Genetic quality and sexual selection: an integrated framework for good genes and compatible genes.

PubMed

Neff, Bryan D; Pitcher, Trevor E

2005-01-01

Why are females so choosy when it comes to mating? This question has puzzled and marveled evolutionary and behavioral ecologists for decades. In mating systems in which males provide direct benefits to the female or her offspring, such as food or shelter, the answer seems straightforward--females should prefer to mate with males that are able to provide more resources. The answer is less clear in other mating systems in which males provide no resources (other than sperm) to females. Theoretical models that account for the evolution of mate choice in such nonresource-based mating systems require that females obtain a genetic benefit through increased offspring fitness from their choice. Empirical studies of nonresource-based mating systems that are characterized by strong female choice for males with elaborate sexual traits (like the large tail of peacocks) suggest that additive genetic benefits can explain only a small percentage of the variation in fitness. Other research on genetic benefits has examined nonadditive effects as another source of genetic variation in fitness and a potential benefit to female mate choice. In this paper, we review the sexual selection literature on genetic quality to address five objectives. First, we attempt to provide an integrated framework for discussing genetic quality. We propose that the term 'good gene' be used exclusively to refer to additive genetic variation in fitness, 'compatible gene' be used to refer to nonadditive genetic variation in fitness, and 'genetic quality' be defined as the sum of the two effects. Second, we review empirical approaches used to calculate the effect size of genetic quality and discuss these approaches in the context of measuring benefits from good genes, compatible genes and both types of genes. Third, we discuss biological mechanisms for acquiring and promoting offspring genetic quality and categorize these into three stages during breeding: (i) precopulatory (mate choice); (ii) postcopulatory, prefertilization (sperm utilization); and (iii) postcopulatory, postfertilization (differential investment). Fourth, we present a verbal model of the effect of good genes sexual selection and compatible genes sexual selection on population genetic variation in fitness, and discuss the potential trade-offs that might exist between mate choice for good genes and mate choice for compatible genes. Fifth, we discuss some future directions for research on genetic quality and sexual selection.

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus).

PubMed

Pereira, R J; Ayres, D R; El Faro, L; Verneque, R S; Vercesi Filho, A E; Albuquerque, L G

2013-09-27

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields.

Genetic Stability of Cognitive Development from Childhood to Adulthood.

ERIC Educational Resources Information Center

DeFries, J. C.; And Others

1987-01-01

A path model of genetic and family environmental transmission was fitted to published twin correlations and to general cognitive ability data from adoptive and nonadoptive families in which children were tested yearly through the fourth year. Longitudinal genetic correlations from infancy to adulthood were modeled explicitly, as were effects of…

Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle

PubMed Central

Cho, C. I.; Alam, M.; Choi, T. J.; Choy, Y. H.; Choi, J. G.; Lee, S. S.; Cho, K. H.

2016-01-01

The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3–L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of polynomials×3 types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea. PMID:26954184

Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle.

PubMed

Cho, C I; Alam, M; Choi, T J; Choy, Y H; Choi, J G; Lee, S S; Cho, K H

2016-05-01

The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3-L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of polynomials×3 types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea.

Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

PubMed Central

Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

2013-01-01

In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

Correlates of male fitness in captive zebra finches--a comparison of methods to disentangle genetic and environmental effects.

PubMed

Bolund, Elisabeth; Schielzeth, Holger; Forstmeier, Wolfgang

2011-11-08

It is a common observation in evolutionary studies that larger, more ornamented or earlier breeding individuals have higher fitness, but that body size, ornamentation or breeding time does not change despite of sometimes substantial heritability for these traits. A possible explanation for this is that these traits do not causally affect fitness, but rather happen to be indirectly correlated with fitness via unmeasured non-heritable aspects of condition (e.g. undernourished offspring grow small and have low fitness as adults due to poor health). Whether this explanation applies to a specific case can be examined by decomposing the covariance between trait and fitness into its genetic and environmental components using pedigree-based animal models. We here examine different methods of doing this for a captive zebra finch population where male fitness was measured in communal aviaries in relation to three phenotypic traits (tarsus length, beak colour and song rate). Our case study illustrates how methods that regress fitness over breeding values for phenotypic traits yield biased estimates as well as anti-conservative standard errors. Hence, it is necessary to estimate the genetic and environmental covariances between trait and fitness directly from a bivariate model. This method, however, is very demanding in terms of sample sizes. In our study parameter estimates of selection gradients for tarsus were consistent with the hypothesis of environmentally induced bias (βA=0.035±0.25 (SE), βE=0.57±0.28 (SE)), yet this differences between genetic and environmental selection gradients falls short of statistical significance. To examine the generality of the idea that phenotypic selection gradients for certain traits (like size) are consistently upwardly biased by environmental covariance a meta-analysis across study systems will be needed.

Correlates of male fitness in captive zebra finches - a comparison of methods to disentangle genetic and environmental effects

PubMed Central

2011-01-01

Backgound It is a common observation in evolutionary studies that larger, more ornamented or earlier breeding individuals have higher fitness, but that body size, ornamentation or breeding time does not change despite of sometimes substantial heritability for these traits. A possible explanation for this is that these traits do not causally affect fitness, but rather happen to be indirectly correlated with fitness via unmeasured non-heritable aspects of condition (e.g. undernourished offspring grow small and have low fitness as adults due to poor health). Whether this explanation applies to a specific case can be examined by decomposing the covariance between trait and fitness into its genetic and environmental components using pedigree-based animal models. We here examine different methods of doing this for a captive zebra finch population where male fitness was measured in communal aviaries in relation to three phenotypic traits (tarsus length, beak colour and song rate). Results Our case study illustrates how methods that regress fitness over breeding values for phenotypic traits yield biased estimates as well as anti-conservative standard errors. Hence, it is necessary to estimate the genetic and environmental covariances between trait and fitness directly from a bivariate model. This method, however, is very demanding in terms of sample sizes. In our study parameter estimates of selection gradients for tarsus were consistent with the hypothesis of environmentally induced bias (βA = 0.035 ± 0.25 (SE), βE = 0.57 ± 0.28 (SE)), yet this differences between genetic and environmental selection gradients falls short of statistical significance. Conclusions To examine the generality of the idea that phenotypic selection gradients for certain traits (like size) are consistently upwardly biased by environmental covariance a meta-analysis across study systems will be needed. PMID:22067225

Life events and personality in late adolescence: genetic and environmental relations.

PubMed

Billig, J P; Hershberger, S L; Iacono, W G; McGue, M

1996-11-01

The relationship between life events and personality was investigated in the Minnesota Twin/Family Study, using 216 monozygotic and 114 dizygotic 17-year-old male twin pairs. Participants completed a life events interview designed for adolescents and the Multidimensional Personality Questionnaire. Life events were categorized into three types: life events to which all members of a family would be subject and those affecting an individual, which can be broadly construed as either nonindependent or independent. Univariate genetic model fitting indicated the presence of significant genetic effects (h2 = 49%) for nonindependent nonfamily life events but not for the other two types of life events. Bivariate genetic model fitting further confirmed that the significant phenotypic correlation between nonindependent life events and personality is in part genetically mediated. Specifically, the findings suggest that genetically influenced individual differences in constraint play a substantial role in life events whose occurrence is not independent of the individual's behavior.

On Using Surrogates with Genetic Programming.

PubMed

Hildebrandt, Torsten; Branke, Jürgen

2015-01-01

One way to accelerate evolutionary algorithms with expensive fitness evaluations is to combine them with surrogate models. Surrogate models are efficiently computable approximations of the fitness function, derived by means of statistical or machine learning techniques from samples of fully evaluated solutions. But these models usually require a numerical representation, and therefore cannot be used with the tree representation of genetic programming (GP). In this paper, we present a new way to use surrogate models with GP. Rather than using the genotype directly as input to the surrogate model, we propose using a phenotypic characterization. This phenotypic characterization can be computed efficiently and allows us to define approximate measures of equivalence and similarity. Using a stochastic, dynamic job shop scenario as an example of simulation-based GP with an expensive fitness evaluation, we show how these ideas can be used to construct surrogate models and improve the convergence speed and solution quality of GP.

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

PubMed Central

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

2016-01-01

Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother’s old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother’s old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington’s genetic assimilation. Our model is able to quantify the evolution of the assimilation because it characterizes the fitness consequences of variation. PMID:26761487

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

PubMed

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

2016-01-01

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

FITPOP, a heuristic simulation model of population dynamics and genetics with special reference to fisheries

USGS Publications Warehouse

McKenna, James E.

2000-01-01

Although, perceiving genetic differences and their effects on fish population dynamics is difficult, simulation models offer a means to explore and illustrate these effects. I partitioned the intrinsic rate of increase parameter of a simple logistic-competition model into three components, allowing specification of effects of relative differences in fitness and mortality, as well as finite rate of increase. This model was placed into an interactive, stochastic environment to allow easy manipulation of model parameters (FITPOP). Simulation results illustrated the effects of subtle differences in genetic and population parameters on total population size, overall fitness, and sensitivity of the system to variability. Several consequences of mixing genetically distinct populations were illustrated. For example, behaviors such as depression of population size after initial introgression and extirpation of native stocks due to continuous stocking of genetically inferior fish were reproduced. It also was shown that carrying capacity relative to the amount of stocking had an important influence on population dynamics. Uncertainty associated with parameter estimates reduced confidence in model projections. The FITPOP model provided a simple tool to explore population dynamics, which may assist in formulating management strategies and identifying research needs.

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials.

PubMed

Mota, L F M; Martins, P G M A; Littiere, T O; Abreu, L R A; Silva, M A; Bonafé, C M

2018-04-01

The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

Effects of genetic distance on heterosis in a Drosophila melanogaster model system.

PubMed

Jensen, Charlotte; Ørsted, Michael; Kristensen, Torsten Nygaard

2018-05-14

Habitat fragmentation and small population sizes can lead to inbreeding and loss of genetic variation, which can potentially cause inbreeding depression and decrease the ability of populations to adapt to altered environmental conditions. One solution to these genetic problems is the implementation of genetic rescue, which re-establishes gene flow between separated populations. Similar techniques are being used in animal and plant breeding to produce superior production animals and plants. To optimize fitness benefits in genetic rescue programs and to secure high yielding domestic varieties in animal and plant breeding, knowledge on the genetic relatedness of populations being crossed is imperative. In this study, we conducted replicated crosses between isogenic Drosophila melanogaster lines from the Drosophila Genetic Reference Panel. We grouped lines in two genetic distance groups to study the effect of genetic divergence between populations on the expression of heterosis in two fitness components; starvation resistance and reproductive output. We further investigated the transgenerational effects of outcrossing by investigating the fitness consequences in both the F 1 - and the F 3 -generations. High fitness enhancements were observed in hybrid offspring compared to parental lines, especially for reproductive output. However, the level of heterosis declined from the F 1 - to the F 3 -generation. Generally, genetic distance did not have strong impact on the level of heterosis detected, although there were exceptions to this pattern. The best predictor of heterosis was performance of parental lines with poorly performing parental lines showing higher hybrid vigour when crossed, i.e. the potential for heterosis was proportional to the level of inbreeding depression. Overall, our results show that outcrossing can have very strong positive fitness consequences for genetically depauperate populations.

