effects of SNPs, and no assumption of an additive genetic model. We conducted a meta-analysis of the log-transformed body mass index of 5892 individuals and identified a variant with a highly suggestive Levene's test P-value of 4.28E-06 near the NEGR1 locus known to be associated with extreme obesity. PMID:23921533
The Genealogical Consequences of Fecundity Variance Polymorphism
Taylor, Jesse E.
2009-01-01
The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik
2014-01-01
This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP...
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. © 2015 The Author(s).
Variance components and genetic parameters for body weight and ...
African Journals Online (AJOL)
model included a direct as well as a maternal additive genetic effect, while only the direct additive genetic eff'ect had a sig- .... deviations from the log likelihood value obtained under the ... (1995).lt would therefore be fair to assume that a.
Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort.
Viñuela, Ana; Brown, Andrew A; Buil, Alfonso; Tsai, Pei-Chien; Davies, Matthew N; Bell, Jordana T; Dermitzakis, Emmanouil T; Spector, Timothy D; Small, Kerrin S
2018-02-15
Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation. © The Author(s) 2017. Published by Oxford University Press.
Comparison of variance estimators for metaanalysis of instrumental variable estimates
Schmidt, A. F.; Hingorani, A. D.; Jefferis, B. J.; White, J.; Groenwold, R. H H; Dudbridge, F.; Ben-Shlomo, Y.; Chaturvedi, N.; Engmann, J.; Hughes, A.; Humphries, S.; Hypponen, E.; Kivimaki, M.; Kuh, D.; Kumari, M.; Menon, U.; Morris, R.; Power, C.; Price, J.; Wannamethee, G.; Whincup, P.
2016-01-01
Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two
Variance components estimation for farrowing traits of three purebred pigs in Korea
Directory of Open Access Journals (Sweden)
Bryan Irvine Lopez
2017-09-01
Full Text Available Objective This study was conducted to estimate breed-specific variance components for total number born (TNB, number born alive (NBA and mortality rate from birth through weaning including stillbirths (MORT of three main swine breeds in Korea. In addition, the importance of including maternal genetic and service sire effects in estimation models was evaluated. Methods Records of farrowing traits from 6,412 Duroc, 18,020 Landrace, and 54,254 Yorkshire sows collected from January 2001 to September 2016 from different farms in Korea were used in the analysis. Animal models and the restricted maximum likelihood method were used to estimate variances in animal genetic, permanent environmental, maternal genetic, service sire and residuals. Results The heritability estimates ranged from 0.072 to 0.102, 0.090 to 0.099, and 0.109 to 0.121 for TNB; 0.087 to 0.110, 0.088 to 0.100, and 0.099 to 0.107 for NBA; and 0.027 to 0.031, 0.050 to 0.053, and 0.073 to 0.081 for MORT in the Duroc, Landrace and Yorkshire breeds, respectively. The proportion of the total variation due to permanent environmental effects, maternal genetic effects, and service sire effects ranged from 0.042 to 0.088, 0.001 to 0.031, and 0.001 to 0.021, respectively. Spearman rank correlations among models ranged from 0.98 to 0.99, demonstrating that the maternal genetic and service sire effects have small effects on the precision of the breeding value. Conclusion Models that include additive genetic and permanent environmental effects are suitable for farrowing traits in Duroc, Landrace, and Yorkshire populations in Korea. This breed-specific variance components estimates for litter traits can be utilized for pig improvement programs in Korea.
Directory of Open Access Journals (Sweden)
Maklakov AA
2008-10-01
Full Text Available Abstract Background Quantifying the amount of standing genetic variation in fitness represents an empirical challenge. Unfortunately, the shortage of detailed studies of the genetic architecture of fitness has hampered progress in several domains of evolutionary biology. One such area is the study of sexual selection. In particular, the evolution of adaptive female choice by indirect genetic benefits relies on the presence of genetic variation for fitness. Female choice by genetic benefits fall broadly into good genes (additive models and compatibility (non-additive models where the strength of selection is dictated by the genetic architecture of fitness. To characterize the genetic architecture of fitness, we employed a quantitative genetic design (the diallel cross in a population of the seed beetle Callosobruchus maculatus, which is known to exhibit post-copulatory female choice. From reciprocal crosses of inbred lines, we assayed egg production, egg-to-adult survival, and lifetime offspring production of the outbred F1 daughters (F1 productivity. Results We used the bio model to estimate six components of genetic and environmental variance in fitness. We found sizeable additive and non-additive genetic variance in F1 productivity, but lower genetic variance in egg-to-adult survival, which was strongly influenced by maternal and paternal effects. Conclusion Our results show that, in order to gain a relevant understanding of the genetic architecture of fitness, measures of offspring fitness should be inclusive and should include quantifications of offspring reproductive success. We note that our estimate of additive genetic variance in F1 productivity (CVA = 14% is sufficient to generate indirect selection on female choice. However, our results also show that the major determinant of offspring fitness is the genetic interaction between parental genomes, as indicated by large amounts of non-additive genetic variance (dominance and/or epistasis
Molecular variance of the Tunisian almond germplasm assessed by ...
African Journals Online (AJOL)
The genetic variance analysis of 82 almond (Prunus dulcis Mill.) genotypes was performed using ten genomic simple sequence repeats (SSRs). A total of 50 genotypes from Tunisia including local landraces identified while prospecting the different sites of Bizerte and Sidi Bouzid (Northern and central parts) which are the ...
Yeaman, Sam; Jarvis, Andy
2006-01-01
Genetic variation is of fundamental importance to biological evolution, yet we still know very little about how it is maintained in nature. Because many species inhabit heterogeneous environments and have pronounced local adaptations, gene flow between differently adapted populations may be a persistent source of genetic variation within populations. If this migration–selection balance is biologically important then there should be strong correlations between genetic variance within populations and the amount of heterogeneity in the environment surrounding them. Here, we use data from a long-term study of 142 populations of lodgepole pine (Pinus contorta) to compare levels of genetic variation in growth response with measures of climatic heterogeneity in the surrounding region. We find that regional heterogeneity explains at least 20% of the variation in genetic variance, suggesting that gene flow and heterogeneous selection may play an important role in maintaining the high levels of genetic variation found within natural populations. PMID:16769628
Mulder, H.A.; Hill, W.G.; Knol, E.F.
2015-01-01
There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of
Genetic variability and heritability estimates of some polygenic traits in upland cotton
International Nuclear Information System (INIS)
Baloch, M.J.
2004-01-01
Plant breeders are more interested in genetic variance rather than phenotypic variance because it is amenable to selection and bring further improvement in the character. Twenty-eight F/sub 2/ progenies were tested in two environments so as to predict genetic variances, heritability estimates and genetic gains. Mean squares for locations were significant for all the five traits suggesting that genotypes performed differently under varying environments. Genetic variances, in most cases, however, were about equal to that of phenotypic variances consequently giving high heritability estimates and significant genetic gains. The broad sense heritability estimates were; 94.2, 92.9, 33.6, 81.9 and 86.9% and genetic gains were; 30.19, 10.55,0.20,0.89 and 1.76 in seed cotton yield, bolls per plant, lint %, fibre length and fibre uniformity ratio, respectively. Substantial genetic variances and high heritability estimates implied that these characters could be improved through selection from segregating populations. (author)
Donoghue, K A; Bird-Gardiner, T; Arthur, P F; Herd, R M; Hegarty, R F
2016-04-01
Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that
Campbell, Ian M; Stewart, Jonathan R; James, Regis A; Lupski, James R; Stankiewicz, Paweł; Olofsson, Peter; Shaw, Chad A
2014-10-02
Most new mutations are observed to arise in fathers, and increasing paternal age positively correlates with the risk of new variants. Interestingly, new mutations in X-linked recessive disease show elevated familial recurrence rates. In male offspring, these mutations must be inherited from mothers. We previously developed a simulation model to consider parental mosaicism as a source of transmitted mutations. In this paper, we extend and formalize the model to provide analytical results and flexible formulas. The results implicate parent of origin and parental mosaicism as central variables in recurrence risk. Consistent with empirical data, our model predicts that more transmitted mutations arise in fathers and that this tendency increases as fathers age. Notably, the lack of expansion later in the male germline determines relatively lower variance in the proportion of mutants, which decreases with paternal age. Subsequently, observation of a transmitted mutation has less impact on the expected risk for future offspring. Conversely, for the female germline, which arrests after clonal expansion in early development, variance in the mutant proportion is higher, and observation of a transmitted mutation dramatically increases the expected risk of recurrence in another pregnancy. Parental somatic mosaicism considerably elevates risk for both parents. These findings have important implications for genetic counseling and for understanding patterns of recurrence in transmission genetics. We provide a convenient online tool and source code implementing our analytical results. These tools permit varying the underlying parameters that influence recurrence risk and could be useful for analyzing risk in diverse family structures. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Modeling the subfilter scalar variance for large eddy simulation in forced isotropic turbulence
Cheminet, Adam; Blanquart, Guillaume
2011-11-01
Static and dynamic model for the subfilter scalar variance in homogeneous isotropic turbulence are investigated using direct numerical simulations (DNS) of a lineary forced passive scalar field. First, we introduce a new scalar forcing technique conditioned only on the scalar field which allows the fluctuating scalar field to reach a statistically stationary state. Statistical properties, including 2nd and 3rd statistical moments, spectra, and probability density functions of the scalar field have been analyzed. Using this technique, we performed constant density and variable density DNS of scalar mixing in isotropic turbulence. The results are used in an a-priori study of scalar variance models. Emphasis is placed on further studying the dynamic model introduced by G. Balarac, H. Pitsch and V. Raman [Phys. Fluids 20, (2008)]. Scalar variance models based on Bedford and Yeo's expansion are accurate for small filter width but errors arise in the inertial subrange. Results suggest that a constant coefficient computed from an assumed Kolmogorov spectrum is often sufficient to predict the subfilter scalar variance.
Markov bridges, bisection and variance reduction
DEFF Research Database (Denmark)
Asmussen, Søren; Hobolth, Asger
. In this paper we firstly consider the problem of generating sample paths from a continuous-time Markov chain conditioned on the endpoints using a new algorithm based on the idea of bisection. Secondly we study the potential of the bisection algorithm for variance reduction. In particular, examples are presented......Time-continuous Markov jump processes is a popular modelling tool in disciplines ranging from computational finance and operations research to human genetics and genomics. The data is often sampled at discrete points in time, and it can be useful to simulate sample paths between the datapoints...
Strong genetic overlap between executive functions and intelligence.
Engelhardt, Laura E; Mann, Frank D; Briley, Daniel A; Church, Jessica A; Harden, K Paige; Tucker-Drob, Elliot M
2016-09-01
Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7 to 15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Study on Analysis of Variance on the indigenous wild and cultivated rice species of Manipur Valley
Medhabati, K.; Rohinikumar, M.; Rajiv Das, K.; Henary, Ch.; Dikash, Th.
2012-10-01
The analysis of variance revealed considerable variation among the cultivars and the wild species for yield and other quantitative characters in both the years of investigation. The highly significant differences among the cultivars in year wise and pooled analysis of variance for all the 12 characters reveal that there are enough genetic variabilities for all the characters studied. The existence of genetic variability is of paramount importance for starting a judicious plant breeding programme. Since introduced high yielding rice cultivars usually do not perform well. Improvement of indigenous cultivars is a clear choice for increase of rice production. The genetic variability of 37 rice germplasms in 12 agronomic characters estimated in the present study can be used in breeding programme
Age-related variation in genetic control of height growth in Douglas-fir.
Namkoong, G; Usanis, R A; Silen, R R
1972-01-01
The development of genetic variances in height growth of Douglas-fir over a 53-year period is analyzed and found to fall into three periods. In the juvenile period, variances in environmental error increase logarithmically, genetic variance within populations exists at moderate levels, and variance among populations is low but increasing. In the early reproductive period, the response to environmental sources of error variance is restricted, genetic variance within populations disappears, and populational differences strongly emerge but do not increase as expected. In the later period, environmental error again increases rapidly, but genetic variance within populations does not reappear and population differences are maintained at about the same level as established in the early reproductive period. The change between the juvenile and early reproductive periods is perhaps associated with the onset of ecological dominance and significant allocations of energy to reproduction.
Directory of Open Access Journals (Sweden)
Gebregziabher Gebreyohannes
2013-09-01
Full Text Available The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY, lactation length (LL, average milk yield per day (YD, initial milk yield (IY, peak milk yield (PY, days to peak (DP and parameters (ln(a and c of the modified incomplete gamma function (MIG in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus Boran (B and Horro (H and their crosses with different fractions of Friesian (F, Jersey (J and Simmental (S. There were 23 breed groups (B, H, and their crossbreds with F, J, and S in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001 by the considered fixed effects. High grade B×F cows (3/16B 13/16F had the highest least squares means (LSM for LY (2,490±178.9 kg, IY (10.5±0.8 kg, PY (12.7±0.9 kg, YD (7.6±0.55 kg and LL (361.4±31.2 d, while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses
Genetic and environmental factors affecting birth size variation
DEFF Research Database (Denmark)
Yokoyama, Yoshie; Jelenkovic, Aline; Hur, Yoon-Mi
2018-01-01
Background: The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birthweight, length and ponderal index (PI) across geographical-cultural regions (Europe, North America and Australia, and East Asia......) and across birth cohorts, and how gestational age modifies these effects. Methods: Data from 26 twin cohorts in 16 countries including 57 613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modelling....... Results: The variance of birthweight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased...
Major questions about derivation of variance-covariance information for nuclear data evaluations
International Nuclear Information System (INIS)
Peelle, R.W.
1982-01-01
The uncertainties in and correlations among some evaluated nuclear data are now evaluated to permit estimation of data-related uncertainties in the outputs of neutronic calculations and to focus data improvement efforts. Questions are discussed that arise in trying to obtain adequate numerical files of variance-covariance uncertainty information. These involve (1) discrepant data, (2) experimental data with incompletely reported uncertainties, (3) uncertainties in nuclear model results, (4) uncertainty data for the resonance regions and for angle and energy distributions, and (5) the role of integral data in nuclear data evaluation. The question also arises whether files of uncertainty data designed for technological applications can suffice to represent past knowledge in an evaluation that includes new data. Directions are indicated toward resolving these questions
Directory of Open Access Journals (Sweden)
Juan Carlos Zambrano
2014-03-01
Full Text Available The objective of this study was to estimate the genetic, phenotypic and environmental parameters for calving interval (CI, days open (DO, number of services per conception (NSC and conception rate (CR in Holstein and Jersey cattle in Antioquia (Colombia. Variance and covariance component estimates were obtained by an animal model that was solved using the derivative-free restricted maximum likelihood method. The means and standard deviations for CI, DO, NSC and CR were: 430.32±77.93 days, 127.15±76.96 days, 1.58±1.03 services per conception and 79.88±28.66% in Holstein cattle, and 409.33±86.48 days, 125.62±86.09 days, 1.48±0.98 services per conception and 84.08±27.23% in Jersey cattle, respectively. The heritability estimates (standard errors were: 0.088(0.037, 0.082(0.037, 0.040(0.025 and 0.030(0.026 in Holstein cattle and 0.072(0.098, 0.090(0.104, 0.093(0.097 and 0.147(0.117 in Jersey cattle, respectively. The results show that the genetic, phenotypic and permanent environmental correlations in the two evaluated breeds were favorable for CI × DO, CI × NSC and DO × NSC, but not for CI × CR, DO × CR and NSC × CR. Genetic and permanent environmental correlations were high in most cases in Holstein cattle, whereas in Jersey cattle they were moderate. In contrast, phenotypic correlations were very low in both breeds, except for CI × DO and NSC × CR, which were high. Overall, the genetic component found was very low (<8% in both evaluated breeds and this implies that their selection would take long time and that a good practical management of the herd will be essential in order to improve the reproductive performance.
Ethical and legal issues arising from complex genetic disorders. DOE final report
Energy Technology Data Exchange (ETDEWEB)
Andrews, Lori
2002-10-09
The project analyzed the challenges raised by complex genetic disorders in genetic counselling, for clinical practice, for public health, for quality assurance, and for protection against discrimination. The research found that, in some settings, solutions created in the context of single gene disorders are more difficult to apply to complex disorders. In other settings, the single gene solutions actually backfired and created additional problems when applied to complex genetic disorders. The literature of five common, complex genetic disorders--Alzheimer's, asthma, coronary heart disease, diabetes, and psychiatric illnesses--was evaluated in depth.
Variance and covariance components for liability of piglet survival during different periods
DEFF Research Database (Denmark)
Su, G; Sorensen, D; Lund, M S
2008-01-01
Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individu...
Conjunctival lymphoma arising from reactive lymphoid hyperplasia
Directory of Open Access Journals (Sweden)
Fukuhara Junichi
2012-09-01
Full Text Available Abstract Extra nodal marginal zone B-cell lymphoma (EMZL of the conjunctiva typically arises in the marginal zone of mucosa-associated lymphoid tissue. The pathogenesis of conjunctival EMZL remains unknown. We describe an unusual case of EMZL arising from reactive lymphoid hyperplasia (RLH of the conjunctiva. A 35-year-old woman had fleshy salmon-pink conjunctival tumors in both eyes, oculus uterque (OU. Specimens from conjunctival tumors in the right eye, oculus dexter (OD, revealed a collection of small lymphoid cells in the stroma. Immunohistochemically, immunoglobulin (Ig light chain restriction was not detected. In contrast, diffuse atypical lymphoid cell infiltration was noted in the left eye, oculus sinister (OS, and positive for CD20, a marker for B cells OS. The tumors were histologically diagnosed as RLH OD, and EMZL OS. PCR analysis detected IgH gene rearrangement in the joining region (JH region OU. After 11 months, a re-biopsy specimen demonstrated EMZL based on compatible pathological and genetic findings OD, arising from RLH. This case suggests that even if the diagnosis of the conjunctival lymphoproliferative lesions is histologically benign, confirmation of the B-cell clonality by checking IgH gene rearrangement should be useful to predict the incidence of malignancy.
Shared genetic variance between the features of the metabolic syndrome: Heritability studies
Povel, C.M.; Boer, J.M.A.; Feskens, E.J.M.
2011-01-01
Heritability estimates of MetS range from approximately 10%–30%. The genetic variation that is shared among MetS features can be calculated by genetic correlation coefficients. The objective of this paper is to identify MetS feature as well as MetS related features which have much genetic variation
Increased genetic variance of BMI with a higher prevalence of obesity
DEFF Research Database (Denmark)
Rokholm, Benjamin; Silventoinen, Karri; Ängquist, Lars
2011-01-01
populations. Several recent studies suggest that the genetic effects on adiposity may be stronger when combined with presumed risk factors for obesity. We tested the hypothesis that a higher prevalence of obesity and overweight and a higher BMI mean is associated with a larger genetic variation in BMI....
Downside Variance Risk Premium
Feunou, Bruno; Jahan-Parvar, Mohammad; Okou, Cedric
2015-01-01
We propose a new decomposition of the variance risk premium in terms of upside and downside variance risk premia. The difference between upside and downside variance risk premia is a measure of skewness risk premium. We establish that the downside variance risk premium is the main component of the variance risk premium, and that the skewness risk premium is a priced factor with significant prediction power for aggregate excess returns. Our empirical investigation highlights the positive and s...
Lebigre, Christophe; Arcese, Peter; Reid, Jane M
2013-07-01
Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased
Sex Estimation From Modern American Humeri and Femora, Accounting for Sample Variance Structure
DEFF Research Database (Denmark)
Boldsen, J. L.; Milner, G. R.; Boldsen, S. K.
2015-01-01
several decades. Results: For measurements individually and collectively, the probabilities of being one sex or the other were generated for samples with an equal distribution of males and females, taking into account the variance structure of the original measurements. The combination providing the best......Objectives: A new procedure for skeletal sex estimation based on humeral and femoral dimensions is presented, based on skeletons from the United States. The approach specifically addresses the problem that arises from a lack of variance homogeneity between the sexes, taking into account prior...... information about the sample's sex ratio, if known. Material and methods: Three measurements useful for estimating the sex of adult skeletons, the humeral and femoral head diameters and the humeral epicondylar breadth, were collected from 258 Americans born between 1893 and 1980 who died within the past...
Directory of Open Access Journals (Sweden)
Mohammad Ali Barati
2016-04-01
Full Text Available Multi-period models of portfolio selection have been developed in the literature with respect to certain assumptions. In this study, for the first time, the portfolio selection problem has been modeled based on mean-semi variance with transaction cost and minimum transaction lots considering functional constraints and fuzzy parameters. Functional constraints such as transaction cost and minimum transaction lots were included. In addition, the returns on assets parameters were considered as trapezoidal fuzzy numbers. An efficient genetic algorithm (GA was designed, results were analyzed using numerical instances and sensitivity analysis were executed. In the numerical study, the problem was solved based on the presence or absence of each mode of constraints including transaction costs and minimum transaction lots. In addition, with the use of sensitivity analysis, the results of the model were presented with the variations of minimum expected rate of programming periods.
Bohlken, Marc M; Brouwer, Rachel M; Mandl, René C W; Kahn, René S; Hulshoff Pol, Hilleke E
2016-09-01
Alterations in intellectual ability and brain structure are important genetic markers for schizophrenia liability. How variations in these phenotypes interact with variance in schizophrenia liability due to genetic or environmental factors is an area of active investigation. Studying these genetic markers using a multivariate twin modeling approach can provide novel leads for (genetic) pathways of schizophrenia development. In a sample of 70 twins discordant for schizophrenia and 130 healthy control twins, structural equation modeling was applied to quantify unique contributions of genetic and environmental factors on human brain structure (cortical thickness, cortical surface and global white matter fractional anisotropy [FA]), intellectual ability and schizophrenia liability. In total, up to 28.1% of the genetic variance (22.8% of total variance) in schizophrenia liability was shared with intelligence quotient (IQ), global-FA, cortical thickness, and cortical surface. The strongest contributor was IQ, sharing on average 16.4% of the genetic variance in schizophrenia liability, followed by cortical thickness (6.3%), global-FA (4.7%) and cortical surface (0.5%). Furthermore, we found that up to 57.4% of the variation due to environmental factors (4.6% of total variance) in schizophrenia was shared with IQ (34.2%) and cortical surface (13.4%). Intellectual ability, FA and cortical thickness show significant and independent shared genetic variance with schizophrenia liability. This suggests that measuring brain-imaging phenotypes helps explain genetic variance in schizophrenia liability that is not captured by variation in IQ. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.
R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization.
Dazard, Jean-Eudes; Xu, Hua; Rao, J Sunil
2011-01-01
We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets ( p ≫ n paradigm), such as in 'omics'-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real 'omics' test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR ('Mean-Variance Regularization'), downloadable from the CRAN.
Directory of Open Access Journals (Sweden)
Ellen Grippi Lira
Full Text Available ABSTRACT: Sunflower (Helianthus annuus L. is an annual crop that stands out for its production of high quality oil and for an efficient selection, being necessary to estimate the components of genetic and phenotypic variance. This study aimed to estimate genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah, evaluating the characters grain yield (YIELD, days to start flowering (DFL based on flowering date in R5, chapter length (CL, weight of a thousand achenes (WTA, plant height (H and oil content (OilC of 16 sunflower genotypes. The experiment was conducted at Embrapa Cerrados, Planaltina, DF, situated at 15º 35’ 30”S latitude, 47º 42’ 30”W longitude and 1.007m above sea level, in soil classified as dystroferric Oxisol. The experimental design used was a complete randomized block with four replicates. The nature for the effects of genotypes and blocks was fixed. Except for the character chapter length, genetic variance was the main component of the phenotypic variance among the genotypes, indicating high genetic variability and experimental efficiency with proper environmental control. In absolute terms, the genetic correlations were superior to phenotypic and environmental. The high values reported for heritability and selective accuracy indicated efficiency of phenotypic selection. Results showed high genetic variability among genotypes, which may contribute to the genetic improvement of sunflower.
Directory of Open Access Journals (Sweden)
Peter M Visscher
2014-04-01
Full Text Available We have recently developed analysis methods (GREML to estimate the genetic variance of a complex trait/disease and the genetic correlation between two complex traits/diseases using genome-wide single nucleotide polymorphism (SNP data in unrelated individuals. Here we use analytical derivations and simulations to quantify the sampling variance of the estimate of the proportion of phenotypic variance captured by all SNPs for quantitative traits and case-control studies. We also derive the approximate sampling variance of the estimate of a genetic correlation in a bivariate analysis, when two complex traits are either measured on the same or different individuals. We show that the sampling variance is inversely proportional to the number of pairwise contrasts in the analysis and to the variance in SNP-derived genetic relationships. For bivariate analysis, the sampling variance of the genetic correlation additionally depends on the harmonic mean of the proportion of variance explained by the SNPs for the two traits and the genetic correlation between the traits, and depends on the phenotypic correlation when the traits are measured on the same individuals. We provide an online tool for calculating the power of detecting genetic (covariation using genome-wide SNP data. The new theory and online tool will be helpful to plan experimental designs to estimate the missing heritability that has not yet been fully revealed through genome-wide association studies, and to estimate the genetic overlap between complex traits (diseases in particular when the traits (diseases are not measured on the same samples.
Genetic variability, heritability and genetic advance of quantitative ...
African Journals Online (AJOL)
ONOS
2010-05-10
May 10, 2010 ... coefficient of variation; h2, heritability; GA, genetic advance;. EMS, ethyl methane ... The analysis of variance (ANOVA) revealed the significance degree among the ... fullest extent. The estimates of range, phenotypic and.
Genetic Characterization of Dog Personality Traits.
Ilska, Joanna; Haskell, Marie J; Blott, Sarah C; Sánchez-Molano, Enrique; Polgar, Zita; Lofgren, Sarah E; Clements, Dylan N; Wiener, Pamela
2017-06-01
The genetic architecture of behavioral traits in dogs is of great interest to owners, breeders, and professionals involved in animal welfare, as well as to scientists studying the genetics of animal (including human) behavior. The genetic component of dog behavior is supported by between-breed differences and some evidence of within-breed variation. However, it is a challenge to gather sufficiently large datasets to dissect the genetic basis of complex traits such as behavior, which are both time-consuming and logistically difficult to measure, and known to be influenced by nongenetic factors. In this study, we exploited the knowledge that owners have of their dogs to generate a large dataset of personality traits in Labrador Retrievers. While accounting for key environmental factors, we demonstrate that genetic variance can be detected for dog personality traits assessed using questionnaire data. We identified substantial genetic variance for several traits, including fetching tendency and fear of loud noises, while other traits revealed negligibly small heritabilities. Genetic correlations were also estimated between traits; however, due to fairly large SEs, only a handful of trait pairs yielded statistically significant estimates. Genomic analyses indicated that these traits are mainly polygenic, such that individual genomic regions have small effects, and suggested chromosomal associations for six of the traits. The polygenic nature of these traits is consistent with previous behavioral genetics studies in other species, for example in mouse, and confirms that large datasets are required to quantify the genetic variance and to identify the individual genes that influence behavioral traits. Copyright © 2017 by the Genetics Society of America.
Education reduces the effects of genetic susceptibilities to poor physical health.
Johnson, Wendy; Kyvik, Kirsten Ohm; Mortensen, Erik L; Skytthe, Axel; Batty, G David; Deary, Ian J
2010-04-01
Greater education is associated with better physical health. This has been of great concern to public health officials. Most demonstrations show that education influences mean levels of health. Little is known about the influence of education on variance in health status, or about how this influence may impact the underlying genetic and environmental sources of health problems. This study explored these influences. In a 2002 postal questionnaire, 21 522 members of same-sex pairs in the Danish Twin Registry born between 1931 and 1982 reported physical health in the 12-item Short Form Health Survey. We used quantitative genetic models to examine how genetic and environmental variance in physical health differed with level of education, adjusting for birth-year effects. and Conclusions As expected, greater education was associated with better physical health. Greater education was also associated with smaller variance in health status. In both sexes, 2 standard deviations (SDs) above mean educational level, variance in physical health was only about half that among those 2 SDs below. This was because fewer highly educated people reported poor health. There was less total variance in health primarily because there was less genetic variance. Education apparently reduced expression of genetic susceptibilities to poor health. The patterns of genetic and environmental correlations suggested that this might take place because more educated people manage their environments to protect their health. If so, fostering the personal charactieristics associated with educational attainment could be important in reducing the education-health gradient.
Estimation of measurement variances
International Nuclear Information System (INIS)
Anon.
1981-01-01
In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time
Developments in statistical analysis in quantitative genetics
DEFF Research Database (Denmark)
Sorensen, Daniel
2009-01-01
of genetic means and variances, models for the analysis of categorical and count data, the statistical genetics of a model postulating that environmental variance is partly under genetic control, and a short discussion of models that incorporate massive genetic marker information. We provide an overview......A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap...... and by Markov chain Monte Carlo (McMC). In this overview a number of specific areas are chosen to illustrate the enormous flexibility that McMC has provided for fitting models and exploring features of data that were previously inaccessible. The selected areas are inferences of the trajectories over time...
Tufto, Jarle
2015-08-01
Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.
Sex-specific genetic effects in physical activity: results from a quantitative genetic analysis.
Diego, Vincent P; de Chaves, Raquel Nichele; Blangero, John; de Souza, Michele Caroline; Santos, Daniel; Gomes, Thayse Natacha; dos Santos, Fernanda Karina; Garganta, Rui; Katzmarzyk, Peter T; Maia, José A R
2015-08-01
The objective of this study is to present a model to estimate sex-specific genetic effects on physical activity (PA) levels and sedentary behaviour (SB) using three generation families. The sample consisted of 100 families covering three generations from Portugal. PA and SB were assessed via the International Physical Activity Questionnaire short form (IPAQ-SF). Sex-specific effects were assessed by genotype-by-sex interaction (GSI) models and sex-specific heritabilities. GSI effects and heterogeneity were tested in the residual environmental variance. SPSS 17 and SOLAR v. 4.1 were used in all computations. The genetic component for PA and SB domains varied from low to moderate (11% to 46%), when analyzing both genders combined. We found GSI effects for vigorous PA (p = 0.02) and time spent watching television (WT) (p < 0.001) that showed significantly higher additive genetic variance estimates in males. The heterogeneity in the residual environmental variance was significant for moderate PA (p = 0.02), vigorous PA (p = 0.006) and total PA (p = 0.001). Sex-specific heritability estimates were significantly higher in males only for WT, with a male-to-female difference in heritability of 42.5 (95% confidence interval: 6.4, 70.4). Low to moderate genetic effects on PA and SB traits were found. Results from the GSI model show that there are sex-specific effects in two phenotypes, VPA and WT with a stronger genetic influence in males.
Directory of Open Access Journals (Sweden)
Struchalin Maksim V
2012-01-01
Full Text Available Abstract Background Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties. We and Pare with colleagues (2010 developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants. Results In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests. Conclusions Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.
Who’s Afraid of Math? Two Sources of Genetic Variance for Mathematical Anxiety
Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A.; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W.; Lyons, Ian M.; Petrill, Stephen A.
2015-01-01
Background Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem-solving and achievement. The present study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Methods Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Results Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and non-familial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. Conclusions The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics, and may extend to other areas of academic achievement. PMID:24611799
Motsepa, Tanki; Aziz, Taha; Fatima, Aeeman; Khalique, Chaudry Masood
2018-03-01
The optimal investment-consumption problem under the constant elasticity of variance (CEV) model is investigated from the perspective of Lie group analysis. The Lie symmetry group of the evolution partial differential equation describing the CEV model is derived. The Lie point symmetries are then used to obtain an exact solution of the governing model satisfying a standard terminal condition. Finally, we construct conservation laws of the underlying equation using the general theorem on conservation laws.
Survival of mutations arising during invasions.
Miller, Judith R
2010-03-01
When a neutral mutation arises in an invading population, it quickly either dies out or 'surfs', i.e. it comes to occupy almost all the habitat available at its time of origin. Beneficial mutations can also surf, as can deleterious mutations over finite time spans. We develop descriptive statistical models that quantify the relationship between the probability that a mutation will surf and demographic parameters for a cellular automaton model of surfing. We also provide a simple analytic model that performs well at predicting the probability of surfing for neutral and beneficial mutations in one dimension. The results suggest that factors - possibly including even abiotic factors - that promote invasion success may also increase the probability of surfing and associated adaptive genetic change, conditioned on such success.
Who is afraid of math? Two sources of genetic variance for mathematical anxiety.
Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W; Lyons, Ian M; Petrill, Stephen A
2014-09-01
Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem solving and achievement. This study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and nonfamilial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics and may extend to other areas of academic achievement. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.
Genetic progress in multistage dairy cattle breeding schemes using genetic markers.
Schrooten, C; Bovenhuis, H; van Arendonk, J A M; Bijma, P
2005-04-01
The aim of this paper was to explore general characteristics of multistage breeding schemes and to evaluate multistage dairy cattle breeding schemes that use information on quantitative trait loci (QTL). Evaluation was either for additional genetic response or for reduction in number of progeny-tested bulls while maintaining the same response. The reduction in response in multistage breeding schemes relative to comparable single-stage breeding schemes (i.e., with the same overall selection intensity and the same amount of information in the final stage of selection) depended on the overall selection intensity, the selection intensity in the various stages of the breeding scheme, and the ratio of the accuracies of selection in the various stages of the breeding scheme. When overall selection intensity was constant, reduction in response increased with increasing selection intensity in the first stage. The decrease in response was highest in schemes with lower overall selection intensity. Reduction in response was limited in schemes with low to average emphasis on first-stage selection, especially if the accuracy of selection in the first stage was relatively high compared with the accuracy in the final stage. Closed nucleus breeding schemes in dairy cattle that use information on QTL were evaluated by deterministic simulation. In the base scheme, the selection index consisted of pedigree information and own performance (dams), or pedigree information and performance of 100 daughters (sires). In alternative breeding schemes, information on a QTL was accounted for by simulating an additional index trait. The fraction of the variance explained by the QTL determined the correlation between the additional index trait and the breeding goal trait. Response in progeny test schemes relative to a base breeding scheme without QTL information ranged from +4.5% (QTL explaining 5% of the additive genetic variance) to +21.2% (QTL explaining 50% of the additive genetic variance). A
Is the Experience of Thermal Pain Genetics Dependent?
Directory of Open Access Journals (Sweden)
Emilia Horjales-Araujo
2015-01-01
Full Text Available It is suggested that genetic variations explain a significant portion of the variability in pain perception; therefore, increased understanding of pain-related genetic influences may identify new targets for therapies and treatments. The relative contribution of the different genes to the variance in clinical and experimental pain responses remains unknown. It is suggested that the genetic contributions to pain perception vary across pain modalities. For example, it has been suggested that more than 60% of the variance in cold pressor responses can be explained by genetic factors; in comparison, only 26% of the variance in heat pain responses is explained by these variations. Thus, the selection of pain model might markedly influence the magnitude of the association between the pain phenotype and genetic variability. Thermal pain sensation is complex with multiple molecular and cellular mechanisms operating alone and in combination within the peripheral and central nervous system. It is thus highly probable that the thermal pain experience is affected by genetic variants in one or more of the pathways involved in the thermal pain signaling. This review aims to present and discuss some of the genetic variations that have previously been associated with different experimental thermal pain models.
MCNP variance reduction overview
International Nuclear Information System (INIS)
Hendricks, J.S.; Booth, T.E.
1985-01-01
The MCNP code is rich in variance reduction features. Standard variance reduction methods found in most Monte Carlo codes are available as well as a number of methods unique to MCNP. We discuss the variance reduction features presently in MCNP as well as new ones under study for possible inclusion in future versions of the code
Familial resemblance of borderline personality disorder features: genetic or cultural transmission?
Directory of Open Access Journals (Sweden)
Marijn A Distel
Full Text Available Borderline personality disorder is a severe personality disorder for which genetic research has been limited to family studies and classical twin studies. These studies indicate that genetic effects explain 35 to 45% of the variance in borderline personality disorder and borderline personality features. However, effects of non-additive (dominance genetic factors, non-random mating and cultural transmission have generally not been explored. In the present study an extended twin-family design was applied to self-report data of twins (N = 5,017 and their siblings (N = 1,266, parents (N = 3,064 and spouses (N = 939 from 4,015 families, to estimate the effects of additive and non-additive genetic and environmental factors, cultural transmission and non-random mating on individual differences in borderline personality features. Results showed that resemblance among biological relatives could completely be attributed to genetic effects. Variation in borderline personality features was explained by additive genetic (21%; 95% CI 17-26% and dominant genetic (24%; 95% CI 17-31% factors. Environmental influences (55%; 95% CI 51-60% explained the remaining variance. Significant resemblance between spouses was observed, which was best explained by phenotypic assortative mating, but it had only a small effect on the genetic variance (1% of the total variance. There was no effect of cultural transmission from parents to offspring.
Spectral Ambiguity of Allan Variance
Greenhall, C. A.
1996-01-01
We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.
