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Sample records for additive genetic variances

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

    PubMed Central

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

    2015-01-01

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

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

    ERIC Educational Resources Information Center

    Miller, Geoffrey F.; Penke, Lars

    2007-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2014-09-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  9. Female and male genetic effects on offspring paternity: additive genetic (co)variances in female extra-pair reproduction and male paternity success in song sparrows (Melospiza melodia).

    PubMed

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

    2014-08-01

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

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

    PubMed

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

    2015-11-22

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

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

    PubMed

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

    2015-03-01

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

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

    PubMed Central

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

    2015-01-01

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

  13. Female mate choice predicts paternity success in the absence of additive genetic variance for other female paternity bias mechanisms in Drosophila serrata.

    PubMed

    Collet, J M; Blows, M W

    2014-11-01

    After choosing a first mate, polyandrous females have access to a range of opportunities to bias paternity, such as repeating matings with the preferred male, facilitating fertilization from the best sperm or differentially investing in offspring according to their sire. Female ability to bias paternity after a first mating has been demonstrated in a few species, but unambiguous evidence remains limited by the access to complex behaviours, sperm storage organs and fertilization processes within females. Even when found at the phenotypic level, the potential evolution of any mechanism allowing females to bias paternity other than mate choice remains little explored. Using a large population of pedigreed females, we developed a simple test to determine whether there is additive genetic variation in female ability to bias paternity after a first, chosen, mating. We applied this method in the highly polyandrous Drosophila serrata, giving females the opportunity to successively mate with two males ad libitum. We found that despite high levels of polyandry (females mated more than once per day), the first mate choice was a significant predictor of male total reproductive success. Importantly, there was no detectable genetic variance in female ability to bias paternity beyond mate choice. Therefore, whether or not females can bias paternity before or after copulation, their role on the evolution of sexual male traits is likely to be limited to their first mate choice in D. serrata.

  14. Bottleneck Effects on Genetic Variance for Courtship Repertoire

    PubMed Central

    Meffert, L. M.

    1995-01-01

    Bottleneck effects on evolutionary potential in mating behavior were addressed through assays of additive genetic variances and resulting phenotypic responses to drift in the courtship repertoires of six two-pair founder-flush lines and two control populations of the housefly. A simulation addressed the complication that an estimate of the genetic variance for a courtship trait (e.g., male performance vigor or the female requirement for copulation) must involve assays against the background behavior of the mating partners. The additive ``environmental'' effect of the mating partner's phenotype simply dilutes the net parent-offspring covariance for a trait. However, if there is an interaction with this ``environmental'' component, negative parent-offspring covariances can result under conditions of high incompatibility between the population's distributions for male performance and female choice requirements, despite high levels of genetic variance. All six bottlenecked lines exhibited significant differentiation from the controls in at least one measure of the parent-offspring covariance for male performance or female choice (estimated by 50 parent-son and 50 parent-daughter covariances for 10 courtship traits per line) which translated to significant phenotypic drift. However, the average effect across traits or across lines did not yield a significant net increase in genetic variance due to bottlenecks. Concerted phenotypic differentiation due to the founder-flush event provided indirect evidence of directional dominance in a subset of traits. Furthermore, indirect evidence of genotype-environment interactions (potentially producing genotype-genotype effects) was found in the negative parent-offspring covariances predicted by the male-female interaction simulation and by the association of the magnitude of phenotypic drift with the absolute value of the parent-offspring covariance. Hence, nonadditive genetic effects on mating behavior may be important in

  15. Selection and genetic (co)variance in bighorn sheep.

    PubMed

    Coltman, David W; O'Donoghue, Paul; Hogg, John T; Festa-Bianchet, Marco

    2005-06-01

    Genetic theory predicts that directional selection should deplete additive genetic variance for traits closely related to fitness, and may favor the maintenance of alleles with antagonistically pleiotropic effects on fitness-related traits. Trait heritability is therefore expected to decline with the degree of association with fitness, and some genetic correlations between selected traits are expected to be negative. Here we demonstrate a negative relationship between trait heritability and association with lifetime reproductive success in a wild population of bighorn sheep (Ovis canadensis) at Ram Mountain, Alberta, Canada. Lower heritability for fitness-related traits, however, was not wholly a consequence of declining genetic variance, because those traits showed high levels of residual variance. Genetic correlations estimated between pairs of traits with significant heritability were positive. Principal component analyses suggest that positive relationships between morphometric traits constitute the main axis of genetic variation. Trade-offs in the form of negative genetic or phenotypic correlations among the traits we have measured do not appear to constrain the potential for evolution in this population.

  16. On the Additive and Dominant Variance and Covariance of Individuals Within the Genomic Selection Scope

    PubMed Central

    Vitezica, Zulma G.; Varona, Luis; Legarra, Andres

    2013-01-01

    Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or “breeding” values of individuals are generated by substitution effects, which involve both “biological” additive and dominant effects of the markers. Dominance deviations include only a portion of the biological dominant effects of the markers. Additive variance includes variation due to the additive and dominant effects of the markers. We describe a matrix of dominant genomic relationships across individuals, D, which is similar to the G matrix used in genomic best linear unbiased prediction. This matrix can be used in a mixed-model context for genomic evaluations or to estimate dominant and additive variances in the population. From the “genotypic” value of individuals, an alternative parameterization defines additive and dominance as the parts attributable to the additive and dominant effect of the markers. This approach underestimates the additive genetic variance and overestimates the dominance variance. Transforming the variances from one model into the other is trivial if the distribution of allelic frequencies is known. We illustrate these results with mouse data (four traits, 1884 mice, and 10,946 markers) and simulated data (2100 individuals and 10,000 markers). Variance components were estimated correctly in the model, considering breeding values and dominance deviations. For the model considering genotypic values, the inclusion of dominant effects biased the estimate of additive variance. Genomic models were more accurate for the estimation of variance components than their pedigree-based counterparts. PMID:24121775

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

    PubMed Central

    Huang, Wen; Mackay, Trudy F. C.

    2016-01-01

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

  18. Comparing estimates of genetic variance across different relationship models.

    PubMed

    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".

  19. Genetic Variance for Body Size in a Natural Population of Drosophila Buzzatii

    PubMed Central

    Ruiz, A.; Santos, M.; Barbadilla, A.; Quezada-Diaz, J. E.; Hasson, E.; Fontdevila, A.

    1991-01-01

    Previous work has shown thorax length to be under directional selection in the Drosophila buzzatii population of Carboneras. In order to predict the genetic consequences of natural selection, genetic variation for this trait was investigated in two ways. First, narrow sense heritability was estimated in the laboratory F(2) generation of a sample of wild flies by means of the offspring-parent regression. A relatively high value, 0.59, was obtained. Because the phenotypic variance of wild flies was 7-9 times that of the flies raised in the laboratory, ``natural'' heritability may be estimated as one-seventh to one-ninth that value. Second, the contribution of the second and fourth chromosomes, which are polymorphic for paracentric inversions, to the genetic variance of thorax length was estimated in the field and in the laboratory. This was done with the assistance of a simple genetic model which shows that the variance among chromosome arrangements and the variance among karyotypes provide minimum estimates of the chromosome's contribution to the additive and genetic variances of the triat, respectively. In males raised under optimal conditions in the laboratory, the variance among second-chromosome karyotypes accounted for 11.43% of the total phenotypic variance and most of this variance was additive; by contrast, the contribution of the fourth chromosome was nonsignificant. The variance among second-chromosome karyotypes accounted for 1.56-1.78% of the total phenotypic variance in wild males and was nonsignificant in wild females. The variance among fourth chromosome karyotypes accounted for 0.14-3.48% of the total phenotypic variance in wild flies. At both chromosomes, the proportion of additive variance was higher in mating flies than in nonmating flies. PMID:1916242

  20. Argentine Population Genetic Structure: Large Variance in Amerindian Contribution

    PubMed Central

    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

  1. Analysis of Variance Components for Genetic Markers with Unphased Genotypes.

    PubMed

    Wang, Tao

    2016-01-01

    An ANOVA type general multi-allele (GMA) model was proposed in Wang (2014) on analysis of variance components for quantitative trait loci or genetic markers with phased or unphased genotypes. In this study, by applying the GMA model, we further examine estimation of the genetic variance components for genetic markers with unphased genotypes based on a random sample from a study population. In one locus and two loci cases, we first derive the least square estimates (LSE) of model parameters in fitting the GMA model. Then we construct estimators of the genetic variance components for one marker locus in a Hardy-Weinberg disequilibrium population and two marker loci in an equilibrium population. Meanwhile, we explore the difference between the classical general linear model (GLM) and GMA based approaches in association analysis of genetic markers with quantitative traits. We show that the GMA model can retain the same partition on the genetic variance components as the traditional Fisher's ANOVA model, while the GLM cannot. We clarify that the standard F-statistics based on the partial reductions in sums of squares from GLM for testing the fixed allelic effects could be inadequate for testing the existence of the variance component when allelic interactions are present. We point out that the GMA model can reduce the confounding between the allelic effects and allelic interactions at least for independent alleles. As a result, the GMA model could be more beneficial than GLM for detecting allelic interactions.

  2. Genetic Variance in the SES-IQ Correlation.

    ERIC Educational Resources Information Center

    Eckland, Bruce K.

    1979-01-01

    Discusses questions dealing with genetic aspects of the correlation between IQ and socioeconomic status (SES). Questions include: How does assortative mating affect the genetic variance of IQ? Is the relationship between an individual's IQ and adult SES a causal one? And how can IQ research improve schools and schooling? (Author/DB)

  3. Age-dependent genetic variance in a life-history trait in the mute swan.

    PubMed

    Charmantier, Anne; Perrins, Christopher; McCleery, Robin H; Sheldon, Ben C

    2006-01-22

    Genetic variance in characters under natural selection in natural populations determines the way those populations respond to that selection. Whether populations show temporal and/or spatial constancy in patterns of genetic variance and covariance is regularly considered, as this will determine whether selection responses are constant over space and time. Much less often considered is whether characters show differing amounts of genetic variance over the life-history of individuals. Such age-specific variation, if present, has important potential consequences for the force of natural selection and for understanding the causes of variation in quantitative characters. Using data from a long-term study of the mute swan Cygnus olor, we report the partitioning of phenotypic variance in timing of breeding (subject to strong natural selection) into component parts over 12 different age classes. We show that the additive genetic variance and heritability of this trait are strongly age-dependent, with higher additive genetic variance present in young and, particularly, old birds, but little evidence of any genetic variance for birds of intermediate ages. These results demonstrate that age can have a very important influence on the components of variation of characters in natural populations, and consequently that separate age classes cannot be assumed to be equivalent, either with respect to their evolutionary potential or response.

  4. Genetic and environmental heterogeneity of residual variance of weight traits in Nellore beef cattle

    PubMed Central

    2012-01-01

    Background Many studies have provided evidence of the existence of genetic heterogeneity of environmental variance, suggesting that it could be exploited to improve robustness and uniformity of livestock by selection. However, little is known about the perspectives of such a selection strategy in beef cattle. Methods A two-step approach was applied to study the genetic heterogeneity of residual variance of weight gain from birth to weaning and long-yearling weight in a Nellore beef cattle population. First, an animal model was fitted to the data and second, the influence of additive and environmental effects on the residual variance of these traits was investigated with different models, in which the log squared estimated residuals for each phenotypic record were analyzed using the restricted maximum likelihood method. Monte Carlo simulation was performed to assess the reliability of variance component estimates from the second step and the accuracy of estimated breeding values for residual variation. Results The results suggest that both genetic and environmental factors have an effect on the residual variance of weight gain from birth to weaning and long-yearling in Nellore beef cattle and that uniformity of these traits could be improved by selecting for lower residual variance, when considering a large amount of information to predict genetic merit for this criterion. Simulations suggested that using the two-step approach would lead to biased estimates of variance components, such that more adequate methods are needed to study the genetic heterogeneity of residual variance in beef cattle. PMID:22672564

  5. Maintenance of Quantitative Genetic Variance Under Partial Self-Fertilization, with Implications for Evolution of Selfing

    PubMed Central

    Lande, Russell; Porcher, Emmanuelle

    2015-01-01

    We analyze two models of the maintenance of quantitative genetic variance in a mixed-mating system of self-fertilization and outcrossing. In both models purely additive genetic variance is maintained by mutation and recombination under stabilizing selection on the phenotype of one or more quantitative characters. The Gaussian allele model (GAM) involves a finite number of unlinked loci in an infinitely large population, with a normal distribution of allelic effects at each locus within lineages selfed for τ consecutive generations since their last outcross. The infinitesimal model for partial selfing (IMS) involves an infinite number of loci in a large but finite population, with a normal distribution of breeding values in lineages of selfing age τ. In both models a stable equilibrium genetic variance exists, the outcrossed equilibrium, nearly equal to that under random mating, for all selfing rates, r, up to critical value, r^, the purging threshold, which approximately equals the mean fitness under random mating relative to that under complete selfing. In the GAM a second stable equilibrium, the purged equilibrium, exists for any positive selfing rate, with genetic variance less than or equal to that under pure selfing; as r increases above r^ the outcrossed equilibrium collapses sharply to the purged equilibrium genetic variance. In the IMS a single stable equilibrium genetic variance exists at each selfing rate; as r increases above r^ the equilibrium genetic variance drops sharply and then declines gradually to that maintained under complete selfing. The implications for evolution of selfing rates, and for adaptive evolution and persistence of predominantly selfing species, provide a theoretical basis for the classical view of Stebbins that predominant selfing constitutes an “evolutionary dead end.” PMID:25969460

  6. Maintenance of Quantitative Genetic Variance Under Partial Self-Fertilization, with Implications for Evolution of Selfing.

    PubMed

    Lande, Russell; Porcher, Emmanuelle

    2015-07-01

    We analyze two models of the maintenance of quantitative genetic variance in a mixed-mating system of self-fertilization and outcrossing. In both models purely additive genetic variance is maintained by mutation and recombination under stabilizing selection on the phenotype of one or more quantitative characters. The Gaussian allele model (GAM) involves a finite number of unlinked loci in an infinitely large population, with a normal distribution of allelic effects at each locus within lineages selfed for τ consecutive generations since their last outcross. The infinitesimal model for partial selfing (IMS) involves an infinite number of loci in a large but finite population, with a normal distribution of breeding values in lineages of selfing age τ. In both models a stable equilibrium genetic variance exists, the outcrossed equilibrium, nearly equal to that under random mating, for all selfing rates, r, up to critical value, [Formula: see text], the purging threshold, which approximately equals the mean fitness under random mating relative to that under complete selfing. In the GAM a second stable equilibrium, the purged equilibrium, exists for any positive selfing rate, with genetic variance less than or equal to that under pure selfing; as r increases above [Formula: see text] the outcrossed equilibrium collapses sharply to the purged equilibrium genetic variance. In the IMS a single stable equilibrium genetic variance exists at each selfing rate; as r increases above [Formula: see text] the equilibrium genetic variance drops sharply and then declines gradually to that maintained under complete selfing. The implications for evolution of selfing rates, and for adaptive evolution and persistence of predominantly selfing species, provide a theoretical basis for the classical view of Stebbins that predominant selfing constitutes an "evolutionary dead end."

  7. Estimates of genetic variance and variance of predicted genetic merits using pedigree or genomic relationship matrices in six Brown Swiss cattle populations for different traits.

    PubMed

    Loberg, A; Dürr, J W; Fikse, W F; Jorjani, H; Crooks, L

    2015-10-01

    The amount of variance captured in genetic estimations may depend on whether a pedigree-based or genomic relationship matrix is used. The purpose of this study was to investigate the genetic variance as well as the variance of predicted genetic merits (PGM) using pedigree-based or genomic relationship matrices in Brown Swiss cattle. We examined a range of traits in six populations amounting to 173 population-trait combinations. A main aim was to determine how using different relationship matrices affect variance estimation. We calculated ratios between different types of estimates and analysed the impact of trait heritability and population size. The genetic variances estimated by REML using a genomic relationship matrix were always smaller than the variances that were similarly estimated using a pedigree-based relationship matrix. The variances from the genomic relationship matrix became closer to estimates from a pedigree relationship matrix as heritability and population size increased. In contrast, variances of predicted genetic merits obtained using a genomic relationship matrix were mostly larger than variances of genetic merit predicted using pedigree-based relationship matrix. The ratio of the genomic to pedigree-based PGM variances decreased as heritability and population size rose. The increased variance among predicted genetic merits is important for animal breeding because this is one of the factors influencing genetic progress.

  8. Ontogenetic changes in genetic variances of age-dependent plasticity along a latitudinal gradient

    PubMed Central

    Nilsson-Örtman, V; Rogell, B; Stoks, R; Johansson, F

    2015-01-01

    The expression of phenotypic plasticity may differ among life stages of the same organism. Age-dependent plasticity can be important for adaptation to heterogeneous environments, but this has only recently been recognized. Whether age-dependent plasticity is a common outcome of local adaptation and whether populations harbor genetic variation in this respect remains largely unknown. To answer these questions, we estimated levels of additive genetic variation in age-dependent plasticity in six species of damselflies sampled from 18 populations along a latitudinal gradient spanning 3600 km. We reared full sib larvae at three temperatures and estimated genetic variances in the height and slope of thermal reaction norms of body size at three points in time during ontogeny using random regression. Our data show that most populations harbor genetic variation in growth rate (reaction norm height) in all ontogenetic stages, but only some populations and ontogenetic stages were found to harbor genetic variation in thermal plasticity (reaction norm slope). Genetic variances in reaction norm height differed among species, while genetic variances in reaction norm slope differed among populations. The slope of the ontogenetic trend in genetic variances of both reaction norm height and slope increased with latitude. We propose that differences in genetic variances reflect temporal and spatial variation in the strength and direction of natural selection on growth trajectories and age-dependent plasticity. Selection on age-dependent plasticity may depend on the interaction between temperature seasonality and time constraints associated with variation in life history traits such as generation length. PMID:25649500

  9. Genetic interactions affecting human gene expression identified by variance association mapping

    PubMed Central

    Brown, Andrew Anand; Buil, Alfonso; Viñuela, Ana; Lappalainen, Tuuli; Zheng, Hou-Feng; Richards, J Brent; Small, Kerrin S; Spector, Timothy D; Dermitzakis, Emmanouil T; Durbin, Richard

    2014-01-01

    Non-additive interaction between genetic variants, or epistasis, is a possible explanation for the gap between heritability of complex traits and the variation explained by identified genetic loci. Interactions give rise to genotype dependent variance, and therefore the identification of variance quantitative trait loci can be an intermediate step to discover both epistasis and gene by environment effects (GxE). Using RNA-sequence data from lymphoblastoid cell lines (LCLs) from the TwinsUK cohort, we identify a candidate set of 508 variance associated SNPs. Exploiting the twin design we show that GxE plays a role in ∼70% of these associations. Further investigation of these loci reveals 57 epistatic interactions that replicated in a smaller dataset, explaining on average 4.3% of phenotypic variance. In 24 cases, more variance is explained by the interaction than their additive contributions. Using molecular phenotypes in this way may provide a route to uncovering genetic interactions underlying more complex traits. DOI: http://dx.doi.org/10.7554/eLife.01381.001 PMID:24771767

  10. Quantitative Genetic Analysis of Temperature Regulation in MUS MUSCULUS. I. Partitioning of Variance

    PubMed Central

    Lacy, Robert C.; Lynch, Carol Becker

    1979-01-01

    Heritabilities (from parent-offspring regression) and intraclass correlations of full sibs for a variety of traits were estimated from 225 litters of a heterogeneous stock (HS/Ibg) of laboratory mice. Initial variance partitioning suggested different adaptive functions for physiological, morphological and behavioral adjustments with respect to their thermoregulatory significance. Metabolic heat-production mechanisms appear to have reached their genetic limits, with little additive genetic variance remaining. This study provided no genetic evidence that body size has a close directional association with fitness in cold environments, since heritability estimates for weight gain and adult weight were similar and high, whether or not the animals were exposed to cold. Behavioral heat conservation mechanisms also displayed considerable amounts of genetic variability. However, due to strong evidence from numerous other studies that behavior serves an important adaptive role for temperature regulation in small mammals, we suggest that fluctuating selection pressures may have acted to maintain heritable variation in these traits. PMID:17248909

  11. Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models

    PubMed Central

    He, Liang; Sillanpää, Mikko J.; Silventoinen, Karri; Kaprio, Jaakko; Pitkäniemi, Janne

    2016-01-01

    Twin studies have been adopted for decades to disentangle the relative genetic and environmental contributions for a wide range of traits. However, heritability estimation based on the classical twin models does not take into account dynamic behavior of the variance components over age. Varying variance of the genetic component over age can imply the existence of gene–environment (G × E) interactions that general genome-wide association studies (GWAS) fail to capture, which may lead to the inconsistency of heritability estimates between twin design and GWAS. Existing parametric G × E interaction models for twin studies are limited by assuming a linear or quadratic form of the variance curves with respect to a moderator that can, however, be overly restricted in reality. Here we propose spline-based approaches to explore the variance curves of the genetic and environmental components. We choose the additive genetic, common, and unique environmental variance components (ACE) model as the starting point. We treat the component variances as variance functions with respect to age modeled by B-splines or P-splines. We develop an empirical Bayes method to estimate the variance curves together with their confidence bands and provide an R package for public use. Our simulations demonstrate that the proposed methods accurately capture dynamic behavior of the component variances in terms of mean square errors with a data set of >10,000 twin pairs. Using the proposed methods as an alternative and major extension to the classical twin models, our analyses with a large-scale Finnish twin data set (19,510 MZ twins and 27,312 DZ same-sex twins) discover that the variances of the A, C, and E components for body mass index (BMI) change substantially across life span in different patterns and the heritability of BMI drops to ∼50% after middle age. The results further indicate that the decline of heritability is due to increasing unique environmental variance, which provides

  12. Quantitative genetic divergence and standing genetic (co)variance in thermal reaction norms along latitude.

    PubMed

    Berger, David; Postma, Erik; Blanckenhorn, Wolf U; Walters, Richard J

    2013-08-01

    Although the potential to adapt to warmer climate is constrained by genetic trade-offs, our understanding of how selection and mutation shape genetic (co)variances in thermal reaction norms is poor. Using 71 isofemale lines of the fly Sepsis punctum, originating from northern, central, and southern European climates, we tested for divergence in juvenile development rate across latitude at five experimental temperatures. To investigate effects of evolutionary history in different climates on standing genetic variation in reaction norms, we further compared genetic (co)variances between regions. Flies were reared on either high or low food resources to explore the role of energy acquisition in determining genetic trade-offs between different temperatures. Although the latter had only weak effects on the strength and sign of genetic correlations, genetic architecture differed significantly between climatic regions, implying that evolution of reaction norms proceeds via different trajectories at high latitude versus low latitude in this system. Accordingly, regional genetic architecture was correlated to region-specific differentiation. Moreover, hot development temperatures were associated with low genetic variance and stronger genetic correlations compared to cooler temperatures. We discuss the evolutionary potential of thermal reaction norms in light of their underlying genetic architectures, evolutionary histories, and the materialization of trade-offs in natural environments.

  13. Age-specific patterns of genetic variance in Drosophila melanogaster. I. Mortality

    SciTech Connect

    Promislow, D.E.L.; Tatar, M.; Curtsinger, J.W.

    1996-06-01

    Peter Medawar proposed that senescence arises from an age-related decline in the force of selection, which allows late-acting deleterious mutations to accumulate. Subsequent workers have suggested that mutation accumulation could produce an age-related increase in additive genetic variance (V{sub A}) for fitness traits, as recently found in Drosophila melanogaster. Here we report results from a genetic analysis of mortality in 65,134 D. melanogaster. Additive genetic variance for female mortality rates increases from 0.007 in the first week of life to 0.325 by the third week, and then declines to 0.002 by the seventh week. Males show a similar pattern, though total variance is lower than in females. In contrast to a predicted divergence in mortality curves, mortality curves of different genotypes are roughly parallel. Using a three-parameter model, we find significant V{sub A} for the slope and constant term of the curve describing age-specific mortality rates, and also for the rate at which mortality decelerates late in life. These results fail to support a prediction derived from Medawar`s {open_quotes}mutation accumulation{close_quotes} theory for the evolution of senescence. However, our results could be consistent with alternative interpretations of evolutionary models of aging. 65 refs., 2 figs., 2 tabs.

  14. Assessment of the genetic variance of late-onset Alzheimer's disease.

    PubMed

    Ridge, Perry G; Hoyt, Kaitlyn B; Boehme, Kevin; Mukherjee, Shubhabrata; Crane, Paul K; Haines, Jonathan L; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Schellenberg, Gerard D; Kauwe, John S K

    2016-05-01

    Alzheimer's disease (AD) is a complex genetic disorder with no effective treatments. More than 20 common markers have been identified, which are associated with AD. Recently, several rare variants have been identified in Amyloid Precursor Protein (APP), Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) and Unc-5 Netrin Receptor C (UNC5C) that affect risk for AD. Despite the many successes, the genetic architecture of AD remains unsolved. We used Genome-wide Complex Trait Analysis to (1) estimate phenotypic variance explained by genetics; (2) calculate genetic variance explained by known AD single nucleotide polymorphisms (SNPs); and (3) identify the genomic locations of variation that explain the remaining unexplained genetic variance. In total, 53.24% of phenotypic variance is explained by genetics, but known AD SNPs only explain 30.62% of the genetic variance. Of the unexplained genetic variance, approximately 41% is explained by unknown SNPs in regions adjacent to known AD SNPs, and the remaining unexplained genetic variance outside these regions.

  15. fullfact: an R package for the analysis of genetic and maternal variance components from full factorial mating designs.

    PubMed

    Houde, Aimee Lee S; Pitcher, Trevor E

    2016-03-01

    Full factorial breeding designs are useful for quantifying the amount of additive genetic, nonadditive genetic, and maternal variance that explain phenotypic traits. Such variance estimates are important for examining evolutionary potential. Traditionally, full factorial mating designs have been analyzed using a two-way analysis of variance, which may produce negative variance values and is not suited for unbalanced designs. Mixed-effects models do not produce negative variance values and are suited for unbalanced designs. However, extracting the variance components, calculating significance values, and estimating confidence intervals and/or power values for the components are not straightforward using traditional analytic methods. We introduce fullfact - an R package that addresses these issues and facilitates the analysis of full factorial mating designs with mixed-effects models. Here, we summarize the functions of the fullfact package. The observed data functions extract the variance explained by random and fixed effects and provide their significance. We then calculate the additive genetic, nonadditive genetic, and maternal variance components explaining the phenotype. In particular, we integrate nonnormal error structures for estimating these components for nonnormal data types. The resampled data functions are used to produce bootstrap-t confidence intervals, which can then be plotted using a simple function. We explore the fullfact package through a worked example. This package will facilitate the analyses of full factorial mating designs in R, especially for the analysis of binary, proportion, and/or count data types and for the ability to incorporate additional random and fixed effects and power analyses.

  16. Effect of captivity on genetic variance for five traits in the large milkweed bug (Oncopeltus fasciatus).

    PubMed

    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.

  17. Age at menarche as a fitness trait: nonadditive genetic variance detected in a large twin sample.

    PubMed Central

    Treloar, S A; Martin, N G

    1990-01-01

    The etiological role of genotype and environment in recalled age at menarche was examined using an unselected sample of 1,177 MZ and 711 DZ twin pairs aged 18 years and older. The correlation for onset of menarche between MZ twins was .65 +/- .03, and that for DZ pairs was .18 +/- .04, although these differed somewhat between four birth cohorts. Environmental factors were more important in the older cohorts (perhaps because of less reliable recall). Total genotypic variance (additive plus nonadditive) ranged from 61% in the oldest cohort to 68% in the youngest cohort. In the oldest birth cohort (born before 1939), there was evidence of greater influence of environmental factors on age at menarche in the second-born twin, although there was no other evidence in the data that birth trauma affected timing. The greater part of the genetic variance was nonadditive (dominance or epistasis), and this is typical of a fitness trait. It appears that genetic nonadditivity is in the decreasing direction, and this is consistent with selection for early menarche during human evolution. Breakdown of inbreeding depression as a possible explanation for the secular decline in age at menarche is discussed. PMID:2349942

  18. Comparison of particle swarm optimization and simulated annealing for locating additional boreholes considering combined variance minimization

    NASA Astrophysics Data System (ADS)

    Soltani-Mohammadi, Saeed; Safa, Mohammad; Mokhtari, Hadi

    2016-10-01

    One of the most important stages in complementary exploration is optimal designing the additional drilling pattern or defining the optimum number and location of additional boreholes. Quite a lot research has been carried out in this regard in which for most of the proposed algorithms, kriging variance minimization as a criterion for uncertainty assessment is defined as objective function and the problem could be solved through optimization methods. Although kriging variance implementation is known to have many advantages in objective function definition, it is not sensitive to local variability. As a result, the only factors evaluated for locating the additional boreholes are initial data configuration and variogram model parameters and the effects of local variability are omitted. In this paper, with the goal of considering the local variability in boundaries uncertainty assessment, the application of combined variance is investigated to define the objective function. Thus in order to verify the applicability of the proposed objective function, it is used to locate the additional boreholes in Esfordi phosphate mine through the implementation of metaheuristic optimization methods such as simulated annealing and particle swarm optimization. Comparison of results from the proposed objective function and conventional methods indicates that the new changes imposed on the objective function has caused the algorithm output to be sensitive to the variations of grade, domain's boundaries and the thickness of mineralization domain. The comparison between the results of different optimization algorithms proved that for the presented case the application of particle swarm optimization is more appropriate than simulated annealing.

  19. A new explained-variance based genetic risk score for predictive modeling of disease risk.

    PubMed

    Che, Ronglin; Motsinger-Reif, Alison A

    2012-09-25

    The goal of association mapping is to identify genetic variants that predict disease, and as the field of human genetics matures, the number of successful association studies is increasing. Many such studies have shown that for many diseases, risk is explained by a reasonably large number of variants that each explains a very small amount of disease risk. This is prompting the use of genetic risk scores in building predictive models, where information across several variants is combined for predictive modeling. In the current study, we compare the performance of four previously proposed genetic risk score methods and present a new method for constructing genetic risk score that incorporates explained variance information. The methods compared include: a simple count Genetic Risk Score, an odds ratio weighted Genetic Risk Score, a direct logistic regression Genetic Risk Score, a polygenic Genetic Risk Score, and the new explained variance weighted Genetic Risk Score. We compare the methods using a wide range of simulations in two steps, with a range of the number of deleterious single nucleotide polymorphisms (SNPs) explaining disease risk, genetic modes, baseline penetrances, sample sizes, relative risks (RR) and minor allele frequencies (MAF). Several measures of model performance were compared including overall power, C-statistic and Akaike's Information Criterion. Our results show the relative performance of methods differs significantly, with the new explained variance weighted GRS (EV-GRS) generally performing favorably to the other methods.

  20. Analysis of Quantitative Traits in Two Long-Term Randomly Mated Soybean Populations I. Genetic Variances

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The genetic effects of long term random mating and natural selection aided by genetic male sterility were evaluated in two soybean [Glycine max (L.) Merr.] populations: RSII and RSIII. Population means, variances, and heritabilities were estimated to determine the effects of 26 generations of random...

  1. The ARMC5 gene shows extensive genetic variance in primary macronodular adrenocortical hyperplasia

    PubMed Central

    Correa, Ricardo; Zilbermint, Mihail; Berthon, Annabel; Espiard, Stephanie; Batsis, Maria; Papadakis, Georgios Z.; Xekouki, Paraskevi; Lodish, Maya B.; Bertherat, Jerome; Faucz, Fabio R.; Stratakis, Constantine A.

    2015-01-01

    Objective Primary macronodular adrenal hyperplasia (PMAH) is a rare type of Cushing’s syndrome (CS) that results in increased cortisol production and bilateral enlargement of the adrenal glands. Recent work showed that the disease may be caused by germline and somatic mutations in the ARMC5 gene, a likely tumor-suppressor gene (TSG). We investigated 20 different adrenal nodules from one patient with PMAH for ARMC5 somatic sequence changes. Design All of the nodules where obtained from a single patient who underwent bilateral adrenalectomy. DNA was extracted by standard protocols and the ARMC5 sequence was determined by the Sanger method. Results Sixteen of 20 adrenocortical nodules harbored, in addition to what appeared to be the germline mutation, a second somatic variant. The p.Trp476* sequence change was present in all 20 nodules, as well as in normal tissue from the adrenal capsule, identifying it as the germline defect; each of the 16 other variants were found in different nodules: 6 were frame shift, 4 were missense, 3 were nonsense, and 1 was a splice site variation. Allelic losses were confirmed in 2 of the nodules. Conclusion This is the most genetic variance of the ARMC5 gene ever described in a single patient with PMAH: each of 16 adrenocortical nodules had a second new, “private”, and -in most cases- completely inactivating ARMC5 defect, in addition to the germline mutation. The data support the notion that ARMC5 is a TSG that needs a second, somatic hit, to mediate tumorigenesis leading to polyclonal nodularity; however, the driver of this extensive genetic variance of the second ARMC5 allele in adrenocortical tissue in the context of a germline defect and PMAH remains a mystery. PMID:26162405

  2. Explaining additional genetic variation in complex traits

    PubMed Central

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

    2015-01-01

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

  3. Quantitative genetic variance and multivariate clines in the Ivyleaf morning glory, Ipomoea hederacea

    PubMed Central

    Stock, Amanda J.; Campitelli, Brandon E.; Stinchcombe, John R.

    2014-01-01

    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. PMID:25002704

  4. Quantitative genetic variance and multivariate clines in the Ivyleaf morning glory, Ipomoea hederacea.

    PubMed

    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.

  5. Age-specific patterns of genetic variance in Drosophila melanogaster. II. Fecundity and its genetic covariance with age-specific mortality

    SciTech Connect

    Tatar, M.; Promislow, D.E.L.; Khazaeli, A.A.; Curtsinger, J.W.

    1996-06-01

    Under the mutation accumulation model of senescence, it was predicted that the additive genetic variance (V{sub A}) for fitness traits will increase with age. We measured age-specific mortality and fecundity from 65,134 Drosophila melanogaster and estimated genetic variance components, based on reciprocal crosses of extracted second chromosome lines. Elsewhere we report the results for mortality. Here, for fecundity, we report a biomodal pattern for V{sub A} with peaks at 3 days and at 17-31 days. Under the antagonistic pleiotropy model of senescence, it was predicted that negative correlations will exist between early and late life history traits. For fecundity itself we find positive genetic correlations among age classes >3 days but negative nonsignificant correlations between fecundity at 3 days and at older age classes. For fecundity vs. age-specific mortality, we find positive fitness correlations (negative genetic correlations) among the traits at all ages >3 days but a negative fitness correlation between fecundity at 3 days and mortality at the oldest ages (positive genetic correlations). For age-specific mortality itself we find overwhelmingly positive genetic correlations among all age classes. The data suggest that mutation accumulation may be a major source of standing genetic variance for senescence. 75 refs., 4 figs., 1 tab.

  6. Good Genes and Sexual Selection in Dung Beetles (Onthophagus taurus): Genetic Variance in Egg-to-Adult and Adult Viability

    PubMed Central

    Garcia-Gonzalez, Francisco; Simmons, Leigh W.

    2011-01-01

    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. PMID:21267411

  7. Ontogeny of additive and maternal genetic effects: lessons from domestic mammals.

    PubMed

    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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We proposed a method to estimate the error variance among non-replicated genotypes, thus to estimate the genetic parameters by using replicated controls. We derived formulas to estimate sampling variances of the genetic parameters. Computer simulation indicated that the proposed methods of estimatin...

  9. Editing genomic DNA in cancer cells with high genetic variance: benefit or risk?

    PubMed

    Wang, Lin; Wang, Yixiang; Guo, Chuanbin

    2014-05-01

    The generation of stably-transfected cell lines is a common and very important technology in cancer science. Considerable knowledge in the field of life sciences has been gained through the modification of the genetic code. However, there is a risk in evaluating exogenous gene function through editing genomic DNA in a cancer cell with high genetic variance. In the present study, we showed that genomic DNA status should be considered when evaluating the exogenous gene function in a cancer cell line with high variant genome through stable transfection technology, immunostaining, wound healing assay, transwell invasion assay, real-time PCR, western blot and karyotyping analysis. Our results showed that the S100P expression level was not related to the migration and invasion abilities in these stably transfected cell lines derived from a human salivary adenoid cystic carcinoma cell line SACC-83. The MMP expression pattern was detected by western blot analysis which matched the biological behaviors in these cells. The genomic analysis showed that SACC-83 presented hypotetraploid karyotyping with high variance. Our data indicated that establishment of stable transgenic cancer cell lines should consider the status of genetic variance in a cancer cell to avoid any biased conclusion.

  10. Colour ornamentation in the blue tit: quantitative genetic (co)variances across sexes.

    PubMed

    Charmantier, A; Wolak, M E; Grégoire, A; Fargevieille, A; Doutrelant, C

    2017-02-01

    Although secondary sexual traits are commonly more developed in males than females, in many animal species females also display elaborate ornaments or weaponry. Indirect selection on correlated traits in males and/or direct sexual or social selection in females are hypothesized to drive the evolution and maintenance of female ornaments. Yet, the relative roles of these evolutionary processes remain unidentified, because little is known about the genetic correlation that might exist between the ornaments of both sexes, and few estimates of sex-specific autosomal or sex-linked genetic variances are available. In this study, we used two wild blue tit populations with 9 years of measurements on two colour ornaments: one structurally based (blue crown) and one carotenoid based (yellow chest). We found significant autosomal heritability for the chromatic part of the structurally based colouration in both sexes, whereas carotenoid chroma was heritable only in males, and the achromatic part of both colour patches was mostly non heritable. Power limitations, which are probably common among most data sets collected so far in wild populations, prevented estimation of sex-linked genetic variance. Bivariate analyses revealed very strong cross-sex genetic correlations in all heritable traits, although the strength of these correlations was not related to the level of sexual dimorphism. In total, our results suggest that males and females share a majority of their genetic variation underlying colour ornamentation, and hence the evolution of these sex-specific traits may depend greatly on correlated responses to selection in the opposite sex.

  11. Stability of genetic variance and covariance for reproductive characters in the face of climate change in a wild bird population.

    PubMed

    Garant, Dany; Hadfield, Jarrod D; Kruuk, Loeske E B; Sheldon, Ben C

    2008-01-01

    Global warming has had numerous effects on populations of animals and plants, with many species in temperate regions experiencing environmental change at unprecedented rates. Populations with low potential for adaptive evolutionary change and plasticity will have little chance of persistence in the face of environmental change. Assessment of the potential for adaptive evolution requires the estimation of quantitative genetic parameters, but it is as yet unclear what impact, if any, global warming will have on the expression of genetic variances and covariances. Here we assess the impact of a changing climate on the genetic architecture underlying three reproductive traits in a wild bird population. We use a large, long-term, data set collected on great tits (Parus major) in Wytham Woods, Oxford, and an 'animal model' approach to quantify the heritability of, and genetic correlations among, laying date, clutch size and egg mass during two periods with contrasting temperature conditions over a 40-year period (1965-1988 [cooler] vs. 1989-2004 [warmer]). We found significant additive genetic variance and heritability for all traits under both temperature regimes. We also found significant negative genetic covariances and correlations between clutch size and egg weight during both periods, and among laying date and clutch size in the colder years only. The overall G matrix comparison among periods, however, showed only a minor difference among periods, thus suggesting that genotype by environment interactions are negligible in this context. Our results therefore suggest that despite substantial changes in temperature and in mean laying date phenotype over the last decades, and despite the large sample sizes available, we are unable to detect any significant change in the genetic architecture of the reproductive traits studied.

  12. Sex-specific genetic variance and the evolution of sexual dimorphism: a systematic review of cross-sex genetic correlations.

    PubMed

    Poissant, Jocelyn; Wilson, Alastair J; Coltman, David W

    2010-01-01

    The independent evolution of the sexes may often be constrained if male and female homologous traits share a similar genetic architecture. Thus, cross-sex genetic covariance is assumed to play a key role in the evolution of sexual dimorphism (SD) with consequent impacts on sexual selection, population dynamics, and speciation processes. We compiled cross-sex genetic correlations (r(MF)) estimates from 114 sources to assess the extent to which the evolution of SD is typically constrained and test several specific hypotheses. First, we tested if r(MF) differed among trait types and especially between fitness components and other traits. We also tested the theoretical prediction of a negative relationship between r(MF) and SD based on the expectation that increases in SD should be facilitated by sex-specific genetic variance. We show that r(MF) is usually large and positive but that it is typically smaller for fitness components. This demonstrates that the evolution of SD is typically genetically constrained and that sex-specific selection coefficients may often be opposite in sign due to sub-optimal levels of SD. Most importantly, we confirm that sex-specific genetic variance is an important contributor to the evolution of SD by validating the prediction of a negative correlation between r(MF) and SD.

  13. The apportionment of total genetic variation by categorical analysis of variance.

    PubMed

    Khang, Tsung Fei; Yap, Von Bing

    2010-01-01

    We wish to suggest the categorical analysis of variance as a means of quantifying the proportion of total genetic variation attributed to different sources of variation. This method potentially challenges researchers to rethink conclusions derived from a well-known method known as the analysis of molecular variance (AMOVA). The CATANOVA framework allows explicit definition, and estimation, of two measures of genetic differentiation. These parameters form the subject of interest in many research programmes, but are often confused with the correlation measures defined in AMOVA, which cannot be interpreted as relative contributions of particular sources of variation. Through a simulation approach, we show that under certain conditions, researchers who use AMOVA to estimate these measures of genetic differentiation may attribute more than justified amounts of total variation to population labels. Moreover, the two measures can also lead to incongruent conclusions regarding the genetic structure of the populations of interest. Fortunately, one of the two measures seems robust to variations in relative sample sizes used. Its merits are illustrated in this paper using mitochondrial haplotype and amplified fragment length polymorphism (AFLP) data.

  14. Genetically Determined Variation in Lysis Time Variance in the Bacteriophage φX174

    PubMed Central

    Baker, Christopher W.; Miller, Craig R.; Thaweethai, Tanayott; Yuan, Jeffrey; Baker, Meghan Hollibaugh; Joyce, Paul; Weinreich, Daniel M.

    2016-01-01

    Researchers in evolutionary genetics recently have recognized an exciting opportunity in decomposing beneficial mutations into their proximal, mechanistic determinants. The application of methods and concepts from molecular biology and life history theory to studies of lytic bacteriophages (phages) has allowed them to understand how natural selection sees mutations influencing life history. This work motivated the research presented here, in which we explored whether, under consistent experimental conditions, small differences in the genome of bacteriophage φX174 could lead to altered life history phenotypes among a panel of eight genetically distinct clones. We assessed the clones’ phenotypes by applying a novel statistical framework to the results of a serially sampled parallel infection assay, in which we simultaneously inoculated each of a large number of replicate host volumes with ∼1 phage particle. We sequentially plated the volumes over the course of infection and counted the plaques that formed after incubation. These counts served as a proxy for the number of phage particles in a single volume as a function of time. From repeated assays, we inferred significant, genetically determined heterogeneity in lysis time and burst size, including lysis time variance. These findings are interesting in light of the genetic and phenotypic constraints on the single-protein lysis mechanism of φX174. We speculate briefly on the mechanisms underlying our results, and we discuss the potential importance of lysis time variance in viral evolution. PMID:26921293

  15. Genetically Determined Variation in Lysis Time Variance in the Bacteriophage φX174.

    PubMed

    Baker, Christopher W; Miller, Craig R; Thaweethai, Tanayott; Yuan, Jeffrey; Baker, Meghan Hollibaugh; Joyce, Paul; Weinreich, Daniel M

    2016-04-07

    Researchers in evolutionary genetics recently have recognized an exciting opportunity in decomposing beneficial mutations into their proximal, mechanistic determinants. The application of methods and concepts from molecular biology and life history theory to studies of lytic bacteriophages (phages) has allowed them to understand how natural selection sees mutations influencing life history. This work motivated the research presented here, in which we explored whether, under consistent experimental conditions, small differences in the genome of bacteriophage φX174 could lead to altered life history phenotypes among a panel of eight genetically distinct clones. We assessed the clones' phenotypes by applying a novel statistical framework to the results of a serially sampled parallel infection assay, in which we simultaneously inoculated each of a large number of replicate host volumes with ∼1 phage particle. We sequentially plated the volumes over the course of infection and counted the plaques that formed after incubation. These counts served as a proxy for the number of phage particles in a single volume as a function of time. From repeated assays, we inferred significant, genetically determined heterogeneity in lysis time and burst size, including lysis time variance. These findings are interesting in light of the genetic and phenotypic constraints on the single-protein lysis mechanism of φX174. We speculate briefly on the mechanisms underlying our results, and we discuss the potential importance of lysis time variance in viral evolution.

  16. Estimation of genetic (co)variances of Gompertz growth function parameters in pigs.

    PubMed

    Coyne, J M; Matilainen, K; Berry, D P; Sevon-Aimonen, M-L; Mäntysaari, E A; Juga, J; Serenius, T; McHugh, N

    2017-04-01

    The objective of this study was to estimate genetic (co)variances for the Gompertz growth function parameters, asymptotic mature weight (A), the ratio of mature weight to birthweight (B) and rate of maturation (k), using alternative modelling approaches. The data set consisted of 51 893 live weight records from 10 201 growing pigs. The growth of each pig was modelled using the Gompertz model employing either a two-step fixed effect or mixed model approach or a one-step mixed model approach using restricted maximum likelihood for the estimation of genetic (co)variance. Heritability estimates for the Gompertz growth function parameters, A (0.40), B (0.69) and k (0.45), were greatest for the one-step approach, compared with the two-step fixed effects approach, A (0.10), B (0.33) and k (0.13), and the two-step mixed model approach, A (0.17), B (0.32) and k (0.18). Inferred genetic correlations (i.e. correlations of estimated breeding values) between growth function parameters within models ranged from -0.78 to 0.76, and across models ranged from 0.28 to 0.73 for parameter A, 0.75 to 0.88 for parameter B and 0.09 to 0.37 for parameter k. Correlations between predicted daily sire live weights based on the Gompertz growth curve parameters' estimated breeding values from 60 to 200 days of age between all three modelled approaches were moderately to strongly correlated (0.75 to 0.95). Results from this study provide heritability estimates for biologically interpretable parameters of pig growth through the quantification of genetic (co)variances, thereby facilitating the estimation of breeding values for inclusion in breeding objectives to aid in breeding and selection decisions.