Prediction of Aerodynamic Coefficients for Wind Tunnel Data using a Genetic Algorithm Optimized Neural Network

NASA Technical Reports Server (NTRS)

Rajkumar, T.; Aragon, Cecilia; Bardina, Jorge; Britten, Roy

2002-01-01

A fast, reliable way of predicting aerodynamic coefficients is produced using a neural network optimized by a genetic algorithm. Basic aerodynamic coefficients (e.g. lift, drag, pitching moment) are modelled as functions of angle of attack and Mach number. The neural network is first trained on a relatively rich set of data from wind tunnel tests of numerical simulations to learn an overall model. Most of the aerodynamic parameters can be well-fitted using polynomial functions. A new set of data, which can be relatively sparse, is then supplied to the network to produce a new model consistent with the previous model and the new data. Because the new model interpolates realistically between the sparse test data points, it is suitable for use in piloted simulations. The genetic algorithm is used to choose a neural network architecture to give best results, avoiding over-and under-fitting of the test data.

Adaptive Topographies and Equilibrium Selection in an Evolutionary Game

PubMed Central

Osinga, Hinke M.; Marshall, James A. R.

2015-01-01

It has long been known in the field of population genetics that adaptive topographies, in which population equilibria maximise mean population fitness for a trait regardless of its genetic bases, do not exist. Whether one chooses to model selection acting on a single locus or multiple loci does matter. In evolutionary game theory, analysis of a simple and general game involving distinct roles for the two players has shown that whether strategies are modelled using a single ‘locus’ or one ‘locus’ for each role, the stable population equilibria are unchanged and correspond to the fitness-maximising evolutionary stable strategies of the game. This is curious given the aforementioned population genetical results on the importance of the genetic bases of traits. Here we present a dynamical systems analysis of the game with roles detailing how, while the stable equilibria in this game are unchanged by the number of ‘loci’ modelled, equilibrium selection may differ under the two modelling approaches. PMID:25706762

Model invariance across genders of the Broad Autism Phenotype Questionnaire.

PubMed

Broderick, Neill; Wade, Jordan L; Meyer, J Patrick; Hull, Michael; Reeve, Ronald E

2015-10-01

ASD is one of the most heritable neuropsychiatric disorders, though comprehensive genetic liability remains elusive. To facilitate genetic research, researchers employ the concept of the broad autism phenotype (BAP), a milder presentation of traits in undiagnosed relatives. Research suggests that the BAP Questionnaire (BAPQ) demonstrates psychometric properties superior to other self-report measures. To examine evidence regarding validity of the BAPQ, the current study used confirmatory factor analysis to test the assumption of model invariance across genders. Results of the current study upheld model invariance at each level of parameter constraint; however, model fit indices suggested limited goodness-of-fit between the proposed model and the sample. Exploratory analyses investigated alternate factor structure models but ultimately supported the proposed three-factor structure model.

Mechanisms underlying the lifetime co-occurrence of tobacco and cannabis use in adolescent and young adult twins

PubMed Central

Agrawal, Arpana; Silberg, Judy L.; Lynskey, Michael T.; Maes, Hermine H.; Eaves, Lindon J.

2009-01-01

Using twins assessed during adolescence (Virginia Twin Study of Adolescent Behavioral Development: 8–17 years) and followed up in early adulthood (Young Adult Follow-Up, 18–27 years), we tested 13 genetically informative models of co-occurrence, adapted for the inclusion of covariates. Models were fit, in Mx, to data at both assessments allowing for a comparison of the mechanisms that underlie the lifetime co-occurrence of cannabis and tobacco use in adolescence and early adulthood. Both cannabis and tobacco use were influenced by additive genetic (38–81%) and non-shared environmental factors with the possible role of non-shared environment in the adolescent assessment only. Causation models, where liability to use cannabis exerted a causal influence on the liability to use tobacco fit the adolescent data best, while the reverse causation model (tobacco causes cannabis) fit the early adult data best. Both causation models (cannabis to tobacco and tobacco to cannabis) and the correlated liabilities model fit data from the adolescent and young adult assessments well. Genetic correlations (0.59–0.74) were moderate. Therefore, the relationship between cannabis and tobacco use is fairly similar during adolescence and early adulthood with reciprocal influences across the two psychoactive substances. However, our study could not exclude the possibility that ‘gateways’ and ‘reverse gateways’, particularly within a genetic context, exist, such that predisposition to using one substance (cannabis or tobacco) modifies predisposition to using the other. Given the high addictive potential of nicotine and the ubiquitous nature of cannabis use, this is a public health concern worthy of considerable attention. PMID:20047801

A Geographically Explicit Genetic Model of Worldwide Human-Settlement History

PubMed Central

Liu, Hua; Prugnolle, Franck; Manica, Andrea; Balloux, François

2006-01-01

Currently available genetic and archaeological evidence is generally interpreted as supportive of a recent single origin of modern humans in East Africa. However, this is where the near consensus on human settlement history ends, and considerable uncertainty clouds any more detailed aspect of human colonization history. Here, we present a dynamic genetic model of human settlement history coupled with explicit geographical distances from East Africa, the likely origin of modern humans. We search for the best-supported parameter space by fitting our analytical prediction to genetic data that are based on 52 human populations analyzed at 783 autosomal microsatellite markers. This framework allows us to jointly estimate the key parameters of the expansion of modern humans. Our best estimates suggest an initial expansion of modern humans ∼56,000 years ago from a small founding population of ∼1,000 effective individuals. Our model further points to high growth rates in newly colonized habitats. The general fit of the model with the data is excellent. This suggests that coupling analytical genetic models with explicit demography and geography provides a powerful tool for making inferences on human-settlement history. PMID:16826514

When three traits make a line: evolution of phenotypic plasticity and genetic assimilation through linear reaction norms in stochastic environments.

PubMed

Ergon, T; Ergon, R

2017-03-01

Genetic assimilation emerges from selection on phenotypic plasticity. Yet, commonly used quantitative genetics models of linear reaction norms considering intercept and slope as traits do not mimic the full process of genetic assimilation. We argue that intercept-slope reaction norm models are insufficient representations of genetic effects on linear reaction norms and that considering reaction norm intercept as a trait is unfortunate because the definition of this trait relates to a specific environmental value (zero) and confounds genetic effects on reaction norm elevation with genetic effects on environmental perception. Instead, we suggest a model with three traits representing genetic effects that, respectively, (i) are independent of the environment, (ii) alter the sensitivity of the phenotype to the environment and (iii) determine how the organism perceives the environment. The model predicts that, given sufficient additive genetic variation in environmental perception, the environmental value at which reaction norms tend to cross will respond rapidly to selection after an abrupt environmental change, and eventually becomes equal to the new mean environment. This readjustment of the zone of canalization becomes completed without changes in genetic correlations, genetic drift or imposing any fitness costs of maintaining plasticity. The asymptotic evolutionary outcome of this three-trait linear reaction norm generally entails a lower degree of phenotypic plasticity than the two-trait model, and maximum expected fitness does not occur at the mean trait values in the population. © 2016 The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.

Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

PubMed

Bellucci, Michael A; Coker, David F

2011-07-28

We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models.

PubMed

Vanderick, S; Troch, T; Gillon, A; Glorieux, G; Gengler, N

2014-12-01

Calving ease scores from Holstein dairy cattle in the Walloon Region of Belgium were analysed using univariate linear and threshold animal models. Variance components and derived genetic parameters were estimated from a data set including 33,155 calving records. Included in the models were season, herd and sex of calf × age of dam classes × group of calvings interaction as fixed effects, herd × year of calving, maternal permanent environment and animal direct and maternal additive genetic as random effects. Models were fitted with the genetic correlation between direct and maternal additive genetic effects either estimated or constrained to zero. Direct heritability for calving ease was approximately 8% with linear models and approximately 12% with threshold models. Maternal heritabilities were approximately 2 and 4%, respectively. Genetic correlation between direct and maternal additive effects was found to be not significantly different from zero. Models were compared in terms of goodness of fit and predictive ability. Criteria of comparison such as mean squared error, correlation between observed and predicted calving ease scores as well as between estimated breeding values were estimated from 85,118 calving records. The results provided few differences between linear and threshold models even though correlations between estimated breeding values from subsets of data for sires with progeny from linear model were 17 and 23% greater for direct and maternal genetic effects, respectively, than from threshold model. For the purpose of genetic evaluation for calving ease in Walloon Holstein dairy cattle, the linear animal model without covariance between direct and maternal additive effects was found to be the best choice. © 2014 Blackwell Verlag GmbH.

Fitness consequences of parental compatibility in the frog Crinia georgiana.

PubMed

Dziminski, Martin A; Roberts, J Dale; Simmons, Leigh W

2008-04-01

Theory suggests that multiple mating by females can evolve as a mechanism for acquiring compatible genes that promote offspring fitness. Genetic compatibility models predict that differences in fitness among offspring arise from interactions between male and female haplotypes. Using a cross-classified breeding design and in vitro fertilization, we raised families of maternal and paternal half-siblings of the frog Crinia georgiana, a species with a polyandrous breeding system and external fertilization. After controlling for variation in maternal provisioning, we found significant effects of interacting parental haplotypes on fertilization success, and nonadditive genetic effects on measures of offspring fitness such as embryo survival, and survival to, size at, and time to metamorphosis. Additive genetic variation due to males and females was negligible, and not statistically significant for any of the fitness traits measured. Combinations of parental haplotypes that resulted in high rates of fertilization produced offspring with higher embryo survival and rapid juvenile development. We suggest that a gamete recognition mechanism for selective fertilization by compatible sperm may promote offspring fitness in this system.

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

PubMed Central

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

2015-01-01

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

Stochastic modeling indicates that aging and somatic evolution in the hematopoetic system are driven by non-cell-autonomous processes.

PubMed

Rozhok, Andrii I; Salstrom, Jennifer L; DeGregori, James

2014-12-01

Age-dependent tissue decline and increased cancer incidence are widely accepted to be rate-limited by the accumulation of somatic mutations over time. Current models of carcinogenesis are dominated by the assumption that oncogenic mutations have defined advantageous fitness effects on recipient stem and progenitor cells, promoting and rate-limiting somatic evolution. However, this assumption is markedly discrepant with evolutionary theory, whereby fitness is a dynamic property of a phenotype imposed upon and widely modulated by environment. We computationally modeled dynamic microenvironment-dependent fitness alterations in hematopoietic stem cells (HSC) within the Sprengel-Liebig system known to govern evolution at the population level. Our model for the first time integrates real data on age-dependent dynamics of HSC division rates, pool size, and accumulation of genetic changes and demonstrates that somatic evolution is not rate-limited by the occurrence of mutations, but instead results from aged microenvironment-driven alterations in the selective/fitness value of previously accumulated genetic changes. Our results are also consistent with evolutionary models of aging and thus oppose both somatic mutation-centric paradigms of carcinogenesis and tissue functional decline. In total, we demonstrate that aging directly promotes HSC fitness decline and somatic evolution via non-cell-autonomous mechanisms.

Experimental evolution reveals antagonistic pleiotropy in reproductive timing but not life span in Caenorhabditis elegans.