Directory of Open Access Journals (Sweden)
Roberto Carvalheiro
2002-07-01
Full Text Available O objetivo deste estudo foi investigar, por meio de dados simulados, o efeito da heterogeneidade de variância residual entre grupos de contemporâneos (GC sobre as avaliações genéticas de bovinos de corte, e comparar o uso de uma avaliação genética ponderada (R¹Isigmae² em relação à avaliação que pressupõe homogeneidade de variância (R=Isigmae². A característica estudada foi ganho de peso pós-desmame corrigido para 345 dias, sendo esta simulada com variância fenotípica de 300 kg² e herdabilidade igual a 0,4. A estrutura de um conjunto real de dados foi utilizada para fornecer os GC e os pais referentes às observações de cada animal. Cinco níveis de heterogeneidade de variância residual foram considerados de forma que os componentes de variância fossem, na média, iguais aos da situação de homogeneidade de variância. Na medida em que níveis mais acentuados de heterogeneidade de variância residual foram considerados, os animais foram selecionados dos GC com maior variabilidade, especialmente com pressão de seleção intensa. Em relação à consistência de predição, os produtos e as vacas tiveram seus valores genéticos preditos mais afetados pela heterogeneidade de variância residual do que os touros. O fator de ponderação utilizado reduziu, mas não eliminou o efeito da heterogeneidade de variância. As avaliações genéticas ponderadas apresentaram resultados iguais ou superiores àqueles obtidos pelas avaliações que assumiram homogeneidade de variância. Mesmo quando não necessário, o uso de avaliações ponderadas produziu resultados não inferiores às avaliações que assumiram homogeneidade de variância.The objective of this study was to investigate, via simulated data, the effect of heterogeneity of residual variance among contemporary groups (CG on genetic evaluation of beef cattle, and to compare a weighted genetic evaluation procedure (R¹Isigmae² with one that assumes homogeneity of
Vasilopoulos, Terrie; Franz, Carol E; Panizzon, Matthew S; Xian, Hong; Grant, Michael D; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C; Kremen, William S
2012-03-01
To examine how genes and environments contribute to relationships among Trail Making Test (TMT) conditions and the extent to which these conditions have unique genetic and environmental influences. Participants included 1,237 middle-aged male twins from the Vietnam Era Twin Study of Aging. The Delis-Kaplan Executive Function System TMT included visual searching, number and letter sequencing, and set-shifting components. Phenotypic correlations among TMT conditions ranged from 0.29 to 0.60, and genes accounted for the majority (58-84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. A common genetic factor, most likely representing a combination of speed and sequencing, accounted for most of the correlation among TMT 1-4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in nonpatient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes.
DEFF Research Database (Denmark)
Bekkevold, Dorte
2006-01-01
Estimates of Atlantic cod Gadus morhua reproductive success, determined using experimental spawning groups and genetic paternity assignment of offspring, showed that within-group variance in male size correlated positively with the degree of male mating skew, predicting a decrease in male reprodu...
Variance-based selection may explain general mating patterns in social insects.
Rueppell, Olav; Johnson, Nels; Rychtár, Jan
2008-06-23
Female mating frequency is one of the key parameters of social insect evolution. Several hypotheses have been suggested to explain multiple mating and considerable empirical research has led to conflicting results. Building on several earlier analyses, we present a simple general model that links the number of queen matings to variance in colony performance and this variance to average colony fitness. The model predicts selection for multiple mating if the average colony succeeds in a focal task, and selection for single mating if the average colony fails, irrespective of the proximate mechanism that links genetic diversity to colony fitness. Empirical support comes from interspecific comparisons, e.g. between the bee genera Apis and Bombus, and from data on several ant species, but more comprehensive empirical tests are needed.
Ivy, T M
2007-03-01
Genetic benefits can enhance the fitness of polyandrous females through the high intrinsic genetic quality of females' mates or through the interaction between female and male genes. I used a full diallel cross, a quantitative genetics design that involves all possible crosses among a set of genetically homogeneous lines, to determine the mechanism through which polyandrous female decorated crickets (Gryllodes sigillatus) obtain genetic benefits. I measured several traits related to fitness and partitioned the phenotypic variance into components representing the contribution of additive genetic variance ('good genes'), nonadditive genetic variance (genetic compatibility), as well as maternal and paternal effects. The results reveal a significant variance attributable to both nonadditive and additive sources in the measured traits, and their influence depended on which trait was considered. The lack of congruence in sources of phenotypic variance among these fitness-related traits suggests that the evolution and maintenance of polyandry are unlikely to have resulted from one selective influence, but rather are the result of the collective effects of a number of factors.
DEFF Research Database (Denmark)
Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage
2012-01-01
of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects...
Genetic influences on alcohol-related hangover.
Slutske, Wendy S; Piasecki, Thomas M; Nathanson, Lisa; Statham, Dixie J; Martin, Nicholas G
2014-12-01
To quantify the relative contributions of genetic and environmental factors to alcohol hangover. Biometric models were used to partition the variance in hangover phenotypes. A community-based sample of Australian twins. Members of the Australian Twin Registry, Cohort II who reported consuming alcohol in the past year when surveyed in 2004-07 (n = 4496). Telephone interviews assessed participants' frequency of drinking to intoxication and frequency of hangover the day after drinking. Analyses examined three phenotypes: hangover frequency, hangover susceptibility (i.e. residual variance in hangover frequency after accounting for intoxication frequency) and hangover resistance (a dichotomous variable defined as having been intoxicated at least once in the past year with no reported hangovers). Genetic factors accounted for 45% [95% confidence interval (CI) = 37-53%] and 40% (95% CI = 33-48%) of the variation in hangover frequency in men and women, respectively. Most of the genetic variation in hangover frequency overlapped with genetic contributions to intoxication frequency. Genetic influences accounted for 24% (95% CI = 14-35%) and 16% (95% CI = 8-25%) of the residual hangover susceptibility variance in men and women, respectively. Forty-three per cent (95% CI = 22-63%) of the variation in hangover resistance was explained by genetic influences, with no evidence for significant sex differences. There was no evidence for shared environmental influences for any of the hangover phenotypes. Individual differences in the propensity to experience a hangover and of being resistant to hangover at a given level of alcohol use are genetically influenced. © 2014 Society for the Study of Addiction.
Human genetic issues from scientific and Islamic perspectives | Alwi ...
African Journals Online (AJOL)
This paper aims at revealing the Human Genome Project (HGP) and human genetic issues arising from science and Islamic perspectives such as Darwin's evolutionary theory, human cloning and eugenics. Finally, issues arising from the applications of human genetic technology need to be addressed to the best possible ...
On the noise variance of a digital mammography system
International Nuclear Information System (INIS)
Burgess, Arthur
2004-01-01
A recent paper by Cooper et al. [Med. Phys. 30, 2614-2621 (2003)] contains some apparently anomalous results concerning the relationship between pixel variance and x-ray exposure for a digital mammography system. They found an unexpected peak in a display domain pixel variance plot as a function of 1/mAs (their Fig. 5) with a decrease in the range corresponding to high display data values, corresponding to low x-ray exposures. As they pointed out, if the detector response is linear in exposure and the transformation from raw to display data scales is logarithmic, then pixel variance should be a monotonically increasing function in the figure. They concluded that the total system transfer curve, between input exposure and display image data values, is not logarithmic over the full exposure range. They separated data analysis into two regions and plotted the logarithm of display image pixel variance as a function of the logarithm of the mAs used to produce the phantom images. They found a slope of minus one for high mAs values and concluded that the transfer function is logarithmic in this region. They found a slope of 0.6 for the low mAs region and concluded that the transfer curve was neither linear nor logarithmic for low exposure values. It is known that the digital mammography system investigated by Cooper et al. has a linear relationship between exposure and raw data values [Vedantham et al., Med. Phys. 27, 558-567 (2000)]. The purpose of this paper is to show that the variance effect found by Cooper et al. (their Fig. 5) arises because the transformation from the raw data scale (14 bits) to the display scale (12 bits), for the digital mammography system they investigated, is not logarithmic for raw data values less than about 300 (display data values greater than about 3300). At low raw data values the transformation is linear and prevents over-ranging of the display data scale. Parametric models for the two transformations will be presented. Results of pixel
Journal of Genetics | Indian Academy of Sciences
Indian Academy of Sciences (India)
polygenes; additive genetic variance; epistasis; dominance; selection ... seem to run out of genetic variability even after many generations of directional selection. ... Conspicuous examples are the small number of loci that changed teosinte to ...
Genetic parameters in a Swine Population
Directory of Open Access Journals (Sweden)
Dana Popa
2010-05-01
Full Text Available The estimation of the variance-covariance components is a very important step in animal breeding because these components are necessary for: estimation of the genetic parameters, prediction of the breeding value and design of animal breeding programs. The estimation of genetic parameters is the first step in the development of a swine breeding program, using artificial insemination. Various procedures exist for estimation of heritability. There are three major procedures used for estimating heritability: analysis of variance (ANOVA, parents-offspring regression and restricted maximum likelihood (REML. By using ANOVA methodology or regression method it is possible to obtain aberrant values of genetic parameters (negative or over unit value of heritability coefficient, for example which can not be interpreting because is out of biological limits.
Genetic variance of Trichomonas vaginalis isolates by Southern hybridization
Ryu, Jae-Sook; Min, Duk-Young; Shin, Myeong-Heon; Cho, Youl-Hee
1998-01-01
In the present study, genomic DNAs were purified from Korean isolates (KT8, KT6, KT-Kim and KT-Lee) and foreign strains (CDC85, IR78 and NYH 286) of Trichomonas vaginalis, and hybridized with a probe based on the repetitive sequence cloned from T. vaginalis to observe the genetic differences. By Southern hybridization, all isolates of T. vaginalis except the NYH286 strain had 11 bands. Therefore all isolates examined were distinguishable into 3 groups according to their banding patterns; i) K...
Analysis of genetic code ambiguity arising from nematode-specific misacylated tRNAs.
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Kiyofumi Hamashima
Full Text Available The faithful translation of the genetic code requires the highly accurate aminoacylation of transfer RNAs (tRNAs. However, it has been shown that nematode-specific V-arm-containing tRNAs (nev-tRNAs are misacylated with leucine in vitro in a manner that transgresses the genetic code. nev-tRNA(Gly (CCC and nev-tRNA(Ile (UAU, which are the major nev-tRNA isotypes, could theoretically decode the glycine (GGG codon and isoleucine (AUA codon as leucine, causing GGG and AUA codon ambiguity in nematode cells. To test this hypothesis, we investigated the functionality of nev-tRNAs and their impact on the proteome of Caenorhabditis elegans. Analysis of the nucleotide sequences in the 3' end regions of the nev-tRNAs showed that they had matured correctly, with the addition of CCA, which is a crucial posttranscriptional modification required for tRNA aminoacylation. The nuclear export of nev-tRNAs was confirmed with an analysis of their subcellular localization. These results show that nev-tRNAs are processed to their mature forms like common tRNAs and are available for translation. However, a whole-cell proteome analysis found no detectable level of nev-tRNA-induced mistranslation in C. elegans cells, suggesting that the genetic code is not ambiguous, at least under normal growth conditions. Our findings indicate that the translational fidelity of the nematode genetic code is strictly maintained, contrary to our expectations, although deviant tRNAs with misacylation properties are highly conserved in the nematode genome.
Genetic Parameters of Common Wheat in Nepal
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Bal Krishna Joshi
2015-12-01
Full Text Available Knowledge on variation within traits and their genetics are prerequisites in crop improvement program. Thus, in present paper we aimed to estimate genetic and environmental indices of common wheat genotypes. For the purpose, eight quantitative traits were measured from 30 wheat genotypes, which were in randomized complete block design with 3 replicates. Components of variance and covariance were estimated along with heritability, genetic gain, realized heritability, coheritability and correlated response. Differences between phenotypic and genotypic variances in heading days, maturity days and plant height were not large. Grain yield and plant height showed the highest phenotypic (18.189% and genotypic (12.06% coefficient of variances, respectively. Phenotypic covariance was higher than genotypic and environmental covariance in most of the traits. The highest heritability and realized heritability were of heading days followed by maturity days. Genetic gain for plant height was the highest. Co-heritability of 1000-grain weight with tillers number was the highest. The highest correlated response was expressed by grain yield with tillers number. This study indicates the possibility of improving wheat genotypes through selection utilizing existing variation in these traits.
Education modifies genetic and environmental influences on BMI
DEFF Research Database (Denmark)
Johnson, Wendy; Kyvik, Kirsten Ohm; Skytthe, Axel
2011-01-01
environmental correlations between education and BMI differed by level of education, analyzing women and men separately. Correlations between education and BMI were -.13 in women, -.15 in men. High BMI's were less frequent among well-educated participants, generating less variance. In women, this was due...... to restriction of all forms of variance, overall by a factor of about 2. In men, genetic variance did not vary with education, but results for shared and nonshared environmental variance were similar to those for women. The contributions of the shared environment to the correlations between education and BMI......Obesity is more common among the less educated, suggesting education-related environmental triggers. Such triggers may act differently dependent on genetic and environmental predisposition to obesity. In a Danish Twin Registry survey, 21,522 twins of same-sex pairs provided zygosity, height, weight...
Genetic and environmental transmission of body mass index fluctuation.
Bergin, Jocilyn E; Neale, Michael C; Eaves, Lindon J; Martin, Nicholas G; Heath, Andrew C; Maes, Hermine H
2012-11-01
This study sought to determine the relationship between body mass index (BMI) fluctuation and cardiovascular disease phenotypes, diabetes, and depression and the role of genetic and environmental factors in individual differences in BMI fluctuation using the extended twin-family model (ETFM). This study included 14,763 twins and their relatives. Health and Lifestyle Questionnaires were obtained from 28,492 individuals from the Virginia 30,000 dataset including twins, parents, siblings, spouses, and children of twins. Self-report cardiovascular disease, diabetes, and depression data were available. From self-reported height and weight, BMI fluctuation was calculated as the difference between highest and lowest BMI after age 18, for individuals 18-80 years. Logistic regression analyses were used to determine the relationship between BMI fluctuation and disease status. The ETFM was used to estimate the significance and contribution of genetic and environmental factors, cultural transmission, and assortative mating components to BMI fluctuation, while controlling for age. We tested sex differences in additive and dominant genetic effects, parental, non-parental, twin, and unique environmental effects. BMI fluctuation was highly associated with disease status, independent of BMI. Genetic effects accounted for ~34 % of variance in BMI fluctuation in males and ~43 % of variance in females. The majority of the variance was accounted for by environmental factors, about a third of which were shared among twins. Assortative mating, and cultural transmission accounted for only a small proportion of variance in this phenotype. Since there are substantial health risks associated with BMI fluctuation and environmental components of BMI fluctuation account for over 60 % of variance in males and over 50 % of variance in females, environmental risk factors may be appropriate targets to reduce BMI fluctuation.
Parameter uncertainty effects on variance-based sensitivity analysis
International Nuclear Information System (INIS)
Yu, W.; Harris, T.J.
2009-01-01
In the past several years there has been considerable commercial and academic interest in methods for variance-based sensitivity analysis. The industrial focus is motivated by the importance of attributing variance contributions to input factors. A more complete understanding of these relationships enables companies to achieve goals related to quality, safety and asset utilization. In a number of applications, it is possible to distinguish between two types of input variables-regressive variables and model parameters. Regressive variables are those that can be influenced by process design or by a control strategy. With model parameters, there are typically no opportunities to directly influence their variability. In this paper, we propose a new method to perform sensitivity analysis through a partitioning of the input variables into these two groupings: regressive variables and model parameters. A sequential analysis is proposed, where first an sensitivity analysis is performed with respect to the regressive variables. In the second step, the uncertainty effects arising from the model parameters are included. This strategy can be quite useful in understanding process variability and in developing strategies to reduce overall variability. When this method is used for nonlinear models which are linear in the parameters, analytical solutions can be utilized. In the more general case of models that are nonlinear in both the regressive variables and the parameters, either first order approximations can be used, or numerically intensive methods must be used
Variance decomposition-based sensitivity analysis via neural networks
International Nuclear Information System (INIS)
Marseguerra, Marzio; Masini, Riccardo; Zio, Enrico; Cojazzi, Giacomo
2003-01-01
This paper illustrates a method for efficiently performing multiparametric sensitivity analyses of the reliability model of a given system. These analyses are of great importance for the identification of critical components in highly hazardous plants, such as the nuclear or chemical ones, thus providing significant insights for their risk-based design and management. The technique used to quantify the importance of a component parameter with respect to the system model is based on a classical decomposition of the variance. When the model of the system is realistically complicated (e.g. by aging, stand-by, maintenance, etc.), its analytical evaluation soon becomes impractical and one is better off resorting to Monte Carlo simulation techniques which, however, could be computationally burdensome. Therefore, since the variance decomposition method requires a large number of system evaluations, each one to be performed by Monte Carlo, the need arises for possibly substituting the Monte Carlo simulation model with a fast, approximated, algorithm. Here we investigate an approach which makes use of neural networks appropriately trained on the results of a Monte Carlo system reliability/availability evaluation to quickly provide with reasonable approximation, the values of the quantities of interest for the sensitivity analyses. The work was a joint effort between the Department of Nuclear Engineering of the Polytechnic of Milan, Italy, and the Institute for Systems, Informatics and Safety, Nuclear Safety Unit of the Joint Research Centre in Ispra, Italy which sponsored the project
High-Grade Leiomyosarcoma Arising in a Previously Replanted Limb
Directory of Open Access Journals (Sweden)
Tiffany J. Pan
2015-01-01
Full Text Available Sarcoma development has been associated with genetics, irradiation, viral infections, and immunodeficiency. Reports of sarcomas arising in the setting of prior trauma, as in burn scars or fracture sites, are rare. We report a case of a leiomyosarcoma arising in an arm that had previously been replanted at the level of the elbow joint following traumatic amputation when the patient was eight years old. He presented twenty-four years later with a 10.8 cm mass in the replanted arm located on the volar forearm. The tumor was completely resected and pathology examination showed a high-grade, subfascial spindle cell sarcoma diagnosed as a grade 3 leiomyosarcoma with stage pT2bNxMx. The patient underwent treatment with brachytherapy, reconstruction with a free flap, and subsequently chemotherapy. To the best of our knowledge, this is the first case report of leiomyosarcoma developing in a replanted extremity. Development of leiomyosarcoma in this case could be related to revascularization, scar formation, or chronic injury after replantation. The patient remains healthy without signs of recurrence at three-year follow-up.
Felleki, M; Lee, D; Lee, Y; Gilmour, A R; Rönnegård, L
2012-12-01
The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being -0·52 for IRWLS and -0·62 in Sorensen & Waagepetersen (2003).
Teacher quality moderates the genetic effects on early reading.
Taylor, J; Roehrig, A D; Soden Hensler, B; Connor, C M; Schatschneider, C
2010-04-23
Children's reading achievement is influenced by genetics as well as by family and school environments. The importance of teacher quality as a specific school environmental influence on reading achievement is unknown. We studied first- and second-grade students in Florida from schools representing diverse environments. Comparison of monozygotic and dizygotic twins, differentiating genetic similarities of 100% and 50%, provided an estimate of genetic variance in reading achievement. Teacher quality was measured by how much reading gain the non-twin classmates achieved. The magnitude of genetic variance associated with twins' oral reading fluency increased as the quality of their teacher increased. In circumstances where the teachers are all excellent, the variability in student reading achievement may appear to be largely due to genetics. However, poor teaching impedes the ability of children to reach their potential.
DEFF Research Database (Denmark)
Casas, Isabel; Mao, Xiuping; Veiga, Helena
This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from...... time-varying coefficient models are the ones showing considerably higher predictive power for stock market returns and financial instability during the financial crisis, suggesting that an extreme volatility period requires models that can adapt quickly to turmoil........ Moreover, a comparison of the overall results reveals that the conditional variance gains predictive power during the global financial crisis period. Furthermore, both the variance risk premium and conditional variance are determined to be predictors of future financial instability, whereas conditional...
Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C
2013-03-01
Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.
Gene interactions and genetics of blast resistance and yield ...
Indian Academy of Sciences (India)
2014-08-11
Aug 11, 2014 ... of chemical measures for the control and management of blast, which are not .... tion of genetic components of variation, epistasis model and gene effects in two .... and environmental variance is estimated from mean variance.
A zero-variance-based scheme for variance reduction in Monte Carlo criticality
Energy Technology Data Exchange (ETDEWEB)
Christoforou, S.; Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)
2006-07-01
A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)
A zero-variance-based scheme for variance reduction in Monte Carlo criticality
International Nuclear Information System (INIS)
Christoforou, S.; Hoogenboom, J. E.
2006-01-01
A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)
Risk-sensitivity and the mean-variance trade-off: decision making in sensorimotor control.
Nagengast, Arne J; Braun, Daniel A; Wolpert, Daniel M
2011-08-07
Numerous psychophysical studies suggest that the sensorimotor system chooses actions that optimize the average cost associated with a movement. Recently, however, violations of this hypothesis have been reported in line with economic theories of decision-making that not only consider the mean payoff, but are also sensitive to risk, that is the variability of the payoff. Here, we examine the hypothesis that risk-sensitivity in sensorimotor control arises as a mean-variance trade-off in movement costs. We designed a motor task in which participants could choose between a sure motor action that resulted in a fixed amount of effort and a risky motor action that resulted in a variable amount of effort that could be either lower or higher than the fixed effort. By changing the mean effort of the risky action while experimentally fixing its variance, we determined indifference points at which participants chose equiprobably between the sure, fixed amount of effort option and the risky, variable effort option. Depending on whether participants accepted a variable effort with a mean that was higher, lower or equal to the fixed effort, they could be classified as risk-seeking, risk-averse or risk-neutral. Most subjects were risk-sensitive in our task consistent with a mean-variance trade-off in effort, thereby, underlining the importance of risk-sensitivity in computational models of sensorimotor control.
Directory of Open Access Journals (Sweden)
Talerngsak Angkuraseranee
2010-05-01
Full Text Available The additive and dominance genetic variances of 5,801 Duroc reproductive and growth records were estimated usingBULPF90 PC-PACK. Estimates were obtained for number born alive (NBA, birth weight (BW, number weaned (NW, andweaning weight (WW. Data were analyzed using two mixed model equations. The first model included fixed effects andrandom effects identifying inbreeding depression, additive gene effect and permanent environments effects. The secondmodel was similar to the first model, but included the dominance genotypic effect. Heritability estimates of NBA, BW, NWand WW from the two models were 0.1558/0.1716, 0.1616/0.1737, 0.0372/0.0874 and 0.1584/0.1516 respectively. Proportionsof dominance effect to total phenotypic variance from the dominance model were 0.1024, 0.1625, 0.0470, and 0.1536 for NBA,BW, NW and WW respectively. Dominance effects were found to have sizable influence on the litter size traits analyzed.Therefore, genetic evaluation with the dominance model (Model 2 is found more appropriate than the animal model (Model 1.
GENETIC CONTRIBUTION OF RAM ON LITTER SIZE IN ŠUMAVA SHEEP
Directory of Open Access Journals (Sweden)
Jitka Schmidová
2015-09-01
Full Text Available The objective of the present study was to quantify the service sire effect in terms of (co variance components of born and weaned lambs number and to propose models for the potential inclusion of this effect in the linear equations for breeding value estimation. The database with 21,324 lambings in Šumava sheep from 1992- 2013 was used. The basic model equation for the analysis of variance of litter size contained effects of ewe´s age at lambing, contemporary group, permanent environmental effect of ewe and direct additive genetic effect of ewe. Two modifications of the basic model were used for estimation of service sire effect. The proportions of variance for the service sire effect for number of born and weaned lambs were 2.1% and 2.0%, when service sire was not included into relationship matrix; while included into the relationship matrix and dividing effect into genetic contribution and permanent environment effect refer that nongenetic effect seems to be bigger than genetic (0.013 vs. 0.009 for number of born and 0.017 vs. 0.004 for number of weaned. Changes in other variance components were relatively low, except of contemporary group. Model including service sire effect as a simple random effect without genetic relationship matrix inclusion is recommended for genetic evaluation of litter size traits.
White Matter Hyperintensities Are Under Strong Genetic Influence.
Sachdev, Perminder S; Thalamuthu, Anbupalam; Mather, Karen A; Ames, David; Wright, Margaret J; Wen, Wei
2016-06-01
The genetic basis of white matter hyperintensities (WMH) is still unknown. This study examines the heritability of WMH in both sexes and in different brain regions, and the influence of age. Participants from the Older Australian Twins Study were recruited (n=320; 92 monozygotic and 68 dizygotic pairs) who volunteered for magnetic resonance imaging scans and medical assessments. Heritability, that is, the ratio of the additive genetic variance to the total phenotypic variance, was estimated using the twin design. Heritability was high for total WMH volume (0.76), and for periventricular WMH (0.64) and deep WMH (0.77), and varied from 0.18 for the cerebellum to 0.76 for the occipital lobe. The genetic correlation between deep and periventricular WMH regions was 0.85, with one additive genetics factor accounting for most of the shared variance. Heritability was consistently higher in women in the cerebral regions. Heritability in deep but not periventricular WMH declined with age, in particular after the age of 75. WMH have a strong genetic influence but this is not uniform through the brain, being higher for deep than periventricular WMH and in the cerebral regions. The genetic influence is higher in women, and there is an age-related decline, most markedly for deep WMH. The data suggest some heterogeneity in the pathogenesis of WMH for different brain regions and for men and women. © 2016 American Heart Association, Inc.
DEFF Research Database (Denmark)
Sørensen, Peter; de los Campos, Gustavo; Morgante, Fabio
2015-01-01
and others more volatile performance. Understanding the mechanisms responsible for environmental variability not only informs medical questions but is relevant in evolution and in agricultural science. In this work fully sequenced inbred lines of Drosophila melanogaster were analyzed to study the nature...... of genetic control of environmental variance for two quantitative traits: starvation resistance (SR) and startle response (SL). The evidence for genetic control of environmental variance is compelling for both traits. Sequence information is incorporated in random regression models to study the underlying...... genetic signals, which are shown to be different in the two traits. Genomic variance in sexual dimorphism was found for SR but not for SL. Indeed, the proportion of variance captured by sequence information and the contribution to this variance from four chromosome segments differ between sexes in SR...
AMOVA-based clustering of population genetic data
Meirmans, P.G.
2012-01-01
Determining the genetic structure of populations is becoming an increasingly important aspect of genetic studies. One of the most frequently used methods is the calculation of F-statistics using an Analysis of Molecular Variance (AMOVA). However, this has the drawback that the population hierarchy
Tucker, Kimberly Pause; Hunter, Margaret E.; Bonde, Robert K.; Austin, James D.; Clark, Ann Marie; Beck, Cathy A.; McGuire, Peter M.; Oli, Madan K.
2012-01-01
Species of management concern that have been affected by human activities typically are characterized by low genetic diversity, which can adversely affect their ability to adapt to environmental changes. We used 18 microsatellite markers to genotype 362 Florida manatees (Trichechus manatus latirostris), and investigated genetic diversity, population structure, and estimated genetically effective population size (Ne). The observed and expected heterozygosity and average number of alleles were 0.455 ± 0.04, 0.479 ± 0.04, and 4.77 ± 0.51, respectively. All measures of Florida manatee genetic diversity were less than averages reported for placental mammals, including fragmented or nonideal populations. Overall estimates of differentiation were low, though significantly greater than zero, and analysis of molecular variance revealed that over 95% of the total variance was among individuals within predefined management units or among individuals along the coastal subpopulations, with only minor portions of variance explained by between group variance. Although genetic issues, as inferred by neutral genetic markers, appear not to be critical at present, the Florida manatee continues to face demographic challenges due to anthropogenic activities and stochastic factors such as red tides, oil spills, and disease outbreaks; these can further reduce genetic diversity of the manatee population.
Marjanovic, Jovana; Mulder, Han A; Khaw, Hooi L; Bijma, Piter
2016-06-10
Animal breeding programs have been very successful in improving the mean levels of traits through selection. However, in recent decades, reducing the variability of trait levels between individuals has become a highly desirable objective. Reaching this objective through genetic selection requires that there is genetic variation in the variability of trait levels, a phenomenon known as genetic heterogeneity of environmental (residual) variance. The aim of our study was to investigate the potential for genetic improvement of uniformity of harvest weight and body size traits (length, depth, and width) in the genetically improved farmed tilapia (GIFT) strain. In order to quantify the genetic variation in uniformity of traits and estimate the genetic correlations between level and variance of the traits, double hierarchical generalized linear models were applied to individual trait values. Our results showed substantial genetic variation in uniformity of all analyzed traits, with genetic coefficients of variation for residual variance ranging from 39 to 58 %. Genetic correlation between trait level and variance was strongly positive for harvest weight (0.60 ± 0.09), moderate and positive for body depth (0.37 ± 0.13), but not significantly different from 0 for body length and width. Our results on the genetic variation in uniformity of harvest weight and body size traits show good prospects for the genetic improvement of uniformity in the GIFT strain. A high and positive genetic correlation was estimated between level and variance of harvest weight, which suggests that selection for heavier fish will also result in more variation in harvest weight. Simultaneous improvement of harvest weight and its uniformity will thus require index selection.
Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.
Dazard, Jean-Eudes; Rao, J Sunil
2012-07-01
The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.
Portfolio optimization using median-variance approach
Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli
2013-04-01
Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.
Bioethics, sport and the genetically enhanced athlete.
Miah, Andy
2002-01-01
This paper begins by acknowledging the interest taken by various international organisations in genetic enhancement and sport, including the US President's Council on Bioethics (July, 2002) and the World Anti-Doping Agency (March, 2002). It is noticed how sporting organisations have been particularly concerned to emphasize the 'threat' of genetics to sport, whereas other institutions have recognised the broader bioethical issues arising from this prospect, which do not readily reject the use of genetic technology in sport. Sports are identified as necessarily 'human' and 'moral' practices, the exploration of which can reveal greater insight into the intuitive fears about genetic modification. It is argued that anti-doping testing measures and sanctions unacceptably persecute the athlete. While there are substantial reasons to be concerned about the use of genetic modification in sport, the desire for policy ought not diminish the need for ethical research; nor ought such research embody the similar guise of traditional 'anti' doping strategies. Rather, the approach to genetics in sport must be informed more by broader social policies in bioethics and recognition of the greater goods arising from genetic technology.
Efficient Cardinality/Mean-Variance Portfolios
Brito, R. Pedro; Vicente, Luís Nunes
2014-01-01
International audience; We propose a novel approach to handle cardinality in portfolio selection, by means of a biobjective cardinality/mean-variance problem, allowing the investor to analyze the efficient tradeoff between return-risk and number of active positions. Recent progress in multiobjective optimization without derivatives allow us to robustly compute (in-sample) the whole cardinality/mean-variance efficient frontier, for a variety of data sets and mean-variance models. Our results s...
Genetic Analysis of Micro-environmental Plasticity in Drosophila melanogaster
DEFF Research Database (Denmark)
Morgante, Fabio; Sorensen, Daniel A; Sørensen, Peter
Quantitative genetic models recognize the potential for genotype by environment interaction, whereby different genotypes have different plastic responses to changes in macro-environmental conditions. Recently, it has been recognized that micro-environmental plasticity (‘residual’ variance) may also...... be genetically variable. This study utilized the Drosophila Genetic Reference Panel (DGRP) to accurately estimate the genetic variance of micro-environmental plasticity for chill coma recovery time and startle response. Estimates of broad sense heritabilities for both traits are substantial (from 0.51 to 0.......77), of the same order as the heritability at the level of the trait mean for startle response and even larger for chill coma recovery. Genome wide association analyses identified molecular variants (from 15 to 31 depending on the sex and the trait) associated with micro-environmental plasticity. These findings...
The effect of sex on the mean and variance of fitness in facultatively sexual rotifers.
Becks, L; Agrawal, A F
2011-03-01
The evolution of sex is a classic problem in evolutionary biology. While this topic has been the focus of much theoretical work, there is a serious dearth of empirical data. A simple yet fundamental question is how sex affects the mean and variance in fitness. Despite its importance to the theory, this type of data is available for only a handful of taxa. Here, we report two experiments in which we measure the effect of sex on the mean and variance in fitness in the monogonont rotifer, Brachionus calyciflorus. Compared to asexually derived offspring, we find that sexual offspring have lower mean fitness and less genetic variance in fitness. These results indicate that, at least in the laboratory, there are both short- and long-term disadvantages associated with sexual reproduction. We briefly review the other available data and highlight the need for future work. © 2010 The Authors. Journal of Evolutionary Biology © 2010 European Society For Evolutionary Biology.
DEFF Research Database (Denmark)
Andersen, Anders Holst; Korsgaard, Inge Riis; Jensen, Just
2002-01-01
In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed...... or random effects). In the different models, expressions are given (when these can be found - otherwise unbiased estimates are given) for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non...... Gaussian traits are generalisations of the well-known formulas for Gaussian traits - and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part...
Genetic variation in efficiency to deposit fat and lean meat in Norwegian Landrace and Duroc pigs.
Martinsen, K H; Ødegård, J; Olsen, D; Meuwissen, T H E
2015-08-01
Feed costs amount to approximately 70% of the total costs in pork production, and feed efficiency is, therefore, an important trait for improving pork production efficiency. Production efficiency is generally improved by selection for high lean growth rate, reduced backfat, and low feed intake. These traits have given an effective slaughter pig but may cause problems in piglet production due to sows with limited body reserves. The aim of the present study was to develop a measure for feed efficiency that expressed the feed requirements per 1 kg deposited lean meat and fat, which is not improved by depositing less fat. Norwegian Landrace ( = 8,161) and Duroc ( = 7,202) boars from Topigs Norsvin's testing station were computed tomography scanned to determine their deposition of lean meat and fat. The trait was analyzed in a univariate animal model, where total feed intake in the test period was the dependent variable and fat and lean meat were included as random regression cofactors. These cofactors were measures for fat and lean meat efficiencies of individual boars. Estimation of fraction of total genetic variance due to lean meat or fat efficiency was calculated by the ratio between the genetic variance of the random regression cofactor and the total genetic variance in total feed intake during the test period. Genetic variance components suggested there was significant genetic variance among Norwegian Landrace and Duroc boars in efficiency for deposition of lean meat (0.23 ± 0.04 and 0.38 ± 0.06) and fat (0.26 ± 0.03 and 0.17 ± 0.03) during the test period. The fraction of the total genetic variance in feed intake explained by lean meat deposition was 12% for Norwegian Landrace and 15% for Duroc. Genetic fractions explained by fat deposition were 20% for Norwegian Landrace and 10% for Duroc. The results suggested a significant part of the total genetic variance in feed intake in the test period was explained by fat and lean meat efficiency. These new
Some Conceptual Deficiencies in "Developmental" Behavior Genetics.
Gottlieb, Gilbert
1995-01-01
Criticizes the application of the statistical procedures of the population-genetic approach within evolutionary biology to the study of psychological development. Argues that the application of the statistical methods of population genetics--primarily the analysis of variance--to the causes of psychological development is bound to result in a…
Litter size, fur quality and genetic analyses of American mink
DEFF Research Database (Denmark)
Thirstrup, Janne Pia
of the skin, have been analyzed. Both fur quality traits and litter size are complex traits underlying quantitative genetic variation. Methods for estimating genetic variance, spanning from pedigree information to the use of different genetic markers, have been utilized in order to gain knowledge about...
Is the experience of thermal pain genetics dependent?
DEFF Research Database (Denmark)
Horjales-Araujo, Emilia; Dahl, Joergen B
2015-01-01
It is suggested that genetic variations explain a significant portion of the variability in pain perception; therefore, increased understanding of pain-related genetic influences may identify new targets for therapies and treatments. The relative contribution of the different genes to the varianc...
Approximation errors during variance propagation
International Nuclear Information System (INIS)
Dinsmore, Stephen
1986-01-01
Risk and reliability analyses are often performed by constructing and quantifying large fault trees. The inputs to these models are component failure events whose probability of occuring are best represented as random variables. This paper examines the errors inherent in two approximation techniques used to calculate the top event's variance from the inputs' variance. Two sample fault trees are evaluated and several three dimensional plots illustrating the magnitude of the error over a wide range of input means and variances are given
The phenotypic variance gradient - a novel concept.
Pertoldi, Cino; Bundgaard, Jørgen; Loeschcke, Volker; Barker, James Stuart Flinton
2014-11-01
Evolutionary ecologists commonly use reaction norms, which show the range of phenotypes produced by a set of genotypes exposed to different environments, to quantify the degree of phenotypic variance and the magnitude of plasticity of morphometric and life-history traits. Significant differences among the values of the slopes of the reaction norms are interpreted as significant differences in phenotypic plasticity, whereas significant differences among phenotypic variances (variance or coefficient of variation) are interpreted as differences in the degree of developmental instability or canalization. We highlight some potential problems with this approach to quantifying phenotypic variance and suggest a novel and more informative way to plot reaction norms: namely "a plot of log (variance) on the y-axis versus log (mean) on the x-axis, with a reference line added". This approach gives an immediate impression of how the degree of phenotypic variance varies across an environmental gradient, taking into account the consequences of the scaling effect of the variance with the mean. The evolutionary implications of the variation in the degree of phenotypic variance, which we call a "phenotypic variance gradient", are discussed together with its potential interactions with variation in the degree of phenotypic plasticity and canalization.
Genetic Variance in Processing Speed Drives Variation in Aging of Spatial and Memory Abilities
Finkel, Deborah; Reynolds, Chandra A.; McArdle, John J.; Hamagami, Fumiaki; Pedersen, Nancy L.
2009-01-01
Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories…
Confidence Interval Approximation For Treatment Variance In ...
African Journals Online (AJOL)
In a random effects model with a single factor, variation is partitioned into two as residual error variance and treatment variance. While a confidence interval can be imposed on the residual error variance, it is not possible to construct an exact confidence interval for the treatment variance. This is because the treatment ...
Wallace, I J; Botigué, L R; Lin, M; Smaers, J B; Henn, B M; Grine, F E
2016-09-01
This study investigates the influence of genetic differentiation in determining worldwide heterogeneity in osteoporosis-related hip fracture rates. The results indicate that global variation in fracture incidence exceeds that expected on the basis of random genetic variance. Worldwide, the incidence of osteoporotic hip fractures varies considerably. This variability is believed to relate mainly to non-genetic factors. It is conceivable, however, that genetic susceptibility indeed differs across populations. Here, we present the first quantitative assessment of the effects of genetic differentiation on global variability in hip fracture rates. We investigate the observed variance in publically reported age-standardized rates of hip fracture among 28 populations from around the world relative to the expected variance given the phylogenetic relatedness of these populations. The extent to which these variances are similar constitutes a "phylogenetic signal," which was measured using the K statistic. Population genetic divergence was calculated using a robust array of genome-wide single nucleotide polymorphisms. While phylogenetic signal is maximized when K > 1, a K value of only 0.103 was detected in the combined-sex fracture rate pattern across the 28 populations, indicating that fracture rates vary more than expected based on phylogenetic relationships. When fracture rates for the sexes were analyzed separately, the degree of phylogenetic signal was also found to be small (females: K = 0.102; males: K = 0.081). The lack of a strong phylogenetic signal underscores the importance of factors other than stochastic genetic diversity in shaping worldwide heterogeneity in hip fracture incidence.