  17. Genetic selection for increased mean and reduced variance of twinning rate in Belclare ewes.

    PubMed

    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.

  18. Sex chromosome linked genetic variance and the evolution of sexual dimorphism of quantitative traits.

    PubMed

    Husby, Arild; Schielzeth, Holger; Forstmeier, Wolfgang; Gustafsson, Lars; Qvarnström, Anna

    2013-03-01

    Theory predicts that sex chromsome linkage should reduce intersexual genetic correlations thereby allowing the evolution of sexual dimorphism. Empirical evidence for sex linkage has come largely from crosses and few studies have examined how sexual dimorphism and sex linkage are related within outbred populations. Here, we use data on an array of different traits measured on over 10,000 individuals from two pedigreed populations of birds (collared flycatcher and zebra finch) to estimate the amount of sex-linked genetic variance (h(2)z ). Of 17 traits examined, eight showed a nonzero h(2)Z estimate but only four were significantly different from zero (wing patch size and tarsus length in collared flycatchers, wing length and beak color in zebra finches). We further tested how sexual dimorphism and the mode of selection operating on the trait relate to the proportion of sex-linked genetic variance. Sexually selected traits did not show higher h(2)Z than morphological traits and there was only a weak positive relationship between h(2)Z and sexual dimorphism. However, given the relative scarcity of empirical studies, it is premature to make conclusions about the role of sex chromosome linkage in the evolution of sexual dimorphism.

  19. Estimation of (co)variance components and genetic parameters of greasy fleece weights in Muzaffarnagari sheep.

    PubMed

    Mandal, A; Neser, F W C; Roy, R; Rout, P K; Notter, D R

    2009-02-01

    Variance components and genetic parameters for greasy fleece weights of Muzaffarnagari sheep maintained at the Central Institute for Research on Goats, Makhdoom, Mathura, India, over a period of 29 years (1976 to 2004) were estimated by restricted maximum likelihood (REML), fitting six animal models including various combinations of maternal effects. Data on body weights at 6 (W6) and 12 months (W12) of age were also included in the study. Records of 2807 lambs descended from 160 rams and 1202 ewes were used for the study. Direct heritability estimates for fleece weight at 6 (FW6) and 12 months of age (FW12), and total fleece weights up to 1 year of age (TFW) were 0.14, 0.16 and 0.25, respectively. Maternal genetic and permanent environmental effects did not significantly influence any of the traits under study. Genetic correlations among fleece weights and body weights were obtained from multivariate analyses. Direct genetic correlations of FW6 with W6 and W12 were relatively large, ranging from 0.61 to 0.67, but only moderate genetic correlations existed between FW12 and W6 (0.39) and between FW12 and W12 (0.49). The genetic correlation between FW6 and FW12 was very high (0.95), but the corresponding phenotypic correlation was much lower (0.28). Heritability estimates for all traits were at least 0.15, indicating that there is potential for their improvement by selection. The moderate to high positive genetic correlations between fleece weights and body weights at 6 and 12 months of age suggest that some of the genetic factors that influence animal growth also influence wool growth. Thus selection to improve the body weights or fleece weights at 6 months of age will also result in genetic improvement of fleece weights at subsequent stages of growth.

  20. Direct and maternal (co)variance components, genetic parameters, and annual trends for growth traits of Makooei sheep in Iran.

    PubMed

    Mohammadi, Hossein; Shahrebabak, Mohammad Moradi; Vatankhah, Mahmood; Shahrebabak, Hossein Moradi

    2013-01-01

    Genetic parameters and genetic trends for birth weight (BW), weaning weight (WW), 6-month weight (6MW), and yearling weight (YW) traits were estimated by using records of 5,634 Makooei lambs, descendants of 289 sires and 1,726 dams, born between 1996 and 2009 at the Makooei sheep breeding station, West Azerbaijan, Iran. The (co)variance components were estimated with different animal models using a restricted maximum likelihood procedure and the most appropriate model for each trait was determined by Akaike's Information Criterion. Breeding values of animals were predicted with best linear unbiased prediction methodology under multi-trait animal models and genetic trends were estimated by regression mean breeding values on birth year. The most appropriate model for BW was a model including direct and maternal genetic effects, regardless of their covariance. The model for WW and 6MW included direct additive genetic effects. The model for YW included direct genetic effects only. Direct heritabilities based on the best model were estimated 0.15 ± 0.04, 0.16 ± 0.03, 0.21 ± 0.04, and 0.22 ± 0.06 for BW, WW, 6MW, and YW, respectively, and maternal heritability obtained 0.08 ± 0.02 for BW. Genetic correlations among the traits were positive and varied from 0.28 for BW-YW to 0.66 for BW-WW and phenotypic correlations were generally lower than the genetic correlations. Genetic trends were 8.1 ± 2, 67.4 ± 5, 38.7 ± 4, and 47.6 ± 6 g per year for BW, WW, 6MW, and YW, respectively.

  1. Colour ornamentation in the blue tit: quantitative genetic (co)variances across sexes

    PubMed Central

    Charmantier, A; Wolak, M E; Grégoire, A; Fargevieille, A; Doutrelant, C

    2017-01-01

    Although secondary sexual traits are commonly more developed in males than females, in many animal species females also display elaborate ornaments or weaponry. Indirect selection on correlated traits in males and/or direct sexual or social selection in females are hypothesized to drive the evolution and maintenance of female ornaments. Yet, the relative roles of these evolutionary processes remain unidentified, because little is known about the genetic correlation that might exist between the ornaments of both sexes, and few estimates of sex-specific autosomal or sex-linked genetic variances are available. In this study, we used two wild blue tit populations with 9 years of measurements on two colour ornaments: one structurally based (blue crown) and one carotenoid based (yellow chest). We found significant autosomal heritability for the chromatic part of the structurally based colouration in both sexes, whereas carotenoid chroma was heritable only in males, and the achromatic part of both colour patches was mostly non heritable. Power limitations, which are probably common among most data sets collected so far in wild populations, prevented estimation of sex-linked genetic variance. Bivariate analyses revealed very strong cross-sex genetic correlations in all heritable traits, although the strength of these correlations was not related to the level of sexual dimorphism. In total, our results suggest that males and females share a majority of their genetic variation underlying colour ornamentation, and hence the evolution of these sex-specific traits may depend greatly on correlated responses to selection in the opposite sex. PMID:27577691

  2. Rapid divergence of genetic variance-covariance matrix within a natural population.

    PubMed

    Doroszuk, Agnieszka; Wojewodzic, Marcin W; Gort, Gerrit; Kammenga, Jan E

    2008-03-01

    The matrix of genetic variances and covariances (G matrix) represents the genetic architecture of multiple traits sharing developmental and genetic processes and is central for predicting phenotypic evolution. These predictions require that the G matrix be stable. Yet the timescale and conditions promoting G matrix stability in natural populations remain unclear. We studied stability of the G matrix in a 20-year evolution field experiment, where a population of the cosmopolitan parthenogenetic soil nematode Acrobeloides nanus was subjected to drift and divergent selection (benign and stress environments). Selection regime did not influence the level of absolute genetic constraints: under both regimes, two genetic dimensions for three life-history traits were identified. A substantial response to selection in principal components structure and in general matrix pattern was indicated by three statistical methods. G structure was also influenced by drift, with higher divergence under benign conditions. These results show that the G matrix might evolve rapidly in natural populations. The observed high dynamics of G structure probably represents the general feature of asexual species and limits the predictive power of G in phenotypic evolution analyses.

  3. Who’s Afraid of Math? Two Sources of Genetic Variance for Mathematical Anxiety

    PubMed Central

    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

  4. Accounting for additive genetic mutations on litter size in Ripollesa sheep.

    PubMed

    Casellas, J; Caja, G; Piedrafita, J

    2010-04-01

    Little is known about mutational variability in livestock, among which only a few mutations with relatively large effects have been reported. In this manuscript, mutational variability was analyzed in 1,765 litter size records from 404 Ripollesa ewes to characterize the magnitude of this genetic source of variation and check the suitability of including mutational effects in genetic evaluations of this breed. Threshold animal models accounting for additive genetic mutations were preferred to models without mutational contributions, with an average difference in the deviance information criterion of more than 5 units. Moreover, the statistical relevance of the additive genetic mutation term was checked through a Bayes factor approach, which showed that the models with mutational variability were 8.5 to 22.7 times more probable than the others. The mutational heritability (percentage of the phenotypic variance accounted for by mutational variance) was 0.6 or 0.9%, depending on whether genetic dominance effects were accounted for by the analytical model. The inclusion of mutational effects in the genetic model for evaluating litter size in Ripollesa ewes called for some minor modifications in the genetic merit order of the individuals evaluated, which suggested that the continuous uploading of new additive mutations could be taken into account to optimize the selection scheme. This study is the first attempt to estimate mutational variances in a livestock species and thereby contribute to better characterization of the genetic background of productive traits of interest.

  5. Population divergence along lines of genetic variance and covariance in the invasive plant Lythrum salicaria in eastern North America.

    PubMed

    Colautti, Robert I; Barrett, Spencer C H

    2011-09-01

    Evolution during biological invasion may occur over contemporary timescales, but the rate of evolutionary change may be inhibited by a lack of standing genetic variation for ecologically relevant traits and by fitness trade-offs among them. The extent to which these genetic constraints limit the evolution of local adaptation during biological invasion has rarely been examined. To investigate genetic constraints on life-history traits, we measured standing genetic variance and covariance in 20 populations of the invasive plant purple loosestrife (Lythrum salicaria) sampled along a latitudinal climatic gradient in eastern North America and grown under uniform conditions in a glasshouse. Genetic variances within and among populations were significant for all traits; however, strong intercorrelations among measurements of seedling growth rate, time to reproductive maturity and adult size suggested that fitness trade-offs have constrained population divergence. Evidence to support this hypothesis was obtained from the genetic variance-covariance matrix (G) and the matrix of (co)variance among population means (D), which were 79.8% (95% C.I. 77.7-82.9%) similar. These results suggest that population divergence during invasive spread of L. salicaria in eastern North America has been constrained by strong genetic correlations among life-history traits, despite large amounts of standing genetic variation for individual traits.

  6. Estimates of (co)variance components and genetic parameters for growth traits of Avikalin sheep.

    PubMed

    Prince, Leslie Leo L; Gowane, Gopal R; Chopra, Ashish; Arora, Amrit L

    2010-08-01

    (Co)variance components and genetic parameters for various growth traits of Avikalin sheep maintained at Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India, were estimated by Restricted Maximum Likelihood, fitting six animal models with various combinations of direct and maternal effects. Records of 3,840 animals descended from 257 sires and 1,194 dams were taken for this study over a period of 32 years (1977-2008). Direct heritability estimates (from best model as per likelihood ratio test) for weight at birth, weaning, 6 and 12 months of age, and average daily gain from birth to weaning, weaning to 6 months, and 6 to 12 months were 0.28 +/- 0.03, 0.20 +/- 0.03, 0.28 +/- 0.07, 0.15 +/- 0.04, 0.21 +/- 0.03, 0.16 and 0.03 +/- 0.03, respectively. Maternal heritability for traits declined as animal grows older and it was not at all evident at adult age and for post-weaning daily gain. Maternal permanent environmental effect (c(2)) declined significantly with advancement of age of animal. A small effect of c(2) on post-weaning weights was probably a carryover effect of pre-weaning maternal influence. A significant large negative genetic correlation was observed between direct and maternal genetic effects for all the traits, indicating antagonistic pleiotropy, which needs special care while formulating breeding plans. A fair rate of genetic progress seems possible in the flock by selection for all traits, but direct and maternal genetic correlation needs to be taken in to consideration.

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

    NASA Astrophysics Data System (ADS)

    Kumral, Mustafa; Ozer, Umit

    2013-03-01

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

  8. Estimation of variance components and genetic trends for twinning rate in Holstein dairy cattle of Iran.

    PubMed

    Ghavi Hossein-Zadeh, N; Nejati-Javaremi, A; Miraei-Ashtiani, S R; Kohram, H

    2009-07-01

    Calving records from the Animal Breeding Center of Iran, collected from January 1991 to December 2007 and comprising 1,163,594 Holstein calving events from 2,552 herds, were analyzed using a linear animal model, linear sire model, threshold animal model, and threshold sire model to estimate variance components, heritabilities, genetic correlations, and genetic trends for twinning rate in the first, second, and third parities. The overall twinning rate was 3.01%. Mean incidence of twins increased from first to fourth and later parities: 1.10, 3.20, 4.22, and 4.50%, respectively. For first-parity cows, a maximum frequency of twinning was observed from January through April (1.36%), and second- and third-parity cows showed peaks from July to September (at 3.35 and 4.55%, respectively). The phenotypic rate of twinning decreased from 1991 to 2007 for the first, second, and third parities. Sire predicted transmitting abilities were estimated using linear sire model and threshold sire model analyses. Sire transmitting abilities for twinning rate in the first, second, and third parities ranged from -0.30 to 0.42, -0.32 to 0.31, and -0.27 to 0.30, respectively. Heritability estimates of twinning rate for parities 1, 2, and 3 ranged from 1.66 to 10.6%, 1.35 to 9.0%, and 1.10 to 7.3%, respectively, using different models for analysis. Heritability estimates for twinning rate, obtained from the analysis of threshold models, were greater than the estimates of linear models. Solutions for age at calving for the first, second, and third parities demonstrated that cows older at calving were more likely to have twins. Genetic correlations for twinning rate between parities 2 and 3 were greater than correlations between parities 1 and 2 and between parities 1 and 3. There was a slightly increasing trend for twinning rate in parities 1, 2, and 3 over time with the analysis of linear animal and linear sire models, but the trend for twinning rate in parities 1, 2, and 3 with threshold

  9. Small Variance in Growth Rate in Annual Plants has Large Effects on Genetic Drift

    Technology Transfer Automated Retrieval System (TEKTRAN)

    When plant size is strongly correlated with plant reproduction, variance in growth rates results in a lognormal distribution of seed production within a population. Fecundity variance affects effective population size (Ne), which reflects the ability of a population to maintain beneficial mutations ...

  10. Knowledge extraction algorithm for variances handling of CP using integrated hybrid genetic double multi-group cooperative PSO and DPSO.

    PubMed

    Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

    2012-04-01

    Although the clinical pathway (CP) predefines predictable standardized care process for a particular diagnosis or procedure, many variances may still unavoidably occur. Some key index parameters have strong relationship with variances handling measures of CP. In real world, these problems are highly nonlinear in nature so that it's hard to develop a comprehensive mathematic model. In this paper, a rule extraction approach based on combing hybrid genetic double multi-group cooperative particle swarm optimization algorithm (PSO) and discrete PSO algorithm (named HGDMCPSO/DPSO) is developed to discovery the previously unknown and potentially complicated nonlinear relationship between key parameters and variances handling measures of CP. Then these extracted rules can provide abnormal variances handling warning for medical professionals. Three numerical experiments on Iris of UCI data sets, Wisconsin breast cancer data sets and CP variances data sets of osteosarcoma preoperative chemotherapy are used to validate the proposed method. When compared with the previous researches, the proposed rule extraction algorithm can obtain the high prediction accuracy, less computing time, more stability and easily comprehended by users, thus it is an effective knowledge extraction tool for CP variances handling.

  11. Unnatural reactive amino acid genetic code additions

    SciTech Connect

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

    2011-02-15

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

  12. Unnatural reactive amino acid genetic code additions

    SciTech Connect

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

    2013-05-21

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

  13. Unnatural reactive amino acid genetic code additions

    SciTech Connect

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

    2011-08-09

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

  14. Unnatural reactive amino acid genetic code additions

    SciTech Connect

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

    2014-08-26

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

  15. Estimates of (co)variance components and genetic parameters for growth traits in Sirohi goat.

    PubMed

    Gowane, Gopal R; Chopra, Ashish; Prakash, Ved; Arora, A L

    2011-01-01

    Data were collected over a period of 21 years (1988-2008) to estimate (co)variance components for birth weight (BWT), weaning weight (WWT), 6-month weight (6WT), 9-month weight (9WT), 12-month weight (12WT), average daily gain from birth to weaning (ADG1), weaning to 6WT (ADG2), and from 6WT to 12WT (ADG3) in Sirohi goats maintained at the Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India. Analyses were carried out by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. The best model was chosen after testing the improvement of the log-likelihood values. Heritability estimates for BWT, WWT, 6WT, 9WT, 12WT, ADG1, ADG2, and ADG3 were 0.39 ± 0.05, 0.09 ± 0.03, 0.06 ± 0.02, 0.09 ± 0.03, 0.11 ± 0.03, 0.10 ± 0.3, 0.04 ± 0.02, and 0.01 ± 0.01, respectively. For BWT and ADG1, only direct effects were significant. Estimate of maternal permanent environmental effect were important for body weights from weaning to 12WT and also for ADG2 and ADG3. However, direct maternal effects were not significant throughout. Estimate of c (2) were 0.06 ± 0.02, 0.03 ± 0.02, 0.06 ± 0.02, 0.05 ± 0.02, 0.02 ± 0.02, and 0.02 ± 0.02 for 3WT, 6WT, 9WT, 12WT, ADG2, and ADG3, respectively. The estimated repeatabilities across years of ewe effects on kid body weights were 0.10, 0.08, 0.05, 0.08, and 0.08 at birth, weaning, 6, 9, and 12 months of age, respectively. Results suggest possibility of modest rate of genetic progress for body weight traits and ADG1 through selection, whereas only slow progress will be possible for post-weaning gain. Genetic and phenotypic correlations between body weight traits were high and positive. High genetic correlation between 6WT and 9WT suggests that selection of animals at 6 months can be carried out instead of present practice of selection at 9 months.

  16. Variance components and genetic parameters for milk production and lactation pattern in an ethiopian multibreed dairy cattle population.

    PubMed

    Gebreyohannes, Gebregziabher; Koonawootrittriron, Skorn; Elzo, Mauricio A; Suwanasopee, Thanathip

    2013-09-01

    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

  17. Sex-specific genetic variances in life-history and morphological traits of the seed beetle Callosobruchus maculatus.

    PubMed

    Hallsson, Lára R; Björklund, Mats

    2012-01-01

    Knowledge of heritability and genetic correlations are of central importance in the study of adaptive trait evolution and genetic constraints. We use a paternal half-sib-full-sib breeding design to investigate the genetic architecture of three life-history and morphological traits in the seed beetle, Callosobruchus maculatus. Heritability was significant for all traits under observation and genetic correlations between traits (r(A)) were low. Interestingly, we found substantial sex-specific genetic effects and low genetic correlations between sexes (r(MF)) in traits that are only moderately (weight at emergence) to slightly (longevity) sexually dimorphic. Furthermore, we found an increased sire ([Formula: see text]) compared to dam ([Formula: see text]) variance component within trait and sex. Our results highlight that the genetic architecture even of the same trait should not be assumed to be the same for males and females. Furthermore, it raises the issue of the presence of unnoticed environmental effects that may inflate estimates of heritability. Overall, our study stresses the fact that estimates of quantitative genetic parameters are not only population, time, environment, but also sex specific. Thus, extrapolation between sexes and studies should be treated with caution.

  18. Genetic Model Fitting in IQ, Assortative Mating & Components of IQ Variance.

    ERIC Educational Resources Information Center

    Capron, Christiane; Vetta, Adrian R.; Vetta, Atam

    1998-01-01

    The biometrical school of scientists who fit models to IQ data traces their intellectual ancestry to R. Fisher (1918), but their genetic models have no predictive value. Fisher himself was critical of the concept of heritability, because assortative mating, such as for IQ, introduces complexities into the study of a genetic trait. (SLD)

  19. Genetic Variance in Processing Speed Drives Variation in Aging of Spatial and Memory Abilities

    ERIC Educational Resources Information Center

    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…

  20. Genetic diversity and variance of Stentor coeruleus (Ciliophora: Heterotrichea) inferred from inter-simple sequence repeat (ISSR) fingerprinting.

    PubMed

    Zhang, Wen-Jing; Lin, Yuan-Shao; Cao, Wen-Qing; Yang, Jun

    2012-01-01

    We used inter-simple sequence repeat fingerprinting to analyze the genetic structure of 16 populations of Stentor coeruleus from three lakes and three ponds in China. Using 14 polymorphic primers, a total of 99 discernible DNA fragments were detected, among which 76 (76.77%) were polymorphic, indicating median genetic diversity in these populations. Further, both Nei's gene diversity (h) and Shannon's information index (I) between the different populations revealed a median genetic diversity. At the same time, gene flow was interpreted to be low. The main factors responsible for the median level of diversity and low gene flow within populations are probably due to a low frequency of sexual recombinations. Analysis of molecular variance showed that there was high genetic differentiation among the five water bodies. Both cluster analysis and a nonmetric multidimensional scaling analysis suggested that genotypes isolated from the same locations displayed a higher genetic similarity than those from different ones, separating populations into subgroups according to their geographical locations. However, there is a weak positive correlation between the genetic distance and geographical distance.

  1. Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix.

    PubMed

    Zhang, Zhe; Erbe, Malena; He, Jinlong; Ober, Ulrike; Gao, Ning; Zhang, Hao; Simianer, Henner; Li, Jiaqi

    2015-02-09

    Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|GA (BLUP-given genetic architecture), which can use genetic architecture information within the dataset at hand rather than from public sources. This is achieved by using a trait-specific covariance matrix ( T: ), which is a weighted sum of a genetic architecture part ( S: matrix) and the realized relationship matrix ( G: ). The algorithm of BLUP|GA (BLUP-given genetic architecture) is provided and illustrated with real and simulated datasets. Predictive ability of BLUP|GA was validated with three model traits in a dairy cattle dataset and 11 traits in three public datasets with a variety of genetic architectures and compared with GBLUP and other approaches. Results show that BLUP|GA outperformed GBLUP in 20 of 21 scenarios in the dairy cattle dataset and outperformed GBLUP, BayesA, and BayesB in 12 of 13 traits in the analyzed public datasets. Further analyses showed that the difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T: and G: matrices. The new strategy applied in BLUP|GA is a favorable and flexible alternative to the standard GBLUP model, allowing to account for the genetic architecture of the quantitative trait under consideration when necessary. This feature is mainly due to the increased similarity between the trait-specific relationship matrix ( T: matrix) and the genetic relationship matrix at unobserved causal loci. Applying BLUP|GA in WGP would ease the burden of model selection.

  2. Nonlinear Epigenetic Variance: Review and Simulations

    ERIC Educational Resources Information Center

    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…

  3. (Co)variance components, genetic parameters and annual trends for calf weights in a Brahman herd kept on floodable savanna.

    PubMed

    Plasse, Dieter; Verde, Omar; Arango, Jesús; Camaripano, Luis; Fossi, Hugo; Romero, Rafael; Rodriguez, Carlos M; Rumbos, José L

    2002-12-31

    (Co)variance components and genetic parameters were estimated for body weights of an elite Brahman herd under a designed, supervised management and genetic program, including strategic artificial insemination (AI). Restricted maximum likelihood methods were used with a univariate animal model for birth weight (BW) and a bivariate model for weaning weight (205-day weight, 205W) and 18-month weight (548-day weight, 548W). Models included random animal direct and maternal genetic effects, maternal permanent environmental effect (c2), and sex-year-month of birth-age of dam and genetic group (identified and unidentified paternity), as fixed effects. Analysis A1 included all calves and analysis A2 included only those with identified sires. Of the 8,066 calves born, 36% were progeny of AI, 11% from single sire and 53% from multi-sire herds. They were born from 1985 to 1998, from 2559 dams and 146 sires (78 identified). Estimates of direct, maternal and total heritabilities from A1 for BW, 205W and 548W were: 0.23, 0.07 and 0.30; 0.08, 0.14 and 0.16; 0.16, 0.04 and 0.28, respectively. Corresponding estimates of direct maternal genetic correlations were 0.22, 0.07 and 0.86, and c2 estimates were 0.04, 0.14 and 0.04, respectively. Estimates of direct and maternal genetic, and permanent environmental correlations between 205W and 548W were: 0.66, 0.70 and 1.00. Variances and genetic parameters from A1 and A2 were, in general, very similar. Estimates of phenotypic, and direct and maternal genetic trends per year from A1 were: 0.393, 0.004 and 0.003 kg (BW), 3.367, 0.142 and 0.115 kg (205W), 1.813, 0.263 and 0.095 kg (548W). Estimates of direct and maternal genetic trends from A2 were: 0.033 and -0.002 kg (BW); 0.186 and 0.276 kg (205W); 0.471 and 0.136 kg (548W). The modern selection methods that have been used recently should be continued, with emphasis on the improvement of cow efficiency for sustainable beef production on floodable savanna combined with improved pasture.

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

    PubMed

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

    2016-05-01

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

  5. Reasoning over genetic variance information in cause-and-effect models of neurodegenerative diseases.

    PubMed

    Naz, Mufassra; Kodamullil, Alpha Tom; Hofmann-Apitius, Martin

    2016-05-01

    The work we present here is based on the recent extension of the syntax of the Biological Expression Language (BEL), which now allows for the representation of genetic variation information in cause-and-effect models. In our article, we describe, how genetic variation information can be used to identify candidate disease mechanisms in diseases with complex aetiology such as Alzheimer's disease and Parkinson's disease. In those diseases, we have to assume that many genetic variants contribute moderately to the overall dysregulation that in the case of neurodegenerative diseases has such a long incubation time until the first clinical symptoms are detectable. Owing to the multilevel nature of dysregulation events, systems biomedicine modelling approaches need to combine mechanistic information from various levels, including gene expression, microRNA (miRNA) expression, protein-protein interaction, genetic variation and pathway. OpenBEL, the open source version of BEL, has recently been extended to match this requirement, and we demonstrate in our article, how candidate mechanisms for early dysregulation events in Alzheimer's disease can be identified based on an integrative mining approach that identifies 'chains of causation' that include single nucleotide polymorphism information in BEL models.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-22

    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.

  8. Temporal Genetic Variance and Propagule-Driven Genetic Structure Characterize Naturalized Rainbow Trout (Oncorhynchus mykiss) from a Patagonian Lake Impacted by Trout Farming

    PubMed Central

    Seeb, Lisa W.; Seeb, James E.; Arismendi, Ivan; Hernández, Cristián E.; Gajardo, Gonzalo; Galleguillos, Ricardo; Cádiz, Maria I.; Musleh, Selim S.

    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

  9. Temporal Genetic Variance and Propagule-Driven Genetic Structure Characterize Naturalized Rainbow Trout (Oncorhynchus mykiss) from a Patagonian Lake Impacted by Trout Farming.

    PubMed

    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

  10. The Expression of Additive and Nonadditive Genetic Variation under Stress

    PubMed Central

    Blows, M. W.; Sokolowski, M. B.

    1995-01-01

    Experimental lines of Drosophila melanogaster derived from a natural population, which had been isolated in the laboratory for ~70 generations, were crossed to determine if the expression of additive, dominance and epistatic genetic variation in development time and viability was associated with the environment. No association was found between the level of additive genetic effects and environmental value for either trait, but nonadditive genetic effects increased at both extremes of the environmental range for development time. The expression of high levels of dominance and epistatic genetic variation at environmental extremes may be a general expectation for some traits. The disruption of the epistatic gene complexes in the parental lines resulted in hybrid breakdown toward faster development and there was some indication of hybrid breakdown toward higher viability. A combination of genetic drift and natural selection had therefore resulted in different epistatic gene complexes being selected after ~70 generations from a common genetic base. After crossing, the hybrid populations were observed for 10 generations. Epistasis contributed on average 12 hr in development time. Fluctuating asymmetry in sternopleural bristle number also evolved in the hybrid populations, decreasing by >18% in the first seven generations after hybridization. PMID:7672585

  11. Noise variance analysis using a flat panel x-ray detector: A method for additive noise assessment with application to breast CT applications

    PubMed Central

    Yang, Kai; Huang, Shih-Ying; Packard, Nathan J.; Boone, John M.

    2010-01-01

    Purpose: A simplified linear model approach was proposed to accurately model the response of a flat panel detector used for breast CT (bCT). Methods: Individual detector pixel mean and variance were measured from bCT projection images acquired both in air and with a polyethylene cylinder, with the detector operating in both fixed low gain and dynamic gain mode. Once the coefficients of the linear model are determined, the fractional additive noise can be used as a quantitative metric to evaluate the system’s efficiency in utilizing x-ray photons, including the performance of different gain modes of the detector. Results: Fractional additive noise increases as the object thickness increases or as the radiation dose to the detector decreases. For bCT scan techniques on the UC Davis prototype scanner (80 kVp, 500 views total, 30 frames∕s), in the low gain mode, additive noise contributes 21% of the total pixel noise variance for a 10 cm object and 44% for a 17 cm object. With the dynamic gain mode, additive noise only represents approximately 2.6% of the total pixel noise variance for a 10 cm object and 7.3% for a 17 cm object. Conclusions: The existence of the signal-independent additive noise is the primary cause for a quadratic relationship between bCT noise variance and the inverse of radiation dose at the detector. With the knowledge of the additive noise contribution to experimentally acquired images, system modifications can be made to reduce the impact of additive noise and improve the quantum noise efficiency of the bCT system. PMID:20831059

  12. Noise variance analysis using a flat panel x-ray detector: A method for additive noise assessment with application to breast CT applications

    SciTech Connect

    Yang Kai; Huang, Shih-Ying; Packard, Nathan J.; Boone, John M.

    2010-07-15

    Purpose: A simplified linear model approach was proposed to accurately model the response of a flat panel detector used for breast CT (bCT). Methods: Individual detector pixel mean and variance were measured from bCT projection images acquired both in air and with a polyethylene cylinder, with the detector operating in both fixed low gain and dynamic gain mode. Once the coefficients of the linear model are determined, the fractional additive noise can be used as a quantitative metric to evaluate the system's efficiency in utilizing x-ray photons, including the performance of different gain modes of the detector. Results: Fractional additive noise increases as the object thickness increases or as the radiation dose to the detector decreases. For bCT scan techniques on the UC Davis prototype scanner (80 kVp, 500 views total, 30 frames/s), in the low gain mode, additive noise contributes 21% of the total pixel noise variance for a 10 cm object and 44% for a 17 cm object. With the dynamic gain mode, additive noise only represents approximately 2.6% of the total pixel noise variance for a 10 cm object and 7.3% for a 17 cm object. Conclusions: The existence of the signal-independent additive noise is the primary cause for a quadratic relationship between bCT noise variance and the inverse of radiation dose at the detector. With the knowledge of the additive noise contribution to experimentally acquired images, system modifications can be made to reduce the impact of additive noise and improve the quantum noise efficiency of the bCT system.

  13. Additive and nonadditive genetic variation in avian personality traits.

    PubMed

    van Oers, K; Drent, P J; de Jong, G; van Noordwijk, A J

    2004-11-01

    Individuals of all vertebrate species differ consistently in their reactions to mildly stressful challenges. These typical reactions, described as personalities or coping strategies, have a clear genetic basis, but the structure of their inheritance in natural populations is almost unknown. We carried out a quantitative genetic analysis of two personality traits (exploration and boldness) and the combination of these two traits (early exploratory behaviour). This study was carried out on the lines resulting from a two-directional artificial selection experiment on early exploratory behaviour (EEB) of great tits (Parus major) originating from a wild population. In analyses using the original lines, reciprocal F(1) and reciprocal first backcross generations, additive, dominance, maternal effects ands sex-dependent expression of exploration, boldness and EEB were estimated. Both additive and dominant genetic effects were important determinants of phenotypic variation in exploratory behaviour and boldness. However, no sex-dependent expression was observed in either of these personality traits. These results are discussed with respect to the maintenance of genetic variation in personality traits, and the expected genetic structure of other behavioural and life history traits in general.

  14. Previous estimates of mitochondrial DNA mutation level variance did not account for sampling error: comparing the mtDNA genetic bottleneck in mice and humans.

    PubMed

    Wonnapinij, Passorn; Chinnery, Patrick F; Samuels, David C

    2010-04-09

    In cases of inherited pathogenic mitochondrial DNA (mtDNA) mutations, a mother and her offspring generally have large and seemingly random differences in the amount of mutated mtDNA that they carry. Comparisons of measured mtDNA mutation level variance values have become an important issue in determining the mechanisms that cause these large random shifts in mutation level. These variance measurements have been made with samples of quite modest size, which should be a source of concern because higher-order statistics, such as variance, are poorly estimated from small sample sizes. We have developed an analysis of the standard error of variance from a sample of size n, and we have defined error bars for variance measurements based on this standard error. We calculate variance error bars for several published sets of measurements of mtDNA mutation level variance and show how the addition of the error bars alters the interpretation of these experimental results. We compare variance measurements from human clinical data and from mouse models and show that the mutation level variance is clearly higher in the human data than it is in the mouse models at both the primary oocyte and offspring stages of inheritance. We discuss how the standard error of variance can be used in the design of experiments measuring mtDNA mutation level variance. Our results show that variance measurements based on fewer than 20 measurements are generally unreliable and ideally more than 50 measurements are required to reliably compare variances with less than a 2-fold difference.

  15. Additional mechanisms conferring genetic susceptibility to Alzheimer’s disease

    PubMed Central

    Calero, Miguel; Gómez-Ramos, Alberto; Calero, Olga; Soriano, Eduardo; Avila, Jesús; Medina, Miguel

    2015-01-01

    Familial Alzheimer’s disease (AD), mostly associated with early onset, is caused by mutations in three genes (APP, PSEN1, and PSEN2) involved in the production of the amyloid β peptide. In contrast, the molecular mechanisms that trigger the most common late onset sporadic AD remain largely unknown. With the implementation of an increasing number of case-control studies and the upcoming of large-scale genome-wide association studies there is a mounting list of genetic risk factors associated with common genetic variants that have been associated with sporadic AD. Besides apolipoprotein E, that presents a strong association with the disease (OR∼4), the rest of these genes have moderate or low degrees of association, with OR ranging from 0.88 to 1.23. Taking together, these genes may account only for a fraction of the attributable AD risk and therefore, rare variants and epistastic gene interactions should be taken into account in order to get the full picture of the genetic risks associated with AD. Here, we review recent whole-exome studies looking for rare variants, somatic brain mutations with a strong association to the disease, and several studies dealing with epistasis as additional mechanisms conferring genetic susceptibility to AD. Altogether, recent evidence underlines the importance of defining molecular and genetic pathways, and networks rather than the contribution of specific genes. PMID:25914626

  16. Genetic (co)variances and breeding value estimation of Gompertz growth curve parameters in Finnish Yorkshire boars, gilts and barrows.

    PubMed

    Koivula, M; Sevón-Aimonen, M-L; Strandén, I; Matilainen, K; Serenius, T; Stalder, K J; Mäntysaari, E A

    2008-06-01

    This paper's objectives were to estimate the genetic (co)variance components of the Gompertz growth curve parameters and to evaluate the relationship of estimated breeding values (EBV) based on average daily gain (ADG) and Gompertz growth curves. Finnish Yorkshire central test station performance data was obtained from the Faba Breeding (Vantaa, Finland). The final data set included 121,488 weight records from 10,111 pigs. Heritability estimates for the Gompertz growth parameters mature weight (alpha), logarithm of mature weight to birth weight ratio (beta) and maturation rate (kappa) were 0.44, 0.55 and 0.31, respectively. Genotypic and phenotypic correlations between the growth curve parameters were high and mainly negative. The only positive relationship was found between alpha and beta. Pearson and Spearman rank correlation coefficients between EBV for ADG and daily gain calculated from Gompertz growth curves were 0.79. The Spearman rank correlation between the sire EBV for ADG and Gompertz growth curve parameter-based ADG for all sires with at least 15 progeny was 0.86. Growth curves differ significantly between individuals and this information could be utilized for selection purposes when improving growth rate in pigs.

  17. Locus BoLA-DRB3 is just an ordinary site of the polygene when explaining genetic variance of somatic cell count and milk yield.

    PubMed

    Oprzadek, Jolanta; Sender, Grazyna; Pawlik, Adrianna; Lukaszewicz, Marek

    2015-11-01

    The study aimed at clarifying the problem of the hitherto contradictory results regarding usefulness of BoLA-DRB3 locus as a marker in selection against mastitis and for milk yield. Treating the BoLA-DRB3 locus effect as random was proposed in place of considering it fixed. Somatic cell counts and milk yields recorded monthly on a test day (22,424) of 619 Polish Holstein cows genotyped for BoLA-DRB3 were analysed with an animal model including a random effect for genotype at this locus. The BoLA-DRB3 alleles were defined as restriction patterns obtained with three endonucleases. Two alternative BoLA-DRB3 additive genotype (co)variance structures were constructed for 161 genotypes recorded. One was based on the allelic similarity of the genotypes resulting in element values of 0 (no common allele), 0.5 (one allele in common), and 1 (diagonal). The other considered restriction site similarity (up to 3 in 1 allele) giving element values of 0 (no common restriction sites) and then increasingly in steps of 1/6 up to 6/6 (diagonal), where the numerator represents the number of common sites between genotypes. The DRB3 variance component for the natural logarithm of somatic cell count did not exceed 0.006 of the polygenic additive component or 0.003 for milk yield. Hence, unless we fail to detect the causative site or to properly define traits being the projection of a site, the effect of the genotype at the BoLA-DRB3 locus does not explain variation in somatic cell count and milk yield at a degree expected of a genetic marker.

  18. Efficient Improvement of Silage Additives by Using Genetic Algorithms

    PubMed Central

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

    2000-01-01

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

  19. Efficient improvement of silage additives by using genetic algorithms.

    PubMed

    Davies, Z S; Gilbert, R J; Merry, R J; Kell, D B; Theodorou, M K; Griffith, G W

    2000-04-01

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

  20. Non-additive and additive genetic effects on extraversion in 3314 Dutch adolescent twins and their parents.

    PubMed

    Rettew, David C; Rebollo-Mesa, Irene; Hudziak, James J; Willemsen, Gonneke; Boomsma, Dorret I

    2008-05-01

    The influence of non-additive genetic influences on personality traits has been increasingly reported in adult populations. Less is known, however, with respect to younger samples. In this study, we examine additive and non-additive genetic contributions to the personality trait of extraversion in 1,689 Dutch twin pairs, 1,505 mothers and 1,637 fathers of the twins. The twins were on average 15.5 years (range 12-18 years). To increase statistical power to detect non-additive genetic influences, data on extraversion were also collected in parents and simultaneously analyzed. Genetic modeling procedures incorporating age as a potential modifier of heritability showed significant influences of additive (20-23%) and non-additive genetic factors (31-33%) in addition to unshared environment (46-48%) for adolescents and for their parents. The additive genetic component was slightly and positively related to age. No significant sex differences were found for either extraversion means or for the magnitude of the genetic and environmental influences. There was no evidence of non-random mating for extraversion in the parental generation. Results show that in addition to additive genetic influences, extraversion in adolescents is influenced by non-additive genetic factors.

  1. Genetic correlations and little genetic variance for reaction norms may limit potential for adaptation to pollution by ionic and nanoparticulate silver in a whitefish (Salmonidae).

    PubMed

    Clark, Emily S; Pompini, Manuel; Uppal, Anshu; Wedekind, Claus

    2016-05-01

    For natural populations to adapt to anthropogenic threats, heritable variation must persist in tolerance traits. Silver nanoparticles, the most widely used engineered nanoparticles, are expected to increase in concentrations in freshwaters. Little is known about how these particles affect wild populations, and whether genetic variation persists in tolerance to permit rapid evolutionary responses. We sampled wild adult whitefish and crossed them in vitro full factorially. In total, 2896 singly raised embryos of 48 families were exposed to two concentrations (0.5 μg/L; 100 μg/L) of differently sized silver nanoparticles or ions (silver nitrate). These doses were not lethal; yet higher concentrations prompted embryos to hatch earlier and at a smaller size. The induced hatching did not vary with nanoparticle size and was stronger in the silver nitrate group. Additive genetic variation for hatching time was significant across all treatments, with no apparent environmental dependencies. No genetic variation was found for hatching plasticity. We found some treatment-dependent heritable variation for larval length and yolk volume, and one instance of additive genetic variation for the reaction norm on length at hatching. Our assessment suggests that the effects of silver exposure on additive genetic variation vary according to trait and silver source. While the long-term fitness consequences of low-level silver exposure on whitefish embryos must be further investigated to determine whether it is, in fact, detrimental, our results suggest that the evolutionary potential for adaptation to these types of pollutants may be low.

  2. Variance in age-specific sex composition of Pacific halibut catches, and comparison of statistical and genetic methods for reconstructing sex ratios

    NASA Astrophysics Data System (ADS)

    Loher, Timothy; Woods, Monica A.; Jimenez-Hidalgo, Isadora; Hauser, Lorenz

    2016-01-01

    Declines in size at age of Pacific halibut Hippoglossus stenolepis, in concert with sexually-dimorphic growth and a constant minimum commercial size limit, have led to the expectation that the sex composition of commercial catches should be increasingly female-biased. Sensitivity analyses suggest that variance in sex composition of landings may be the most influential source of uncertainty affecting current understanding of spawning stock biomass. However, there is no reliable way to determine sex at landing because all halibut are eviscerated at sea. In 2014, a statistical method based on survey data was developed to estimate the probability that fish of any given length at age (LAA) would be female, derived from the fundamental observation that large, young fish are likely female whereas small, old fish have a high probability of being male. Here, we examine variability in age-specific sex composition using at-sea commercial and closed-season survey catches, and compare the accuracy of the survey-based LAA technique to genetic markers for reconstructing the sex composition of catches. Sexing by LAA performed best for summer-collected samples, consistent with the hypothesis that the ability to characterize catches can be influenced by seasonal demographic shifts. Additionally, differences between survey and commercial selectivity that allow fishers to harvest larger fish within cohorts may generate important mismatch between survey and commercial datasets. Length-at-age-based estimates ranged from 4.7% underestimation of female proportion to 12.0% overestimation, with mean error of 5.8 ± 1.5%. Ratios determined by genetics were closer to true sample proportions and displayed less variability; estimation to within < 1% of true ratios was limited to genetics. Genetic estimation of female proportions ranged from 4.9% underestimation to 2.5% overestimation, with a mean absolute error of 1.2 ± 1.2%. Males were generally more difficult to assign than females: 6.7% of

  3. Variance, Genetic Control, and Spatial Phenotypic Plasticity of Morphological and Phenological Traits in Prunus spinosa and Its Large Fruited Forms (P. x fruticans)

    PubMed Central

    Vander Mijnsbrugge, Kristine; Turcsán, Arion; Depypere, Leander; Steenackers, Marijke

    2016-01-01

    Prunus spinosa is a highly esteemed shrub in forest and landscape plantings. Shrubs with larger organs occur often and are considered either as large fruited forms of P. spinosa or as P. x fruticans, involving a hybridization process with the ancient cultivated P. insititia (crop-to-wild gene flow). As climate change may augment hybridization processes in the future, a hybrid origin is important to detect. In addition, studying crop-to-wild gene flow can give insights in putative consequences for the wild populations. We studied the P. spinosa–P. x fruticans group, focusing on morphology and phenology in three experimental plantations. Two plantings harbored cuttings of P. spinosa (clone plantations). A third plantation comprised of a half-sib offspring from a population with both P. spinosa and P. x fruticans (family plantation). Several results point to a hybridization process as the origin of P. x fruticans. The clone plantation revealed endocarp traits to be more genetically controlled than fruit size, while this was the opposite in the family plantation, suggesting the control of fruit size being derived from the putative P. insititia parent. Bud burst, flower opening, and leaf fall were genetically controlled in the clone plantation, whereas in the family plantation intrafamily variability was remarkably large for the bud burst and leaf fall, but not for the flower opening. This suggests there is a reduced genetic control for the first two phenophases, possibly caused by historic hybridization events. Pubescence on the long shoot leaves in the family plantation deviated from the short shoot leaves on the same plants and from long and short shoot leaves in the clone plantation, suggesting again a P. insititia origin. Finally, we quantified spatial phenotypic plasticity, indicating how P. spinosa may react in a changing environment. In contrast to the bud burst and leaf fall, flower opening did not demonstrate plasticity. The fruit size was diminished at the

  4. Prediction of testcross means and variances among F3 progenies of F1 crosses from testcross means and genetic distances of their parents in maize.

    PubMed

    Melchinger, A E; Gumber, R K; Leipert, R B; Vuylsteke, M; Kuiper, M

    1998-03-01

    Prediction of the means and genetic variances in segregating generations could help to assess the breeding potential of base populations. In this study, we investigated whether the testcross (TC) means and variances of F3 progenies from F1 crosses in European maize can be predicted from the TC means of their parents and F1 crosses and four measures of parental genetic divergence: genetic distance (GD) determined by 194 RFLP or 691 AFLP(TM) (1) markers, mid-parent heterosis (MPH), and absolute difference between the TC means of parents (∣P1-P2∣). The experimental materials comprised six sets of crosses; each set consisted of four elite inbreds from the flint or dent germplasm and the six possible F1 crosses between them, which were evaluated for mid-parent heterosis. Testcross progenies of these materials and 20 random F3 plants per F1 cross were produced with a single-cross tester from the opposite heterotic group and evaluated in two environments. The characters studied were plant height, dry matter content and grain yield. The genetic distance between parent lines ranged between 0.17 and 0.70 for RFLPs and between 0.14 and 0.57 for AFLPs in the six sets. Testcross-means of parents, F1 crosses, and F3 populations averaged across the six crosses in a particular set generally agreed well for all three traits. Bartlett's test revealed heterogeneous TC variances among the six crosses in all sets for plant height, in four sets for grain yield and in five sets for dry matter content. Correlations among the TC means of the parents, F1 crosses, and F3 populations were highly significant and positive for all traits. Estimates of the TC variance among F3 progenies for the 36 crosses showed only low correlations with the four measures of parental genetic divergence for all traits. The results demonstrated that for our material, the TC means of the parents or the parental F1 cross can be used as predictors for the TC means of F3 populations. However, the prediction of the

  5. Autosomal and X-Linked Additive Genetic Variation for Lifespan and Aging: Comparisons Within and Between the Sexes in Drosophila melanogaster.