PubMed

Anderson, Jennifer L; Reynolds, Rose M; Morran, Levi T; Tolman-Thompson, Julie; Phillips, Patrick C

2011-12-01

Many mutations that dramatically extend life span in model organisms come with substantial fitness costs. Although these genetic manipulations provide valuable insight into molecular modulators of life span, it is currently unclear whether life-span extension is unavoidably linked to fitness costs. To examine this relationship, we evolved a genetically heterogeneous population of Caenorhabditis elegans for 47 generations, selecting for early fecundity. We asked whether an increase in early fecundity would necessitate a decrease in longevity or late fecundity (antagonistic pleiotropy). Caenorhabditis elegans experimentally evolved for increased early reproduction and decreased late reproduction but suffered no total fitness or life-span costs. Given that antagonistic pleiotropy among these traits has been previously demonstrated in some cases, we conclude that the genetic constraint is not absolute, that is, it is possible to uncouple longevity from early fecundity using genetic variation segregating within and among natural populations.

A map of local adaptation in Arabidopsis thaliana.

PubMed

Fournier-Level, A; Korte, A; Cooper, M D; Nordborg, M; Schmitt, J; Wilczek, A M

2011-10-07

Local adaptation is critical for species persistence in the face of rapid environmental change, but its genetic basis is not well understood. Growing the model plant Arabidopsis thaliana in field experiments in four sites across the species' native range, we identified candidate loci for local adaptation from a genome-wide association study of lifetime fitness in geographically diverse accessions. Fitness-associated loci exhibited both geographic and climatic signatures of local adaptation. Relative to genomic controls, high-fitness alleles were generally distributed closer to the site where they increased fitness, occupying specific and distinct climate spaces. Independent loci with different molecular functions contributed most strongly to fitness variation in each site. Independent local adaptation by distinct genetic mechanisms may facilitate a flexible evolutionary response to changing environment across a species range.

Genomic Prediction Accounting for Residual Heteroskedasticity

PubMed Central

Ou, Zhining; Tempelman, Robert J.; Steibel, Juan P.; Ernst, Catherine W.; Bates, Ronald O.; Bello, Nora M.

2015-01-01

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. PMID:26564950

The long-term evolution of multilocus traits under frequency-dependent disruptive selection.

PubMed

van Doorn, G Sander; Dieckmann, Ulf

2006-11-01

Frequency-dependent disruptive selection is widely recognized as an important source of genetic variation. Its evolutionary consequences have been extensively studied using phenotypic evolutionary models, based on quantitative genetics, game theory, or adaptive dynamics. However, the genetic assumptions underlying these approaches are highly idealized and, even worse, predict different consequences of frequency-dependent disruptive selection. Population genetic models, by contrast, enable genotypic evolutionary models, but traditionally assume constant fitness values. Only a minority of these models thus addresses frequency-dependent selection, and only a few of these do so in a multilocus context. An inherent limitation of these remaining studies is that they only investigate the short-term maintenance of genetic variation. Consequently, the long-term evolution of multilocus characters under frequency-dependent disruptive selection remains poorly understood. We aim to bridge this gap between phenotypic and genotypic models by studying a multilocus version of Levene's soft-selection model. Individual-based simulations and deterministic approximations based on adaptive dynamics theory provide insights into the underlying evolutionary dynamics. Our analysis uncovers a general pattern of polymorphism formation and collapse, likely to apply to a wide variety of genetic systems: after convergence to a fitness minimum and the subsequent establishment of genetic polymorphism at multiple loci, genetic variation becomes increasingly concentrated on a few loci, until eventually only a single polymorphic locus remains. This evolutionary process combines features observed in quantitative genetics and adaptive dynamics models, and it can be explained as a consequence of changes in the selection regime that are inherent to frequency-dependent disruptive selection. Our findings demonstrate that the potential of frequency-dependent disruptive selection to maintain polygenic variation is considerably smaller than previously expected.

An examination of environmental and genetic contributions to the determinants of suicidal behavior among male twins

PubMed Central

Smith, April Rose; Ribeiro, Jessica; Mikolajewski, Amy; Taylor, Jeanette; Joiner, Thomas; Iacono, William G.

2012-01-01

The purpose of the present study was to examine the relative association of genetic and environmental factors with individual differences in each of the proximal, jointly necessary, and sufficient causes for suicidal behavior, according to the Interpersonal-Psychological Theory of Suicide (IPTS; Joiner, 2005). We examined data on derived scales measuring acquired capability, belongingness, and burdensomeness (the determinants of suicidal behavior, according to theory) from 348 adolescent male twins. Univariate biometrical models were used to estimate the magnitude of additive genetic (A), non-additive genetic (D), shared environmental (C), and nonshared environmental (E) effects associated with the variance in acquired capability, belongingness, and burdensomeness. The best fitting model for the acquired capability allowed for additive genetic and environmental effects, whereas the best fitting model for burdensomeness and belongingness allowed for shared and nonshared environmental effects. The present research extends prior work by specifying the environmental and genetic contributions to the components of the IPTS, and our findings suggest that belongingness and burdensomeness may be more appropriate targets for clinical intervention than acquired capability as these factors may be more malleable or amenable to change. PMID:22417928

Indirect genetic effect model using feeding behaviour traits to define the degree of interaction between mates: an implementation in pigs growth rate.

PubMed

Ragab, M; Piles, M; Quintanilla, R; Sánchez, J P

2018-06-06

An alternative implementation of the animal model including indirect genetic effect (IGE) is presented considering pair-mate-specific interaction degrees to improve the performance of the model. Data consisted of average daily gain (ADG) records from 663 pigs kept in groups of 10 to 14 mates during the fattening period. Three types of models were used to fit ADG data: (i) animal model (AM); (ii) AM with classical IGE (AM-IGE); and (iii) AM fitting IGE with a specific degree of interaction between each pair of mates (AM-IGEi). Several feeding behavior phenotypes were used to define the pair-mate-specific degree of interaction in AM-IGEi: feeding rate (g/min), feeding frequency (min/day), the time between consecutive visits to the feeder (min/day), occupation time (min/day) and an index considering all these variables. All models included systematic effects batch, initial age (covariate), final age (covariate), number of pigs per pen (covariate), plus the random effect of the pen. Estimated posterior mean (posterior SD) of heritability was 0.47 (0.15) using AM. Including social genetic effects in the model, total heritable variance expressed as a proportion of total phenotypic variance (T 2) was 0.54 (0.29) using AM-IGE, whereas it ranged from 0.51 to 0.55 (0.12 to 0.14) with AM-IGEi, depending on the behavior trait used to define social interactions. These results confirm the contribution of IGEs to the total heritable variation of ADG. Moreover, important differences between models were observed in EBV rankings. The percentage of coincidence of top 10% animals between AM and AM-IGEi ranged from 0.44 to 0.89 and from 0.41to 0.68 between AM-IGE and AM-IGEi. Based on the goodness of fit and predictive ability, social models are preferred for the genetic evaluation of ADG. Among models including IGEs, when the pair-specific degree of interaction was defined using feeding behavior phenotypes we obtained an increase in the accuracy of genetic parameters estimates, the better goodness of fit and higher predictive ability. We conclude that feeding behavior variables can be used to measure the interaction between pen mates and to improve the performance of models including IGEs.

Dominance genetic and maternal effects for genetic evaluation of egg production traits in dual-purpose chickens.

PubMed

Jasouri, M; Zamani, P; Alijani, S

2017-10-01

1. A study was conducted to study direct dominance genetic and maternal effects on genetic evaluation of production traits in dual-purpose chickens. The data set consisted of records of body weight and egg production of 49 749 Mazandaran fowls from 19 consecutive generations. Based on combinations of different random effects, including direct additive and dominance genetic and maternal additive genetic and environmental effects, 8 different models were compared. 2. Inclusion of a maternal genetic effect in the models noticeably improved goodness of fit for all traits. Direct dominance genetic effect did not have noticeable effects on goodness of fit but simultaneous inclusion of both direct dominance and maternal additive genetic effects improved fitting criteria and accuracies of genetic parameter estimates for hatching body weight and egg production traits. 3. Estimates of heritability (h 2 ) for body weights at hatch, 8 weeks and 12 weeks of age (BW0, BW8 and BW12, respectively), age at sexual maturity (ASM), average egg weights at 28-32 weeks of laying period (AEW), egg number (EN) and egg production intensity (EI) were 0.08, 0.21, 0.22, 0.22, 0.21, 0.09 and 0.10, respectively. For BW0, BW8, BW12, ASM, AEW, EN and EI, proportion of dominance genetic to total phenotypic variance (d 2 ) were 0.06, 0.08, 0.01, 0.06, 0.06, 0.08 and 0.07 and maternal heritability estimates (m 2 ) were 0.05, 0.04, 0.03, 0.13, 0.21, 0.07 and 0.03, respectively. Negligible coefficients of maternal environmental effect (c 2 ) from 0.01 to 0.08 were estimated for all traits, other than BW0, which had an estimate of 0.30. 4. Breeding values (BVs) estimated for body weights at early ages (BW0 and BW8) were considerably affected by components of the models, but almost similar BVs were estimated by different models for higher age body weight (BW12) and egg production traits (ASM, AEW, EN and EI). Generally, it could be concluded that inclusion of maternal effects (both genetic and environmental) and, to a lesser extent, direct dominance genetic effect would improve the accuracy of genetic evaluation for early age body weights in dual-purpose chickens.

The genetic basis for cognitive ability, memory, and depression symptomatology in middle-aged and elderly chinese twins.

PubMed

Xu, Chunsheng; Sun, Jianping; Ji, Fuling; Tian, Xiaocao; Duan, Haiping; Zhai, Yaoming; Wang, Shaojie; Pang, Zengchang; Zhang, Dongfeng; Zhao, Zhongtang; Li, Shuxia; Hjelmborg, Jacob V B; Christensen, Kaare; Tan, Qihua

2015-02-01

The genetic influences on aging-related phenotypes, including cognition and depression, have been well confirmed in the Western populations. We performed the first twin-based analysis on cognitive performance, memory and depression status in middle-aged and elderly Chinese twins, representing the world's largest and most rapidly aging population. The sample consisted of 384 twin pairs with a median age of 50 years. Cognitive function was measured using the Montreal Cognitive Assessment (MoCA) scale; memory was assessed using the revised Wechsler Adult Intelligence scale; depression symptomatology was evaluated by the self-reported 30-item Geriatric Depression (GDS-30)scale. Both univariate and multivariate twin models were fitted to the three phenotypes with full and nested models and compared to select the best fitting models. Univariate analysis showed moderate-to-high genetic influences with heritability 0.44 for cognition and 0.56 for memory. Multivariate analysis by the reduced Cholesky model estimated significant genetic (rG = 0.69) and unique environmental (rE = 0.25) correlation between cognitive ability and memory. The model also estimated weak but significant inverse genetic correlation for depression with cognition (-0.31) and memory (-0.28). No significant unique environmental correlation was found for depression with other two phenotypes. In conclusion, there can be a common genetic architecture for cognitive ability and memory that weakly correlates with depression symptomatology, but in the opposite direction.

Detection of mastitis in dairy cattle by use of mixture models for repeated somatic cell scores: a Bayesian approach via Gibbs sampling.