Baek, Eun Kyeng; Ferron, John M
2013-03-01
Multilevel models (MLM) have been used as a method for analyzing multiple-baseline single-case data. However, some concerns can be raised because the models that have been used assume that the Level-1 error covariance matrix is the same for all participants. The purpose of this study was to extend the application of MLM of single-case data in order to accommodate across-participant variation in the Level-1 residual variance and autocorrelation. This more general model was then used in the analysis of single-case data sets to illustrate the method, to estimate the degree to which the autocorrelation and residual variances differed across participants, and to examine whether inferences about treatment effects were sensitive to whether or not the Level-1 error covariance matrix was allowed to vary across participants. The results from the analyses of five published studies showed that when the Level-1 error covariance matrix was allowed to vary across participants, some relatively large differences in autocorrelation estimates and error variance estimates emerged. The changes in modeling the variance structure did not change the conclusions about which fixed effects were statistically significant in most of the studies, but there was one exception. The fit indices did not consistently support selecting either the more complex covariance structure, which allowed the covariance parameters to vary across participants, or the simpler covariance structure. Given the uncertainty in model specification that may arise when modeling single-case data, researchers should consider conducting sensitivity analyses to examine the degree to which their conclusions are sensitive to modeling choices.
Genetic Parameters of Common Wheat in Nepal
Bal Krishna Joshi; Dhruba Bahadur Thapa; Madan Raj Bhatta
2015-01-01
Knowledge on variation within traits and their genetics are prerequisites in crop improvement program. Thus, in present paper we aimed to estimate genetic and environmental indices of common wheat genotypes. For the purpose, eight quantitative traits were measured from 30 wheat genotypes, which were in randomized complete block design with 3 replicates. Components of variance and covariance were estimated along with heritability, genetic gain, realized heritability, coheritability and correla...
Genetic adaptability of durum wheat to salinity level at germination ...
African Journals Online (AJOL)
Administrator
2011-05-23
May 23, 2011 ... Keys words: Durum wheat, genetic-adaptability, salinity level. ... tolerance of crop proves the first way to overcome the limitation of crops ... Analysis of variance using GLM procedures (SAS, 1990) were used ... Additive, dominance and environmental variance components were ..... Breeding for stability of.
Primary diffuse large B cell lymphoma arising from a leiomyoma of the uterine corpus.
Zhao, Lianhua; Ma, Qiang; Wang, Qiushi; Zeng, Ying; Luo, Qingya; Xiao, Hualiang
2016-01-20
Primary diffuse large B cell lymphoma (DLBCL) of the uterus is rare, and primary DLBCL arising from a uterine leiomyoma (collision tumor) has not been reported in the literature. We describe the clinical, histological, immunohistochemical, and molecular features of primary DLBCL arising from a leiomyoma in the uterine corpus. A 73-year-old female patient had a uterine mass for 23 years. An ultrasound scan revealed marked enlargement of the uterus, measuring 18.2 × 13 × 16.3 cm, with a 17.6 × 10.9 × 11.6 cm hypoechoic mass in the uterine corpus. The tumors consisted of medium- to large-sized cells exhibiting a diffuse pattern of growth with a well-circumscribed leiomyoma. The neoplastic cells strongly expressed CD79α, CD20 and PAX5. Molecular analyses indicated clonal B-cell receptor gene rearrangement. To the best of our knowledge, no previous cases of primary DLBCL arising from a leiomyoma have been reported. It is necessary to differentiate a diagnosis of primary DLBCL arising from a leiomyoma from that of leiomyoma with florid reactive lymphocytic infiltration (lymphoma-like lesion). Careful analysis of clinical, histological, immunophenotypic, and genetic features is required to establish the correct diagnosis.
Assessment of genetic diversity within sour cherry clones
DEFF Research Database (Denmark)
Clausen, Sabine Karin; Andersen, Sven Bode; Henriksen, K.
2013-01-01
of improved breeding material. However, no differences in allele profile were found between or within the clones, calling into question the extent of the available genetic diversity and indicating that the observed variance in yield may have to be explained by other genetic mechanisms, including epigenetic...
Genetic variability of indigenous cowpea genotypes as determined ...
African Journals Online (AJOL)
Bayesian statistics coupled with the Markov chain Monte Carlo technique was applied to determine population structure, while the genetic variability was established by analysis of molecular variance. UPGMA analysis allowed the separation of the genotypes into three groups, but no relationship between the genetic and ...
Portfolio optimization with mean-variance model
Hoe, Lam Weng; Siew, Lam Weng
2016-06-01
Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.
Direct and maternal genetic effects for birth weight in dorper and ...
African Journals Online (AJOL)
Variance components for birth (BWT) in Dorper and Mutton Merino sheep were estimated by Average Information Restricted Maximum Likelihood (AIREML). Animal model was fitted allowing for genetic maternal effects and a genetic covariance between direct and maternal effects. Estimates of heritability for direct genetic ...
The effects of stress and sex on selection, genetic covariance, and the evolutionary response.
Holman, L; Jacomb, F
2017-10-01
The capacity of a population to adapt to selection (evolvability) depends on whether the structure of genetic variation permits the evolution of fitter trait combinations. Selection, genetic variance and genetic covariance can change under environmental stress, and males and females are not genetically independent, yet the combined effects of stress and dioecy on evolvability are not well understood. Here, we estimate selection, genetic (co)variance and evolvability in both sexes of Tribolium castaneum flour beetles under stressful and benign conditions, using a half-sib breeding design. Although stress uncovered substantial latent heritability, stress also affected genetic covariance, such that evolvability remained low under stress. Sexual selection on males and natural selection on females favoured a similar phenotype, and there was positive intersex genetic covariance. Consequently, sexual selection on males augmented adaptation in females, and intralocus sexual conflict was weak or absent. This study highlights that increased heritability does not necessarily increase evolvability, suggests that selection can deplete genetic variance for multivariate trait combinations with strong effects on fitness, and tests the recent hypothesis that sexual conflict is weaker in stressful or novel environments. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.
Deater-Deckard, Kirby; Cutting, Laurie; Thompson, Lee A.; Petrill, Stephen A.
2012-01-01
The purpose of the current study was to investigate potential genetic and environmental correlations between working memory and three behavioral aspects of the attention network (i.e., executive, alerting, and orienting) using a twin design. Data were from 90 monozygotic (39% male) and 112 same-sex dizygotic (41% male) twins. Individual differences in working memory performance (digit span) and parent-rated measures of executive, alerting, and orienting attention included modest to moderate genetic variance, modest shared environmental variance, and modest to moderate nonshared environmental variance. As hypothesized, working memory performance was correlated with executive and alerting attention, but not orienting attention. The correlation between working memory, executive attention, and alerting attention was completely accounted for by overlapping genetic covariance, suggesting a common genetic mechanism or mechanisms underlying the links between working memory and certain parent-rated indicators of attentive behavior. PMID:21948215
A family-based joint test for mean and variance heterogeneity for quantitative traits.
Cao, Ying; Maxwell, Taylor J; Wei, Peng
2015-01-01
Traditional quantitative trait locus (QTL) analysis focuses on identifying loci associated with mean heterogeneity. Recent research has discovered loci associated with phenotype variance heterogeneity (vQTL), which is important in studying genetic association with complex traits, especially for identifying gene-gene and gene-environment interactions. While several tests have been proposed to detect vQTL for unrelated individuals, there are no tests for related individuals, commonly seen in family-based genetic studies. Here we introduce a likelihood ratio test (LRT) for identifying mean and variance heterogeneity simultaneously or for either effect alone, adjusting for covariates and family relatedness using a linear mixed effect model approach. The LRT test statistic for normally distributed quantitative traits approximately follows χ(2)-distributions. To correct for inflated Type I error for non-normally distributed quantitative traits, we propose a parametric bootstrap-based LRT that removes the best linear unbiased prediction (BLUP) of family random effect. Simulation studies show that our family-based test controls Type I error and has good power, while Type I error inflation is observed when family relatedness is ignored. We demonstrate the utility and efficiency gains of the proposed method using data from the Framingham Heart Study to detect loci associated with body mass index (BMI) variability. © 2014 John Wiley & Sons Ltd/University College London.
Analysis of genetic structure in Melia volkensii (Gurke.) populations ...
African Journals Online (AJOL)
Administrator
2Farm Forestry Programme, Kenya Forestry Research Institute, P. O. Box 20412, Nairobi, Kenya. Accepted 5 ... were used to estimate genetic distances between populations and for construction of neighbour-joining phenograms. Analysis of Molecular Variance (AMOVA) indicated significant genetic differentiation between ...
Sleep Reactivity and Insomnia: Genetic and Environmental Influences
Drake, Christopher L.; Friedman, Naomi P.; Wright, Kenneth P.; Roth, Thomas
2011-01-01
Study Objectives: Determine the genetic and environmental contributions to sleep reactivity and insomnia. Design: Population-based twin cohort. Participants: 1782 individual twins (988 monozygotic or MZ; 1,086 dizygotic or DZ), including 744 complete twin pairs (377 MZ and 367 DZ). Mean age was 22.5 ± 2.8 years; gender distribution was 59% women. Measurements: Sleep reactivity was measured using the Ford Insomnia Response to Stress Test (FIRST). The criterion for insomnia was having difficulty falling asleep, staying asleep, or nonrefreshing sleep “usually or always” for ≥ 1 month, with at least “somewhat” interference with daily functioning. Results: The prevalence of insomnia was 21%. Heritability estimates for sleep reactivity were 29% for females and 43% for males. The environmental variance for sleep reactivity was greater for females and entirely due to nonshared effects. Insomnia was 43% to 55% heritable for males and females, respectively; the sex difference was not significant. The genetic variances in insomnia and FIRST scores were correlated (r = 0.54 in females, r = 0.64 in males), as were the environmental variances (r = 0.32 in females, r = 0.37 in males). In terms of individual insomnia symptoms, difficulty staying asleep (25% to 35%) and nonrefreshing sleep (34% to 35%) showed relatively more genetic influences than difficulty falling asleep (0%). Conclusions: Sleep reactivity to stress has a substantial genetic component, as well as an environmental component. The finding that FIRST scores and insomnia symptoms share genetic influences is consistent with the hypothesis that sleep reactivity may be a genetic vulnerability for developing insomnia. Citation: Drake CL; Friedman NP; Wright KP; Roth T. Sleep reactivity and insomnia: genetic and environmental influences. SLEEP 2011;34(9):1179-1188. PMID:21886355
Genetic improvement of vegetables
International Nuclear Information System (INIS)
Jaramillo Vasquez, J.G.
2001-01-01
Some genetic bases of the improvement of vegetables are given. The objectives of the genetic improvement and the fundamental stages of this process are done. The sources of genetic variation are indicated and they are related the reproduction systems of the main horticultural species. It is analyzed the concept of genetic inheritance like base to determine the procedures more appropriate of improvement. The approaches are discussed, has more than enough phenotypic value, genetic action and genotypic variance; Equally the heredability concepts and value of improvement. The conventional methods of improvement are described, like they are: the introduction of species or varieties, the selection, the pure line, the pedigree method, the selection for families, the recurrent selection, the selection for unique seed, the haploids method, the selection for heterosis and the synthetic varieties
Behavior genetic modeling of human fertility
DEFF Research Database (Denmark)
Rodgers, J L; Kohler, H P; Kyvik, K O
2001-01-01
Behavior genetic designs and analysis can be used to address issues of central importance to demography. We use this methodology to document genetic influence on human fertility. Our data come from Danish twin pairs born from 1953 to 1959, measured on age at first attempt to get pregnant (First......Try) and number of children (NumCh). Behavior genetic models were fitted using structural equation modeling and DF analysis. A consistent medium-level additive genetic influence was found for NumCh, equal across genders; a stronger genetic influence was identified for FirstTry, greater for females than for males....... A bivariate analysis indicated significant shared genetic variance between NumCh and FirstTry....
Least-squares variance component estimation
Teunissen, P.J.G.; Amiri-Simkooei, A.R.
2007-01-01
Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a user-defined weight
Update on the role of genetics in the onset of age-related macular degeneration
Francis, Peter James; Klein, Michael L
2011-01-01
Age-related macular degeneration (AMD), akin to other common age-related diseases, has a complex pathogenesis and arises from the interplay of genes, environmental factors, and personal characteristics. The past decade has seen very significant strides towards identification of those precise genetic variants associated with disease. That genes encoding proteins of the (alternative) complement pathway (CFH, C2, CFB, C3, CFI) are major players in etiology came as a surprise to many but has already lead to the development of therapies entering human clinical trials. Other genes replicated in many populations ARMS2, APOE, variants near TIMP3, and genes involved in lipid metabolism have also been implicated in disease pathogenesis. The genes discovered to date can be estimated to account for approximately 50% of the genetic variance of AMD and have been discovered by candidate gene approaches, pathway analysis, and latterly genome-wide association studies. Next generation sequencing modalities and meta-analysis techniques are being employed with the aim of identifying the remaining rarer but, perhaps, individually more significant sequence variations, linked to disease status. Complementary studies have also begun to utilize this genetic information to develop clinically useful algorithms to predict AMD risk and evaluate pharmacogenetics. In this article, contemporary commentary is provided on rapidly progressing efforts to elucidate the genetic pathogenesis of AMD as the field stands at the end of the first decade of the 21st century. PMID:21887094
Genet and tic vari d seed iability yield t oc y and h traits i cciden ...
African Journals Online (AJOL)
SAM
between two variables; δ2x is the genotypic or phenotypic variance of the variable x, δ2y is the genotypic or phenotypic variance of the variable yield y. .... var = genotypic variance; Env var = environmental variance; PCV = phenotypic coefficient of variability; GCV = genotypic coefficient of variability; Gen adv% = genetic ...
Genes, Culture and Conservatism-A Psychometric-Genetic Approach.
Schwabe, Inga; Jonker, Wilfried; van den Berg, Stéphanie M
2016-07-01
The Wilson-Patterson conservatism scale was psychometrically evaluated using homogeneity analysis and item response theory models. Results showed that this scale actually measures two different aspects in people: on the one hand people vary in their agreement with either conservative or liberal catch-phrases and on the other hand people vary in their use of the "?" response category of the scale. A 9-item subscale was constructed, consisting of items that seemed to measure liberalism, and this subscale was subsequently used in a biometric analysis including genotype-environment interaction, correcting for non-homogeneous measurement error. Biometric results showed significant genetic and shared environmental influences, and significant genotype-environment interaction effects, suggesting that individuals with a genetic predisposition for conservatism show more non-shared variance but less shared variance than individuals with a genetic predisposition for liberalism.
Directory of Open Access Journals (Sweden)
Kristine Vander Mijnsbrugge
2016-11-01
diminished at the growth site with the shortest growing season while interestingly, the leaf width was enlarged. Leaf size traits appeared more plastic on the long shoots compared to the short shoots, although partitioning of variance did not display a lesser genetic
Mihai, Georgeta; Birsan, Marius-Victor; Teodosiu, Maria; Dumitrescu, Alexandru; Daia, Mihai; Mirancea, Ionel; Ivanov, Paula; Alin, Alexandru
2017-04-01
Mountain ecosystems are extremely vulnerable to climate change. The real potential for adaptation depends upon the existence of a wide genetic diversity in trees populations, upon the adaptive genetic variation, respectively. Genetic diversity offers the guarantee that forest species can survive, adapt and evolve under the influence of changing environmental conditions. The aim of this study is to evaluate the genetic diversity and adaptive genetic potential of two local species - Norway spruce and European silver fir - in the context of regional climate change. Based on data from a long-term provenance experiments network and climate variables spanning over more than 50 years, we have investigated the impact of climatic factors on growth performance and adaptation of tree species. Our results indicate that climatic and geographic factors significantly affect forest site productivity. Mean annual temperature and annual precipitation amount were found to be statistically significant explanatory variables. Combining the additive genetic model with the analysis of nuclear markers we obtained different images of the genetic structure of tree populations. As genetic indicators we used: gene frequencies, genetic diversity, genetic differentiation, genetic variance, plasticity. Spatial genetic analyses have allowed identifying the genetic centers holding high genetic diversity which will be valuable sources of gene able to buffer the negative effects of future climate change. Correlations between the marginal populations and in the optimal vegetation, between the level of genetic diversity and ecosystem stability, will allow the assessment of future risks arising from current genetic structure. Therefore, the strategies for sustainable forest management have to rely on the adaptive genetic variation and local adaptation of the valuable genetic resources. This work was realized within the framework of the project GENCLIM (Evaluating the adaptive potential of the main
Harrison, Jay M; Howard, Delia; Malven, Marianne; Halls, Steven C; Culler, Angela H; Harrigan, George G; Wolfinger, Russell D
2013-07-03
Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented. Results of the traditional analysis of variance approach confirmed the compositional equivalence of the GM and non-GM cotton. The multivariate approach of PVCA provided further information on the impact of location and germplasm on compositional variability relative to GM.
All definitions of the metabolic syndrome include some form of obesity as one of the possible features. Body mass index (BMI) has a known genetic component, currently estimated to account for about 70% of the population variance in weight status for non-syndromal obesity. Much research effort has be...
Directory of Open Access Journals (Sweden)
Dowling Damian K
2011-07-01
Full Text Available Abstract Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass, and each trait harboured significant additive genetic variance in the standard temperature (27°C only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass. Of the female traits measured, only ovary mass for crickets
Quantitative genetic analysis of total glucosinolate, oil and protein ...
African Journals Online (AJOL)
Quantitative genetic analysis of total glucosinolate, oil and protein contents in Ethiopian mustard ( Brassica carinata A. Braun) ... Seeds were analyzed using HPLC (glucosinolates), NMR (oil) and NIRS (protein). Analyses of variance, Hayman's method of diallel analysis and a mixed linear model of genetic analysis were ...
Genetics of zinc tolerance in Anthoxanthum odoratum and Agrostis tenuis
Energy Technology Data Exchange (ETDEWEB)
Gartside, D W; McNeilly, T
1974-01-01
The genetic control of zinc tolerance in the grass Anthoxanthum odoratum and Agrostis tenuis has been examined using both the pair cross technique and the diallele analysis procedure used by others. Evidence is presented that the genetic control of zinc tolerance in both species is dominant and directional with a high degree of additive genetic variance.
Theory and Practice in Quantitative Genetics
DEFF Research Database (Denmark)
Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C
2003-01-01
With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative...... geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships......) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each...
The evolving genetic foundations of eating disorders.
Klump, K L; Kaye, W H; Strober, M
2001-06-01
Data described earlier are clear in establishing a role for genes in the development of eating abnormalities. Estimates from the most rigorous studies suggest that more than 50% of the variance in eating disorders and disordered eating behaviors can be accounted for by genetic effects. These high estimates indicate a need for studies identifying the specific genes contributing to this large proportion of variance. Twin and family studies suggest that several heritable characteristics that are commonly comorbid with AN and BN may share genetic transmission with these disorders, including anxiety disorders or traits, body weight, and possibly major depression. Moreover, some developmental research suggests that the genes involved in ovarian hormones or the genes that these steroids affect also may be genetically linked to eating abnormalities. Molecular genetic research of these disorders is in its infant stages. However, promising areas for future research have already been identified (e.g., 5-HT2A receptor gene, UCP-2/UCP-3 gene, and estrogen receptor beta gene), and several large-scale linkage and association studies are underway. These studies likely will provide invaluable information regarding the appropriate phenotypes to be included in genetic studies and the genes with the most influence on the development of these disorders.
Genetic parameters for reproduction rate in the Tygerhoek Merino ...
African Journals Online (AJOL)
Dolling, 1963; Lewer, Rae & Wickham, 1983). Genetic. Number of lambing opportunities correlations involving EclEm and Ld/Lb, that showed. 2. 3. 4. 5 little genetic variation (Cloete &Heydenrych, 1987)were. Item particularly unstable. Negative between-sire variance. First set of data components prevented the estimation of ...
Genetic parameters for EUROP carcass traits within different groups of cattle in Ireland
Hickey, J.M.; Keane, M.G.; Kenny, D.A.; Cromie, A.R.; Veerkamp, R.F.
2007-01-01
The first objective of this study was to test the ability of systems of weighing and classifying bovine carcasses used in commercial abattoirs in Ireland to provide information that can be used for the purposes of genetic evaluation of carcass weight, carcass fatness class, and carcass conformation class. Secondly, the study aimed to test whether genetic and phenotypic variances differed by breed of sire. Variance components for carcass traits were estimated for crosses between dairy cows and...
Speed Variance and Its Influence on Accidents.
Garber, Nicholas J.; Gadirau, Ravi
A study was conducted to investigate the traffic engineering factors that influence speed variance and to determine to what extent speed variance affects accident rates. Detailed analyses were carried out to relate speed variance with posted speed limit, design speeds, and other traffic variables. The major factor identified was the difference…
Tests for genetic interactions in type 1 diabetes
DEFF Research Database (Denmark)
Morahan, Grant; Mehta, Munish; James, Ian
2011-01-01
Interactions between genetic and environmental factors lead to immune dysregulation causing type 1 diabetes and other autoimmune disorders. Recently, many common genetic variants have been associated with type 1 diabetes risk, but each has modest individual effects. Familial clustering of type 1...... diabetes has not been explained fully and could arise from many factors, including undetected genetic variation and gene interactions....
DEFF Research Database (Denmark)
Chown, Steven L.; Jumbam, Keafon R.; Sørensen, Jesper Givskov
2009-01-01
used during assessments of critical thermal limits to activity. To date, the focus of work has almost exclusively been on the effects of rate variation on mean values of the critical limits. 2. If the rate of temperature change used in an experimental trial affects not only the trait mean but also its...... this is the case for critical thermal limits using a population of the model species Drosophila melanogaster and the invasive ant species Linepithema humile. 4. We found that effects of the different rates of temperature change are variable among traits and species. However, in general, different rates...... of temperature change resulted in different phenotypic variances and different estimates of heritability, presuming that genetic variance remains constant. We also found that different rates resulted in different conclusions regarding the responses of the species to acclimation, especially in the case of L...
Röring, Johan
2017-01-01
Volatility is a common risk measure in the field of finance that describes the magnitude of an asset’s up and down movement. From only being a risk measure, volatility has become an asset class of its own and volatility derivatives enable traders to get an isolated exposure to an asset’s volatility. Two kinds of volatility derivatives are volatility swaps and variance swaps. The problem with volatility swaps and variance swaps is that they require estimations of the future variance and volati...
Local variances in biomonitoring
International Nuclear Information System (INIS)
Wolterbeek, H.T.
1999-01-01
The present study deals with the (larger-scaled) biomonitoring survey and specifically focuses on the sampling site. In most surveys, the sampling site is simply selected or defined as a spot of (geographical) dimensions which is small relative to the dimensions of the total survey area. Implicitly it is assumed that the sampling site is essentially homogeneous with respect to the investigated variation in survey parameters. As such, the sampling site is mostly regarded as 'the basic unit' of the survey. As a logical consequence, the local (sampling site) variance should also be seen as a basic and important characteristic of the survey. During the study, work is carried out to gain more knowledge of the local variance. Multiple sampling is carried out at a specific site (tree bark, mosses, soils), multi-elemental analyses are carried out by NAA, and local variances are investigated by conventional statistics, factor analytical techniques, and bootstrapping. Consequences of the outcomes are discussed in the context of sampling, sample handling and survey quality. (author)
Genetic parameters for litter size in Black Slavonian pigs
Energy Technology Data Exchange (ETDEWEB)
Skorput, D.; Gorjanc, G.; Dikic, M.; Lujovic, Z.
2014-06-01
The objective of this study was to estimate genetic parameters for litter size of Black Slavonian pigs using the repeatability, multiple trait, and random regression models, and to consider the possibility to increase litter size in Black Slavonian pigs by selection. A total of 4,733 litter records from the first to the sixth parity from sows that farrowed between January 1998 and December 2010 were included in the analysis. Individual record consisted of the following variables: breeding organisation (eight regions), parity (1-6), service boar, and farrowing season (monthyear interaction). Estimation of all the covariance components with three different models was based on the residual maximum likelihood method. Estimate of additive genetic variance and heritability for number of piglets born alive with repeatability model was 0.23 and 0.10, respectively. Estimates of additive genetic variance with multiple trait and random regression model were in a wider range from 0.05 to 0.65 across parities, and heritabilities were estimated in the range between 0.03 and 0.26. Estimates of phenotypic and additive genetic correlations were much smoother with random regression model in comparison with multiple trait model. Due to unexpected changes of variances along trajectory obtained with multiple trait and random regression model, the best option for genetic evaluation of litter size for now could be the use of repeatability model. With increasing number of data with proper data structure alternative modelling of litter size of Black Slavonian pig using multiple trait and random regression model could be taken into consideration. (Author)
Genetic parameters for litter size in Black Slavonian pigs
Directory of Open Access Journals (Sweden)
Dubravko Skorput
2014-02-01
Full Text Available The objective of this study was to estimate genetic parameters for litter size of Black Slavonian pigs using the repeatability, multiple trait, and random regression models, and to consider the possibility to increase litter size in Black Slavonian pigs by selection. A total of 4733 litter records from the first to the sixth parity from sows that farrowed between January 1998 and December 2010 were included in the analysis. Individual record consisted of the following variables: breeding organisation (eight regions, parity (1-6, service boar, and farrowing season (month-year interaction. Estimation of all the covariance components with three different models was based on the residual maximum likelihood method. Estimate of additive genetic variance and heritability for number of piglets born alive with repeatability model was 0.23 and 0.10, respectively. Estimates of additive genetic variance with multiple trait and random regression model were in a wider range from 0.05 to 0.65 across parities, and heritabilities were estimated in the range between 0.03 and 0.26. Estimates of phenotypic and additive genetic correlations were much smoother with random regression model in comparison with multiple trait model. Due to unexpected changes of variances along trajectory obtained with multiple trait and random regression model, the best option for genetic evaluation of litter size for now could be the use of repeatability model. With increasing number of data with proper data structure alternative modelling of litter size of Black Slavonian pig using multiple trait and random regression model could be taken into consideration.
Genetics and intelligence differences: five special findings
Plomin, R; Deary, I J
2015-01-01
Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for ‘positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century—Genome-wide Complex Trait Analysis (GCTA)—which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic
The Analysis of Polyploid Genetic Data.
Meirmans, Patrick G; Liu, Shenglin; van Tienderen, Peter H
2018-03-16
Though polyploidy is an important aspect of the evolutionary genetics of both plants and animals, the development of population genetic theory of polyploids has seriously lagged behind that of diploids. This is unfortunate since the analysis of polyploid genetic data-and the interpretation of the results-requires even more scrutiny than with diploid data. This is because of several polyploidy-specific complications in segregation and genotyping such as tetrasomy, double reduction, and missing dosage information. Here, we review the theoretical and statistical aspects of the population genetics of polyploids. We discuss several widely used types of inferences, including genetic diversity, Hardy-Weinberg equilibrium, population differentiation, genetic distance, and detecting population structure. For each, we point out how the statistical approach, expected result, and interpretation differ between different ploidy levels. We also discuss for each type of inference what biases may arise from the polyploid-specific complications and how these biases can be overcome. From our overview, it is clear that the statistical toolbox that is available for the analysis of genetic data is flexible and still expanding. Modern sequencing techniques will soon be able to overcome some of the current limitations to the analysis of polyploid data, though the techniques are lagging behind those available for diploids. Furthermore, the availability of more data may aggravate the biases that can arise, and increase the risk of false inferences. Therefore, simulations such as we used throughout this review are an important tool to verify the results of analyses of polyploid genetic data.
Dynamic Mean-Variance Asset Allocation
Basak, Suleyman; Chabakauri, Georgy
2009-01-01
Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in ...
Stocking the genetic supermarket: reproductive genetic technologies and collective action problems.
Gyngell, Chris; Douglas, Thomas
2015-05-01
Reproductive genetic technologies (RGTs) allow parents to decide whether their future children will have or lack certain genetic predispositions. A popular model that has been proposed for regulating access to RGTs is the 'genetic supermarket'. In the genetic supermarket, parents are free to make decisions about which genes to select for their children with little state interference. One possible consequence of the genetic supermarket is that collective action problems will arise: if rational individuals use the genetic supermarket in isolation from one another, this may have a negative effect on society as a whole, including future generations. In this article we argue that RGTs targeting height, innate immunity, and certain cognitive traits could lead to collective action problems. We then discuss whether this risk could in principle justify state intervention in the genetic supermarket. We argue that there is a plausible prima facie case for the view that such state intervention would be justified and respond to a number of arguments that might be adduced against that view. © 2014 The Authors. Bioethics published by John Wiley & Sons Ltd.
Genetic and Environmental Influences on Global Family Conflict
Horwitz, Briana N.; Neiderhiser, Jenae M.; Ganiban, Jody M.; Spotts, Erica L.; Lichtenstein, Paul; Reiss, David
2010-01-01
This study examined genetic and environmental influences on global family conflict. The sample comprised 872 same-sex pairs of twin parents, their spouses/partners and one adolescent child per twin from the Twin and Offspring Study in Sweden (TOSS). The twins, spouses and child each reported on the degree of family conflict, and there was significant agreement among the family members’ ratings. These shared perspectives were explained by one common factor, indexing global family conflict. Genetic influences explained 36% of the variance in this common factor, suggesting that twins’ heritable characteristics contribute to family conflict, via genotype-environment correlation. Nonshared environmental effects explained the remaining 64% of this variance, indicating that twins’ unique childhood and/or current family experiences also play an important role. PMID:20438198
Genetic alterations during radiation-induced carcinogenesis
International Nuclear Information System (INIS)
Kodama, Seiji
1995-01-01
This paper reviews radiation-induced genetic alterations and its carcinogenesis, focusing on the previous in vitro assay outcome. A colony formation assay using Syrian hamster fetal cells and focus formation assay using mouse C3H10T1/2 cells are currently available to find malignant transformation of cells. Such in vitro assays has proposed the hypothesis that radiation-induced carcinogenesis arises from at least two-stage processes; i.e., that an early step induced by irradiation plays an important role in promoting the potential to cause the subsequent mutation. A type of genetic instability induced by radiation results in a persistently elevated frequency of spontaneous mutations, so-called the phenomenon of delayed reproductive death. One possible mechanism by which genetic instability arises has been shown to be due to the development of abnormality in the gene group involved in the maintenance mechanism of genome stability. Another possibility has also been shown to stem from the loss of telomere (the extremities of a chromosome). The importance of search for radiation-induced genetic instability is emphasized in view of the elucidation of carcinogenesis. (N.K.)
The Variance Composition of Firm Growth Rates
Directory of Open Access Journals (Sweden)
Luiz Artur Ledur Brito
2009-04-01
Full Text Available Firms exhibit a wide variability in growth rates. This can be seen as another manifestation of the fact that firms are different from one another in several respects. This study investigated this variability using the variance components technique previously used to decompose the variance of financial performance. The main source of variation in growth rates, responsible for more than 40% of total variance, corresponds to individual, idiosyncratic firm aspects and not to industry, country, or macroeconomic conditions prevailing in specific years. Firm growth, similar to financial performance, is mostly unique to specific firms and not an industry or country related phenomenon. This finding also justifies using growth as an alternative outcome of superior firm resources and as a complementary dimension of competitive advantage. This also links this research with the resource-based view of strategy. Country was the second source of variation with around 10% of total variance. The analysis was done using the Compustat Global database with 80,320 observations, comprising 13,221 companies in 47 countries, covering the years of 1994 to 2002. It also compared the variance structure of growth to the variance structure of financial performance in the same sample.
Directory of Open Access Journals (Sweden)
Antonia Kécya França Moita
2010-07-01
Full Text Available Registros de produção de leite de 754 búfalas da raça Murrah foram utilizados com o objetivo de avaliar o efeito da heterogeneidade de variâncias na avaliação genética. Os componentes de covariância foram estimados pelo método da máxima verossimilhança restrita utilizando-se quatro modelos bicaracterísticos, considerando, como efeitos fixos, estação de parto e rebanho-ano de parto, e idade da vaca como covariável (efeito linear e quadrático. Os quatro modelos utilizados foram: modelo aditivo; modelo de repetibilidade; modelo aditivo com inclusão interação reprodutor x rebanho-ano; modelo de repetibilidade com inclusão da interação reprodutor x rebanho-ano. Os rebanhos foram classificados em duas classes de desvio-padrão fenotípico para produção de leite e análises bicaracterísticas foram realizadas considerando cada classe de desvio-padrão como característica diferente. Foi conduzida também uma análise unicaracterística desconsiderando as classes de desvio-padrão fenotípico, incluindo o efeito da interação reprodutor x rebanho-ano. As estimativas de componentes de variância genética aditiva foram maiores na classe de alto desvio-padrão, comparadas às de baixo desvio-padrão. A maioria dos animais selecionados nos arquivos sem estratificação foi selecionada para alto desvio-padrão. Apesar do aumento nas variâncias aditivas e do erro nas de classes de alto desvio-padrão, suas herdabilidades foram menores, com exceção do modelo 2, cujo herdabilidade foi maior para a classe de alto desvio-padrão. Quando rebanhos são classificados em alto e baixo desvio-padrão fenotípico e a produção de leite nas diferentes classes é avaliada em modelo multicaracterística, a avaliação genética considera a heterogeneidade de variâncias entre rebanhos.Milk yield records of 754 Murrah female buffaloes were used to evaluate the effects of heterogeneity of variance among herds on genetic evaluation. The
Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.
Sztepanacz, Jacqueline L; Blows, Mark W
2017-07-01
The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.
Schenker, Victoria J; Petrill, Stephen A
2015-01-01
This study investigated the genetic and environmental influences on observed associations between listening comprehension, reading motivation, and reading comprehension. Univariate and multivariate quantitative genetic models were conducted in a sample of 284 pairs of twins at a mean age of 9.81 years. Genetic and nonshared environmental factors accounted for statistically significant variance in listening and reading comprehension, and nonshared environmental factors accounted for variance in reading motivation. Furthermore, listening comprehension demonstrated unique genetic and nonshared environmental influences but also had overlapping genetic influences with reading comprehension. Reading motivation and reading comprehension each had unique and overlapping nonshared environmental contributions. Therefore, listening comprehension appears to be related to reading primarily due to genetic factors whereas motivation appears to affect reading via child-specific, nonshared environmental effects. Copyright © 2015 Elsevier Inc. All rights reserved.
Schenker, Victoria J.; Petrill, Stephen A.
2015-01-01
This study investigated the genetic and environmental influences on observed associations between listening comprehension, reading motivation, and reading comprehension. Univariate and multivariate quantitative genetic models were conducted in a sample of 284 pairs of twins at a mean age of 9.81 years. Genetic and nonshared environmental factors accounted for statistically significant variance in listening and reading comprehension, and nonshared environmental factors accounted for variance in reading motivation. Furthermore, listening comprehension demonstrated unique genetic and nonshared environmental influences but also had overlapping genetic influences with reading comprehension. Reading motivation and reading comprehension each had unique and overlapping nonshared environmental contributions. Therefore, listening comprehension appears to be related to reading primarily due to genetic factors whereas motivation appears to affect reading via child-specific, nonshared environmental effects. PMID:26321677
Genetic and environmental effects on body mass index from infancy to the onset of adulthood
DEFF Research Database (Denmark)
Silventoinen, Karri; Jelenkovic, Aline; Sund, Reijo
2016-01-01
BACKGROUND: Both genetic and environmental factors are known to affect body mass index (BMI), but detailed understanding of how their effects differ during childhood and adolescence is lacking. OBJECTIVES: We analyzed the genetic and environmental contributions to BMI variation from infancy...... were based on 383,092 BMI measurements. Variation in BMI was decomposed into genetic and environmental components through genetic structural equation modeling. RESULTS: The variance of BMI increased from 5 y of age along with increasing mean BMI. The proportion of BMI variation explained by additive...... environment was not observed. The sex-specific expression of genetic factors was seen in infancy but was most prominent at 13 y of age and older. The variance of BMI was highest in North America and Australia and lowest in East Asia, but the relative proportion of genetic variation to total variation remained...
Directory of Open Access Journals (Sweden)
Jensen Just
2002-05-01
Full Text Available Abstract In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed or random effects. In the different models, expressions are given (when these can be found – otherwise unbiased estimates are given for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non Gaussian traits are generalisations of the well-known formulas for Gaussian traits – and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part of the model (heritability on the normally distributed level of the model or a generalised version of heritability plays a central role in these formulas.
Genetic structure and diversity of the Neem Germplasm Bank from ...
African Journals Online (AJOL)
Particular
2013-05-15
May 15, 2013 ... ... fragment length polymorphism; AMOVA, molecular variance analysis. ... are technically simple, suitable for large-scale germplasm ... Brazil, our study aims to evaluate the genetic structure and genetic ... voltage of 100 V for 90 min. Gel was .... which does not justify an extra effort in labor (Bekessy et.
Estimating the encounter rate variance in distance sampling
Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.
2009-01-01
The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.
Tour de France Champions born or made: where do we take the genetics of performance?