    PubMed

    Griffin, Robert M; Schielzeth, Holger; Friberg, Urban

    2016-12-07

    Theory makes several predictions concerning differences in genetic variation between the X chromosome and the autosomes due to male X hemizygosity. The X chromosome should: (i) typically show relatively less standing genetic variation than the autosomes, (ii) exhibit more variation in males compared to females because of dosage compensation, and (iii) potentially be enriched with sex-specific genetic variation. Here, we address each of these predictions for lifespan and aging in Drosophila melanogaster To achieve unbiased estimates of X and autosomal additive genetic variance, we use 80 chromosome substitution lines; 40 for the X chromosome and 40 combining the two major autosomes, which we assay for sex-specific and cross-sex genetic (co)variation. We find significant X and autosomal additive genetic variance for both traits in both sexes (with reservation for X-linked variation of aging in females), but no conclusive evidence for depletion of X-linked variation (measured through females). Males display more X-linked variation for lifespan than females, but it is unclear if this is due to dosage compensation since also autosomal variation is larger in males. Finally, our results suggest that the X chromosome is enriched for sex-specific genetic variation in lifespan but results were less conclusive for aging overall. Collectively, these results suggest that the X chromosome has reduced capacity to respond to sexually concordant selection on lifespan from standing genetic variation, while its ability to respond to sexually antagonistic selection may be augmented.

  6. Autosomal and X-Linked Additive Genetic Variation for Lifespan and Aging: Comparisons Within and Between the Sexes in Drosophila melanogaster

    PubMed Central

    Griffin, Robert M.; Schielzeth, Holger; Friberg, Urban

    2016-01-01

    Theory makes several predictions concerning differences in genetic variation between the X chromosome and the autosomes due to male X hemizygosity. The X chromosome should: (i) typically show relatively less standing genetic variation than the autosomes, (ii) exhibit more variation in males compared to females because of dosage compensation, and (iii) potentially be enriched with sex-specific genetic variation. Here, we address each of these predictions for lifespan and aging in Drosophila melanogaster. To achieve unbiased estimates of X and autosomal additive genetic variance, we use 80 chromosome substitution lines; 40 for the X chromosome and 40 combining the two major autosomes, which we assay for sex-specific and cross-sex genetic (co)variation. We find significant X and autosomal additive genetic variance for both traits in both sexes (with reservation for X-linked variation of aging in females), but no conclusive evidence for depletion of X-linked variation (measured through females). Males display more X-linked variation for lifespan than females, but it is unclear if this is due to dosage compensation since also autosomal variation is larger in males. Finally, our results suggest that the X chromosome is enriched for sex-specific genetic variation in lifespan but results were less conclusive for aging overall. Collectively, these results suggest that the X chromosome has reduced capacity to respond to sexually concordant selection on lifespan from standing genetic variation, while its ability to respond to sexually antagonistic selection may be augmented. PMID:27678519

  7. Genetic Assessment of Additional Endophenotypes from the Consortium on the Genetics of Schizophrenia Family Study

    PubMed Central

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

    2015-01-01

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

  8. Variance Components and Genetic Parameters Estimated for Fat and Protein Content in Individual Months of Lactation: The Case of Tsigai Sheep.

    PubMed

    Oravcová, Marta

    2016-02-01

    The objective of this study was to assess variance components and genetic parameters for fat and protein content in Tsigai sheep using multivariate animal models in which fat and protein content in individual months of lactation were treated as different traits, and univariate models in which fat and protein content were treated as repeated measures of the same traits. Test day measurements were taken between the second and the seventh month of lactation. The fixed effects were lactation number, litter size and days in milk. The random effects were animal genetic effect and permanent environmental effect of ewe. The effect of flock-year-month of test day measurement was fitted either as a fixed (FYM) or random (fym) effect. Heritabilities for fat content were estimated between 0.06 and 0.17 (FYM fitted) and between 0.06 and 0.11 (fym fitted). Heritabilities for protein content were estimated between 0.15 and 0.23 (FYM fitted) and between 0.10 and 0.18 (fym fitted). For fat content, variance ratios of permanent environmental effect of ewe were estimated between 0.04 and 0.11 (FYM fitted) and between 0.02 and 0.06 (fym fitted). For protein content, variance ratios of permanent environmental effect of ewe were estimated between 0.13 and 0.20 (FYM fitted) and between 0.08 and 0.12 (fym fitted). The proportion of phenotypic variance explained by fym effect ranged from 0.39 to 0.43 for fat content and from 0.25 to 0.36 for protein content. Genetic correlations between individual months of lactation ranged from 0.74 to 0.99 (fat content) and from 0.64 to 0.99 (protein content). Fat content heritabilities estimated with univariate animal models roughly corresponded with heritability estimates from multivariate models: 0.13 (FYM fitted) and 0.07 (fym fitted). Protein content heritabilities estimated with univariate animal models also corresponded with heritability estimates from multivariate models: 0.18 (FYM fitted) and 0.13 (fym fitted).

  9. Genetic control of the environmental variance for birth weight in seven generations of a divergent selection experiment in mice.

    PubMed

    Formoso-Rafferty, N; Cervantes, I; Ibáñez-Escriche, N; Gutiérrez, J P

    2016-06-01

    Data from seven generations of a divergent selection experiment designed for environmental variability of birth weight were analysed to estimate genetic parameters and to explore signs of selection response. A total of 10 783 birth weight records from 638 females and 1127 litters in combination with 10 007 pedigree records were used. Each record of birth weight was assigned to the mother of the pup in a heteroscedastic model, and after seven generations of selection, evidence of success in the selection process was shown. A Bayesian analysis showed that success of the selection process started from the first generation for birth weight and from the second generation for its environmental variability. Genetic parameters were estimated across generations. However, only from the third generation onwards were the records useful to consider the results to be reliable. The results showed a consistent positive and low genetic correlation between the birth weight trait and its environmental variability, which could allow an independent selection process. This study has demonstrated that the genetic control of the birth weight environmental variability is possible in mice. Nevertheless, before the results are applied directly in farm animals, it would be worth confirming any other implications on other important traits, such as robustness, longevity and welfare.

  10. School Performance and Genetic and Environmental Variance in Antisocial Behavior at the Transition from Adolescence to Adulthood

    PubMed Central

    Johnson, Wendy; McGue, Matthew K.; Iacono, William G.

    2009-01-01

    Antisocial behavior increases in adolescence, particularly among those who perform poorly in school. As adolescents move into adulthood, both educational attainment and the extent to which antisocial behavior continues have implications for their abilities to take on constructive social roles. We used a population-representative longitudinal twin study to explore how links between genetic and environmental influences at ages 17 and 24 may be implicated in the developmental processes involved. At age 17, expression of both genetic and nonshared environmental vulnerabilities unique to antisocial behavior was greater among those with low GPA than among those with higher GPA. This suggested that maintenance of high GPA buffered the impact of both genetic and environmental influences encouraging antisocial behavior. When GPA was high, both genetic and environmental influences involved in both traits encouraged good school performance and restrained antisocial behavior. At age 24, however, correlated family environmental influences drove the association between educational attainment and antisocial behavior. Antisocial characteristics involving school performance and educational attainment that transcend generations may slot individuals into social categories that restrict opportunities and reinforce antisocial characteristics. PMID:19586174

  11. (Co)variance components and genetic parameters for growth traits in Arabi sheep using different animal models.

    PubMed

    Shokrollahi, B; Baneh, H

    2012-02-08

    The objective of the present study was to estimate genetic parameters for body weight at different ages in Arabi sheep using data collected from 1999 to 2009. Investigated traits consisted of birth weight (N = 2776), weaning weight (N = 2002) and weight at six months of age (N = 1885). The data were analyzed using restricted maximum likelihood analysis, by fitting univariate and multivariate animal models. All three weight traits were significantly influenced by birth year, sex and birth type. Age of dam only significantly affected birth weight. Log-likelihood ratio tests were conducted to determine the most suitable model for each growth trait in univariate analyses. Direct and total heritability estimates for birth weight, weaning weight and weight at six months of age (based on the best model) were 0.42 and 0.16 (model 4), 0.38 and 0.13 (model 4) and 0.14 and 0.14 (model 1), respectively. Estimation of maternal heritability for birth weight and weaning weight was 0.22 and 0.18, respectively. Genetic and phenotypic correlations among these traits were positive. Phenotypic correlations among traits were low to moderate. Genetic correlations among traits were positive and higher than the corresponding phenotypic correlations. Weaning weight had a strong and significant correlation with weight at six months of age (0.99). We conclude that selection can be made in animals based on weaning weight instead of the present practice of selection based on weight at six months.

  12. Effective population size of steelhead trout: influence of variance in reproductive success, hatchery programs, and genetic compensation between life-history forms.

    PubMed

    Araki, Hitoshi; Waples, Robin S; Ardren, William R; Cooper, Becky; Blouin, Michael S

    2007-03-01

    The effective population size is influenced by many biological factors in natural populations. To evaluate their relative importance, we estimated the effective number of breeders per year (Nb) and effective population size per generation (Ne) in anadromous steelhead trout (Oncorhynchus mykiss) in the Hood River, Oregon (USA). Using demographic data and genetic parentage analysis on an almost complete sample of all adults that returned to the river over 15 years (>15,000 individuals), we estimated Nb for 13 run years and Ne for three entire generations. The results are as follows: (i) the ratio of Ne to the estimated census population size (N) was 0.17-0.40, with large variance in reproductive success among individuals being the primary cause of the reduction in Ne/N; (ii) fish from a traditional hatchery program (Htrad: nonlocal, multiple generations in a hatchery) had negative effects on Nb, not only by reducing mean reproductive success but also by increasing variance in reproductive success among breeding parents, whereas no sign of such effects was found in fish from supplementation hatchery programs (Hsupp: local, single generation in a hatchery); and (iii) Nb was relatively stable among run years, despite the widely fluctuating annual run sizes of anadromous adults. We found high levels of reproductive contribution of nonanadromous parents to anadromous offspring when anadromous run size is small, suggesting a genetic compensation between life-history forms (anadromous and nonanadromous). This is the first study showing that reproductive interaction between different life-history forms can buffer the genetic impact of fluctuating census size on Ne.

  13. μ-Calpain, calpastatin, and growth hormone receptor genetic effects on preweaning performance, carcass quality traits, and residual variance of tenderness in Angus cattle selected to increase minor haplotype and allele frequencies.

    PubMed

    Tait, R G; Shackelford, S D; Wheeler, T L; King, D A; Casas, E; Thallman, R M; Smith, T P L; Bennett, G L

    2014-02-01

    Genetic marker effects and interactions are estimated with poor precision when minor marker allele frequencies are low. An Angus population was subjected to marker assisted selection for multiple years to increase divergent haplotype and minor marker allele frequencies to 1) estimate effect size and mode of inheritance for previously reported SNP on targeted beef carcass quality traits; 2) estimate effects of previously reported SNP on nontarget performance traits; and 3) evaluate tenderness SNP specific residual variance models compared to a single residual variance model for tenderness. Divergent haplotypes within µ-calpain (CAPN1), and SNP within calpastatin (CAST) and growth hormone receptor (GHR) were successfully selected to increase their frequencies. Traits evaluated were birth BW, weaning BW, final BW, fat thickness, LM area, USDA marbling score, yield grade, slice shear force (SSF), and visible and near infrared predicted slice shear force. Both CAPN1 and CAST exhibited additive (P < 0.001) modes of inheritance for SSF and neither exhibited dominance (P ≥ 0.19). Furthermore, the interaction between CAPN1 and CAST for SSF was not significant (P = 0.55). Estimated additive effects of CAPN1 (1.049 kg) and CAST (1.257 kg) on SSF were large in this study. Animals homozygous for tender alleles at both CAPN1 and CAST would have 4.61 kg lower SSF (38.6% of the mean) than animals homozygous tough for both markers. There was also an effect of CAST on yield grade (P < 0.02). The tender CAST allele was associated with more red meat yield and less trimmable fat. There were no significant effects (P ≥ 0.23) for GHR on any of the traits evaluated in this study. Furthermore, CAST specific residual variance models were found to fit significantly better (P < 0.001) than single residual variance models for SSF, with the tougher genotypes having larger residual variance. Thus, the risk of a tough steak from the undesired CAST genotype is increased through both an

  14. The genetic structure of Asian corn borer, Ostrinia furnacalis, populations in China: haplotype variance in northern populations and potential impact on management of resistance to transgenic maize.

    PubMed

    Li, Jing; Coates, Brad S; Kim, Kyung Seok; Bourguet, Denis; Ponsard, Sergine; He, Kanglai; Wang, Zhenying

    2014-01-01

    Asian corn borer, Ostrinia furnacalis (Guenée), is a severe pest that infests cultivated maize in the major production regions of China. Populations show genotype-by-environment variation in voltinism, such that populations with a single generation (univoltine) are fixed in Northern China where growing seasons are short. Low genetic differentiation was found among samples from 33 collection sites across China and one site from North Korea (n=1673) using variation at 6 nuclear microsatellite loci (ENA corrected global FST=0.020; P value<0.05). Analysis of molecular variance indicated that geographic region, number of generations or voltinism accounted for <0.38% of the total genetic variation at nuclear loci and was corroborated by clustering of co-ancestries among genotypes using the program STRUCTURE. In contrast, a mitochondrial haplotype network identified 4 distinct clusters, where 70.5% of samples from univoltine populations were within a single group. Univoltine populations were also placed into a unique cluster using Population Graph and Principal component analyses, which showed significant differentiation with multivoltine populations (φST=0.400; P value<0.01). This study suggests that gene flow among O. furnacalis in China may be high among regions, with the exception of northeastern localities. Haplotype variation may be due to random genetic drift resulting from partial reproductive isolation between univoltine and multivoltine O. furnacalis populations. Such reproductive isolation might impact the potential spread of alleles that confer resistance to transgenic maize in China.

  15. Genetic variance contributes to ingestive processes: a survey of eleven inbred mouse strains for fat (Intralipid) intake.

    PubMed

    Lewis, Sarah R; Dym, Cheryl; Chai, Christina; Singh, Amreeta; Kest, Benjamin; Bodnar, Richard J

    2007-01-30

    Genetic variation across inbred and outbred mouse strains have been observed for intake of sweet solutions, salts, bitter tastants and a high-fat diet. Our laboratory recently reported marked strain differences in the amounts and/or percentages of kilocalories of sucrose consumed among 11 inbred and one outbred mouse strains exposed to a wide range of nine sucrose concentrations (0.0001-5%) in two-bottle 24-h preference tests. To assess whether differences in fat intake were similarly associated with genetic variation, the present study examined intake of chow, water and an emulsified fat source (Intralipid) across nine different concentrations (0.00001-5%) in the same 11 inbred and 1 outbred mouse strains using two-bottle 24-h preference tests, which controlled for Intralipid concentration presentation effects, Intralipid and water bottle positions, and measurement of kilocalorie intake consumed as Intralipid or chow. Strains displayed differential increases in Intralipid intake relative to corresponding water with significant effects observed at the seven (BALB/cJ: 0.001% threshold sensitivity), four (AKR/J, C57BL/6J, DBA/2J, SWR/J: 0.5% threshold sensitivity), three (CD-1, C57BL/10J, SJL/J: 1% threshold sensitivity) and two (A/J, CBA/J, C3H/HeJ, 129P3/J: 2% threshold sensitivity) highest concentrations. In assessing the percentage of kilocalories consumed as Intralipid, SWR/J mice consumed significantly more at the three highest concentrations to a greater degree than BALB/cJ, C57BL/6J, CD-1, C3H/HeJ, DBA/J and 129P3/J strains which in turn consumed more than A/J, AKR/J, CBA/J, C57BL/10J and SJL/J mice. Relatively strong (h2 = 0.73-0.79) heritability estimates were obtained for weight-adjusted Intralipid intake at those concentrations (0.001-1%) that displayed the largest strain-specific effects in sensitivity to Intralipid. The identification of strains with diverging abilities to regulate kilocalorie intake when presented with high Intralipid concentrations

  16. Estimates of (co)variance components and genetic parameters for body weights and first greasy fleece weight in Bharat Merino sheep.

    PubMed

    Gowane, G R; Chopra, A; Prince, L L L; Paswan, C; Arora, A L

    2010-03-01

    (Co)variance components and genetic parameters of weight at birth (BWT), weaning (3WT), 6, 9 and 12 months of age (6WT, 9WT and 12WT, respectively) and first greasy fleece weight (GFW) of Bharat Merino sheep, maintained at Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India, were estimated by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. Data were collected over a period of 10 years (1998 to 2007). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for BWT, 3WT, 6WT, 9WT and 12WT and first GFW were 0.05 ± 0.03, 0.04 ± 0.02, 0.00, 0.03 ± 0.03, 0.09 ± 0.05 and 0.05 ± 0.03, respectively. There was no evidence for the maternal genetic effect on the traits under study. Maternal permanent environmental effect contributed 19% for BWT and 6% to 11% from 3WT to 9WT and 11% for first GFW. Maternal permanent environmental effect on the post-3WT was a carryover effect of maternal influences during pre-weaning age. A low rate of genetic progress seems possible in the flock through selection. Direct genetic correlations between body weight traits were positive and ranged from 0.36 between BWT and 6WT to 0.94 between 3WT and 6WT and between 6WT and 12WT. Genetic correlations of 3WT with 6WT, 9WT and 12WT were high and positive (0.94, 0.93 and 0.93, respectively), suggesting that genetic gain in post-3WT will be maintained if selection age is reduced to 3 months. The genetic correlations of GFW with live weights were 0.01, 0.16, 0.18, 0.40 and 0.32 for BWT, 3WT, 6WT, 9WT and 12WT, respectively. Correlations of permanent environmental effects of the dam across different traits were high and positive for all the traits (0.45 to 0.98).

  17. Effects of single nucleotide polymorphism marker density on degree of genetic variance explained and genomic evaluation for carcass traits in Japanese Black beef cattle

    PubMed Central

    2014-01-01

    Background Japanese Black cattle are a beef breed whose meat is well known to excel in meat quality, especially in marbling, and whose effective population size is relatively low in Japan. Unlike dairy cattle, the accuracy of genomic evaluation (GE) for carcass traits in beef cattle, including this breed, has been poorly studied. For carcass weight and marbling score in the breed, as well as the extent of whole genome linkage disequilibrium (LD), the effects of equally-spaced single nucleotide polymorphisms (SNPs) density on genomic relationship matrix (G matrix), genetic variance explained and GE were investigated using the genotype data of about 40,000 SNPs and two statistical models. Results Using all pairs of two adjacent SNPs in the whole SNP set, the means of LD (r 2 ) at ranges 0–0.1, 0.1–0.2, 0.2–0.5 and 0.5–1 Mb were 0.22, 0.13, 0.10 and 0.08, respectively, and 25.7, 13.9, 10.4 and 6.4% of the r 2 values exceeded 0.3, respectively. While about 90% of the genetic variance for carcass weight estimated using all available SNPs was explained using 4,000–6,000 SNPs, the corresponding percentage for marbling score was consistently lower. With the conventional linear model incorporating the G matrix, correlation between the genomic estimated breeding values (GEBVs) obtained using 4,000 SNPs and all available SNPs was 0.99 for carcass weight and 0.98 for marbling score, with an underestimation of the former GEBVs, especially for marbling score. Conclusions The Japanese Black is likely to be in a breed group with a relatively high extent of whole genome LD. The results indicated that the degree of marbling is controlled by only QTLs with relatively small effects, compared with carcass weight, and that using at least 4,000 equally-spaced SNPs, there is a possibility of ranking animals genetically for these carcass traits in this breed. PMID:24491120

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

    PubMed

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

    2016-08-01

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

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

    PubMed

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

    2015-12-01

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

  20. The contribution of additive genetic variation to personality variation: heritability of personality.

    PubMed

    Dochtermann, Ned A; Schwab, Tori; Sih, Andrew

    2015-01-07

    Individual animals frequently exhibit repeatable differences from other members of their population, differences now commonly referred to as 'animal personality'. Personality differences can arise, for example, from differences in permanent environmental effects--including parental and epigenetic contributors--and the effect of additive genetic variation. Although several studies have evaluated the heritability of behaviour, less is known about general patterns of heritability and additive genetic variation in animal personality. As overall variation in behaviour includes both the among-individual differences that reflect different personalities and temporary environmental effects, it is possible for personality to be largely genetically influenced even when heritability of behaviour per se is quite low. The relative contribution of additive genetic variation to personality variation can be estimated whenever both repeatability and heritability are estimated for the same data. Using published estimates to address this issue, we found that approximately 52% of animal personality variation was attributable to additive genetic variation. Thus, while the heritability of behaviour is often moderate or low, the heritability of personality is much higher. Our results therefore (i) demonstrate that genetic differences are likely to be a major contributor to variation in animal personality and (ii) support the phenotypic gambit: that evolutionary inferences drawn from repeatability estimates may often be justified.

  1. Genetic algorithm-guided discovery of additive combinations that direct quantum dot assembly.

    PubMed

    Bawazer, Lukmaan A; Ihli, Johannes; Comyn, Timothy P; Critchley, Kevin; Empson, Christopher J; Meldrum, Fiona C

    2015-01-14

    The use of combinations of organic additives to control crystallization, as occurs in biomineralization, is rarely investigated due to the vast potential reaction space. It is demonstrated here that combinatorial approaches led by genetic algorithm heuristics can enable identification of active additive combinations, and four key organic molecules are rapidly identified, which generate highly fluorescent CdS quantum dot superstructures.

  2. Nonlinear selection and the evolution of variances and covariances for continuous characters in an anole.

    PubMed

    Revell, L J; Mahler, D L; Sweeney, J R; Sobotka, M; Fancher, V E; Losos, J B

    2010-02-01

    The pattern of genetic variances and covariances among characters, summarized in the additive genetic variance-covariance matrix, G, determines how a population will respond to linear natural selection. However, G itself also evolves in response to selection. In particular, we expect that, over time, G will evolve correspondence with the pattern of multivariate nonlinear natural selection. In this study, we substitute the phenotypic variance-covariance matrix (P) for G to determine if the pattern of multivariate nonlinear selection in a natural population of Anolis cristatellus, an arboreal lizard from Puerto Rico, has influenced the evolution of genetic variances and covariances in this species. Although results varied among our estimates of P and fitness, and among our analytic techniques, we find significant evidence for congruence between nonlinear selection and P, suggesting that natural selection may have influenced the evolution of genetic constraint in this species.

  3. Direct and maternal (co)variance components, genetic parameters and annual trends for growth traits of Dorper sheep in semi-arid Kenya.

    PubMed

    Kariuki, C M; Ilatsia, Evans D; Kosgey, Isaac S; Kahi, Alexander K

    2010-03-01

    Genetic and phenotypic parameters were estimated for lamb growth traits for the Dorper sheep in semi-arid Kenya using an animal model. Data on lamb growth performance were extracted from available performance records at the Sheep and Goats Station in Naivasha, Kenya. Growth traits considered were body weights at birth (BW0, kg), at 1 month (BW1, kg), at 2 months (BW2, kg), at weaning (WW, kg), at 6 months (BW6, kg), at 9 months (BW9, kg) and at yearling (YW, kg), average daily gain from birth to 6 months (ADG(0-6), gm) and from 6 months to 1 year (ADG(6-12), gm). Direct heritability estimates were, correspondingly, 0.18, 0.36, 0.32, 0.28, 0.21, 0.14, 0.29, 0.12 and 0.30 for BW0, BW1, BW2, WW, BW6, BW9, YW, ADG(0-6) and ADG(6-12). The corresponding maternal genetic heritability estimates for body weights up to 9 months were 0.16, 0.10, 0.10, 0.19, 0.21 and 0.18. Direct-maternal genetic correlations were negative and high ranging between -0.47 to -0.94. Negative genetic correlations were observed for ADG(0-6)-ADG(6-12), BW2-ADG(6-12), WW-ADG(6-12) and BW6-ADG(6-12). Phenotypic correlations ranged from 0.15 to 0.96. Maternal effects are important in the growth performance of the Dorper sheep though a negative correlation exists between direct and maternal genetic effects. The current study has provided important information on the extent of additive genetic variation in the existing flocks that could now be used in determining the merit of breeding rams and ewes for sale to the commercial flocks. The estimates provided would form the basis of designing breeding schemes for the Dorper sheep in Kenya. Implications of the study to future Dorper sheep breeding programmes are also discussed.

  4. Comparing GWAS Results of Complex Traits Using Full Genetic Model and Additive Models for Revealing Genetic Architecture

    PubMed Central

    Monir, Md. Mamun; Zhu, Jun

    2017-01-01

    Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits. PMID:28079101

  5. Additives

    NASA Technical Reports Server (NTRS)

    Smalheer, C. V.

    1973-01-01

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

  6. Inheritance of dermatoglyphic traits in twins: univariate and bivariate variance decomposition analysis.

    PubMed

    Karmakar, Bibha; Malkin, Ida; Kobyliansky, Eugene

    2012-01-01

    Dermatoglyphic traits in a sample of twins were analyzed to estimate the resemblance between MZ and DZ twins and to evaluate the mode of inheritance by using the maximum likelihood-based Variance decomposition analysis. The additive genetic variance component was significant in both sexes for four traits--PII, AB_RC, RC_HB, and ATD_L. AB RC and RC_HB had significant sex differences in means, whereas PII and ATD_L did not. The results of the Bivariate Variance decomposition analysis revealed that PII and RC_HB have a significant correlation in both genetic and residual components. Significant correlation in the additive genetic variance between AB_RC and ATD_L was observed. The same analysis only for the females sub-sample in the three traits RBL, RBR and AB_DIS shows that the additive genetic RBR component was significant and the AB_DIS sibling component was not significant while others cannot be constrained to zero. The additive variance for AB DIS sibling component was not significant. The three components additive, sibling and residual were significantly correlated between each pair of traits revealed by the Bivariate Variance decomposition analysis.

  7. Product versus additive threshold models for analysis of reproduction outcomes in animal genetics.

    PubMed

    David, I; Bodin, L; Gianola, D; Legarra, A; Manfredi, E; Robert-Granié, C

    2009-08-01

    The phenotypic observation of some reproduction traits (e.g., insemination success, interval from lambing to insemination) is the result of environmental and genetic factors acting on 2 individuals: the male and female involved in a mating couple. In animal genetics, the main approach (called additive model) proposed for studying such traits assumes that the phenotype is linked to a purely additive combination, either on the observed scale for continuous traits or on some underlying scale for discrete traits, of environmental and genetic effects affecting the 2 individuals. Statistical models proposed for studying human fecundability generally consider reproduction outcomes as the product of hypothetical unobservable variables. Taking inspiration from these works, we propose a model (product threshold model) for studying a binary reproduction trait that supposes that the observed phenotype is the product of 2 unobserved phenotypes, 1 for each individual. We developed a Gibbs sampling algorithm for fitting a Bayesian product threshold model including additive genetic effects and showed by simulation that it is feasible and that it provides good estimates of the parameters. We showed that fitting an additive threshold model to data that are simulated under a product threshold model provides biased estimates, especially for individuals with high breeding values. A main advantage of the product threshold model is that, in contrast to the additive model, it provides distinct estimates of fixed effects affecting each of the 2 unobserved phenotypes.

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

    PubMed Central

    2012-01-01

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

  9. Do Health Professionals Need Additional Competencies for Stratified Cancer Prevention Based on Genetic Risk Profiling?

    PubMed Central

    Chowdhury, Susmita; Henneman, Lidewij; Dent, Tom; Hall, Alison; Burton, Alice; Pharoah, Paul; Pashayan, Nora; Burton, Hilary

    2015-01-01

    There is growing evidence that inclusion of genetic information about known common susceptibility variants may enable population risk-stratification and personalized prevention for common diseases including cancer. This would require the inclusion of genetic testing as an integral part of individual risk assessment of an asymptomatic individual. Front line health professionals would be expected to interact with and assist asymptomatic individuals through the risk stratification process. In that case, additional knowledge and skills may be needed. Current guidelines and frameworks for genetic competencies of non-specialist health professionals place an emphasis on rare inherited genetic diseases. For common diseases, health professionals do use risk assessment tools but such tools currently do not assess genetic susceptibility of individuals. In this article, we compare the skills and knowledge needed by non-genetic health professionals, if risk-stratified prevention is implemented, with existing competence recommendations from the UK, USA and Europe, in order to assess the gaps in current competences. We found that health professionals would benefit from understanding the contribution of common genetic variations in disease risk, the rationale for a risk-stratified prevention pathway, and the implications of using genomic information in risk-assessment and risk management of asymptomatic individuals for common disease prevention. PMID:26068647

  10. Do Health Professionals Need Additional Competencies for Stratified Cancer Prevention Based on Genetic Risk Profiling?

    PubMed

    Chowdhury, Susmita; Henneman, Lidewij; Dent, Tom; Hall, Alison; Burton, Alice; Pharoah, Paul; Pashayan, Nora; Burton, Hilary

    2015-06-09

    There is growing evidence that inclusion of genetic information about known common susceptibility variants may enable population risk-stratification and personalized prevention for common diseases including cancer. This would require the inclusion of genetic testing as an integral part of individual risk assessment of an asymptomatic individual. Front line health professionals would be expected to interact with and assist asymptomatic individuals through the risk stratification process. In that case, additional knowledge and skills may be needed. Current guidelines and frameworks for genetic competencies of non-specialist health professionals place an emphasis on rare inherited genetic diseases. For common diseases, health professionals do use risk assessment tools but such tools currently do not assess genetic susceptibility of individuals. In this article, we compare the skills and knowledge needed by non-genetic health professionals, if risk-stratified prevention is implemented, with existing competence recommendations from the UK, USA and Europe, in order to assess the gaps in current competences. We found that health professionals would benefit from understanding the contribution of common genetic variations in disease risk, the rationale for a risk-stratified prevention pathway, and the implications of using genomic information in risk-assessment and risk management of asymptomatic individuals for common disease prevention.

  11. Additive genetic breeding values correlate with the load of partially deleterious mutations.

    PubMed

    Tomkins, Joseph L; Penrose, Marissa A; Greeff, Johan; LeBas, Natasha R

    2010-05-14

    The mutation-selection-balance model predicts most additive genetic variation to arise from numerous mildly deleterious mutations of small effect. Correspondingly, "good genes" models of sexual selection and recent models for the evolution of sex are built on the assumption that mutational loads and breeding values for fitness-related traits are correlated. In support of this concept, inbreeding depression was negatively genetically correlated with breeding values for traits under natural and sexual selection in the weevil Callosobruchus maculatus. The correlations were stronger in males and strongest for condition. These results confirm the role of existing, partially recessive mutations in maintaining additive genetic variation in outbred populations, reveal the nature of good genes under sexual selection, and show how sexual selection can offset the cost of sex.

  12. Significant variance in genetic diversity among populations of Schistosoma haematobium detected using microsatellite DNA loci from a genome-wide database

    PubMed Central

    2013-01-01

    species (i.e., using DNA sequences conserved among species), as well as other markers that are specific to species or species-groups (i.e., using DNA sequences that differ among species). Full genome-sequencing of additional species and specimens of S. haematobium, S. japonicum, and S. mansoni is desirable to better characterize differences within and among these species, to develop additional genetic markers, and to examine genes as well as conserved non-coding elements associated with drug resistance. PMID:24499537

  13. Does variance in drinking motives explain the genetic overlap between personality and alcohol use disorder symptoms? A twin study of young women

    PubMed Central

    Littlefield, Andrew K.; Agrawal, Arpana; Ellingson, Jarrod M.; Kristjansson, Sean; Madden, Pamela A. F.; Bucholz, Kathleen K.; Slutske, Wendy S.; Heath, Andrew C.; Sher, Kenneth J.

    2011-01-01

    Background Genetic risk for alcohol dependence has been shown to overlap with genetic factors contributing to variation in dimensions of personality. Though drinking motives have been posited as important mediators of the alcohol-personality relation, the extent to which the genetic covariance between alcohol use disorder (AUD) symptoms (i.e. abuse and dependence criteria) and personality is explained by genetic factors contributing to variation in drinking motives remains unclear. Methods Using data from 2,904 young adult female twins, the phenotypic and genetic associations among personality dimensions (constraint [measured by the Multidimensional Personality Questionnaire; Tellegen, 1982], conscientiousness, neuroticism, and agreeableness [measured by the NEO-PI; Costa & McCrae, 1985]), internal drinking motives (enhancement and coping motives [measured by the Drinking Motive Questionnaire; Cooper, 1994]), and AUD symptoms were tested. Results Significant genetic associations were found between all personality measures and AUD symptoms. Coping motives showed significant genetic overlap with AUD symptoms and most personality measures, whereas enhancement motives were not significantly heritable. Adjusting for coping motives, genetic correlations between AUD symptoms and traits of neuroticism and agreeableness were no longer statistically significant. Conclusions Findings suggest that genetic variation in drinking to cope might account for a considerable proportion of the genetic covariance between specific personality dimensions and AUD symptoms. PMID:21790670

  14. Additive genetic variation in schizophrenia risk is shared by populations of African and European descent.

    PubMed

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

    2013-09-05

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

  15. Generalized analysis of molecular variance.

    PubMed

    Nievergelt, Caroline M; Libiger, Ondrej; Schork, Nicholas J

    2007-04-06

    Many studies in the fields of genetic epidemiology and applied population genetics are predicated on, or require, an assessment of the genetic background diversity of the individuals chosen for study. A number of strategies have been developed for assessing genetic background diversity. These strategies typically focus on genotype data collected on the individuals in the study, based on a panel of DNA markers. However, many of these strategies are either rooted in cluster analysis techniques, and hence suffer from problems inherent to the assignment of the biological and statistical meaning to resulting clusters, or have formulations that do not permit easy and intuitive extensions. We describe a very general approach to the problem of assessing genetic background diversity that extends the analysis of molecular variance (AMOVA) strategy introduced by Excoffier and colleagues some time ago. As in the original AMOVA strategy, the proposed approach, termed generalized AMOVA (GAMOVA), requires a genetic similarity matrix constructed from the allelic profiles of individuals under study and/or allele frequency summaries of the populations from which the individuals have been sampled. The proposed strategy can be used to either estimate the fraction of genetic variation explained by grouping factors such as country of origin, race, or ethnicity, or to quantify the strength of the relationship of the observed genetic background variation to quantitative measures collected on the subjects, such as blood pressure levels or anthropometric measures. Since the formulation of our test statistic is rooted in multivariate linear models, sets of variables can be related to genetic background in multiple regression-like contexts. GAMOVA can also be used to complement graphical representations of genetic diversity such as tree diagrams (dendrograms) or heatmaps. We examine features, advantages, and power of the proposed procedure and showcase its flexibility by using it to analyze a

  16. Cosmology without cosmic variance

    SciTech Connect

    Bernstein, Gary M.; Cai, Yan -Chuan

    2011-10-01

    The growth of structures in the Universe is described by a function G that is predicted by the combination of the expansion history of the Universe and the laws of gravity within it. We examine the improvements in constraints on G that are available from the combination of a large-scale galaxy redshift survey with a weak gravitational lensing survey of background sources. We describe a new combination of such observations that in principle this yields a measure of the growth rate that is free of sample variance, i.e. the uncertainty in G can be reduced without bound by increasing the number of redshifts obtained within a finite survey volume. The addition of background weak lensing data to a redshift survey increases information on G by an amount equivalent to a 10-fold increase in the volume of a standard redshift-space distortion measurement - if the lensing signal can be measured to sub-per cent accuracy. This argues that a combined lensing and redshift survey over a common low-redshift volume of the Universe is a more powerful test of general relativity than an isolated redshift survey over larger volume at high redshift, especially as surveys begin to cover most of the available sky.

  17. Cosmology without cosmic variance

    DOE PAGES

    Bernstein, Gary M.; Cai, Yan -Chuan

    2011-10-01

    The growth of structures in the Universe is described by a function G that is predicted by the combination of the expansion history of the Universe and the laws of gravity within it. We examine the improvements in constraints on G that are available from the combination of a large-scale galaxy redshift survey with a weak gravitational lensing survey of background sources. We describe a new combination of such observations that in principle this yields a measure of the growth rate that is free of sample variance, i.e. the uncertainty in G can be reduced without bound by increasing themore » number of redshifts obtained within a finite survey volume. The addition of background weak lensing data to a redshift survey increases information on G by an amount equivalent to a 10-fold increase in the volume of a standard redshift-space distortion measurement - if the lensing signal can be measured to sub-per cent accuracy. This argues that a combined lensing and redshift survey over a common low-redshift volume of the Universe is a more powerful test of general relativity than an isolated redshift survey over larger volume at high redshift, especially as surveys begin to cover most of the available sky.« less

  18. Widespread evidence for non-additive genetic variation in Cloninger's and Eysenck's personality dimensions using a twin plus sibling design.

    PubMed

    Keller, Matthew C; Coventry, William L; Heath, Andrew C; Martin, Nicholas G

    2005-11-01

    Studies using the classical twin design often conclude that most genetic variation underlying personality is additive in nature. However, studies analyzing only twins are very limited in their ability to detect non-additive genetic variation and are unable to detect sources of variation unique to twins, which can mask non-additive genetic variation. The current study assessed 9672 MZ and DZ twin individuals and 3241 of their siblings to investigate the environmental and genetic architecture underlying eight dimensions of personality: four from Eysenck's Personality Questionnaire and four from Cloninger's Temperament and Character Inventory. Broad-sense heritability estimates from best-fitting models were two to three times greater than the narrow-sense heritability estimates for Harm Avoidance, Novelty Seeking, Reward Dependence, Persistence, Extraversion, and Neuroticism. This genetic non-additivity could be due to dominance, additive-by-additive epistasis, or to additive genetic effects combined with higher-order epistasis. Environmental effects unique to twins were detected for both Lie and Psychoticism but accounted for little overall variation. Our results illustrate the increased sensitivity afforded by extending the classical twin design to include siblings, and may provide clues to the evolutionary origins of genetic variation underlying personality.

  19. Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure.

    PubMed

    Crossa, José; Burgueño, Juan; Dreisigacker, Susanne; Vargas, Mateo; Herrera-Foessel, Sybil A; Lillemo, Morten; Singh, Ravi P; Trethowan, Richard; Warburton, Marilyn; Franco, Jorge; Reynolds, Matthew; Crouch, Jonathan H; Ortiz, Rodomiro

    2007-11-01

    Linkage disequilibrium can be used for identifying associations between traits of interest and genetic markers. This study used mapped diversity array technology (DArT) markers to find associations with resistance to stem rust, leaf rust, yellow rust, and powdery mildew, plus grain yield in five historical wheat international multienvironment trials from the International Maize and Wheat Improvement Center (CIMMYT). Two linear mixed models were used to assess marker-trait associations incorporating information on population structure and covariance between relatives. An integrated map containing 813 DArT markers and 831 other markers was constructed. Several linkage disequilibrium clusters bearing multiple host plant resistance genes were found. Most of the associated markers were found in genomic regions where previous reports had found genes or quantitative trait loci (QTL) influencing the same traits, providing an independent validation of this approach. In addition, many new chromosome regions for disease resistance and grain yield were identified in the wheat genome. Phenotyping across up to 60 environments and years allowed modeling of genotype x environment interaction, thereby making possible the identification of markers contributing to both additive and additive x additive interaction effects of traits.

  20. Using pooled data to estimate variance components and breeding values for traits affected by social interactions

    PubMed Central

    2013-01-01

    Background Through social interactions, individuals affect one another’s phenotype. In such cases, an individual’s phenotype is affected by the direct (genetic) effect of the individual itself and the indirect (genetic) effects of the group mates. Using data on individual phenotypes, direct and indirect genetic (co)variances can be estimated. Together, they compose the total genetic variance that determines a population’s potential to respond to selection. However, it can be difficult or expensive to obtain individual phenotypes. Phenotypes on traits such as egg production and feed intake are, therefore, often collected on group level. In this study, we investigated whether direct, indirect and total genetic variances, and breeding values can be estimated from pooled data (pooled by group). In addition, we determined the optimal group composition, i.e. the optimal number of families represented in a group to minimise the standard error of the estimates. Methods This study was performed in three steps. First, all research questions were answered by theoretical derivations. Second, a simulation study was conducted to investigate the estimation of variance components and optimal group composition. Third, individual and pooled survival records on 12 944 purebred laying hens were analysed to investigate the estimation of breeding values and response to selection. Results Through theoretical derivations and simulations, we showed that the total genetic variance can be estimated from pooled data, but the underlying direct and indirect genetic (co)variances cannot. Moreover, we showed that the most accurate estimates are obtained when group members belong to the same family. Additional theoretical derivations and data analyses on survival records showed that the total genetic variance and breeding values can be estimated from pooled data. Moreover, the correlation between the estimated total breeding values obtained from individual and pooled data was surprisingly

  1. Functional analysis of variance for association studies.

    PubMed

    Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Greenwood, Mark C; Wei, Changshuai; Lu, Qing

    2014-01-01

    While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA) method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1) it tests for a joint effect of gene variants, including both common and rare; (2) it fully utilizes linkage disequilibrium and genetic position information; and (3) allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods - SKAT and a previously proposed method based on functional linear models (FLM), - especially if a sample size of a study is small and/or sequence variants have low to moderate effects. We conduct an empirical study by applying three methods (FANOVA, SKAT and FLM) to sequencing data from Dallas Heart Study. While SKAT and FLM respectively detected ANGPTL 4 and ANGPTL 3 associated with obesity, FANOVA was able to identify both genes associated with obesity.

  2. The quantum Allan variance

    NASA Astrophysics Data System (ADS)

    Chabuda, Krzysztof; Leroux, Ian D.; Demkowicz-Dobrzański, Rafał

    2016-08-01

    The instability of an atomic clock is characterized by the Allan variance, a measure widely used to describe the noise of frequency standards. We provide an explicit method to find the ultimate bound on the Allan variance of an atomic clock in the most general scenario where N atoms are prepared in an arbitrarily entangled state and arbitrary measurement and feedback are allowed, including those exploiting coherences between succeeding interrogation steps. While the method is rigorous and general, it becomes numerically challenging for large N and long averaging times.

  3. Conversations across Meaning Variance

    ERIC Educational Resources Information Center

    Cordero, Alberto

    2013-01-01

    Progressive interpretations of scientific theories have long been denounced as naive, because of the inescapability of meaning variance. The charge reportedly applies to recent realist moves that focus on theory-parts rather than whole theories. This paper considers the question of what "theory-parts" of epistemic significance (if any) relevantly…

  4. Genetic variance contributes to dopamine and opioid receptor antagonist-induced inhibition of intralipid (fat) intake in inbred and outbred mouse strains.

    PubMed

    Dym, Cheryl T; Bae, Veronica S; Kraft, Tamar; Yakubov, Yakov; Winn, Amanda; Sclafani, Anthony; Bodnar, Richard J

    2010-02-26

    Preference for and intake of solid and emulsified fat (intralipid) solutions vary across different mouse strains. Fat intake in rodents is inhibited by dopamine and opioid receptor antagonists, but any variation in these responses as a function of genetic background is unknown. Therefore, the present study compared the ability of dopamine D1-like (SCH23390) and general opioid (naltrexone) receptor antagonism to alter intake of fat emulsions (intralipid) in mice. Two-hour intakes of 5% intralipid were measured (5-120 min) in seven inbred (BALB/c, C57BL/6, C57BL/10, DBA/2, SJL, SWR, 129P3) and one outbred (CD-1) mouse strains following treatment with vehicle, SCH23390 (50-1600 nmol/kg, ip) and naltrexone (0.001-5 mg/kg, sc). SCH23390 significantly, dose-dependently and differentially reduced intralipid intake at all five (DBA/2, SWR, CD-1), four (SJL, C57BL/6), three (129P3) and one (C57BL/10) of the doses tested, but failed to affect intralipid intake in BALB/c mice. Naltrexone significantly, dose-dependently and differentially reduced intralipid intake at all four (DBA/2), three (SWR, SJL), two (CD-1, C57BL/10) and one (C57BL/6, 129P3) of the doses tested, and also failed to affect intralipid intake in BALB/cJ mice. SCH23390 and naltrexone were respectively 13.3-fold and 9.3-fold more potent in inhibiting intralipid intake in the most sensitive (DBA/2) relative to the least sensitive (BALB/c) mouse strains. A strong positive relationship (r=0.91) was observed for the abilities of SCH23390 and naltrexone to inhibit intralipid intake across strains. These findings indicate that dopaminergic and opioid signaling mechanisms differentially control intralipid intake across different mouse strains, suggesting important genetic and pharmacological interactions in the short-term control of rewarding and post-ingestive consequences of fat intake.

  5. Toxicological safety assessment of genetically modified Bacillus thuringiensis with additional N-acyl homoserine lactonase gene.

    PubMed

    Peng, Donghai; Zhou, Chenfei; Chen, Shouwen; Ruan, Lifang; Yu, Ziniu; Sun, Ming

    2008-01-01

    The aim of the present study is to evaluate the toxicology safety to mammals of a genetically modified (GM) Bacillus thuringiensis with an additional N-acyl homoserine lactones gene (aiiA), which possesses insecticidal activity together with restraint of bacterial pathogenicity and is intended for use as a multifunctional biopesticide. Safety assessments included an acute oral toxicity test and 28-d animal feeding study in Wistar rats, primary eye and dermal irritation in Zealand White rabbits, and delayed contact hypersensitivity in guinea pigs. Tests were conducted using spray-dried powder preparation. This GM product showed toxicity neither in oral acute toxicity test nor in 28-d animal feeding test at a dose of 5,000 mg/kg body weight. During the animal feeding test, there were no significant differences in growth, food and water consumption, hematology, blood biochemical indices, organ weights, and histopathology finding between rats in controls and tested groups. Tested animals in primary eye and dermal irritation and delayed contact hypersensitivity test were also devoid of any toxicity compared to controls. All the above results demonstrated that the GM based multifunctional B. thuringiensis has low toxicity and low eye and dermal irritation and would not cause hypersensitivity to laboratory mammals and therefore could be regarded as safe for use as a pesticide.