PubMed

Odegård, J; Jensen, J; Madsen, P; Gianola, D; Klemetsdal, G; Heringstad, B

2003-11-01

The distribution of somatic cell scores could be regarded as a mixture of at least two components depending on a cow's udder health status. A heteroscedastic two-component Bayesian normal mixture model with random effects was developed and implemented via Gibbs sampling. The model was evaluated using datasets consisting of simulated somatic cell score records. Somatic cell score was simulated as a mixture representing two alternative udder health statuses ("healthy" or "diseased"). Animals were assigned randomly to the two components according to the probability of group membership (Pm). Random effects (additive genetic and permanent environment), when included, had identical distributions across mixture components. Posterior probabilities of putative mastitis were estimated for all observations, and model adequacy was evaluated using measures of sensitivity, specificity, and posterior probability of misclassification. Fitting different residual variances in the two mixture components caused some bias in estimation of parameters. When the components were difficult to disentangle, so were their residual variances, causing bias in estimation of Pm and of location parameters of the two underlying distributions. When all variance components were identical across mixture components, the mixture model analyses returned parameter estimates essentially without bias and with a high degree of precision. Including random effects in the model increased the probability of correct classification substantially. No sizable differences in probability of correct classification were found between models in which a single cow effect (ignoring relationships) was fitted and models where this effect was split into genetic and permanent environmental components, utilizing relationship information. When genetic and permanent environmental effects were fitted, the between-replicate variance of estimates of posterior means was smaller because the model accounted for random genetic drift.

Deletion analysis of Streptococcus pneumoniae late competence genes distinguishes virulence determinants that are dependent or independent of competence induction.

PubMed

Zhu, Luchang; Lin, Jingjun; Kuang, Zhizhou; Vidal, Jorge E; Lau, Gee W

2015-07-01

The competence regulon of Streptococcus pneumoniae (pneumococcus) is crucial for genetic transformation. During competence development, the alternative sigma factor ComX is activated, which in turn, initiates transcription of 80 'late' competence genes. Interestingly, only 16 late genes are essential for genetic transformation. We hypothesized that these late genes that are dispensable for competence are beneficial to pneumococcal fitness during infection. These late genes were systematically deleted, and the resulting mutants were examined for their fitness during mouse models of bacteremia and acute pneumonia. Among these, 14 late genes were important for fitness in mice. Significantly, deletion of some late genes attenuated pneumococcal fitness to the same level in both wild-type and ComX-null genetic backgrounds, suggesting that the constitutive baseline expression of these genes was important for bacterial fitness. In contrast, some mutants were attenuated only in the wild-type genetic background but not in the ComX-null background, suggesting that specific expression of these genes during competence state contributed to pneumococcal fitness. Increased virulence during competence state was partially caused by the induction of allolytic enzymes that enhanced pneumolysin release. These results distinguish the role of basal expression versus competence induction in virulence functions encoded by ComX-regulated late competence genes. © 2015 John Wiley & Sons Ltd.

Assessment of Poisson, probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep.

PubMed

Peñagaricano, F; Urioste, J I; Naya, H; de los Campos, G; Gianola, D

2011-04-01

Black skin spots are associated with pigmented fibres in wool, an important quality fault. Our objective was to assess alternative models for genetic analysis of presence (BINBS) and number (NUMBS) of black spots in Corriedale sheep. During 2002-08, 5624 records from 2839 animals in two flocks, aged 1 through 6 years, were taken at shearing. Four models were considered: linear and probit for BINBS and linear and Poisson for NUMBS. All models included flock-year and age as fixed effects and animal and permanent environmental as random effects. Models were fitted to the whole data set and were also compared based on their predictive ability in cross-validation. Estimates of heritability ranged from 0.154 to 0.230 for BINBS and 0.269 to 0.474 for NUMBS. For BINBS, the probit model fitted slightly better to the data than the linear model. Predictions of random effects from these models were highly correlated, and both models exhibited similar predictive ability. For NUMBS, the Poisson model, with a residual term to account for overdispersion, performed better than the linear model in goodness of fit and predictive ability. Predictions of random effects from the Poisson model were more strongly correlated with those from BINBS models than those from the linear model. Overall, the use of probit or linear models for BINBS and of a Poisson model with a residual for NUMBS seems a reasonable choice for genetic selection purposes in Corriedale sheep. © 2010 Blackwell Verlag GmbH.

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana

PubMed Central

Fournier-Level, Alexandre; Perry, Emily O.; Wang, Jonathan A.; Braun, Peter T.; Migneault, Andrew; Cooper, Martha D.; Metcalf, C. Jessica E.; Schmitt, Johanna

2016-01-01

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico “resurrection experiments” showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana.

PubMed

Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna

2016-05-17

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation.

Division of labour and the evolution of multicellularity

PubMed Central

Ispolatov, Iaroslav; Ackermann, Martin; Doebeli, Michael

2012-01-01

Understanding the emergence and evolution of multicellularity and cellular differentiation is a core problem in biology. We develop a quantitative model that shows that a multicellular form emerges from genetically identical unicellular ancestors when the compartmentalization of poorly compatible physiological processes into component cells of an aggregate produces a fitness advantage. This division of labour between the cells in the aggregate occurs spontaneously at the regulatory level owing to mechanisms present in unicellular ancestors and does not require any genetic predisposition for a particular role in the aggregate or any orchestrated cooperative behaviour of aggregate cells. Mathematically, aggregation implies an increase in the dimensionality of phenotype space that generates a fitness landscape with new fitness maxima, in which the unicellular states of optimized metabolism become fitness saddle points. Evolution of multicellularity is modelled as evolution of a hereditary parameter: the propensity of cells to stick together, which determines the fraction of time a cell spends in the aggregate form. Stickiness can increase evolutionarily owing to the fitness advantage generated by the division of labour between cells in an aggregate. PMID:22158952

A Genetic Study of Attention Deficit Hyperactivity Disorder, Conduct Disorder, Oppositional Defiant Disorder and Reading Disability: Aetiological Overlaps and Implications

ERIC Educational Resources Information Center

Martin, Neilson C.; Levy, Florence; Pieka, Jan; Hay, David A.

2006-01-01

Attention Deficit Hyperactivity Disorder (ADHD) commonly co-occurs with Oppositional Defiant Disorder, Conduct Disorder and Reading Disability. Twin studies are an important approach to understanding and modelling potential causes of such comorbidity. Univariate and bivariate genetic models were fitted to maternal report data from 2040 families of…

Genomic Prediction Accounting for Residual Heteroskedasticity.

PubMed

Ou, Zhining; Tempelman, Robert J; Steibel, Juan P; Ernst, Catherine W; Bates, Ronald O; Bello, Nora M

2015-11-12

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. Copyright © 2016 Ou et al.

Applying Biometric Growth Curve Models to Developmental Synchronies in Cognitive Development: The Louisville Twin Study.

PubMed

Finkel, Deborah; Davis, Deborah Winders; Turkheimer, Eric; Dickens, William T

2015-11-01

Biometric latent growth curve models were applied to data from the LTS in order to replicate and extend Wilson's (Child Dev 54:298-316, 1983) findings. Assessments of cognitive development were available from 8 measurement occasions covering the period 4-15 years for 1032 individuals. Latent growth curve models were fit to percent correct for 7 subscales: information, similarities, arithmetic, vocabulary, comprehension, picture completion, and block design. Models were fit separately to WPPSI (ages 4-6 years) and WISC-R (ages 7-15). Results indicated the expected increases in heritability in younger childhood, and plateaus in heritability as children reached age 10 years. Heritability of change, per se (slope estimates), varied dramatically across domains. Significant genetic influences on slope parameters that were independent of initial levels of performance were found for only information and picture completion subscales. Thus evidence for both genetic continuity and genetic innovation in the development of cognitive abilities in childhood were found.

A genetically informative developmental study of the relationship between conduct disorder and peer deviance in males

PubMed Central

Kendler, K. S.; Jacobson, K.; Myers, J. M.; Eaves, L. J.

2014-01-01

Background Conduct disorder (CD) and peer deviance (PD) both powerfully predict future externalizing behaviors. Although levels of CD and PD are strongly correlated, the causal relationship between them has remained controversial and has not been examined by a genetically informative study. Method Levels of CD and PD were assessed in 746 adult male–male twin pairs at personal interview for ages 8–11, 12–14 and 15–17 years using a life history calendar. Model fitting was performed using the Mx program. Results The best-fit model indicated an active developmental relationship between CD and PD including forward transmission of both traits over time and strong causal relationships between CD and PD within time periods. The best-fit model indicated that the causal relationship for genetic risk factors was from CD to PD and was constant over time. For common environmental factors, the causal pathways ran from PD to CD and were stronger in earlier than later age periods. Conclusions A genetically informative model revealed causal pathways difficult to elucidate by other methods. Genes influence risk for CD, which, through social selection, impacts on the deviance of peers. Shared environment, through family and community processes, encourages or discourages adolescent deviant behavior, which, via social influence, alters risk for CD. Social influence is more important than social selection in childhood, but by late adolescence social selection becomes predominant. These findings have implications for prevention efforts for CD and associated externalizing disorders. PMID:17935643

Estimation of genetic parameters for milk yield in Murrah buffaloes by Bayesian inference.

PubMed

Breda, F C; Albuquerque, L G; Euclydes, R F; Bignardi, A B; Baldi, F; Torres, R A; Barbosa, L; Tonhati, H

2010-02-01

Random regression models were used to estimate genetic parameters for test-day milk yield in Murrah buffaloes using Bayesian inference. Data comprised 17,935 test-day milk records from 1,433 buffaloes. Twelve models were tested using different combinations of third-, fourth-, fifth-, sixth-, and seventh-order orthogonal polynomials of weeks of lactation for additive genetic and permanent environmental effects. All models included the fixed effects of contemporary group, number of daily milkings and age of cow at calving as covariate (linear and quadratic effect). In addition, residual variances were considered to be heterogeneous with 6 classes of variance. Models were selected based on the residual mean square error, weighted average of residual variance estimates, and estimates of variance components, heritabilities, correlations, eigenvalues, and eigenfunctions. Results indicated that changes in the order of fit for additive genetic and permanent environmental random effects influenced the estimation of genetic parameters. Heritability estimates ranged from 0.19 to 0.31. Genetic correlation estimates were close to unity between adjacent test-day records, but decreased gradually as the interval between test-days increased. Results from mean squared error and weighted averages of residual variance estimates suggested that a model considering sixth- and seventh-order Legendre polynomials for additive and permanent environmental effects, respectively, and 6 classes for residual variances, provided the best fit. Nevertheless, this model presented the largest degree of complexity. A more parsimonious model, with fourth- and sixth-order polynomials, respectively, for these same effects, yielded very similar genetic parameter estimates. Therefore, this last model is recommended for routine applications. Copyright 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Constrained Genetic Algorithm with Adaptively Defined Fitness Function in MRS Quantification

NASA Astrophysics Data System (ADS)

Papakostas, G. A.; Karras, D. A.; Mertzios, B. G.; Graveron-Demilly, D.; van Ormondt, D.

MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on Computational Intelligence tools, such as Neural Networks (NNs), demonstrated a good performance but not without drawbacks already discussed by the authors. On the other hand preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS quantification using the Voigt line shape model. This paper investigates a novel constrained genetic algorithm involving a generic and adaptively defined fitness function which extends the simple genetic algorithm methodology in case of noisy signals. The applicability of this new algorithm is scrutinized through experimentation in artificial MRS signals interleaved with noise, regarding its signal fitting capabilities. Although extensive experiments with real world MRS signals are necessary, the herein shown performance illustrates the method's potential to be established as a generic MRS metabolites quantification procedure.

Modeling multilayer x-ray reflectivity using genetic algorithms

NASA Astrophysics Data System (ADS)

Sánchez del Río, M.; Pareschi, G.; Michetschläger, C.

2000-06-01

The x-ray reflectivity of a multilayer is a non-linear function of many parameters (materials, layer thickness, density, roughness). Non-linear fitting of experimental data with simulations requires the use of initial values sufficiently close to the optimum value. This is a difficult task when the topology of the space of the variables is highly structured. We apply global optimization methods to fit multilayer reflectivity. Genetic algorithms are stochastic methods based on the model of natural evolution: the improvement of a population along successive generations. A complete set of initial parameters constitutes an individual. The population is a collection of individuals. Each generation is built from the parent generation by applying some operators (selection, crossover, mutation, etc.) on the members of the parent generation. The pressure of selection drives the population to include "good" individuals. For large number of generations, the best individuals will approximate the optimum parameters. Some results on fitting experimental hard x-ray reflectivity data for Ni/C and W/Si multilayers using genetic algorithms are presented. This method can also be applied to design multilayers optimized for a target application.

Genetics and child psychiatry: I Advances in quantitative and molecular genetics.

PubMed

Rutter, M; Silberg, J; O'Connor, T; Simonoff, E

1999-01-01

Advances in quantitative psychiatric genetics as a whole are reviewed with respect to conceptual and methodological issues in relation to statistical model fitting, new genetic designs, twin and adoptee studies, definition of the phenotype, pervasiveness of genetic influences, pervasiveness of environmental influences, shared and nonshared environmental effects, and nature-nurture interplay. Advances in molecular genetics are discussed in relation to the shifts in research strategies to investigate multifactorial disorders (affected relative linkage designs, association strategies, and quantitative trait loci studies); new techniques and identified genetic mechanisms (expansion of trinucleotide repeats, genomic imprinting, mitochondrial DNA, fluorescent in-situ hybridisation, behavioural phenotypes, and animal models); and the successful localisation of genes.

Deriving estimates of individual variability in genetic potentials of performance traits for 3 dairy breeds, using a model of lifetime nutrient partitioning.

PubMed

Phuong, H N; Martin, O; de Boer, I J M; Ingvartsen, K L; Schmidely, Ph; Friggens, N C

2015-01-01

This study explored the ability of an existing lifetime nutrient partitioning model for simulating individual variability in genetic potentials of dairy cows. Generally, the model assumes a universal trajectory of dynamic partitioning of priority between life functions and genetic scaling parameters are then incorporated to simulate individual difference in performance. Data of 102 cows including 180 lactations of 3 breeds: Danish Red, Danish Holstein, and Jersey, which were completely independent from those used previously for model development, were used. Individual cow performance records through sequential lactations were used to derive genetic scaling parameters for each animal by calibrating the model to achieve best fit, cow by cow. The model was able to fit individual curves of body weight, and milk fat, milk protein, and milk lactose concentrations with a high degree of accuracy. Daily milk yield and dry matter intake were satisfactorily predicted in early and mid lactation, but underpredictions were found in late lactation. Breeds and parities did not significantly affect the prediction accuracy. The means of genetic scaling parameters between Danish Red and Danish Holstein were similar but significantly different from those of Jersey. The extent of correlations between the genetic scaling parameters was consistent with that reported in the literature. In conclusion, this model is of value as a tool to derive estimates of genetic potentials of milk yield, milk composition, body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise. The model enables simulation of the effects of a genetic selection strategy on lifetime efficiency of individual cows, which has a main advantage of including the rearing costs, and thus, can be used to explore the impact of future selection on animal performance and efficiency. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A test of genetic models for the evolutionary maintenance of same-sex sexual behaviour.

PubMed

Hoskins, Jessica L; Ritchie, Michael G; Bailey, Nathan W

2015-06-22

The evolutionary maintenance of same-sex sexual behaviour (SSB) has received increasing attention because it is perceived to be an evolutionary paradox. The genetic basis of SSB is almost wholly unknown in non-human animals, though this is key to understanding its persistence. Recent theoretical work has yielded broadly applicable predictions centred on two genetic models for SSB: overdominance and sexual antagonism. Using Drosophila melanogaster, we assayed natural genetic variation for male SSB and empirically tested predictions about the mode of inheritance and fitness consequences of alleles influencing its expression. We screened 50 inbred lines derived from a wild population for male-male courtship and copulation behaviour, and examined crosses between the lines for evidence of overdominance and antagonistic fecundity selection. Consistent variation among lines revealed heritable genetic variation for SSB, but the nature of the genetic variation was complex. Phenotypic and fitness variation was consistent with expectations under overdominance, although predictions of the sexual antagonism model were also supported. We found an unexpected and strong paternal effect on the expression of SSB, suggesting possible Y-linkage of the trait. Our results inform evolutionary genetic mechanisms that might maintain low but persistently observed levels of male SSB in D. melanogaster, but highlight a need for broader taxonomic representation in studies of its evolutionary causes. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

How do the effects of mutations add up?

NASA Astrophysics Data System (ADS)

Velenich, Andrea; Dai, Mingjie; Gore, Jeff

2011-03-01

Genetic mutations affect the fitness of any organism and provide the variability necessary for natural selection to occur. Given the fitness of a wild type organism and the fitness of mutants A and B which differ from the wild type by a single mutation, predicting the fitness of the double mutant AB is a fundamental problem with broad implications in many fields, from evolutionary theory to medicine. Analysis of millions of double gene knockouts in yeast reveals that, on average, the fitness of AB is the product of the fitness of A and the fitness of B. However, most pairs of mutations deviate from this mean behavior in a way that challenges existing theoretical models. We propose a natural generalization of the geometric Fisher's model which accommodates the experimentally observed features and allows us to characterize the fitness landscape of yeast.

The heritability of cluster A personality disorders assessed by both personal interview and questionnaire.

PubMed

Kendler, Kenneth S; Myers, John; Torgersen, Svenn; Neale, Michael C; Reichborn-Kjennerud, Ted

2007-05-01

Personality disorders (PDs) as assessed by questionnaires and personal interviews are heritable. However, we know neither how much unreliability of measurement impacts on heritability estimates nor whether the genetic and environmental risk factors assessed by these two methods are the same. We wish to know whether the same set of PD vulnerability factors are assessed by these two methods. A total of 3334 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP) completed a questionnaire containing 91 PD items. One to 6 years later, 1386 of these pairs were interviewed with the Structured Interview for DSM-IV Personality (SIDP-IV). Self-report items predicting interview results were selected by regression. Measurement models were fitted using Mx. In the best-fit models, the latent liabilities to paranoid personality disorder (PPD), schizoid personality disorder (SPD) and schizotypal personality disorder (STPD) were all highly heritable with no evidence of shared environmental effects. For PPD and STPD, only unique environmental effects were specific to the interview measure whereas both environmental and genetic effects were found to be specific to the questionnaire assessment. For SPD, the best-fit model contained genetic and environmental effects specific to both forms of assessment. The latent liabilities to the cluster A PDs are highly heritable but are assessed by current methods with only moderate reliability. The personal interviews assessed the genetic risk for the latent trait with excellent specificity for PPD and STPD and good specificity for SPD. However, for all three PDs, the questionnaires were less specific, also indexing an independent set of genetic risk factors.

Modeling lactation curves and estimation of genetic parameters in Holstein cows using multiple-trait random regression models.

PubMed

Kheirabadi, Khabat; Rashidi, Amir; Alijani, Sadegh; Imumorin, Ikhide

2014-11-01

We compared the goodness of fit of three mathematical functions (including: Legendre polynomials, Lidauer-Mäntysaari function and Wilmink function) for describing the lactation curve of primiparous Iranian Holstein cows by using multiple-trait random regression models (MT-RRM). Lactational submodels provided the largest daily additive genetic (AG) and permanent environmental (PE) variance estimates at the end and at the onset of lactation, respectively, as well as low genetic correlations between peripheral test-day records. For all models, heritability estimates were highest at the end of lactation (245 to 305 days) and ranged from 0.05 to 0.26, 0.03 to 0.12 and 0.04 to 0.24 for milk, fat and protein yields, respectively. Generally, the genetic correlations between traits depend on how far apart they are or whether they are on the same day in any two traits. On average, genetic correlations between milk and fat were the lowest and those between fat and protein were intermediate, while those between milk and protein were the highest. Results from all criteria (Akaike's and Schwarz's Bayesian information criterion, and -2*logarithm of the likelihood function) suggested that a model with 2 and 5 coefficients of Legendre polynomials for AG and PE effects, respectively, was the most adequate for fitting the data. © 2014 Japanese Society of Animal Science.

Joint effects of pleiotropic selection and stabilizing selection on the maintenance of quantitative genetic variation at mutation-selection balance.

PubMed Central

Zhang, Xu-Sheng; Hill, William G

2002-01-01

In quantitative genetics, there are two basic "conflicting" observations: abundant polygenic variation and strong stabilizing selection that should rapidly deplete that variation. This conflict, although having attracted much theoretical attention, still stands open. Two classes of model have been proposed: real stabilizing selection directly on the metric trait under study and apparent stabilizing selection caused solely by the deleterious pleiotropic side effects of mutations on fitness. Here these models are combined and the total stabilizing selection observed is assumed to derive simultaneously through these two different mechanisms. Mutations have effects on a metric trait and on fitness, and both effects vary continuously. The genetic variance (V(G)) and the observed strength of total stabilizing selection (V(s,t)) are analyzed with a rare-alleles model. Both kinds of selection reduce V(G) but their roles in depleting it are not independent: The magnitude of pleiotropic selection depends on real stabilizing selection and such dependence is subject to the shape of the distributions of mutational effects. The genetic variation maintained thus depends on the kurtosis as well as the variance of mutational effects: All else being equal, V(G) increases with increasing leptokurtosis of mutational effects on fitness, while for a given distribution of mutational effects on fitness, V(G) decreases with increasing leptokurtosis of mutational effects on the trait. The V(G) and V(s,t) are determined primarily by real stabilizing selection while pleiotropic effects, which can be large, have only a limited impact. This finding provides some promise that a high heritability can be explained under strong total stabilizing selection for what are regarded as typical values of mutation and selection parameters. PMID:12242254

Childhood separation anxiety disorder and adult onset panic attacks share a common genetic diathesis.