Moran, Colin N; Pitsiladis, Yannis P
2017-07-01
Cyclists in the Tour de France are endurance specialists. Twin and family studies have shown that approximately 50% of the variance in a number of performance-related phenotypes (whether measured at baseline, i.e., natural talent, or in response to training) including those important to cycling can be explained by genetic variation. Research into the specific genetic variants that are responsible has identified over 200 genes containing common genetic variants involved in the genetic predisposition to physical performance. However, typically these explain only a small portion of the variance, perhaps 1-2% and collectively they rarely explain anything approaching the 50% of the variance identified in the twin and family studies. Thus, there is a gap in our understanding of the relationship between heritability and performance. This gap may be bridged by investigation of rare variants or epigenetic variation or by altering study designs through increased collaborations to pool existing cohorts together. Initial findings from such efforts show promising results. This mini-review will touch on the genetics and epigenetics of sporting performance, how they relate to cyclists in the Tour de France and where best future efforts may be directed as well as discuss some preliminary research findings.
Welch, Allison M; Smith, Michael J; Gerhardt, H Carl
2014-06-01
Genetic variation in sexual displays is crucial for an evolutionary response to sexual selection, but can be eroded by strong selection. Identifying the magnitude and sources of additive genetic variance underlying sexually selected traits is thus an important issue in evolutionary biology. We conducted a quantitative genetics experiment with gray treefrogs (Hyla versicolor) to investigate genetic variances and covariances among features of the male advertisement call. Two energetically expensive traits showed significant genetic variation: call duration, expressed as number of pulses per call, and call rate, represented by its inverse, call period. These two properties also showed significant genetic covariance, consistent with an energetic constraint to call production. Combining the genetic variance-covariance matrix with previous estimates of directional sexual selection imposed by female preferences predicts a limited increase in call duration but no change in call rate despite significant selection on both traits. In addition to constraints imposed by the genetic covariance structure, an evolutionary response to sexual selection may also be limited by high energetic costs of long-duration calls and by preferences that act most strongly against very short-duration calls. Meanwhile, the persistence of these preferences could be explained by costs of mating with males with especially unattractive calls. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.
Towards the ultimate variance-conserving convection scheme
International Nuclear Information System (INIS)
Os, J.J.A.M. van; Uittenbogaard, R.E.
2004-01-01
In the past various arguments have been used for applying kinetic energy-conserving advection schemes in numerical simulations of incompressible fluid flows. One argument is obeying the programmed dissipation by viscous stresses or by sub-grid stresses in Direct Numerical Simulation and Large Eddy Simulation, see e.g. [Phys. Fluids A 3 (7) (1991) 1766]. Another argument is that, according to e.g. [J. Comput. Phys. 6 (1970) 392; 1 (1966) 119], energy-conserving convection schemes are more stable i.e. by prohibiting a spurious blow-up of volume-integrated energy in a closed volume without external energy sources. In the above-mentioned references it is stated that nonlinear instability is due to spatial truncation rather than to time truncation and therefore these papers are mainly concerned with the spatial integration. In this paper we demonstrate that discretized temporal integration of a spatially variance-conserving convection scheme can induce non-energy conserving solutions. In this paper the conservation of the variance of a scalar property is taken as a simple model for the conservation of kinetic energy. In addition, the derivation and testing of a variance-conserving scheme allows for a clear definition of kinetic energy-conserving advection schemes for solving the Navier-Stokes equations. Consequently, we first derive and test a strictly variance-conserving space-time discretization for the convection term in the convection-diffusion equation. Our starting point is the variance-conserving spatial discretization of the convection operator presented by Piacsek and Williams [J. Comput. Phys. 6 (1970) 392]. In terms of its conservation properties, our variance-conserving scheme is compared to other spatially variance-conserving schemes as well as with the non-variance-conserving schemes applied in our shallow-water solver, see e.g. [Direct and Large-eddy Simulation Workshop IV, ERCOFTAC Series, Kluwer Academic Publishers, 2001, pp. 409-287
Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F
2003-11-01
Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.
Stress-induced variation in evolution: from behavioural plasticity to genetic assimilation.
Badyaev, Alexander V
2005-05-07
Extreme environments are closely associated with phenotypic evolution, yet the mechanisms behind this relationship are poorly understood. Several themes and approaches in recent studies significantly further our understanding of the importance that stress-induced variation plays in evolution. First, stressful environments modify (and often reduce) the integration of neuroendocrinological, morphological and behavioural regulatory systems. Second, such reduced integration and subsequent accommodation of stress-induced variation by developmental systems enables organismal 'memory' of a stressful event as well as phenotypic and genetic assimilation of the response to a stressor. Third, in complex functional systems, a stress-induced increase in phenotypic and genetic variance is often directional, channelled by existing ontogenetic pathways. This accounts for similarity among individuals in stress-induced changes and thus significantly facilitates the rate of adaptive evolution. Fourth, accumulation of phenotypically neutral genetic variation might be a common property of locally adapted and complex organismal systems, and extreme environments facilitate the phenotypic expression of this variance. Finally, stress-induced effects and stress-resistance strategies often persist for several generations through maternal, ecological and cultural inheritance. These transgenerational effects, along with both the complexity of developmental systems and stressor recurrence, might facilitate genetic assimilation of stress-induced effects. Accumulation of phenotypically neutral genetic variance by developmental systems and phenotypic accommodation of stress-induced effects, together with the inheritance of stress-induced modifications, ensure the evolutionary persistence of stress-response strategies and provide a link between individual adaptability and evolutionary adaptation.
Evaluation of genetic diversity of Panicum turgidum Forssk from Saudi Arabia.
Assaeed, Abdulaziz M; Al-Faifi, Sulieman A; Migdadi, Hussein M; El-Bana, Magdy I; Al Qarawi, Abdulaziz A; Khan, Mohammad Altaf
2018-01-01
The genetic diversity of 177 accessions of Panicum turgidum Forssk, representing ten populations collected from four geographical regions in Saudi Arabia, was analyzed using amplified fragment length polymorphism (AFLP) markers. A set of four primer-pairs with two/three selective nucleotides scored 836 AFLP amplified fragments (putative loci/genome landmarks), all of which were polymorphic. Populations collected from the southern region of the country showed the highest genetic diversity parameters, whereas those collected from the central regions showed the lowest values. Analysis of molecular variance (AMOVA) revealed that 78% of the genetic variability was attributable to differences within populations. Pairwise values for population differentiation and genetic structure were statistically significant for all variances. The UPGMA dendrogram, validated by principal coordinate analysis-grouped accessions, corresponded to the geographical origin of the accessions. Mantel's test showed that there was a significant correlation between the genetic and geographical distances ( r = 0.35, P < 0.04). In summary, the AFLP assay demonstrated the existence of substantial genetic variation in P. turgidum . The relationship between the genetic diversity and geographical source of P. turgidum populations of Saudi Arabia, as revealed through this comprehensive study, will enable effective resource management and restoration of new areas without compromising adaptation and genetic diversity.
[Genetic diversity of wild Cynodon dactylon germplasm detected by SRAP markers].
Yi, Yang-Jie; Zhang, Xin-Quan; Huang, Lin-Kai; Ling, Yao; Ma, Xiao; Liu, Wei
2008-01-01
Sequence-related amplified polymorphism (SRAP) molecular markers were used to detect the genetic diversity of 32 wild accessions of Cynodon dactylon collected from Sichuan, Chongqing, Guizhou and Tibet, China. The following results were obtained. (1) Fourteen primer pairs produced 132 polymorphic bands, averaged 9.4 bands per primer pair. The percentage of polymorphic bands in average was 79.8%. The Nei's genetic similarity coefficient of the tested accessions ranged from 0.591 to 0.957, and the average Nei's coefficient was 0.759. These results suggested that there was rich genetic diversity among the wild resources of Cynodon dactylon tested. (2) Thirty two wild accessions were clustered into four groups. Moreover, the accessions from the same origin frequently clustered into one group. The findings implied that a correlation among the wild resources, geographical and ecological environment. (3) Genetic differentiation between and within six eco-geographical groups of C. dactylon was estimated by Shannon's diversity index, which showed that 65.56% genetic variance existed within group, and 34.44% genetic variance was among groups. (4) Based on Nei's unbiased measures of genetic identity, UPGMA cluster analysis measures of six eco-geographical groups of Cynodon dactylon, indicated that there was a correlation between genetic differentiation and eco-geographical habits among the groups.
The Distribution of the Sample Minimum-Variance Frontier
Raymond Kan; Daniel R. Smith
2008-01-01
In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us t...
Minimum variance and variance of outgoing quality limit MDS-1(c1, c2) plans
Raju, C.; Vidya, R.
2016-06-01
In this article, the outgoing quality (OQ) and total inspection (TI) of multiple deferred state sampling plans MDS-1(c1,c2) are studied. It is assumed that the inspection is rejection rectification. Procedures for designing MDS-1(c1,c2) sampling plans with minimum variance of OQ and TI are developed. A procedure for obtaining a plan for a designated upper limit for the variance of the OQ (VOQL) is outlined.
The Relationship Between Burnout and Occupational Stress in Genetic Counselors.
Johnstone, Brittney; Kaiser, Amy; Injeyan, Marie C; Sappleton, Karen; Chitayat, David; Stephens, Derek; Shuman, Cheryl
2016-08-01
Burnout represents a critical disruption in an individual's relationship with work, resulting in a state of exhaustion in which one's occupational value and capacity to perform are questioned. Burnout can negatively affect an individual's personal life, as well as employers in terms of decreased work quality, patient/client satisfaction, and employee retention. Occupational stress is a known contributor to burnout and occurs as a result of employment requirements and factors intrinsic to the work environment. Empirical research examining genetic counselor-specific burnout is limited; however, existing data suggests that genetic counselors are at increased risk for burnout. To investigate the relationship between occupational stress and burnout in genetic counselors, we administered an online survey to members of three genetic counselor professional organizations. Validated measures included the Maslach Burnout Inventory-General Survey (an instrument measuring burnout on three subscales: exhaustion, cynicism, and professional efficacy) and the Occupational Stress Inventory-Revised (an instrument measuring occupational stress on 14 subscales). Of the 353 respondents, more than 40 % had either considered leaving or left their job role due to burnout. Multiple regression analysis yielded significant predictors for burnout risk. The identified sets of predictors account for approximately 59 % of the variance in exhaustion, 58 % of the variance in cynicism, and 43 % of the variance in professional efficacy. Our data confirm that a significant number of genetic counselors experience burnout and that burnout is correlated with specific aspects of occupational stress. Based on these findings, practice and research recommendations are presented.
Directory of Open Access Journals (Sweden)
Saudino Kimberly J
2010-12-01
Full Text Available Abstract Background A twin study design was used to assess the degree to which additive genetic variance influences ADHD symptom scores across two ages during infancy. A further objective in the study was to observe whether genetic association with a number of candidate markers reflects results from the quantitative genetic analysis. Method We have studied 312 twin pairs at two time-points, age 2 and age 3. A composite measure of ADHD symptoms from two parent-rating scales: The Child Behavior Checklist/1.5 - 5 years (CBCL hyperactivity scale and the Revised Rutter Parent Scale for Preschool Children (RRPSPC was used for both quantitative and molecular genetic analyses. Results At ages 2 and 3 ADHD symptoms are highly heritable (h2 = 0.79 and 0.78, respectively with a high level of genetic stability across these ages. However, we also observe a significant level of genetic change from age 2 to age 3. There are modest influences of non-shared environment at each age independently (e2 = 0.22 and 0.21, respectively, with these influences being largely age-specific. In addition, we find modest association signals in DAT1 and NET1 at both ages, along with suggestive specific effects of 5-HTT and DRD4 at age 3. Conclusions ADHD symptoms are heritable at ages 2 and 3. Additive genetic variance is largely shared across these ages, although there are significant new effects emerging at age 3. Results from our genetic association analysis reflect these levels of stability and change and, more generally, suggest a requirement for consideration of age-specific genotypic effects in future molecular studies.
Sangnawakij, Patarawan; Böhning, Dankmar; Adams, Stephen; Stanton, Michael; Holling, Heinz
2017-04-30
Statistical inference for analyzing the results from several independent studies on the same quantity of interest has been investigated frequently in recent decades. Typically, any meta-analytic inference requires that the quantity of interest is available from each study together with an estimate of its variability. The current work is motivated by a meta-analysis on comparing two treatments (thoracoscopic and open) of congenital lung malformations in young children. Quantities of interest include continuous end-points such as length of operation or number of chest tube days. As studies only report mean values (and no standard errors or confidence intervals), the question arises how meta-analytic inference can be developed. We suggest two methods to estimate study-specific variances in such a meta-analysis, where only sample means and sample sizes are available in the treatment arms. A general likelihood ratio test is derived for testing equality of variances in two groups. By means of simulation studies, the bias and estimated standard error of the overall mean difference from both methodologies are evaluated and compared with two existing approaches: complete study analysis only and partial variance information. The performance of the test is evaluated in terms of type I error. Additionally, we illustrate these methods in the meta-analysis on comparing thoracoscopic and open surgery for congenital lung malformations and in a meta-analysis on the change in renal function after kidney donation. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Genetic analysis of body weight in South African Angora kids and ...
African Journals Online (AJOL)
Variance and covariance components and ratios pertaining to direct additive genetic variation, maternal additive genetic variation, maternal permanent environmental variation, and the relationship between direct and maternal effects for birth weight (BW; kg), weaning weight (WW; kg) and body weight at 8, 12 and 16 ...
Discrete and continuous time dynamic mean-variance analysis
Reiss, Ariane
1999-01-01
Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...
Jacobson, Kristen C; Hoffman, Christy L; Vasilopoulos, Terrie; Kremen, William S; Panizzon, Matthew S; Grant, Michael D; Lyons, Michael J; Xian, Hong; Franz, Carol E
2012-12-01
There is growing evidence that pet ownership and human-animal interaction (HAI) have benefits for human physical and psychological well-being. However, there may be pre-existing characteristics related to patterns of pet ownership and interactions with pets that could potentially bias results of research on HAI. The present study uses a behavioral genetic design to estimate the degree to which genetic and environmental factors contribute to individual differences in frequency of play with pets among adult men. Participants were from the ongoing longitudinal Vietnam Era Twin Study of Aging (VETSA), a population-based sample of 1,237 monozygotic (MZ) and dizygotic (DZ) twins aged 51-60 years. Results demonstrate that MZ twins have higher correlations than DZ twins on frequency of pet play, suggesting that genetic factors play a role in individual differences in interactions with pets. Structural equation modeling revealed that, according to the best model, genetic factors accounted for as much as 37% of the variance in pet play, although the majority of variance (63-71%) was due to environmental factors that are unique to each twin. Shared environmental factors, which would include childhood exposure to pets, overall accounted for influenced characteristics.
Genetic and environmental sources of individual differences in views on aging.
Kornadt, Anna E; Kandler, Christian
2017-06-01
Views on aging are central psychosocial variables in the aging process, but knowledge about their determinants is still fragmental. Thus, the authors investigated the degree to which genetic and environmental factors contribute to individual differences in various domains of views on aging (wisdom, work, fitness, and family), and whether these variance components vary across ages. They analyzed data from 350 monozygotic and 322 dizygotic twin pairs from the Midlife Development in the U.S. (MIDUS) study, aged 25-74. Individual differences in views on aging were mainly due to individual-specific environmental and genetic effects. However, depending on the domain, genetic and environmental contributions to the variance differed. Furthermore, for some domains, variability was larger for older participants; this was attributable to increases in environmental components. This study extends research on genetic and environmental sources of psychosocial variables and stimulates future studies investigating the etiology of views on aging across the life span. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Strong Genetic Overlap Between Executive Functions and Intelligence
Engelhardt, Laura E.; Mann, Frank D.; Briley, Daniel A.; Church, Jessica A.; Harden, K. Paige; Tucker-Drob, Elliot M.
2016-01-01
Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision-making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic infl...
Revision: Variance Inflation in Regression
Directory of Open Access Journals (Sweden)
D. R. Jensen
2013-01-01
the intercept; and (iv variance deflation may occur, where ill-conditioned data yield smaller variances than their orthogonal surrogates. Conventional VIFs have all regressors linked, or none, often untenable in practice. Beyond these, our models enable the unlinking of regressors that can be unlinked, while preserving dependence among those intrinsically linked. Moreover, known collinearity indices are extended to encompass angles between subspaces of regressors. To reaccess ill-conditioned data, we consider case studies ranging from elementary examples to data from the literature.
Van Hulle, Carol A; Moore, Mollie N; Shirtcliff, Elizabeth A; Lemery-Chalfant, Kathryn; Goldsmith, H Hill
2015-05-01
Although several studies have shown that pubertal tempo and timing are shaped by genetic and environmental factors, few studies consider to what extent endocrine triggers of puberty are shaped by genetic and environmental factors. Doing so moves the field from examining correlated developmentally-sensitive biomarkers toward understanding what drives those associations. Two puberty related hormones, dehydroepiandrosterone and testosterone, were assayed from salivary samples in 118 MZ (62 % female), 111 same sex DZ (46 % female) and 103 opposite-sex DZ twin pairs, aged 12-16 years (M = 13.1, SD = 1.3). Pubertal status was assessed with a composite of mother- and self-reports. We used biometric models to estimate the genetic and environmental influences on the variance and covariance in testosterone and DHEA, with and without controlling for their association with puberty, and to test for sex differences. In males, the variance in testosterone and pubertal status was due to shared and non-shared environmental factors; variation in DHEA was due to genetic and non-shared environmental factors. In females, variance in testosterone was due to genetic and non-shared environmental factors; genetic, shared, and non-shared environmental factors contributed equally to variation in DHEA. In males, the testosterone-DHEA covariance was primarily due to shared environmental factors that overlapped with puberty as well as shared and non-shared environmental covariation specific to testosterone and DHEA. In females, the testosterone-DHEA covariance was due to genetic factors overlapping with pubertal status, and shared and non-shared environmental covariation specific to testosterone and DHEA.
Directory of Open Access Journals (Sweden)
Omnia Gamal El-Dien
2016-03-01
Full Text Available 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.
Genetic Variation in Schizophrenia Liability is Shared With Intellectual Ability and Brain Structure
Bohlken, Marc M; Brouwer, Rachel M; Mandl, René C W; Kahn, René S; Hulshoff Pol, Hilleke E
2016-01-01
BACKGROUND: Alterations in intellectual ability and brain structure are important genetic markers for schizophrenia liability. How variations in these phenotypes interact with variance in schizophrenia liability due to genetic or environmental factors is an area of active investigation. Studying
Variance estimation for generalized Cavalieri estimators
Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen
2011-01-01
The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.
Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study.
Rijsdijk, Frühling V; Vernon, P A; Boomsma, Dorret I
2002-05-01
Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard Progressive test score, collected in 194 18-year-old Dutch twin pairs. We investigated whether first-order group factors possess genetic and environmental variance independent of the higher-order general factor and whether the hierarchical structure is significant for all sources of variance. A hierarchical model with the 3 Cohen group-factors (verbal comprehension, perceptual organisation and freedom-from-distractibility) and a higher-order g factor showed the best fit to the phenotypic data and to additive genetic influences (A), whereas the unique environmental source of variance (E) could be modeled by a single general factor and specifics. There was no evidence for common environmental influences. The covariation among the WAIS group factors and the covariation between the group factors and the Raven is predominantly influenced by a second-order genetic factor and strongly support the notion of a biological basis of g.
Variance components and selection response for feather-pecking behavior in laying hens.
Su, G; Kjaer, J B; Sørensen, P
2005-01-01
Variance components and selection response for feather pecking behavior were studied by analyzing the data from a divergent selection experiment. An investigation indicated that a Box-Cox transformation with power lambda = -0.2 made the data approximately normally distributed and gave the best fit for the model. Variance components and selection response were estimated using Bayesian analysis with Gibbs sampling technique. The total variation was rather large for the investigated traits in both the low feather-pecking line (LP) and the high feather-pecking line (HP). Based on the mean of marginal posterior distribution, in the Box-Cox transformed scale, heritability for number of feather pecking bouts (FP bouts) was 0.174 in line LP and 0.139 in line HP. For number of feather-pecking pecks (FP pecks), heritability was 0.139 in line LP and 0.105 in line HP. No full-sib group effect and observation pen effect were found in the 2 traits. After 4 generations of selection, the total response for number of FP bouts in the transformed scale was 58 and 74% of the mean of the first generation in line LP and line HP, respectively. The total response for number of FP pecks was 47 and 46% of the mean of the first generation in line LP and line HP, respectively. The variance components and the realized selection response together suggest that genetic selection can be effective in minimizing FP behavior. This would be expected to reduce one of the major welfare problems in laying hens.
Multiperiod Mean-Variance Portfolio Optimization via Market Cloning
International Nuclear Information System (INIS)
Ankirchner, Stefan; Dermoune, Azzouz
2011-01-01
The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.
Multiperiod Mean-Variance Portfolio Optimization via Market Cloning
Energy Technology Data Exchange (ETDEWEB)
Ankirchner, Stefan, E-mail: ankirchner@hcm.uni-bonn.de [Rheinische Friedrich-Wilhelms-Universitaet Bonn, Institut fuer Angewandte Mathematik, Hausdorff Center for Mathematics (Germany); Dermoune, Azzouz, E-mail: Azzouz.Dermoune@math.univ-lille1.fr [Universite des Sciences et Technologies de Lille, Laboratoire Paul Painleve UMR CNRS 8524 (France)
2011-08-15
The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.
Genetic evaluation of European quails by random regression models
Directory of Open Access Journals (Sweden)
Flaviana Miranda Gonçalves
2012-09-01
Full Text Available The objective of this study was to compare different random regression models, defined from different classes of heterogeneity of variance combined with different Legendre polynomial orders for the estimate of (covariance of quails. The data came from 28,076 observations of 4,507 female meat quails of the LF1 lineage. Quail body weights were determined at birth and 1, 14, 21, 28, 35 and 42 days of age. Six different classes of residual variance were fitted to Legendre polynomial functions (orders ranging from 2 to 6 to determine which model had the best fit to describe the (covariance structures as a function of time. According to the evaluated criteria (AIC, BIC and LRT, the model with six classes of residual variances and of sixth-order Legendre polynomial was the best fit. The estimated additive genetic variance increased from birth to 28 days of age, and dropped slightly from 35 to 42 days. The heritability estimates decreased along the growth curve and changed from 0.51 (1 day to 0.16 (42 days. Animal genetic and permanent environmental correlation estimates between weights and age classes were always high and positive, except for birth weight. The sixth order Legendre polynomial, along with the residual variance divided into six classes was the best fit for the growth rate curve of meat quails; therefore, they should be considered for breeding evaluation processes by random regression models.
Genetic variance of sunflower yield components - Heliantus annuus L.
Directory of Open Access Journals (Sweden)
Hladni Nada
2003-01-01
Full Text Available The main goals of sunflower breeding in Yugoslavia and abroad are increased seed yield and oil content per unit area and increased resistance to diseases, insects and stress conditions via an optimization of plant architecture. In order to determine the mode of inheritance, gene effects and correlations of total leaf number per plant, total leaf area and plant height, six genetically divergent inbred lines of sunflower were subjected to half diallel crosses. Significant differences in mean values of all the traits were found in the F1 and F2 generations. Additive gene effects were more important in the inheritance of total leaf number per plant and plant height, while in the case of total leaf area per plant the nonadditive ones were more important looking at all the combinations in the F1 and F2 generations. The average degree of dominance (Hi/D1/2 was lower than one for total leaf number per plant and plant height, so the mode of inheritance was partial dominance, while with total leaf area the value was higher than one, indicating super dominance as the mode of inheritance. Significant positive correlation was found: between total leaf area per plant and total leaf number per plant (0.285* and plant height (0.278*. The results of the study are of importance for further sunflower breeding work.
Genetic and Environmental Contributions to Cranial Capacity in Black and White Adolescents.
Rushton, J. Philippe; Osborne, R. Travis
1995-01-01
Data from 236 pairs of black twins and white twins aged 13-17 years were used to examine genetic and environmental factors influencing cranial size, an indirect estimate of brain volume. Genetic factors are required to account for the phenotypic variance in cranial capacity. (SLD)
Individual differences in P300 amplitude: a genetic study in adolescent twins
van Beijsterveldt, C.E.M.; Molenaar, P.C.M.; de Geus, E.J.C.; Boomsma, D.I.
1998-01-01
Using quantitative genetic research designs, we decomposed phenotypic variance in P300 parameters into genetic and environmental components. The twin method was used to carry out this decomposition. Event related potentials (ERPs) were measured during a visual oddball paradigm in a sample of 213
Individual differences in P300 amplitude: A genetic study in adolescent twins.
van Beijsterveld, C.E.M.; Molenaar, P.C.M.; de Geus, E.J.C.; Boomsma, D.I.
1998-01-01
Using quantitative genetic research designs, we decomposed phenotypic variance in P300 parameters into genetic and environmental components. The twin method was used to carry out this decomposition. Event related potentials (ERPs) were measured during a visual oddball paradigm in a sample of 213
Minimum Variance Portfolios in the Brazilian Equity Market
Directory of Open Access Journals (Sweden)
Alexandre Rubesam
2013-03-01
Full Text Available We investigate minimum variance portfolios in the Brazilian equity market using different methods to estimate the covariance matrix, from the simple model of using the sample covariance to multivariate GARCH models. We compare the performance of the minimum variance portfolios to those of the following benchmarks: (i the IBOVESPA equity index, (ii an equally-weighted portfolio, (iii the maximum Sharpe ratio portfolio and (iv the maximum growth portfolio. Our results show that the minimum variance portfolio has higher returns with lower risk compared to the benchmarks. We also consider long-short 130/30 minimum variance portfolios and obtain similar results. The minimum variance portfolio invests in relatively few stocks with low βs measured with respect to the IBOVESPA index, being easily replicable by individual and institutional investors alike.
Segal, N L; Feng, R; McGuire, S A; Allison, D B; Miller, S
2009-01-01
Earlier studies have established that a substantial percentage of variance in obesity-related phenotypes is explained by genetic components. However, only one study has used both virtual twins (VTs) and biological twins and was able to simultaneously estimate additive genetic, non-additive genetic, shared environmental and unshared environmental components in body mass index (BMI). Our current goal was to re-estimate four components of variance in BMI, applying a more rigorous model to biological and virtual multiples with additional data. Virtual multiples share the same family environment, offering unique opportunities to estimate common environmental influence on phenotypes that cannot be separated from the non-additive genetic component using only biological multiples. Data included 929 individuals from 164 monozygotic twin pairs, 156 dizygotic twin pairs, five triplet sets, one quadruplet set, 128 VT pairs, two virtual triplet sets and two virtual quadruplet sets. Virtual multiples consist of one biological child (or twins or triplets) plus one same-aged adoptee who are all raised together since infancy. We estimated the additive genetic, non-additive genetic, shared environmental and unshared random components in BMI using a linear mixed model. The analysis was adjusted for age, age(2), age(3), height, height(2), height(3), gender and race. Both non-additive genetic and common environmental contributions were significant in our model (P-valuesrole in BMI and that common environmental factors such as diet or exercise also affect BMI. This conclusion is consistent with our earlier study using a smaller sample and shows the utility of virtual multiples for separating non-additive genetic variance from common environmental variance.
Why risk is not variance: an expository note.
Cox, Louis Anthony Tony
2008-08-01
Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.
Education reduces the effects of genetic susceptibilities to poor physical health
DEFF Research Database (Denmark)
Johnson, Wendy; Kyvik, Kirsten Ohm; Mortensen, Erik L
2010-01-01
BACKGROUND: Greater education is associated with better physical health. This has been of great concern to public health officials. Most demonstrations show that education influences mean levels of health. Little is known about the influence of education on variance in health status, or about how...... this influence may impact the underlying genetic and environmental sources of health problems. This study explored these influences. METHODS: In a 2002 postal questionnaire, 21 522 members of same-sex pairs in the Danish Twin Registry born between 1931 and 1982 reported physical health in the 12-item Short Form...... Health Survey. We used quantitative genetic models to examine how genetic and environmental variance in physical health differed with level of education, adjusting for birth-year effects. RESULTS: and Conclusions As expected, greater education was associated with better physical health. Greater education...
Genetic Variants Contribute to Gene Expression Variability in Humans
Hulse, Amanda M.; Cai, James J.
2013-01-01
Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and gene expression. Most of these studies focused on the mean of gene expression level, but not the variance of gene expression level (i.e., gene expression variability). In the present study, we systematically explore genome-wide association between genetic variants and gene expression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of gene expression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of gene expression and the genotypes are termed expression variability QTL (evQTL). Using a data set of gene expression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of gene expression variability is discussed. PMID:23150607
Beaver, Kevin M.
2011-01-01
A growing body of empirical research reveals that genetic factors account for a substantial amount of variance in measures of antisocial behaviors. At the same time, evidence is also emerging indicating that certain environmental factors moderate the effects that genetic factors have on antisocial outcomes. Despite this line of research, much…
SCoT marker for the assessment of genetic diversity in saudi arabian date palm cultivars
International Nuclear Information System (INIS)
Qurainy, F.A.; Tarroum, M.
2015-01-01
Different types of molecular markers based on DNA have been used for the assessment of genetic diversity in the plant species. Start Codon Targeted Polymorphism (SCoT) marker has recently become the marker of choice in genetic diversity studies. SCoT marker was used for the assessment of genetic diversity in Saudi Arabian date palm cultivars. The percentage of polymorphic loci (PPL) at population level ranged from 3.28 to 13.11 with an average of 7.10. The Neis gene diversity (h) and Shannons Information index (I) were 0.033 and 0.046, respectively. However, at cultivar level, PPL, Neis gene diversity (h) and Shannons Information index (I) were 42.62, 0.090 and 0.155, respectively. Analysis of molecular variance (AMOVA) showed 48% of variation within the populations, whereas 52% was found among the populations. A hierarchical analysis of molecular variance revealed level of genetic differentiation among populations (52% of total variance, P = 0.001), consistent with the gene differentiation coefficient (Gst = 0.631). Unweighted pair group method of arithmetic averages (UPGMA) cluster analysis of the SCoT marker data divided the six cultivars and their populations into five main clusters at 0.95 genetic similarity coefficient level. (author)
Finkel, Deborah; Franz, Carol E; Horwitz, Briana; Christensen, Kaare; Gatz, Margaret; Johnson, Wendy; Kaprio, Jaako; Korhonen, Tellervo; Niederheiser, Jenae; Petersen, Inge; Rose, Richard J; Silventoinen, Karri
2015-10-14
From the IGEMS Consortium, data were available from 26,579 individuals aged 23 to 102 years on 3 subjective health items: self-rated health (SRH), health compared to others (COMP), and impact of health on activities (ACT). Marital status was a marker of environmental resources that may moderate genetic and environmental influences on subjective health. Results differed for the 3 subjective health items, indicating that they do not tap the same construct. Although there was little impact of marital status on variance components for women, marital status was a significant modifier of variance in all 3 subjective health measures for men. For both SRH and ACT, single men demonstrated greater shared and nonshared environmental variance than married men. For the COMP variable, genetic variance was greater for single men vs. married men. Results suggest gender differences in the role of marriage as a source of resources that are associated with subjective health.
Variance bias analysis for the Gelbard's batch method
Energy Technology Data Exchange (ETDEWEB)
Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)
2014-05-15
In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.
Han, Lide; Yang, Jian; Zhu, Jun
2007-06-01
A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.
Li, Mengjiao; Chen, Jie; Li, Xinying; Deater-Deckard, Kirby
2015-07-01
Affiliation with deviant peers is associated with biologically influenced personal attributes, and is itself a major contributor to growth in antisocial behavior over childhood and adolescence. Several studies have shown that variance in child and adolescent deviant peer affiliation includes genetic and non-genetic influences, but none have examined longitudinal genetic and environmental stability or change within the context of harsh parenting. To address this gap, we tested the moderating role of harsh parenting on genetic and environmental stability or change of deviant peer affiliation in a longitudinal (spanning one and a half years) study of Chinese child and adolescent twin pairs (N = 993, 52.0% female). Using multiple informants (child- and parent-reports) and measurement methods to minimize rater bias, we found that individual differences in deviant peer affiliation at each assessment were similarly explained by moderate genetic and nonshared environmental variance. The longitudinal stability and change of deviant peer affiliation were explained by genetic and nonshared environmental factors. The results also revealed that the genetic variance for deviant peer affiliation is higher in the families with harsher parenting. This amplified genetic risk underscores the role of harsh parenting in the selection and socialization process of deviant peer relationships.
Improved analysis of all-sky meteor radar measurements of gravity wave variances and momentum fluxes
Directory of Open Access Journals (Sweden)
V. F. Andrioli
2013-05-01
Full Text Available The advantages of using a composite day analysis for all-sky interferometric meteor radars when measuring mean winds and tides are widely known. On the other hand, problems arise if this technique is applied to Hocking's (2005 gravity wave analysis for all-sky meteor radars. In this paper we describe how a simple change in the procedure makes it possible to use a composite day in Hocking's analysis. Also, we explain how a modified composite day can be constructed to test its ability to measure gravity wave momentum fluxes. Test results for specified mean, tidal, and gravity wave fields, including tidal amplitudes and gravity wave momentum fluxes varying strongly with altitude and/or time, suggest that the modified composite day allows characterization of monthly mean profiles of the gravity wave momentum fluxes, with good accuracy at least at the altitudes where the meteor counts are large (from 89 to 92.5 km. In the present work we also show that the variances measured with Hocking's method are often contaminated by the tidal fields and suggest a method of empirical correction derived from a simple simulation model. The results presented here greatly increase our confidence because they show that our technique is able to remove the tide-induced false variances from Hocking's analysis.
Integrating Variances into an Analytical Database
Sanchez, Carlos
2010-01-01
For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.
DEFF Research Database (Denmark)
Sahana, Goutam; Janss, Luc; Guldbrandtsen, Bernt
The use of genomic information in genetic evaluation has revolutionized dairy cattle breeding. It remains a major challenge to understand the genetic basis of variation for quantitative traits. Here, we study the genetic architecture for milk, fat, protein, mastitis and fertility indices in dairy...... cattle using NGS variants. The analysis was done using a linear mixed model (LMM) and a Bayesian mixture model (BMM). The top 10 QTL identified by LMM analyses explained 22.61, 23.86, 10.88, 18.58 and 14.83% of the total genetic variance for these traits respectively. Trait-specific sets of 4,964 SNPs...... from NGS variants (most ‘associated’ SNP for each 0.5 Mbp bin) explained 81.0, 81.6, 85.0, 60.4 and 70.9% of total genetic variance for milk, fat, protein, mastitis and fertility indices when analyzed simultaneously by BMM...
Regional sensitivity analysis using revised mean and variance ratio functions
International Nuclear Information System (INIS)
Wei, Pengfei; Lu, Zhenzhou; Ruan, Wenbin; Song, Jingwen
2014-01-01
The variance ratio function, derived from the contribution to sample variance (CSV) plot, is a regional sensitivity index for studying how much the output deviates from the original mean of model output when the distribution range of one input is reduced and to measure the contribution of different distribution ranges of each input to the variance of model output. In this paper, the revised mean and variance ratio functions are developed for quantifying the actual change of the model output mean and variance, respectively, when one reduces the range of one input. The connection between the revised variance ratio function and the original one is derived and discussed. It is shown that compared with the classical variance ratio function, the revised one is more suitable to the evaluation of model output variance due to reduced ranges of model inputs. A Monte Carlo procedure, which needs only a set of samples for implementing it, is developed for efficiently computing the revised mean and variance ratio functions. The revised mean and variance ratio functions are compared with the classical ones by using the Ishigami function. At last, they are applied to a planar 10-bar structure
Genetic diversity, classification and comparative study on the larval ...
African Journals Online (AJOL)
Genetic diversity, classification and comparative study on the larval phenotypic ... B. mori showed different performance based on larval phenotypic data. The analysis of variance regarding the studied traits showed that different strains have ...
DEFF Research Database (Denmark)
Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S
2018-01-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns...... the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes...... in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely...
Family Conflict Interacts with Genetic Liability in Predicting Childhood and Adolescent Depression
Rice, Frances; Harold, Gordon T.; Shelton, Katherine H.; Thapar, Anita
2006-01-01
Objective: To test for gene-environment interaction with depressive symptoms and family conflict. Specifically, to first examine whether the influence of family conflict in predicting depressive symptoms is increased in individuals at genetic risk of depression. Second, to test whether the genetic component of variance in depressive symptoms…
Sex versus asex: An analysis of the role of variance conversion.
Lewis-Pye, Andrew E M; Montalbán, Antonio
2017-04-01
The question as to why most complex organisms reproduce sexually remains a very active research area in evolutionary biology. Theories dating back to Weismann have suggested that the key may lie in the creation of increased variability in offspring, causing enhanced response to selection. Under appropriate conditions, selection is known to result in the generation of negative linkage disequilibrium, with the effect of recombination then being to increase genetic variance by reducing these negative associations between alleles. It has therefore been a matter of significant interest to understand precisely those conditions resulting in negative linkage disequilibrium, and to recognise also the conditions in which the corresponding increase in genetic variation will be advantageous. Here, we prove rigorous results for the multi-locus case, detailing the build up of negative linkage disequilibrium, and describing the long term effect on population fitness for models with and without bounds on fitness contributions from individual alleles. Under the assumption of large but finite bounds on fitness contributions from alleles, the non-linear nature of the effect of recombination on a population presents serious obstacles in finding the genetic composition of populations at equilibrium, and in establishing convergence to those equilibria. We describe techniques for analysing the long term behaviour of sexual and asexual populations for such models, and use these techniques to establish conditions resulting in higher fitnesses for sexually reproducing populations. Copyright © 2017 Elsevier Inc. All rights reserved.
The genotype-environment interaction variance in rice-seed protein determination
International Nuclear Information System (INIS)
Ismachin, M.