  6. Genetic variance in the HIV-1 founder virus Vpr affects its ability to induce cell cycle G₂arrest and cell apoptosis.

    PubMed

    Jianyuan, Zhao; Jiwei, Ding; Zeyun, Mi; Jinming, Zhou; Tao, Wei; Shan, Cen

    2015-05-01

    In the event of acute infection, only a few HIV-1 viral variants can establish the initial productive clinical infection, and these viral variants are known as transmitted/founder viruses (T/F viruses). As one of the accessory proteins of HIV-1, viral protein R (Vpr) plays an important role in viral replication. Therefore, the characterization of T/F virus Vpr is beneficial to understand how virus replicates in a new host. In this study, flow cytometry was used to analyze the effect of G₂arrest and cell apoptosis induced by the T/F virus Vpr and the chronic strain MJ4 Vpr. The results showed that the ability of T/F virus ZM246 Vpr and ZM247 Vpr inducing G₂arrest and cell apoptosis are more potent than the MJ4 Vpr. The comparison of protein sequences indicated that the amino acids of 77, 85 and 94 contain high freqency mutations, suggesting that these sites may be involved in inducing G₂arrest and cell apoptosis. Taken together, our work suggests that in acute infections, T/F viruses increase the capacity of G₂arrest and cell apoptosis and promote viral replication and transmission in a new host by Vpr genetic mutation.

  7. Decomposing variation in male reproductive success: age-specific variances and covariances through extra-pair and within-pair reproduction.

    PubMed

    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

  8. [Questions safety and tendency of using genetically modified microorganisms in food, food additives and food derived].

    PubMed

    Khovaev, A A

    2008-01-01

    In this article analysis questions of using genetically modified microorganisms in manufacture food production, present new GMM used in manufacture -food ferments; results of medical biological appraisal/ microbiological and genetic expert examination/ of food, getting by use microorganisms or there producents with indication modern of control methods.

  9. Spectral Ambiguity of Allan Variance

    NASA Technical Reports Server (NTRS)

    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.

  10. Variance Decomposition Using an IRT Measurement Model

    PubMed Central

    Glas, Cees A. W.; Boomsma, Dorret I.

    2007-01-01

    Large scale research projects in behaviour genetics and genetic epidemiology are often based on questionnaire or interview data. Typically, a number of items is presented to a number of subjects, the subjects’ sum scores on the items are computed, and the variance of sum scores is decomposed into a number of variance components. This paper discusses several disadvantages of the approach of analysing sum scores, such as the attenuation of correlations amongst sum scores due to their unreliability. It is shown that the framework of Item Response Theory (IRT) offers a solution to most of these problems. We argue that an IRT approach in combination with Markov chain Monte Carlo (MCMC) estimation provides a flexible and efficient framework for modelling behavioural phenotypes. Next, we use data simulation to illustrate the potentially huge bias in estimating variance components on the basis of sum scores. We then apply the IRT approach with an analysis of attention problems in young adult twins where the variance decomposition model is extended with an IRT measurement model. We show that when estimating an IRT measurement model and a variance decomposition model simultaneously, the estimate for the heritability of attention problems increases from 40% (based on sum scores) to 73%. PMID:17534709

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. The genetic architecture of fitness in a seed beetle: assessing the potential for indirect genetic benefits of female choice

    PubMed Central

    2008-01-01

    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) for F1 productivity. We

  13. Genotypic-specific variance in Caenorhabditis elegans lifetime fecundity

    PubMed Central

    Diaz, S Anaid; Viney, Mark

    2014-01-01

    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. PMID:25360248

  14. Nominal analysis of "variance".

    PubMed

    Weiss, David J

    2009-08-01

    Nominal responses are the natural way for people to report actions or opinions. Because nominal responses do not generate numerical data, they have been underutilized in behavioral research. On those occasions in which nominal responses are elicited, the responses are customarily aggregated over people or trials so that large-sample statistics can be employed. A new analysis is proposed that directly associates differences among responses with particular sources in factorial designs. A pair of nominal responses either matches or does not; when responses do not match, they vary. That analogue to variance is incorporated in the nominal analysis of "variance" (NANOVA) procedure, wherein the proportions of matches associated with sources play the same role as do sums of squares in an ANOVA. The NANOVA table is structured like an ANOVA table. The significance levels of the N ratios formed by comparing proportions are determined by resampling. Fictitious behavioral examples featuring independent groups and repeated measures designs are presented. A Windows program for the analysis is available.

  15. Double decomposition: decomposing the variance in subcomponents of male extra-pair reproductive success.

    PubMed

    Losdat, Sylvain; Arcese, Peter; Reid, Jane M

    2015-09-01

    1. Extra-pair reproductive success (EPRS) is a key component of male fitness in socially monogamous systems and could cause selection on female extra-pair reproduction if extra-pair offspring (EPO) inherit high value for EPRS from their successful extra-pair fathers. However, EPRS is itself a composite trait that can be fully decomposed into subcomponents of variation, each of which can be further decomposed into genetic and environmental variances. However, such decompositions have not been implemented in wild populations, impeding evolutionary inference. 2. We first show that EPRS can be decomposed into the product of three life-history subcomponents: the number of broods available to a focal male to sire EPO, the male's probability of siring an EPO in an available brood and the number of offspring in available broods. This decomposition of EPRS facilitates estimation from field data because all subcomponents can be quantified from paternity data without need to quantify extra-pair matings. Our decomposition also highlights that the number of available broods, and hence population structure and demography, might contribute substantially to variance in male EPRS and fitness. 3. We then used 20 years of complete genetic paternity and pedigree data from wild song sparrows (Melospiza melodia) to partition variance in each of the three subcomponents of EPRS, and thereby estimate their additive genetic variance and heritability conditioned on effects of male coefficient of inbreeding, age and social status. 4. All three subcomponents of EPRS showed some degree of within-male repeatability, reflecting combined permanent environmental and genetic effects. Number of available broods and offspring per brood showed low additive genetic variances. The estimated additive genetic variance in extra-pair siring probability was larger, although the 95% credible interval still converged towards zero. Siring probability also showed inbreeding depression and increased with male age

  16. 29 CFR 2590.702-1 - Additional requirements prohibiting discrimination based on genetic information.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... diabetes. A begins to experience excessive sweating, thirst, and fatigue. A's physician examines A and... adult onset diabetes mellitus (Type 2 diabetes). (ii) Conclusion. In this Example 1, A has been... involved. The diagnosis is not based principally on genetic information. Thus, Type 2 diabetes...

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

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... diabetes. A begins to experience excessive sweating, thirst, and fatigue. A's physician examines A and... adult onset diabetes mellitus (Type 2 diabetes). (ii) Conclusion. In this Example 1, A has been... involved. The diagnosis is not based principally on genetic information. Thus, Type 2 diabetes...

  18. Genetic variation at the TPH2 gene influences impulsivity in addition to eating disorders.

    PubMed

    Slof-Op't Landt, Margarita C T; Bartels, Meike; Middeldorp, Christel M; van Beijsterveldt, Catherina E M; Slagboom, P Eline; Boomsma, Dorret I; van Furth, Eric F; Meulenbelt, Ingrid

    2013-01-01

    Genes are involved in eating disorders (EDs) and self-induced vomiting (SV), a key symptom of different types of EDs. Perfectionism and impulsivity are potential risk factors for EDs. TPH2 (tryptophan hydroxylase 2) SNP rs1473473 was previously associated with anorexia nervosa and EDs characterized by SV. Could perfectionism or impulsivity be underlying the association between rs1473473 and EDs? Genetic association between TPH2 SNP rs1473473 and perfectionism or impulsivity was first evaluated in a random control group (N = 512). The associations obtained in this control group were subsequently tested in a group of patients with an ED (N = 267). The minor allele of rs1473473 (OR = 1.49) was more frequent in impulsive controls, but also in impulsive patients with an ED (OR = 1.83). The largest effect was found in the patients with an ED characterized by SV (OR = 2.51, p = 0.02). Genetic variation at the TPH2 gene appeared to affect impulsivity which, in turn, might predispose to the SV phenotype.

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

    PubMed

    Brazzola, Gregory; Chèvre, Nathalie; Wedekind, Claus

    2014-11-01

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

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

    PubMed Central

    Brazzola, Gregory; Chèvre, Nathalie; Wedekind, Claus

    2014-01-01

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

  1. Decomposing genomic variance using information from GWA, GWE and eQTL analysis.

    PubMed

    Ehsani, A; Janss, L; Pomp, D; Sørensen, P

    2016-04-01

    A commonly used procedure in genome-wide association (GWA), genome-wide expression (GWE) and expression quantitative trait locus (eQTL) analyses is based on a bottom-up experimental approach that attempts to individually associate molecular variants with complex traits. Top-down modeling of the entire set of genomic data and partitioning of the overall variance into subcomponents may provide further insight into the genetic basis of complex traits. To test this approach, we performed a whole-genome variance components analysis and partitioned the genomic variance using information from GWA, GWE and eQTL analyses of growth-related traits in a mouse F2 population. We characterized the mouse trait genetic architecture by ordering single nucleotide polymorphisms (SNPs) based on their P-values and studying the areas under the curve (AUCs). The observed traits were found to have a genomic variance profile that differed significantly from that expected of a trait under an infinitesimal model. This situation was particularly true for both body weight and body fat, for which the AUCs were much higher compared with that of glucose. In addition, SNPs with a high degree of trait-specific regulatory potential (SNPs associated with subset of transcripts that significantly associated with a specific trait) explained a larger proportion of the genomic variance than did SNPs with high overall regulatory potential (SNPs associated with transcripts using traditional eQTL analysis). We introduced AUC measures of genomic variance profiles that can be used to quantify relative importance of SNPs as well as degree of deviation of a trait's inheritance from an infinitesimal model. The shape of the curve aids global understanding of traits: The steeper the left-hand side of the curve, the fewer the number of SNPs controlling most of the phenotypic variance.

  2. Additional studies of sheep haemopexin: genetic control, frequencies and postnatal development.

    PubMed

    Stratil, A; Bobák, P; Margetín, M; Glasnák, V

    1989-01-01

    This study presents evidence that sheep haemopexin phenotypes are genetically controlled by three alleles, HpxA, HpxB1 and HpxB2, of a single autosomal locus. Frequencies of two alleles, HpxA and HpxB (HpxB encompasses two isoalleles, HpxB1 and HpxB2), were studied in eight sheep breeds in Czechoslovakia. The frequency of the HpxA allele was highest (ranging from 0.81 in Merino to 1.0 in East Friesian sheep). Qualitative and quantitative changes in haemopexin during postnatal development were studied by starch gel electrophoresis and rocket immunoelectrophoresis respectively. In electrophoresis, 1- or 2-day-old lambs had two very weak zones corresponding in mobility to two slower zones of adult animals. Later, the third more anodic zone appeared and gradually increased in intensity. In 1-month-old lambs the patterns were practically identical with those of adult animals. Using rocket immunoelectrophoresis, the level of haemopexin shortly after birth was practically zero. It rose sharply till the sixth day of life; then the level continued to rise slowly till about 1 month of age. The mean haemopexin level in adult sheep was 64.5 +/- 18.26 (SD) mg/100ml serum, ranging from 30.5 to 116.5 mg/100ml.

  3. The majority of genetic variation in orangutan personality and subjective well-being is nonadditive.

    PubMed

    Adams, Mark James; King, James E; Weiss, Alexander

    2012-07-01

    The heritability of human personality is well-established. Recent research indicates that nonadditive genetic effects, such as dominance and epistasis, play a large role in personality variation. One possible explanation for the latter finding is that there has been recent selection on human personality. To test this possibility, we estimated additive and nonadditive genetic variance in personality and subjective well-being of zoo-housed orangutans. More than half of the genetic variance in these traits could be attributed to nonadditive genetic effects, modeled as dominance. Subjective well-being had genetic overlap with personality, though less so than has been found in humans or chimpanzees. Since a large portion of nonadditive genetic variance in personality is not unique to humans, the nonadditivity of human personality is not sufficient evidence for recent selection of personality in humans. Nonadditive genetic variance may be a general feature of the genetic structure of personality in primates and other animals.

  4. The population genetic theory of hidden variation and genetic robustness.

    PubMed

    Hermisson, Joachim; Wagner, Günter P

    2004-12-01

    One of the most solid generalizations of transmission genetics is that the phenotypic variance of populations carrying a major mutation is increased relative to the wild type. At least some part of this higher variance is genetic and due to release of previously hidden variation. Similarly, stressful environments also lead to the expression of hidden variation. These two observations have been considered as evidence that the wild type has evolved robustness against genetic variation, i.e., genetic canalization. In this article we present a general model for the interaction of a major mutation or a novel environment with the additive genetic basis of a quantitative character under stabilizing selection. We introduce an approximation to the genetic variance in mutation-selection-drift balance that includes the previously used stochastic Gaussian and house-of-cards approximations as limiting cases. We then show that the release of hidden genetic variation is a generic property of models with epistasis or genotype-environment interaction, regardless of whether the wild-type genotype is canalized or not. As a consequence, the additive genetic variance increases upon a change in the environment or the genetic background even if the mutant character state is as robust as the wild-type character. Estimates show that this predicted increase can be considerable, in particular in large populations and if there are conditionally neutral alleles at the loci underlying the trait. A brief review of the relevant literature suggests that the assumptions of this model are likely to be generic for polygenic traits. We conclude that the release of hidden genetic variance due to a major mutation or environmental stress does not demonstrate canalization of the wild-type genotype.

  5. Sampling Errors of Variance Components.

    ERIC Educational Resources Information Center

    Sanders, Piet F.

    A study on sampling errors of variance components was conducted within the framework of generalizability theory by P. L. Smith (1978). The study used an intuitive approach for solving the problem of how to allocate the number of conditions to different facets in order to produce the most stable estimate of the universe score variance. Optimization…

  6. Variance estimation for nucleotide substitution models.

    PubMed

    Chen, Weishan; Wang, Hsiuying

    2015-09-01

    The current variance estimators for most evolutionary models were derived when a nucleotide substitution number estimator was approximated with a simple first order Taylor expansion. In this study, we derive three variance estimators for the F81, F84, HKY85 and TN93 nucleotide substitution models, respectively. They are obtained using the second order Taylor expansion of the substitution number estimator, the first order Taylor expansion of a squared deviation and the second order Taylor expansion of a squared deviation, respectively. These variance estimators are compared with the existing variance estimator in terms of a simulation study. It shows that the variance estimator, which is derived using the second order Taylor expansion of a squared deviation, is more accurate than the other three estimators. In addition, we also compare these estimators with an estimator derived by the bootstrap method. The simulation shows that the performance of this bootstrap estimator is similar to the estimator derived by the second order Taylor expansion of a squared deviation. Since the latter one has an explicit form, it is more efficient than the bootstrap estimator.

  7. A general unified framework to assess the sampling variance of heritability estimates using pedigree or marker-based relationships.

    PubMed

    Visscher, Peter M; Goddard, Michael E

    2015-01-01

    Heritability is a population parameter of importance in evolution, plant and animal breeding, and human medical genetics. It can be estimated using pedigree designs and, more recently, using relationships estimated from markers. We derive the sampling variance of the estimate of heritability for a wide range of experimental designs, assuming that estimation is by maximum likelihood and that the resemblance between relatives is solely due to additive genetic variation. We show that well-known results for balanced designs are special cases of a more general unified framework. For pedigree designs, the sampling variance is inversely proportional to the variance of relationship in the pedigree and it is proportional to 1/N, whereas for population samples it is approximately proportional to 1/N(2), where N is the sample size. Variation in relatedness is a key parameter in the quantification of the sampling variance of heritability. Consequently, the sampling variance is high for populations with large recent effective population size (e.g., humans) because this causes low variation in relationship. However, even using human population samples, low sampling variance is possible with high N.

  8. Direct and indirect genetic and fine-scale location effects on breeding date in song sparrows.

    PubMed

    Germain, Ryan R; Wolak, Matthew E; Arcese, Peter; Losdat, Sylvain; Reid, Jane M

    2016-11-01

    Quantifying direct and indirect genetic effects of interacting females and males on variation in jointly expressed life-history traits is central to predicting microevolutionary dynamics. However, accurately estimating sex-specific additive genetic variances in such traits remains difficult in wild populations, especially if related individuals inhabit similar fine-scale environments. Breeding date is a key life-history trait that responds to environmental phenology and mediates individual and population responses to environmental change. However, no studies have estimated female (direct) and male (indirect) additive genetic and inbreeding effects on breeding date, and estimated the cross-sex genetic correlation, while simultaneously accounting for fine-scale environmental effects of breeding locations, impeding prediction of microevolutionary dynamics. We fitted animal models to 38 years of song sparrow (Melospiza melodia) phenology and pedigree data to estimate sex-specific additive genetic variances in breeding date, and the cross-sex genetic correlation, thereby estimating the total additive genetic variance while simultaneously estimating sex-specific inbreeding depression. We further fitted three forms of spatial animal model to explicitly estimate variance in breeding date attributable to breeding location, overlap among breeding locations and spatial autocorrelation. We thereby quantified fine-scale location variances in breeding date and quantified the degree to which estimating such variances affected the estimated additive genetic variances. The non-spatial animal model estimated nonzero female and male additive genetic variances in breeding date (sex-specific heritabilities: 0·07 and 0·02, respectively) and a strong, positive cross-sex genetic correlation (0·99), creating substantial total additive genetic variance (0·18). Breeding date varied with female, but not male inbreeding coefficient, revealing direct, but not indirect, inbreeding

  9. Genetic evidence for an additional function of phage T4 gene 32 protein: interaction with ligase.

    PubMed

    Mosig, G; Breschkin, A M

    1975-04-01

    Gene 32 of bacteriophage T4 is essential for DNA replication, recombination, and repair. In an attempt to clarify the role of the corresponding gene product, we have looked for mutations that specifically inactivate one but not all of its functions and for compensating suppressor mutations in other genes. Here we describe a gene 32 ts mutant that does not produce progeny, but in contrast to an am mutant investigated by others, is capable of some primary and secondary DNA replication and of forming "joint" recombinational intermediates after infection of Escherichia coli B at the restrictive temperature. However, parental and progeny DNA strands are not ligated to covalently linked "recombinant" molecules, and single strands of vegetative DNA do not exceed unit length. Progeny production as well as capacity for covalent linkage in this gene 32 ts mutant are partially restored by additional rII mutations. Suppression by rII depends on functioning host ligase [EC 6.5.1.2; poly(deoxyribonucleotide):poly(deoxyribonucleotide) ligase (AMP-forming, NMN-forming)]. This gene 32 ts mutation (unlike some others) in turn suppresses the characteristic plaque morphology of rII mutants. We conclude that gene 32 protein, in addition to its role in DNA replication and in the formation of "joint" recombinational intermediates, interacts with T4 ligase [EC 6.5.1.1; poly(deoxyribonucleotide):poly(deoxyribonucleotide) ligase (AMP-forming)] when recombining DNA strands are covalently linked. The protein of the mutant that we describe here is mainly defective in this interaction, thus inactivating T4 ligase in recombination. Suppressing rII mutations facilitate substitution of host ligase. There is suggestive evidence that these interactions occur at the membrane.

  10. Integrating Variances into an Analytical Database

    NASA Technical Reports Server (NTRS)

    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.

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

    PubMed Central

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

    2015-01-01

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

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

    SciTech Connect

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

    1989-08-01

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

  13. Selection enhanced estimates of µ-calpain, calpastatin, and dacylglycerol O-acyltransferase 1 genetic effects on pre-weaning performance, carcass quality traits, and residual variance of tenderness in composite ... cattle

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Selection of the composite MARC III population for markers allowed better estimates of effects and inheritance of markers for targeted carcass quality traits (n=254) and nontargeted traits and an evaluation of SNP specific residual variance models for tenderness. Genotypic effects of CAPN1 haplotyp...

  14. Molecular basis of inherited antithrombin deficiency in Portuguese families: identification of genetic alterations and screening for additional thrombotic risk factors.

    PubMed

    David, Dezsö; Ribeiro, Sofia; Ferrão, Lénia; Gago, Teresa; Crespo, Francisco

    2004-06-01

    Antithrombin (AT), the most important coagulation serine proteases inhibitor, plays an important role in maintaining the hemostatic balance. Inherited AT deficiency, mainly characterized by predisposition to recurrent venous thromboembolism, is transmitted in an autosomal dominant manner. In this study, we analyzed the underlying genetic alterations in 12 unrelated Portuguese thrombophilic families with AT deficiency. At the same time, the modulating effect of the FV Leiden mutation, PT 20210A, PAI-1 4G, and MTHFR 677T allelic variants, on the thrombotic risk of AT deficient patients was also evaluated. Three novel frameshift alterations, a 4-bp deletion in exon 4 and two 1-bp insertions in exon 6, were identified in six unrelated type I AT deficient families. A novel missense mutation in exon 3a, which changes the highly conserved F147 residue, and a novel splice site mutation in the invariant acceptor AG dinucleotide of intron 2 were also identified in unrelated type I AT deficient families. In addition to these, two previously reported missense mutations changing the AT reactive site bond (R393-S394) and leading to type II-RS deficiency, and a previously reported cryptic splice site mutation (IVS4-14G-->A), were also identified. In these families, increased thrombotic risk associated with co-inheritance of the FV Leiden mutation and of the PAI-1 4G variant was also observed. In conclusion, we present the first data regarding the underlying genetic alterations in Portuguese thrombophilic families with AT deficiency, and confirm that the FV Leiden mutation and probably the PAI-1 4G variant represent additional thrombotic risk factors in these families.

  15. Response to selection in finite locus models with non-additive effects.

    PubMed

    Esfandyari, Hadi; Henryon, Mark; Berg, Peer; Thomasen, Jorn Rind; Bijma, Piter; Sørensen, Anders Christian

    2017-01-12

    Under the finite-locus model in the absence of mutation, the additive genetic variation is expected to decrease when directional selection is acting on a population, according to quantitative-genetic theory. However, some theoretical studies of selection suggest that the level of additive variance can be sustained or even increased when non-additive genetic effects are present. We tested the hypothesis that finite-locus models with both additive and non-additive genetic effects maintain more additive genetic variance (V_A) and realize larger medium-to-long term genetic gains than models with only additive effects when the trait under selection is subject to truncation selection. Four genetic models that included additive, dominance, and additive-by-additive epistatic effects were simulated. The simulated genome for individuals consisted of 25 chromosomes, each with a length of 1M. One hundred bi-allelic QTL, four on each chromosome, were considered. In each generation, 100 sires and 100 dams were mated, producing five progeny per mating. The population was selected for a single trait (h(2)=0.1) for 100 discrete generations with selection on phenotype or BLUP-EBV. V_A decreased with directional truncation selection even in presence of non-additive genetic effects. Non-additive effects influenced long-term response to selection and among genetic models additive gene action had highest response to selection. In addition, in all genetic models, BLUP-EBV resulted in a greater fixation of favourable and unfavourable alleles and higher response than phenotypic selection. In conclusion, for the schemes we simulated, the presence of non-additive genetic effects had little effect in changes of additive variance and V_A decreased by directional selection.

  16. Genetics

    MedlinePlus

    ... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...

  17. VPSim: Variance propagation by simulation

    SciTech Connect

    Burr, T.; Coulter, C.A.; Prommel, J.

    1997-12-01

    One of the fundamental concepts in a materials control and accountability system for nuclear safeguards is the materials balance (MB). All transfers into and out of a material balance area are measured, as are the beginning and ending inventories. The resulting MB measures the material loss, MB = T{sub in} + I{sub B} {minus} T{sub out} {minus} I{sub E}. To interpret the MB, the authors must estimate its measurement error standard deviation, {sigma}{sub MB}. When feasible, they use a method usually known as propagation of variance (POV) to estimate {sigma}{sub MB}. The application of POV for estimating the measurement error variance of an MB is straightforward but tedious. By applying POV to individual measurement error standard deviations they can estimate {sigma}{sub MB} (or more generally, they can estimate the variance-covariance matrix, {Sigma}, of a sequence of MBs). This report describes a new computer program (VPSim) that uses simulation to estimate the {Sigma} matrix of a sequence of MBs. Given the proper input data, VPSim calculates the MB and {sigma}{sub MB}, or calculates a sequence of n MBs and the associated n-by-n covariance matrix, {Sigma}. The covariance matrix, {Sigma}, contains the variance of each MB in the diagonal entries and the covariance between pairs of MBs in the off-diagonal entries.

  18. Analysis of Variance: Variably Complex

    ERIC Educational Resources Information Center

    Drummond, Gordon B.; Vowler, Sarah L.

    2012-01-01

    These authors have previously described how to use the "t" test to compare two groups. In this article, they describe the use of a different test, analysis of variance (ANOVA) to compare more than two groups. ANOVA is a test of group differences: do at least two of the means differ from each other? ANOVA assumes (1) normal distribution…

  19. The Effect of an Experimental Bottleneck upon Quantitative Genetic Variation in the Housefly

    PubMed Central

    Bryant, Edwin H.; McCommas, Steven A.; Combs, Lisa M.

    1986-01-01

    Effects of a population bottleneck (founder-flush cycle) upon quantitative genetic variation of morphometric traits were examined in replicated experimental lines of the housefly founded with one, four or 16 pairs of flies. Heritability and additive genetic variances for eight morphometric traits generally increased as a result of the bottleneck, but the pattern of increase among bottleneck sizes differed among traits. Principal axes of the additive genetic correlation matrix for the control line yielded two suites of traits, one associated with general body size and another set largely independent of body size. In the former set containing five of the traits, additive genetic variance was greatest in the bottleneck size of four pairs, whereas in the latter set of two traits the largest additive genetic variance occurred in the smallest bottleneck size of one pair. One trait exhibited changes in additive genetic variance intermediate between these two major responses. These results were inconsistent with models of additive effects of alleles within loci or of additive effects among loci. An observed decline in viability measures and body size in the bottleneck lines also indicated that there was nonadditivity of allelic effects for these traits. Several possible nonadditive models were explored that increased additive genetic variance as a result of a bottleneck. These included a model with complete dominance, a model with overdominance and a model incorporating multiplicative epistasis. PMID:17246359

  20. Environmental and genetic effects on early growth traits in Moghani sheep breeds.

    PubMed

    Lavvaf, A; Noshary, A; Keshtkaran, A

    2007-08-01

    The effects of environmental factors on early growth traits (birth weight, weaning weight, body weight at 6 months of age and daily gain from birth to weaning and weaning to 6 months of age) using 10432 records in Moghani sheep breed were studied and Genetic and Environmental variance component were estimated using 8468 records of Jafarabad Animal Breeding Station from 1999 to 2004. Birth year on all traits and dam age had significant effect only for birth and weaning weight. Sex of lambs and birth type had no significant effect only daily gain from weaning to 6 months of age. Additive genetic direct variance, maternal environmental variance and heritability were estimate by REML fitting two different Animal models. The estimate of maternal environment variance was higher than additive genetic direct variance in some traits. Estimates of direct heritability for all traits were low.

  1. Variance decomposition in stochastic simulators

    SciTech Connect

    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.

  2. Estimating the Modified Allan Variance

    NASA Technical Reports Server (NTRS)

    Greenhall, Charles

    1995-01-01

    The third-difference approach to modified Allan variance (MVAR) leads to a tractable formula for a measure of MVAR estimator confidence, the equivalent degrees of freedom (edf), in the presence of power-law phase noise. The effect of estimation stride on edf is tabulated. A simple approximation for edf is given, and its errors are tabulated. A theorem allowing conservative estimates of edf in the presence of compound noise processes is given.

  3. Relating the Hadamard Variance to MCS Kalman Filter Clock Estimation

    NASA Technical Reports Server (NTRS)

    Hutsell, Steven T.

    1996-01-01

    The Global Positioning System (GPS) Master Control Station (MCS) currently makes significant use of the Allan Variance. This two-sample variance equation has proven excellent as a handy, understandable tool, both for time domain analysis of GPS cesium frequency standards, and for fine tuning the MCS's state estimation of these atomic clocks. The Allan Variance does not explicitly converge for the nose types of alpha less than or equal to minus 3 and can be greatly affected by frequency drift. Because GPS rubidium frequency standards exhibit non-trivial aging and aging noise characteristics, the basic Allan Variance analysis must be augmented in order to (a) compensate for a dynamic frequency drift, and (b) characterize two additional noise types, specifically alpha = minus 3, and alpha = minus 4. As the GPS program progresses, we will utilize a larger percentage of rubidium frequency standards than ever before. Hence, GPS rubidium clock characterization will require more attention than ever before. The three sample variance, commonly referred to as a renormalized Hadamard Variance, is unaffected by linear frequency drift, converges for alpha is greater than minus 5, and thus has utility for modeling noise in GPS rubidium frequency standards. This paper demonstrates the potential of Hadamard Variance analysis in GPS operations, and presents an equation that relates the Hadamard Variance to the MCS's Kalman filter process noises.

  4. Additive genetic variation in resistance of Nile tilapia (Oreochromis niloticus) to Streptococcus iniae and S. agalactiae capsular type Ib: is genetic resistance correlated?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Streptococcus (S.) iniae and S. agalactiae are both economically important Gram positive bacterial pathogens affecting the globally farmed tilapia (Oreochromis spp.). Historically control of these bacteria in tilapia culture has included biosecurity, therapeutants and vaccination strategies. Genet...

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

    PubMed

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

    2016-06-01

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

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

    PubMed

    Holmans, Peter; Moskvina, Valentina; Jones, Lesley; Sharma, Manu; Vedernikov, Alexey; Buchel, Finja; Saad, Mohamad; Sadd, Mohamad; Bras, Jose M; Bettella, Francesco; Nicolaou, Nayia; Simón-Sánchez, Javier; Mittag, Florian; Gibbs, J Raphael; Schulte, Claudia; Durr, Alexandra; Guerreiro, Rita; Hernandez, Dena; Brice, Alexis; Stefánsson, Hreinn; Majamaa, Kari; Gasser, Thomas; Heutink, Peter; Wood, Nicholas W; Martinez, Maria; Singleton, Andrew B; Nalls, Michael A; Hardy, John; Morris, Huw R; Williams, Nigel M

    2013-03-01

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

  7. The evolution and consequences of sex-specific reproductive variance.

    PubMed

    Mullon, Charles; Reuter, Max; Lehmann, Laurent

    2014-01-01

    Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction.

  8. The Evolution and Consequences of Sex-Specific Reproductive Variance

    PubMed Central

    Mullon, Charles; Reuter, Max; Lehmann, Laurent

    2014-01-01

    Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction. PMID:24172130

  9. Estimating the Modified Allan Variance

    NASA Technical Reports Server (NTRS)

    Greenhall, Charles

    1995-01-01

    A paper at the 1992 FCS showed how to express the modified Allan variance (mvar) in terms of the third difference of the cumulative sum of time residuals. Although this reformulated definition was presented merely as a computational trick for simplifying the calculation of mvar estimates, it has since turned out to be a powerful theoretical tool for deriving the statistical quality of those estimates in terms of their equivalent degrees of freedom (edf), defined for an estimator V by edf V = 2(EV)2/(var V). Confidence intervals for mvar can then be constructed from levels of the appropriate 2 distribution.

  10. Mitral disc-valve variance

    PubMed Central

    Berroya, Renato B.; Escano, Fernando B.

    1972-01-01

    This report deals with a rare complication of disc-valve prosthesis in the mitral area. A significant disc poppet and struts destruction of mitral Beall valve prostheses occurred 20 and 17 months after implantation. The resulting valve incompetence in the first case contributed to the death of the patient. The durability of Teflon prosthetic valves appears to be in question and this type of valve probably will be unacceptable if there is an increasing number of disc-valve variance in the future. Images PMID:5017573

  11. µ-Calpain, calpastatin, and growth hormone receptor genetic effects on preweaning performance, carcass quality traits, and residual variance of tenderness in Angus cattle selected to increase minor haplotype ... frequencies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic marker effects and interactions are estimated with poor precision when minor marker allele frequencies are low. An Angus population was subjected to marker assisted selection for multiple years to increase divergent haplotype and minor marker allele frequencies to 1) estimate effect size an...

  12. A Wavelet Perspective on the Allan Variance.

    PubMed

    Percival, Donald B

    2016-04-01

    The origins of the Allan variance trace back 50 years ago to two seminal papers, one by Allan (1966) and the other by Barnes (1966). Since then, the Allan variance has played a leading role in the characterization of high-performance time and frequency standards. Wavelets first arose in the early 1980s in the geophysical literature, and the discrete wavelet transform (DWT) became prominent in the late 1980s in the signal processing literature. Flandrin (1992) briefly documented a connection between the Allan variance and a wavelet transform based upon the Haar wavelet. Percival and Guttorp (1994) noted that one popular estimator of the Allan variance-the maximal overlap estimator-can be interpreted in terms of a version of the DWT now widely referred to as the maximal overlap DWT (MODWT). In particular, when the MODWT is based on the Haar wavelet, the variance of the resulting wavelet coefficients-the wavelet variance-is identical to the Allan variance when the latter is multiplied by one-half. The theory behind the wavelet variance can thus deepen our understanding of the Allan variance. In this paper, we review basic wavelet variance theory with an emphasis on the Haar-based wavelet variance and its connection to the Allan variance. We then note that estimation theory for the wavelet variance offers a means of constructing asymptotically correct confidence intervals (CIs) for the Allan variance without reverting to the common practice of specifying a power-law noise type a priori. We also review recent work on specialized estimators of the wavelet variance that are of interest when some observations are missing (gappy data) or in the presence of contamination (rogue observations or outliers). It is a simple matter to adapt these estimators to become estimators of the Allan variance. Finally we note that wavelet variances based upon wavelets other than the Haar offer interesting generalizations of the Allan variance.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. Genetic and environmental components of phenotypic variation in immune response and body size of a colonial bird, Delichon urbica (the house martin).

    PubMed

    Christe, P; Moller, A P; Saino, N; De Lope, F

    2000-07-01

    Directional selection for parasite resistance is often intense in highly social host species. Using a partial cross-fostering experiment we studied environmental and genetic variation in immune response and morphology in a highly colonial bird species, the house martin (Delichon urbica). We manipulated intensity of infestation of house martin nests by the haematophagous parasitic house martin bug Oeciacus hirundinis either by spraying nests with a weak pesticide or by inoculating them with 50 bugs. Parasitism significantly affected tarsus length, T cell response, immunoglobulin and leucocyte concentrations. We found evidence of strong environmental effects on nestling body mass, body condition, wing length and tarsus length, and evidence of significant additive genetic variance for wing length and haematocrit. We found significant environmental variance, but no significant additive genetic variance in immune response parameters such as T cell response to the antigenic phytohemagglutinin, immunoglobulins, and relative and absolute numbers of leucocytes. Environmental variances were generally greater than additive genetic variances, and the low heritabilities of phenotypic traits were mainly a consequence of large environmental variances and small additive genetic variances. Hence, highly social bird species such as the house martin, which are subject to intense selection by parasites, have a limited scope for immediate microevolutionary response to selection because of low heritabilities, but also a limited scope for long-term response to selection because evolvability as indicated by small additive genetic coefficients of variation is weak.

  15. Warped functional analysis of variance.

    PubMed

    Gervini, Daniel; Carter, Patrick A

    2014-09-01

    This article presents an Analysis of Variance model for functional data that explicitly incorporates phase variability through a time-warping component, allowing for a unified approach to estimation and inference in presence of amplitude and time variability. The focus is on single-random-factor models but the approach can be easily generalized to more complex ANOVA models. The behavior of the estimators is studied by simulation, and an application to the analysis of growth curves of flour beetles is presented. Although the model assumes a smooth latent process behind the observed trajectories, smootheness of the observed data is not required; the method can be applied to irregular time grids, which are common in longitudinal studies.

  16. Direct and maternal (co)variance components and heritability estimates for body weights in Chokla sheep.

    PubMed

    Kushwaha, B P; Mandal, A; Arora, A L; Kumar, R; Kumar, S; Notter, D R

    2009-08-01

    Estimates of (co)variance components were obtained for weights at birth, weaning and 6, 9 and 12 months of age in Chokla sheep maintained at the Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India, over a period of 21 years (1980-2000). Records of 2030 lambs descended from 150 rams and 616 ewes were used in the study. Analyses were carried out by restricted maximum likelihood (REML) fitting an animal model and ignoring or including maternal genetic or permanent environmental effects. Six different animal models were fitted for all traits. The best model was chosen after testing the improvement of the log-likelihood values. Direct heritability estimates were inflated substantially for all traits when maternal effects were ignored. Heritability estimates for weight at birth, weaning and 6, 9 and 12 months of age were 0.20, 0.18, 0.16, 0.22 and 0.23, respectively in the best models. Additive maternal and maternal permanent environmental effects were both significant at birth, accounting for 9% and 12% of phenotypic variance, respectively, but the source of maternal effects (additive versus permanent environmental) at later ages could not be clearly identified. The estimated repeatabilities across years of ewe effects on lamb body weights were 0.26, 0.14, 0.12, 0.13, and 0.15 at birth, weaning, 6, 9 and 12 months of age, respectively. These results indicate that modest rates of genetic progress are possible for all weights.

  17. Speed Variance and Its Influence on Accidents.

    ERIC Educational Resources Information Center

    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…

  18. Multivariate Granger causality and generalized variance

    NASA Astrophysics Data System (ADS)

    Barrett, Adam B.; Barnett, Lionel; Seth, Anil K.

    2010-04-01

    Granger causality analysis is a popular method for inference on directed interactions in complex systems of many variables. A shortcoming of the standard framework for Granger causality is that it only allows for examination of interactions between single (univariate) variables within a system, perhaps conditioned on other variables. However, interactions do not necessarily take place between single variables but may occur among groups or “ensembles” of variables. In this study we establish a principled framework for Granger causality in the context of causal interactions among two or more multivariate sets of variables. Building on Geweke’s seminal 1982 work, we offer additional justifications for one particular form of multivariate Granger causality based on the generalized variances of residual errors. Taken together, our results support a comprehensive and theoretically consistent extension of Granger causality to the multivariate case. Treated individually, they highlight several specific advantages of the generalized variance measure, which we illustrate using applications in neuroscience as an example. We further show how the measure can be used to define “partial” Granger causality in the multivariate context and we also motivate reformulations of “causal density” and “Granger autonomy.” Our results are directly applicable to experimental data and promise to reveal new types of functional relations in complex systems, neural and otherwise.

  19. Multivariate Granger causality and generalized variance.

    PubMed

    Barrett, Adam B; Barnett, Lionel; Seth, Anil K

    2010-04-01

    Granger causality analysis is a popular method for inference on directed interactions in complex systems of many variables. A shortcoming of the standard framework for Granger causality is that it only allows for examination of interactions between single (univariate) variables within a system, perhaps conditioned on other variables. However, interactions do not necessarily take place between single variables but may occur among groups or "ensembles" of variables. In this study we establish a principled framework for Granger causality in the context of causal interactions among two or more multivariate sets of variables. Building on Geweke's seminal 1982 work, we offer additional justifications for one particular form of multivariate Granger causality based on the generalized variances of residual errors. Taken together, our results support a comprehensive and theoretically consistent extension of Granger causality to the multivariate case. Treated individually, they highlight several specific advantages of the generalized variance measure, which we illustrate using applications in neuroscience as an example. We further show how the measure can be used to define "partial" Granger causality in the multivariate context and we also motivate reformulations of "causal density" and "Granger autonomy." Our results are directly applicable to experimental data and promise to reveal new types of functional relations in complex systems, neural and otherwise.

  20. Increasing selection response by Bayesian modeling of heterogeneous environmental variances

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Heterogeneity of environmental variance among genotypes reduces selection response because genotypes with higher variance are more likely to be selected than low-variance genotypes. Modeling heterogeneous variances to obtain weighted means corrected for heterogeneous variances is difficult in likel...

  1. Estimation of genetic parameters and environmental factors on early growth traits for Lori breed sheep using single trait animal model.

    PubMed

    Lavvaf, A; Noshary, A

    2008-01-01

    The effects of different environmental factors and estimation of genetic parameters on early growth traits for Lori breed sheep including birth weight, weaning weight and body weight at 6 months of age using 19960 records from 35 herds of Lorestan Jahad Agriculture Organization were studied in the cities of Aleshtar, Khorramabad and Poldokhtar from 1995 to 2003. The effect of herd, sex of lambs, dam age and birth year on all traits and birth type had significant effect only on weaning weight. Different single trait animal models estimated the components of direct additive genetic variance, maternal genetic variance and maternal permanent environment variance through restricted maximum likelihood using environmental factors as a fixe effect and different random effects. The results showed that direct additive genetic effect had additionally significant effect on all traits moreover maternal additive genetic and maternal permanent environment effects. Results also revealed that the maternal permanent environment variance for all traits is higher than maternal genetic variance. Also the direct heritability for all traits was higher than maternal heritability. Estimation of the direct heritability from the birth to 6 months of age showed a reducing trend that could arise from high dependence of birth and weaning weight on maternal environment conditions as compared with the age conditions afterward. The genetic assessment of growth traits in Lori breed sheep without inclusion of maternal effect in animal model causes decreased selection accuracy and incorrect genetic assessment of the lambs.

  2. Restricted sample variance reduces generalizability.

    PubMed

    Lakes, Kimberley D

    2013-06-01

    One factor that affects the reliability of observed scores is restriction of range on the construct measured for a particular group of study participants. This study illustrates how researchers can use generalizability theory to evaluate the impact of restriction of range in particular sample characteristics on the generalizability of test scores and to estimate how changes in measurement design could improve the generalizability of the test scores. An observer-rated measure of child self-regulation (Response to Challenge Scale; Lakes, 2011) is used to examine scores for 198 children (Grades K through 5) within the generalizability theory (GT) framework. The generalizability of ratings within relatively developmentally homogeneous samples is examined and illustrates the effect of reduced variance among ratees on generalizability. Forecasts for g coefficients of various D study designs demonstrate how higher generalizability could be achieved by increasing the number of raters or items. In summary, the research presented illustrates the importance of and procedures for evaluating the generalizability of a set of scores in a particular research context.

  3. Genetic parameters and trends in the Chilean multibreed dairy cattle population.

    PubMed

    Elzo, M A; Jara, A; Barria, N

    2004-05-01

    Estimates of additive and nonadditive multibreed co-variance components, genetic parameters, and predicted genetic values for first lactation 305-d mature equivalent (ME) milk yield, fat yield, and protein yield were computed using data from a sample of 3316 cows from the Chilean Holstein-other breeds multibreed population. Variances and covariances were estimated by 2-trait REML analyses using a Generalized Expectation-Maximization algorithm applied to multibreed populations. Multiple estimates of additive genetic, nonadditive genetic, and environmental variances from 2-trait analyses were averaged to yield a single variance estimate for each trait and effect. Heritabilities were moderate for all traits in Holstein, other, and Holstein x other crossbred groups. Interbreed interactibilities (ratio of nonadditive genetic to phenotypic variances) were all near zero. Multibreed additive, nonadditive, and total genetic trends were estimated using the complete dataset (56,277 cows). Upward trends between 1990 and 2000 existed for all traits, genetic effects, and breed groups, except for 305-d ME protein yield in 1/4 Holstein, indicating that Chilean dairy producers were successful in choosing progressively better semen and sires from imported and local sources over time.

  4. Genetic structure of spatial and verbal working memory.

    PubMed

    Ando, J; Ono, Y; Wright, M J

    2001-11-01

    Working memory (WM) encompasses both short-term memory (storage) and executive functions that play an essential role in all forms of cognition. In this study, the genetic structure of storage and executive functions engaged in both a spatial and verbal WM span task is investigated using a twin sample. The sample consists of 143 monozygotic (MZ) and 93 dizygotic (DZ) Japanese twin pairs, ages 16 to 29 years. In 155 (87 MZ, 62 DZ) of these pairs, cognitive ability scores from the Kyodai Japanese IQ test are also obtained. The phenotypic relationship between WM and cognitive ability is confirmed (r = 0.26-0.44). Individual differences in WM storage and executive functions are found to be significantly influenced by genes, with heritability estimates all moderately high (43%-49%), and estimates for cognitive ability comparable to previous studies (65%). A large part of the genetic variance in storage and executive functions in both spatial and verbal modalities is due to a common genetic factor that accounts for 11% to 43% of the variance. In the reduced sample, this common genetic factor accounts for 64% and 26% of the variance in spatial and verbal cognitive ability, respectively. Additional genetic variance in WM (7%-30%) is due to modality specific factors (spatial and verbal) and a storage specific factor that may be particularly important for the verbal modality. None of the variance in cognitive ability is accounted for by the modality and storage genetic factors, suggesting these may be specific to WM.

  5. Genetics

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. Genetics

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Familial resemblance of borderline personality disorder features: genetic or cultural transmission?

    PubMed

    Distel, Marijn A; Rebollo-Mesa, Irene; Willemsen, Gonneke; Derom, Catherine A; Trull, Timothy J; Martin, Nicholas G; Boomsma, Dorret I

    2009-01-01

    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.

  8. Genetic influences on adolescent eating habits.

    PubMed

    Beaver, Kevin M; Flores, Tori; Boutwell, Brian B; Gibson, Chris L

    2012-04-01

    Behavioral genetic research shows that variation in eating habits and food consumption is due to genetic and environmental factors. The current study extends this line of research by examining the genetic contribution to adolescent eating habits. Analysis of sibling pairs drawn from the National Longitudinal Study of Adolescent Health (Add Health) revealed significant genetic influences on variance in an unhealthy eating habits scale (h(2) = .42), a healthy eating habits scale (h(2) = .51), the number of meals eaten at a fast-food restaurant (h(2) = .33), and the total number of meals eaten per week (h(2) = .26). Most of the remaining variance was due to nonshared environmental factors. Additional analyses conducted separately for males and females revealed a similar pattern of findings. The authors note the limitations of the study and offer suggestions for future research.