PubMed

Roberson-Nay, Roxann; Eaves, Lindon J; Hettema, John M; Kendler, Kenneth S; Silberg, Judy L

2012-04-01

Childhood separation anxiety disorder (SAD) is hypothesized to share etiologic roots with panic disorder. The aim of this study was to estimate the genetic and environmental sources of covariance between childhood SAD and adult onset panic attacks (AOPA), with the primary goal to determine whether these two phenotypes share a common genetic diathesis. Participants included parents and their monozygotic or dizygotic twins (n = 1,437 twin pairs) participating in the Virginia Twin Study of Adolescent Behavioral Development and those twins who later completed the Young Adult Follow-Up (YAFU). The Child and Adolescent Psychiatric Assessment was completed at three waves during childhood/adolescence followed by the Structured Clinical Interview for DSM-III-R at the YAFU. Two separate, bivariate Cholesky models were fit to childhood diagnoses of SAD and overanxious disorder (OAD), respectively, and their relation with AOPA; a trivariate Cholesky model also examined the collective influence of childhood SAD and OAD on AOPA. In the best-fitting bivariate model, the covariation between SAD and AOPA was accounted for by genetic and unique environmental factors only, with the genetic factor associated with childhood SAD explaining significant variance in AOPA. Environmental risk factors were not significantly shared between SAD and AOPA. By contrast, the genetic factor associated with childhood OAD did not contribute significantly to AOPA. Results of the trivariate Cholesky reaffirmed outcomes of bivariate models. These data indicate that childhood SAD and AOPA share a common genetic diathesis that is not observed for childhood OAD, strongly supporting the hypothesis of a specific genetic etiologic link between the two phenotypes. © 2012 Wiley Periodicals, Inc.

Centromere-associated meiotic drive and female fitness variation in Mimulus.

PubMed

Fishman, Lila; Kelly, John K

2015-05-01

Female meiotic drive, in which chromosomal variants preferentially segregate to the egg pole during asymmetric female meiosis, is a theoretically pervasive but still mysterious form of selfish evolution. Like other selfish genetic elements, driving chromosomes may be maintained as balanced polymorphisms by pleiotropic or linked fitness costs. A centromere-associated driver (D) with a ∼58:42 female-specific transmission advantage occurs at intermediate frequency (32-40%) in the Iron Mountain population of the yellow monkeyflower, Mimulus guttatus. Previously determined male fertility costs are sufficient to prevent the fixation of D, but predict a higher equilibrium frequency. To better understand the dynamics and effects of D, we developed a new population genetic model and measured genotype-specific lifetime female fitness in the wild. In three of four years, and across all years, D imposed significant recessive seedset costs, most likely due to hitchhiking by deleterious mutations. With both male and female costs as measured, and 58:42 drive, our model predicts an equilibrium frequency of D (38%) very close to the observed value. Thus, D represents a rare selfish genetic element whose local population genetic dynamics have been fully parameterized, and the observation of equilibrium sets the stage for investigations of coevolution with suppressors. © 2015 The Author(s).

Common Psychiatric Disorders and Caffeine Use, Tolerance, and Withdrawal: An Examination of Shared Genetic and Environmental Effects

PubMed Central

Bergin, Jocilyn E.; Kendler, Kenneth S.

2012-01-01

Background Previous studies examined caffeine use and caffeine dependence and risk for the symptoms, or diagnosis, of psychiatric disorders. The current study aimed to determine if generalized anxiety disorder (GAD), panic disorder, phobias, major depressive disorder (MDD), anorexia nervosa (AN), or bulimia nervosa (BN) shared common genetic or environmental factors with caffeine use, caffeine tolerance, or caffeine withdrawal. Method Using 2,270 women from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders, bivariate Cholesky decomposition models were used to determine if any of the psychiatric disorders shared genetic or environmental factors with caffeine use phenotypes. Results GAD, phobias, and MDD shared genetic factors with caffeine use, with genetic correlations estimated to be 0.48, 0.25, and 0.38, respectively. Removal of the shared genetic and environmental parameter for phobias and caffeine use resulted in a significantly worse fitting model. MDD shared unique environmental factors (environmental correlation = 0.23) with caffeine tolerance; the genetic correlation between AN and caffeine tolerance and BN and caffeine tolerance were 0.64 and 0.49, respectively. Removal of the genetic and environmental correlation parameters resulted in significantly worse fitting models for GAD, phobias, MDD, AN, and BN, which suggested that there was significant shared liability between each of these phenotypes and caffeine tolerance. GAD had modest genetic correlations with caffeine tolerance, 0.24, and caffeine withdrawal, 0.35. Conclusions There was suggestive evidence of shared genetic and environmental liability between psychiatric disorders and caffeine phenotypes. This might inform us about the etiology of the comorbidity between these phenotypes. PMID:22854069

Common psychiatric disorders and caffeine use, tolerance, and withdrawal: an examination of shared genetic and environmental effects.

PubMed

Bergin, Jocilyn E; Kendler, Kenneth S

2012-08-01

Previous studies examined caffeine use and caffeine dependence and risk for the symptoms, or diagnosis, of psychiatric disorders. The current study aimed to determine if generalized anxiety disorder (GAD), panic disorder, phobias, major depressive disorder (MDD), anorexia nervosa (AN), or bulimia nervosa (BN) shared common genetic or environmental factors with caffeine use, caffeine tolerance, or caffeine withdrawal. Using 2,270 women from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders, bivariate Cholesky decomposition models were used to determine if any of the psychiatric disorders shared genetic or environmental factors with caffeine use phenotypes. GAD, phobias, and MDD shared genetic factors with caffeine use, with genetic correlations estimated to be 0.48, 0.25, and 0.38, respectively. Removal of the shared genetic and environmental parameter for phobias and caffeine use resulted in a significantly worse fitting model. MDD shared unique environmental factors (environmental correlation=0.23) with caffeine tolerance; the genetic correlation between AN and caffeine tolerance and BN and caffeine tolerance were 0.64 and 0.49, respectively. Removal of the genetic and environmental correlation parameters resulted in significantly worse fitting models for GAD, phobias, MDD, AN, and BN, which suggested that there was significant shared liability between each of these phenotypes and caffeine tolerance. GAD had modest genetic correlations with caffeine tolerance, 0.24, and caffeine withdrawal, 0.35. There was suggestive evidence of shared genetic and environmental liability between psychiatric disorders and caffeine phenotypes. This might inform us about the etiology of the comorbidity between these phenotypes.

"The Theory was Beautiful Indeed": Rise, Fall and Circulation of Maximizing Methods in Population Genetics (1930-1980).

PubMed

Grodwohl, Jean-Baptiste

2017-08-01

Describing the theoretical population geneticists of the 1960s, Joseph Felsenstein reminisced: "our central obsession was finding out what function evolution would try to maximize. Population geneticists used to think, following Sewall Wright, that mean relative fitness, W, would be maximized by natural selection" (Felsenstein 2000). The present paper describes the genesis, diffusion and fall of this "obsession", by giving a biography of the mean fitness function in population genetics. This modeling method devised by Sewall Wright in the 1930s found its heyday in the late 1950s and early 1960s, in the wake of Motoo Kimura's and Richard Lewontin's works. It seemed a reliable guide in the mathematical study of deterministic effects (the study of natural selection in populations of infinite size, with no drift), leading to powerful generalizations presenting law-like properties. Progress in population genetics theory, it then seemed, would come from the application of this method to the study of systems with several genes. This ambition came to a halt in the context of the influential objections made by the Australian mathematician Patrick Moran in 1963. These objections triggered a controversy between mathematically- and biologically-inclined geneticists, with affected both the formal standards and the aims of population genetics as a science. Over the course of the 1960s, the mean fitness method withered with the ambition of developing the deterministic theory. The mathematical theory became increasingly complex. Kimura re-focused his modeling work on the theory of random processes; as a result of his computer simulations, Lewontin became the staunchest critic of maximizing principles in evolutionary biology. The mean fitness method then migrated to other research areas, being refashioned and used in evolutionary quantitative genetics and behavioral ecology.

Convergent integration of animal model and human studies of bipolar disorder (manic-depressive illness).

PubMed

Le-Niculescu, Helen; Patel, Sagar D; Niculescu, Alexander B

2010-10-01

Animal models and human studies of bipolar disorder and other psychiatric disorders are becoming increasingly integrated, prompted by recent successes. Particularly for genomics, the convergence and integration of data across species, experimental modalities and technical platforms is providing a fit-to-disease way of extracting reproducible and biologically important signal, in sharp contrast to the fit-to-cohort effect, disappointing findings to date, and limited reproducibility of human genetic analyses alone. Such work in psychiatry can provide an example of how to address other genetically complex disorders, and in turn will benefit by incorporating concepts from other areas, such as cancer biology and diabetes. Copyright © 2010. Published by Elsevier Ltd.

Deletion analysis of Streptococcus pneumoniae late competence genes distinguishes virulence determinants that are dependent or independent of competence induction

PubMed Central

Zhu, Luchang; Lin, Jingjun; Kuang, Zhizhou; Vidal, Jorge E.; Lau, Gee W.

2015-01-01

Summary The competence regulon of Streptococcus pneumoniae (pneumococcus) is crucial for genetic transformation. During competence development, the alternative sigma factor ComX is activated, which in turn, initiates transcription of 80 “late” competence genes. Interestingly, only 16 late genes are essential for genetic transformation. We hypothesized that these late genes that are dispensable for competence are beneficial to pneumococcal fitness during infection. These late genes were systematically deleted, and the resulting mutants were examined for their fitness during mouse models of bacteremia and acute pneumonia. Among these, 14 late genes were important for fitness in mice. Significantly, deletion of some late genes attenuated pneumococcal fitness to the same level in both wild-type and ComX-null genetic backgrounds, suggesting that the constitutive baseline expression of these genes was important for bacterial fitness. In contrast, some mutants were attenuated only in the wild-type genetic background but not in the ComX-null background, suggesting that specific expression of these genes during competence state contributed to pneumococcal fitness. Increased virulence during competence state was partially caused by the induction of allolytic enzymes that enhanced pneumolysin release. These results distinguish the role of basal expression versus competence induction in virulence functions encoded by ComX-regulated late competence genes. Graphical abstract During genetic transformation of pneumococcus, the alternative sigma factor ComX regulates expression of 14 late competence genes important for virulence. The constitutive baseline expression of some of these genes is important for bacteremia and acute pneumonia infections. In contrast, elevated expression of DprA, CbpD, CibAB, and Cinbox are dependent on competence development, enhancing the release of pneumolysin. These results distinguish the role of basal expression versus competence induction in virulence determinants regulated by ComX. PMID:25846124

Relatedness, conflict, and the evolution of eusociality.

PubMed

Liao, Xiaoyun; Rong, Stephen; Queller, David C

2015-03-01

The evolution of sterile worker castes in eusocial insects was a major problem in evolutionary theory until Hamilton developed a method called inclusive fitness. He used it to show that sterile castes could evolve via kin selection, in which a gene for altruistic sterility is favored when the altruism sufficiently benefits relatives carrying the gene. Inclusive fitness theory is well supported empirically and has been applied to many other areas, but a recent paper argued that the general method of inclusive fitness was wrong and advocated an alternative population genetic method. The claim of these authors was bolstered by a new model of the evolution of eusociality with novel conclusions that appeared to overturn some major results from inclusive fitness. Here we report an expanded examination of this kind of model for the evolution of eusociality and show that all three of its apparently novel conclusions are essentially false. Contrary to their claims, genetic relatedness is important and causal, workers are agents that can evolve to be in conflict with the queen, and eusociality is not so difficult to evolve. The misleading conclusions all resulted not from incorrect math but from overgeneralizing from narrow assumptions or parameter values. For example, all of their models implicitly assumed high relatedness, but modifying the model to allow lower relatedness shows that relatedness is essential and causal in the evolution of eusociality. Their modeling strategy, properly applied, actually confirms major insights of inclusive fitness studies of kin selection. This broad agreement of different models shows that social evolution theory, rather than being in turmoil, is supported by multiple theoretical approaches. It also suggests that extensive prior work using inclusive fitness, from microbial interactions to human evolution, should be considered robust unless shown otherwise.