1976-01-01
Many environmental factors influence the protein content of cereal seed. This fact procured difficulties in breeding for protein. Yield is another example on which so many environmental factors are of influence. The length of time required by the plant to reach maturity, is also affected by the environmental factors; even though its effect is not too decisive. In this investigation the genotypic variance and the genotype-environment interaction variance which contribute to the total variance or phenotypic variance was analysed, with purpose to give an idea to the breeder how selection should be made. It was found that genotype-environment interaction variance is larger than the genotypic variance in contribution to total variance of protein-seed determination or yield. In the analysis of the time required to reach maturity it was found that genotypic variance is larger than the genotype-environment interaction variance. It is therefore clear, why selection for time required to reach maturity is much easier than selection for protein or yield. Selected protein in one location may be different from that to other locations. (author)
Estimation of measurement variances
International Nuclear Information System (INIS)
Jaech, J.L.
1984-01-01
The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented
Miyo, Takahiro; Oguma, Yuzuru; Charlesworth, Brian
2006-08-01
To elucidate genetic variation in susceptibility to organophosphate insecticides within natural populations of Drosophila melanogaster, we conducted an analysis of variance for mortality data sets of isofemale lines (10-286 lines) used in the previous studies. Susceptibility of isofemale lines to the three organophosphate insecticides was continuously distributed within each natural population, ranging from susceptible to resistant. Analysis of variance showed highly significant variation among isofemale lines in susceptibility to each insecticide for each natural population. Significant genetic variances in susceptibility to the three chemicals were estimated for the Katsunuma population; 0.0529-0.2722 for malathion, 0.0492-0.1603 for prothiophos, and 0.0469-0.1696 for fenitrothion. Contrary to the consistent seasonal tendency towards an increase in mean susceptibility in the fall, reported in the previous study, genetic variances in susceptibility to the three organophosphates did not change significantly in 1997 but tended to increase by 2- to 5-times in 1998. We tested whether both the observed situations, maintenance and increase in genetic variance in organophosphate resistance, can be generated under circumstances in which the levels of resistance to the three organophosphates tended to decrease, by conducting a simulation analysis, based on the hypothesis that resistant genotypes have lower fitnesses than susceptible ones under the density-independent condition. The simulation analysis generally explained the pattern in the mean susceptibility and genetic variances in susceptibility to the three organophosphates, observed in the Katsunuma population of D. melanogaster. It was suggested that the differences in the frequencies of resistance genes in the summer population could affect the patterns in genetic variance in organophosphate resistance in the fall population.
29 CFR 1905.5 - Effect of variances.
2010-07-01
...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...
Realized range-based estimation of integrated variance
DEFF Research Database (Denmark)
Christensen, Kim; Podolskij, Mark
2007-01-01
We provide a set of probabilistic laws for estimating the quadratic variation of continuous semimartingales with the realized range-based variance-a statistic that replaces every squared return of the realized variance with a normalized squared range. If the entire sample path of the process is a...
Experimental game theory and behavior genetics.
Cesarini, David; Dawes, Christopher T; Johannesson, Magnus; Lichtenstein, Paul; Wallace, Björn
2009-06-01
We summarize the findings from a research program studying the heritability of behavior in a number of widely used economic games, including trust, dictator, and ultimatum games. Results from the standard behavior genetic variance decomposition suggest that strategies and fundamental economic preference parameters are moderately heritable, with estimates ranging from 18 to 42%. In addition, we also report new evidence on so-called "hyperfair" preferences in the ultimatum game. We discuss the implications of our findings with special reference to current efforts that seek to understand the molecular genetic architecture of complex social behaviors.
Genetic analysis of some agronomic traits in groundnut (Arachis hypogaea L.
Directory of Open Access Journals (Sweden)
M.K. Alam
2013-12-01
Full Text Available A 10×10 half diallel experiment was conducted on groundnut (Arachis hypogaea L. to ascertain the gene action and genetic parameters of ten traits including 50% flowering, no. of pods per plant, plant height, harvest index, pod index, 100 pod weight, 100 kernel weight, pod size, diseases infection and yield per plot. The experiments were carried out in the Department of Genetics and Plant Breeding, Bangladesh Agricultural University (BAU, Mymensingh during the cropping season of 2010-2011. The estimates of gene effects indicated that significance of both additive and non-additive variance for pod size, 100 pod weight and diseases infection among the traits and presence of over dominance satisfying assumptions of diallel except dormancy. However, both the additive and non-additive gene affects together importance to control of most quantitative traits in the groundnut. The average degree of dominance (H1/D 1/2 (H1 = dominance variance, D = additive variance was higher than one, indicating over dominance for all the traits. The narrow-sense heritability was high for 50% flowering (38%, harvest index (35%, pod size (52%, 100 pod weight (35% and yield per plot (41% indicating that great genetic gain could be achieved for them.
Variance Function Partially Linear Single-Index Models1.
Lian, Heng; Liang, Hua; Carroll, Raymond J
2015-01-01
We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.
Genetics Home Reference: scalp-ear-nipple syndrome
... of the tissues that arise from the ectoderm (ectodermal dysplasia) and leads to the signs and symptoms of ... named? Additional Information & Resources MedlinePlus (2 links) Encyclopedia: Ectodermal dysplasia Health Topic: Skin Conditions Genetic and Rare Diseases ...
Genetic studies on two soybean cultivars irradiated with gamma rays
International Nuclear Information System (INIS)
El-Demerdash, H.M.
2007-01-01
In the present study, the effect of gamma irradiation was used in two Egyptian soybean cultivars; Giza-22 and Giza-82, to induce genetic variability with doses of 100, 150 and 200 Gy. Some agronomic characters were tested in M1 and M2 generations single plants. Oil and protein contents were measured from the resulted mutants of the two soybean cultivars at M2 generation. Some genetic parameters were estimated on the mean values of M2 generation. The results showed significant differences induced by gamma ray doses in all studied characters, particularly for 200 Gy in M1 generation. Gamma irradiation increased the genetic variability in M2 generation, which helped in selecting some high yielding mutants and some mutants with high oil and protein contents from the two cultivars. The estimated coefficients of phenotypic variance as well as coefficient of genotypic variance were high for seeds weight/plant, pod weight/plant, number of seeds/plant, number of pods/plant and number of nods/plant which showed better scope in genetic improvement. Heritability in the broad sense was high in most of the studied characters. The expected genetic advance (G.A) from selection was high for number of seeds, for number of pods, for pods weight and for mature plant height
Wesseldijk, Laura W; Fedko, Iryna O; Bartels, Meike; Nivard, Michel G; van Beijsterveldt, Catharina E M; Boomsma, Dorret I; Middeldorp, Christel M
2017-04-01
The assessment of children's psychopathology is often based on parental report. Earlier studies have suggested that rater bias can affect the estimates of genetic, shared environmental and unique environmental influences on differences between children. The availability of a large dataset of maternal as well as paternal ratings of psychopathology in 7-year old children enabled (i) the analysis of informant effects on these assessments, and (ii) to obtain more reliable estimates of the genetic and non-genetic effects. DSM-oriented measures of affective, anxiety, somatic, attention-deficit/hyperactivity, oppositional-defiant, conduct, and obsessive-compulsive problems were rated for 12,310 twin pairs from the Netherlands Twin Register by mothers (N = 12,085) and fathers (N = 8,516). The effects of genetic and non-genetic effects were estimated on the common and rater-specific variance. For all scales, mean scores on maternal ratings exceeded paternal ratings. Parents largely agreed on the ranking of their child's problems (r 0.60-0.75). The heritability was estimated over 55% for maternal and paternal ratings for all scales, except for conduct problems (44-46%). Unbiased shared environmental influences, i.e., on the common variance, were significant for affective (13%), oppositional (13%), and conduct problems (37%). In clinical settings, different cutoffs for (sub)clinical scores could be applied to paternal and maternal ratings of their child's psychopathology. Only for conduct problems, shared environmental and genetic influences explain an equal amount in differences between children. For the other scales, genetic factors explain the majority of the variance, especially for the common part that is free of rater bias. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley
Primary extradural meningioma arising from the calvarium
Directory of Open Access Journals (Sweden)
N Ravi
2013-06-01
Full Text Available Meningiomas are the most common intracranial tumours. Meningiomas arising at other locations are termed primary extradural meningiomas (EDM and are rare. Here we report a case of EDM arising from the calvarium – a primary calvarial meningioma (PCM.
Individual differences in personality traits reflect structural variance in specific brain regions.
Gardini, Simona; Cloninger, C Robert; Venneri, Annalena
2009-06-30
Personality dimensions such as novelty seeking (NS), harm avoidance (HA), reward dependence (RD) and persistence (PER) are said to be heritable, stable across time and dependent on genetic and neurobiological factors. Recently a better understanding of the relationship between personality traits and brain structures/systems has become possible due to advances in neuroimaging techniques. This Magnetic Resonance Imaging (MRI) study investigated if individual differences in these personality traits reflected structural variance in specific brain regions. A large sample of eighty five young adult participants completed the Three-dimensional Personality Questionnaire (TPQ) and had their brain imaged with MRI. A voxel-based correlation analysis was carried out between individuals' personality trait scores and grey matter volume values extracted from 3D brain scans. NS correlated positively with grey matter volume in frontal and posterior cingulate regions. HA showed a negative correlation with grey matter volume in orbito-frontal, occipital and parietal structures. RD was negatively correlated with grey matter volume in the caudate nucleus and in the rectal frontal gyrus. PER showed a positive correlation with grey matter volume in the precuneus, paracentral lobule and parahippocampal gyrus. These results indicate that individual differences in the main personality dimensions of NS, HA, RD and PER, may reflect structural variance in specific brain areas.
Discrete time and continuous time dynamic mean-variance analysis
Reiss, Ariane
1999-01-01
Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...
CMB-S4 and the hemispherical variance anomaly
O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.
2017-09-01
Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.
Squamous cell carcinoma arising in an odontogenic cyst
International Nuclear Information System (INIS)
Yu, Jae Jung; Hwang, Eui Hwan; Lee, Sang Rae; Choi, Jeong Hee
2003-01-01
Squamous cell carcinoma arising in an odontogenic cyst is uncommon. The diagnosis of carcinoma arising in a cyst requires that there must be an area of microscopic transition from the benign epithelial cyst lining to the invasive squamous cell carcinoma. We report a histopathologically proven case of squamous cell carcinoma arising in a residual mandibular cyst in a 54-year-old woman.
Expected Stock Returns and Variance Risk Premia
DEFF Research Database (Denmark)
Bollerslev, Tim; Zhou, Hao
risk premium with the P/E ratio results in an R2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of "model-free", as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed...
Components of genetic variability of ear length of silage maize
Directory of Open Access Journals (Sweden)
Sečanski Mile
2006-01-01
Full Text Available The objective of this study was to evaluate following parameters of the ear length of silage maize: variability of inbred lines and their diallel hybrids, superior-parent heterosis and genetic components of variability and habitability on the basis of a diallel set. The analysis of genetic variance shows that the additive component (D was lower than the dominant (H1 and H2 genetic variances, while the frequency of dominant genes (u for this trait was greater than the frequency of recessive genes (v Furthermore, this is also confirmed by the dominant to recessive genes ratio in parental inbreeds for the ear length (Kd/Kr> 1, which is greater than unity during both investigation years. The calculated value of the average degree of dominance √H1/D is greater than unity, pointing out to superdominance in inheritance of this trait in both years of investigation, which is also confirmed by the results of Vr/Wr regression analysis of inheritance of the ear length. As a presence of the non-allelic interaction was established it is necessary to study effects of epitasis as it can have a greater significance in certain hybrids. A greater value of dominant than additive variance resulted in high broad-sense habitability for ear length in both investigation years.
Allowable variance set on left ventricular function parameter
International Nuclear Information System (INIS)
Zhou Li'na; Qi Zhongzhi; Zeng Yu; Ou Xiaohong; Li Lin
2010-01-01
Purpose: To evaluate the influence of allowable Variance settings on left ventricular function parameter of the arrhythmia patients during gated myocardial perfusion imaging. Method: 42 patients with evident arrhythmia underwent myocardial perfusion SPECT, 3 different allowable variance with 20%, 60%, 100% would be set before acquisition for every patients,and they will be acquired simultaneously. After reconstruction by Astonish, end-diastole volume(EDV) and end-systolic volume (ESV) and left ventricular ejection fraction (LVEF) would be computed with Quantitative Gated SPECT(QGS). Using SPSS software EDV, ESV, EF values of analysis of variance. Result: there is no statistical difference between three groups. Conclusion: arrhythmia patients undergo Gated myocardial perfusion imaging, Allowable Variance settings on EDV, ESV, EF value does not have a statistical meaning. (authors)
Directory of Open Access Journals (Sweden)
G. R. Pasha
2006-07-01
Full Text Available In this paper, we present that how much the variances of the classical estimators, namely, maximum likelihood estimator and moment estimator deviate from the minimum variance bound while estimating for the Maxwell distribution. We also sketch this difference for the negative integer moment estimator. We note the poor performance of the negative integer moment estimator in the said consideration while maximum likelihood estimator attains minimum variance bound and becomes an attractive choice.
Directory of Open Access Journals (Sweden)
Poivey Jean-Paul
2011-09-01
Full Text Available Abstract Background The pre-weaning growth rate of lambs, an important component of meat market production, is affected by maternal and direct genetic effects. The French genetic evaluation model takes into account the number of lambs suckled by applying a multiplicative factor (1 for a lamb reared as a single, 0.7 for twin-reared lambs to the maternal genetic effect, in addition to including the birth*rearing type combination as a fixed effect, which acts on the mean. However, little evidence has been provided to justify the use of this multiplicative model. The two main objectives of the present study were to determine, by comparing models of analysis, 1 whether pre-weaning growth is the same trait in single- and twin-reared lambs and 2 whether the multiplicative coefficient represents a good approach for taking this possible difference into account. Methods Data on the pre-weaning growth rate, defined as the average daily gain from birth to 45 days of age on 29,612 Romane lambs born between 1987 and 2009 at the experimental farm of La Sapinière (INRA-France were used to compare eight models that account for the number of lambs per dam reared in various ways. Models were compared using the Akaike information criteria. Results The model that best fitted the data assumed that 1 direct (maternal effects correspond to the same trait regardless of the number of lambs reared, 2 the permanent environmental effects and variances associated with the dam depend on the number of lambs reared and 3 the residual variance depends on the number of lambs reared. Even though this model fitted the data better than a model that included a multiplicative coefficient, little difference was found between EBV from the different models (the correlation between EBV varied from 0.979 to 0.999. Conclusions Based on experimental data, the current genetic evaluation model can be improved to better take into account the number of lambs reared. Thus, it would be of
Towards a mathematical foundation of minimum-variance theory
Energy Technology Data Exchange (ETDEWEB)
Feng Jianfeng [COGS, Sussex University, Brighton (United Kingdom); Zhang Kewei [SMS, Sussex University, Brighton (United Kingdom); Wei Gang [Mathematical Department, Baptist University, Hong Kong (China)
2002-08-30
The minimum-variance theory which accounts for arm and eye movements with noise signal inputs was proposed by Harris and Wolpert (1998 Nature 394 780-4). Here we present a detailed theoretical analysis of the theory and analytical solutions of the theory are obtained. Furthermore, we propose a new version of the minimum-variance theory, which is more realistic for a biological system. For the new version we show numerically that the variance is considerably reduced. (author)
Solitary Fibrous Tumor Arising from Stomach: CT Findings
Park, Sung Hee; Kwon, Jieun; Park, Jong-pil; Park, Mi-Suk; Lim, Joon Seok; Kim, Joo Hee; Kim, Ki Whang
2007-01-01
Solitary fibrous tumors are spindle-cell neoplasms that usually develop in the pleura and peritoneum, and rarely arise in the stomach. To our knowledge, there is only one case reporting a solitary fibrous tumor arising from stomach in the English literature. Here we report the case of a 26-year-old man with a large solitary fibrous tumor arising from the stomach which involved the submucosa and muscular layer and resembled a gastrointestinal stromal tumor in the stomach, based on what was seen during abdominal computed tomography. A solitary fibrous tumor arising from the stomach, although rare, could be considered as a diagnostic possibility for gastric submucosal tumors. PMID:18159603
Direct encoding of orientation variance in the visual system.
Norman, Liam J; Heywood, Charles A; Kentridge, Robert W
2015-01-01
Our perception of regional irregularity, an example of which is orientation variance, seems effortless when we view two patches of texture that differ in this attribute. Little is understood, however, of how the visual system encodes a regional statistic like orientation variance, but there is some evidence to suggest that it is directly encoded by populations of neurons tuned broadly to high or low levels. The present study shows that selective adaptation to low or high levels of variance results in a perceptual aftereffect that shifts the perceived level of variance of a subsequently viewed texture in the direction away from that of the adapting stimulus (Experiments 1 and 2). Importantly, the effect is durable across changes in mean orientation, suggesting that the encoding of orientation variance is independent of global first moment orientation statistics (i.e., mean orientation). In Experiment 3 it was shown that the variance-specific aftereffect did not show signs of being encoded in a spatiotopic reference frame, similar to the equivalent aftereffect of adaptation to the first moment orientation statistic (the tilt aftereffect), which is represented in the primary visual cortex and exists only in retinotopic coordinates. Experiment 4 shows that a neuropsychological patient with damage to ventral areas of the cortex but spared intact early areas retains sensitivity to orientation variance. Together these results suggest that orientation variance is encoded directly by the visual system and possibly at an early cortical stage.
Directory of Open Access Journals (Sweden)
Maria Gabriela Campolina Diniz Peixoto
2014-05-01
Full Text Available The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524 of test-day milk yield (TDMY from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects, whereas the contemporary group, calving age (linear and quadratic effects and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.
Network Structure and Biased Variance Estimation in Respondent Driven Sampling.
Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J
2015-01-01
This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.
Behavioral and environmental modification of the genetic influence on body mass index: A twin study
Horn, Erin E.; Turkheimer, Eric; Strachan, Eric; Duncan, Glen E.
2015-01-01
Body mass index (BMI) has a strong genetic basis, with a heritability around 0.75, but is also influenced by numerous behavioral and environmental factors. Aspects of the built environment (e.g., environmental walkability) are hypothesized to influence obesity by directly affecting BMI, by facilitating or inhibiting behaviors such as physical activity that are related to BMI, or by suppressing genetic tendencies toward higher BMI. The present study investigated relative influences of physical activity and walkability on variance in BMI using 5,079 same-sex adult twin pairs (70% monozygotic, 65% female). High activity and walkability levels independently suppressed genetic variance in BMI. Estimating their effects simultaneously, however, suggested that the walkability effect was mediated by activity. The suppressive effect of activity on variance in BMI was present even with a tendency for low-BMI individuals to select into environments that require higher activity levels. Overall, our results point to community- or macro-level interventions that facilitate individual-level behaviors as a plausible approach to addressing the obesity epidemic among U.S. adults. PMID:25894925
Estimation of genetic parameters related to eggshell strength using random regression models.
Guo, J; Ma, M; Qu, L; Shen, M; Dou, T; Wang, K
2015-01-01
This study examined the changes in eggshell strength and the genetic parameters related to this trait throughout a hen's laying life using random regression. The data were collected from a crossbred population between 2011 and 2014, where the eggshell strength was determined repeatedly for 2260 hens. Using random regression models (RRMs), several Legendre polynomials were employed to estimate the fixed, direct genetic and permanent environment effects. The residual effects were treated as independently distributed with heterogeneous variance for each test week. The direct genetic variance was included with second-order Legendre polynomials and the permanent environment with third-order Legendre polynomials. The heritability of eggshell strength ranged from 0.26 to 0.43, the repeatability ranged between 0.47 and 0.69, and the estimated genetic correlations between test weeks was high at > 0.67. The first eigenvalue of the genetic covariance matrix accounted for about 97% of the sum of all the eigenvalues. The flexibility and statistical power of RRM suggest that this model could be an effective method to improve eggshell quality and to reduce losses due to cracked eggs in a breeding plan.
Local variances in biomonitoring
International Nuclear Information System (INIS)
Wolterbeek, H.Th; Verburg, T.G.
2001-01-01
The present study was undertaken to explore possibilities to judge survey quality on basis of a limited and restricted number of a-priori observations. Here, quality is defined as the ratio between survey and local variance (signal-to-noise ratio). The results indicate that the presented surveys do not permit such judgement; the discussion also suggests that the 5-fold local sampling strategies do not merit any sound judgement. As it stands, uncertainties in local determinations may largely obscure possibilities to judge survey quality. The results further imply that surveys will benefit from procedures, controls and approaches in sampling and sample handling, to assess both average, variance and the nature of the distribution of elemental concentrations in local sites. This reasoning is compatible with the idea of the site as a basic homogeneous survey unit, which is implicitly and conceptually underlying any survey performed. (author)
A pattern recognition approach to transistor array parameter variance
da F. Costa, Luciano; Silva, Filipi N.; Comin, Cesar H.
2018-06-01
The properties of semiconductor devices, including bipolar junction transistors (BJTs), are known to vary substantially in terms of their parameters. In this work, an experimental approach, including pattern recognition concepts and methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), was used to experimentally investigate the variation among BJTs belonging to integrated circuits known as transistor arrays. It was shown that a good deal of the devices variance can be captured using only two PCA axes. It was also verified that, though substantially small variation of parameters is observed for BJT from the same array, larger variation arises between BJTs from distinct arrays, suggesting the consideration of device characteristics in more critical analog designs. As a consequence of its supervised nature, LDA was able to provide a substantial separation of the BJT into clusters, corresponding to each transistor array. In addition, the LDA mapping into two dimensions revealed a clear relationship between the considered measurements. Interestingly, a specific mapping suggested by the PCA, involving the total harmonic distortion variation expressed in terms of the average voltage gain, yielded an even better separation between the transistor array clusters. All in all, this work yielded interesting results from both semiconductor engineering and pattern recognition perspectives.
Genetic diversity in natural populations of Buriti (Mauritia flexuosa L. f.
Directory of Open Access Journals (Sweden)
Liene Rocha Picanço Gomes
2011-01-01
Full Text Available This study aimed to characterize the genetic diversity of buriti populations by AFLP (Amplified Fragment LengthPolymorphism markers. The analysis was performed in four populations used by traditional communities in the state of Amazonia(Bom Jesus do Anamã, Lauro Sodré, Santa Luzia do Buiçuzinho, and Esperança II. From each population 30 plants wererandomly selected. To obtain the markers four primer combinations were used. The percentage of polymorphic loci was estimated,the molecular variance among and within populations analyzed and a dendrogram constructed. The primers detected 339 polymorphicloci ranging from 81.1 % to 91.1 % among populations. Analysis of molecular variance attributed 77.18 % to variation within and22.8 % to variation between populations. The dendrogram indicated the formation of two groups, showing that the populations ofBom Jesus do Anamã and Lauro Sodré are genetically most similar and thet the genetic and geographical distances are notcorrelated.
DEFF Research Database (Denmark)
Busch, Alexander S; Hagen, Casper P; Main, Katharina M
2017-01-01
Context: Although genetic factors play a pivotal role in male pubertal timing, genome-wide association studies have identified only a few loci. Genetic variation of follicle-stimulating hormone (FSH) action affects adult reproductive parameters and female pubertal timing. Objective: To investigate...... effective FSH action. Effects explained 1.7% (Denmark) and 1.5% (Chile) of the variance. In addition, BMI z score was negatively associated with pubertal timing (β = -0.35 years in both cohorts), explaining 17.2% (Denmark) and 7.2% (Chile) of the variance. Conclusion: In two ethnically distinct populations...
Genetic differentiation and gene flow between the Tunisian ovine ...
African Journals Online (AJOL)
Haifa
Sheep is an important livestock species of Tunisia. They contribute greatly ... Genetic differentiation coefficient (Gst) over all loci was 0.1922, the fixation index [Fst by Analysis of molecular variance ..... their first cross with the D'Man. Anim. Res.
Routledge, Kylie M; Burton, Karen L O; Williams, Leanne M; Harris, Anthony; Schofield, Peter R; Clark, C Richard; Gatt, Justine M
2016-10-30
Mental wellbeing and mental illness symptoms are typically conceptualized as opposite ends of a continuum, despite only sharing about a quarter in common variance. We investigated the normative variation in measures of wellbeing and of depression and anxiety in 1486 twins who did not meet clinical criteria for an overt diagnosis. We quantified the shared versus distinct genetic and environmental variance between wellbeing and depression and anxiety symptoms. The majority of participants (93%) reported levels of depression and anxiety symptoms within the healthy range, yet only 23% reported a wellbeing score within the "flourishing" range: the remainder were within the ranges of "moderate" (67%) or "languishing" (10%). In twin models, measures of wellbeing and of depression and anxiety shared 50.09% of variance due to genetic factors and 18.27% due to environmental factors; the rest of the variance was due to unique variation impacting wellbeing or depression and anxiety symptoms. These findings suggest that an absence of clinically-significant symptoms of depression and anxiety does not necessarily indicate that an individual is flourishing. Both unique and shared genetic and environmental factors may determine why some individuals flourish in the absence of symptoms while others do not. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
The quantitative genetics of phenotypic variation in animals
Hill, W.G.; Mulder, H.A.; Zhang, X.S.
2007-01-01
Considerable attention has been paid to estimating genetic variability in quantitative traits and to how it is maintained and changed by selection in natural and domesticated populations, but rather little attention has been paid to how levels of environmental and phenotypic variance are influenced.
Some variance reduction methods for numerical stochastic homogenization.
Blanc, X; Le Bris, C; Legoll, F
2016-04-28
We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).
Potato breeding cycles typically last 6-7 years because of the modest seed multiplication rate and large number of traits required of new varieties. Genomic selection has the potential to increase genetic gain per unit of time, through higher accuracy and/or a shorter cycle. Both possibilities were ...
Restricted Variance Interaction Effects
DEFF Research Database (Denmark)
Cortina, Jose M.; Köhler, Tine; Keeler, Kathleen R.
2018-01-01
Although interaction hypotheses are increasingly common in our field, many recent articles point out that authors often have difficulty justifying them. The purpose of this article is to describe a particular type of interaction: the restricted variance (RV) interaction. The essence of the RV int...
Variance Swaps in BM&F: Pricing and Viability of Hedge
Directory of Open Access Journals (Sweden)
Richard John Brostowicz Junior
2010-07-01
Full Text Available A variance swap can theoretically be priced with an infinite set of vanilla calls and puts options considering that the realized variance follows a purely diffusive process with continuous monitoring. In this article we willanalyze the possible differences in pricing considering discrete monitoring of realized variance. It will analyze the pricing of variance swaps with payoff in dollars, since there is a OTC market that works this way and thatpotentially serve as a hedge for the variance swaps traded in BM&F. Additionally, will be tested the feasibility of hedge of variance swaps when there is liquidity in just a few exercise prices, as is the case of FX optionstraded in BM&F. Thus be assembled portfolios containing variance swaps and their replicating portfolios using the available exercise prices as proposed in (DEMETERFI et al., 1999. With these portfolios, the effectiveness of the hedge was not robust in mostly of tests conducted in this work.
Genetic Properties of Some Economic Traits in Isfahan Native Fowl Using Bayesian and REML Methods
Directory of Open Access Journals (Sweden)
Salehinasab M
2015-12-01
Full Text Available The objective of the present study was to estimate heritability values for some performance and egg quality traits of native fowl in Isfahan breeding center using REML and Bayesian approaches. The records were about 51521 and 975 for performance and egg quality traits, respectively. At the first step, variance components were estimated for body weight at hatch (BW0, body weight at 8 weeks of age (BW8, weight at sexual maturity (WSM, egg yolk weight (YW, egg Haugh unit and eggshell thickness, via REML approach using ASREML software. At the second step, the same traits were analyzed via Bayesian approach using Gibbs3f90 software. In both approaches six different animal models were applied and the best model was determined using likelihood ratio test (LRT and deviance information criterion (DIC for REML and Bayesian approaches, respectively. Heritability estimates for BW0, WSM and ST were the same in both approaches. For BW0, LRT and DIC indexes confirmed that the model consisting maternal genetic, permanent environmental and direct genetic effects was significantly better than other models. For WSM, a model consisting of maternal permanent environmental effect in addition to direct genetic effect was the best. For shell thickness, the basic model consisting direct genetic effect was the best. The results for BW8, YW and Haugh unit, were different between the two approaches. The reason behind this tiny differences was that the convergence could not be achieved for some models in REML approach and thus for these traits the Bayesian approach estimated the variance components more accurately. The results indicated that ignoring maternal effects, overestimates the direct genetic variance and heritability for most of the traits. Also, the Bayesian-based software could take more variance components into account.
Genetic influences on level and stability of self-esteem
Neiss, Michelle; Sedikides, Constantine; Stevenson, Jim
2006-01-01
We attempted to clarify the relation between self-esteem level (high vs. low) and perceived self-esteem stability (within-person variability) by using a behavioral genetics approach. We tested whether the same or independent genetic and environmental influences impact on level and stability. Adolescent twin siblings (n = 183 pairs) completed level and stability scales at two time points. Heritability for both was substantial. The remaining variance in each was attributable to non-shared envir...
Wilms tumor arising in extracoelomic paravertebral soft tissues.
LENUS (Irish Health Repository)
Mulligan, Linda
2012-02-01
Extrarenal Wilms tumor (ERWT) is a well-established entity which most commonly arises within the genitourinary tract, including intracoelomic paranephric soft tissue. Rarely, ERWT arises within teratoma, and it tends to occur predominantly in distinct settings, such as females with spinal defects and males with testicular teratomas. We report a unique ERWT arising within an extracoelomic teratoma of the paraspinal musculature, thereby expanding the range of reported locations for this unusual tumor.
Integrating mean and variance heterogeneities to identify differentially expressed genes.
Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen
2016-12-06
In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment
Simultaneous Monte Carlo zero-variance estimates of several correlated means
International Nuclear Information System (INIS)
Booth, T.E.
1998-01-01
Zero-variance biasing procedures are normally associated with estimating a single mean or tally. In particular, a zero-variance solution occurs when every sampling is made proportional to the product of the true probability multiplied by the expected score (importance) subsequent to the sampling; i.e., the zero-variance sampling is importance weighted. Because every tally has a different importance function, a zero-variance biasing for one tally cannot be a zero-variance biasing for another tally (unless the tallies are perfectly correlated). The way to optimize the situation when the required tallies have positive correlation is shown
Variance estimation in the analysis of microarray data
Wang, Yuedong
2009-04-01
Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.
Estimates of genetic parameters of body weight in descendants of x-irradiated rat spermatogonia
International Nuclear Information System (INIS)
Gianola, D.; Chapman, A.B.; Rutledge, J.J.
1977-01-01
Effects of nine generations of 450 R per generation of ancestral spermatogonial x irradiation of inbred rats on genetic parameters of body weight at 3, 6 and 10 weeks of age and of weight gains between these periods were studied. Covariances among relatives were estimated by mixed model and regression techniques in randomly selected lines with (R) and without (C) radiation history. Analyses of the data were based on five linear genetic models combining additive direct, additive indirect (maternal), dominance and environmental effects. Parameters in these models were estimated by generalized least-squares. A model including direct and indirect genetic effects fit more closely to the data in both R and C lines. Overdominance of induced mutations did not seem to be present. Ancestral irradiation increased maternal additive genetic variances of body weights and gains but not direct genetic variances. Theoretically, due to a negative direct-maternal genetic correlation, within full-sib family selection would be ineffective in increasing body weight at six weeks in both R and C lines. However, progress from mass selection would be expected to be faster in the R lines
A Genetic Epidemiological Mega Analysis of Smoking Initiation in Adolescents.
Maes, Hermine H; Prom-Wormley, Elizabeth; Eaves, Lindon J; Rhee, Soo Hyun; Hewitt, John K; Young, Susan; Corley, Robin; McGue, Matt; Iacono, William G; Legrand, Lisa; Samek, Diana R; Murrelle, E Lenn; Silberg, Judy L; Miles, Donna R; Schieken, Richard M; Beunen, Gaston P; Thomis, Martine; Rose, Richard J; Dick, Danielle M; Boomsma, Dorret I; Bartels, Meike; Vink, Jacqueline M; Lichtenstein, Paul; White, Victoria; Kaprio, Jaakko; Neale, Michael C
2017-04-01
Previous studies in adolescents were not adequately powered to accurately disentangle genetic and environmental influences on smoking initiation (SI) across adolescence. Mega-analysis of pooled genetically informative data on SI was performed, with structural equation modeling, to test equality of prevalence and correlations across cultural backgrounds, and to estimate the significance and effect size of genetic and environmental effects according to the classical twin study, in adolescent male and female twins from same-sex and opposite-sex twin pairs (N = 19 313 pairs) between ages 10 and 19, with 76 358 longitudinal assessments between 1983 and 2007, from 11 population-based twin samples from the United States, Europe, and Australia. Although prevalences differed between samples, twin correlations did not, suggesting similar etiology of SI across developed countries. The estimate of additive genetic contributions to liability of SI increased from approximately 15% to 45% from ages 13 to 19. Correspondingly, shared environmental factors accounted for a substantial proportion of variance in liability to SI at age 13 (70%) and gradually less by age 19 (40%). Both additive genetic and shared environmental factors significantly contribute to variance in SI throughout adolescence. The present study, the largest genetic epidemiological study on SI to date, found consistent results across 11 studies for the etiology of SI. Environmental factors, especially those shared by siblings in a family, primarily influence SI variance in early adolescence, while an increasing role of genetic factors is seen at later ages, which has important implications for prevention strategies. This is the first study to find evidence of genetic factors in liability to SI at ages as young as 12. It also shows the strongest evidence to date for decay of effects of the shared environment from early adolescence to young adulthood. We found remarkable consistency of twin correlations across
Esophageal leiomyoma arising in an epiphrenic diverticulum
International Nuclear Information System (INIS)
Hamilton, S.
1988-01-01
A 32-year old woman was found at surgery to have an esophageal leiomyoma arising within an epiphrenic diverticulum. These uncommon conditions may rarely occur together, causing difficulty in diagnosis of the leiomyoma. Other neoplasms may also arise in an epiphrenic diverticulum and should be borne in mind in this situation. (orig.)
The capture of heritable variation for genetic quality through social competition.
Wolf, Jason B; Harris, W Edwin; Royle, Nick J
2008-09-01
In theory, females of many species choose mates based on traits that are indicators of male genetic quality. A fundamental question in evolutionary biology is why genetic variation for such indicator traits persists despite strong persistent selection imposed by female preference, which is known as the lek paradox. One potential solution to the lek paradox suggests that the traits that are targets of mate choice should evolve condition-dependent expression and that condition should have a large genetic variance. Condition is expected to exhibit high genetic variance because it is affected by a large number of physiological processes and hence, condition-dependent traits should 'capture' variation contributed by a large number of loci. We suggest that a potentially important cause of variation in condition is competition for limited resources. Here, we discuss a pair of models to analyze the evolutionary genetics of traits affected by success in social competition for resources. We show that competition can contribute to genetic variation of 'competition-dependent' traits that have fundamentally different evolutionary properties than other sources of variation. Competition dependence can make traits honest indicators of genetic quality by revealing the relative competitive ability of males, can provide a component of heritable variation that does not contribute to trait evolution, and can help maintain heritable variation under directional selection. Here we provide a general introduction to the concept of competition dependence and briefly introduce two models to demonstrate the potential evolutionary consequences of competition-dependent trait expression.
Behavioral genetics and criminal responsibility at the courtroom.
Tatarelli, Roberto; Del Casale, Antonio; Tatarelli, Caterina; Serata, Daniele; Rapinesi, Chiara; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo
2014-04-01
Several questions arise from the recent use of behavioral genetic research data in the courtroom. Ethical issues concerning the influence of biological factors on human free will, must be considered when specific gene patterns are advocated to constrain court's judgment, especially regarding violent crimes. Aggression genetics studies are both difficult to interpret and inconsistent, hence, in the absence of a psychiatric diagnosis, genetic data are currently difficult to prioritize in the courtroom. The judge's probabilistic considerations in formulating a sentence must take into account causality, and the latter cannot be currently ensured by genetic data. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Variance computations for functional of absolute risk estimates.
Pfeiffer, R M; Petracci, E
2011-07-01
We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.
76 FR 78698 - Proposed Revocation of Permanent Variances
2011-12-19
... Administration (``OSHA'' or ``the Agency'') granted permanent variances to 24 companies engaged in the... DEPARTMENT OF LABOR Occupational Safety and Health Administration [Docket No. OSHA-2011-0054] Proposed Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA...
Kandler, Christian; Bleidorn, Wiebke; Riemann, Rainer
2012-03-01
In this study, we used an extended twin family design to investigate the influences of genetic and cultural transmission as well as different sources of nonrandom mating on 2 core aspects of political orientation: acceptance of inequality and rejecting system change. In addition, we studied the sources of phenotypic links between Big Five personality traits and political beliefs using self- and other reports. Data of 1,992 individuals (224 monozygotic and 166 dizygotic twin pairs, 92 unmatched twins, 530 spouses of twins, 268 fathers, and 322 mothers) were analyzed. Genetically informative analyses showed that political attitudes are genetically but not environmentally transmitted from parents to offspring and that a substantial proportion of this genetic variance can be accounted for by genetic variance in personality traits. Beyond genetic effects and genotypic assortative mating, generation-specific environmental sources act to increase twins' and spouses' resemblance in political beliefs. The results suggest multiple sources of political orientations in a modern democracy.
Directory of Open Access Journals (Sweden)
Ajay Singh
2016-06-01
Full Text Available 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.