  9. Plants with genetically modified events combined by conventional breeding: an assessment of the need for additional regulatory data.

    PubMed

    Pilacinski, W; Crawford, A; Downey, R; Harvey, B; Huber, S; Hunst, P; Lahman, L K; MacIntosh, S; Pohl, M; Rickard, C; Tagliani, L; Weber, N

    2011-01-01

    Crop varieties with multiple GM events combined by conventional breeding have become important in global agriculture. The regulatory requirements in different countries for such products vary considerably, placing an additional burden on regulatory agencies in countries where the submission of additional data is required and delaying the introduction of innovative products to meet agricultural needs. The process of conventional plant breeding has predictably provided safe food and feed products both historically and in the modern era of plant breeding. Thus, previously approved GM events that have been combined by conventional plant breeding and contain GM traits that are not likely to interact in a manner affecting safety should be considered to be as safe as their conventional counterparts. Such combined GM event crop varieties should require little, if any, additional regulatory data to meet regulatory requirements.

  10. 40 CFR 59.106 - Variance.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated...

  11. 40 CFR 59.106 - Variance.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated...

  12. 40 CFR 59.106 - Variance.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated...

  13. 40 CFR 59.106 - Variance.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated...

  14. 40 CFR 59.106 - Variance.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated...

  15. Analysis of variance components of testcross progenies in an autotetraploid species and consequences for recurrent selection with a tester.

    PubMed

    Gallais, A

    1992-01-01

    For autotetraploid species the development of the concept of test value (value in testcross) leads to a simple description of the variance among testcross progenies. When defining directly genetic effects at the level of the value of the progenies, there is no contribution of triand tetragenic interactions. To estimate additive and dominance variances it is only necessary to have the population of progenies structured in half-sib or full-sib families; it is then possible to determine the presence of epistasis using a two-way mating design. When the theory of recurrent selection is applied dominance variance can be neglected for the prediction of genetic advance in one cycle as well for the development of combined selection when progenies are structured in families. The results are similar to those for diploids with two-locus epistasis. The more efficient scheme consists of the development of pair-crossing in off-season generations (for intercrossing) and simultaneous crossing of each plant to the tester. In comparison to the classical scheme, the relative efficiency of such a scheme is 41%. The use of combined selection will further increase this superiority.

  16. Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

    PubMed Central

    Yadav, Anupama; Dhole, Kaustubh

    2016-01-01

    Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets. PMID:28172852

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

    PubMed

    Moreira, X; Zas, R; Sampedro, L

    2013-05-01

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

  18. Mitochondrial genetic effects on latent class variables associated with susceptibility to alcoholism.

    PubMed

    Lease, Loren R; Winnier, Deidre A; Williams, Jeff T; Dyer, Thomas D; Almasy, Laura; Mahaney, Michael C

    2005-12-30

    We report the results of statistical genetic analyses of data from the Collaborative Study on the Genetics of Alcoholism prepared for the Genetic Analysis Workshop 14 to detect and characterize maternally inherited mitochondrial genetic effects on variation in latent class psychiatric/behavioral variables employed in the diagnosis of alcoholism. Using published extensions to variance decomposition methods for statistical genetic analysis of continuous and discrete traits we: 1) estimated the proportion of the variance in each trait due to the effects of mitochondrial DNA (mtDNA), 2) tested for pleiotropy, both mitochondrial genetic and residual additive genetic, between trait pairs, and 3) evaluated whether the simultaneous estimation of mitochondrial genetic effects on these traits improves our ability to detect and localize quantitative trait loci (QTL) in the nuclear genome. After correction for multiple testing, we find significant (p < 0.009) mitochondrial genetic contributions to the variance for two latent class variables. Although we do detect significant residual additive genetic correlations between the two traits, there is no evidence of a residual mitochondrial genetic correlation between them. Evidence for autosomal QTL for these traits is improved when linkage screens are conditioned on significant mitochondrial genetic effects. We conclude that mitochondrial genes may contribute to variation in some latent class psychiatric/behavioral variables associated with alcoholism.

  19. Variance Design and Air Pollution Control

    ERIC Educational Resources Information Center

    Ferrar, Terry A.; Brownstein, Alan B.

    1975-01-01

    Air pollution control authorities were forced to relax air quality standards during the winter of 1972 by granting variances. This paper examines the institutional characteristics of these variance policies from an economic incentive standpoint, sets up desirable structural criteria for institutional design and arrives at policy guidelines for…

  20. 10 CFR 1022.16 - Variances.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 4 2012-01-01 2012-01-01 false Variances. 1022.16 Section 1022.16 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) COMPLIANCE WITH FLOODPLAIN AND WETLAND ENVIRONMENTAL REVIEW REQUIREMENTS Procedures for Floodplain and Wetland Reviews § 1022.16 Variances. (a) Emergency actions. DOE may...

  1. 10 CFR 1022.16 - Variances.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 4 2014-01-01 2014-01-01 false Variances. 1022.16 Section 1022.16 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) COMPLIANCE WITH FLOODPLAIN AND WETLAND ENVIRONMENTAL REVIEW REQUIREMENTS Procedures for Floodplain and Wetland Reviews § 1022.16 Variances. (a) Emergency actions. DOE may...

  2. 10 CFR 1022.16 - Variances.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Variances. 1022.16 Section 1022.16 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) COMPLIANCE WITH FLOODPLAIN AND WETLAND ENVIRONMENTAL REVIEW REQUIREMENTS Procedures for Floodplain and Wetland Reviews § 1022.16 Variances. (a) Emergency actions. DOE may...

  3. 10 CFR 1022.16 - Variances.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 4 2011-01-01 2011-01-01 false Variances. 1022.16 Section 1022.16 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) COMPLIANCE WITH FLOODPLAIN AND WETLAND ENVIRONMENTAL REVIEW REQUIREMENTS Procedures for Floodplain and Wetland Reviews § 1022.16 Variances. (a) Emergency actions. DOE may...

  4. 10 CFR 1022.16 - Variances.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 10 Energy 4 2013-01-01 2013-01-01 false Variances. 1022.16 Section 1022.16 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) COMPLIANCE WITH FLOODPLAIN AND WETLAND ENVIRONMENTAL REVIEW REQUIREMENTS Procedures for Floodplain and Wetland Reviews § 1022.16 Variances. (a) Emergency actions. DOE may...

  5. 40 CFR 142.41 - Variance request.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of...

  6. 40 CFR 142.41 - Variance request.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of...

  7. 40 CFR 142.41 - Variance request.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of...

  8. Portfolio optimization with mean-variance model

    NASA Astrophysics Data System (ADS)

    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.

  9. Estimation of Epistatic Variance Components and Heritability in Founder Populations and Crosses

    PubMed Central

    Young, Alexander I.; Durbin, Richard

    2014-01-01

    Genetic association studies have explained only a small proportion of the estimated heritability of complex traits, leaving the remaining heritability “missing.” Genetic interactions have been proposed as an explanation for this, because they lead to overestimates of the heritability and are hard to detect. Whether this explanation is true depends on the proportion of variance attributable to genetic interactions, which is difficult to measure in outbred populations. Founder populations exhibit a greater range of kinship than outbred populations, which helps in fitting the epistatic variance. We extend classic theory to founder populations, giving the covariance between individuals due to epistasis of any order. We recover the classic theory as a limit, and we derive a recently proposed estimator of the narrow sense heritability as a corollary. We extend the variance decomposition to include dominance. We show in simulations that it would be possible to estimate the variance from pairwise interactions with samples of a few thousand from strongly bottlenecked human founder populations, and we provide an analytical approximation of the standard error. Applying these methods to 46 traits measured in a yeast (Saccharomyces cerevisiae) cross, we estimate that pairwise interactions explain 10% of the phenotypic variance on average and that third- and higher-order interactions explain 14% of the phenotypic variance on average. We search for third-order interactions, discovering an interaction that is shared between two traits. Our methods will be relevant to future studies of epistatic variance in founder populations and crosses. PMID:25326236

  10. Variance Assistance Document: Land Disposal Restrictions Treatability Variances and Determinations of Equivalent Treatment

    EPA Pesticide Factsheets

    This document provides assistance to those seeking to submit a variance request for LDR treatability variances and determinations of equivalent treatment regarding the hazardous waste land disposal restrictions program.

  11. Portfolio optimization using median-variance approach

    NASA Astrophysics Data System (ADS)

    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.

  12. Neural field theory with variance dynamics.

    PubMed

    Robinson, P A

    2013-06-01

    Previous neural field models have mostly been concerned with prediction of mean neural activity and with second order quantities such as its variance, but without feedback of second order quantities on the dynamics. Here the effects of feedback of the variance on the steady states and adiabatic dynamics of neural systems are calculated using linear neural field theory to estimate the neural voltage variance, then including this quantity in the total variance parameter of the nonlinear firing rate-voltage response function, and thus into determination of the fixed points and the variance itself. The general results further clarify the limits of validity of approaches with and without inclusion of variance dynamics. Specific applications show that stability against a saddle-node bifurcation is reduced in a purely cortical system, but can be either increased or decreased in the corticothalamic case, depending on the initial state. Estimates of critical variance scalings near saddle-node bifurcation are also found, including physiologically based normalizations and new scalings for mean firing rate and the position of the bifurcation.

  13. Variance estimation for stratified propensity score estimators.

    PubMed

    Williamson, E J; Morley, R; Lucas, A; Carpenter, J R

    2012-07-10

    Propensity score methods are increasingly used to estimate the effect of a treatment or exposure on an outcome in non-randomised studies. We focus on one such method, stratification on the propensity score, comparing it with the method of inverse-probability weighting by the propensity score. The propensity score--the conditional probability of receiving the treatment given observed covariates--is usually an unknown probability estimated from the data. Estimators for the variance of treatment effect estimates typically used in practice, however, do not take into account that the propensity score itself has been estimated from the data. By deriving the asymptotic marginal variance of the stratified estimate of treatment effect, correctly taking into account the estimation of the propensity score, we show that routinely used variance estimators are likely to produce confidence intervals that are too conservative when the propensity score model includes variables that predict (cause) the outcome, but only weakly predict the treatment. In contrast, a comparison with the analogous marginal variance for the inverse probability weighted (IPW) estimator shows that routinely used variance estimators for the IPW estimator are likely to produce confidence intervals that are almost always too conservative. Because exact calculation of the asymptotic marginal variance is likely to be complex, particularly for the stratified estimator, we suggest that bootstrap estimates of variance should be used in practice.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-10-03

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

  16. Measurement of Allan variance and phase noise at fractions of a millihertz

    NASA Technical Reports Server (NTRS)

    Conroy, Bruce L.; Le, Duc

    1990-01-01

    Although the measurement of Allan variance of oscillators is well documented, there is a need for a simplified system for finding the degradation of phase noise and Allan variance step-by-step through a system. This article describes an instrumentation system for simultaneous measurement of additive phase noise and degradation in Allan variance through a transmitter system. Also included are measurements of a 20-kW X-band transmitter showing the effect of adding a pass tube regulator.

  17. Marker-Based Estimates Reveal Significant Non-additive Effects in Clonally Propagated Cassava (Manihot esculenta): Implications for the Prediction of Total Genetic Value and the Selection of Varieties.

    PubMed

    Wolfe, Marnin D; Kulakow, Peter; Rabbi, Ismail Y; Jannink, Jean-Luc

    2016-08-31

    In clonally propagated crops, non-additive genetic effects can be effectively exploited by the identification of superior genetic individuals as varieties. Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop that feeds hundreds of millions. We quantified the amount and nature of non-additive genetic variation for three key traits in a breeding population of cassava from sub-Saharan Africa using additive and non-additive genome-wide marker-based relationship matrices. We then assessed the accuracy of genomic prediction for total (additive plus non-additive) genetic value. We confirmed previous findings based on diallel populations, that non-additive genetic variation is significant for key cassava traits. Specifically, we found that dominance is particularly important for root yield and epistasis contributes strongly to variation in CMD resistance. Further, we showed that total genetic value predicted observed phenotypes more accurately than additive only models for root yield but not for dry matter content, which is mostly additive or for CMD resistance, which has high narrow-sense heritability. We address the implication of these results for cassava breeding and put our work in the context of previous results in cassava, and other plant and animal species.

  18. Reducing variance in batch partitioning measurements

    SciTech Connect

    Mariner, Paul E.

    2010-08-11

    The partitioning experiment is commonly performed with little or no attention to reducing measurement variance. Batch test procedures such as those used to measure K{sub d} values (e.g., ASTM D 4646 and EPA402 -R-99-004A) do not explain how to evaluate measurement uncertainty nor how to minimize measurement variance. In fact, ASTM D 4646 prescribes a sorbent:water ratio that prevents variance minimization. Consequently, the variance of a set of partitioning measurements can be extreme and even absurd. Such data sets, which are commonplace, hamper probabilistic modeling efforts. An error-savvy design requires adjustment of the solution:sorbent ratio so that approximately half of the sorbate partitions to the sorbent. Results of Monte Carlo simulations indicate that this simple step can markedly improve the precision and statistical characterization of partitioning uncertainty.

  19. 78 FR 14122 - Revocation of Permanent Variances

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-04

    ... Occupational Safety and Health Administration Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA), Labor. ACTION: Notice of revocation. SUMMARY: With this notice, OSHA is... into consideration these newly corrected cross references. DATES: The effective date of the...

  20. 40 CFR 59.206 - Variances.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who...

  1. 40 CFR 59.206 - Variances.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who...

  2. 40 CFR 59.206 - Variances.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who...

  3. 40 CFR 59.206 - Variances.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who...

  4. 40 CFR 59.206 - Variances.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who...

  5. Sex reduces genetic variation: a multidisciplinary review.

    PubMed

    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.

  6. Phonocardiographic diagnosis of aortic ball variance.

    PubMed

    Hylen, J C; Kloster, F E; Herr, R H; Hull, P Q; Ames, A W; Starr, A; Griswold, H E

    1968-07-01

    Fatty infiltration causing changes in the silastic poppet of the Model 1000 series Starr-Edwards aortic valve prostheses (ball variance) has been detected with increasing frequency and can result in sudden death. Phonocardiograms were recorded on 12 patients with ball variance confirmed by operation and of 31 controls. Ten of the 12 patients with ball variance were distinguished from the controls by an aortic opening sound (AO) less than half as intense as the aortic closure sound (AC) at the second right intercostal space (AO/AC ratio less than 0.5). Both AO and AC were decreased in two patients with ball variance, with the loss of the characteristic high frequency and amplitude of these sounds. The only patient having a diminished AO/AC ratio (0.42) without ball variance at reoperation had a clot extending over the aortic valve struts. The phonocardiographic findings have been the most reliable objective evidence of ball variance in patients with Starr-Edwards aortic prosthesis of the Model 1000 series.

  7. Quantitative Genetics of the Aging of Reproductive Traits in the Houbara Bustard

    PubMed Central

    Chantepie, Stéphane; Robert, Alexandre; Sorci, Gabriele; Hingrat, Yves; Charmantier, Anne; Leveque, Gwénaëlle; Lacroix, Frédéric; Teplitsky, Céline

    2015-01-01

    Do all traits within an organism age for the same reason? Evolutionary theories of aging share a common assumption: the strength of natural selection declines with age. A corollary is that additive genetic variance should increase with age. However, not all senescent traits display such increases suggesting that other mechanisms may be at play. Using longitudinal data collected from more than 5400 houbara bustards (Chlamydotis undulata) with an exhaustive recorded pedigree, we investigated the genetics of aging in one female reproductive trait (egg production) and three male reproductive traits (courtship display rate, ejaculate size and sperm viability), that display senescence at the phenotypic level. Animal models revealed an increase in additive genetic variance with age for courtship display rate and egg production but an unexpected absence of increased additive genetic variance for ejaculate size and no additive genetic variance for sperm viability. Our results suggest that the mechanisms behind the senescence of some traits are linked with a change in genetic expression, whereas for some other traits, aging may result from the constraints associated with physiological wear and tear on the organism throughout the life of the individual. PMID:26218735

  8. Quantitative Genetics of the Aging of Reproductive Traits in the Houbara Bustard.

    PubMed

    Chantepie, Stéphane; Robert, Alexandre; Sorci, Gabriele; Hingrat, Yves; Charmantier, Anne; Leveque, Gwénaëlle; Lacroix, Frédéric; Teplitsky, Céline

    2015-01-01

    Do all traits within an organism age for the same reason? Evolutionary theories of aging share a common assumption: the strength of natural selection declines with age. A corollary is that additive genetic variance should increase with age. However, not all senescent traits display such increases suggesting that other mechanisms may be at play. Using longitudinal data collected from more than 5400 houbara bustards (Chlamydotis undulata) with an exhaustive recorded pedigree, we investigated the genetics of aging in one female reproductive trait (egg production) and three male reproductive traits (courtship display rate, ejaculate size and sperm viability), that display senescence at the phenotypic level. Animal models revealed an increase in additive genetic variance with age for courtship display rate and egg production but an unexpected absence of increased additive genetic variance for ejaculate size and no additive genetic variance for sperm viability. Our results suggest that the mechanisms behind the senescence of some traits are linked with a change in genetic expression, whereas for some other traits, aging may result from the constraints associated with physiological wear and tear on the organism throughout the life of the individual.

  9. Doppler variance imaging for three-dimensional retina and choroid angiography

    NASA Astrophysics Data System (ADS)

    Yu, Lingfeng; Chen, Zhongping

    2010-01-01

    We demonstrate the use of Doppler variance (standard deviation) imaging for 3-D in vivo angiography in the human eye. In addition to the regular optical Doppler tomography velocity and structural images, we use the variance of blood flow velocity to map the retina and choroid vessels. Variance imaging is subject to bulk motion artifacts as in phase-resolved Doppler imaging, and a histogram-based method is proposed for bulk-motion correction in variance imaging. Experiments were performed to demonstrate the effectiveness of the proposed method for 3-D vasculature imaging of human retina and choroid.

  10. Methods to Estimate the Between-Study Variance and Its Uncertainty in Meta-Analysis

    ERIC Educational Resources Information Center

    Veroniki, Areti Angeliki; Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian P. T.; Langan, Dean; Salanti, Georgia

    2016-01-01

    Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance,…

  11. On Studying Common Factor Variance in Multiple-Component Measuring Instruments

    ERIC Educational Resources Information Center

    Raykov, Tenko; Pohl, Steffi

    2013-01-01

    A method for examining common factor variance in multiple-component measuring instruments is outlined. The procedure is based on an application of the latent variable modeling methodology and is concerned with evaluating observed variance explained by a global factor and by one or more additional component-specific factors. The approach furnishes…

  12. The phenotypic and genetic covariance structure of drosphilid wings.

    PubMed

    McGuigan, Katrina; Blows, Mark W

    2007-04-01

    Evolutionary constraint results from the interaction between the distribution of available genetic variation and the position of selective optima. The availability of genetic variance in multitrait systems, as described by the additive genetic variance-covariance matrix (G), has been the subject of recent attempts to assess the prevalence of genetic constraints. However, evolutionary constraints have not yet been considered from the perspective of the phenotypes available to multivariate selection, and whether genetic variance is present in all phenotypes potentially under selection. Determining the rank of the phenotypic variance-covariance matrix (P) to characterize the phenotypes available to selection, and contrasting it with the rank of G, may provide a general approach to determining the prevalence of genetic constraints. In a study of a laboratory population of Drosophila bunnanda from northern Australia we applied factor-analytic modeling to repeated measures of individual wing phenotypes to determine the dimensionality of the phenotypic space described by P. The phenotypic space spanned by the 10 wing traits had 10 statistically supported dimensions. In contrast, factor-analytic modeling of G estimated for the same 10 traits from a paternal half-sibling breeding design suggested G had fewer dimensions than traits. Statistical support was found for only five and two genetic dimensions, describing a total of 99% and 72% of genetic variance in wing morphology in females and males, respectively. The observed mismatch in dimensionality between P and G suggests that although selection might act to shift the intragenerational population mean toward any trait combination, evolution may be restricted to fewer dimensions.

  13. [Genetic and epigenetic mechanisms in obesity].

    PubMed

    Hinney, A; Herrfurth, N; Schonnop, L; Volckmar, A-L

    2015-02-01

    Obesity is a relevant medical problem. Around 60 % of German adults are overweight, 20 % are obese. The hereditary contribution to the variance of body weight is high. Nevertheless, molecular genetic studies have as yet explained only a small part of the inter-individual variability in the body mass index (BMI). Monogenic forms of obesity, in which loss of a single gene product leads to extreme obesity, are very infrequent. Variance of body weight is commonly explained by a complex interplay of many genetic variants (polygenic obesity). Each variant contributes only a small amount to the body weight. Currently, the largest published analysis of individuals of European origin identified 32 genetic variations (single nucleotide polymorphisms, SNPs) associated with BMI (obesity). Overall, these polygenic obesity variants only explain about 5 % of the variance of the BMI. In addition to the DNA variants epigenetic factors seem to also play a role in body weight regulation. These epigenetic marks can change in the course of life. They might provide an interface between genetic and environmental influences. It is conceivable that in future it will be possible to use epigenetic and genetic markers to detect a predisposition for obesity and to improve prevention and therapy.

  14. Discrimination of frequency variance for tonal sequences.

    PubMed

    Byrne, Andrew J; Viemeister, Neal F; Stellmack, Mark A

    2014-12-01

    Real-world auditory stimuli are highly variable across occurrences and sources. The present study examined the sensitivity of human listeners to differences in global stimulus variability. In a two-interval, forced-choice task, variance discrimination was measured using sequences of five 100-ms tone pulses. The frequency of each pulse was sampled randomly from a distribution that was Gaussian in logarithmic frequency. In the non-signal interval, the sampled distribution had a variance of σSTAN (2), while in the signal interval, the variance of the sequence was σSIG (2) (with σSIG (2) >  σSTAN (2)). The listener's task was to choose the interval with the larger variance. To constrain possible decision strategies, the mean frequency of the sampling distribution of each interval was randomly chosen for each presentation. Psychometric functions were measured for various values of σSTAN (2). Although the performance was remarkably similar across listeners, overall performance was poorer than that of an ideal observer (IO) which perfectly compares interval variances. However, like the IO, Weber's Law behavior was observed, with a constant ratio of ( σSIG (2)- σSTAN (2)) to σSTAN (2) yielding similar performance. A model which degraded the IO with a frequency-resolution noise and a computational noise provided a reasonable fit to the real data.

  15. Estimation of genetic parameters and genetic changes for growth characteristics of Santa Ines sheep.

    PubMed

    Aguirre, E L; Mattos, E C; Eler, J P; Barreto Neto, A D; Ferraz, J B

    2016-08-19

    Studying genetic parameters and genetic changes in Santa Ines sheep is important, because it is the commonest breed in Brazil. This study obtained genetic data from 37,735 pedigree records of lambs over 12 years (2003-2014) from 33 flocks in 10 Brazilian States; 11,851 records of performance were available. (Co)variance components, genetic parameters and breeding values estimates were obtained by derivative-free restricted maximum likelihood in a univariate analysis that included maternal additive genetic and maternal permanent environmental effects. Birth weight, weaning weight, weight at 180 days of age, weight at 270 days of age, average daily weight gain in the following states: from birth to weaning, from weaning to 6 months, from 6 months to 9 months, and from weaning to 9 months; presence of hair in fur and leg muscularity were assessed. (Co)variance component values increased in the weight traits with age. A significant maternal effect was found in the pre-weaned stage that decreased in the post-weaned stage. High values were estimated for the maternal permanent environmental effect, possibly because of the extensive grassland that was available. High total heritability values were estimated for all of the traits evaluated. Significant, positive correlations were found between direct and maternal additive genetic traits with a gradual decrease as the lambs gained independence from their mothers. The genetic trends observed were irregular and incremental. Significant genetic variance suggests that direct selection for pre-weaning traits results in indirect selection of maternal abilities, and individual selection of any post-weaning trait results in rapid genetic improvement.

  16. Genetics and intelligence differences: five special findings.

    PubMed

    Plomin, R; Deary, I J

    2015-02-01

    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 architecture

  17. Variance in binary stellar population synthesis

    NASA Astrophysics Data System (ADS)

    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.

  18. Monitoring Impact of a Pesticide Treatment on Bacterial Soil Communities by Metabolic and Genetic Fingerprinting in Addition to Conventional Testing Procedures

    PubMed Central

    Engelen, Bert; Meinken, Kristin; von Wintzingerode, Friedrich; Heuer, Holger; Malkomes, Hans-Peter; Backhaus, Horst

    1998-01-01

    Herbogil (dinoterb), a reference herbicide, the mineral oil Oleo (paraffin oil used as an additive to herbicides), and Goltix (metamitron) were taken as model compounds for the study of impacts on microbial soil communities. After the treatment of soil samples, effects on metabolic sum parameters were determined by monitoring substrate-induced respiration (SIR) and dehydrogenase activity, as well as carbon and nitrogen mineralization. These conventional ecotoxicological testing procedures are used in pesticide registration. Inhibition of biomass-related activities and stimulation of nitrogen mineralization were the most significant effects caused by the application of Herbogil. Even though Goltix and Oleo were used at a higher dosage (10 times higher), the application of Goltix resulted in smaller effects and the additive Oleo was the least-active compound, with minor stimulation of test parameters at later observation times. The results served as a background for investigation of the power of “fingerprinting” methods in microbial ecology. Changes in catabolic activities induced by treatments were analyzed by using the 95 carbon sources provided by the BIOLOG system. Variations in the complex metabolic fingerprints demonstrated inhibition of many catabolic pathways after the application of Herbogil. Again, the effects of the other compounds were expressed at much lower levels and comprised stimulations as well as inhibitions. Testing for significance by a multivariate t test indicated that the sensitivity of this method was similar to the sensitivities of the conventional testing procedures. The variation of sensitive carbon sources, as determined by factor weights at different observation times, indicated the dynamics of the community shift induced by the Herbogil treatment in more detail. DNA extractions from soil resulted in a collection of molecules representing the genetic composition of total bacterial communities. Distinct and highly reproducible

  19. A Simple Algorithm for Approximating Confidence on the Modified Allan Variance and the Time Variance

    NASA Technical Reports Server (NTRS)

    Weiss, Marc A.; Greenhall, Charles A.

    1996-01-01

    An approximating algorithm for computing equvalent degrees of freedom of the Modified Allan Variance and its square root, the Modified Allan Deviation (MVAR and MDEV), and the Time Variance and Time Deviation (TVAR and TDEV) is presented, along with an algorithm for approximating the inverse chi-square distribution.

  20. Genetics of Growth Reaction Norms in Farmed Rainbow Trout

    PubMed Central

    Sae-Lim, Panya; Mulder, Han; Gjerde, Bjarne; Koskinen, Heikki; Lillehammer, Marie; Kause, Antti

    2015-01-01

    Rainbow trout is farmed globally under diverse uncontrollable environments. Fish with low macroenvironmental sensitivity (ES) of growth is important to thrive and grow under these uncontrollable environments. The ES may evolve as a correlated response to selection for growth in one environment when the genetic correlation between ES and growth is nonzero. The aims of this study were to quantify additive genetic variance for ES of body weight (BW), defined as the slope of reaction norm across breeding environment (BE) and production environment (PE), and to estimate the genetic correlation (rg(int, sl)) between BW and ES. To estimate heritable variance of ES, the coheritability of ES was derived using selection index theory. The BW records from 43,040 rainbow trout performing either in freshwater or seawater were analysed using a reaction norm model. High additive genetic variance for ES (9584) was observed, inferring that genetic changes in ES can be expected. The coheritability for ES was either -0.06 (intercept at PE) or -0.08 (intercept at BE), suggesting that BW observation in either PE or BE results in low accuracy of selection for ES. Yet, the rg(int, sl) was negative (-0.41 to -0.33) indicating that selection for BW in one environment is expected to result in more sensitive fish. To avoid an increase of ES while selecting for BW, it is possible to have equal genetic gain in BW in both environments so that ES is maintained stable. PMID:26267268

  1. Genetic variation of individual alpha frequency (IAF) and alpha power in a large adolescent twin sample.

    PubMed

    Smit, Christine M; Wright, Margaret J; Hansell, Narelle K; Geffen, Gina M; Martin, Nicholas G

    2006-08-01

    To further clarify the mode of genetic transmission on individual alpha frequency (IAF) and alpha power, the extent to which individual differences in these alpha indices are influenced by genetic factors were examined in a large sample of adolescent twins (237 MZ, 282 DZ pairs; aged 16). EEG was measured at rest (eyes closed) from the right occipital site, and a second EEG recording for 50 twin pairs obtained approximately 3 months after the initial collection, enabled an estimation of measurement error. Analyses confirmed a strong genetic influence on both IAF (h(2)=0.81) and alpha power (h(2)=0.82), and there was little support for non-additive genetic (dominance) variance. A small but significant negative correlation (-0.18) was found between IAF and alpha power, but genetic influences on IAF and alpha power were largely independent. All non-genetic variance was due to unreliability, with no significant variance attributed to unique environmental factors. Relationships between the alpha and IQ indices were also explored but were generally either non-significant or very low. The findings confirm the high heritability for both IAF and alpha power, they further suggest that the mode of genetic transmission is due to additive genetic factors, that genetic influences on the underlying neural mechanisms of alpha frequency and power are largely specific, and that individual differences in alpha activity are influenced little by developmental plasticity and individual experiences.

  2. Rate of evolutionary change in cranial morphology of the marsupial genus Monodelphis is constrained by the availability of additive genetic variation.

    PubMed

    Porto, A; Sebastião, H; Pavan, S E; VandeBerg, J L; Marroig, G; Cheverud, J M

    2015-04-01

    We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyse the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation.

  3. Testing Interaction Effects without Discarding Variance.

    ERIC Educational Resources Information Center

    Lopez, Kay A.

    Analysis of variance (ANOVA) and multiple regression are two of the most commonly used methods of data analysis in behavioral science research. Although ANOVA was intended for use with experimental designs, educational researchers have used ANOVA extensively in aptitude-treatment interaction (ATI) research. This practice tends to make researchers…

  4. 29 CFR 1920.2 - Variances.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 29 Labor 7 2010-07-01 2010-07-01 false Variances. 1920.2 Section 1920.2 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR (CONTINUED) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR...

  5. 21 CFR 1010.4 - Variances.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... Dockets Management, except for information regarded as confidential under section 537(e) of the act. (d... Management (HFA-305), Food and Drug Administration, 5630 Fishers Lane, rm. 1061, Rockville, MD 20852. (1) The application for variance shall include the following information: (i) A description of the product and...

  6. Formative Use of Intuitive Analysis of Variance

    ERIC Educational Resources Information Center

    Trumpower, David L.

    2013-01-01

    Students' informal inferential reasoning (IIR) is often inconsistent with the normative logic underlying formal statistical methods such as Analysis of Variance (ANOVA), even after instruction. In two experiments reported here, student's IIR was assessed using an intuitive ANOVA task at the beginning and end of a statistics course. In both…

  7. Understanding gender variance in children and adolescents.

    PubMed

    Simons, Lisa K; Leibowitz, Scott F; Hidalgo, Marco A

    2014-06-01

    Gender variance is an umbrella term used to describe gender identity, expression, or behavior that falls outside of culturally defined norms associated with a specific gender. In recent years, growing media coverage has heightened public awareness about gender variance in childhood and adolescence, and an increasing number of referrals to clinics specializing in care for gender-variant youth have been reported in the United States. Gender-variant expression, behavior, and identity may present in childhood and adolescence in a number of ways, and youth with gender variance have unique health needs. For those experiencing gender dysphoria, or distress encountered by the discordance between biological sex and gender identity, puberty is often an exceptionally challenging time. Pediatric primary care providers may be families' first resource for education and support, and they play a critical role in supporting the health of youth with gender variance by screening for psychosocial problems and health risks, referring for gender-specific mental health and medical care, and providing ongoing advocacy and support.

  8. 10 CFR 1021.343 - Variances.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Variances. 1021.343 Section 1021.343 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) NATIONAL ENVIRONMENTAL POLICY ACT IMPLEMENTING PROCEDURES Implementing... arrangements for emergency actions having significant environmental impacts. DOE shall document,...

  9. 21 CFR 1010.4 - Variances.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... the study was conducted in compliance with the good laboratory practice regulations set forth in part... application for variance shall include the following information: (i) A description of the product and its... equipment, the proposed location of each unit. (viii) Such other information required by regulation or...

  10. Parameterization of Incident and Infragravity Swash Variance

    NASA Astrophysics Data System (ADS)

    Stockdon, H. F.; Holman, R. A.; Sallenger, A. H.

    2002-12-01

    By clearly defining the forcing and morphologic controls of swash variance in both the incident and infragravity frequency bands, we are able to derive a more complete parameterization for extreme runup that may be applicable to a wide range of beach and wave conditions. It is expected that the dynamics of the incident and infragravity bands will have different dependencies on offshore wave conditions and local beach slopes. For example, previous studies have shown that swash variance in the incident band depends on foreshore beach slope while the infragravity variance depends more on a weighted mean slope across the surf zone. Because the physics of each band is parameterized differently, the amount that each frequency band contributes to the total swash variance will vary from site to site and, often, at a single site as the profile configuration changes over time. Using water level time series (measured at the shoreline) collected during nine dynamically different field experiments, we test the expected behavior of both incident and infragravity swash and the contribution each makes to total variance. At the dissipative sites (Iribarren number, \\xi0, <0.3) located in Oregon and the Netherlands, the incident band swash is saturated with respect to offshore wave height. Conversely, on the intermediate and reflective beaches, the amplitudes of both incident and infragravity swash variance grow with increasing offshore wave height. While infragravity band swash at all sites appears to increase linearly with offshore wave height, the magnitudes of the response are somewhat greater on reflective beaches than on dissipative beaches. This means that for the same offshore wave conditions the swash on a steeper foreshore will be larger than that on a more gently sloping foreshore. The potential control of the surf zone slope on infragravity band swash is examined at Duck, North Carolina, (0.3 < \\xi0 < 4.0), where significant differences in the relationship between swash

  11. 42 CFR 456.525 - Request for renewal of variance.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from...

  12. 42 CFR 456.525 - Request for renewal of variance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from...

  13. 42 CFR 456.521 - Conditions for granting variance requests.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from...

  14. 42 CFR 456.521 - Conditions for granting variance requests.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from...

  15. Genetic parameters related to environmental variability of weight traits in a selection experiment for weight gain in mice; signs of correlated canalised response

    PubMed Central

    Ibáñez-Escriche, Noelia; Moreno, Almudena; Nieto, Blanca; Piqueras, Pepa; Salgado, Concepción; Gutiérrez, Juan Pablo

    2008-01-01

    Data from an experimental mice population selected from 18 generations to increase weight gain were used to estimate the genetic parameters associated with environmental variability. The analysis involved three traits: weight at 21 days, weight at 42 days and weight gain between 21 and 42 days. A dataset of 5273 records for males was studied. Data were analysed using Bayesian procedures by comparing the Deviance Information Criterion (DIC) value of two different models: one assuming homogeneous environmental variances and another assuming them as heterogeneous. The model assuming heterogeneity was better in all cases and also showed higher additive genetic variances and lower common environmental variances. The heterogeneity of residual variance was associated with systematic and additive genetic effects thus making reduction by selection possible. Genetic correlations between the additive genetic effects on mean and environmental variance of the traits analysed were always negative, ranging from -0.19 to -0.38. An increase in the heritability of the traits was found when considering the genetic determination of the environmental variability. A suggested correlated canalised response was found in terms of coefficient of variation but it could be insufficient to compensate for the scale effect associated with an increase of the mean. PMID:18400150

  16. Longitudinal variance-components analysis of the Framingham Heart Study data

    PubMed Central

    Macgregor, Stuart; Knott, Sara A; White, Ian; Visscher, Peter M

    2003-01-01

    The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records). In addition to RR, conventional univariate variance component techniques were applied. The traits of interest were BMI, HDLC, total cholesterol, and height. The longitudinal method allowed the characterization of the change in QTL effects with aging. A QTL affecting BMI was shown to act mainly at early ages. PMID:14975090

  17. Longitudinal variance-components analysis of the Framingham Heart Study data.

    PubMed

    Macgregor, Stuart; Knott, Sara A; White, Ian; Visscher, Peter M

    2003-12-31

    The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records). In addition to RR, conventional univariate variance component techniques were applied. The traits of interest were BMI, HDLC, total cholesterol, and height. The longitudinal method allowed the characterization of the change in QTL effects with aging. A QTL affecting BMI was shown to act mainly at early ages.

  18. Modality-Driven Classification and Visualization of Ensemble Variance

    SciTech Connect

    Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

    2016-10-01

    Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.

  19. Dynamic Programming Using Polar Variance for Image Segmentation.

    PubMed

    Rosado-Toro, Jose A; Altbach, Maria I; Rodriguez, Jeffrey J

    2016-10-06

    When using polar dynamic programming (PDP) for image segmentation, the object size is one of the main features used. This is because if size is left unconstrained the final segmentation may include high-gradient regions that are not associated with the object. In this paper, we propose a new feature, polar variance, which allows the algorithm to segment objects of different sizes without the need for training data. The polar variance is the variance in a polar region between a user-selected origin and a pixel we want to analyze. We also incorporate a new technique that allows PDP to segment complex shapes by finding low-gradient regions and growing them. The experimental analysis consisted on comparing our technique with different active contour segmentation techniques on a series of tests. The tests consisted on robustness to additive Gaussian noise, segmentation accuracy with different grayscale images and finally robustness to algorithm-specific parameters. Experimental results show that our technique performs favorably when compared to other segmentation techniques.

  20. Kernel-based variance component estimation and whole-genome prediction of pre-corrected phenotypes and progeny tests for dairy cow health traits

    PubMed Central

    Morota, Gota; Boddhireddy, Prashanth; Vukasinovic, Natascha; Gianola, Daniel; DeNise, Sue

    2014-01-01

    Prediction of complex trait phenotypes in the presence of unknown gene action is an ongoing challenge in animals, plants, and humans. Development of flexible predictive models that perform well irrespective of genetic and environmental architectures is desirable. Methods that can address non-additive variation in a non-explicit manner are gaining attention for this purpose and, in particular, semi-parametric kernel-based methods have been applied to diverse datasets, mostly providing encouraging results. On the other hand, the gains obtained from these methods have been smaller when smoothed values such as estimated breeding value (EBV) have been used as response variables. However, less emphasis has been placed on the choice of phenotypes to be used in kernel-based whole-genome prediction. This study aimed to evaluate differences between semi-parametric and parametric approaches using two types of response variables and molecular markers as inputs. Pre-corrected phenotypes (PCP) and EBV obtained for dairy cow health traits were used for this comparison. We observed that non-additive genetic variances were major contributors to total genetic variances in PCP, whereas additivity was the largest contributor to variability of EBV, as expected. Within the kernels evaluated, non-parametric methods yielded slightly better predictive performance across traits relative to their additive counterparts regardless of the type of response variable used. This reinforces the view that non-parametric kernels aiming to capture non-linear relationships between a panel of SNPs and phenotypes are appealing for complex trait prediction. However, like past studies, the gain in predictive correlation was not large for either PCP or EBV. We conclude that capturing non-additive genetic variation, especially epistatic variation, in a cross-validation framework remains a significant challenge even when it is important, as seems to be the case for health traits in dairy cows. PMID:24715901

  1. Analysis of variance of microarray data.

    PubMed

    Ayroles, Julien F; Gibson, Greg

    2006-01-01

    Analysis of variance (ANOVA) is an approach used to identify differentially expressed genes in complex experimental designs. It is based on testing for the significance of the magnitude of effect of two or more treatments taking into account the variance within and between treatment classes. ANOVA is a highly flexible analytical approach that allows investigators to simultaneously assess the contributions of multiple factors to gene expression variation, including technical (dye, batch) effects and biological (sex, genotype, drug, time) ones, as well as interactions between factors. This chapter provides an overview of the theory of linear mixture modeling and the sequence of steps involved in fitting gene-specific models and discusses essential features of experimental design. Commercial and open-source software for performing ANOVA is widely available.

  2. Analysis of Variance of Multiply Imputed Data.

    PubMed

    van Ginkel, Joost R; Kroonenberg, Pieter M

    2014-01-01

    As a procedure for handling missing data, Multiple imputation consists of estimating the missing data multiple times to create several complete versions of an incomplete data set. All these data sets are analyzed by the same statistical procedure, and the results are pooled for interpretation. So far, no explicit rules for pooling F-tests of (repeated-measures) analysis of variance have been defined. In this paper we outline the appropriate procedure for the results of analysis of variance for multiply imputed data sets. It involves both reformulation of the ANOVA model as a regression model using effect coding of the predictors and applying already existing combination rules for regression models. The proposed procedure is illustrated using three example data sets. The pooled results of these three examples provide plausible F- and p-values.

  3. Systems Engineering Programmatic Estimation Using Technology Variance

    NASA Technical Reports Server (NTRS)

    Mog, Robert A.

    2000-01-01

    Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed on the subsystems and components comprising the system of interest. Technological "return" and "variation" parameters are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.

  4. Systems Engineering Programmatic Estimation Using Technology Variance

    NASA Technical Reports Server (NTRS)

    Mog, Robert A.

    2000-01-01

    Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed oil the subsystems and components comprising the system of interest. Technological "returns" and "variation" parameters, are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.

  5. A multivariate analysis of genetic variation in the advertisement call of the gray treefrog, Hyla versicolor.

    PubMed

    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.

  6. Directional variance analysis of annual rings

    NASA Astrophysics Data System (ADS)

    Kumpulainen, P.; Marjanen, K.

    2010-07-01

    The wood quality measurement methods are of increasing importance in the wood industry. The goal is to produce more high quality products with higher marketing value than is produced today. One of the key factors for increasing the market value is to provide better measurements for increased information to support the decisions made later in the product chain. Strength and stiffness are important properties of the wood. They are related to mean annual ring width and its deviation. These indicators can be estimated from images taken from the log ends by two-dimensional power spectrum analysis. The spectrum analysis has been used successfully for images of pine. However, the annual rings in birch, for example are less distinguishable and the basic spectrum analysis method does not give reliable results. A novel method for local log end variance analysis based on Radon-transform is proposed. The directions and the positions of the annual rings can be estimated from local minimum and maximum variance estimates. Applying the spectrum analysis on the maximum local variance estimate instead of the original image produces more reliable estimate of the annual ring width. The proposed method is not limited to log end analysis only. It is usable in other two-dimensional random signal and texture analysis tasks.

  7. Variance and skewness in the FIRST survey

    NASA Astrophysics Data System (ADS)

    Magliocchetti, M.; Maddox, S. J.; Lahav, O.; Wall, J. V.

    1998-10-01

    We investigate the large-scale clustering of radio sources in the FIRST 1.4-GHz survey by analysing the distribution function (counts in cells). We select a reliable sample from the the FIRST catalogue, paying particular attention to the problem of how to define single radio sources from the multiple components listed. We also consider the incompleteness of the catalogue. We estimate the angular two-point correlation function w(theta), the variance Psi_2 and skewness Psi_3 of the distribution for the various subsamples chosen on different criteria. Both w(theta) and Psi_2 show power-law behaviour with an amplitude corresponding to a spatial correlation length of r_0~10h^-1Mpc. We detect significant skewness in the distribution, the first such detection in radio surveys. This skewness is found to be related to the variance through Psi_3=S_3(Psi_2)^alpha, with alpha=1.9+/-0.1, consistent with the non-linear gravitational growth of perturbations from primordial Gaussian initial conditions. We show that the amplitude of variance and the skewness are consistent with realistic models of galaxy clustering.

  8. Hypothesis exploration with visualization of variance

    PubMed Central

    2014-01-01

    Background The Consortium for Neuropsychiatric Phenomics (CNP) at UCLA was an investigation into the biological bases of traits such as memory and response inhibition phenotypes—to explore whether they are linked to syndromes including ADHD, Bipolar disorder, and Schizophrenia. An aim of the consortium was in moving from traditional categorical approaches for psychiatric syndromes towards more quantitative approaches based on large-scale analysis of the space of human variation. It represented an application of phenomics—wide-scale, systematic study of phenotypes—to neuropsychiatry research. Results This paper reports on a system for exploration of hypotheses in data obtained from the LA2K, LA3C, and LA5C studies in CNP. ViVA is a system for exploratory data analysis using novel mathematical models and methods for visualization of variance. An example of these methods is called VISOVA, a combination of visualization and analysis of variance, with the flavor of exploration associated with ANOVA in biomedical hypothesis generation. It permits visual identification of phenotype profiles—patterns of values across phenotypes—that characterize groups. Visualization enables screening and refinement of hypotheses about variance structure of sets of phenotypes. Conclusions The ViVA system was designed for exploration of neuropsychiatric hypotheses by interdisciplinary teams. Automated visualization in ViVA supports ‘natural selection’ on a pool of hypotheses, and permits deeper understanding of the statistical architecture of the data. Large-scale perspective of this kind could lead to better neuropsychiatric diagnostics. PMID:25097666

  9. Variance Reduction Factor of Nuclear Data for Integral Neutronics Parameters

    SciTech Connect

    Chiba, G. Tsuji, M.; Narabayashi, T.

    2015-01-15

    We propose a new quantity, a variance reduction factor, to identify nuclear data for which further improvements are required to reduce uncertainties of target integral neutronics parameters. Important energy ranges can be also identified with this variance reduction factor. Variance reduction factors are calculated for several integral neutronics parameters. The usefulness of the variance reduction factors is demonstrated.

  10. Applications of non-parametric statistics and analysis of variance on sample variances

    NASA Technical Reports Server (NTRS)

    Myers, R. H.