Statistical aspects of evolution under natural selection, with implications for the advantage of sexual reproduction.

PubMed

Crouch, Daniel J M

2017-10-27

The prevalence of sexual reproduction remains mysterious, as it poses clear evolutionary drawbacks compared to reproducing asexually. Several possible explanations exist, with one of the most likely being that finite population size causes linkage disequilibria to randomly generate and impede the progress of natural selection, and that these are eroded by recombination via sexual reproduction. Previous investigations have either analysed this phenomenon in detail for small numbers of loci, or performed population simulations for many loci. Here we present a quantitative genetic model for fitness, based on the Price Equation, in order to examine the theoretical consequences of randomly generated linkage disequilibria when there are many loci. In addition, most previous work has been concerned with the long-term consequences of deleterious linkage disequilibria for population fitness. The expected change in mean fitness between consecutive generations, a measure of short-term evolutionary success, is shown under random environmental influences to be related to the autocovariance in mean fitness between the generations, capturing the effects of stochastic forces such as genetic drift. Interaction between genetic drift and natural selection, due to randomly generated linkage disequilibria, is demonstrated to be one possible source of mean fitness autocovariance. This suggests a possible role for sexual reproduction in reducing the negative effects of genetic drift, thereby improving the short-term efficacy of natural selection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Frequency dependence 3.0: an attempt at codifying the evolutionary ecology perspective.

PubMed

Metz, Johan A J; Geritz, Stefan A H

2016-03-01

The fitness concept and perforce the definition of frequency independent fitnesses from population genetics is closely tied to discrete time population models with non-overlapping generations. Evolutionary ecologists generally focus on trait evolution through repeated mutant substitutions in populations with complicated life histories. This goes with using the per capita invasion speed of mutants as their fitness. In this paper we develop a concept of frequency independence that attempts to capture the practical use of the term by ecologists, which although inspired by population genetics rarely fits its strict definition. We propose to call the invasion fitnesses of an eco-evolutionary model frequency independent when the phenotypes can be ranked by competitive strength, measured by who can invade whom. This is equivalent to the absence of weak priority effects, protected dimorphisms and rock-scissor-paper configurations. Our concept differs from that of Heino et al. (TREE 13:367-370, 1998) in that it is based only on the signs of the invasion fitnesses, whereas Heino et al. based their definitions on the structure of the feedback environment, summarising the effect of all direct and indirect interactions between individuals on fitness. As it turns out, according to our new definition an eco-evolutionary model has frequency independent fitnesses if and only if the effect of the feedback environment on the fitness signs can be summarised by a single scalar with monotonic effect. This may be compared with Heino et al.'s concept of trivial frequency dependence defined by the environmental feedback influencing fitness, and not just its sign, in a scalar manner, without any monotonicity restriction. As it turns out, absence of the latter restriction leaves room for rock-scissor-paper configurations. Since in 'realistic' (as opposed to toy) models frequency independence is exceedingly rare, we also define a concept of weak frequency dependence, which can be interpreted intuitively as almost frequency independence, and analyse in which sense and to what extent the restrictions on the potential model outcomes of the frequency independent case stay intact for models with weak frequency dependence.

Using Genetic Algorithm and MODFLOW to Characterize Aquifer System of Northwest Florida

EPA Science Inventory

By integrating Genetic Algorithm and MODFLOW2005, an optimizing tool is developed to characterize the aquifer system of Region II, Northwest Florida. The history and the newest available observation data of the aquifer system is fitted automatically by using the numerical model c...

Evolution of Fitness in Experimental Populations of Vesicular Stomatitis Virus

PubMed Central

Elena, S. F.; Gonzalez-Candelas, F.; Novella, I. S.; Duarte, E. A.; Clarke, D. K.; Domingo, E.; Holland, J. J.; Moya, A.

1996-01-01

The evolution of fitness in experimental clonal populations of vesicular stomatitis virus (VSV) has been compared under different genetic (fitness of initial clone) and demographic (population dynamics) regimes. In spite of the high genetic heterogeneity among replicates within experiments, there is a clear effect of population dynamics on the evolution of fitness. Those populations that went through strong periodic bottlenecks showed a decreased fitness in competition experiments with wild type. Conversely, mutant populations that were transferred under the dynamics of continuous population expansions increased their fitness when compared with the same wild type. The magnitude of the observed effect depended on the fitness of the original viral clone. Thus, high fitness clones showed a larger reduction in fitness than low fitness clones under dynamics with included periodic bottleneck. In contrast, the gain in fitness was larger the lower the initial fitness of the viral clone. The quantitative genetic analysis of the trait ``fitness'' in the resulting populations shows that genetic variation for the trait is positively correlated with the magnitude of the change in the same trait. The results are interpreted in terms of the operation of MULLER's ratchet and genetic drift as opposed to the appearance of beneficial mutations. PMID:8849878

The etiology of social aggression: a nuclear twin family study.

PubMed

Slawinski, Brooke L; Klump, Kelly L; Burt, S Alexandra

2018-04-02

Social aggression is a form of antisocial behavior in which social relationships and social status are used to damage reputations and inflict emotional harm on others. Despite extensive research examining the prevalence and consequences of social aggression, only a few studies have examined its genetic-environmental etiology, with markedly inconsistent results. We estimated the etiology of social aggression using the nuclear twin family (NTF) model. Maternal-report, paternal-report, and teacher-report data were collected for twin social aggression (N = 1030 pairs). We also examined the data using the classical twin (CT) model to evaluate whether its strict assumptions may have biased previous heritability estimates. The best-fitting NTF model for all informants was the ASFE model, indicating that additive genetic, sibling environmental, familial environmental, and non-shared environmental influences significantly contribute to the etiology of social aggression in middle childhood. However, the best-fitting CT model varied across informants, ranging from AE and ACE to CE. Specific heritability estimates for both NTF and CT models also varied across informants such that teacher reports indicated greater genetic influences and father reports indicated greater shared environmental influences. Although the specific NTF parameter estimates varied across informants, social aggression generally emerged as largely additive genetic (A = 0.15-0.77) and sibling environmental (S = 0.42-0.72) in origin. Such findings not only highlight an important role for individual genetic risk in the etiology of social aggression, but also raise important questions regarding the role of the environment.

A behavioral-genetic investigation of bulimia nervosa and its relationship with alcohol use disorder

PubMed Central

Trace, Sara Elizabeth; Thornton, Laura Marie; Baker, Jessica Helen; Root, Tammy Lynn; Janson, Lauren Elizabeth; Lichtenstein, Paul; Pedersen, Nancy Lee; Bulik, Cynthia Marie

2013-01-01

Bulimia nervosa (BN) and alcohol use disorder (AUD) frequently co-occur and may share genetic factors; however, the nature of their association is not fully understood. We assessed the extent to which the same genetic and environmental factors contribute to liability to BN and AUD. A bivariate structural equation model using a Cholesky decomposition was fit to data from 7,241 women who participated in the Swedish Twin study of Adults: Genes and Environment. The proportion of variance accounted for by genetic and environmental factors for BN and AUD and the genetic and environmental correlations between these disorders were estimated. In the best-fitting model, the heritability estimates were 0.55 (95% CI: 0.37; 0.70) for BN and 0.62 (95% CI: 0.54; 0.70) for AUD. Unique environmental factors accounted for the remainder of variance for BN. The genetic correlation between BN and AUD was 0.23 (95% CI: 0.01; 0.44), and the correlation between the unique environmental factors for the two disorders was 0.35 (95% CI: 0.08; 0.61), suggesting moderate overlap in these factors. Findings from this investigation provide additional support that some of the same genetic factors may influence liability to both BN and AUD. PMID:23790978

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

PubMed

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

2015-10-01

Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Simplified process model discovery based on role-oriented genetic mining.

PubMed

Zhao, Weidong; Liu, Xi; Dai, Weihui

2014-01-01

Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

Using Genetic Algorithm and MODFLOW to Characterize Aquifer System of Northwest Florida (Published Proceedings)

EPA Science Inventory

By integrating Genetic Algorithm and MODFLOW2005, an optimizing tool is developed to characterize the aquifer system of Region II, Northwest Florida. The history and the newest available observation data of the aquifer system is fitted automatically by using the numerical model c...

Random regression models on Legendre polynomials to estimate genetic parameters for weights from birth to adult age in Canchim cattle.

PubMed

Baldi, F; Albuquerque, L G; Alencar, M M

2010-08-01

The objective of this work was to estimate covariance functions for direct and maternal genetic effects, animal and maternal permanent environmental effects, and subsequently, to derive relevant genetic parameters for growth traits in Canchim cattle. Data comprised 49,011 weight records on 2435 females from birth to adult age. The model of analysis included fixed effects of contemporary groups (year and month of birth and at weighing) and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were allowed to vary and were modelled by a step function with 1, 4 or 11 classes based on animal's age. The model fitting four classes of residual variances was the best. A total of 12 random regression models from second to seventh order were used to model direct and maternal genetic effects, animal and maternal permanent environmental effects. The model with direct and maternal genetic effects, animal and maternal permanent environmental effects fitted by quadric, cubic, quintic and linear Legendre polynomials, respectively, was the most adequate to describe the covariance structure of the data. Estimates of direct and maternal heritability obtained by multi-trait (seven traits) and random regression models were very similar. Selection for higher weight at any age, especially after weaning, will produce an increase in mature cow weight. The possibility to modify the growth curve in Canchim cattle to obtain animals with rapid growth at early ages and moderate to low mature cow weight is limited.

Genetic parameters of legendre polynomials for first parity lactation curves.

PubMed

Pool, M H; Janss, L L; Meuwissen, T H

2000-11-01

Variance components of the covariance function coefficients in a random regression test-day model were estimated by Legendre polynomials up to a fifth order for first-parity records of Dutch dairy cows using Gibbs sampling. Two Legendre polynomials of equal order were used to model the random part of the lactation curve, one for the genetic component and one for permanent environment. Test-day records from cows registered between 1990 to 1996 and collected by regular milk recording were available. For the data set, 23,700 complete lactations were selected from 475 herds sired by 262 sires. Because the application of a random regression model is limited by computing capacity, we investigated the minimum order needed to fit the variance structure in the data sufficiently. Predictions of genetic and permanent environmental variance structures were compared with bivariate estimates on 30-d intervals. A third-order or higher polynomial modeled the shape of variance curves over DIM with sufficient accuracy for the genetic and permanent environment part. Also, the genetic correlation structure was fitted with sufficient accuracy by a third-order polynomial, but, for the permanent environmental component, a fourth order was needed. Because equal orders are suggested in the literature, a fourth-order Legendre polynomial is recommended in this study. However, a rank of three for the genetic covariance matrix and of four for permanent environment allows a simpler covariance function with a reduced number of parameters based on the eigenvalues and eigenvectors.