Directory of Open Access Journals (Sweden)
Siti Hidayati
2015-05-01
Full Text Available The aims of this study were (1 to analyze the phenotypic performance of Ettawa Grade (EG goat; (2to estimate the heritability of birth weight (BW, weaning weight (WW, yearling weight (YW, and geneticcorrelation between two body weights on the third different period; and (3 to analyze the variance andcovariance component of body weight. The material used were the exiting records of 437 EG goats in BalaiPembibitan Ternak Unggul dan Hijauan Pakan Ternak Pelaihari, South Kalimantan. These goats originatedfrom the crossing between 19 males and 216 females from periods of 2009 - 2012. Nested Design methodwas used to etimate the phenotypic correlation, heritability and genetic correlation. Variance componentswere determined from heritability estimation, while covariance components were determined from geneticcerrelation estimation. Phenotypic correlation between BW and WW, between BW and YW, and betweenWW and YW were 0.19 (low; 0.31 (medium; 0.65 (high; respectively. Heritability of BW, WW, and YW were0.43±0.23 (high; WW 0.27±0.19 (medium; and YW 1.01±0.38 (excludeof the h2 value, respectively.Genetic correlation between BW and WW, between BW and YW, and between WW and YW were -0.04(negative low; 0.49 (positive medium; and -0.41 (negative medium, respectively. Variance components ofbuck, ewes, and kid for BW were 10.76%; 37.16%; and 52.09%, respectively, for WW were 6.67%; 38.52%;and 54.81%, respectively, and for YW were 25.15%; 58.37%; and 16.43%, respectively. Covariancecomponents of buck, ewes, and kid between BW and WW were -3.91%; 66.45%; and 37.46%, respectively,between BW and YW were 65.68%; 16.50%; and 17.82, and between WW and YW were -5.14%; 83.87%; and21.28%, respectively. In conclusions variance component of ewes and kid were high in body weight at birthand weaning time. Therefore, selection should be conducted for body weight at birth and weaning time.
Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore
2013-11-01
Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
Diagnostic checking in linear processes with infinit variance
Krämer, Walter; Runde, Ralf
1998-01-01
We consider empirical autocorrelations of residuals from infinite variance autoregressive processes. Unlike the finite-variance case, it emerges that the limiting distribution, after suitable normalization, is not always more concentrated around zero when residuals rather than true innovations are employed.
DEFF Research Database (Denmark)
Li, Shuxia; Kyvik, Kirsten Ohm; Duan, Haiping
2016-01-01
twin study on long-term stability of metabolic phenotypes in Danish and Chinese twins identified a common pattern of high genetic control over phenotype conservation, and at the same time revealed population-specific patterns of genetic and common environmental regulation on the variance as well...
Soave, David; Sun, Lei
2017-09-01
We generalize Levene's test for variance (scale) heterogeneity between k groups for more complex data, when there are sample correlation and group membership uncertainty. Following a two-stage regression framework, we show that least absolute deviation regression must be used in the stage 1 analysis to ensure a correct asymptotic χk-12/(k-1) distribution of the generalized scale (gS) test statistic. We then show that the proposed gS test is independent of the generalized location test, under the joint null hypothesis of no mean and no variance heterogeneity. Consequently, we generalize the recently proposed joint location-scale (gJLS) test, valuable in settings where there is an interaction effect but one interacting variable is not available. We evaluate the proposed method via an extensive simulation study and two genetic association application studies. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
RR-Interval variance of electrocardiogram for atrial fibrillation detection
Nuryani, N.; Solikhah, M.; Nugoho, A. S.; Afdala, A.; Anzihory, E.
2016-11-01
Atrial fibrillation is a serious heart problem originated from the upper chamber of the heart. The common indication of atrial fibrillation is irregularity of R peak-to-R-peak time interval, which is shortly called RR interval. The irregularity could be represented using variance or spread of RR interval. This article presents a system to detect atrial fibrillation using variances. Using clinical data of patients with atrial fibrillation attack, it is shown that the variance of electrocardiographic RR interval are higher during atrial fibrillation, compared to the normal one. Utilizing a simple detection technique and variances of RR intervals, we find a good performance of atrial fibrillation detection.
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
Ma, Hui-qiang
2014-01-01
We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance effici...
Assessing the genetic overlap between BMI and cognitive function
Marioni, R E; Yang, J; Dykiert, D; Mõttus, R; Campbell, A; Ibrahim-Verbaas, Carla A; Bressler, Jan; Debette, Stephanie; Schuur, Maaike; Smith, Albert V; Davies, Gail; Bennett, David A; Deary, Ian J; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosely Jr, Thomas H; Davies, G; Hayward, C; Porteous, D J; Visscher, P M; Deary, I J
2016-01-01
Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at Pcognitive function. PMID:26857597
Genetic component in learning ability in bees.
Kerr, W E; Moura Duarte, F A; Oliveira, R S
1975-10-01
Twenty-five bees, five from each of five hives, were trained to collect food at a table. When the bee reached the table, time was recorded for 12 visits. Then a blue and yellow pan was substituted for the original metal pan, and time and correct responses were recorded for 30 trips (discrimination phase). Finally, food was taken from the pan and extinction was recorded as incorrect responses for 20 visits. Variance analysis was carried out, and genetic variance was undetected for discrimination, but was detected for extinction. It is concluded that learning is very important for bees, so that any impairment in such ability affects colony survival.
Genetic estimation of hot carcass weight in indigenous Matebele ...
African Journals Online (AJOL)
Genetic parameter estimation for simple carcass traits has been confined to the improved goat breeds worldwide unlike in the unimproved breeds in developing countries where goats are numerous. Variance components for additive direct, additive maternal, permanent environmental maternal effects, the covariance ...
Genetic diversity of Actinobacillus lignieresii isolates from different hosts
DEFF Research Database (Denmark)
Kokotovic, Branko; Angen, Øystein; Bisgaard, Magne
2011-01-01
Genetic diversity detected by analysis of amplified fragment length polymorphisms (AFLPs) of 54 Actinobacilus lignieresii isolates from different hosts and geographic localities is described. On the basis of variances in AFLP profiles, the strains were grouped in two major clusters; one comprisin...
Variance based OFDM frame synchronization
Directory of Open Access Journals (Sweden)
Z. Fedra
2012-04-01
Full Text Available The paper deals with a new frame synchronization scheme for OFDM systems and calculates the complexity of this scheme. The scheme is based on the computing of the detection window variance. The variance is computed in two delayed times, so a modified Early-Late loop is used for the frame position detection. The proposed algorithm deals with different variants of OFDM parameters including guard interval, cyclic prefix, and has good properties regarding the choice of the algorithm's parameters since the parameters may be chosen within a wide range without having a high influence on system performance. The verification of the proposed algorithm functionality has been performed on a development environment using universal software radio peripheral (USRP hardware.
Solitary Fibrous Tumor Arising from Stomach: CT Findings
Park, Sung Hee; Kim, Myeong-Jin; Kwon, Jieun; Park, Jong-pil; Park, Mi-Suk; Lim, Joon Seok; Kim, Joo Hee; Kim, Ki Whang
2007-01-01
Solitary fibrous tumors are spindle-cell neoplasms that usually develop in the pleura and peritoneum, and rarely arise in the stomach. To our knowledge, there is only one case reporting a solitary fibrous tumor arising from stomach in the English literature. Here we report the case of a 26-year-old man with a large solitary fibrous tumor arising from the stomach which involved the submucosa and muscular layer and resembled a gastrointestinal stromal tumor in the stomach, based on what was see...
Genetic influences on political ideologies
DEFF Research Database (Denmark)
Hatemi, Peter K; Medland, Sarah E; Klemmensen, Robert
2014-01-01
Almost 40 years ago, evidence from large studies of adult twins and their relatives suggested that between 30 and 60 % of the variance in social and political attitudes could be explained by genetic influences. However, these findings have not been widely accepted or incorporated into the dominant...... paradigms that explain the etiology of political ideology. This has been attributed in part to measurement and sample limitations, as well the relative absence of molecular genetic studies. Here we present results from original analyses of a combined sample of over 12,000 twins pairs, ascertained from nine...... different studies conducted in five democracies, sampled over the course of four decades. We provide evidence that genetic factors play a role in the formation of political ideology, regardless of how ideology is measured, the era, or the population sampled. The only exception is a question that explicitly...
The potential of shifting recombination hotspots to increase genetic gain in livestock breeding.
Gonen, Serap; Battagin, Mara; Johnston, Susan E; Gorjanc, Gregor; Hickey, John M
2017-07-04
This study uses simulation to explore and quantify the potential effect of shifting recombination hotspots on genetic gain in livestock breeding programs. We simulated three scenarios that differed in the locations of quantitative trait nucleotides (QTN) and recombination hotspots in the genome. In scenario 1, QTN were randomly distributed along the chromosomes and recombination was restricted to occur within specific genomic regions (i.e. recombination hotspots). In the other two scenarios, both QTN and recombination hotspots were located in specific regions, but differed in whether the QTN occurred outside of (scenario 2) or inside (scenario 3) recombination hotspots. We split each chromosome into 250, 500 or 1000 regions per chromosome of which 10% were recombination hotspots and/or contained QTN. The breeding program was run for 21 generations of selection, after which recombination hotspot regions were kept the same or were shifted to adjacent regions for a further 80 generations of selection. We evaluated the effect of shifting recombination hotspots on genetic gain, genetic variance and genic variance. Our results show that shifting recombination hotspots reduced the decline of genetic and genic variance by releasing standing allelic variation in the form of new allele combinations. This in turn resulted in larger increases in genetic gain. However, the benefit of shifting recombination hotspots for increased genetic gain was only observed when QTN were initially outside recombination hotspots. If QTN were initially inside recombination hotspots then shifting them decreased genetic gain. Shifting recombination hotspots to regions of the genome where recombination had not occurred for 21 generations of selection (i.e. recombination deserts) released more of the standing allelic variation available in each generation and thus increased genetic gain. However, whether and how much increase in genetic gain was achieved by shifting recombination hotspots depended
Means and Variances without Calculus
Kinney, John J.
2005-01-01
This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.
The role of genetic diversity in nest cooling in a wild honey bee, Apis florea.
Jones, Julia C; Nanork, Piyamas; Oldroyd, Benjamin P
2007-02-01
Simulation studies of the task threshold model for task allocation in social insect colonies suggest that nest temperature homeostasis is enhanced if workers have slightly different thresholds for engaging in tasks related to nest thermoregulation. Genetic variance in task thresholds is one way a distribution of task thresholds can be generated. Apis mellifera colonies with large genetic diversity are able to maintain more stable brood nest temperatures than colonies that are genetically uniform. If this phenomenon is generalizable to other species, we would predict that patrilines should vary in the threshold in which they engage in thermoregulatory tasks. We exposed A. florea colonies to different temperatures experimentally, and retrieved fanning workers at these different temperatures. In many cases we found statistically significant differences in the proportion of fanning workers of different patrilines at different experimental temperatures. This suggests that genetically different workers have different thresholds for performing the thermoregulatory task of fanning. We suggest, therefore, that genetically based variance in task threshold is a widespread phenomenon in the genus Apis.
Application of variance reduction technique to nuclear transmutation system driven by accelerator
Energy Technology Data Exchange (ETDEWEB)
Sasa, Toshinobu [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1998-03-01
In Japan, it is the basic policy to dispose the high level radioactive waste arising from spent nuclear fuel in stable deep strata after glass solidification. If the useful elements in the waste can be separated and utilized, resources are effectively used, and it can be expected to guarantee high economical efficiency and safety in the disposal in strata. Japan Atomic Energy Research Institute proposed the hybrid type transmutation system, in which high intensity proton accelerator and subcritical fast core are combined, or the nuclear reactor which is optimized for the exclusive use for transmutation. The tungsten target, minor actinide nitride fuel transmutation system and the melted minor actinide chloride salt target fuel transmutation system are outlined. The conceptual figures of both systems are shown. As the method of analysis, Version 2.70 of Lahet Code System which was developed by Los Alamos National Laboratory in USA was adopted. In case of carrying out the analysis of accelerator-driven subcritical core in the energy range below 20 MeV, variance reduction technique must be applied. (K.I.)
King, Elizabeth G; Sanderson, Brian J; McNeil, Casey L; Long, Anthony D; Macdonald, Stuart J
2014-05-01
Modern genetic mapping is plagued by the "missing heritability" problem, which refers to the discordance between the estimated heritabilities of quantitative traits and the variance accounted for by mapped causative variants. One major potential explanation for the missing heritability is allelic heterogeneity, in which there are multiple causative variants at each causative gene with only a fraction having been identified. The majority of genome-wide association studies (GWAS) implicitly assume that a single SNP can explain all the variance for a causative locus. However, if allelic heterogeneity is prevalent, a substantial amount of genetic variance will remain unexplained. In this paper, we take a haplotype-based mapping approach and quantify the number of alleles segregating at each locus using a large set of 7922 eQTL contributing to regulatory variation in the Drosophila melanogaster female head. Not only does this study provide a comprehensive eQTL map for a major community genetic resource, the Drosophila Synthetic Population Resource, but it also provides a direct test of the allelic heterogeneity hypothesis. We find that 95% of cis-eQTLs and 78% of trans-eQTLs are due to multiple alleles, demonstrating that allelic heterogeneity is widespread in Drosophila eQTL. Allelic heterogeneity likely contributes significantly to the missing heritability problem common in GWAS studies.
Beyond the Mean: Sensitivities of the Variance of Population Growth.
Trotter, Meredith V; Krishna-Kumar, Siddharth; Tuljapurkar, Shripad
2013-03-01
Populations in variable environments are described by both a mean growth rate and a variance of stochastic population growth. Increasing variance will increase the width of confidence bounds around estimates of population size, growth, probability of and time to quasi-extinction. However, traditional sensitivity analyses of stochastic matrix models only consider the sensitivity of the mean growth rate. We derive an exact method for calculating the sensitivity of the variance in population growth to changes in demographic parameters. Sensitivities of the variance also allow a new sensitivity calculation for the cumulative probability of quasi-extinction. We apply this new analysis tool to an empirical dataset on at-risk polar bears to demonstrate its utility in conservation biology We find that in many cases a change in life history parameters will increase both the mean and variance of population growth of polar bears. This counterintuitive behaviour of the variance complicates predictions about overall population impacts of management interventions. Sensitivity calculations for cumulative extinction risk factor in changes to both mean and variance, providing a highly useful quantitative tool for conservation management. The mean stochastic growth rate and its sensitivities do not fully describe the dynamics of population growth. The use of variance sensitivities gives a more complete understanding of population dynamics and facilitates the calculation of new sensitivities for extinction processes.
A quantitative genetic analysis of intermediate asthma phenotypes
DEFF Research Database (Denmark)
Thomsen, S.F.; Ferreira, M.A.R.; Kyvik, K.O.
2009-01-01
to the observed data using maximum likelihood methods. RESULTS: Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most......AIM: To study the relative contribution of genetic and environmental factors to the correlation between exhaled nitric oxide (FeNO), airway responsiveness, airway obstruction, and serum total immunoglobulin E (IgE). METHODS: Within a sampling frame of 21,162 twin subjects, 20-49 years of age, from...... substantial genetic similarity was observed between FeNO and serum total IgE, genetic correlation (rhoA) = 0.37, whereas the strongest environmental resemblance was observed between airway responsiveness and airway obstruction, specific environmental correlation (rhoE) = -0.46, and between FeNO and airway...
A quantitative genetic analysis of intermediate asthma phenotypes
DEFF Research Database (Denmark)
Thomsen, S F; Ferreira, M A R; Kyvik, K O
2009-01-01
to the observed data using maximum likelihood methods. Results: Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most......Aim: To study the relative contribution of genetic and environmental factors to the correlation between exhaled nitric oxide (FeNO), airway responsiveness, airway obstruction, and serum total immunoglobulin E (IgE). Methods: Within a sampling frame of 21 162 twin subjects, 20-49 years of age, from...... substantial genetic similarity was observed between FeNO and serum total IgE, genetic correlation (rho(A)) = 0.37, whereas the strongest environmental resemblance was observed between airway responsiveness and airway obstruction, specific environmental correlation (rho(E)) = -0.46, and between FeNO and airway...
Evaluation of Mean and Variance Integrals without Integration
Joarder, A. H.; Omar, M. H.
2007-01-01
The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…
Approximate zero-variance Monte Carlo estimation of Markovian unreliability
International Nuclear Information System (INIS)
Delcoux, J.L.; Labeau, P.E.; Devooght, J.
1997-01-01
Monte Carlo simulation has become an important tool for the estimation of reliability characteristics, since conventional numerical methods are no more efficient when the size of the system to solve increases. However, evaluating by a simulation the probability of occurrence of very rare events means playing a very large number of histories of the system, which leads to unacceptable computation times. Acceleration and variance reduction techniques have to be worked out. We show in this paper how to write the equations of Markovian reliability as a transport problem, and how the well known zero-variance scheme can be adapted to this application. But such a method is always specific to the estimation of one quality, while a Monte Carlo simulation allows to perform simultaneously estimations of diverse quantities. Therefore, the estimation of one of them could be made more accurate while degrading at the same time the variance of other estimations. We propound here a method to reduce simultaneously the variance for several quantities, by using probability laws that would lead to zero-variance in the estimation of a mean of these quantities. Just like the zero-variance one, the method we propound is impossible to perform exactly. However, we show that simple approximations of it may be very efficient. (author)
Primary extradural meningioma arising from the calvarium | Ravi ...
African Journals Online (AJOL)
Meningiomas are the most common intracranial tumours. Meningiomas arising at other locations are termed primary extradural meningiomas (EDMs) and are rare. Here we report a case of EDM arising from the calvarium – a primary calvarial meningioma (PCM).
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
Directory of Open Access Journals (Sweden)
Hui-qiang Ma
2014-01-01
Full Text Available We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.
Variance in binary stellar population synthesis
Breivik, Katelyn; Larson, Shane L.
2016-03-01
In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations in less than a week, thus allowing a full exploration of the variance associated with a binary stellar evolution model.
International Nuclear Information System (INIS)
Chaumot, Arnaud; Gos, Pierre; Garric, Jeanne; Geffard, Olivier
2009-01-01
Questioning the likelihood that populations adapt to contamination is critical for ecotoxicological risk assessment. The appraisal of genetic variance in chemical sensitivities within populations is currently used to evaluate a priori this evolutionary potential. Nevertheless, conclusions from this approach are questionable since non-additive genetic components in chemical tolerance could limit the response of such complex phenotypic traits to selection. Coupling quantitative genetics with ecotoxicology, this study illustrates how the comparison between cadmium sensitivities among Gammarus siblings enabled discrimination between genetic variance components in chemical tolerance. The results revealed that, whereas genetically determined differences in lethal tolerance exist within the studied population, such differences were not significantly heritable since genetic variance mainly relied on non-additive components. Therefore the potential for genetic adaptation to acute Cd stress appeared to be weak. These outcomes are discussed in regard to previous findings for asexual daphnids, which suggest a strong potency of genetic adaptation to environmental contamination, but which contrast with compiled field observations where adaptation is not the rule. Hereafter, we formulate the reconciling hypothesis of a widespread weakness of additive components in tolerance to contaminants, which needs to be further tested to gain insight into the question of the likelihood of adaptation to contamination.
Estimating non-genetic and genetic parameters of pre-weaning growth traits in Raini Cashmere goat.
Barazandeh, Arsalan; Moghbeli, Sadrollah Molaei; Vatankhah, Mahmood; Mohammadabadi, Mohammadreza
2012-04-01
Data and pedigree information used in the present study were 3,022 records of kids obtained from the breeding station of Raini goat. The studied traits were birth weight (BW), weaning weight (WW), average daily gain from birth to weaning (ADG) and Kleiber ratio at weaning (KR). The model included the fixed effects of sex of kid, type of birth, age of dam, year of birth, month of birth, and age of kid (days) as covariate that had significant effects, and random effects direct additive genetic, maternal additive genetic, maternal permanent environmental effects and residual. (Co) variance components were estimated using univariate and multivariate analysis by WOMBAT software applying four animal models including and ignoring maternal effects. Likelihood ratio test used to determine the most appropriate models. Heritability (h(a)(2)) estimates for BW, WW, ADG, and KR according to suitable model were 0.12 ± 0.05, 0.08 ± 0.06, 0.10 ± 0.06, and 0.06 ± 0.05, respectively. Estimates of the proportion of maternal permanent environmental effect to phenotypic variance (c(2)) were 0.17 ± 0.03, 0.07 ± 0.03, and 0.07 ± 0.03 for BW, WW, and ADG, respectively. Genetic correlations among traits were positive and ranged from 0.53 (BW-ADG) to 1.00 (WW-ADG, WW-KR, and ADG-KR). The maternal permanent environmental correlations between BW-WW, BW-ADG, and WW-ADG were 0.54, 0.48, and 0.99, respectively. Results indicated that maternal effects, especially maternal permanent environmental effects are an important source of variation in pre-weaning growth trait and ignoring those in the model redound incorrect genetic evaluation of kids.
Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A
2018-03-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.
Genetic parameters of growth, body, and egg traits in Japanese quails
African Journals Online (AJOL)
SARAH
2014-07-31
Jul 31, 2014 ... egg traits as well as genetic and phenotypic relationships between these traits in Japanese quails reared in the ... Japanese quail is the smallest avian species farmed .... 2 = cross classified “family” variance component.
Seasonal genetic variation associated with population dynamics of a poecilogonous polychaete worm
DEFF Research Database (Denmark)
Thonig, Anne; Banta, Gary Thomas; Hansen, Benni Winding
2017-01-01
Poecilogonous species show variation in developmental mode, with larvae that differ both morphologically and ecologically. The spionid polychaete Pygospio elegans shows variation in developmental mode not only between populations, but also seasonally within populations. We investigated...... differentiation at two of the sites. The seasonal genetic shift correlated with the appearance of new size cohorts in the populations. Additionally, we found that the genetic composition of reproductive individuals did not always reflect the genetic composition of the entire sample, indicating that variance...
A Mean variance analysis of arbitrage portfolios
Fang, Shuhong
2007-03-01
Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.
Mean-Variance Optimization in Markov Decision Processes
Mannor, Shie; Tsitsiklis, John N.
2011-01-01
We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomized or history-based policies can improve performance. We prove that the complexity of computing a policy that maximizes the mean reward under a variance constraint is NP-hard for some cases, and strongly NP-hard for others. We finally offer pseudo-polynomial exact and approximation algorithms.
Capturing Option Anomalies with a Variance-Dependent Pricing Kernel
DEFF Research Database (Denmark)
Christoffersen, Peter; Heston, Steven; Jacobs, Kris
2013-01-01
We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric...... evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation...... for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution....
Gender Variance and Educational Psychology: Implications for Practice
Yavuz, Carrie
2016-01-01
The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…
DEFF Research Database (Denmark)
Jacobsen, B. H.; Hansen, Michael Møller; Loeschcke, V.
2005-01-01
The northern pike Esox lucius L. is a freshwater fish exhibiting pronounced population subdivision and low genetic variability. However, there is limited knowledge on phylogeographical patterns within the species, and it is not known whether the low genetic variability reflects primarily current...... low effective population sizes or historical bottlenecks. We analysed six microsatellite loci in ten populations from Europe and North America. Genetic variation was low, with the average number of alleles within populations ranging from 2.3 to 4.0 per locus. Genetic differentiation among populations...... was high (overall theta(ST) = 0.51; overall rho(ST) = 0.50). Multidimensional scaling analysis of genetic distances between populations and spatial analysis of molecular variance suggested a single phylogeographical race within the sampled populations from northern Europe, whereas North American...
Bruning, Andrea; Gaitán-Espitia, Juan Diego; González, Avia; Bartheld, José Luis; Nespolo, Roberto F
2013-01-01
Life-history evolution-the way organisms allocate time and energy to reproduction, survival, and growth-is a central question in evolutionary biology. One of its main tenets, the allocation principle, predicts that selection will reduce energy costs of maintenance in order to divert energy to survival and reproduction. The empirical support for this principle is the existence of a negative relationship between fitness and metabolic rate, which has been observed in some ectotherms. In juvenile animals, a key function affecting fitness is growth rate, since fast growers will reproduce sooner and maximize survival. In principle, design constraints dictate that growth rate cannot be reduced without affecting maintenance costs. Hence, it is predicted that juveniles will show a positive relationship between fitness (growth rate) and metabolic rate, contrarily to what has been observed in adults. Here we explored this problem using land snails (Cornu aspersum). We estimated the additive genetic variance-covariance matrix for growth and standard metabolic rate (SMR; rate of CO2 production) using 34 half-sibling families. We measured eggs, hatchlings, and juveniles in 208 offspring that were isolated right after egg laying (i.e., minimizing maternal and common environmental variance). Surprisingly, our results showed that additive genetic effects (narrow-sense heritabilities, h(2)) and additive genetic correlations (rG) were small and nonsignificant. However, the nonadditive proportion of phenotypic variances and correlations (rC) were unexpectedly large and significant. In fact, nonadditive genetic effects were positive for growth rate and SMR ([Formula: see text]; [Formula: see text]), supporting the idea that fitness (growth rate) cannot be maximized without incurring maintenance costs. Large nonadditive genetic variances could result as a consequence of selection eroding the additive genetic component, which suggests that past selection could have produced nonadditive
Smit, D.J.A.; Boomsma, D.I.; Schnack, H.G.; Hulshoff Pol, H.E.; de Geus, E.J.C.
2012-01-01
The human electroencephalogram (EEG) consists of oscillations that reflect the summation of postsynaptic potentials at the dendritic tree of cortical neurons. The strength of the oscillations (EEG power) is a highly genetic trait that has been related to individual differences in many phenotypes,
DEFF Research Database (Denmark)
Shirali, Mahmoud; Nielsen, Vivi Hunnicke; Møller, Steen Henrik
Heritability of residual feed intake (RFI) increased from low to high over the growing period in male and female mink. The lowest heritability for RFI (male: 0.04 ± 0.01 standard deviation (SD); female: 0.05 ± 0.01 SD) was in early and the highest heritability (male: 0.33 ± 0.02; female: 0.34 ± 0.......02 SD) was achieved at the late growth stages. The genetic correlation between different growth stages for RFI showed a high association (0.91 to 0.98) between early and late growing periods. However, phenotypic correlations were lower from 0.29 to 0.50. The residual variances were substantially higher...
Energy Technology Data Exchange (ETDEWEB)
Christoforou, Stavros, E-mail: stavros.christoforou@gmail.com [Kirinthou 17, 34100, Chalkida (Greece); Hoogenboom, J. Eduard, E-mail: j.e.hoogenboom@tudelft.nl [Department of Applied Sciences, Delft University of Technology (Netherlands)
2011-07-01
A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k{sub eff} estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)
Variance-in-Mean Effects of the Long Forward-Rate Slope
DEFF Research Database (Denmark)
Christiansen, Charlotte
2005-01-01
This paper contains an empirical analysis of the dependence of the long forward-rate slope on the long-rate variance. The long forward-rate slope and the long rate are described by a bivariate GARCH-in-mean model. In accordance with theory, a negative long-rate variance-in-mean effect for the long...... forward-rate slope is documented. Thus, the greater the long-rate variance, the steeper the long forward-rate curve slopes downward (the long forward-rate slope is negative). The variance-in-mean effect is both statistically and economically significant....
Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S
2007-05-01
The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.
Mano, Hiroyuki; Tanaka, Yoshinari
2017-12-01
This study examines the spatial difference in genetic variation for tolerance to a pesticide, fenitrothion, in Daphnia galeata at field sites in Lake Kasumigaura, Japan. We estimated genetic values of isofemale lines established from dormant eggs of D. galeata collected from field sampling sites with the toxicant threshold model applied using acute toxicity. We compared genetic values and variances and broad-sense heritability across different sites in the lake. Results showed that the mean tolerance values to fenitrothion did not differ spatially. The variance in genetic value and heritability of fenitrothion tolerance significantly differed between sampling sites, revealing that long-term ecological risk of fenitrothion may differ between local populations in the lake. These results have implications for aquatic toxicology research, suggesting that differences in genetic variation of tolerance to a chemical among local populations must be considered for understanding the long-term ecological risks of the chemical over a large geographic area.
Genetic Evaluation and Ranking of Different Animal Models Using ...
African Journals Online (AJOL)
An animal model utilizes all relationships available in a given data set. Estimates for variance components for additive direct, additive maternal, maternal environmental and direct environmental effects, and their covariances between direct and maternal genetic effects for post weaning growth traits have been obtained with ...
Genetic parameters for quail body weights using a random ...
African Journals Online (AJOL)
A model including fixed and random linear regressions is described for analyzing body weights at different ages. In this study, (co)variance components, heritabilities for quail weekly weights and genetic correlations among these weights were estimated using a random regression model by DFREML under DXMRR option.
Genetic diversity in wild populations of Paulownia fortune.
Li, H Y; Ru, G X; Zhang, J; Lu, Y Y
2014-11-01
The genetic diversities of 16 Paulownia fortunei populations involving 143 individuals collected from 6 provinces in China were analyzed using amplified fragment length polymorphism (AFLP). A total of 9 primer pairs with 1169 polymorphic loci were screened out, and each pair possessed 132 bands on average. The percentage of polymorphic bands (98.57%), the effective number of alleles (1.2138-1.2726), Nei's genetic diversity (0.1566-0.1887), and Shannon's information index (0.2692-0.3117) indicated a plentiful genetic diversity and different among Paulownia fortunei populations. The genetic differentiation coefficient between populations was 0.2386, while the gene flow was 1.0954, and the low gene exchange promoted genetic differentiation. Analysis of variance indicated that genetic variation mainly occurred within populations (81.62% of total variation) rather than among populations (18.38%). The 16 populations were divided by unweighted pair-group method with arithmetic means (UPGMA) into 4 groups with obvious regionalism, in which the populations with close geographical locations (latitude) were clustered together.
A maternal-effect genetic incompatibility in Caenorhabditis elegans
Burga, Alejandro; Ben-David, Eyal; Kruglyak, Leonid
2017-01-01
Selfish genetic elements spread in natural populations and have an important role in genome evolution. We discovered a selfish element causing a genetic incompatibility between strains of the nematode Caenorhabditis elegans . The element is made up of sup-35 , a maternal-effect toxin that kills developing embryos, and pha-1 , its zygotically expressed antidote. pha-1 has long been considered essential for pharynx development based on its mutant phenotype, but this phenotype in fact arises fro...
Direct to consumer genetic testing-law and policy concerns in Ireland.
de Paor, Aisling
2017-11-25
With rapid scientific and technological advances, the past few years has witnessed the emergence of a new genetic era and a growing understanding of the genetic make-up of human beings. These advances have propelled the introduction of companies offering direct to consumer (DTC) genetic testing, which facilitates the direct provision of such tests to consumers, (for example, via the internet). Although DTC genetic testing offers benefits by enhancing consumer accessibility to such technology, promoting proactive healthcare and increasing genetic awareness, it presents a myriad of challenges, from an ethical, legal and regulatory perspective. As DTC genetic testing usually eliminates the need for a medical professional in accessing genetic tests, this lack of professional guidance and counselling may result in misinterpretation and confusion regarding results. In addition, an evident concern relates to the scientific validity and quality of these tests. A further problem arising is the lack or inadequacy of regulation in this field. Despite the increasing accessibility of DTC genetic testing, this legislative vacuum is apparent in Ireland, where there is no concrete legislation. This article explores the main ethical, legal and regulatory issues arising with the advent of rapid advances in DTC genetic testing in Ireland. Further, with inevitable future advances in genetic science, as well as increasing internet accessibility, the challenges presented are likely to become more amplified. In consideration of the ethical and legal challenges, this paper highlights the regulation of DTC genetic testing as a growing concern in Ireland, recognising its importance to both the scientific community as well as in respect of enhancing consumer confidence in such technologies.
A behavioral-genetic investigation of bulimia nervosa and its relationship with alcohol use disorder
Trace, Sara Elizabeth; Thornton, Laura Marie; Baker, Jessica Helen; Root, Tammy Lynn; Janson, Lauren Elizabeth; Lichtenstein, Paul; Pedersen, Nancy Lee; Bulik, Cynthia Marie
2013-01-01
Bulimia nervosa (BN) and alcohol use disorder (AUD) frequently co-occur and may share genetic factors; however, the nature of their association is not fully understood. We assessed the extent to which the same genetic and environmental factors contribute to liability to BN and AUD. A bivariate structural equation model using a Cholesky decomposition was fit to data from 7,241 women who participated in the Swedish Twin study of Adults: Genes and Environment. The proportion of variance accounted for by genetic and environmental factors for BN and AUD and the genetic and environmental correlations between these disorders were estimated. In the best-fitting model, the heritability estimates were 0.55 (95% CI: 0.37; 0.70) for BN and 0.62 (95% CI: 0.54; 0.70) for AUD. Unique environmental factors accounted for the remainder of variance for BN. The genetic correlation between BN and AUD was 0.23 (95% CI: 0.01; 0.44), and the correlation between the unique environmental factors for the two disorders was 0.35 (95% CI: 0.08; 0.61), suggesting moderate overlap in these factors. Findings from this investigation provide additional support that some of the same genetic factors may influence liability to both BN and AUD. PMID:23790978
Variance-based sensitivity indices for models with dependent inputs
International Nuclear Information System (INIS)
Mara, Thierry A.; Tarantola, Stefano
2012-01-01
Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.
Simultaneous Monte Carlo zero-variance estimates of several correlated means
International Nuclear Information System (INIS)
Booth, T.E.
1997-08-01
Zero variance procedures have been in existence since the dawn of Monte Carlo. Previous works all treat the problem of zero variance solutions for a single tally. One often wants to get low variance solutions to more than one tally. When the sets of random walks needed for two tallies are similar, it is more efficient to do zero variance biasing for both tallies in the same Monte Carlo run, instead of two separate runs. The theory presented here correlates the random walks of particles by the similarity of their tallies. Particles with dissimilar tallies rapidly become uncorrelated whereas particles with similar tallies will stay correlated through most of their random walk. The theory herein should allow practitioners to make efficient use of zero-variance biasing procedures in practical problems
Variance swap payoffs, risk premia and extreme market conditions
DEFF Research Database (Denmark)
Rombouts, Jeroen V.K.; Stentoft, Lars; Violante, Francesco
This paper estimates the Variance Risk Premium (VRP) directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, we extract the VRP by using signal extraction techniques based on a state-space representation of our model in combination with a simple economic....... The latter variables and the VRP generate different return predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French portfolios....
Prevalence and detection of psychosocial problems in cancer genetic counseling.
Eijzenga, W; Bleiker, E M A; Hahn, D E E; Van der Kolk, L E; Sidharta, G N; Aaronson, N K
2015-12-01
Only a minority of individuals who undergo cancer genetic counseling experience heightened levels of psychological distress, but many more experience a range of cancer genetic-specific psychosocial problems. The aim of this study was to estimate the prevalence of such psychosocial problems, and to identify possible demographic and clinical variables associated significantly with them. Consenting individuals scheduled to undergo cancer genetic counseling completed the Psychosocial Aspects of Hereditary Cancer (PAHC) questionnaire, the Hospital Anxiety and Depression Scale (HADS) and the Distress Thermometer (DT) prior to or immediately following their counseling session. More than half of the 137 participants reported problems on three or more domains of the PAHC, most often in the domains 'living with cancer' (84%), 'family issues' (46%), 'hereditary predisposition' (45%), and 'child-related issues' (42%). Correlations between the PAHC, the HADS and the DT were low. Previous contact with a psychosocial worker, and having a personal history of cancer were associated significantly with HADS scores, but explained little variance (9%). No background variables were associated significantly with the DT. Previous contact with a psychosocial worker, and having children were significantly associated with several PAHC domains, again explaining only a small percentage of the variance (2-14%). The majority of counselees experience specific cancer genetic counseling-related psychosocial problems. Only a few background variables are associated significantly with distress or psychosocial problems. Thus we recommend using the PAHC or a similar problem-oriented questionnaire routinely in cancer genetic counseling to identify individuals with such problems.
Estimating quadratic variation using realized variance
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2002-01-01
with a rather general SV model - which is a special case of the semimartingale model. Then QV is integrated variance and we can derive the asymptotic distribution of the RV and its rate of convergence. These results do not require us to specify a model for either the drift or volatility functions, although we...... have to impose some weak regularity assumptions. We illustrate the use of the limit theory on some exchange rate data and some stock data. We show that even with large values of M the RV is sometimes a quite noisy estimator of integrated variance. Copyright © 2002 John Wiley & Sons, Ltd....
Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability
DEFF Research Database (Denmark)
Rombouts, Jerome V.K.; Stentoft, Lars; Violante, Francesco
We develop a joint framework linking the physical variance and its risk neutral expectation implying variance risk premia that are persistent, appropriately reacting to changes in level and variability of the variance and naturally satisfying the sign constraint. Using option market data and real...... events and only marginally by the premium associated with normal price fluctuations....
A note on minimum-variance theory and beyond
Energy Technology Data Exchange (ETDEWEB)
Feng Jianfeng [Department of Informatics, Sussex University, Brighton, BN1 9QH (United Kingdom); Tartaglia, Giangaetano [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy); Tirozzi, Brunello [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy)
2004-04-30
We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons.
A note on minimum-variance theory and beyond
International Nuclear Information System (INIS)
Feng Jianfeng; Tartaglia, Giangaetano; Tirozzi, Brunello
2004-01-01
We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons
Sex reduces genetic variation: a multidisciplinary review.
Gorelick, Root; Heng, Henry H Q
2011-04-01
For over a century, the paradigm has been that sex invariably increases genetic variation, despite many renowned biologists asserting that sex decreases most genetic variation. Sex is usually perceived as the source of additive genetic variance that drives eukaryotic evolution vis-à-vis adaptation and Fisher's fundamental theorem. However, evidence for sex decreasing genetic variation appears in ecology, paleontology, population genetics, and cancer biology. The common thread among many of these disciplines is that sex acts like a coarse filter, weeding out major changes, such as chromosomal rearrangements (that are almost always deleterious), but letting minor variation, such as changes at the nucleotide or gene level (that are often neutral), flow through the sexual sieve. Sex acts as a constraint on genomic and epigenetic variation, thereby limiting adaptive evolution. The diverse reasons for sex reducing genetic variation (especially at the genome level) and slowing down evolution may provide a sufficient benefit to offset the famed costs of sex. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.
Advances in the genetically complex autoinflammatory diseases.