    1981-01-01

    Nonparametric methods that are available for NASA-type applications are discussed. An attempt will be made here to survey what can be used, to attempt recommendations as to when each would be applicable, and to compare the methods, when possible, with the usual normal-theory procedures that are avavilable for the Gaussion analog. It is important here to point out the hypotheses that are being tested, the assumptions that are being made, and limitations of the nonparametric procedures. The appropriateness of doing analysis of variance on sample variances are also discussed and studied. This procedure is followed in several NASA simulation projects. On the surface this would appear to be reasonably sound procedure. However, difficulties involved center around the normality problem and the basic homogeneous variance assumption that is mase in usual analysis of variance problems. These difficulties discussed and guidelines given for using the methods.

  11. Minimum variance and variance of outgoing quality limit MDS-1(c1, c2) plans

    NASA Astrophysics Data System (ADS)

    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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  13. Left or right? Sources of political orientation: the roles of genetic factors, cultural transmission, assortative mating, and personality.

    PubMed

    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.

  14. Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle

    PubMed Central

    Naserkheil, Masoumeh; Miraie-Ashtiani, Seyed Reza; Nejati-Javaremi, Ardeshir; Son, Jihyun; Lee, Deukhwan

    2016-01-01

    The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran. PMID:26954192

  15. A proxy for variance in dense matching over homogeneous terrain

    NASA Astrophysics Data System (ADS)

    Altena, Bas; Cockx, Liesbet; Goedemé, Toon

    2014-05-01

    variance in intensity, the topography was reconstructed entirely. This indicates that to a large extent interpolation was applied. To assess this amount of interpolation processing is done with imagery which is gradually downgraded. Through linking these products with the variance indicator (SNR) this results in a quantitative relation of the interpolation influence onto the topography estimation in respect to contrast. Our proposed method is capable of providing a clear indication of variance in reconstructions from UAV photogrammetry. This indicator has a practical advantage, as it can be implemented before the computational intensive matching phase. As such an acquired dataset can be tested in the field. If an area with too little contrast is identified, camera settings can be adjusted for a new flight, or additional measurements can be done through traditional means.

  16. Study on Analysis of Variance on the indigenous wild and cultivated rice species of Manipur Valley

    NASA Astrophysics Data System (ADS)

    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

  17. FMRI group analysis combining effect estimates and their variances

    PubMed Central

    Chen, Gang; Saad, Ziad S.; Nath, Audrey R.; Beauchamp, Michael S.; Cox, Robert W.

    2012-01-01

    Conventional functional magnetic resonance imaging (FMRI) group analysis makes two key assumptions that are not always justified. First, the data from each subject is condensed into a single number per voxel, under the assumption that within-subject variance for the effect of interest is the same across all subjects or is negligible relative to the cross-subject variance. Second, it is assumed that all data values are drawn from the same Gaussian distribution with no outliers. We propose an approach that does not make such strong assumptions, and present a computationally efficient frequentist approach to FMRI group analysis, which we term mixed-effects multilevel analysis (MEMA), that incorporates both the variability across subjects and the precision estimate of each effect of interest from individual subject analyses. On average, the more accurate tests result in higher statistical power, especially when conventional variance assumptions do not hold, or in the presence of outliers. In addition, various heterogeneity measures are available with MEMA that may assist the investigator in further improving the modeling. Our method allows group effect t-tests and comparisons among conditions and among groups. In addition, it has the capability to incorporate subject-specific covariates such as age, IQ, or behavioral data. Simulations were performed to illustrate power comparisons and the capability of controlling type I errors among various significance testing methods, and the results indicated that the testing statistic we adopted struck a good balance between power gain and type I error control. Our approach is instantiated in an open-source, freely distributed program that may be used on any dataset stored in the universal neuroimaging file transfer (NIfTI) format. To date, the main impediment for more accurate testing that incorporates both within- and cross-subject variability has been the high computational cost. Our efficient implementation makes this approach

  18. Visual SLAM Using Variance Grid Maps

    NASA Technical Reports Server (NTRS)

    Howard, Andrew B.; Marks, Tim K.

    2011-01-01

    An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance

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

    PubMed

    Bijma, P

    2014-01-01

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

  20. The defect variance of random spherical harmonics

    NASA Astrophysics Data System (ADS)

    Marinucci, Domenico; Wigman, Igor

    2011-09-01

    The defect of a function f:M\\rightarrow {R} is defined as the difference between the measure of the positive and negative regions. In this paper, we begin the analysis of the distribution of defect of random Gaussian spherical harmonics. By an easy argument, the defect is non-trivial only for even degree and the expected value always vanishes. Our principal result is evaluating the defect variance, asymptotically in the high-frequency limit. As other geometric functionals of random eigenfunctions, the defect may be used as a tool to probe the statistical properties of spherical random fields, a topic of great interest for modern cosmological data analysis.

  1. Changes in variance explained by top SNP windows over generations for three traits in broiler chicken

    PubMed Central

    Fragomeni, Breno de Oliveira; Misztal, Ignacy; Lourenco, Daniela Lino; Aguilar, Ignacio; Okimoto, Ronald; Muir, William M.

    2014-01-01

    The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1–3, 2–4, 3–5, and 1–5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated. PMID:25324857

  2. Evolution of Robustness and Plasticity under Environmental Fluctuation: Formulation in Terms of Phenotypic Variances

    NASA Astrophysics Data System (ADS)

    Kaneko, Kunihiko

    2012-09-01

    The characterization of plasticity, robustness, and evolvability, an important issue in biology, is studied in terms of phenotypic fluctuations. By numerically evolving gene regulatory networks, the proportionality between the phenotypic variances of epigenetic and genetic origins is confirmed. The former is given by the variance of the phenotypic fluctuation due to noise in the developmental process; and the latter, by the variance of the phenotypic fluctuation due to genetic mutation. The relationship suggests a link between robustness to noise and to mutation, since robustness can be defined by the sharpness of the distribution of the phenotype. Next, the proportionality between the variances is demonstrated to also hold over expressions of different genes (phenotypic traits) when the system acquires robustness through the evolution. Then, evolution under environmental variation is numerically investigated and it is found that both the adaptability to a novel environment and the robustness are made compatible when a certain degree of phenotypic fluctuations exists due to noise. The highest adaptability is achieved at a certain noise level at which the gene expression dynamics are near the critical state to lose the robustness. Based on our results, we revisit Waddington's canalization and genetic assimilation with regard to the two types of phenotypic fluctuations.

  3. Changes in variance explained by top SNP windows over generations for three traits in broiler chicken.

    PubMed

    Fragomeni, Breno de Oliveira; Misztal, Ignacy; Lourenco, Daniela Lino; Aguilar, Ignacio; Okimoto, Ronald; Muir, William M

    2014-01-01

    The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.

  4. Additive effects of LPL, APOA5 and APOE variant combinations on triglyceride levels and hypertriglyceridemia: results of the ICARIA genetic sub-study

    PubMed Central

    2010-01-01

    Background Hypertriglyceridemia (HTG) is a well-established independent risk factor for cardiovascular disease and the influence of several genetic variants in genes related with triglyceride (TG) metabolism has been described, including LPL, APOA5 and APOE. The combined analysis of these polymorphisms could produce clinically meaningful complementary information. Methods A subgroup of the ICARIA study comprising 1825 Spanish subjects (80% men, mean age 36 years) was genotyped for the LPL-HindIII (rs320), S447X (rs328), D9N (rs1801177) and N291S (rs268) polymorphisms, the APOA5-S19W (rs3135506) and -1131T/C (rs662799) variants, and the APOE polymorphism (rs429358; rs7412) using PCR and restriction analysis and TaqMan assays. We used regression analyses to examine their combined effects on TG levels (with the log-transformed variable) and the association of variant combinations with TG levels and hypertriglyceridemia (TG ≥ 1.69 mmol/L), including the covariates: gender, age, waist circumference, blood glucose, blood pressure, smoking and alcohol consumption. Results We found a significant lowering effect of the LPL-HindIII and S447X polymorphisms (p < 0.0001). In addition, the D9N, N291S, S19W and -1131T/C variants and the APOE-ε4 allele were significantly associated with an independent additive TG-raising effect (p < 0.05, p < 0.01, p < 0.001, p < 0.0001 and p < 0.001, respectively). Grouping individuals according to the presence of TG-lowering or TG-raising polymorphisms showed significant differences in TG levels (p < 0.0001), with the lowest levels exhibited by carriers of two lowering variants (10.2% reduction in TG geometric mean with respect to individuals who were homozygous for the frequent alleles of all the variants), and the highest levels in carriers of raising combinations (25.1% mean TG increase). Thus, carrying two lowering variants was protective against HTG (OR = 0.62; 95% CI, 0.39-0.98; p = 0.042) and having one single raising polymorphism (OR

  5. River meanders - Theory of minimum variance

    USGS Publications Warehouse

    Langbein, Walter Basil; Leopold, Luna Bergere

    1966-01-01

    Meanders are the result of erosion-deposition processes tending toward the most stable form in which the variability of certain essential properties is minimized. This minimization involves the adjustment of the planimetric geometry and the hydraulic factors of depth, velocity, and local slope.The planimetric geometry of a meander is that of a random walk whose most frequent form minimizes the sum of the squares of the changes in direction in each successive unit length. The direction angles are then sine functions of channel distance. This yields a meander shape typically present in meandering rivers and has the characteristic that the ratio of meander length to average radius of curvature in the bend is 4.7.Depth, velocity, and slope are shown by field observations to be adjusted so as to decrease the variance of shear and the friction factor in a meander curve over that in an otherwise comparable straight reach of the same riverSince theory and observation indicate meanders achieve the minimum variance postulated, it follows that for channels in which alternating pools and riffles occur, meandering is the most probable form of channel geometry and thus is more stable geometry than a straight or nonmeandering alinement.

  6. Variance and Skewness in the FIRST Survey

    NASA Astrophysics Data System (ADS)

    Magliocchetti, M.; Maddox, S. J.; Lahav, O.; Wall, J. V.

    We investigate the large-scale clustering of radio sources by analysing the distribution function of the FIRST 1.4 GHz survey. We select a reliable galaxy sample from the FIRST catalogue, paying particular attention to the definition of single radio sources from the multiple components listed in the FIRST catalogue. We estimate the variance, Ψ2, and skewness, Ψ3, of the distribution function for the best galaxy subsample. Ψ2 shows power-law behaviour as a function of cell size, with an amplitude corresponding a spatial correlation length of r0 ~10 h-1 Mpc. We detect significant skewness in the distribution, and find that it is related to the variance through the relation Ψ3 = S3 (Ψ2)α with α = 1.9 +/- 0.1 consistent with the non-linear growth of perturbations from primordial Gaussian initial conditions. We show that the amplitude of clustering (corresponding to a spatial correlation length of r0 ~10 h-1 Mpc) and skewness are consistent with realistic models of galaxy clustering.

  7. Hybrid biasing approaches for global variance reduction.

    PubMed

    Wu, Zeyun; Abdel-Khalik, Hany S

    2013-02-01

    A new variant of Monte Carlo-deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses.

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

    PubMed

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

    2016-06-20

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

  9. An Empirical Temperature Variance Source Model in Heated Jets

    NASA Technical Reports Server (NTRS)

    Khavaran, Abbas; Bridges, James

    2012-01-01

    An acoustic analogy approach is implemented that models the sources of jet noise in heated jets. The equivalent sources of turbulent mixing noise are recognized as the differences between the fluctuating and Favre-averaged Reynolds stresses and enthalpy fluxes. While in a conventional acoustic analogy only Reynolds stress components are scrutinized for their noise generation properties, it is now accepted that a comprehensive source model should include the additional entropy source term. Following Goldstein s generalized acoustic analogy, the set of Euler equations are divided into two sets of equations that govern a non-radiating base flow plus its residual components. When the base flow is considered as a locally parallel mean flow, the residual equations may be rearranged to form an inhomogeneous third-order wave equation. A general solution is written subsequently using a Green s function method while all non-linear terms are treated as the equivalent sources of aerodynamic sound and are modeled accordingly. In a previous study, a specialized Reynolds-averaged Navier-Stokes (RANS) solver was implemented to compute the variance of thermal fluctuations that determine the enthalpy flux source strength. The main objective here is to present an empirical model capable of providing a reasonable estimate of the stagnation temperature variance in a jet. Such a model is parameterized as a function of the mean stagnation temperature gradient in the jet, and is evaluated using commonly available RANS solvers. The ensuing thermal source distribution is compared with measurements as well as computational result from a dedicated RANS solver that employs an enthalpy variance and dissipation rate model. Turbulent mixing noise predictions are presented for a wide range of jet temperature ratios from 1.0 to 3.20.

  10. The contribution of the mitochondrial genome to sex-specific fitness variance.

    PubMed

    Smith, Shane R T; Connallon, Tim

    2017-03-28

    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.

  11. 40 CFR 59.509 - Can I get a variance?

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... its application is complete. (d) The Administrator will issue a variance if the criteria specified in... entity will achieve compliance with this subpart. (f) A variance will cease to be effective upon...

  12. 40 CFR 59.509 - Can I get a variance?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... its application is complete. (d) The Administrator will issue a variance if the criteria specified in... entity will achieve compliance with this subpart. (f) A variance will cease to be effective upon...

  13. Applications of Variance Fractal Dimension: a Survey

    NASA Astrophysics Data System (ADS)

    Phinyomark, Angkoon; Phukpattaranont, Pornchai; Limsakul, Chusak

    2012-04-01

    Chaotic dynamical systems are pervasive in nature and can be shown to be deterministic through fractal analysis. There are numerous methods that can be used to estimate the fractal dimension. Among the usual fractal estimation methods, variance fractal dimension (VFD) is one of the most significant fractal analysis methods that can be implemented for real-time systems. The basic concept and theory of VFD are presented. Recent research and the development of several applications based on VFD are reviewed and explained in detail, such as biomedical signal processing and pattern recognition, speech communication, geophysical signal analysis, power systems and communication systems. The important parameters that need to be considered in computing the VFD are discussed, including the window size and the window increment of the feature, and the step size of the VFD. Directions for future research of VFD are also briefly outlined.

  14. An Unbiased Estimator of Gene Diversity with Improved Variance for Samples Containing Related and Inbred Individuals of any Ploidy.

    PubMed

    Harris, Alexandre M; DeGiorgio, Michael

    2017-02-09

    Gene diversity, or expected heterozygosity (H), is a common statistic for assessing genetic variation within populations. Estimation of this statistic decreases in accuracy and precision when individuals are related or inbred, due to increased dependence among allele copies in the sample. The original unbiased estimator of expected heterozygosity underestimates true population diversity in samples containing relatives, as it only accounts for sample size. More recently, a general unbiased estimator of expected heterozygosity was developed that explicitly accounts for related and inbred individuals in samples. Though unbiased, this estimator's variance is greater than that of the original estimator. To address this issue, we introduce a general unbiased estimator of gene diversity for samples containing related or inbred individuals, which employs the best linear unbiased estimator of allele frequencies, rather than the commonly used sample proportion. We examine the properties of this estimator, [Formula: see text] relative to alternative estimators using simulations and theoretical predictions, and show that it predominantly has the smallest mean squared error relative to others. Further, we empirically assess the performance of [Formula: see text] on a global human microsatellite dataset of 5795 individuals, from 267 populations, genotyped at 645 loci. Additionally, we show that the improved variance of [Formula: see text] leads to improved estimates of the population differentiation statistic, [Formula: see text] which employs measures of gene diversity within its calculation. Finally, we provide an R script, BestHet, to compute this estimator from genomic and pedigree data.

  15. An Unbiased Estimator of Gene Diversity with Improved Variance for Samples Containing Related and Inbred Individuals of any Ploidy

    PubMed Central

    Harris, Alexandre M.; DeGiorgio, Michael

    2016-01-01

    Gene diversity, or expected heterozygosity (H), is a common statistic for assessing genetic variation within populations. Estimation of this statistic decreases in accuracy and precision when individuals are related or inbred, due to increased dependence among allele copies in the sample. The original unbiased estimator of expected heterozygosity underestimates true population diversity in samples containing relatives, as it only accounts for sample size. More recently, a general unbiased estimator of expected heterozygosity was developed that explicitly accounts for related and inbred individuals in samples. Though unbiased, this estimator’s variance is greater than that of the original estimator. To address this issue, we introduce a general unbiased estimator of gene diversity for samples containing related or inbred individuals, which employs the best linear unbiased estimator of allele frequencies, rather than the commonly used sample proportion. We examine the properties of this estimator, H∼BLUE, relative to alternative estimators using simulations and theoretical predictions, and show that it predominantly has the smallest mean squared error relative to others. Further, we empirically assess the performance of H∼BLUE on a global human microsatellite dataset of 5795 individuals, from 267 populations, genotyped at 645 loci. Additionally, we show that the improved variance of H∼BLUE leads to improved estimates of the population differentiation statistic, FST, which employs measures of gene diversity within its calculation. Finally, we provide an R script, BestHet, to compute this estimator from genomic and pedigree data. PMID:28040781

  16. Addition of four-hundred fifty-five microsatellite marker loci to the high density Gossypium hirsutum TM-1 x G. barbadense 3-79 genetic map

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A high density genetic linkage map plays important roles in understanding genome structure of tetraploid cotton, dissecting economically important traits, identifying molecular markers associated with a trait, and cloning a gene of interest through map-based cloning strategy. Four hundred fifty f...

  17. Considering Oil Production Variance as an Indicator of Peak Production

    DTIC Science & Technology

    2010-06-07

    Acquisition Cost ( IRAC ) Oil Prices. Source: Data used to construct graph acquired from the EIA (http://tonto.eia.doe.gov/country/timeline/oil_chronology.cfm...Acquisition Cost ( IRAC ). Production vs. Price – Variance Comparison Oil production variance and oil price variance have never been so far

  18. A New Nonparametric Levene Test for Equal Variances

    ERIC Educational Resources Information Center

    Nordstokke, David W.; Zumbo, Bruno D.

    2010-01-01

    Tests of the equality of variances are sometimes used on their own to compare variability across groups of experimental or non-experimental conditions but they are most often used alongside other methods to support assumptions made about variances. A new nonparametric test of equality of variances is described and compared to current "gold…

  19. Evolutionary quantitative genetics of nonlinear developmental systems.

    PubMed

    Morrissey, Michael B

    2015-08-01

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

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

    PubMed Central

    2011-01-01

    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 reared at the cooler

  1. Genetics of human body size and shape: pleiotropic and independent genetic determinants of adiposity.

    PubMed

    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.

  2. Genetic origins of social networks in rhesus macaques

    PubMed Central

    Brent, Lauren J. N.; Heilbronner, Sarah R.; Horvath, Julie E.; Gonzalez-Martinez, Janis; Ruiz-Lambides, Angelina; Robinson, Athy G.; Skene, J. H. Pate; Platt, Michael L.

    2013-01-01

    Sociality is believed to have evolved as a strategy for animals to cope with their environments. Yet the genetic basis of sociality remains unclear. Here we provide evidence that social network tendencies are heritable in a gregarious primate. The tendency for rhesus macaques, Macaca mulatta, to be tied affiliatively to others via connections mediated by their social partners - analogous to friends of friends in people - demonstrated additive genetic variance. Affiliative tendencies were predicted by genetic variation at two loci involved in serotonergic signalling, although this result did not withstand correction for multiple tests. Aggressive tendencies were also heritable and were related to reproductive output, a fitness proxy. Our findings suggest that, like humans, the skills and temperaments that shape the formation of multi-agent relationships have a genetic basis in nonhuman primates, and, as such, begin to fill the gaps in our understanding of the genetic basis of sociality. PMID:23304433

  3. Cyclostationary analysis with logarithmic variance stabilisation

    NASA Astrophysics Data System (ADS)

    Borghesani, Pietro; Shahriar, Md Rifat

    2016-03-01

    Second order cyclostationary (CS2) components in vibration or acoustic emission signals are typical symptoms of a wide variety of faults in rotating and alternating mechanical systems. The square envelope spectrum (SES), obtained via Hilbert transform of the original signal, is at the basis of the most common indicators used for detection of CS2 components. It has been shown that the SES is equivalent to an autocorrelation of the signal's discrete Fourier transform, and that CS2 components are a cause of high correlations in the frequency domain of the signal, thus resulting in peaks in the SES. Statistical tests have been proposed to determine if peaks in the SES are likely to belong to a normal variability in the signal or if they are proper symptoms of CS2 components. Despite the need for automated fault recognition and the theoretical soundness of these tests, this approach to machine diagnostics has been mostly neglected in industrial applications. In fact, in a series of experimental applications, even with proper pre-whitening steps, it has been found that healthy machines might produce high spectral correlations and therefore result in a highly biased SES distribution which might cause a series of false positives. In this paper a new envelope spectrum is defined, with the theoretical intent of rendering the hypothesis test variance-free. This newly proposed indicator will prove unbiased in case of multiple CS2 sources of spectral correlation, thus reducing the risk of false alarms.

  4. Correcting an analysis of variance for clustering.

    PubMed

    Hedges, Larry V; Rhoads, Christopher H

    2011-02-01

    A great deal of educational and social data arises from cluster sampling designs where clusters involve schools, classrooms, or communities. A mistake that is sometimes encountered in the analysis of such data is to ignore the effect of clustering and analyse the data as if it were based on a simple random sample. This typically leads to an overstatement of the precision of results and too liberal conclusions about precision and statistical significance of mean differences. This paper gives simple corrections to the test statistics that would be computed in an analysis of variance if clustering were (incorrectly) ignored. The corrections are multiplicative factors depending on the total sample size, the cluster size, and the intraclass correlation structure. For example, the corrected F statistic has Fisher's F distribution with reduced degrees of freedom. The corrected statistic reduces to the F statistic computed by ignoring clustering when the intraclass correlations are zero. It reduces to the F statistic computed using cluster means when the intraclass correlations are unity, and it is in between otherwise. A similar adjustment to the usual statistic for testing a linear contrast among group means is described.

  5. Estimating discharge measurement uncertainty using the interpolated variance estimator

    USGS Publications Warehouse

    Cohn, T.; Kiang, J.; Mason, R.

    2012-01-01

    Methods for quantifying the uncertainty in discharge measurements typically identify various sources of uncertainty and then estimate the uncertainty from each of these sources by applying the results of empirical or laboratory studies. If actual measurement conditions are not consistent with those encountered in the empirical or laboratory studies, these methods may give poor estimates of discharge uncertainty. This paper presents an alternative method for estimating discharge measurement uncertainty that uses statistical techniques and at-site observations. This Interpolated Variance Estimator (IVE) estimates uncertainty based on the data collected during the streamflow measurement and therefore reflects the conditions encountered at the site. The IVE has the additional advantage of capturing all sources of random uncertainty in the velocity and depth measurements. It can be applied to velocity-area discharge measurements that use a velocity meter to measure point velocities at multiple vertical sections in a channel cross section.

  6. Progress in unraveling the genetic etiology of Parkinson disease in a genomic era.

    PubMed

    Verstraeten, Aline; Theuns, Jessie; Van Broeckhoven, Christine

    2015-03-01

    Parkinson disease (PD) and Parkinson-plus syndromes are genetically heterogeneous neurological diseases. Initial studies into the genetic causes of PD relied on classical molecular genetic approaches in well-documented case families. More recently, these approaches have been combined with exome sequencing and together have identified 15 causal genes. Additionally, genome-wide association studies (GWASs) have discovered over 25 genetic risk factors. Elucidation of the genetic architecture of sporadic and familial parkinsonism, however, has lagged behind that of simple Mendelian conditions, suggesting the existence of features confounding genetic data interpretation. Here we discuss the successes and potential pitfalls of gene discovery in PD and related disorders in the post-genomic era. With an estimated 30% of trait variance currently unexplained, tackling current limitations will further expedite gene discovery and lead to increased application of these genetic insights in molecular diagnostics using gene panel and exome sequencing strategies.

  7. On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series

    PubMed Central

    Fransson, Peter

    2016-01-01

    Abstract Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed. PMID:27784176

  8. On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

    PubMed

    Thompson, William Hedley; Fransson, Peter

    2016-12-01

    Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

  9. Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

    PubMed Central

    Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

    2015-01-01

    Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

  10. Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course.

    PubMed

    Graff, Mariaelisa; Ngwa, Julius S; Workalemahu, Tsegaselassie; Homuth, Georg; Schipf, Sabine; Teumer, Alexander; Völzke, Henry; Wallaschofski, Henri; Abecasis, Goncalo R; Edward, Lakatta; Francesco, Cucca; Sanna, Serena; Scheet, Paul; Schlessinger, David; Sidore, Carlo; Xiao, Xiangjun; Wang, Zhaoming; Chanock, Stephen J; Jacobs, Kevin B; Hayes, Richard B; Hu, Frank; Van Dam, Rob M; Crout, Richard J; Marazita, Mary L; Shaffer, John R; Atwood, Larry D; Fox, Caroline S; Heard-Costa, Nancy L; White, Charles; Choh, Audrey C; Czerwinski, Stefan A; Demerath, Ellen W; Dyer, Thomas D; Towne, Bradford; Amin, Najaf; Oostra, Ben A; Van Duijn, Cornelia M; Zillikens, M Carola; Esko, Tõnu; Nelis, Mari; Nikopensius, Tit; Metspalu, Andres; Strachan, David P; Monda, Keri; Qi, Lu; North, Kari E; Cupples, L Adrienne; Gordon-Larsen, Penny; Berndt, Sonja I

    2013-09-01

    Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10⁻⁸) near FTO (P = 3.72 × 10⁻²³), TMEM18 (P = 3.24 × 10⁻¹⁷), MC4R (P = 4.41 × 10⁻¹⁷), TNNI3K (P = 4.32 × 10⁻¹¹), SEC16B (P = 6.24 × 10⁻⁹), GNPDA2 (P = 1.11 × 10⁻⁸) and POMC (P = 4.94 × 10⁻⁸) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10⁻⁵ after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18-90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages.

  11. Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course

    PubMed Central

    Graff, Mariaelisa; Ngwa, Julius S.; Workalemahu, Tsegaselassie; Homuth, Georg; Schipf, Sabine; Teumer, Alexander; Völzke, Henry; Wallaschofski, Henri; Abecasis, Goncalo R.; Edward, Lakatta; Francesco, Cucca; Sanna, Serena; Scheet, Paul; Schlessinger, David; Sidore, Carlo; Xiao, Xiangjun; Wang, Zhaoming; Chanock, Stephen J.; Jacobs, Kevin B.; Hayes, Richard B.; Hu, Frank; Van Dam, Rob M.; Crout, Richard J.; Marazita, Mary L.; Shaffer, John R; Atwood, Larry D.; Fox, Caroline S.; Heard-Costa, Nancy L.; White, Charles; Choh, Audrey C.; Czerwinski, Stefan A.; Demerath, Ellen W.; Dyer, Thomas D.; Towne, Bradford; Amin, Najaf; Oostra, Ben A.; Van Duijn, Cornelia M.; Zillikens, M. Carola; Esko, Tõnu; Nelis, Mari; Nikopensius, Tit; Metspalu, Andres; Strachan, David P.; Monda, Keri; Qi, Lu; North, Kari E.; Cupples, L. Adrienne; Gordon-Larsen, Penny; Berndt, Sonja I.

    2013-01-01

    Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10−8) near FTO (P = 3.72 × 10−23), TMEM18 (P = 3.24 × 10−17), MC4R (P = 4.41 × 10−17), TNNI3K (P = 4.32 × 10−11), SEC16B (P = 6.24 × 10−9), GNPDA2 (P = 1.11 × 10−8) and POMC (P = 4.94 × 10−8) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10−5 after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18–90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages. PMID:23669352

  12. A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

    PubMed

    Hu, Pingsha; Maiti, Tapabrata

    2011-01-01

    Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

  13. Potential variance affecting homeotic Ultrabithorax and Antennapedia phenotypes in Drosophila melanogaster.

    PubMed Central

    Gibson, G; Wemple, M; van Helden, S

    1999-01-01

    Introgression of homeotic mutations into wild-type genetic backgrounds results in a wide variety of phenotypes and implies that major effect modifiers of extreme phenotypes are not uncommon in natural populations of Drosophila. A composite interval mapping procedure was used to demonstrate that one major effect locus accounts for three-quarters of the variance for haltere to wing margin transformation in Ultrabithorax flies, yet has no obvious effect on wild-type development. Several other genetic backgrounds result in enlargement of the haltere significantly beyond the normal range of haploinsufficient phenotypes, suggesting genetic variation in cofactors that mediate homeotic protein function. Introgression of Antennapedia produces lines with heritable phenotypes ranging from almost complete suppression to perfect antennal leg formation, as well as transformations that are restricted to either the distal or proximal portion of the appendage. It is argued that the existence of "potential" variance, which is genetic variation whose effects are not observable in wild-type individuals, is a prerequisite for the uncoupling of genetic from phenotypic divergence. PMID:10049924

  14. Molecular genetics and subjective well-being.

    PubMed

    Rietveld, Cornelius A; Cesarini, David; Benjamin, Daniel J; Koellinger, Philipp D; De Neve, Jan-Emmanuel; Tiemeier, Henning; Johannesson, Magnus; Magnusson, Patrik K E; Pedersen, Nancy L; Krueger, Robert F; Bartels, Meike

    2013-06-11

    Subjective well-being (SWB) is a major topic of research across the social sciences. Twin and family studies have found that genetic factors may account for as much as 30-40% of the variance in SWB. Here, we study genetic contributions to SWB in a pooled sample of ≈ 11,500 unrelated, comprehensively-genotyped Swedish and Dutch individuals. We apply a recently developed method to estimate "common narrow heritability": the fraction of variance in SWB that can be explained by the cumulative additive effects of genetic polymorphisms that are common in the population. Our estimates are 5-10% for single-question survey measures of SWB, and 12-18% after correction for measurement error in the SWB measures. Our results suggest guarded optimism about the prospects of using genetic data in SWB research because, although the common narrow heritability is not large, the polymorphisms that contribute to it could feasibly be discovered with a sufficiently large sample of individuals.

  15. Molecular genetics and subjective well-being

    PubMed Central

    Rietveld, Cornelius A.; Cesarini, David; Benjamin, Daniel J.; Koellinger, Philipp D.; De Neve, Jan-Emmanuel; Tiemeier, Henning; Johannesson, Magnus; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Krueger, Robert F.; Bartels, Meike

    2013-01-01

    Subjective well-being (SWB) is a major topic of research across the social sciences. Twin and family studies have found that genetic factors may account for as much as 30–40% of the variance in SWB. Here, we study genetic contributions to SWB in a pooled sample of ≈11,500 unrelated, comprehensively-genotyped Swedish and Dutch individuals. We apply a recently developed method to estimate “common narrow heritability”: the fraction of variance in SWB that can be explained by the cumulative additive effects of genetic polymorphisms that are common in the population. Our estimates are 5–10% for single-question survey measures of SWB, and 12–18% after correction for measurement error in the SWB measures. Our results suggest guarded optimism about the prospects of using genetic data in SWB research because, although the common narrow heritability is not large, the polymorphisms that contribute to it could feasibly be discovered with a sufficiently large sample of individuals. PMID:23708117

  16. Evolutionary genetics of maternal effects

    PubMed Central

    Wolf, Jason B.; Wade, Michael J.

    2016-01-01

    Maternal genetic effects (MGEs), where genes expressed by mothers affect the phenotype of their offspring, are important sources of phenotypic diversity in a myriad of organisms. We use a single‐locus model to examine how MGEs contribute patterns of heritable and nonheritable variation and influence evolutionary dynamics in randomly mating and inbreeding populations. We elucidate the influence of MGEs by examining the offspring genotype‐phenotype relationship, which determines how MGEs affect evolutionary dynamics in response to selection on offspring phenotypes. This approach reveals important results that are not apparent from classic quantitative genetic treatments of MGEs. We show that additive and dominance MGEs make different contributions to evolutionary dynamics and patterns of variation, which are differentially affected by inbreeding. Dominance MGEs make the offspring genotype‐phenotype relationship frequency dependent, resulting in the appearance of negative frequency‐dependent selection, while additive MGEs contribute a component of parent‐of‐origin dependent variation. Inbreeding amplifies the contribution of MGEs to the additive genetic variance and, therefore enhances their evolutionary response. Considering evolutionary dynamics of allele frequency change on an adaptive landscape, we show that this landscape differs from the mean fitness surface, and therefore, under some condition, fitness peaks can exist but not be “available” to the evolving population. PMID:26969266

  17. Estimating the encounter rate variance in distance sampling

    USGS Publications Warehouse

    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.

  18. Heritability and genetic correlations of personality traits in a wild population of yellow-bellied marmots (Marmota flaviventris).

    PubMed

    Petelle, M B; Martin, J G A; Blumstein, D T

    2015-10-01

    Describing and quantifying animal personality is now an integral part of behavioural studies because individually distinctive behaviours have ecological and evolutionary consequences. Yet, to fully understand how personality traits may respond to selection, one must understand the underlying heritability and genetic correlations between traits. Previous studies have reported a moderate degree of heritability of personality traits, but few of these studies have either been conducted in the wild or estimated the genetic correlations between personality traits. Estimating the additive genetic variance and covariance in the wild is crucial to understand the evolutionary potential of behavioural traits. Enhanced environmental variation could reduce heritability and genetic correlations, thus leading to different evolutionary predictions. We estimated the additive genetic variance and covariance of docility in the trap, sociability (mirror image stimulation), and exploration and activity in two different contexts (open-field and mirror image simulation experiments) in a wild population of yellow-bellied marmots (Marmota flaviventris). We estimated both heritability of behaviours and of personality traits and found nonzero additive genetic variance in these traits. We also found nonzero maternal, permanent environment and year effects. Finally, we found four phenotypic correlations between traits, and one positive genetic correlation between activity in the open-field test and sociability. We also found permanent environment correlations between activity in both tests and docility and exploration in the MIS test. This is one of a handful of studies to adopt a quantitative genetic approach to explain variation in personality traits in the wild and, thus, provides important insights into the potential variance available for selection.

  19. Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

    SciTech Connect

    Ankirchner, Stefan; Dermoune, Azzouz

    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.

  20. Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

    PubMed

    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.

  1. Network Structure and Biased Variance Estimation in Respondent Driven Sampling

    PubMed Central

    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. PMID:26679927

  2. RR-Interval variance of electrocardiogram for atrial fibrillation detection

    NASA Astrophysics Data System (ADS)

    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.

  3. Simulations of the Hadamard Variance: Probability Distributions and Confidence Intervals.

    PubMed

    Ashby, Neil; Patla, Bijunath

    2016-04-01

    Power-law noise in clocks and oscillators can be simulated by Fourier transforming a modified spectrum of white phase noise. This approach has been applied successfully to simulation of the Allan variance and the modified Allan variance in both overlapping and nonoverlapping forms. When significant frequency drift is present in an oscillator, at large sampling times the Allan variance overestimates the intrinsic noise, while the Hadamard variance is insensitive to frequency drift. The simulation method is extended in this paper to predict the Hadamard variance for the common types of power-law noise. Symmetric real matrices are introduced whose traces-the sums of their eigenvalues-are equal to the Hadamard variances, in overlapping or nonoverlapping forms, as well as for the corresponding forms of the modified Hadamard variance. We show that the standard relations between spectral densities and Hadamard variance are obtained with this method. The matrix eigenvalues determine probability distributions for observing a variance at an arbitrary value of the sampling interval τ, and hence for estimating confidence in the measurements.

  4. A NEW VARIANCE ESTIMATOR FOR PARAMETERS OF SEMI-PARAMETRIC GENERALIZED ADDITIVE MODELS. (R829213)

    EPA Science Inventory

    The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

  5. VARIANCES MAY BE UNDERESTIMATED USING AVAILABLE SOFTWARE FOR GENERALIZED ADDITIVE MODELS. (R829213)

    EPA Science Inventory

    The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

  6. 77 FR 9637 - Process for Requesting a Variance From Vegetation Standards for Levees and Floodwalls; Additional...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-17

    ..., channels, or shore-line or river-bank protection systems such as revetments, sand dunes, and barrier islands. b. New federally authorized cost-shared levee projects shall be designed to meet the...

  7. A Note on Noncentrality Parameters for Contrast Tests in a One-Way Analysis of Variance

    ERIC Educational Resources Information Center

    Liu, Xiaofeng Steven

    2010-01-01

    The noncentrality parameter for a contrast test in a one-way analysis of variance is based on the dot product of 2 vectors whose geometric meaning in a Euclidian space offers mnemonic hints about its constituents. Additionally, the noncentrality parameters for a set of orthogonal contrasts sum up to the noncentrality parameter for the omnibus…

  8. Genetic architecture of survival and fitness-related traits in two populations of Atlantic salmon

    PubMed Central

    Houde, A LS; Wilson, C C; Neff, B D

    2013-01-01

    The additive genetic effects of traits can be used to predict evolutionary trajectories, such as responses to selection. Non-additive genetic and maternal environmental effects can also change evolutionary trajectories and influence phenotypes, but these effects have received less attention by researchers. We partitioned the phenotypic variance of survival and fitness-related traits into additive genetic, non-additive genetic and maternal environmental effects using a full-factorial breeding design within two allopatric populations of Atlantic salmon (Salmo salar). Maternal environmental effects were large at early life stages, but decreased during development, with non-additive genetic effects being most significant at later juvenile stages (alevin and fry). Non-additive genetic effects were also, on average, larger than additive genetic effects. The populations, generally, did not differ in the trait values or inferred genetic architecture of the traits. Any differences between the populations for trait values could be explained by maternal environmental effects. We discuss whether the similarities in architectures of these populations is the result of natural selection across a common juvenile environment. PMID:23942281

  9. Genome-wide interaction of genotype by erythrocyte n-3 PUFAs contributes to phenotypic variance of diabetes-related traits

    Technology Transfer Automated Retrieval System (TEKTRAN)

    While genome-wide association studies (GWAS) and candidate gene approach have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. The present study aimed to examine variance contribu...

  10. Antioxidant value addition in human diets: genetic transformation of Brassica juncea with gamma-TMT gene for increased alpha-tocopherol content.

    PubMed

    Yusuf, Mohd Aslam; Sarin, Neera Bhalla

    2007-02-01

    Alpha-tocopherol, the most biologically active form of vitamin E, is implicated in decreasing the risk of several types of cancers, coronary heart disease and a number of degenerative human conditions, when taken in excess of the recommended daily allowance. Natural alpha-tocopherol has twice the bioavailability of the synthetic isomer. This study describes a successful attempt at fortifying human diets with natural alpha-tocopherol by taking recourse to genetic engineering of an important oilseed crop, Brassica juncea. Gamma-tocopherol methyl transferase cDNA from Arabidopsis thaliana, coding for the enzyme catalysing the conversion of the large gamma-tocopherol pool to alpha-tocopherol, was overexpressed in B. juncea plants. The successful integration of the transgene was confirmed by PCR and Southern blot analysis, while the enhanced transcript level was evident in the northern blot analysis. HPLC analysis of the seeds of the T1 transgenic lines showed a shift in tocopherol profile with the highest over-expressors having alpha-tocopherol levels as high as sixfold over the non-transgenic controls. This study discusses the production of a transgenic oilseed crop with high alpha-tocopherol levels, which can provide a feasible, innocuous, and inexpensive way of taking the beneficial effects of high alpha-tocopherol intake to the masses.

  11. Analysis of variance of designed chromatographic data sets: The analysis of variance-target projection approach.

    PubMed

    Marini, Federico; de Beer, Dalene; Joubert, Elizabeth; Walczak, Beata

    2015-07-31

    Direct application of popular approaches, e.g., Principal Component Analysis (PCA) or Partial Least Squares (PLS) to chromatographic data originating from a well-designed experimental study including more than one factor is not recommended. In the case of a well-designed experiment involving two or more factors (crossed or nested), data are usually decomposed into the contributions associated with the studied factors (and with their interactions), and the individual effect matrices are then analyzed using, e.g., PCA, as in the case of ASCA (analysis of variance combined with simultaneous component analysis). As an alternative to the ASCA method, we propose the application of PLS followed by target projection (TP), which allows a one-factor representation of the model for each column in the design dummy matrix. PLS application follows after proper deflation of the experimental matrix, i.e., to what are called the residuals under the reduced ANOVA model. The proposed approach (ANOVA-TP) is well suited for the study of designed chromatographic data of complex samples. It allows testing of statistical significance of the studied effects, 'biomarker' identification, and enables straightforward visualization and accurate estimation of between- and within-class variance. The proposed approach has been successfully applied to a case study aimed at evaluating the effect of pasteurization on the concentrations of various phenolic constituents of rooibos tea of different quality grades and its outcomes have been compared to those of ASCA.

  12. Genome-wide evaluation for quantitative trait loci under the variance component model

    PubMed Central

    Han, Lide

    2010-01-01

    The identity-by-descent (IBD) based variance component analysis is an important method for mapping quantitative trait loci (QTL) in outbred populations. The interval-mapping approach and various modified versions of it may have limited use in evaluating the genetic variances of the entire genome because they require evaluation of multiple models and model selection. In this study, we developed a multiple variance component model for genome-wide evaluation using both the maximum likelihood (ML) method and the MCMC implemented Bayesian method. We placed one QTL in every few cM on the entire genome and estimated the QTL variances and positions simultaneously in a single model. Genomic regions that have no QTL usually showed no evidence of QTL while regions with large QTL always showed strong evidence of QTL. While the Bayesian method produced the optimal result, the ML method is computationally more efficient than the Bayesian method. Simulation experiments were conducted to demonstrate the efficacy of the new methods. Electronic supplementary material The online version of this article (doi:10.1007/s10709-010-9497-1) contains supplementary material, which is available to authorized users. PMID:20835884

  13. Feasibility study: protein denaturation and coagulation monitoring with speckle variance optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Lee, Changho; Cheon, Gyeongwoo; Kim, Do-Hyun; Kang, Jin U.

    2016-12-01

    We performed the feasibility study using speckle variance optical coherence tomography (SvOCT) to monitor the thermally induced protein denaturation and coagulation process as a function of temperature and depth. SvOCT provided the depth-resolved image of protein denaturation and coagulation with microscale resolution. This study was conducted using egg white. During the heating process, as the temperature increased, increases in the speckle variance signal was observed as the egg white proteins coagulated. Additionally, by calculating the cross-correlation coefficient in specific areas, denaturized egg white conditions were successfully estimated. These results indicate that SvOCT could be used to monitor the denaturation process of various proteins.

  14. Fractional Brownian Motion with Stochastic Variance:. Modeling Absolute Returns in STOCK Markets

    NASA Astrophysics Data System (ADS)

    Roman, H. E.; Porto, M.

    We discuss a model for simulating a long-time memory in time series characterized in addition by a stochastic variance. The model is based on a combination of fractional Brownian motion (FBM) concepts, for dealing with the long-time memory, with an autoregressive scheme with conditional heteroskedasticity (ARCH), responsible for the stochastic variance of the series, and is denoted as FBMARCH. Unlike well-known fractionally integrated autoregressive models, FBMARCH admits finite second moments. The resulting probability distribution functions have power-law tails with exponents similar to ARCH models. This idea is applied to the description of long-time autocorrelations of absolute returns ubiquitously observed in stock markets.

  15. Multibreed genetic evaluation in bovines using simulated data employing a composite population.

    PubMed

    Bocchi, A L; Oliveira, H N; Ferraz, J B S; Eler, J P

    2016-10-05

    Genetic evaluations in Brazil are performed within each animal breed; however, with the wide range of extant genetic groups in the country and the increased use of genetic crossing as a form of rapid meat production, more elaborate programs that can jointly evaluate animals of different genetic groups are needed. Genetic evaluation of a composite breed is difficult because of the variation in the genetic composition of a given herd, as well as the inclusion of non-additive genetic effects among breeds that can be important for selecting traits in certain breed combinations. Newer models include additive and non-additive effects; however, few studies have investigated these aspects in tropical breeds. The aim of this study was to simulate genetic values to compare different models. Non-inclusion of maternal effects in models leads to overestimation of variance and direct heritability. Estimates of the biological additive effects are influenced by the maternal effects; however, estimates of the non-additive effects are minimally influenced by the maternal effects and are well estimated in any situation. The studied models effectively predict the direct genetic values.

  16. Variance and bias confidence criteria for ERA modal parameter identification. [Eigensystem Realization Algorithm

    NASA Technical Reports Server (NTRS)

    Longman, Richard W.; Bergmann, Martin; Juang, Jer-Nan

    1988-01-01

    For the ERA system identification algorithm, perturbation methods are used to develop expressions for variance and bias of the identified modal parameters. Based on the statistics of the measurement noise, the variance results serve as confidence criteria by indicating how likely the true parameters are to lie within any chosen interval about their identified values. This replaces the use of expensive and time-consuming Monte Carlo computer runs to obtain similar information. The bias estimates help guide the ERA user in his choice of which data points to use and how much data to use in order to obtain the best results, performing the trade-off between the bias and scatter. Also, when the uncertainty in the bias is sufficiently small, the bias information can be used to correct the ERA results. In addition, expressions for the variance and bias of the singular values serve as tools to help the ERA user decide the proper modal order.

  17. On discrete stochastic processes with long-lasting time dependence in the variance

    NASA Astrophysics Data System (ADS)

    Queirós, S. M. D.

    2008-11-01

    In this manuscript, we analytically and numerically study statistical properties of an heteroskedastic process based on the celebrated ARCH generator of random variables whose variance is defined by a memory of qm-exponencial, form (eqm=1 x=ex). Specifically, we inspect the self-correlation function of squared random variables as well as the kurtosis. In addition, by numerical procedures, we infer the stationary probability density function of both of the heteroskedastic random variables and the variance, the multiscaling properties, the first-passage times distribution, and the dependence degree. Finally, we introduce an asymmetric variance version of the model that enables us to reproduce the so-called leverage effect in financial markets.

  18. Splitting the variance of statistical learning performance: A parametric investigation of exposure duration and transitional probabilities.

    PubMed

    Bogaerts, Louisa; Siegelman, Noam; Frost, Ram

    2016-08-01

    What determines individuals' efficacy in detecting regularities in visual statistical learning? Our theoretical starting point assumes that the variance in performance of statistical learning (SL) can be split into the variance related to efficiency in encoding representations within a modality and the variance related to the relative computational efficiency of detecting the distributional properties of the encoded representations. Using a novel methodology, we dissociated encoding from higher-order learning factors, by independently manipulating exposure duration and transitional probabilities in a stream of visual shapes. Our results show that the encoding of shapes and the retrieving of their transitional probabilities are not independent and additive processes, but interact to jointly determine SL performance. The theoretical implications of these findings for a mechanistic explanation of SL are discussed.

  19. 29 CFR 1905.5 - Effect of variances.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 29 Labor 5 2010-07-01 2010-07-01 false Effect of variances. 1905.5 Section 1905.5 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR RULES OF PRACTICE FOR VARIANCES, LIMITATIONS, VARIATIONS, TOLERANCES, AND EXEMPTIONS UNDER THE WILLIAMS-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT...

  20. 36 CFR 27.4 - Variances and exceptions.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 36 Parks, Forests, and Public Property 1 2013-07-01 2013-07-01 false Variances and exceptions. 27.4 Section 27.4 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE INTERIOR CAPE COD NATIONAL SEASHORE; ZONING STANDARDS § 27.4 Variances and exceptions. (a) Zoning bylaws...

  1. 36 CFR 27.4 - Variances and exceptions.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Variances and exceptions. 27.4 Section 27.4 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE INTERIOR CAPE COD NATIONAL SEASHORE; ZONING STANDARDS § 27.4 Variances and exceptions. (a) Zoning bylaws...

  2. 36 CFR 27.4 - Variances and exceptions.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 36 Parks, Forests, and Public Property 1 2012-07-01 2012-07-01 false Variances and exceptions. 27.4 Section 27.4 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE INTERIOR CAPE COD NATIONAL SEASHORE; ZONING STANDARDS § 27.4 Variances and exceptions. (a) Zoning bylaws...

  3. 36 CFR 27.4 - Variances and exceptions.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 36 Parks, Forests, and Public Property 1 2014-07-01 2014-07-01 false Variances and exceptions. 27.4 Section 27.4 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE INTERIOR CAPE COD NATIONAL SEASHORE; ZONING STANDARDS § 27.4 Variances and exceptions. (a) Zoning bylaws...

  4. 36 CFR 27.4 - Variances and exceptions.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 36 Parks, Forests, and Public Property 1 2011-07-01 2011-07-01 false Variances and exceptions. 27.4 Section 27.4 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE INTERIOR CAPE COD NATIONAL SEASHORE; ZONING STANDARDS § 27.4 Variances and exceptions. (a) Zoning bylaws...

  5. 40 CFR 141.4 - Variances and exemptions.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 24 2013-07-01 2013-07-01 false Variances and exemptions. 141.4 Section 141.4 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS General § 141.4 Variances and exemptions....

  6. 40 CFR 141.4 - Variances and exemptions.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 23 2014-07-01 2014-07-01 false Variances and exemptions. 141.4 Section 141.4 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS General § 141.4 Variances and exemptions....

  7. 40 CFR 141.4 - Variances and exemptions.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Variances and exemptions. 141.4 Section 141.4 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS General § 141.4 Variances and exemptions....

  8. 40 CFR 141.4 - Variances and exemptions.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 24 2012-07-01 2012-07-01 false Variances and exemptions. 141.4 Section 141.4 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS General § 141.4 Variances and exemptions....

  9. 40 CFR 141.4 - Variances and exemptions.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Variances and exemptions. 141.4 Section 141.4 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS General § 141.4 Variances and exemptions....

  10. Determining Sample Sizes for Precise Contrast Analysis with Heterogeneous Variances

    ERIC Educational Resources Information Center

    Jan, Show-Li; Shieh, Gwowen

    2014-01-01

    The analysis of variance (ANOVA) is one of the most frequently used statistical analyses in practical applications. Accordingly, the single and multiple comparison procedures are frequently applied to assess the differences among mean effects. However, the underlying assumption of homogeneous variances may not always be tenable. This study…

  11. 76 FR 78698 - Proposed Revocation of Permanent Variances

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-19

    ... Occupational Safety and Health Administration Proposed Revocation of Permanent Variances AGENCY: Occupational... short and plain statement detailing (1) how the proposed revocation would affect the requesting party..., subpart L. The following table provides information about the variances proposed for revocation by...

  12. Gender Variance and Educational Psychology: Implications for Practice

    ERIC Educational Resources Information Center

    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…

  13. 42 CFR 456.522 - Content of request for variance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time..., mental hospital, and ICF located within a 50-mile radius of the facility; (e) The distance and...

  14. A Study of Variance Estimation Methods. Working Paper Series.

    ERIC Educational Resources Information Center

    Zhang, Fan; Weng, Stanley; Salvucci, Sameena; Hu, Ming-xiu

    This working paper contains reports of five studies of variance estimation methods. The first, An Empirical Study of Poststratified Estimator, by Fan Zhang uses data from the National Household Education Survey to illustrate use of poststratified estimation. The second paper, BRR Variance Estimation Using BPLX Hadamard Procedure, by Stanley Weng…

  15. Conceptual Complexity and the Bias/Variance Tradeoff

    ERIC Educational Resources Information Center

    Briscoe, Erica; Feldman, Jacob

    2011-01-01

    In this paper we propose that the conventional dichotomy between exemplar-based and prototype-based models of concept learning is helpfully viewed as an instance of what is known in the statistical learning literature as the "bias/variance tradeoff". The bias/variance tradeoff can be thought of as a sliding scale that modulates how closely any…

  16. Variances and Covariances of Kendall's Tau and Their Estimation.

    ERIC Educational Resources Information Center

    Cliff, Norman; Charlin, Ventura

    1991-01-01

    Variance formulas of H. E. Daniels and M. G. Kendall (1947) are generalized to allow for the presence of ties and variance of the sample tau correlation. Applications of these generalized formulas are discussed and illustrated using data from a 1965 study of contraceptive use in 15 developing countries. (SLD)

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

    SciTech Connect

    Phillips, K.; Matheny, A.P. Jr.

    1995-02-27

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

  18. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle.

    PubMed

    Singh, Ajay; Singh, Avtar; Singh, Manvendra; Prakash, Ved; Ambhore, G S; Sahoo, S K; Dash, Soumya

    2016-06-01

    A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

  19. Food additives

    PubMed Central

    Spencer, Michael

    1974-01-01

    Food additives are discussed from the food technology point of view. The reasons for their use are summarized: (1) to protect food from chemical and microbiological attack; (2) to even out seasonal supplies; (3) to improve their eating quality; (4) to improve their nutritional value. The various types of food additives are considered, e.g. colours, flavours, emulsifiers, bread and flour additives, preservatives, and nutritional additives. The paper concludes with consideration of those circumstances in which the use of additives is (a) justified and (b) unjustified. PMID:4467857

  20. Variance component model to account for sample structure in genome-wide association studies.

    PubMed

    Kang, Hyun Min; Sul, Jae Hoon; Service, Susan K; Zaitlen, Noah A; Kong, Sit-Yee; Freimer, Nelson B; Sabatti, Chiara; Eskin, Eleazar

    2010-04-01

    Although genome-wide association studies (GWASs) have identified numerous loci associated with complex traits, imprecise modeling of the genetic relatedness within study samples may cause substantial inflation of test statistics and possibly spurious associations. Variance component approaches, such as efficient mixed-model association (EMMA), can correct for a wide range of sample structures by explicitly accounting for pairwise relatedness between individuals, using high-density markers to model the phenotype distribution; but such approaches are computationally impractical. We report here a variance component approach implemented in publicly available software, EMMA eXpedited (EMMAX), that reduces the computational time for analyzing large GWAS data sets from years to hours. We apply this method to two human GWAS data sets, performing association analysis for ten quantitative traits from the Northern Finland Birth Cohort and seven common diseases from the Wellcome Trust Case Control Consortium. We find that EMMAX outperforms both principal component analysis and genomic control in correcting for sample structure.

  1. Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models.

    PubMed

    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).

  2. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste... as boilers, or applications for non-waste determinations. (a) The applicant must apply to...

  3. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste... as boilers, or applications for non-waste determinations. (a) The applicant must apply to...

  4. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste... as boilers, or applications for non-waste determinations. (a) The applicant must apply to...

  5. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste... as boilers, or applications for non-waste determinations. (a) The applicant must apply to...

  6. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste... as boilers, or applications for non-waste determinations. (a) The applicant must apply to...

  7. Genetic mechanisms of pollution resistance in a marine invertebrate.

    PubMed

    Galletly, Bronwyn C; Blows, Mark W; Marshall, Dustin J

    2007-12-01

    Pollution is a common stress in the marine environment and one of today's most powerful agents of selection, yet we have little understanding of how anthropogenic toxicants influence mechanisms of adaptation in marine populations. Due to their life history strategies, marine invertebrates are unable to avoid stress and must adapt to variable environments. We examined the genetic basis of pollution resistance across multiple environments using the marine invertebrate, Styela plicata. Gametes were crossed in a quantitative genetic breeding design to enable partitioning of additive genetic variance across a concentration gradient of a common marine pollutant, copper. Hatching success was scored as a measure of stress resistance in copper concentrations of 0, 75, 150, and 350 microg/L. There was a significant genotype x environment interaction in hatching success across copper concentrations. Further analysis using factor analytic modeling confirmed a significant dimension of across-environment genetic variation where the genetic basis of resistance to stress in the first three environments differed from that in the environment of highest copper concentration. A second genetic dimension further differentiated between the genetic basis of resistance to low and high stress environments. These results suggest that marine organisms use different genetic mechanisms to adapt to different levels of pollution and that the level of genetic variation to adapt to intense pollution stresses may be limited.

  8. Estimates of genetic parameters of body weight in descendants of X-irradiated rat spermatogonia.

    PubMed

    Gianola, D; Chapman, A B; Rutledge, J J

    1977-08-01

    Effects of nine generations of 450r 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.

  9. Monozygotic twins affected with major depressive disorder have greater variance in methylation than their unaffected co-twin.

    PubMed

    Byrne, E M; Carrillo-Roa, T; Henders, A K; Bowdler, L; McRae, A F; Heath, A C; Martin, N G; Montgomery, G W; Krause, L; Wray, N R

    2013-06-11

    Our understanding of major depressive disorder (MDD) has focused on the influence of genetic variation and environmental risk factors. Growing evidence suggests the additional role of epigenetic mechanisms influencing susceptibility for complex traits. DNA sequence within discordant monozygotic twin (MZT) pairs is virtually identical; thus, they represent a powerful design for studying the contribution of epigenetic factors to disease liability. The aim of this study was to investigate whether specific methylation profiles in white blood cells could contribute to the aetiology of MDD. Participants were drawn from the Queensland Twin Registry and comprised 12 MZT pairs discordant for MDD and 12 MZT pairs concordant for no MDD and low neuroticism. Bisulphite treatment and genome-wide interrogation of differentially methylated CpG sites using the Illumina Human Methylation 450 BeadChip were performed in WBC-derived DNA. No overall difference in mean global methylation between cases and their unaffected co-twins was found; however, the differences in females was significant (P=0.005). The difference in variance across all probes between affected and unaffected twins was highly significant (P<2.2 × 10⁻¹⁶), with 52.4% of probes having higher variance in cases (binomial P-value<2.2 × 10⁻¹⁶). No significant differences in methylation were observed between discordant MZT pairs and their matched concordant MZT (permutation minimum P=0.11) at any individual probe. Larger samples are likely to be needed to identify true associations between methylation differences at specific CpG sites.

  10. Filtered kriging for spatial data with heterogeneous measurement error variances.

    PubMed

    Christensen, William F

    2011-09-01

    When predicting values for the measurement-error-free component of an observed spatial process, it is generally assumed that the process has a common measurement error variance. However, it is often the case that each measurement in a spatial data set has a known, site-specific measurement error variance, rendering the observed process nonstationary. We present a simple approach for estimating the semivariogram of the unobservable measurement-error-free process using a bias adjustment of the classical semivariogram formula. We then develop a new kriging predictor that filters the measurement errors. For scenarios where each site's measurement error variance is a function of the process of interest, we recommend an approach that also uses a variance-stabilizing transformation. The properties of the heterogeneous variance measurement-error-filtered kriging (HFK) predictor and variance-stabilized HFK predictor, and the improvement of these approaches over standard measurement-error-filtered kriging are demonstrated using simulation. The approach is illustrated with climate model output from the Hudson Strait area in northern Canada. In the illustration, locations with high or low measurement error variances are appropriately down- or upweighted in the prediction of the underlying process, yielding a realistically smooth picture of the phenomenon of interest.

  11. Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation

    NASA Technical Reports Server (NTRS)

    Wu, Dong L.; Eckermann, Stephen D.

    2008-01-01

    The gravity wave (GW)-resolving capabilities of 118-GHz saturated thermal radiances acquired throughout the stratosphere by the Microwave Limb Sounder (MLS) on the Aura satellite are investigated and initial results presented. Because the saturated (optically thick) radiances resolve GW perturbations from a given altitude at different horizontal locations, variances are evaluated at 12 pressure altitudes between 21 and 51 km using the 40 saturated radiances found at the bottom of each limb scan. Forward modeling simulations show that these variances are controlled mostly by GWs with vertical wavelengths z 5 km and horizontal along-track wavelengths of y 100-200 km. The tilted cigar-shaped three-dimensional weighting functions yield highly selective responses to GWs of high intrinsic frequency that propagate toward the instrument. The latter property is used to infer the net meridional component of GW propagation by differencing the variances acquired from ascending (A) and descending (D) orbits. Because of improved vertical resolution and sensitivity, Aura MLS GW variances are 5?8 times larger than those from the Upper Atmosphere Research Satellite (UARS) MLS. Like UARS MLS variances, monthly-mean Aura MLS variances in January and July 2005 are enhanced when local background wind speeds are large, due largely to GW visibility effects. Zonal asymmetries in variance maps reveal enhanced GW activity at high latitudes due to forcing by flow over major mountain ranges and at tropical and subtropical latitudes due to enhanced deep convective generation as inferred from contemporaneous MLS cloud-ice data. At 21-28-km altitude (heights not measured by the UARS MLS), GW variance in the tropics is systematically enhanced and shows clear variations with the phase of the quasi-biennial oscillation, in general agreement with GW temperature variances derived from radiosonde, rocketsonde, and limb-scan vertical profiles.

  12. Genotype-specific environmental impact on the variance of blood values in inbred and F1 hybrid mice.

    PubMed

    Klempt, Martina; Rathkolb, Birgit; Fuchs, Edith; de Angelis, Martin Hrabé; Wolf, Eckhard; Aigner, Bernhard

    2006-02-01

    Mice are important models for biomedical research because of the possibility of standardizing genetic background and environmental conditions, which both affect phenotypic variability. Inbred mouse strains as well as F1 hybrid mice are routinely used as genetically defined animal models; however, only a few studies investigated the variance of phenotypic parameters in inbred versus F1 hybrid mice and the potential interference of the genetic background with different housing conditions. Thus, we analyzed the ranges of clinical chemical and hematologic parameters in C3H and C57BL/6 inbred mice and their reciprocal F1 hybrids (B6C3F1, C3B6F1) in two different mouse facilities. Two thirds of the blood parameters examined in the same strain differed between the facilities for both the inbred strains and the F1 hybrid lines. The relation of the values between inbred and F1 hybrid mice was also affected by the facility. The variance of blood parameters in F1 hybrid mice compared with their parental inbred strains was inconsistent in one facility but generally smaller in the other facility. A subsequent study of F1 hybrid animals derived from the parental strains C3H and BALB/c, which was done in the latter housing unit, detected no general difference in the variance of blood parameters between F1 hybrid and inbred mice. Our study clearly demonstrates the possibility of major interactions between genotype and environment regarding the variance of clinical chemical and hematologic parameters.

  13. Chromatic visualization of reflectivity variance within hybridized directional OCT images

    NASA Astrophysics Data System (ADS)

    Makhijani, Vikram S.; Roorda, Austin; Bayabo, Jan Kristine; Tong, Kevin K.; Rivera-Carpio, Carlos A.; Lujan, Brandon J.

    2013-03-01

    This study presents a new method of visualizing hybridized images of retinal spectral domain optical coherence tomography (SDOCT) data comprised of varied directional reflectivity. Due to the varying reflectivity of certain retinal structures relative to angle of incident light, SDOCT images obtained with differing entry positions result in nonequivalent images of corresponding cellular and extracellular structures, especially within layers containing photoreceptor components. Harnessing this property, cross-sectional pathologic and non-pathologic macular images were obtained from multiple pupil entry positions using commercially-available OCT systems, and custom segmentation, alignment, and hybridization algorithms were developed to chromatically visualize the composite variance of reflectivity effects. In these images, strong relative reflectivity from any given direction visualizes as relative intensity of its corresponding color channel. Evident in non-pathologic images was marked enhancement of Henle's fiber layer (HFL) visualization and varying reflectivity patterns of the inner limiting membrane (ILM) and photoreceptor inner/outer segment junctions (IS/OS). Pathologic images displayed similar and additional patterns. Such visualization may allow a more intuitive understanding of structural and physiologic processes in retinal pathologies.

  14. Evolution of elaborate parental care: phenotypic and genetic correlations between parent and offspring traits

    PubMed Central

    Andrews, Clare P.; Kruuk, Loeske E. B.

    2017-01-01

    The evolution of elaborate forms of parental care is an important topic in behavioral ecology, yet the factors shaping the evolution of complex suites of parental and offspring traits are poorly understood. Here, we use a multivariate quantitative genetic approach to study phenotypic and genetic correlations between parental and offspring traits in the burying beetle Nicrophorus vespilloides. To this end, we recorded 2 prenatal traits (clutch size and egg size), 2 postnatal parental behaviors (direct care directed toward larvae and indirect care directed toward resource maintenance), 1 offspring behavior (begging), and 2 measures of breeding success (larval dispersal mass and number of dispersing larvae). Females breeding on larger carcasses provided less direct care but produced larger larvae than females breeding on smaller carcasses. Furthermore, there were positive phenotypic correlations between clutch size, direct, and indirect care. Both egg size and direct care were positively correlated with dispersal mass, whereas clutch size was negatively correlated with dispersal mass. Clutch size and number of dispersed larvae showed genetic variance both in terms of differences between populations of origin and significant heritabilities. However, we found no evidence of genetic variance underlying other parental or offspring traits. Our results suggest that correlations between suites of parental traits are driven by variation in individual quality rather than trade-offs, that some parental traits promote offspring growth while others increase the number of offspring produced, and that parental and offspring traits might respond slowly to selection due to low levels of additive genetic variance. PMID:28127224

  15. Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance.

    PubMed

    Hickey, John M; Veerkamp, Roel F; Calus, Mario P L; Mulder, Han A; Thompson, Robin

    2009-02-09

    Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo sampling can be used to calculate approximations of the prediction error variance, which converge to the true values if enough samples are used. However, in practical situations the number of samples, which are computationally feasible, is limited. The objective of this study was to compare the convergence rate of different formulations of the prediction error variance calculated using Monte Carlo sampling. Four of these formulations were published, four were corresponding alternative versions, and two were derived as part of this study. The different formulations had different convergence rates and these were shown to depend on the number of samples and on the level of prediction error variance. Four formulations were competitive and these made use of information on either the variance of the estimated breeding value and on the variance of the true breeding value minus the estimated breeding value or on the covariance between the true and estimated breeding values.

  16. Blinded sample size re-estimation in superiority and noninferiority trials: bias versus variance in variance estimation.

    PubMed

    Friede, Tim; Kieser, Meinhard

    2013-01-01

    The internal pilot study design allows for modifying the sample size during an ongoing study based on a blinded estimate of the variance thus maintaining the trial integrity. Various blinded sample size re-estimation procedures have been proposed in the literature. We compare the blinded sample size re-estimation procedures based on the one-sample variance of the pooled data with a blinded procedure using the randomization block information with respect to bias and variance of the variance estimators, and the distribution of the resulting sample sizes, power, and actual type I error rate. For reference, sample size re-estimation based on the unblinded variance is also included in the comparison. It is shown that using an unbiased variance estimator (such as the one using the randomization block information) for sample size re-estimation does not guarantee that the desired power is achieved. Moreover, in situations that are common in clinical trials, the variance estimator that employs the randomization block length shows a higher variability than the simple one-sample estimator and in turn the sample size resulting from the related re-estimation procedure. This higher variability can lead to a lower power as was demonstrated in the setting of noninferiority trials. In summary, the one-sample estimator obtained from the pooled data is extremely simple to apply, shows good performance, and is therefore recommended for application.

  17. Food additives

    MedlinePlus

    ... or natural. Natural food additives include: Herbs or spices to add flavor to foods Vinegar for pickling ... Certain colors improve the appearance of foods. Many spices, as well as natural and man-made flavors, ...

  18. 40 CFR 59.509 - Can I get a variance?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ...) NATIONAL VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Aerosol Coatings § 59.509 Can I get a variance? (a)...

  19. 40 CFR 59.509 - Can I get a variance?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ...) NATIONAL VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Aerosol Coatings § 59.509 Can I get a variance? (a)...

  20. RISK ANALYSIS, ANALYSIS OF VARIANCE: GETTING MORE FROM OUR DATA

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Analysis of variance (ANOVA) and regression are common statistical techniques used to analyze agronomic experimental data and determine significant differences among yields due to treatments or other experimental factors. Risk analysis provides an alternate and complimentary examination of the same...

  1. Some variance reduction methods for numerical stochastic homogenization.

    PubMed

    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.

  2. Bayesian adaptive Markov chain Monte Carlo estimation of genetic parameters.

    PubMed

    Mathew, B; Bauer, A M; Koistinen, P; Reetz, T C; Léon, J; Sillanpää, M J

    2012-10-01

    Accurate and fast estimation of genetic parameters that underlie quantitative traits using mixed linear models with additive and dominance effects is of great importance in both natural and breeding populations. Here, we propose a new fast adaptive Markov chain Monte Carlo (MCMC) sampling algorithm for the estimation of genetic parameters in the linear mixed model with several random effects. In the learning phase of our algorithm, we use the hybrid Gibbs sampler to learn the covariance structure of the variance components. In the second phase of the algorithm, we use this covariance structure to formulate an effective proposal distribution for a Metropolis-Hastings algorithm, which uses a likelihood function in which the random effects have been integrated out. Compared with the hybrid Gibbs sampler, the new algorithm had better mixing properties and was approximately twice as fast to run. Our new algorithm was able to detect different modes in the posterior distribution. In addition, the posterior mode estimates from the adaptive MCMC method were close to the REML (residual maximum likelihood) estimates. Moreover, our exponential prior for inverse variance components was vague and enabled the estimated mode of the posterior variance to be practically zero, which was in agreement with the support from the likelihood (in the case of no dominance). The method performance is illustrated using simulated data sets with replicates and field data in barley.

  3. Genetic control of leaf curl in maize.

    PubMed

    Entringer, G C; Guedes, F L; Oliveira, A A; Nascimento, J P; Souza, J C

    2014-03-17

    Among the many implications of climatic change on agriculture, drought is expected to continue to have a major impact on agribusinesses. Leaf curling is an anatomical characteristic that might be potentially used to enhance plant tolerance to water deficit. Hence, we aimed to study the genetic control of leaf curl in maize. From 2 contrasting inbred lines for the trait, generations F1, F2, and the backcrosses were obtained. All of these generations were evaluated in a randomized block design with 2 replicates. Leaf curl samples were collected from 3 leaves above the first ear at the tasseling stage, and quantified by dividing the width of the leaf blade with natural curling against its extended width. The mean and variance components were estimated by the weighted least square method. It was found that the trait studied has predominance of the additive effects, with genetic control being attributed to few genes that favor selection and exhibit minimal influence from the environment.

  4. Hidden item variance in multiple mini-interview scores.

    PubMed

    Zaidi, Nikki L Bibler; Swoboda, Christopher M; Kelcey, Benjamin M; Manuel, R Stephen

    2017-05-01

    The extant literature has largely ignored a potentially significant source of variance in multiple mini-interview (MMI) scores by "hiding" the variance attributable to the sample of attributes used on an evaluation form. This potential source of hidden variance can be defined as rating items, which typically comprise an MMI evaluation form. Due to its multi-faceted, repeated measures format, reliability for the MMI has been primarily evaluated using generalizability (G) theory. A key assumption of G theory is that G studies model the most important sources of variance to which a researcher plans to generalize. Because G studies can only attribute variance to the facets that are modeled in a G study, failure to model potentially substantial sources of variation in MMI scores can result in biased estimates of variance components. This study demonstrates the implications of hiding the item facet in MMI studies when true item-level effects exist. An extensive Monte Carlo simulation study was conducted to examine whether a commonly used hidden item, person-by-station (p × s|i) G study design results in biased estimated variance components. Estimates from this hidden item model were compared with estimates from a more complete person-by-station-by-item (p × s × i) model. Results suggest that when true item-level effects exist, the hidden item model (p × s|i) will result in biased variance components which can bias reliability estimates; therefore, researchers should consider using the more complete person-by-station-by-item model (p × s × i) when evaluating generalizability of MMI scores.

  5. Allan variance of time series models for measurement data

    NASA Astrophysics Data System (ADS)

    Zhang, Nien Fan

    2008-10-01

    The uncertainty of the mean of autocorrelated measurements from a stationary process has been discussed in the literature. However, when the measurements are from a non-stationary process, how to assess their uncertainty remains unresolved. Allan variance or two-sample variance has been used in time and frequency metrology for more than three decades as a substitute for the classical variance to characterize the stability of clocks or frequency standards when the underlying process is a 1/f noise process. However, its applications are related only to the noise models characterized by the power law of the spectral density. In this paper, from the viewpoint of the time domain, we provide a statistical underpinning of the Allan variance for discrete stationary processes, random walk and long-memory processes such as the fractional difference processes including the noise models usually considered in time and frequency metrology. Results show that the Allan variance is a better measure of the process variation than the classical variance of the random walk and the non-stationary fractional difference processes including the 1/f noise.

  6. Variance estimation in the analysis of microarray data.

    PubMed

    Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J

    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.

  7. Variance estimation for systematic designs in spatial surveys.

    PubMed

    Fewster, R M

    2011-12-01

    In spatial surveys for estimating the density of objects in a survey region, systematic designs will generally yield lower variance than random designs. However, estimating the systematic variance is well known to be a difficult problem. Existing methods tend to overestimate the variance, so although the variance is genuinely reduced, it is over-reported, and the gain from the more efficient design is lost. The current approaches to estimating a systematic variance for spatial surveys are to approximate the systematic design by a random design, or approximate it by a stratified design. Previous work has shown that approximation by a random design can perform very poorly, while approximation by a stratified design is an improvement but can still be severely biased in some situations. We develop a new estimator based on modeling the encounter process over space. The new "striplet" estimator has negligible bias and excellent precision in a wide range of simulation scenarios, including strip-sampling, distance-sampling, and quadrat-sampling surveys, and including populations that are highly trended or have strong aggregation of objects. We apply the new estimator to survey data for the spotted hyena (Crocuta crocuta) in the Serengeti National Park, Tanzania, and find that the reported coefficient of variation for estimated density is 20% using approximation by a random design, 17% using approximation by a stratified design, and 11% using the new striplet estimator. This large reduction in reported variance is verified by simulation.

  8. Genetic determination of fatty acid composition in Spanish Churra sheep milk.

    PubMed

    Sánchez, J P; San Primitivo, F; Barbosa, E; Varona, L; de la Fuente, L F

    2010-01-01

    The objective of this study was to estimate the genetic variation of ovine milk fatty acid (FA) composition. We collected 4,100 milk samples in 14 herds from 976 Churra ewes sired mostly by 15 AI rams and analyzed them by gas-liquid chromatography for milk fatty acid composition. The studied traits were 12 individual FA contents (proportion in relation to the total amount of FA), 3 groups of fatty acids [saturated fatty acids (SFA), monounsaturated FA (MUFA), and polyunsaturated FA (PUFA)], and 2 FA ratios (n-6:n-3 and C18:2 cis-9,trans-11:C18:1 trans-11). In addition, percentages of fat and protein and daily milk yield were studied. For the analysis, repeatability animal models were implemented using Bayesian methods. In an initial step, univariate methods were conducted to test the hypothesis of the traits showing additive genetic determination. Deviance information criterion and Bayes factor were employed as model choice criteria. All the studied SFA showed additive genetic variance, but the estimated heritabilities were low. Among unsaturated FA (UFA), only C18:1 trans-11 and C18:2 cis-9,cis-12 showed additive genetic variation, their estimated heritabilities being [marginal posterior mean (marginal posterior SD)] 0.02(0.01) and 0.11(0.04), respectively. For the FA groups, only PUFA showed significant additive genetic variation. None of the studied ratios of FA showed additive genetic variation. In second multitrait analyses, genetic correlations between individual FA and production traits, and between groups of FA and ratios of FA and production traits, were investigated. Positive genetic correlations were estimated among medium-chain SFA, ranging from 0 to 0.85, but this parameter was close to zero between long-chain SFA (C16:0 and C18:0). Between long- and medium-chain SFA, estimated genetic correlations were negative, around -0.6. Among those UFA showing significant additive genetic variance, genetic correlations were close to zero. The estimated genetic

  9. Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance.

    PubMed

    Bernardo, R

    1996-11-01

    Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06-0.35), smallest for moisture (0.00-0.02), and intermediate for yield (0.02-0.06) and stalk lodging (0.02-0.08). The ratio of dominance variance (v D) to total genetic variance (v G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that VD for a given trait has little contribution to VG. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.

  10. Genetic research: who is at risk for alcoholism.

    PubMed

    Foroud, Tatiana; Edenberg, Howard J; Crabbe, John C

    2010-01-01

    The National Institute on Alcohol Abuse and Alcoholism (NIAAA) was founded 40 years ago to help elucidate the biological underpinnings of alcohol dependence, including the potential contribution of genetic factors. Twin, adoption, and family studies conclusively demonstrated that genetic factors account for 50 to 60 percent of the variance in risk for developing alcoholism. Case-control studies and linkage analyses have helped identify DNA variants that contribute to increased risk, and the NIAAA-sponsored Collaborative Studies on Genetics of Alcoholism (COGA) has the expressed goal of identifying contributing genes using state-of-the-art genetic technologies. These efforts have ascertained several genes that may contribute to an increased risk of alcoholism, including certain variants encoding alcohol-metabolizing enzymes and neurotransmitter receptors. Genome-wide association studies allowing the analysis of millions of genetic markers located throughout the genome will enable discovery of further candidate genes. In addition to these human studies, genetic animal models of alcohol's effects and alcohol use have greatly advanced our understanding of the genetic basis of alcoholism, resulting in the identification of quantitative trait loci and allowing for targeted manipulation of candidate genes. Novel research approaches-for example, into epigenetic mechanisms of gene regulation-also are under way and undoubtedly will further clarify the genetic basis of alcoholism.

  11. Genetic and environmental influences on impulsivity: A meta-analysis of twin, family and adoption studies

    PubMed Central

    Bezdjian, Serena; Baker, Laura A.; Tuvblad, Catherine

    2011-01-01

    A meta-analysis of twin, family and adoption studies was conducted to estimate the magnitude of genetic and environmental influences on impulsivity. The best fitting model for 41 key studies (58 independent samples from 14 month old infants to adults; N = 27,147) included equal proportions of variance due to genetic (0.50) and non-shared environmental (0.50) influences, with genetic effects being both additive (0.38) and non-additive (0.12). Shared environmental effects were unimportant in explaining individual differences in impulsivity. Age, sex, and study design (twin vs. adoption) were all significant moderators of the magnitude of genetic and environmental influences on impulsivity. The relative contribution of genetic effects (broad sense heritability) and unique environmental effects were also found to be important throughout development from childhood to adulthood. Total genetic effects were found to be important for all ages, but appeared to be strongest in children. Analyses also demonstrated that genetic effects appeared to be stronger in males than in females. Method of assessment (laboratory tasks vs. questionnaires), however, was not a significant moderator of the genetic and environmental influences on impulsivity. These results provide a structured synthesis of existing behavior genetic studies on impulsivity by providing a clearer understanding of the relative genetic and environmental contributions in impulsive traits through various stages of development. PMID:21889436

  12. Genetic pleiotropy between asthma and obesity in a community-based sample of twins

    PubMed Central

    Hallstrand, Teal S.; Fischer, Mary E.; Wurfel, Mark M.; Afari, Niloofar; Buchwald, Dedra; Goldberg, Jack

    2007-01-01

    Background Asthma and obesity are common conditions that are strongly associated. This association might be due to shared genetic or environmental causes. Objective We sought to determine whether a shared genetic cause is responsible for the association between asthma and obesity and to estimate the magnitude of shared genetic cause. Methods The analyses were performed with 1001 monozygotic and 383 dizygotic same-sex twin pairs within the University of Washington Twin Registry. The presence of asthma was determined by self-report of a physician diagnosis of asthma, and body mass index (BMI) was calculated by using self-reported height and weight. Obesity was defined as a BMI of 30 or greater. The association between asthma and BMI was assessed by means of mixed-effects ordinal regression. Twin correlations examined the association of asthma and obesity. Univariate and bivariate structural equation models estimated the components of variance attributable to genetic and environmental effects. Results A strong association between asthma and BMI was identified in the sample population (P < .001). Substantial heritability was detected for asthma (53%) and obesity (77%), which is indicative of additive genetic influences on each disorder. The best-fitting model of shared components of variance indicated that 8% of the genetic component of obesity is shared with asthma. Conclusion The covariation between obesity and asthma is predominantly caused by shared genetic risk factors for both conditions. PMID:16337451

  13. A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

    PubMed

    Ben Taieb, Souhaib; Atiya, Amir F

    2016-01-01

    Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

  14. Variance analysis by use of a low cost desk top calculator.

    PubMed

    González Revaldería, J; Villafruela, J J; Sabater, J; Lamas, S; Ortuño, J

    1986-01-01

    A simple program for an HP-97 desk top calculator, which can be adapted to an HP-67, is presented. This program detects the presence of an added component of variance in any series classified with a unique criterion. Each series can be formed by any number of data. The program supplies additional information about this component. A brief theoretical description and a practical example are also included.

  15. Potlining Additives

    SciTech Connect

    Rudolf Keller

    2004-08-10

    In this project, a concept to improve the performance of aluminum production cells by introducing potlining additives was examined and tested. Boron oxide was added to cathode blocks, and titanium was dissolved in the metal pool; this resulted in the formation of titanium diboride and caused the molten aluminum to wet the carbonaceous cathode surface. Such wetting reportedly leads to operational improvements and extended cell life. In addition, boron oxide suppresses cyanide formation. This final report presents and discusses the results of this project. Substantial economic benefits for the practical implementation of the technology are projected, especially for modern cells with graphitized blocks. For example, with an energy savings of about 5% and an increase in pot life from 1500 to 2500 days, a cost savings of $ 0.023 per pound of aluminum produced is projected for a 200 kA pot.

  16. Phosphazene additives

    DOEpatents

    Harrup, Mason K; Rollins, Harry W

    2013-11-26

    An additive comprising a phosphazene compound that has at least two reactive functional groups and at least one capping functional group bonded to phosphorus atoms of the phosphazene compound. One of the at least two reactive functional groups is configured to react with cellulose and the other of the at least two reactive functional groups is configured to react with a resin, such as an amine resin of a polycarboxylic acid resin. The at least one capping functional group is selected from the group consisting of a short chain ether group, an alkoxy group, or an aryloxy group. Also disclosed are an additive-resin admixture, a method of treating a wood product, and a wood product.

  17. Genetic analysis of growth rate and Kleiber ratio in Zandi sheep.

    PubMed

    Ghafouri-Kesbi, Farhad; Abbasi, Mokhtar Ali; Afraz, Fazlollah; Babaei, Mohammad; Baneh, Hasan; Abdollahi Arpanahi, Rostam

    2011-08-01

    Genetic parameters for average daily gain from birth to weaning (ADGa), birth to 6 months (ADGb), weaning to 6 months (ADGc), weaning to yearling age (ADGd), and corresponding Kleiber ratios (KRa, KRb, KRc, and KRd) were estimated by using records of 3,533 Zandi lambs, descendent of 163 sires and 1265 dams, born between 1991 and 2005 at the Zandi Sheep Breeding Station at Khojir National Park, Tehran, Iran. A derivative-free algorithm combined with a series of six single-trait linear animal models was used to estimate phenotypic variance and its direct, maternal, and residual components. In addition, bivariate analyses were done to estimate (co)variance components between traits. Estimates of direct heritability (h(2)) were 0.11, 0.15, 0.09, 0.10, 0.10, 0.10, 0.06, and 0.07 for ADGa, ADGb, ADGc, ADGd, KRa, KRb, KRc, and KRd, respectively, thereby indicating the presence of low additive genetic variation for growth rate and Kleiber ratio in this population of Zandi sheep. Maternal genetic component was found to be significant on ADGa and KRa and contributed 3% and 5%, respectively, in total phenotypic variance of ADGa and KRa. A widespread range of genetic correlations among traits studied was observed. Except for negative genetic correlations between ADGa and KRc, ADGa and KRd, and between KRa and KRc, in other cases, genetic correlations were positive and moderate to very high. Phenotypic correlations ranged from -0.49 (ADGa/KRd) to 0.94 (ADGc/KRc). These results indicate that selecting for improved growth rate or Kleiber ratio in Zandi sheep would generate a relatively slow genetic progress.

  18. Estimation of Model Error Variances During Data Assimilation

    NASA Technical Reports Server (NTRS)

    Dee, Dick

    2003-01-01

    Data assimilation is all about understanding the error characteristics of the data and models that are used in the assimilation process. Reliable error estimates are needed to implement observational quality control, bias correction of observations and model fields, and intelligent data selection. Meaningful covariance specifications are obviously required for the analysis as well, since the impact of any single observation strongly depends on the assumed structure of the background errors. Operational atmospheric data assimilation systems still rely primarily on climatological background error covariances. To obtain error estimates that reflect both the character of the flow and the current state of the observing system, it is necessary to solve three problems: (1) how to account for the short-term evolution of errors in the initial conditions; (2) how to estimate the additional component of error caused by model defects; and (3) how to compute the error reduction in the analysis due to observational information. Various approaches are now available that provide approximate solutions to the first and third of these problems. However, the useful accuracy of these solutions very much depends on the size and character of the model errors and the ability to account for them. Model errors represent the real-world forcing of the error evolution in a data assimilation system. Clearly, meaningful model error estimates and/or statistics must be based on information external to the model itself. The most obvious information source is observational, and since the volume of available geophysical data is growing rapidly, there is some hope that a purely statistical approach to model error estimation can be viable. This requires that the observation errors themselves are well understood and quantifiable. We will discuss some of these challenges and present a new sequential scheme for estimating model error variances from observations in the context of an atmospheric data

  19. Accounting for heterogeneous variances in multitrait evaluation of Jersey type traits.

    PubMed

    Gengler, N; Wiggans, G R; Thornton, L L M; Wright, J R; Druet, T

    2006-08-01

    The multitrait genetic evaluation system for type traits was modified to estimate adjustments for heterogeneous variance (HV) simultaneously with estimated breeding values (EBV) for final score and 14 linear traits. Each variance within herd, year, and parity was regressed toward a predicted variance, which was determined by fitting a model with fixed effects of the mean final score for herd, size of the contemporary group, appraisal month, and year-season and a random effect for herd-appraisal date. Herd-appraisal date was included as a random effect to regress the observed heterogeneity for a given herd-appraisal date toward the fixed effects. Method R was used to estimate variances for the heterogeneity model in each EBV iteration. To evaluate the effect of the adjustment, parent averages were calculated from evaluations with recent appraisals removed. The adjustment slightly improved correlations within birth year between those parent averages and EBV from current data on bulls for most traits, but did not improve correlations for final score, strength, dairy form, teat length, or foot angle. Annual trends for EBV were lower with HV adjustment than for unadjusted EBV for all traits except final score and rump angle for cows and rump width for bulls, which were essentially unchanged. Standard deviations of Mendelian sampling (evaluation minus mean of parent evaluations) declined less over time for HV-adjusted than for unadjusted evaluations. The slope at year 2000 of Mendelian-sampling standard deviations from HV-adjusted evaluations ranged from 10.0% for udder depth to 42.7% for teat length compared with the slope for unadjusted evaluations. This HV adjustment, which was implemented for USDA evaluations in May 2001 for Jerseys and in 2002 for other breeds, improves the accuracy of evaluations, particularly comparisons over time, by accounting for the change in variation.

  20. Variance in male lifetime reproductive success and estimation of the degree of polygyny in a primate.

    PubMed

    Dubuc, Constance; Ruiz-Lambides, Angelina; Widdig, Anja

    2014-07-01

    The degree of polygyny is predicted to influence the strength of direct male-male competition, leading to a high variance in male lifetime reproductive success and to reproduction limited to the prime period of adulthood. Here, we explore the variance in male lifetime reproductive success and reproductive time in an anthropoid primate forming multimale-multifemale groups. Males of this species form dominance hierarchies, which are expected to skew reproduction toward few high-ranking males. At the same time, however, females mate with multiple males (polygynandry), which should limit the degree of polygyny. Using 20 years of genetic and demographic data, we calculated lifetime reproductive success for the free-ranging rhesus macaque (Macaca mulatta) population of Cayo Santiago for subjects that died naturally or reached senescence. Our results show that 1) male lifetime reproductive success was significantly skewed (range: 0-47 offspring; males reproducing below average: 62.8%; nonbreeders: 17.4%), 2) variance in male lifetime reproductive success was 5 times larger than in females, and 3) male lifetime reproductive success was more influenced by variation in fecundity (60%) than longevity (25%), suggesting that some direct male-male competition takes place. However, the opportunity for selection (i.e., standardized variance in male lifetime reproductive success) is low compared with that in other large mammal species characterized by a high degree of polygyny. Moreover, male reproductive life extended much beyond the prime period, showing that physical strength was not required to acquire mates. We conclude that rhesus macaques exhibit a moderate degree of polygyny and, therefore, low levels of direct male-male competition for fertile females, despite the fact that males form linear dominance hierarchies.

  1. Genetic effects of individual chromosomes in cotton cultivars detected by using chromosome substitution lines as genetic probes.

    PubMed

    Wu, Jixiang; Jenkins, Johnie N; McCarty, Jack C; Saha, Sukumar

    2010-12-01

    Determination of chromosomes or chromosome arms with desirable genes in different inbred lines and/or crosses should provide useful genetic information for crop improvement. In this study, we applied a modified additive-dominance model to analyze a data set of 13 cotton chromosome substitution lines and their recurrent parent TM-1, five commercial cultivars, and their 70 F(2) hybrids. The chromosome additive and dominance variance components for eight agronomic and fiber traits were determined. On average, each chromosome or chromosome arm was associated with 6.5 traits in terms of additive and/or dominance effects. The chromosomes or chromosome arms, which contributed significant additive variances for the traits investigated, included 2, 16, 18, 25, 5sh (short arm), 14sh, 15sh, 22sh, and 22Lo (long arm). Chromosome additive effects were also predicted in this study. The results showed that CS-B 25 was favorably associated with several fiber traits, while FM966 was favorably associated with both yield and fiber traits with alleles on multiple chromosomes or chromosome arms. Thus, this study should provide valuable genetic information on pure line development for several improved traits such as yield and fiber quality.

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

    PubMed Central

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

    2016-01-01

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

  3. Estimating Variances of Horizontal Wind Fluctuations in Stable Conditions

    NASA Astrophysics Data System (ADS)

    Luhar, Ashok K.

    2010-05-01

    Information concerning the average wind speed and the variances of lateral and longitudinal wind velocity fluctuations is required by dispersion models to characterise turbulence in the atmospheric boundary layer. When the winds are weak, the scalar average wind speed and the vector average wind speed need to be clearly distinguished and both lateral and longitudinal wind velocity fluctuations assume equal importance in dispersion calculations. We examine commonly-used methods of estimating these variances from wind-speed and wind-direction statistics measured separately, for example, by a cup anemometer and a wind vane, and evaluate the implied relationship between the scalar and vector wind speeds, using measurements taken under low-wind stable conditions. We highlight several inconsistencies inherent in the existing formulations and show that the widely-used assumption that the lateral velocity variance is equal to the longitudinal velocity variance is not necessarily true. We derive improved relations for the two variances, and although data under stable stratification are considered for comparison, our analysis is applicable more generally.

  4. Practice reduces task relevant variance modulation and forms nominal trajectory

    NASA Astrophysics Data System (ADS)

    Osu, Rieko; Morishige, Ken-Ichi; Nakanishi, Jun; Miyamoto, Hiroyuki; Kawato, Mitsuo

    2015-12-01

    Humans are capable of achieving complex tasks with redundant degrees of freedom. Much attention has been paid to task relevant variance modulation as an indication of online feedback control strategies to cope with motor variability. Meanwhile, it has been discussed that the brain learns internal models of environments to realize feedforward control with nominal trajectories. Here we examined trajectory variance in both spatial and temporal domains to elucidate the relative contribution of these control schemas. We asked subjects to learn reaching movements with multiple via-points, and found that hand trajectories converged to stereotyped trajectories with the reduction of task relevant variance modulation as learning proceeded. Furthermore, variance reduction was not always associated with task constraints but was highly correlated with the velocity profile. A model assuming noise both on the nominal trajectory and motor command was able to reproduce the observed variance modulation, supporting an expression of nominal trajectories in the brain. The learning-related decrease in task-relevant modulation revealed a reduction in the influence of optimal feedback around the task constraints. After practice, the major part of computation seems to be taken over by the feedforward controller around the nominal trajectory with feedback added only when it becomes necessary.