Ombrello, Michael J
2015-07-01
Monogenic diseases usually demonstrate Mendelian inheritance and are caused by highly penetrant genetic variants of a single gene. In contrast, genetically complex diseases arise from a combination of multiple genetic and environmental factors. The concept of autoinflammation originally emerged from the identification of individual, activating lesions of the innate immune system as the molecular basis of the hereditary periodic fever syndromes. In addition to these rare, monogenic forms of autoinflammation, genetically complex autoinflammatory diseases like the periodic fever, aphthous stomatitis, pharyngitis, and cervical adenitis (PFAPA) syndrome, chronic recurrent multifocal osteomyelitis (CRMO), Behçet's disease, and systemic arthritis also fulfill the definition of autoinflammatory diseases-namely, the development of apparently unprovoked episodes of inflammation without identifiable exogenous triggers and in the absence of autoimmunity. Interestingly, investigations of these genetically complex autoinflammatory diseases have implicated both innate and adaptive immune abnormalities, blurring the line between autoinflammation and autoimmunity. This reinforces the paradigm of concerted innate and adaptive immune dysfunction leading to genetically complex autoinflammatory phenotypes.
Nazarian, Alireza; Gezan, Salvador A
2016-03-01
The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Population genetic differentiation of height and body mass index across Europe
DEFF Research Database (Denmark)
Robinson, Matthew R.; Hemani, Gibran; Medina-Gomez, Carolina
2015-01-01
Across-nation differences in the mean values for complex traits are common(1-8), but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European...... countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population...... genetic differences. Population genetic divergence differed significantly from that in a null model (height, P
Directory of Open Access Journals (Sweden)
Van Tassel CP.
1998-01-01
Full Text Available Nonadditive genetic effects are currently ignored in national genetic evaluations of farm animals because of ignorance of thelevel of dominance variance for traits of interest and the difficult computational problems involved. Potential gains fromincluding the effects of dominance in genetic evaluations include “purification” of additive values and availability ofpredictions of specific combining abilities for each pair of prospective parents. This study focused on making evaluation withdominance effects feasible computationally and on ascertaining benefits of such an evaluation for dairy cattle, beef cattle,and swine. Using iteration on data, computing costs for evaluation with dominance effects included costs could be less thantwice expensive as with only an additive model. With Method Â, variance components could be estimated for problemsinvolving up to 10 millions equations. Dominance effects accounted for up to 10% of phenotypic variance; estimates werelarger for growth traits. As a percentage of additive variance, the estimate of dominance variance reached 78% for 21-d litterweight of swine and 47% for post weaning weight of beef cattle. When dominance effects are ignored, additive evaluationsare “contaminated”; effects are greatest for evaluations of dams in a single large family. These changes in ranking wereimportant for dairy cattle, especially for dams of full-sibs, but were less important for swine. Specific combining abilitiescannot be included in sire evaluations and need to be computed separately for each set of parents. The predictions of specificcombining abilities could be used in computerized mating programs via the Internet. Gains from including the dominanceeffect in genetic evaluations would be moderate but would outweigh expenditures to produce those evaluations.
Estimating High-Frequency Based (Co-) Variances: A Unified Approach
DEFF Research Database (Denmark)
Voev, Valeri; Nolte, Ingmar
We propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent...... and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Aït-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling...
Increased genetic risk for obesity in premature coronary artery disease.
Cole, Christopher B; Nikpay, Majid; Stewart, Alexandre F R; McPherson, Ruth
2016-04-01
There is ongoing controversy as to whether obesity confers risk for CAD independently of associated risk factors including diabetes mellitus. We have carried out a Mendelian randomization study using a genetic risk score (GRS) for body mass index (BMI) based on 35 risk alleles to investigate this question in a population of 5831 early onset CAD cases without diabetes mellitus and 3832 elderly healthy control subjects, all of strictly European ancestry, with adjustment for traditional risk factors (TRFs). We then estimated the genetic correlation between these BMI and CAD (rg) by relating the pairwise genetic similarity matrix to a phenotypic covariance matrix between these two traits. GRSBMI significantly (P=2.12 × 10(-12)) associated with CAD status in a multivariate model adjusted for TRFs, with a per allele odds ratio (OR) of 1.06 (95% CI 1.042-1.076). The addition of GRSBMI to TRFs explained 0.75% of CAD variance and yielded a continuous net recombination index of 16.54% (95% CI=11.82-21.26%, P<0.0001). To test whether GRSBMI explained CAD status when adjusted for measured BMI, separate models were constructed in which the score and BMI were either included as covariates or not. The addition of BMI explained ~1.9% of CAD variance and GRSBMI plus BMI explained 2.65% of CAD variance. Finally, using bivariate restricted maximum likelihood analysis, we provide strong evidence of genome-wide pleiotropy between obesity and CAD. This analysis supports the hypothesis that obesity is a causal risk factor for CAD.
Siren, J; Ovaskainen, O; Merilä, J
2017-10-01
The genetic variance-covariance matrix (G) is a quantity of central importance in evolutionary biology due to its influence on the rate and direction of multivariate evolution. However, the predictive power of empirically estimated G-matrices is limited for two reasons. First, phenotypes are high-dimensional, whereas traditional statistical methods are tuned to estimate and analyse low-dimensional matrices. Second, the stability of G to environmental effects and over time remains poorly understood. Using Bayesian sparse factor analysis (BSFG) designed to estimate high-dimensional G-matrices, we analysed levels variation and covariation in 10,527 expressed genes in a large (n = 563) half-sib breeding design of three-spined sticklebacks subject to two temperature treatments. We found significant differences in the structure of G between the treatments: heritabilities and evolvabilities were higher in the warm than in the low-temperature treatment, suggesting more and faster opportunity to evolve in warm (stressful) conditions. Furthermore, comparison of G and its phenotypic equivalent P revealed the latter is a poor substitute of the former. Most strikingly, the results suggest that the expected impact of G on evolvability-as well as the similarity among G-matrices-may depend strongly on the number of traits included into analyses. In our results, the inclusion of only few traits in the analyses leads to underestimation in the differences between the G-matrices and their predicted impacts on evolution. While the results highlight the challenges involved in estimating G, they also illustrate that by enabling the estimation of large G-matrices, the BSFG method can improve predicted evolutionary responses to selection. © 2017 John Wiley & Sons Ltd.
Directory of Open Access Journals (Sweden)
Carolina L. A. Da Silva
2018-04-01
Full Text Available We investigated (1 the relationship between the estimated breeding values (EBVs for litter traits at birth and ovulation rate (OR, average corpora luteal weight, uterine length and embryonic survival and development traits in gilts at 35 days of pregnancy by linear regression, (2 the genetic variance of OR, average corpora lutea (CL weight, uterine length and embryonic survival and development traits at 35 days of pregnancy, and (3 the genetic correlations between these traits. Landrace (n = 86 and Yorkshire × Landrace (n = 304 gilts were inseminated and slaughtered at 35 days of pregnancy. OR was assessed by dissection of the CL on both ovaries. Individual CL was weighed and the average CL weight calculated. The number of embryos (total and vital were counted and the vital embryos were individually weighed for calculation of within litter average and standard deviation (SD of the embryo weight. Length of the uterine implantation site of the vital embryos was measured and the average per gilt calculated. Results suggests that increasing the EBV for total number of piglets born would proportionally increase OR and number of embryos, while decreasing the average CL weight. On the contrary, increasing the EBV for average piglet birth weight and for within litter birth weight standard deviation would increase the average CL weight. There was no relationship between the EBVs for BW and for BWSD and vital embryonic weight at 35 days of pregnancy. OR, average CL weight, number of embryos, average weight and implantation length of the vital embryos had all moderate to high heritabilities, ranging from 0.36 (±0.18 to 0.70 (±0.17. Thus, results indicate that there is ample genetic variation in OR, average CL weight and embryonic development traits. This knowledge could be used to optimize the balance between selection for litter size, average piglets birth weight and within litter birth weight uniformity.
International Nuclear Information System (INIS)
Christoforou, Stavros; Hoogenboom, J. Eduard
2011-01-01
A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k_e_f_f estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)
Genetic liability to disability pension in women and men: a prospective population-based twin study.
Directory of Open Access Journals (Sweden)
Jurgita Narusyte
Full Text Available BACKGROUND: Previous studies of risk factors for disability pension (DP have mainly focused on psychosocial, or environmental, factors, while the relative importance of genetic effects has been less studied. Sex differences in biological mechanisms have not been investigated at all. METHODS: The study sample included 46,454 Swedish twins, consisting of 23,227 complete twin pairs, born 1928-1958, who were followed during 1993-2008. Data on DP, including diagnoses, were obtained from the National Social Insurance Agency. Within-pair similarity in liability to DP was assessed by calculating intraclass correlations. Genetic and environmental influences on liability to DP were estimated by applying discrete-time frailty modeling. RESULTS: During follow-up, 7,669 individuals were granted DP (18.8% women and 14.1% men. Intraclass correlations were generally higher in MZ pairs than DZ pairs, while DZ same-sexed pairs were more similar than opposite-sexed pairs. The best-fitting model indicated that genetic factors contributed 49% (95% CI: 39-59 to the variance in DP due to mental diagnoses, 35% (95% CI: 29-41 due to musculoskeletal diagnoses, and 27% (95% CI: 20-33 due to all other diagnoses. In both sexes, genetic effects common to all ages explained one-third, whereas age-specific factors almost two-thirds, of the total variance in liability to DP irrespective of diagnosis. Sex differences in liability to DP were indicated, in that partly different sets of genes were found to operate in women and men, even though the magnitude of genetic variance explained was equal for both sexes. CONCLUSIONS: The findings of the study suggest that genetic effects are important for liability to DP due to different diagnoses. Moreover, genetic contributions to liability to DP tend to differ between women and men, even though the overall relative contribution of genetic influences does not differ by sex. Hence, the pathways leading to DP might differ between women and
Livshits, G; Yakovenko, K; Ginsburg, E; Kobyliansky, E
1998-01-01
The present study utilized pedigree data from three ethnically different populations of Kirghizstan, Turkmenia and Chuvasha. Principal component analysis was performed on a matrix of genetic correlations between 22 measures of adiposity, including skinfolds, circumferences and indices. Findings are summarized as follows: (1) All three genetic matrices were not positive definite and the first four factors retained even after exclusion RG > or = 1.0, explained from 88% to 97% of the total additive genetic variation in the 22 trials studied. This clearly emphasizes the massive involvement of pleiotropic gene effects in the variability of adiposity traits. (2) Despite the quite natural differences in pairwise correlations between the adiposity traits in the three ethnically different samples under study, factor analysis revealed a common basic pattern of covariability for the adiposity traits. In each of the three samples, four genetic factors were retained, namely, the amount of subcutaneous fat, the total body obesity, the pattern of distribution of subcutaneous fat and the central adiposity distribution. (3) Genetic correlations between the retained four factors were virtually non-existent, suggesting that several independent genetic sources may be governing the variation of adiposity traits. (4) Variance decomposition analysis on the obtained genetic factors leaves no doubt regarding the substantial familial and (most probably genetic) effects on variation of each factor in each studied population. The similarity of results in the three different samples indicates that the findings may be deemed valid and reliable descriptions of the genetic variation and covariation pattern of adiposity traits in the human species.
Directory of Open Access Journals (Sweden)
Elizabeth G King
2014-05-01
Full Text Available Modern genetic mapping is plagued by the "missing heritability" problem, which refers to the discordance between the estimated heritabilities of quantitative traits and the variance accounted for by mapped causative variants. One major potential explanation for the missing heritability is allelic heterogeneity, in which there are multiple causative variants at each causative gene with only a fraction having been identified. The majority of genome-wide association studies (GWAS implicitly assume that a single SNP can explain all the variance for a causative locus. However, if allelic heterogeneity is prevalent, a substantial amount of genetic variance will remain unexplained. In this paper, we take a haplotype-based mapping approach and quantify the number of alleles segregating at each locus using a large set of 7922 eQTL contributing to regulatory variation in the Drosophila melanogaster female head. Not only does this study provide a comprehensive eQTL map for a major community genetic resource, the Drosophila Synthetic Population Resource, but it also provides a direct test of the allelic heterogeneity hypothesis. We find that 95% of cis-eQTLs and 78% of trans-eQTLs are due to multiple alleles, demonstrating that allelic heterogeneity is widespread in Drosophila eQTL. Allelic heterogeneity likely contributes significantly to the missing heritability problem common in GWAS studies.
Lipschutz-Powell, Debby; Woolliams, John A.; Bijma, Piter; Doeschl-Wilson, Andrea B.
2012-01-01
Reducing disease prevalence through selection for host resistance offers a desirable alternative to chemical treatment. Selection for host resistance has proven difficult, however, due to low heritability estimates. These low estimates may be caused by a failure to capture all the relevant genetic variance in disease resistance, as genetic analysis currently is not taylored to estimate genetic variation in infectivity. Host infectivity is the propensity of transmitting infection upon contact with a susceptible individual, and can be regarded as an indirect effect to disease status. It may be caused by a combination of physiological and behavioural traits. Though genetic variation in infectivity is difficult to measure directly, Indirect Genetic Effect (IGE) models, also referred to as associative effects or social interaction models, allow the estimation of this variance from more readily available binary disease data (infected/non-infected). We therefore generated binary disease data from simulated populations with known amounts of variation in susceptibility and infectivity to test the adequacy of traditional and IGE models. Our results show that a conventional model fails to capture the genetic variation in infectivity inherent in populations with simulated infectivity. An IGE model, on the other hand, does capture some of the variation in infectivity. Comparison with expected genetic variance suggests that there is scope for further methodological improvement, and that potential responses to selection may be greater than values presented here. Nonetheless, selection using an index of estimated direct and indirect breeding values was shown to have a greater genetic selection differential and reduced future disease risk than traditional selection for resistance only. These findings suggest that if genetic variation in infectivity substantially contributes to disease transmission, then breeding designs which explicitly incorporate IGEs might help reduce disease
Mosing, Miriam A.; Gordon, Scott D.; Medland, Sarah E.; Statham, Dixie J.; Nelson, Elliot C.; Heath, Andrew C.; Martin, Nicholas G.; Wray, Naomi R.
2011-01-01
Background Major depression (MD) and anxiety disorders such as panic disorder (PD), agoraphobia (AG) and social phobia (SP) are heritable and highly comorbid. However, the relative importance of genetic and environmental aetiology of the covariation between these disorders, particularly the relationship between PD and AG is less clear. Methods The present study measured MD, PD and AG in a population sample of 5440 twin pairs and 1245 single twins, about 45% of whom were also scored for SP. Prevalences, within individual comorbidity and twin odds ratios for comorbidity are reported. A behavioural genetic analysis of the four disorders using the classical twin design was conducted. Results Odds ratios for MD, PD, AG, and SP in twins of individuals diagnosed with one of the four disorders were increased. Heritability estimates under a threshold-liability model for MD, PD, AG, and SP respectively were 0.33 (CI:0.30–0.42), 0.38 (CI:0.24–0.55), 0.48 (CI:0.37–0.65) of, and 0.39 (CI:0.16–0.65), with no evidence for any variance explained by the common environment shared by twins. We find that a common genetic factor explains a moderate proportion of variance in these four disorders. The genetic correlation between PD and AG was 0.83. Conclusion MD, PD, AG, and SP strongly co-aggregate within families and common genetic factors explain a moderate proportion of variance in these four disorders. The high genetic correlation between PD and AG and the increased odds ratio for PD and AG in siblings of those with AG without PD suggests a common genetic aetiology for PD and AG. PMID:19750555
International Nuclear Information System (INIS)
Iqbal, Z.M.; Khan, S.A.
2003-01-01
Partial regression coefficient, genotypic and phenotypic variabilities, heritability co-heritability and genetic advance were studied in 15 Potato varieties of exotic and local origin. Both genotypic and phenotypic coefficients of variations were high for scab and rhizoctonia incidence percentage. Significant partial regression coefficient for emergence percentage indicated its relative importance in tuber yield. High heritability (broadsense) estimates coupled with high genetic advance for plant height, number of stems per plant and scab percentage revealed substantial contribution of additive genetic variance in the expression of these traits. Hence, the selection based on these characters could play a significant role in their improvement the dominance and epistatic variance was more important for character expression of yield ha/sup -1/, emergence and rhizoctonia percentage. This phenomenon is mainly due to the accumulative effects of low heritability and low to moderate genetic advance. The high co-heritability coupled with negative genotypic and phenotypic covariance revealed that selection of varieties having low scab and rhizoctonia percentage resulted in more potato yield. (author)
Li, Yang; Pirvu, Traian A
2011-01-01
This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program. The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.
Shikishima, Chizuru; Hiraishi, Kai; Yamagata, Shinji; Ando, Juko; Okada, Mitsuhiro
2015-01-01
Why does decision making differ among individuals? People sometimes make seemingly inconsistent decisions with lower expected (monetary) utility even when objective information of probabilities and reward are provided. It is noteworthy, however, that a certain proportion of people do not provide anomalous responses, choosing the alternatives with higher expected utility, thus appearing to be more "rational." We investigated the genetic and environmental influences on these types of individual differences in decision making using a classical Allais problem task. Participants were 1,199 Japanese adult twins aged 20-47. Univariate genetic analysis revealed that approximately a third of the Allais problem response variance was explained by genetic factors and the rest by environmental factors unique to individuals and measurement error. The environmental factor shared between families did not contribute to the variance. Subsequent multivariate genetic analysis clarified that decision making using the expected utility theory was associated with general intelligence and that the association was largely mediated by the same genetic factor. We approach the mechanism underlying two types of "rational" decision making from the perspective of genetic correlations with cognitive abilities.
General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.
de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael
2016-11-01
Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.
Modelling volatility by variance decomposition
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the condit...
2011-06-01
clavata. Heredity 101:120–126 Crow JF, Denniston C (1988) Inbreeding and variance effective population numbers. Evolution 42:482–495 Dixo M, Metzger JP...University Press, Cambridge, pp 361–366 Young A, Boyle T, Brown T (1996) The population genetic consequences of habitat fragmentation for plants . Trends
Rushton, J Philippe
2004-12-22
Although 51 twin and adoption studies have been performed on the genetic architecture of antisocial behaviour, only four previous studies have examined a genetic contribution to pro-social behaviour. Earlier work by the author with the University of London Institute of Psychiatry Adult Twin Register found that genes contributed approximately half of the variance to measures of self-report altruism, empathy, nurturance and aggression, including acts of violence. The present study extends those results by using a 22-item Social Responsibility Questionnaire with 174 pairs of monozygotic twins and 148 pairs of dizygotic twins. Forty-two per cent of the reliable variance was due to the twins' genes, 23% to the twins' common environment and the remainder to the twins' non-shared environment.
Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction
The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...
Assessment of genetic variability of maize inbred lines and their ...
African Journals Online (AJOL)
Assessment of genetic variability of maize inbred lines and their hybrids under normal and drought conditions. ... Nigeria Agricultural Journal ... Analysis of variance revealed significant differences for most of the characters under study which indicates the presence of sufficient amount of variability offering ample scope for ...
Silberg, Judy L; Gillespie, Nathan; Moore, Ashlee A; Eaves, Lindon J; Bates, John; Aggen, Steven; Pfister, Elizabeth; Canino, Glorisa
2015-04-01
Despite an increasing recognition that psychiatric disorders can be diagnosed as early as preschool, little is known how early genetic and environmental risk factors contribute to the development of psychiatric disorders during this very early period of development. We assessed infant temperament at age 1, and attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and separation anxiety disorder (SAD) at ages 3 through 5 years in a sample of Hispanic twins. Genetic, shared, and non-shared environmental effects were estimated for each temperamental construct and psychiatric disorder using the statistical program MX. Multivariate genetic models were fitted to determine whether the same or different sets of genes and environments account for the co-occurrence between early temperament and preschool psychiatric disorders. Additive genetic factors accounted for 61% of the variance in ADHD, 21% in ODD, and 28% in SAD. Shared environmental factors accounted for 34% of the variance in ODD and 15% of SAD. The genetic influence on difficult temperament was significantly associated with preschool ADHD, SAD, and ODD. The association between ODD and SAD was due to both genetic and family environmental factors. The temperamental trait of resistance to control was entirely accounted for by the shared family environment. There are different genetic and family environmental pathways between infant temperament and psychiatric diagnoses in this sample of Puerto Rican preschool age children.
Endogeneously arising network allocation rules
Slikker, M.
2006-01-01
In this paper we study endogenously arising network allocation rules. We focus on three allocation rules: the Myerson value, the position value and the component-wise egalitarian solution. For any of these three rules we provide a characterization based on component efficiency and some balanced
Decomposition of Variance for Spatial Cox Processes.
Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus
2013-03-01
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.
Effects of censoring on parameter estimates and power in genetic modeling
Derks, Eske M.; Dolan, Conor V.; Boomsma, Dorret I.
2004-01-01
Genetic and environmental influences on variance in phenotypic traits may be estimated with normal theory Maximum Likelihood (ML). However, when the assumption of multivariate normality is not met, this method may result in biased parameter estimates and incorrect likelihood ratio tests. We
Effects of censoring on parameter estimates and power in genetic modeling.
Derks, E.M.; Dolan, C.V.; Boomsma, D.I.
2004-01-01
Genetic and environmental influences on variance in phenotypic traits may be estimated with normal theory Maximum Likelihood (ML). However, when the assumption of multivariate normality is not met, this method may result in biased parameter estimates and incorrect likelihood ratio tests. We
Grammatical and lexical variance in English
Quirk, Randolph
2014-01-01
Written by one of Britain's most distinguished linguists, this book is concerned with the phenomenon of variance in English grammar and vocabulary across regional, social, stylistic and temporal space.
Variance decomposition in stochastic simulators.
Le Maître, O P; Knio, O M; Moraes, A
2015-06-28
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Le Maître, O. P.; Knio, O. M.; Moraes, A.
2015-06-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Energy Technology Data Exchange (ETDEWEB)
Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)
2015-06-28
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance-based Salt Body Reconstruction
Ovcharenko, Oleg
2017-05-26
Seismic inversions of salt bodies are challenging when updating velocity models based on Born approximation- inspired gradient methods. We propose a variance-based method for velocity model reconstruction in regions complicated by massive salt bodies. The novel idea lies in retrieving useful information from simultaneous updates corresponding to different single frequencies. Instead of the commonly used averaging of single-iteration monofrequency gradients, our algorithm iteratively reconstructs salt bodies in an outer loop based on updates from a set of multiple frequencies after a few iterations of full-waveform inversion. The variance among these updates is used to identify areas where considerable cycle-skipping occurs. In such areas, we update velocities by interpolating maximum velocities within a certain region. The result of several recursive interpolations is later used as a new starting model to improve results of conventional full-waveform inversion. An application on part of the BP 2004 model highlights the evolution of the proposed approach and demonstrates its effectiveness.
Variance decomposition in stochastic simulators
Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro
2015-01-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Study books on ADHD genetics: balanced or biased?
Te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans
2017-06-01
Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master's programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics' outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them.
Alu polymorphic insertions reveal genetic structure of north Indian populations.
Tripathi, Manorama; Tripathi, Piyush; Chauhan, Ugam Kumari; Herrera, Rene J; Agrawal, Suraksha
2008-10-01
The Indian subcontinent is characterized by the ancestral and cultural diversity of its people. Genetic input from several unique source populations and from the unique social architecture provided by the caste system has shaped the current genetic landscape of India. In the present study 200 individuals each from three upper-caste and four middle-caste Hindu groups and from two Muslim populations in North India were examined for 10 polymorphic Alu insertions (PAIs). The investigated PAIs exhibit high levels of polymorphism and average heterozygosity. Limited interpopulation variance and genetic flow in the present study suggest admixture. The results of this study demonstrate that, contrary to common belief, the caste system has not provided an impermeable barrier to genetic exchange among Indian groups.
Carcinoma arising in thyroglossal remnants
van Vuuren, P. A.; Balm, A. J.; Gregor, R. T.; Hilgers, F. J.; Loftus, B. M.; Delprat, C. C.; Rutgers, E. J.
1994-01-01
Three patients with a papillary carcinoma arising in a thyroglossal duct cyst are presented and the literature is reviewed. This rare malignancy is seen mostly in women between the ages of 20 and 50 years. The distribution of carcinoma subtypes differs from that of thyroid carcinomas and
Host nutrition alters the variance in parasite transmission potential.
Vale, Pedro F; Choisy, Marc; Little, Tom J
2013-04-23
The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.
Genetic contribution to patent ductus arteriosus in the premature newborn.
Bhandari, Vineet; Zhou, Gongfu; Bizzarro, Matthew J; Buhimschi, Catalin; Hussain, Naveed; Gruen, Jeffrey R; Zhang, Heping
2009-02-01
The most common congenital heart disease in the newborn population, patent ductus arteriosus, accounts for significant morbidity in preterm newborns. In addition to prematurity and environmental factors, we hypothesized that genetic factors play a significant role in this condition. The objective of this study was to quantify the contribution of genetic factors to the variance in liability for patent ductus arteriosus in premature newborns. A retrospective study (1991-2006) from 2 centers was performed by using zygosity data from premature twins born at Patent ductus arteriosus was diagnosed by echocardiography at each center. Mixed-effects logistic regression was used to assess the effect of specific covariates. Latent variable probit modeling was then performed to estimate the heritability of patent ductus arteriosus, and mixed-effects probit modeling was used to quantify the genetic component. We obtained data from 333 dizygotic twin pairs and 99 monozygotic twin pairs from 2 centers (Yale University and University of Connecticut). Data on chorioamnionitis, antenatal steroids, gestational age, body weight, gender, respiratory distress syndrome, patent ductus arteriosus, necrotizing enterocolitis, oxygen supplementation, and bronchopulmonary dysplasia were comparable between monozygotic and dizygotic twins. We found that gestational age, respiratory distress syndrome, and institution were significant covariates for patent ductus arteriosus. After controlling for specific covariates, genetic factors or the shared environment accounted for 76.1% of the variance in liability for patent ductus arteriosus. Preterm patent ductus arteriosus is highly familial (contributed to by genetic and environmental factors), with the effect being mainly environmental, after controlling for known confounders.
Directory of Open Access Journals (Sweden)
Guy M L Perry
Full Text Available Our work in a rodent model of urinary calcium suggests genetic and gender effects on increased residual variability in urine chemistries. Based on these findings, we hypothesized that sex would similarly be associated with residual variation in human urine solutes. Sex-related effects on residuals might affect the establishment of physiological baselines and error in medical assays.We tested the effects of sex on residual variation in urine chemistry by estimating coefficients of variation (CV for urinary solutes in paired sequential 24-h urines (≤72 hour interval in 6,758 females and 9,024 males aged 16-80 submitted to a clinical laboratory.Females had higher CVs than males for urinary phosphorus overall at the False Discovery Rate (P0.3. Males had higher CVs for citrate (P<0.01 from ages 16-45 and females higher CVs for citrate (P<0.01 from ages 56-80, suggesting effects of an extant oestral cycle on residual variance.Our findings indicate the effects of sex on residual variance of the excretion of urinary solutes including phosphorus and citrate; differences in CV by sex might reflect dietary lability, differences in the fidelity of reporting or genetic differentiation in renal solute consistency. Such an effect could complicate medical analysis by the addition of random error to phenotypic assays. Renal analysis might require explicit incorporation of heterogeneity among factorial effects, and for sex in particular.
International Nuclear Information System (INIS)
Bartusch, Cajsa; Odlare, Monica; Wallin, Fredrik; Wester, Lars
2012-01-01
Highlights: ► Statistical analysis of variance are of considerable value in identifying key indicators for policy update. ► Variance in residential electricity use is partly explained by household features. ► Variance in residential electricity use is partly explained by building properties. ► Household behavior has a profound impact on individual electricity use. -- Abstract: Improved means of controlling electricity consumption plays an important part in boosting energy efficiency in the Swedish power market. Developing policy instruments to that end requires more in-depth statistics on electricity use in the residential sector, among other things. The aim of the study has accordingly been to assess the extent of variance in annual electricity consumption in single-family homes as well as to estimate the impact of household features and building properties in this respect using independent samples t-tests and one-way as well as univariate independent samples analyses of variance. Statistically significant variances associated with geographic area, heating system, number of family members, family composition, year of construction, electric water heater and electric underfloor heating have been established. The overall result of the analyses is nevertheless that variance in residential electricity consumption cannot be fully explained by independent variables related to household and building characteristics alone. As for the methodological approach, the results further suggest that methods for statistical analysis of variance are of considerable value in indentifying key indicators for policy update and development.
Discussion on variance reduction technique for shielding
Energy Technology Data Exchange (ETDEWEB)
Maekawa, Fujio [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1998-03-01
As the task of the engineering design activity of the international thermonuclear fusion experimental reactor (ITER), on 316 type stainless steel (SS316) and the compound system of SS316 and water, the shielding experiment using the D-T neutron source of FNS in Japan Atomic Energy Research Institute has been carried out. However, in these analyses, enormous working time and computing time were required for determining the Weight Window parameter. Limitation or complication was felt when the variance reduction by Weight Window method of MCNP code was carried out. For the purpose of avoiding this difficulty, investigation was performed on the effectiveness of the variance reduction by cell importance method. The conditions of calculation in all cases are shown. As the results, the distribution of fractional standard deviation (FSD) related to neutrons and gamma-ray flux in the direction of shield depth is reported. There is the optimal importance change, and when importance was increased at the same rate as that of the attenuation of neutron or gamma-ray flux, the optimal variance reduction can be done. (K.I.)
Mosing, Miriam A; Gordon, Scott D; Medland, Sarah E; Statham, Dixie J; Nelson, Elliot C; Heath, Andrew C; Martin, Nicholas G; Wray, Naomi R
2009-01-01
Major depression (MD) and anxiety disorders such as panic disorder (PD), agoraphobia (AG), and social phobia (SP) are heritable and highly co-morbid. However, the relative importance of genetic and environmental etiology of the covariation between these disorders, particularly the relationship between PD and AG, is less clear. This study measured MD, PD, and AG in a population sample of 5,440 twin pairs and 1,245 single twins, about 45% of whom were also scored for SP. Prevalences, within individual co-morbidity and twin odds ratios for co-morbidity, are reported. A behavioral genetic analysis of the four disorders using the classical twin design was conducted. Odds ratios for MD, PD, AG, and SP in twins of individuals diagnosed with one of the four disorders were increased. Heritability estimates under a threshold-liability model for MD, PD, AG, and SP respectively were .33 (CI: 0.30-0.42), .38 (CI: 0.24-0.55), .48 (CI: 0.37-0.65), and .39 (CI: 0.16-0.65), with no evidence for any variance explained by the common environment shared by twins. We find that a common genetic factor explains a moderate proportion of variance in these four disorders. The genetic correlation between PD and AG was .83. MD, PD, AG, and SP strongly co-aggregate within families and common genetic factors explain a moderate proportion of variance in these four disorders. The high genetic correlation between PD and AG and the increased odds ratio for PD and AG in siblings of those with AG without PD suggests a common genetic etiology for PD and AG.
Estimation in a multiplicative mixed model involving a genetic relationship matrix
Directory of Open Access Journals (Sweden)
Eccleston John A
2009-04-01
Full Text Available Abstract Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.
Capturing option anomalies with a variance-dependent pricing kernel
Christoffersen, P.; Heston, S.; Jacobs, K.
2013-01-01
We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is
29 CFR 1904.38 - Variances from the recordkeeping rule.
2010-07-01
..., DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Other OSHA Injury and Illness... he or she finds appropriate. (iv) If the Assistant Secretary grants your variance petition, OSHA will... Secretary is reviewing your variance petition. (4) If I have already been cited by OSHA for not following...
Genetic divergence of tomato subsamples
Directory of Open Access Journals (Sweden)
André Pugnal Mattedi
2014-02-01
Full Text Available Understanding the genetic variability of a species is crucial for the progress of a genetic breeding program and requires characterization and evaluation of germplasm. This study aimed to characterize and evaluate 101 tomato subsamples of the Salad group (fresh market and two commercial controls, one of the Salad group (cv. Fanny and another of the Santa Cruz group (cv. Santa Clara. Four experiments were conducted in a randomized block design with three replications and five plants per plot. The joint analysis of variance was performed and characteristics with significant complex interaction between control and experiment were excluded. Subsequently, the multicollinearity diagnostic test was carried out and characteristics that contributed to severe multicollinearity were excluded. The relative importance of each characteristics for genetic divergence was calculated by the Singh's method (Singh, 1981, and the less important ones were excluded according to Garcia (1998. Results showed large genetic divergence among the subsamples for morphological, agronomic and organoleptic characteristics, indicating potential for genetic improvement. The characteristics total soluble solids, mean number of good fruits per plant, endocarp thickness, mean mass of marketable fruit per plant, total acidity, mean number of unmarketable fruit per plant, internode diameter, internode length, main stem thickness and leaf width contributed little to the genetic divergence between the subsamples and may be excluded in future studies.
DEFF Research Database (Denmark)
Ketola, Tarmo; Kellermann, Vanessa; Kristensen, Torsten Nygård
2012-01-01
and their fluctuations. How species will respond to these changes is uncertain, particularly as there is a lack of studies which compare genetic performances in constant vs. fluctuating environments. In this study, we used a nested full-sib/half-sib breeding design to examine how the genetic variances and heritabilities...
Adenosarcoma arising in hepatic endometriosis
International Nuclear Information System (INIS)
N'Senda, P.; Dahan, H.; Tubiana, J.M.; Arrive, L.; Wendum, D.; Balladur, P.
2000-01-01
We report a case of adenosarcoma arising in hepatic endometriosis. Both CT and MR scans demontrated a huge heterogeneous mass containing septated, thick-walled cystic lesions. After enlarged right hepatectomy, the patient was asymptomatic with no abnormalities at liver and abdominal CT scan at 2-year follow-up. (orig.)
Adenosarcoma arising in hepatic endometriosis
Energy Technology Data Exchange (ETDEWEB)
N' Senda, P.; Dahan, H.; Tubiana, J.M.; Arrive, L. [Service de Radiologie, Hopital Saint-Antoine, 75 - Paris (France); Wendum, D. [Service d' Anatomie Pathologie, Hopital Saint-Antoine, 75 - Paris (France); Balladur, P. [Service de Chirurgie Digestive et Generale, Hopital Saint-Antoine, 75 - Paris (France)
2000-08-01
We report a case of adenosarcoma arising in hepatic endometriosis. Both CT and MR scans demontrated a huge heterogeneous mass containing septated, thick-walled cystic lesions. After enlarged right hepatectomy, the patient was asymptomatic with no abnormalities at liver and abdominal CT scan at 2-year follow-up. (orig.)
Kläning, Ulla; Trumbetta, Susan L; Gottesman, Irving I; Skytthe, Axel; Kyvik, Kirsten O; Bertelsen, Aksel
2016-03-01
We studied schizophrenia liability in a Danish population-based sample of 44 twin pairs (13 MZ, 31 DZ, SS plus OS) in order to replicate previous twin study findings using contemporary diagnostic criteria, to examine genetic liability shared between schizophrenia and other disorders, and to explore whether variance in schizophrenia liability attributable to environmental factors may have decreased with successive cohorts exposed to improvements in public health. ICD-10 diagnoses were determined by clinical interview. Although the best-fitting, most parsimonious biometric model of schizophrenia liability specified variance attributable to additive genetic and non-shared environmental factors, this model did not differ significantly from a model that also included non-additive genetic factors, consistent with recent interview-based twin studies. Schizophrenia showed strong genetic links to other psychotic disorders but much less so for the broader category of psychiatric disorders in general. We also observed a marginally significant decline in schizophrenia variance attributable to environmental factors over successive Western European cohorts, consistent perhaps with improvements in diagnosis and in prenatal and perinatal care and with a secular decline in the prevalence of schizophrenia in that region.
Directory of Open Access Journals (Sweden)
C. I. Cho
2016-05-01
Full Text Available The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs, and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK, fat yield (FAT, protein yield (PROT, and solids-not-fat yield (SNF. The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP of the third to fifth order (L3–L5, fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order. The residual variances in the models were either homogeneous (HOM or heterogeneous (15 classes, HET15; 60 classes, HET60. A total of nine models (3 orders of polynomials×3 types of residual variance including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC and/or Schwarz Bayesian information criteria (BIC statistics to identify the model(s of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF and L4-HET15 (FAT, which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first
Analysis of ulnar variance as a risk factor for developing scaphoid nonunion.
Lirola-Palmero, S; Salvà-Coll, G; Terrades-Cladera, F J
2015-01-01
Ulnar variance may be a risk factor of developing scaphoid non-union. A review was made of the posteroanterior wrist radiographs of 95 patients who were diagnosed of scaphoid fracture. All fractures with displacement less than 1mm treated conservatively were included. The ulnar variance was measured in all patients. Ulnar variance was measured in standard posteroanterior wrist radiographs of 95 patients. Eighteen patients (19%) developed scaphoid nonunion, with a mean value of ulnar variance of -1.34 (-/+ 0.85) mm (CI -2.25 - 0.41). Seventy seven patients (81%) healed correctly, and the mean value of ulnar variance was -0.04 (-/+ 1.85) mm (CI -0.46 - 0.38). A significant difference was observed in the distribution of ulnar variance (pvariance less than -1mm, and ulnar variance greater than -1mm. It appears that patients with ulnar variance less than -1mm had an OR 4.58 (CI 1.51 to 13.89) with pvariance less than -1mm have a greater risk of developing scaphoid nonunion, OR 4.58 (CI 1.51 to 13.89) with p<.007. Copyright © 2014 SECOT. Published by Elsevier Espana. All rights reserved.
Genetic Allee effects and their interaction with ecological Allee effects.