  5. Increased spatial variance accompanies reorganization of two continental shelf ecosystems.

    PubMed

    Litzow, Michael A; Urban, J Daniel; Laurel, Benjamin J

    2008-09-01

    Phase transitions between alternate stable states in marine ecosystems lead to disruptive changes in ecosystem services, especially fisheries productivity. We used trawl survey data spanning phase transitions in the North Pacific (Gulf of Alaska) and the North Atlantic (Scotian Shelf) to test for increases in ecosystem variability that might provide early warning of such transitions. In both time series, elevated spatial variability in a measure of community composition (ratio of cod [Gadus sp.] abundance to prey abundance) accompanied transitions between ecosystem states, and variability was negatively correlated with distance from the ecosystem transition point. In the Gulf of Alaska, where the phase transition was apparently the result of a sudden perturbation (climate regime shift), variance increased one year before the transition in mean state occurred. On the Scotian Shelf, where ecosystem reorganization was the result of persistent overfishing, a significant increase in variance occurred three years before the transition in mean state was detected. However, we could not reject the alternate explanation that increased variance may also have simply been inherent to the final stable state in that ecosystem. Increased variance has been previously observed around transition points in models, but rarely in real ecosystems, and our results demonstrate the possible management value in tracking the variance of key parameters in exploited ecosystems.

  6. Genetic Contribution to Biological Aging: The Framingham Study

    PubMed Central

    Karasik, David; Hannan, Marian T.; Cupples, L. Adrienne; Felson, David T.; Kiel, Douglas P.

    2005-01-01

    This study assessed the contribution of genetic and nongenetic factors to biological aging in American Caucasians. The studied sample included 1402 members of 288 pedigrees from the Framingham Heart Study. The original cohort participants received hand radiography in 1967–1969 (mean age, 58.7 years) and their offspring in 1992–1993 (mean age, 51.6 years). An osseographic score was applied to hand radiographs. Standardized residuals between Osseographic Scoring System-predicted age and actual age were used as a measure of biological age (BA). In variance component genetic analysis, sex, cohort, height, body mass index, and, in women, menopausal status and estrogen use, jointly explained approximately 6% of the total variance of BA. Genetic factors explained an additional 57%. Linkage analysis of covariate-adjusted BA suggested the presence of quantitative trait loci on chromosomes 3p, 7q, 11p, 16q, and 21q. In conclusion, the variation in BA measured by radiography was strongly governed by genetic factors in a sample of American adults. PMID:15031305

  7. Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study.

    PubMed

    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.

  8. Saturation of number variance in embedded random-matrix ensembles.

    PubMed

    Prakash, Ravi; Pandey, Akhilesh

    2016-05-01

    We study fluctuation properties of embedded random matrix ensembles of noninteracting particles. For ensemble of two noninteracting particle systems, we find that unlike the spectra of classical random matrices, correlation functions are nonstationary. In the locally stationary region of spectra, we study the number variance and the spacing distributions. The spacing distributions follow the Poisson statistics, which is a key behavior of uncorrelated spectra. The number variance varies linearly as in the Poisson case for short correlation lengths but a kind of regularization occurs for large correlation lengths, and the number variance approaches saturation values. These results are known in the study of integrable systems but are being demonstrated for the first time in random matrix theory. We conjecture that the interacting particle cases, which exhibit the characteristics of classical random matrices for short correlation lengths, will also show saturation effects for large correlation lengths.

  9. Monte Carlo variance reduction approaches for non-Boltzmann tallies

    SciTech Connect

    Booth, T.E.

    1992-12-01

    Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed.

  10. Impact of Damping Uncertainty on SEA Model Response Variance

    NASA Technical Reports Server (NTRS)

    Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

    2010-01-01

    Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

  11. Genetic control of the number of leaves above the ear in maize.

    PubMed

    Freire, A I; Dias, K O G; Oliveira, L B V; Nalin, R S; Guedes, F L; Souza, J C

    2015-02-13

    In this study, we examined the genetic control of the number of leaves above the first ear in maize. The F₂ generations and the backcrosses were obtained from 2 contrasting lines for this trait. All generations were assessed in a completely randomized block design with 2 replications. The number of leaves above the ear was counted when the plants were in the tasseling stage at the level of plants per plot. Mean and variance components were estimated using the weighted least square method. We observed a predominance of non-additive effects in the genetic control of number of leaves above the ear. These results indicate that this trait shows high heritability.

  12. The mean and variance of phylogenetic diversity under rarefaction.

    PubMed

    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.

  13. Enhancing area of review capabilities: Implementing a variance program

    SciTech Connect

    De Leon, F.

    1995-12-01

    The Railroad Commission of Texas (RRC) has regulated oil-field injection well operations since issuing its first injection permit in 1938. The Environmental Protection Agency (EPA) granted the RRC primary enforcement responsibility for the Class H Underground Injection Control (UIC) Program in April 1982. At that time, the added level of groundwater protection afforded by an Area of Review (AOR) on previously permitted Class H wells was not deemed necessary or cost effective. A proposed EPA rule change will require AORs to be performed on all pre-primacy Class II wells unless a variance can be justified. A variance methodology has been developed by researchers at the University of Missouri-Rolla in conjunction with the American Petroleum Institute (API). This paper will outline the RRC approach to implementing the AOR variance methodology. The RRC`s UIC program tracks 49,256 pre-primacy wells. Approximately 25,598 of these wells have active permits and will be subject to the proposed AOR requirements. The potential workload of performing AORs or granting variances for this many wells makes the development of a Geographic Information System (GIS) imperative. The RRC has recently completed a digitized map of the entire state and has spotted 890,000 of an estimated 1.2 million wells. Integrating this digital state map into a GIS will allow the RRC to tie its many data systems together. Once in place, this integrated data system will be used to evaluate AOR variances for pre-primacy wells on a field-wide basis. It will also reduce the regulatory cost of permitting by allowing the RRC staff to perform AORs or grant variances for the approximately 3,000 new and amended permit applications requiring AORs each year.

  14. The dynamic Allan Variance IV: characterization of atomic clock anomalies.

    PubMed

    Galleani, Lorenzo; Tavella, Patrizia

    2015-05-01

    The number of applications where precise clocks play a key role is steadily increasing, satellite navigation being the main example. Precise clock anomalies are hence critical events, and their characterization is a fundamental problem. When an anomaly occurs, the clock stability changes with time, and this variation can be characterized with the dynamic Allan variance (DAVAR). We obtain the DAVAR for a series of common clock anomalies, namely, a sinusoidal term, a phase jump, a frequency jump, and a sudden change in the clock noise variance. These anomalies are particularly common in space clocks. Our analytic results clarify how the clock stability changes during these anomalies.

  15. Entropy, Fisher Information and Variance with Frost-Musulin Potenial

    NASA Astrophysics Data System (ADS)

    Idiodi, J. O. A.; Onate, C. A.

    2016-09-01

    This study presents the Shannon and Renyi information entropy for both position and momentum space and the Fisher information for the position-dependent mass Schrödinger equation with the Frost-Musulin potential. The analysis of the quantum mechanical probability has been obtained via the Fisher information. The variance information of this potential is equally computed. This controls both the chemical properties and physical properties of some of the molecular systems. We have observed the behaviour of the Shannon entropy. Renyi entropy, Fisher information and variance with the quantum number n respectively.

  16. Studying Variance in the Galactic Ultra-compact Binary Population

    NASA Astrophysics Data System (ADS)

    Larson, Shane; Breivik, Katelyn

    2017-01-01

    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 on week-long timescales, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

  17. The principle of stationary variance in quantum field theory

    NASA Astrophysics Data System (ADS)

    Siringo, Fabio

    2014-02-01

    The principle of stationary variance is advocated as a viable variational approach to quantum field theory (QFT). The method is based on the principle that the variance of energy should be at its minimum when the state of a quantum system reaches its best approximation for an eigenstate. While not too much popular in quantum mechanics (QM), the method is shown to be valuable in QFT and three special examples are given in very different areas ranging from Heisenberg model of antiferromagnetism (AF) to quantum electrodynamics (QED) and gauge theories.

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

    PubMed

    Flores, E B; van der Werf, J

    2015-08-01

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

  19. The genetic and environmental relationship between Cloninger's dimensions of temperament and character.

    PubMed

    Gillespie, Nathan A; Cloninger, C Robert; Heath, Andrew C; Martin, Nicholas G

    2003-12-01

    The purpose of this study was to determine whether Cloninger's revised 7-factor model of personality showed incremental validity over his four dimensions of temperament. A sample of 2517 Australian twins aged over 50 between 1993 and 1995 returned completed self-reported measures of Self-directedness, Cooperativeness, and Self-transcendence from Cloninger's Temperament and Character Inventory. Many of these twins had participated in a 1988 study containing Cloninger's temperament measures of Harm Avoidance, Novelty Seeking, Reward Dependence and Persistence. Contrary to theoretical expectations, univariate analyses revealed that familial aggregation for the character dimensions could be entirely explained by additive gene action alone. Although temperament explained 26, 37 and 10% of additive genetic variance in Self-directedness, Cooperativeness and Self-transcendence, respectively, seven genetic factors were required to explain the genetic variance among the TPQ dimensions, and almost all of the non-shared environmental variance was unique to each dimension of character. Our results indicate that the inclusion of all seven dimensions in a taxonomy of personality is warranted.

  20. Variance components models for gene-environment interaction in twin analysis.

    PubMed

    Purcell, Shaun

    2002-12-01

    Gene-environment interaction is likely to be a common and important source of variation for complex behavioral traits. Often conceptualized as the genetic control of sensitivity to the environment, it can be incorporated in variance components twin analyses by partitioning genetic effects into a mean part, which is independent of the environment, and a part that is a linear function of the environment. The model allows for one or more environmental moderator variables (that possibly interact with each other) that may i). be continuous or binary ii). differ between twins within a pair iii). interact with residual environmental as well as genetic effects iv) have nonlinear moderating properties v). show scalar (different magnitudes) or qualitative (different genes) interactions vi). be correlated with genetic effects acting upon the trait, to allow for a test of gene-environment interaction in the presence of gene-environment correlation. Aspects and applications of a class of models are explored by simulation, in the context of both individual differences twin analysis and, in a companion paper (Purcell & Sham, 2002) sibpair quantitative trait locus linkage analysis. As well as elucidating environmental pathways, consideration of gene-environment interaction in quantitative and molecular studies will potentially direct and enhance gene-mapping efforts.

  1. Further results related to variance past lifetime class & associated orderings and their properties

    NASA Astrophysics Data System (ADS)

    Mahdy, Mervat

    2016-11-01

    If the random variable T denotes the lifetime of a unit, then the random variable T(t) = [ t - T ∣ T ≤ t ] , for a fixed t > 0, is known as the past lifetime. In this study, we present some new properties of the mean and variance for past lifetime classes (orderings). In addition, we consider an (n - r + 1) -out-of- n system with identical components where it is assumed that the lifetimes of the components are i.i.d. We assume that the system fails before time x, x > 0. Under these conditions, we are interested in studying the variance time elapsed since the failure of the components. Several properties of this function are studied and an example is provided. Finally, some applications in economic theory are described with real data.

  2. The application of analysis of variance (ANOVA) to different experimental designs in optometry.

    PubMed

    Armstrong, R A; Eperjesi, F; Gilmartin, B

    2002-05-01

    Analysis of variance (ANOVA) is the most efficient method available for the analysis of experimental data. Analysis of variance is a method of considerable complexity and subtlety, with many different variations, each of which applies in a particular experimental context. Hence, it is possible to apply the wrong type of ANOVA to data and, therefore, to draw an erroneous conclusion from an experiment. This article reviews the types of ANOVA most likely to arise in clinical experiments in optometry including the one-way ANOVA ('fixed' and 'random effect' models), two-way ANOVA in randomised blocks, three-way ANOVA, and factorial experimental designs (including the varieties known as 'split-plot' and 'repeated measures'). For each ANOVA, the appropriate experimental design is described, a statistical model is formulated, and the advantages and limitations of each type of design discussed. In addition, the problems of non-conformity to the statistical model and determination of the number of replications are considered.

  3. Variance stabilizing transformations in patch-based bilateral filters for poisson noise image denoising.

    PubMed

    de Deckerk, Arnaud; Lee, John Aldo; Verlysen, Michel

    2009-01-01

    Denoising is a key step in the processing of medical images. It aims at improving both the interpretability and visual aspect of the images. Yet, designing a robust and efficient denoising tool remains an unsolved challenge and a specific issue concerns the noise model. Many filters typically assume that noise is additive and Gaussian, with uniform variance. In contrast, noise in medical images often has more complex properties. This paper considers images with Poissonian noise and the patch-based bilateral filters, that is, filters that involve a tonal kernel and pair wise comparisons between shifted blocks of the images. The main aim is then to integrate two variance stabilizing transformations that allow the filters to work with Gaussianized noise. The performances of these filters are compared to those of the classical bilateral filter with the same transformations. The experiments include an artificial benchmark as well as a positron emission tomography image.

  4. Moose body mass variation revisited: disentangling effects of environmental conditions and genetics.

    PubMed

    Herfindal, Ivar; Haanes, Hallvard; Solberg, Erling J; Røed, Knut H; Høgda, Kjell Arild; Sæther, Bernt-Erik

    2014-02-01

    Large-scale geographical variation in phenotypic traits within species is often correlated to local environmental conditions and population density. Such phenotypic variation has recently been shown to also be influenced by genetic structuring of populations. In ungulates, large-scale geographical variation in phenotypic traits, such as body mass, has been related to environmental conditions and population density, but little is known about the genetic influences. Research on the genetic structure of moose suggests two distinct genetic lineages in Norway, structured along a north-south gradient. This corresponds with many environmental gradients, thus genetic structuring provides an additional factor affecting geographical phenotypic variation in Norwegian moose. We investigated if genetic structure explained geographical variation in body mass in Norwegian moose while accounting for environmental conditions, age and sex, and if it captured some of the variance in body mass that previously was attributed to environmental factors. Genetic structuring of moose was the most important variable in explaining the geographic variation in body mass within age and sex classes. Several environmental variables also had strong explanatory power, related to habitat diversity, environmental seasonality and winter harshness. The results suggest that environmental conditions, landscape characteristics, and genetic structure should be evaluated together when explaining large-scale patterns in phenotypic characters or life history traits. However, to better understand the role of genetic and environmental effects on phenotypic traits in moose, an extended individual-based study of variation in fitness-related characters is needed, preferably in an area of convergence between different genetic lineages.

  5. 10 CFR 52.93 - Exemptions and variances.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 2 2010-01-01 2010-01-01 false Exemptions and variances. 52.93 Section 52.93 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSES, CERTIFICATIONS, AND APPROVALS FOR NUCLEAR POWER PLANTS... referencing a nuclear power reactor manufactured under a manufacturing license issued under subpart F of...

  6. 10 CFR 52.93 - Exemptions and variances.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 2 2011-01-01 2011-01-01 false Exemptions and variances. 52.93 Section 52.93 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSES, CERTIFICATIONS, AND APPROVALS FOR NUCLEAR POWER PLANTS... referencing a nuclear power reactor manufactured under a manufacturing license issued under subpart F of...

  7. 10 CFR 52.93 - Exemptions and variances.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 2 2014-01-01 2014-01-01 false Exemptions and variances. 52.93 Section 52.93 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSES, CERTIFICATIONS, AND APPROVALS FOR NUCLEAR POWER PLANTS... referencing a nuclear power reactor manufactured under a manufacturing license issued under subpart F of...

  8. 10 CFR 52.93 - Exemptions and variances.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 10 Energy 2 2013-01-01 2013-01-01 false Exemptions and variances. 52.93 Section 52.93 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSES, CERTIFICATIONS, AND APPROVALS FOR NUCLEAR POWER PLANTS... referencing a nuclear power reactor manufactured under a manufacturing license issued under subpart F of...

  9. 10 CFR 52.93 - Exemptions and variances.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 2 2012-01-01 2012-01-01 false Exemptions and variances. 52.93 Section 52.93 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) LICENSES, CERTIFICATIONS, AND APPROVALS FOR NUCLEAR POWER PLANTS... referencing a nuclear power reactor manufactured under a manufacturing license issued under subpart F of...

  10. Variance Components for NLS: Partitioning the Design Effect.

    ERIC Educational Resources Information Center

    Folsom, Ralph E., Jr.

    This memorandum demonstrates a variance components methodology for partitioning the overall design effect (D) for a ratio mean into stratification (S), unequal weighting (W), and clustering (C) effects, so that D = WSC. In section 2, a sample selection scheme modeled after the National Longitudinal Study of the High School Class of 1972 (NKS)…

  11. Allan Variance Calculation for Nonuniformly Spaced Input Data

    DTIC Science & Technology

    2015-01-01

    Approved for public release; distribution is unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT The Allan Variance ( AV ) characterizes the...temporal randomness in sensor output data streams at various times scales. The conventional formula for calculating the AV assumes that the data...presents a modified approach to AV calculation, which accommodates nonuniformly spaced time samples. The basic concept of the modified approach is

  12. Variance in Math Achievement Attributable to Visual Cognitive Constructs

    ERIC Educational Resources Information Center

    Oehlert, Jeremy J.

    2012-01-01

    Previous research has reported positive correlations between math achievement and the cognitive constructs of spatial visualization, working memory, and general intelligence; however, no single study has assessed variance in math achievement attributable to all three constructs, examined in combination. The current study fills this gap in the…

  13. Temporal Relation Extraction in Outcome Variances of Clinical Pathways.

    PubMed

    Yamashita, Takanori; Wakata, Yoshifumi; Hamai, Satoshi; Nakashima, Yasuharu; Iwamoto, Yukihide; Franagan, Brendan; Nakashima, Naoki; Hirokawa, Sachio

    2015-01-01

    Recently the clinical pathway has progressed with digitalization and the analysis of activity. There are many previous studies on the clinical pathway but not many feed directly into medical practice. We constructed a mind map system that applies the spanning tree. This system can visualize temporal relations in outcome variances, and indicate outcomes that affect long-term hospitalization.

  14. 40 CFR 142.43 - Disposition of a variance request.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....43 Section 142.43 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the... issue a denial. Such notice shall include a statement of reasons for the proposed denial, and...

  15. Numbers Of Degrees Of Freedom Of Allan-Variance Estimators

    NASA Technical Reports Server (NTRS)

    Greenhall, Charles A.

    1992-01-01

    Report discusses formulas for estimation of Allan variances. Presents algorithms for closed-form approximations of numbers of degrees of freedom characterizing results obtained when various estimators applied to five power-law components of classical mathematical model of clock noise.

  16. 41 CFR 50-204.1a - Variances.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... PUBLIC CONTRACTS, DEPARTMENT OF LABOR 204-SAFETY AND HEALTH STANDARDS FOR FEDERAL SUPPLY CONTRACTS Scope... Public Contracts Act and the Occupational Safety and Health Act of 1970. ... 41 Public Contracts and Property Management 1 2013-07-01 2013-07-01 false Variances....

  17. 41 CFR 50-204.1a - Variances.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... PUBLIC CONTRACTS, DEPARTMENT OF LABOR 204-SAFETY AND HEALTH STANDARDS FOR FEDERAL SUPPLY CONTRACTS Scope... Public Contracts Act and the Occupational Safety and Health Act of 1970. ... 41 Public Contracts and Property Management 1 2014-07-01 2014-07-01 false Variances....

  18. 41 CFR 50-204.1a - Variances.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... PUBLIC CONTRACTS, DEPARTMENT OF LABOR 204-SAFETY AND HEALTH STANDARDS FOR FEDERAL SUPPLY CONTRACTS Scope... Public Contracts Act and the Occupational Safety and Health Act of 1970. ... 41 Public Contracts and Property Management 1 2010-07-01 2010-07-01 true Variances....

  19. 41 CFR 50-204.1a - Variances.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... PUBLIC CONTRACTS, DEPARTMENT OF LABOR 204-SAFETY AND HEALTH STANDARDS FOR FEDERAL SUPPLY CONTRACTS Scope... Public Contracts Act and the Occupational Safety and Health Act of 1970. ... 41 Public Contracts and Property Management 1 2012-07-01 2009-07-01 true Variances....

  20. The Variance of Intraclass Correlations in Three and Four Level

    ERIC Educational Resources Information Center

    Hedges, Larry V.; Hedberg, Eric C.; Kuyper, Arend M.

    2012-01-01

    Intraclass correlations are used to summarize the variance decomposition in popula- tions with multilevel hierarchical structure. There has recently been considerable interest in estimating intraclass correlations from surveys or designed experiments to provide design parameters for planning future large-scale randomized experiments. The large…

  1. 40 CFR 190.11 - Variances for unusual operations.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ....11 Section 190.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) RADIATION PROTECTION PROGRAMS ENVIRONMENTAL RADIATION PROTECTION STANDARDS FOR NUCLEAR POWER OPERATIONS Environmental Standards for the Uranium Fuel Cycle § 190.11 Variances for unusual operations. The standards specified...

  2. 40 CFR 190.11 - Variances for unusual operations.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ....11 Section 190.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) RADIATION PROTECTION PROGRAMS ENVIRONMENTAL RADIATION PROTECTION STANDARDS FOR NUCLEAR POWER OPERATIONS Environmental Standards for the Uranium Fuel Cycle § 190.11 Variances for unusual operations. The standards specified...

  3. 40 CFR 190.11 - Variances for unusual operations.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ....11 Section 190.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) RADIATION PROTECTION PROGRAMS ENVIRONMENTAL RADIATION PROTECTION STANDARDS FOR NUCLEAR POWER OPERATIONS Environmental Standards for the Uranium Fuel Cycle § 190.11 Variances for unusual operations. The standards specified...

  4. 40 CFR 190.11 - Variances for unusual operations.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....11 Section 190.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) RADIATION PROTECTION PROGRAMS ENVIRONMENTAL RADIATION PROTECTION STANDARDS FOR NUCLEAR POWER OPERATIONS Environmental Standards for the Uranium Fuel Cycle § 190.11 Variances for unusual operations. The standards specified...

  5. 40 CFR 190.11 - Variances for unusual operations.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ....11 Section 190.11 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) RADIATION PROTECTION PROGRAMS ENVIRONMENTAL RADIATION PROTECTION STANDARDS FOR NUCLEAR POWER OPERATIONS Environmental Standards for the Uranium Fuel Cycle § 190.11 Variances for unusual operations. The standards specified...

  6. Infinite variance in fermion quantum Monte Carlo calculations

    NASA Astrophysics Data System (ADS)

    Shi, Hao; Zhang, Shiwei

    2016-03-01

    For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.

  7. 21 CFR 821.2 - Exemptions and variances.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES MEDICAL DEVICE TRACKING REQUIREMENTS General Provisions § 821.2 Exemptions and variances. (a) A... following: (1) The name of the device and device class and representative labeling showing the intended...

  8. 21 CFR 821.2 - Exemptions and variances.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES MEDICAL DEVICE TRACKING REQUIREMENTS General Provisions § 821.2 Exemptions and variances. (a) A... following: (1) The name of the device and device class and representative labeling showing the intended...

  9. 21 CFR 821.2 - Exemptions and variances.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES MEDICAL DEVICE TRACKING REQUIREMENTS General Provisions § 821.2 Exemptions and variances. (a) A... following: (1) The name of the device and device class and representative labeling showing the intended...

  10. Perspective projection for variance pose face recognition from camera calibration

    NASA Astrophysics Data System (ADS)

    Fakhir, M. M.; Woo, W. L.; Chambers, J. A.; Dlay, S. S.

    2016-04-01

    Variance pose is an important research topic in face recognition. The alteration of distance parameters across variance pose face features is a challenging. We provide a solution for this problem using perspective projection for variance pose face recognition. Our method infers intrinsic camera parameters of the image which enable the projection of the image plane into 3D. After this, face box tracking and centre of eyes detection can be identified using our novel technique to verify the virtual face feature measurements. The coordinate system of the perspective projection for face tracking allows the holistic dimensions for the face to be fixed in different orientations. The training of frontal images and the rest of the poses on FERET database determine the distance from the centre of eyes to the corner of box face. The recognition system compares the gallery of images against different poses. The system initially utilises information on position of both eyes then focuses principally on closest eye in order to gather data with greater reliability. Differentiation between the distances and position of the right and left eyes is a unique feature of our work with our algorithm outperforming other state of the art algorithms thus enabling stable measurement in variance pose for each individual.

  11. Dominance, Information, and Hierarchical Scaling of Variance Space.

    ERIC Educational Resources Information Center

    Ceurvorst, Robert W.; Krus, David J.

    1979-01-01

    A method for computation of dominance relations and for construction of their corresponding hierarchical structures is presented. The link between dominance and variance allows integration of the mathematical theory of information with least squares statistical procedures without recourse to logarithmic transformations of the data. (Author/CTM)

  12. Explaining Common Variance Shared by Early Numeracy and Literacy

    ERIC Educational Resources Information Center

    Davidse, N. J.; De Jong, M. T.; Bus, A. G.

    2014-01-01

    How can it be explained that early literacy and numeracy share variance? We specifically tested whether the correlation between four early literacy skills (rhyming, letter knowledge, emergent writing, and orthographic knowledge) and simple sums (non-symbolic and story condition) reduced after taking into account preschool attention control,…

  13. The Threat of Common Method Variance Bias to Theory Building

    ERIC Educational Resources Information Center

    Reio, Thomas G., Jr.

    2010-01-01

    The need for more theory building scholarship remains one of the pressing issues in the field of HRD. Researchers can employ quantitative, qualitative, and/or mixed methods to support vital theory-building efforts, understanding however that each approach has its limitations. The purpose of this article is to explore common method variance bias as…

  14. Analysis of Variance: What Is Your Statistical Software Actually Doing?

    ERIC Educational Resources Information Center

    Li, Jian; Lomax, Richard G.

    2011-01-01

    Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…

  15. 40 CFR 52.1390 - Missoula variance provision.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 4 2014-07-01 2014-07-01 false Missoula variance provision. 52.1390 Section 52.1390 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS... from any requirement of an applicable implementation plan with respect to a stationary source....

  16. Comparison of Turbulent Thermal Diffusivity and Scalar Variance Models

    NASA Technical Reports Server (NTRS)

    Yoder, Dennis A.

    2016-01-01

    In this study, several variable turbulent Prandtl number formulations are examined for boundary layers, pipe flow, and axisymmetric jets. The model formulations include simple algebraic relations between the thermal diffusivity and turbulent viscosity as well as more complex models that solve transport equations for the thermal variance and its dissipation rate. Results are compared with available data for wall heat transfer and profile measurements of mean temperature, the root-mean-square (RMS) fluctuating temperature, turbulent heat flux and turbulent Prandtl number. For wall-bounded problems, the algebraic models are found to best predict the rise in turbulent Prandtl number near the wall as well as the log-layer temperature profile, while the thermal variance models provide a good representation of the RMS temperature fluctuations. In jet flows, the algebraic models provide no benefit over a constant turbulent Prandtl number approach. Application of the thermal variance models finds that some significantly overpredict the temperature variance in the plume and most underpredict the thermal growth rate of the jet. The models yield very similar fluctuating temperature intensities in jets from straight pipes and smooth contraction nozzles, in contrast to data that indicate the latter should have noticeably higher values. For the particular low subsonic heated jet cases examined, changes in the turbulent Prandtl number had no effect on the centerline velocity decay.

  17. Intuitive Analysis of Variance-- A Formative Assessment Approach

    ERIC Educational Resources Information Center

    Trumpower, David

    2013-01-01

    This article describes an assessment activity that can show students how much they intuitively understand about statistics, but also alert them to common misunderstandings. How the activity can be used formatively to help improve students' conceptual understanding of analysis of variance is discussed. (Contains 1 figure and 1 table.)

  18. Unbiased Estimates of Variance Components with Bootstrap Procedures

    ERIC Educational Resources Information Center

    Brennan, Robert L.

    2007-01-01

    This article provides general procedures for obtaining unbiased estimates of variance components for any random-model balanced design under any bootstrap sampling plan, with the focus on designs of the type typically used in generalizability theory. The results reported here are particularly helpful when the bootstrap is used to estimate standard…

  19. 40 CFR 124.64 - Appeals of variances.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 124.64 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS PROCEDURES...) When a State issues a permit on which EPA has made a variance decision, separate appeals of the State... issues in both proceedings, the Regional Administrator will decide, in consultation with State...

  20. Exploratory Multivariate Analysis of Variance: Contrasts and Variables.

    ERIC Educational Resources Information Center

    Barcikowski, Robert S.; Elliott, Ronald S.

    The contribution of individual variables to overall multivariate significance in a multivariate analysis of variance (MANOVA) is investigated using a combination of canonical discriminant analysis and Roy-Bose simultaneous confidence intervals. Difficulties with this procedure are discussed, and its advantages are illustrated using examples based…

  1. 20 CFR 901.40 - Proof; variance; amendment of pleadings.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Proof; variance; amendment of pleadings. 901.40 Section 901.40 Employees' Benefits JOINT BOARD FOR THE ENROLLMENT OF ACTUARIES REGULATIONS GOVERNING THE PERFORMANCE OF ACTUARIAL SERVICES UNDER THE EMPLOYEE RETIREMENT INCOME SECURITY ACT OF...

  2. 40 CFR 142.43 - Disposition of a variance request.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ....43 Section 142.43 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the... issue a denial. Such notice shall include a statement of reasons for the proposed denial, and...

  3. 36 CFR 30.5 - Variances, exceptions, and use permits.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... OF THE INTERIOR WHISKEYTOWN-SHASTA-TRINITY NATIONAL RECREATION AREA: ZONING STANDARDS FOR WHISKEYTOWN UNIT § 30.5 Variances, exceptions, and use permits. (a) Zoning ordinances or amendments thereto, for the zoning districts comprising the Whiskeytown Unit of the Whiskeytown-Shasta-Trinity...

  4. Infinite variance in fermion quantum Monte Carlo calculations.

    PubMed

    Shi, Hao; Zhang, Shiwei

    2016-03-01

    For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.

  5. 44 CFR 60.6 - Variances and exceptions.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... pattern inconsistent with the objectives of sound flood plain management, the Federal Insurance... (i) a showing of good and sufficient cause, (ii) a determination that failure to grant the variance... public expense, create nuisances, cause fraud on or victimization of the public, or conflict...

  6. 44 CFR 60.6 - Variances and exceptions.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... pattern inconsistent with the objectives of sound flood plain management, the Federal Insurance... (i) a showing of good and sufficient cause, (ii) a determination that failure to grant the variance... public expense, create nuisances, cause fraud on or victimization of the public, or conflict...

  7. Genetic Structure in Dwarf Bamboo (Bashania fangiana) Clonal Populations with Different Genet Ages

    PubMed Central

    Ma, Qing-qing; Song, Hui-xing; Zhou, Shi-qiang; Yang, Wan-qin; Li, De-sheng; Chen, Jin-song

    2013-01-01

    Amplified fragment length polymorphism (AFLP) fingerprints were used to reveal genotypic diversity of dwarf bamboo (Bashania fangiana) clonal populations with two different genet ages (≤30 years versus >70 years) at Wolong National Natural Reserve, Sichuan province, China. We generated AFLP fingerprints for 96 leaf samples, collected at 30 m intervals in the two populations, using ten selective primer pairs. A total of 92 genotypes were identified from the both populations. The mean proportion of distinguishable genotypes (G/N) was 0.9583 (0.9375 to 0.9792) and Simpson's index of diversity (D) was 0.9982 (0.9973 to 0.9991). So, two B. fangiana populations were multiclonal and highly diverse. The largest single clone may occur over a distance of about 30 m. Our results demonstrated that the genotypic diversity and genet density of B. fangiana clonal population did not change significantly (47 versus 45) with genet aging and low partitioned genetic differentiation was between the two populations (Gst = 0.0571). The analysis of molecular variance consistently showed that a large proportion of the genetic variation (87.79%) existed among the individuals within populations, whereas only 12.21% were found among populations. In addition, the high level of genotypic diversity in the two populations implies that the further works were needed to investigate the reasons for the poor seed set in B. fangiana after flowering. PMID:24244360

  8. 29 CFR 1905.11 - Variances and other relief under section 6(d).

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... ADMINISTRATION, DEPARTMENT OF LABOR RULES OF PRACTICE FOR VARIANCES, LIMITATIONS, VARIATIONS, TOLERANCES, AND..., Limitations, Variations, Tolerances, Exemptions and Other Relief § 1905.11 Variances and other relief...

  9. Gravity Wave Variances and Propagation Derived from AIRS Radiances

    NASA Technical Reports Server (NTRS)

    Gong, Jie; Wu, Dong L.; Eckermann, S. D.

    2012-01-01

    As the first gravity wave (GW) climatology study using nadir-viewing infrared sounders, 50 Atmospheric Infrared Sounder (AIRS) radiance channels are selected to estimate GW variances at pressure levels between 2-100 hPa. The GW variance for each scan in the cross-track direction is derived from radiance perturbations in the scan, independently of adjacent scans along the orbit. Since the scanning swaths are perpendicular to the satellite orbits, which are inclined meridionally at most latitudes, the zonal component of GW propagation can be inferred by differencing the variances derived between the westmost and the eastmost viewing angles. Consistent with previous GW studies using various satellite instruments, monthly mean AIRS variance shows large enhancements over meridionally oriented mountain ranges as well as some islands at winter hemisphere high latitudes. Enhanced wave activities are also found above tropical deep convective regions. GWs prefer to propagate westward above mountain ranges, and eastward above deep convection. AIRS 90 field-of-views (FOVs), ranging from +48 deg. to -48 deg. off nadir, can detect large-amplitude GWs with a phase velocity propagating preferentially at steep angles (e.g., those from orographic and convective sources). The annual cycle dominates the GW variances and the preferred propagation directions for all latitudes. Indication of a weak two-year variation in the tropics is found, which is presumably related to the Quasi-biennial oscillation (QBO). AIRS geometry makes its out-tracks capable of detecting GWs with vertical wavelengths substantially shorter than the thickness of instrument weighting functions. The novel discovery of AIRS capability of observing shallow inertia GWs will expand the potential of satellite GW remote sensing and provide further constraints on the GW drag parameterization schemes in the general circulation models (GCMs).

  10. Hydrograph variances over different timescales in hydropower production networks

    NASA Astrophysics Data System (ADS)

    Zmijewski, Nicholas; Wörman, Anders

    2016-08-01

    The operation of water reservoirs involves a spectrum of timescales based on the distribution of stream flow travel times between reservoirs, as well as the technical, environmental, and social constraints imposed on the operation. In this research, a hydrodynamically based description of the flow between hydropower stations was implemented to study the relative importance of wave diffusion on the spectrum of hydrograph variance in a regulated watershed. Using spectral decomposition of the effluence hydrograph of a watershed, an exact expression of the variance in the outflow response was derived, as a function of the trends of hydraulic and geomorphologic dispersion and management of production and reservoirs. We show that the power spectra of involved time-series follow nearly fractal patterns, which facilitates examination of the relative importance of wave diffusion and possible changes in production demand on the outflow spectrum. The exact spectral solution can also identify statistical bounds of future demand patterns due to limitations in storage capacity. The impact of the hydraulic description of the stream flow on the reservoir discharge was examined for a given power demand in River Dalälven, Sweden, as function of a stream flow Peclet number. The regulation of hydropower production on the River Dalälven generally increased the short-term variance in the effluence hydrograph, whereas wave diffusion decreased the short-term variance over periods of <1 week, depending on the Peclet number (Pe) of the stream reach. This implies that flow variance becomes more erratic (closer to white noise) as a result of current production objectives.

  11. Variance in the reproductive success of dominant male mountain gorillas.

    PubMed

    Robbins, Andrew M; Gray, Maryke; Uwingeli, Prosper; Mburanumwe, Innocent; Kagoda, Edwin; Robbins, Martha M

    2014-10-01

    Using 30 years of demographic data from 15 groups, this study estimates how harem size, female fertility, and offspring survival may contribute to variance in the siring rates of dominant male mountain gorillas throughout the Virunga Volcano Region. As predicted for polygynous species, differences in harem size were the greatest source of variance in the siring rate, whereas differences in female fertility and offspring survival were relatively minor. Harem size was positively correlated with offspring survival, even after removing all known and suspected cases of infanticide, so the correlation does not seem to reflect differences in the ability of males to protect their offspring. Harem size was not significantly correlated with female fertility, which is consistent with the hypothesis that mountain gorillas have minimal feeding competition. Harem size, offspring survival, and siring rates were not significantly correlated with the proportion of dominant tenures that occurred in multimale groups versus one-male groups; even though infanticide is less likely when those tenures end in multimale groups than one-male groups. In contrast with the relatively small contribution of offspring survival to variance in the siring rates of this study, offspring survival is a major source of variance in the male reproductive success of western gorillas, which have greater predation risks and significantly higher rates of infanticide. If differences in offspring protection are less important among male mountain gorillas than western gorillas, then the relative importance of other factors may be greater for mountain gorillas. Thus, our study illustrates how variance in male reproductive success and its components can differ between closely related species.

  12. The efficiency of close inbreeding to reduce genetic adaptation to captivity.

    PubMed

    Theodorou, K; Couvet, D

    2015-01-01

    Although ex situ conservation is indispensable for thousands of species, captive breeding is associated with negative genetic changes: loss of genetic variance and genetic adaptation to captivity that is deleterious in the wild. We used quantitative genetic individual-based simulations to model the effect of genetic management on the evolution of a quantitative trait and the associated fitness of wild-born individuals that are brought to captivity. We also examined the feasibility of the breeding strategies under a scenario of a large number of loci subject to deleterious mutations. We compared two breeding strategies: repeated half-sib mating and a method of minimizing mean coancestry (referred to as gc/mc). Our major finding was that half-sib mating is more effective in reducing genetic adaptation to captivity than the gc/mc method. Moreover, half-sib mating retains larger allelic and adaptive genetic variance. Relative to initial standing variation, the additive variance of the quantitative trait increased under half-sib mating during the sojourn in captivity. Although fragmentation into smaller populations improves the efficiency of the gc/mc method, half-sib mating still performs better in the scenarios tested. Half-sib mating shows two caveats that could mitigate its beneficial effects: low heterozygosity and high risk of extinction when populations are of low fecundity and size and one of the following conditions are met: (i) the strength of selection in captivity is comparable with that in the wild, (ii) deleterious mutations are numerous and only slightly deleterious. Experimental validation of half-sib mating is therefore needed for the advancement of captive breeding programs.

  13. Genetic control of inflorescence in common bean.

    PubMed

    Guilherme, S R; Ramalho, M A P; de F B Abreu, A; Pereira, L A

    2014-12-04

    The number of pods per common bean plant is a primary component of grain yield, which depends on the number of flowers produced and on the flower set. Thus, a larger number of flowers per plant would increase yield. Lines with inflorescences that had a large number of flowers compared to common bean plants now under cultivation were identified. We analyzed the genetic control of this trait and its association with grain yield. The cultivar BRSMG Talismã was crossed with 2 lines, L.59583 and L.59692, which have a large number of flowers. The F1, F2, and F3 generations were obtained. These generations were assessed together with the parents in a randomized block experimental design with 2 replications. The traits assessed included length of inflorescence, number of pods per inflorescence, number of pods per plant, number of grains per plant, 100-grain weight, and grain yield per plant. Mean genetic components and variance were estimated. The traits length of inflorescence and number of pods per inflorescence exhibited genetic control with predominance that showed an additive effect. In the 2 crosses, genetic control of grain yield and of its primary components showed that the allelic interaction of dominance was high. The wide variability in the traits assessed may be used to increase yield of the common bean plant by increasing the number of flowers on the plant.

  14. Species interactions differ in their genetic robustness

    DOE PAGES

    Chubiz, Lon M.; Granger, Brian R.; Segre, Daniel; ...

    2015-04-14

    Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S.more » enterica. The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.« less

  15. Sampling-variance effects on detecting density dependence from temporal trends in natural populations

    USGS Publications Warehouse

    Shenk, T.M.; White, Gary C.; Burnham, K.P.

    1998-01-01

    Monte Carlo simulations were conducted to evaluate robustness of four tests to detect density dependence, from series of population abundances, to the addition of sampling variance. Population abundances were generated from random walk, stochastic exponential growth, and density-dependent population models. Population abundance estimates were generated with sampling variances distributed as lognormal and constant coefficients of variation (cv) from 0.00 to 1.00. In general, when data were generated under a random walk, Type I error rates increased rapidly for Bulmer's R, Pollard et al.'s, and Dennis and Taper's tests with increasing magnitude of sampling variance for n > 5 yr and all values of process variation. Bulmer's R* test maintained a constant 5% Type I error rate for n > 5 yr and all magnitudes of sampling variance in the population abundance estimates. When abundances were generated from two stochastic exponential growth models (R = 0.05 and R = 0.10), Type I errors again increased with increasing sampling variance; magnitude of Type I error rates were higher for the slower growing population. Therefore, sampling error inflated Type I error rates, invalidating the tests, for all except Bulmer's R* test. Comparable simulations for abundance estimates generated from a density-dependent growth rate model were conducted to estimate power of the tests. Type II error rates were influenced by the relationship of initial population size to carrying capacity (K), length of time series, as well as sampling error. Given the inflated Type I error rates for all but Bulmer, s R*, power was overestimated for the remaining tests, resulting in density: dependence being detected more often than it existed. Population abundances of natural populations are almost exclusively estimated rather than censused, assuring sampling error. Therefore, because these tests have been shown to be either invalid when only sampling variance occurs in the population abundances (Bulmer's R

  16. Hierarchical Bayesian modeling of heterogeneous variances in average daily weight gain of commercial feedlot cattle.

    PubMed

    Cernicchiaro, N; Renter, D G; Xiang, S; White, B J; Bello, N M

    2013-06-01

    Variability in ADG of feedlot cattle can affect profits, thus making overall returns more unstable. Hence, knowledge of the factors that contribute to heterogeneity of variances in animal performance can help feedlot managers evaluate risks and minimize profit volatility when making managerial and economic decisions in commercial feedlots. The objectives of the present study were to evaluate heteroskedasticity, defined as heterogeneity of variances, in ADG of cohorts of commercial feedlot cattle, and to identify cattle demographic factors at feedlot arrival as potential sources of variance heterogeneity, accounting for cohort- and feedlot-level information in the data structure. An operational dataset compiled from 24,050 cohorts from 25 U. S. commercial feedlots in 2005 and 2006 was used for this study. Inference was based on a hierarchical Bayesian model implemented with Markov chain Monte Carlo, whereby cohorts were modeled at the residual level and feedlot-year clusters were modeled as random effects. Forward model selection based on deviance information criteria was used to screen potentially important explanatory variables for heteroskedasticity at cohort- and feedlot-year levels. The Bayesian modeling framework was preferred as it naturally accommodates the inherently hierarchical structure of feedlot data whereby cohorts are nested within feedlot-year clusters. Evidence for heterogeneity of variance components of ADG was substantial and primarily concentrated at the cohort level. Feedlot-year specific effects were, by far, the greatest contributors to ADG heteroskedasticity among cohorts, with an estimated ∼12-fold change in dispersion between most and least extreme feedlot-year clusters. In addition, identifiable demographic factors associated with greater heterogeneity of cohort-level variance included smaller cohort sizes, fewer days on feed, and greater arrival BW, as well as feedlot arrival during summer months. These results support that

  17. Increased genetic risk for obesity in premature coronary artery disease.

    PubMed

    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.

  18. Genetic and environmental influences on the continuous scales of the Myers-Briggs Type Indicator: an analysis based on twins reared apart.

    PubMed

    Bouchard, T J; Hur, Y M

    1998-04-01

    The Myers-Briggs Type Indicator was administered to a sample of 61 monozygotic twins reared apart (MZA), 49 dizygotic twins reared apart (DZA), and 92 spouses, who participated in the Minnesota Study of Twins Reared Apart (MISTRA) from 1979 to 1995. Twins' scores on the continuous scales were subjected to behavior genetic model-fitting procedures. Extraversion-Introversion and Thinking-Feeling yielded heritabilities of about .60, consisting largely of nonadditive genetic variance. Sensing-Intuition and Judgment-Perception yielded heritabilities of about .40, consisting largely of additive genetic variance. Spouse correlations for three of the four scales were near zero and not statistically significant; one spouse correlation (Sensing-Intuition) was modestly positive and statistically significant.

  19. NASTRAN variance analysis and plotting of HBDY elements. [analysis of uncertainties of the computer results as a function of uncertainties in the input data

    NASA Technical Reports Server (NTRS)

    Harder, R. L.

    1974-01-01

    The NASTRAN Thermal Analyzer has been intended to do variance analysis and plot the thermal boundary elements. The objective of the variance analysis addition is to assess the sensitivity of temperature variances resulting from uncertainties inherent in input parameters for heat conduction analysis. The plotting capability provides the ability to check the geometry (location, size and orientation) of the boundary elements of a model in relation to the conduction elements. Variance analysis is the study of uncertainties of the computed results as a function of uncertainties of the input data. To study this problem using NASTRAN, a solution is made for both the expected values of all inputs, plus another solution for each uncertain variable. A variance analysis module subtracts the results to form derivatives, and then can determine the expected deviations of output quantities.

  20. On the measurement of frequency and of its sample variance with high-resolution counters

    SciTech Connect

    Rubiola, Enrico

    2005-05-15

    A frequency counter measures the input frequency {nu} averaged over a suitable time {tau}, versus the reference clock. High resolution is achieved by interpolating the clock signal. Further increased resolution is obtained by averaging multiple frequency measurements highly overlapped. In the presence of additive white noise or white phase noise, the square uncertainty improves from {sigma}{sub {nu}}{sup 2}{proportional_to}1/{tau}{sup 2} to {sigma}{sub {nu}}{sup 2}{proportional_to}1/{tau}{sup 3}. Surprisingly, when a file of contiguous data is fed into the formula of the two-sample (Allan) variance {sigma}{sub y}{sup 2}({tau})=E{l_brace}(1/2)(y{sub k+1}-y{sub k}){sup 2}{r_brace} of the fractional frequency fluctuation y, the result is the modified Allan variance mod {sigma}{sub y}{sup 2}({tau}). But if a sufficient number of contiguous measures are averaged in order to get a longer {tau} and the data are fed into the same formula, the results is the (nonmodified) Allan variance. Of course interpretation mistakes are around the corner if the counter internal process is not well understood. The typical domain of interest is the the short-term stability measurement of oscillators.