Wittmann, Meike J; Stuis, Hanna; Metzler, Dirk
2018-01-01
It is now widely accepted that genetic processes such as inbreeding depression and loss of genetic variation can increase the extinction risk of small populations. However, it is generally unclear whether extinction risk from genetic causes gradually increases with decreasing population size or whether there is a sharp transition around a specific threshold population size. In the ecological literature, such threshold phenomena are called 'strong Allee effects' and they can arise for example from mate limitation in small populations. In this study, we aim to (i) develop a meaningful notion of a 'strong genetic Allee effect', (ii) explore whether and under what conditions such an effect can arise from inbreeding depression due to recessive deleterious mutations, and (iii) quantify the interaction of potential genetic Allee effects with the well-known mate-finding Allee effect. We define a strong genetic Allee effect as a genetic process that causes a population's survival probability to be a sigmoid function of its initial size. The inflection point of this function defines the critical population size. To characterize survival-probability curves, we develop and analyse simple stochastic models for the ecology and genetics of small populations. Our results indicate that inbreeding depression can indeed cause a strong genetic Allee effect, but only if individuals carry sufficiently many deleterious mutations (lethal equivalents). Populations suffering from a genetic Allee effect often first grow, then decline as inbreeding depression sets in and then potentially recover as deleterious mutations are purged. Critical population sizes of ecological and genetic Allee effects appear to be often additive, but even superadditive interactions are possible. Many published estimates for the number of lethal equivalents in birds and mammals fall in the parameter range where strong genetic Allee effects are expected. Unfortunately, extinction risk due to genetic Allee effects
Decomposition of variance in terms of conditional means
Directory of Open Access Journals (Sweden)
Alessandro Figà Talamanca
2013-05-01
Full Text Available Two different sets of data are used to test an apparently new approach to the analysis of the variance of a numerical variable which depends on qualitative variables. We suggest that this approach be used to complement other existing techniques to study the interdependence of the variables involved. According to our method, the variance is expressed as a sum of orthogonal components, obtained as differences of conditional means, with respect to the qualitative characters. The resulting expression for the variance depends on the ordering in which the characters are considered. We suggest an algorithm which leads to an ordering which is deemed natural. The first set of data concerns the score achieved by a population of students on an entrance examination based on a multiple choice test with 30 questions. In this case the qualitative characters are dyadic and correspond to correct or incorrect answer to each question. The second set of data concerns the delay to obtain the degree for a population of graduates of Italian universities. The variance in this case is analyzed with respect to a set of seven specific qualitative characters of the population studied (gender, previous education, working condition, parent's educational level, field of study, etc..
Directory of Open Access Journals (Sweden)
Hossein Farasat
Full Text Available Species often exhibit different levels of genetic structuring correlated to their environment. However, understanding how environmental heterogeneity influences genetic variation is difficult because the effects of gene flow, drift and selection are confounded. We investigated the genetic variation and its ecological correlates in an endemic and critically endangered stream breeding mountain newt, Neurergus kaiseri, within its entire range in southwestern Iran. We identified two geographic regions based on phylogenetic relationships using Bayesian inference and maximum likelihood of 779 bp mtDNA (D-loop in 111 individuals from ten of twelve known breeding populations. This analysis revealed a clear divergence between northern populations, located in more humid habitats at higher elevation, and southern populations, from drier habitats at lower elevations regions. From seven haplotypes found in these populations none was shared between the two regions. Analysis of molecular variance (AMOVA of N. kaiseri indicates that 94.03% of sequence variation is distributed among newt populations and 5.97% within them. Moreover, a high degree of genetic subdivision, mainly attributable to the existence of significant variance among the two regions is shown (θCT = 0.94, P = 0.002. The positive and significant correlation between geographic and genetic distances (r = 0.61, P = 0.002 following controlling for environmental distance suggests an important influence of geographic divergence of the sites in shaping the genetic variation and may provide tools for a possible conservation based prioritization policy for the endangered species.
42 CFR 456.522 - Content of request for variance.
2010-10-01
... 42 Public Health 4 2010-10-01 2010-10-01 false Content of request for variance. 456.522 Section 456.522 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... perform UR within the time requirements for which the variance is requested and its good faith efforts to...
On the Endogeneity of the Mean-Variance Efficient Frontier.
Somerville, R. A.; O'Connell, Paul G. J.
2002-01-01
Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…
Assessment of ulnar variance: a radiological investigation in a Dutch population
Energy Technology Data Exchange (ETDEWEB)
Schuurman, A.H. [Dept. of Plastic, Reconstructive and Hand Surgery, University Medical Centre, Utrecht (Netherlands); Dept. of Plastic Surgery, University Medical Centre, Utrecht (Netherlands); Maas, M.; Dijkstra, P.F. [Dept. of Radiology, Univ. of Amsterdam (Netherlands); Kauer, J.M.G. [Dept. of Anatomy and Embryology, Univ. of Nijmegen (Netherlands)
2001-11-01
Objective: A radiological study was performed to evaluate ulnar variance in 68 Dutch patients using an electronic digitizer compared with Palmer's concentric circle method. Using the digitizer method only, the effect of different wrist positions and grip on ulnar variance was then investigated. Finally the distribution of ulnar variance in the selected patients was investigated also using the digitizer method. Design and patients: All radiographs were performed with the wrist in a standard zero-rotation position (posteroanterior) and in supination (anteroposterior). Palmer's concentric circle method and an electronic digitizer connected to a personal computer were used to measure ulnar variance. The digitizer consists of a Plexiglas plate with an electronically activated grid beneath it. A radiograph is placed on the plate and a cursor activates a point on the grid. Three plots are marked on the radius and one plot on the most distal part of the ulnar head. The digitizer then determines the difference between a radius passing through the radius plots and the ulnar plot. Results and conclusions: Using the concentric circle method we found an ulna plus predominance, but an ulna minus predominance when using the digitizer method. Overall the ulnar variance distribution for Palmer's method was 41.9% ulna plus, 25.7% neutral and 32.4% ulna minus variance, and for the digitizer method was 40.4% ulna plus, 1.5% neutral and 58.1% ulna minus. The percentage ulnar variance greater than 1 mm on standard radiographs increased from 23% to 58% using the digitizer, with maximum grip, clearly demonstrating the (dynamic) effect of grip on ulnar variance. This almost threefold increase was found to be a significant difference. Significant differences were found between ulnar variance when different wrist positions were compared. (orig.)
Li, Wen-Dong; Stanek, Kevin C; Zhang, Zhen; Ones, Deniz S; McGue, Matt
2016-11-01
Job satisfaction research has unfolded as an exemplary manifestation of the "person versus environment" debate in applied psychology. With the increasing recognition of the importance of time, it is informative to examine a question critical to the dispositional view of job satisfaction: Are genetic influences on job satisfaction stable across different time points? Drawing upon dispositional and situational perspectives on job satisfaction and recent research in developmental behavioral genetics, we examined whether the relative potency of genetic (i.e., the person) and environmental influences on job satisfaction changed over time in a 3-wave longitudinal twin study. Biometric behavioral genetics analyses showed that genetic influences accounted for 31.2% of the variance in job satisfaction measured at approximately Age 21, which was markedly greater than the 18.7% and 19.8% of variance explained by genetic factors at Age 25 and Age 30. Such genetic influences were mediated via positive affectivity and negative affectivity, but not via general mental ability. After partialing out genetic influences, environmental influences on job satisfaction were related to interpersonal conflict at work and occupational status, and these influences were relatively stable across the 3 time points. These results offer important implications for organizations and employees to better understand and implement practices to enhance job satisfaction. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Origins of gene, genetic code, protein and life
Indian Academy of Sciences (India)
Unknown
have concluded that newly-born genes are products of nonstop frames (NSF) ... research to determine tertiary structures of proteins such ... the present earth, is favourable for new genes to arise, if ..... NGG) in the universal genetic code table, cannot satisfy ..... which has been proposed to explain the development of life on.
Genetic diversity of indigenous chickens from selected areas in Kenya using microsatellite markers
Directory of Open Access Journals (Sweden)
Okoth Noah Okumu
2017-12-01
Full Text Available In this study, indigenous chickens were collected from eight different regions in Kenya and kept at InCIP-Egerton University. These were studied using eighteen microsatellite markers to determine genetic variation. Statistics related to genetic variation were estimated using GenALEx6. Mean percentage polymorphic loci (PPL was 96.71% and 4% genetic variance (p ≥ 0.003 was seen between the eight populations. MCW0123 marker had the highest genetic variance of 13% among populations (p ≥ 0.003 at 95% CI. Mean He ranged from 0.351 ± 0.031 (SIB to 0.434 ± 0.022 (BM with a grand mean He of 0.399 ± 0.011 across the populations using the microsatellite markers. Nei’s genetic distance ranged from 0.016 (SIB and WP to 0.126 (NR and SIB. DARwin6.501 analysis software was used to draw the population dendrogram and two major population clusters were observed, also seen with PCoA. This study found a lot of genetic variation and relatedness within and among populations. Based on the phylogenetic tree result, it is concluded that the clustering of the chicken populations in the present study is not based on geographical proximity. The microsatellite markers used in this study were suitable for the measurement of the genetic biodiversity and relationship of Kenyan chicken populations. These results can therefore serve as an initial step to plan the conservation of indigenous chickens in Kenya.
DEFF Research Database (Denmark)
Baillie, J. Kenneth; Bretherick, Andrew; Haley, Christopher S.
2018-01-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcrip...
Variance and covariance calculations for nuclear materials accounting using ''MAVARIC''
International Nuclear Information System (INIS)
Nasseri, K.K.
1987-07-01
Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined
A versatile omnibus test for detecting mean and variance heterogeneity.
Cao, Ying; Wei, Peng; Bailey, Matthew; Kauwe, John S K; Maxwell, Taylor J
2014-01-01
Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (G × G), or gene-by-environment interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRT(MV)) or either effect alone (LRT(M) or LRT(V)) in the presence of covariates. Using extensive simulations for our method and others, we found that all parametric tests were sensitive to nonnormality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant, we demonstrate how LD can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D', and relatively low r² values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance-only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect G × G interactions and also how vQTL are related to relationship loci, and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait.
Variance and covariance calculations for nuclear materials accounting using 'MAVARIC'
International Nuclear Information System (INIS)
Nasseri, K.K.
1987-01-01
Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined
Genetics of Gigantism and Acromegaly
Hannah-Shmouni, Fady; Trivellin, Giampaolo; Stratakis, Constantine A.
2016-01-01
Gigantism and acromegaly are rare disorders that are caused by excessive GH secretion and/or high levels of its mediator, IGF-1. Gigantism occurs when excess GH or IGF-1 lead to increased linear growth, before the end of puberty and epiphyseal closure. The majority of cases arise from a benign GH-secreting pituitary adenoma, with an incidence of pituitary gigantism and acromegaly of approximately 8 and 11 per million person-years, respectively. Over the past two decades, our increasing understanding of the molecular and genetic etiologies of pituitary gigantism and acromegaly yielded several genetic causes, including multiple endocrine neoplasia type 1 and 4, McCune-Albright syndrome, Carney complex, familial isolated pituitary adenoma, pituitary adenoma association due to defects in familial succinate dehydrogenase genes, and the recently identified X-linked acrogigantism. The early diagnosis of these conditions helps guide early intervention, screening, and genetic counseling of patients and their family members. In this review, we provide a concise and up-to-date discussion on the genetics of gigantism and acromegaly. PMID:27657986
Genetics of gigantism and acromegaly.
Hannah-Shmouni, Fady; Trivellin, Giampaolo; Stratakis, Constantine A
Gigantism and acromegaly are rare disorders that are caused by excessive GH secretion and/or high levels of its mediator, IGF-1. Gigantism occurs when excess GH or IGF-1 lead to increased linear growth, before the end of puberty and epiphyseal closure. The majority of cases arise from a benign GH-secreting pituitary adenoma, with an incidence of pituitary gigantism and acromegaly of approximately 8 and 11 per million person-years, respectively. Over the past two decades, our increasing understanding of the molecular and genetic etiologies of pituitary gigantism and acromegaly yielded several genetic causes, including multiple endocrine neoplasia type 1 and 4, McCune-Albright syndrome, Carney complex, familial isolated pituitary adenoma, pituitary adenoma association due to defects in familial succinate dehydrogenase genes, and the recently identified X-linked acrogigantism. The early diagnosis of these conditions helps guide early intervention, screening, and genetic counseling of patients and their family members. In this review, we provide a concise and up-to-date discussion on the genetics of gigantism and acromegaly. Published by Elsevier Ltd.
Directory of Open Access Journals (Sweden)
J.E.G. Campelo
2003-12-01
Full Text Available Verificou-se a influência da heterogeneidade de variâncias na avaliação genética de bovinos de corte da raça Tabapuã. Dados de pesos corrigidos aos 120, 240 e 420 dias de idade foram estratificados com base no desvio-padrão fenotípico do peso aos 120 dias dos grupos de contemporâneos em três classes: baixo (18,9kg desvio-padrão. Nas análises de múltiplas características, em que o peso foi considerado característica distinta em cada classe de desvio-padrão, constatou-se que as variâncias genéticas e residuais foram maiores com o aumento do desvio-padrão da classe. As herdabilidades foram 0,26, 0,32 e 0,37 (peso aos 120 dias, 0,28, 0,35 e 0,35 (peso aos 240 dias e 0,14, 0,18 e 0,18 (peso aos 420 dias nas classes de baixo, médio e alto desvio-padrão, respectivamente. As correlações genéticas entre o mesmo peso, nas classes de baixo e alto desvio-padrão foram inferiores a 0,80. As correlações entre os valores genéticos, obtidos de análises múltiplas e de análise geral (sem as classes, foram superiores a 0,93. Observou-se que os reprodutores seriam classificados de forma similar se for considerada ou não a presença de variâncias heterogêneas nas análises.Data from Tabapuã beef cattle were used to study the influence of variance heterogeneity on genetic evaluation. Adjusted weights at 120, 240 and 420 days of age were classified in three classes of standard deviation: low (18.9kg, based on phenotypic standard deviation of the weight at 120 days of age of the contemporary groups. Multiple trait analyses, considering each class of phenotypic standard deviation as a distinct trait, were performed. The genetic and residual variances increased as the phenotypic standard deviation of the class increased. Heritabilities for low, medium and high phenotypic standard deviation classes were 0.26, 0.32 and 0.37 (weight at 120 days, 0.28, 0.35 and 0.35 (weight at 240 days and 0.14, 0.18 and 0.18 (weight at 420 days
Global Variance Risk Premium and Forex Return Predictability
Aloosh, Arash
2014-01-01
In a long-run risk model with stochastic volatility and frictionless markets, I express expected forex returns as a function of consumption growth variances and stock variance risk premiums (VRPs)—the difference between the risk-neutral and statistical expectations of market return variation. This provides a motivation for using the forward-looking information available in stock market volatility indices to predict forex returns. Empirically, I find that stock VRPs predict forex returns at a ...
Directory of Open Access Journals (Sweden)
Haley Christopher S
2009-01-01
Full Text Available Abstract Introduction Variance component QTL methodology was used to analyse three candidate regions on chicken chromosomes 1, 4 and 5 for dominant and parent-of-origin QTL effects. Data were available for bodyweight and conformation score measured at 40 days from a two-generation commercial broiler dam line. One hundred dams were nested in 46 sires with phenotypes and genotypes on 2708 offspring. Linear models were constructed to simultaneously estimate fixed, polygenic and QTL effects. Different genetic models were compared using likelihood ratio test statistics derived from the comparison of full with reduced or null models. Empirical thresholds were derived by permutation analysis. Results Dominant QTL were found for bodyweight on chicken chromosome 4 and for bodyweight and conformation score on chicken chromosome 5. Suggestive evidence for a maternally expressed QTL for bodyweight and conformation score was found on chromosome 1 in a region corresponding to orthologous imprinted regions in the human and mouse. Conclusion Initial results suggest that variance component analysis can be applied within commercial populations for the direct detection of segregating dominant and parent of origin effects.
Directory of Open Access Journals (Sweden)
Legault Christian
2000-01-01
Full Text Available Abstract Genetic parameters of body weight at 4 (W4 w, 8 (W8 w and 22 (W22 w weeks of age, days from 20 to 100 kg (DT, average backfat thickness at 100 kg (ABT, teat number (TEAT, number of good teats (GTEAT, total number of piglets born (TNB, born alive (NBA and weaned (NW per litter, and birth to weaning survival rate (SURV were estimated in the Chinese × European Tiameslan composite line using restricted maximum likelihood methodology applied to a multiple trait animal model. Performance data from a total of 4 881 males and 4 799 females from 1 341 litters were analysed. Different models were fitted to the data in order to estimate the importance of maternal effects on production traits, as well as genetic correlations between male and female performance. The results showed the existence of significant maternal effects on W4w, W8w and ABT and of variance heterogeneity between sexes for W22w, DT, ABT and GTEAT. Genetic correlations between sexes were 0.79, 0.71 and 0.82, respectively, for W22w, DT and ABT and above 0.90 for the other traits. Heritability estimates were larger than (ABT and TEAT or similar to (other traits average literature values. Some genetic antagonism was evidenced between production traits, particularly W4w, W8w and ABT, and reproductive traits.
Social isolation, loneliness and depression in young adulthood: a behavioural genetic analysis.
Matthews, Timothy; Danese, Andrea; Wertz, Jasmin; Odgers, Candice L; Ambler, Antony; Moffitt, Terrie E; Arseneault, Louise
2016-03-01
To investigate the association between social isolation and loneliness, how they relate to depression, and whether these associations are explained by genetic influences. We used data from the age-18 wave of the Environmental Risk Longitudinal Twin Study, a birth cohort of 1116 same-sex twin pairs born in England and Wales in 1994 and 1995. Participants reported on their levels of social isolation, loneliness and depressive symptoms. We conducted regression analyses to test the differential associations of isolation and loneliness with depression. Using the twin study design, we estimated the proportion of variance in each construct and their covariance that was accounted for by genetic and environmental factors. Social isolation and loneliness were moderately correlated (r = 0.39), reflecting the separateness of these constructs, and both were associated with depression. When entered simultaneously in a regression analysis, loneliness was more robustly associated with depression. We observed similar degrees of genetic influence on social isolation (40 %) and loneliness (38 %), and a smaller genetic influence on depressive symptoms (29 %), with the remaining variance accounted for by the non-shared environment. Genetic correlations of 0.65 between isolation and loneliness and 0.63 between loneliness and depression indicated a strong role of genetic influences in the co-occurrence of these phenotypes. Socially isolated young adults do not necessarily experience loneliness. However, those who are lonely are often depressed, partly because the same genes influence loneliness and depression. Interventions should not only aim at increasing social connections but also focus on subjective feelings of loneliness.
Long current to nowhere? — Genetic connectivity of Jasus tristani ...
African Journals Online (AJOL)
Our results show that J. tristani in the southern Atlantic share a most recent common ancestry that dates back at least one million years. Analyses of molecular variance and pairwise Φst analyses reveal shallow but significant genetic partitioning between Vema Seamount and all other locations. No population differentiation ...
2010-07-01
...) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR WORKERS...) or 6(d) of the Williams-Steiger Occupational Safety and Health Act of 1970 (29 U.S.C. 655). The... under the Williams-Steiger Occupational Safety and Health Act of 1970, and any variance from §§ 1910.13...
Zero-intelligence realized variance estimation
Gatheral, J.; Oomen, R.C.A.
2010-01-01
Given a time series of intra-day tick-by-tick price data, how can realized variance be estimated? The obvious estimator—the sum of squared returns between trades—is biased by microstructure effects such as bid-ask bounce and so in the past, practitioners were advised to drop most of the data and
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García-González Francisco
2008-05-01
Full Text Available Abstract Background The determination of genetic variation in sperm competitive ability is fundamental to distinguish between post-copulatory sexual selection models based on good-genes vs compatible genes. The sexy-sperm and the good-sperm hypotheses for the evolution of polyandry require additive (intrinsic effects of genes influencing sperm competitiveness, whereas the genetic incompatibility hypothesis invokes non-additive genetic effects. A male's sperm competitive ability is typically estimated from his fertilization success, a measure that is dependent on the ability of rival sperm competitors to fertilize the ova. It is well known that fertilization success may be conditional to genotypic interactions among males as well as between males and females. However, the consequences of effects arising from the random sampling of sperm competitors upon the estimation of genetic variance in sperm competitiveness have been overlooked. Here I perform simulations of mating trials performed in the context of sibling analysis to investigate whether the ability to detect additive genetic variance underlying the sperm competitiveness phenotype is hindered by the relative nature of fertilization success measurements. Results Fertilization success values render biased sperm competitive ability values. Furthermore, asymmetries among males in the errors committed when estimating sperm competitive abilities are likely to exist as long as males exhibit variation in sperm competitiveness. Critically, random effects arising from the relative nature of fertilization success lead to an underestimation of underlying additive genetic variance in sperm competitive ability. Conclusion The results show that, regardless of the existence of genotypic interactions affecting the output of sperm competition, fertilization success is not a perfect predictor of sperm competitive ability because of the stochasticity of the background used to obtain fertilization success
A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.
Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio
2017-11-01
Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this
The mean and variance of phylogenetic diversity under rarefaction.
Nipperess, David A; Matsen, Frederick A
2013-06-01
Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.
Bio-inspired computational heuristics to study Lane-Emden systems arising in astrophysics model.
Ahmad, Iftikhar; Raja, Muhammad Asif Zahoor; Bilal, Muhammad; Ashraf, Farooq
2016-01-01
This study reports novel hybrid computational methods for the solutions of nonlinear singular Lane-Emden type differential equation arising in astrophysics models by exploiting the strength of unsupervised neural network models and stochastic optimization techniques. In the scheme the neural network, sub-part of large field called soft computing, is exploited for modelling of the equation in an unsupervised manner. The proposed approximated solutions of higher order ordinary differential equation are calculated with the weights of neural networks trained with genetic algorithm, and pattern search hybrid with sequential quadratic programming for rapid local convergence. The results of proposed solvers for solving the nonlinear singular systems are in good agreements with the standard solutions. Accuracy and convergence the design schemes are demonstrated by the results of statistical performance measures based on the sufficient large number of independent runs.
Genetic analysis of growth traits in Iranian Makuie sheep breed
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Mohammad Farhadian
2012-01-01
Full Text Available The Makuie sheep is a fat-tailed sheep breed which can be found in the Azerbaijan province of Iran. In 1986, a Makuie sheep breeding station was established in the city of Maku in order to breed, protect and purify this breed. The genetic parameters for birth weight, weaning weight (3 months, 6-month, 9-month and yearling weight, and average daily gain from birth to weaning traits were estimated based on 25 years of data using DFREML software. Six different models were applied and a likelihood ratio test (LRT was used to select the appropriate model. Bivariate analysis was used to define the genetic correlation between studied traits. Based on the LRT, model II was selected as an appropriate model for all studied traits. Direct heritability estimates of birth, weaning, 6-month, 9-month and yearling weights and average daily gain from birth to weaning were 0.36, 0.41, 0.48, 0.42, 0.36 and 0.37, respectively. Estimates of direct genetic correlation between birth and weaning weights, birth and 6-month weights, birth and 9-month weights, as well as between birth and yearling weights were 0.57, 0.49, 0.46 and 0.32, respectively. The results suggest there is a substantial additive genetic variability for studied traits in the Makuie sheep breed population, and the direct additive effect and maternal permanent environment variance are the main source of phenotypic variance.
Using variances to comply with resource conservation and recovery act treatment standards
International Nuclear Information System (INIS)
Ranek, N.L.
2002-01-01
When a waste generated, treated, or disposed of at a site in the United States is classified as hazardous under the Resource Conservation and Recovery Act and is destined for land disposal, the waste manager responsible for that site must select an approach to comply with land disposal restrictions (LDR) treatment standards. This paper focuses on the approach of obtaining a variance from existing, applicable LDR treatment standards. It describes the types of available variances, which include (1) determination of equivalent treatment (DET); (2) treatability variance; and (3) treatment variance for contaminated soil. The process for obtaining each type of variance is also described. Data are presented showing that historically the U.S. Environmental Protection Agency (EPA) processed DET petitions within one year of their date of submission. However, a 1999 EPA policy change added public participation to the DET petition review, which may lengthen processing time in the future. Regarding site-specific treatability variances, data are presented showing an EPA processing time of between 10 and 16 months. Only one generically applicable treatability variance has been granted, which took 30 months to process. No treatment variances for contaminated soil, which were added to the federal LDR program in 1998, are identified as having been granted.
Principal component approach in variance component estimation for international sire evaluation
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Jakobsen Jette
2011-05-01
Full Text Available Abstract Background The dairy cattle breeding industry is a highly globalized business, which needs internationally comparable and reliable breeding values of sires. The international Bull Evaluation Service, Interbull, was established in 1983 to respond to this need. Currently, Interbull performs multiple-trait across country evaluations (MACE for several traits and breeds in dairy cattle and provides international breeding values to its member countries. Estimating parameters for MACE is challenging since the structure of datasets and conventional use of multiple-trait models easily result in over-parameterized genetic covariance matrices. The number of parameters to be estimated can be reduced by taking into account only the leading principal components of the traits considered. For MACE, this is readily implemented in a random regression model. Methods This article compares two principal component approaches to estimate variance components for MACE using real datasets. The methods tested were a REML approach that directly estimates the genetic principal components (direct PC and the so-called bottom-up REML approach (bottom-up PC, in which traits are sequentially added to the analysis and the statistically significant genetic principal components are retained. Furthermore, this article evaluates the utility of the bottom-up PC approach to determine the appropriate rank of the (covariance matrix. Results Our study demonstrates the usefulness of both approaches and shows that they can be applied to large multi-country models considering all concerned countries simultaneously. These strategies can thus replace the current practice of estimating the covariance components required through a series of analyses involving selected subsets of traits. Our results support the importance of using the appropriate rank in the genetic (covariance matrix. Using too low a rank resulted in biased parameter estimates, whereas too high a rank did not result in
Rey, Martin P.; Pontzen, Andrew
2018-02-01
Recent work has studied the interplay between a galaxy's history and its observable properties using `genetically modified' cosmological zoom simulations. The approach systematically generates alternative histories for a halo, while keeping its cosmological environment fixed. Applications to date altered linear properties of the initial conditions, such as the mean overdensity of specified regions; we extend the formulation to include quadratic features, such as local variance, that determines the overall importance of smooth accretion relative to mergers in a galaxy's history. We introduce an efficient algorithm for this new class of modification and demonstrate its ability to control the variance of a region in a one-dimensional toy model. Outcomes of this work are twofold: (i) a clarification of the formulation of genetic modifications and (ii) a proof of concept for quadratic modifications leading the way to a forthcoming implementation in cosmological simulations.
Genetic diversity of Mycosphaerella fijiensis in Brazil analyzed using an ERIC-PCR marker.
Silva, G F; Paixão, R D V; Queiroz, C B; Santana, M F; Souza, A; Sousa, N R; Hanada, R E; Gasparotto, L
2014-09-26
The Enterobacterial repetitive intergenic consensus (ERIC) marker was used to analyze the genetic variability of Mycosphaerella fijiensis, the causative agent of Black Sigatoka disease in banana plants. A total of 123 isolates were used, which were divided into populations based on their original hosts and collection sites in Brazil. A total of 9 loci were amplified, 77.8% of which were found to be polymorphic. The genetic diversity found in the population was 0.20. Analysis of molecular variance (AMOVA) demonstrated that the highest level of genetic variation is within populations. Cluster analysis revealed three main groups in Brazil, with no correlation between geographic and genetic distance.
Expansion Under Climate Change: The Genetic Consequences.
Garnier, Jimmy; Lewis, Mark A
2016-11-01
Range expansion and range shifts are crucial population responses to climate change. Genetic consequences are not well understood but are clearly coupled to ecological dynamics that, in turn, are driven by shifting climate conditions. We model a population with a deterministic reaction-diffusion model coupled to a heterogeneous environment that develops in time due to climate change. We decompose the resulting travelling wave solution into neutral genetic components to analyse the spatio-temporal dynamics of its genetic structure. Our analysis shows that range expansions and range shifts under slow climate change preserve genetic diversity. This is because slow climate change creates range boundaries that promote spatial mixing of genetic components. Mathematically, the mixing leads to so-called pushed travelling wave solutions. This mixing phenomenon is not seen in spatially homogeneous environments, where range expansion reduces genetic diversity through gene surfing arising from pulled travelling wave solutions. However, the preservation of diversity is diminished when climate change occurs too quickly. Using diversity indices, we show that fast expansions and range shifts erode genetic diversity more than slow range expansions and range shifts. Our study provides analytical insight into the dynamics of travelling wave solutions in heterogeneous environments.
Gini estimation under infinite variance
A. Fontanari (Andrea); N.N. Taleb (Nassim Nicholas); P. Cirillo (Pasquale)
2018-01-01
textabstractWe study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α∈(1,2)). We show that, in such a case, the Gini coefficient
Kendler, Kenneth S.; Myers, John M.; Keyes, Corey L. M.
2012-01-01
To determine the relationship between the genetic and environmental risk factors for externalizing psychopathology and mental wellbeing, we examined detailed measures of emotional, social and psychological wellbeing, and a history of alcohol-related problems and smoking behavior in the last year in 1,386 individual twins from same-sex pairs from the MIDUS national US sample assessed in 1995. Cholesky decomposition analyses were performed with the Mx program. The best fit model contained one highly heritable common externalizing psychopathology factor for both substance use/abuse measures, and one strongly heritable common factor for the three wellbeing measures. Genetic and environmental risk factors for externalizing psychopathology were both negatively associated with levels of mental wellbeing and accounted for, respectively, 7% and 21% of its genetic and environmental influences. Adding internalizing psychopathology assessed in the last year to the model, genetic risk factors unique for externalizing psychopathology were now positively related to levels of mental wellbeing, although accounting for only 5% of the genetic variance. Environmental risk factors unique to externalizing psychopathology continued to be negatively associated with mental wellbeing, accounting for 26% of the environmental variance. When both internalizing psychopathology and externalizing psychopathology are associated with mental wellbeing, the strongest risk factors for low mental wellbeing are genetic factors that impact on both internalizing psychopathology and externalizing psychopathology, and environmental factors unique to externalizing psychopathology. In this model, genetic risk factors for externalizing psychopathology predict, albeit weakly, higher levels of mental wellbeing. PMID:22506307
Cutaneous osteosarcoma arising from a burn scar
Energy Technology Data Exchange (ETDEWEB)
Lee, Min A.; Yi, Jaehyuck [Kyungpook National University, Department of Radiology, College of Medicine, Daegu (Korea, Republic of); Kyungpook National University Hospital, Department of Radiology, Daegu (Korea, Republic of); Chae, Jong Min [Kyungpook National University, Department of Pathology, College of Medicine, Daegu (Korea, Republic of)
2017-04-15
Tumors that develop in old burn scars are usually squamous cell carcinomas. Sarcomas have also been reported, albeit rarely. To our knowledge, there has been only one case report of an extraskeletal osteosarcoma arising in a prior burn scar reported in the English-language literature, mainly discussing the clinicopathological features. Herein, we present a case of cutaneous osteosarcoma visualized as a mineralized soft-tissue mass arising from the scar associated with a previous skin burn over the back. This seems to be the first report describing the imaging features of a cutaneous osteosarcoma from an old burn scar. (orig.)
Directory of Open Access Journals (Sweden)
Chizuru eShikishima
2015-11-01
Full Text Available Why does decision making differ among individuals? People sometimes make seemingly inconsistent decisions with lower expected (monetary utility even when objective information of probabilities and rewards are provided. It is noteworthy, however, that a certain proportion of people do not provide anomalous responses, choosing the alternatives with higher expected utility, thus appearing to be more rational. We investigated the genetic and environmental influences on these types of individual differences in decision making using a classical Allais problem task. Participants were 1,199 Japanese adult twins aged 20–47. Univariate genetic analysis revealed that approximately a third of the Allais problem response variance was explained by genetic factors and the rest by environmental factors unique to individuals and measurement error. The environmental factor shared between families did not contribute to the variance. Subsequent multivariate genetic analysis clarified that decision making using the expected utility theory was associated with general intelligence and that the association was largely mediated by the same genetic factor. We approach the mechanism underlying two types of rational decision making from the perspective of genetic correlations with cognitive abilities.
Variance analysis of forecasted streamflow maxima in a wet temperate climate
Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.
2018-05-01
Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.
Investigation on Genetic Variation of Iran Watermelon Accession
Directory of Open Access Journals (Sweden)
majid reza kiyani
2009-06-01
Full Text Available In order to determine of genetic variation in germplasm of 120 watermelon accessions, a field trial conducted at agricultural and natural resource research center of khorasan . These Accessions with four commercial cultivars as control were planted in agnomental design with six replications. 15 quantitative morphological traits were measured and some statistical parameter and analysis include of Mean, Coefficient variance, cluster analysis, correlation regression coefficients were determine for this traits. yield, Sugar percent , time between flowering and ripping, fruit length, fruit width, fruit mass to fruit weight ratio , fruit skin to fruit weight ratio , seed weight to fruit weight ratio , 100 seed weight , seed length , seed diameter , seed width were the most useful traits for identifying of genotypes from each other. A one side analysis of variance was performed for different regions genetic diversity detection, which indicated a significant difference between regions for all traits except fruit Ph and fruit skin thickness. Cluster analysis divided genotypes into eight groups based on quantitative data. Correlation analysis between traits showed a significant relation between yield and all traits except fruit ph, time to flowering and seed fruit length.
Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework
International Nuclear Information System (INIS)
Zhou, X.Y.; Li, D.
2000-01-01
This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be 'embedded' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem
Replica approach to mean-variance portfolio optimization
Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre
2016-12-01
We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r = N/T optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.
Linkage disequilibrium and association mapping.
Weir, B S
2008-01-01
Linkage disequilibrium refers to the association between alleles at different loci. The standard definition applies to two alleles in the same gamete, and it can be regarded as the covariance of indicator variables for the states of those two alleles. The corresponding correlation coefficient rho is the parameter that arises naturally in discussions of tests of association between markers and genetic diseases. A general treatment of association tests makes use of the additive and nonadditive components of variance for the disease gene. In almost all expressions that describe the behavior of association tests, additive variance components are modified by the squared correlation coefficient rho2 and the nonadditive variance components by rho4, suggesting that nonadditive components have less influence than additive components on association tests.
Realized Variance and Market Microstructure Noise
DEFF Research Database (Denmark)
Hansen, Peter R.; Lunde, Asger
2006-01-01
We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel......-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise its time-dependent and correlated with increments in the efficient price. This has important implications for volatility...... estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient...
Directory of Open Access Journals (Sweden)
Domozych Wojciech
2016-12-01
Full Text Available Dissociation is commonly regarded as a disruption in the normally integrated functions of memory, knowledge, affect, sensation or behavior. The present study utilized behavioral genetics’ methodology to investigate genetic and environmental basis of the relationship between dissociation and Cloninger’s temperament and character traits. A sample of 83 monozygotic and 65 dizygotic twins were administered self-report measures which assessed dissociative experiences along with personality dimensions. Significant correlations and high loads of common genetic variance between dissociative experiences and personality traits of novelty seeking, self-directedness, cooperativeness and self-transcendence were identified. Heritability of dissociative experiences was estimated at 62%. The study shows that there exists a considerable amount of genetic variance overlap between dissociation and personality dimensions. It also supports the hypothesis that propensity to dissociate is highly heritable
Spot Variance Path Estimation and its Application to High Frequency Jump Testing
Bos, C.S.; Janus, P.; Koopman, S.J.
2012-01-01
This paper considers spot variance path estimation from datasets of intraday high-frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects, and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used to
A novel genetic tool for clonal analysis of fourth chromosome mutations
Sousa-Neves, Rui; Schinaman, Joseph M.
2012-01-01
The fourth chromosome of Drosophila remains one of the most intractable regions of the fly genome to genetic analysis. The main difficulty posed to the genetic analyses of mutations on this chromosome arises from the fact that it does not undergo meiotic recombination, which makes recombination mapping impossible, and also prevents clonal analysis of mutations, a technique which relies on recombination to introduce the prerequisite recessive markers and FLP-recombinase recognition targets (FR...
Genetic control of the angular leaf spot reaction in common bean leaves and pods
Directory of Open Access Journals (Sweden)
Jerônimo Constantino Borel
2011-12-01
Full Text Available Information about genetic control of plant reaction to pathogens is essential in plant breeding programs focusing resistance. This study aimed to obtain information about genetic control of the angular leaf spot reaction in leaves and pods from common bean (Phaseolus vulgaris L. line ESAL 686. This line was crossed with cultivars Jalo EEP 558 (resistant, Cornell 49-242 (resistant and Carioca MG (susceptible. Generations F1, F2 and backcrosses (BC11 and BC21 were obtained. In the dry season (2009, parents and respective populations were evaluated for angular leaf spot reaction under field conditions. Disease severity was evaluated on leaves and pods using diagrammatic scales. Severity scores were obtained and mean and variance genetic components were estimated for both. Segregation of F2 generation was analyzed for some crosses. Different genes control angular leaf spot reaction in leaves and pods. Mean and variance components showed predominance of additive effects. Heritability was high, however, was greater on pods than on leaves which indicated that leaf reaction is more influenced by the environment.
ANALISIS PORTOFOLIO RESAMPLED EFFICIENT FRONTIER BERDASARKAN OPTIMASI MEAN-VARIANCE
Abdurakhman, Abdurakhman
2008-01-01
Keputusan alokasi asset yang tepat pada investasi portofolio dapat memaksimalkan keuntungan dan atau meminimalkan risiko. Metode yang sering dipakai dalam optimasi portofolio adalah metode Mean-Variance Markowitz. Dalam prakteknya, metode ini mempunyai kelemahan tidak terlalu stabil. Sedikit perubahan dalam estimasi parameter input menyebabkan perubahan besar pada komposisi portofolio. Untuk itu dikembangkan metode optimasi portofolio yang dapat mengatasi ketidakstabilan metode Mean-Variance ...