Genetic diversity in the interference selection limit.

PubMed

Good, Benjamin H; Walczak, Aleksandra M; Neher, Richard A; Desai, Michael M

2014-03-01

Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a "linkage block"). We exploit this insensitivity in a new "coarse-grained" coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability.

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

PubMed

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait networks if the edges can be anchored to genetic marker data. R software tutorials, data, and supplementary material can be downloaded from: http://www.genetics.ucla.edu/labs/horvath/aten/NEO.

Genomic Model with Correlation Between Additive and Dominance Effects.

PubMed

Xiang, Tao; Christensen, Ole Fredslund; Vitezica, Zulma Gladis; Legarra, Andres

2018-05-09

Dominance genetic effects are rarely included in pedigree-based genetic evaluation. With the availability of single nucleotide polymorphism markers and the development of genomic evaluation, estimates of dominance genetic effects have become feasible using genomic best linear unbiased prediction (GBLUP). Usually, studies involving additive and dominance genetic effects ignore possible relationships between them. It has been often suggested that the magnitude of functional additive and dominance effects at the quantitative trait loci are related, but there is no existing GBLUP-like approach accounting for such correlation. Wellmann and Bennewitz showed two ways of considering directional relationships between additive and dominance effects, which they estimated in a Bayesian framework. However, these relationships cannot be fitted at the level of individuals instead of loci in a mixed model and are not compatible with standard animal or plant breeding software. This comes from a fundamental ambiguity in assigning the reference allele at a given locus. We show that, if there has been selection, assigning the most frequent as the reference allele orients the correlation between functional additive and dominance effects. As a consequence, the most frequent reference allele is expected to have a positive value. We also demonstrate that selection creates negative covariance between genotypic additive and dominance genetic values. For parameter estimation, it is possible to use a combined additive and dominance relationship matrix computed from marker genotypes, and to use standard restricted maximum likelihood (REML) algorithms based on an equivalent model. Through a simulation study, we show that such correlations can easily be estimated by mixed model software and accuracy of prediction for genetic values is slightly improved if such correlations are used in GBLUP. However, a model assuming uncorrelated effects and fitting orthogonal breeding values and dominant deviations performed similarly for prediction. Copyright © 2018, Genetics.

Inversion method applied to the rotation curves of galaxies

NASA Astrophysics Data System (ADS)

Márquez-Caicedo, L. A.; Lora-Clavijo, F. D.; Sanabria-Gómez, J. D.

2017-07-01

We used simulated annealing, Montecarlo and genetic algorithm methods for matching both numerical data of density and velocity profiles in some low surface brigthness galaxies with theoretical models of Boehmer-Harko, Navarro-Frenk-White and Pseudo Isothermal Profiles for galaxies with dark matter halos. We found that Navarro-Frenk-White model does not fit at all in contrast with the other two models which fit very well. Inversion methods have been widely used in various branches of science including astrophysics (Charbonneau 1995, ApJS, 101, 309). In this work we have used three different parametric inversion methods (MonteCarlo, Genetic Algorithm and Simmulated Annealing) in order to determine the best fit of the observed data of the density and velocity profiles of a set of low surface brigthness galaxies (De Block et al. 2001, ApJ, 122, 2396) with three models of galaxies containing dark mattter. The parameters adjusted by the inversion methods were the central density and a characteristic distance in the Boehmer-Harko BH (Boehmer & Harko 2007, JCAP, 6, 25), Navarro-Frenk-White NFW (Navarro et al. 2007, ApJ, 490, 493) and Pseudo Isothermal Profile PI (Robles & Matos 2012, MNRAS, 422, 282). The results obtained showed that the BH and PI Profile dark matter galaxies fit very well for both the density and the velocity profiles, in contrast the NFW model did not make good adjustments to the profiles in any analized galaxy.

Sex versus asex: An analysis of the role of variance conversion.

PubMed

Lewis-Pye, Andrew E M; Montalbán, Antonio

2017-04-01

The question as to why most complex organisms reproduce sexually remains a very active research area in evolutionary biology. Theories dating back to Weismann have suggested that the key may lie in the creation of increased variability in offspring, causing enhanced response to selection. Under appropriate conditions, selection is known to result in the generation of negative linkage disequilibrium, with the effect of recombination then being to increase genetic variance by reducing these negative associations between alleles. It has therefore been a matter of significant interest to understand precisely those conditions resulting in negative linkage disequilibrium, and to recognise also the conditions in which the corresponding increase in genetic variation will be advantageous. Here, we prove rigorous results for the multi-locus case, detailing the build up of negative linkage disequilibrium, and describing the long term effect on population fitness for models with and without bounds on fitness contributions from individual alleles. Under the assumption of large but finite bounds on fitness contributions from alleles, the non-linear nature of the effect of recombination on a population presents serious obstacles in finding the genetic composition of populations at equilibrium, and in establishing convergence to those equilibria. We describe techniques for analysing the long term behaviour of sexual and asexual populations for such models, and use these techniques to establish conditions resulting in higher fitnesses for sexually reproducing populations. Copyright © 2017 Elsevier Inc. All rights reserved.

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

PubMed Central

Rees, Mark; Rose, Karen E

2002-01-01

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed. PMID:12137582

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

PubMed

Rees, Mark; Rose, Karen E

2002-07-22

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed.

LIGO detector characterization with genetic programming

NASA Astrophysics Data System (ADS)

Cavaglia, Marco; Staats, Kai; Errico, Luciano; Mogushi, Kentaro; Gabbard, Hunter

2017-01-01

Genetic Programming (GP) is a supervised approach to Machine Learning. GP has for two decades been applied to a diversity of problems, from predictive and financial modelling to data mining, from code repair to optical character recognition and product design. GP uses a stochastic search, tournament, and fitness function to explore a solution space. GP evolves a population of individual programs, through multiple generations, following the principals of biological evolution (mutation and reproduction) to discover a model that best fits or categorizes features in a given data set. We apply GP to categorization of LIGO noise and show that it can effectively be used to characterize the detector non-astrophysical noise both in low latency and offline searches. National Science Foundation award PHY-1404139.

Evolution of complex dynamics

NASA Astrophysics Data System (ADS)

Wilds, Roy; Kauffman, Stuart A.; Glass, Leon

2008-09-01

We study the evolution of complex dynamics in a model of a genetic regulatory network. The fitness is associated with the topological entropy in a class of piecewise linear equations, and the mutations are associated with changes in the logical structure of the network. We compare hill climbing evolution, in which only mutations that increase the fitness are allowed, with neutral evolution, in which mutations that leave the fitness unchanged are allowed. The simple structure of the fitness landscape enables us to estimate analytically the rates of hill climbing and neutral evolution. In this model, allowing neutral mutations accelerates the rate of evolutionary advancement for low mutation frequencies. These results are applicable to evolution in natural and technological systems.

Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

PubMed Central

Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.

2013-01-01

Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933

Maintenance of Genetic Variability under Strong Stabilizing Selection: A Two-Locus Model

PubMed Central

Gavrilets, S.; Hastings, A.

1993-01-01

We study a two locus model with additive contributions to the phenotype to explore the relationship between stabilizing selection and recombination. We show that if the double heterozygote has the optimum phenotype and the contributions of the loci to the trait are different, then any symmetric stabilizing selection fitness function can maintain genetic variability provided selection is sufficiently strong relative to linkage. We present results of a detailed analysis of the quadratic fitness function which show that selection need not be extremely strong relative to recombination for the polymorphic equilibria to be stable. At these polymorphic equilibria the mean value of the trait, in general, is not equal to the optimum phenotype, there exists a large level of negative linkage disequilibrium which ``hides'' additive genetic variance, and different equilibria can be stable simultaneously. We analyze dependence of different characteristics of these equilibria on the location of optimum phenotype, on the difference in allelic effect, and on the strength of selection relative to recombination. Our overall result that stabilizing selection does not necessarily eliminate genetic variability is compatible with some experimental results where the lines subject to strong stabilizing selection did not have significant reductions in genetic variability. PMID:8514145

Hamilton's missing link.

PubMed

van Veelen, Matthijs

2007-06-07

Hamilton's famous rule was presented in 1964 in a paper called "The genetical theory of social behaviour (I and II)", Journal of Theoretical Biology 7, 1-16, 17-32. The paper contains a mathematical genetical model from which the rule supposedly follows, but it does not provide a link between the paper's central result, which states that selection dynamics take the population to a state where mean inclusive fitness is maximized, and the rule, which states that selection will lead to maximization of individual inclusive fitness. This note provides a condition under which Hamilton's rule does follow from his central result.

Linear time algorithms to construct populations fitting multiple constraint distributions at genomic scales.

PubMed

Siragusa, Enrico; Haiminen, Niina; Utro, Filippo; Parida, Laxmi

2017-10-09

Computer simulations can be used to study population genetic methods, models and parameters, as well as to predict potential outcomes. For example, in plant populations, predicting the outcome of breeding operations can be studied using simulations. In-silico construction of populations with pre-specified characteristics is an important task in breeding optimization and other population genetic studies. We present two linear time Simulation using Best-fit Algorithms (SimBA) for two classes of problems where each co-fits two distributions: SimBA-LD fits linkage disequilibrium and minimum allele frequency distributions, while SimBA-hap fits founder-haplotype and polyploid allele dosage distributions. An incremental gap-filling version of previously introduced SimBA-LD is here demonstrated to accurately fit the target distributions, allowing efficient large scale simulations. SimBA-hap accuracy and efficiency is demonstrated by simulating tetraploid populations with varying numbers of founder haplotypes, we evaluate both a linear time greedy algoritm and an optimal solution based on mixed-integer programming. SimBA is available on http://researcher.watson.ibm.com/project/5669.

Specificity of genetic and environmental risk factors for symptoms of cannabis, cocaine, alcohol, caffeine, and nicotine dependence.

PubMed

Kendler, Kenneth S; Myers, John; Prescott, Carol A

2007-11-01

Although genetic risk factors have been found to contribute to dependence on both licit and illicit psychoactive substances, we know little of how these risk factors interrelate. To clarify the structure of genetic and environmental risk factors for symptoms of dependence on cannabis, cocaine, alcohol, caffeine, and nicotine in males and females. Lifetime history by structured clinical interview. General community. Four thousand eight hundred sixty-five members of male-male and female-female pairs from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. Main Outcome Measure Lifetime symptoms of abuse of and dependence on cannabis, cocaine, alcohol, caffeine, and nicotine. Controlling for greater symptom prevalence in males, genetic and environmental parameters could be equated across sexes. Two models explained the data well. The best-fit exploratory model contained 2 genetic factors and 1 individual environmental factor contributing to all substances. The first genetic factor loaded strongly on cocaine and cannabis dependence; the second, on alcohol and nicotine dependence. Nicotine and caffeine had high substance-specific genetic effects. A confirmatory model, which also fit well, contained 1 illicit drug genetic factor--loading only on cannabis and cocaine--and 1 licit drug genetic factor loading on alcohol, caffeine, and nicotine. However, these factors were highly intercorrelated (r = + 0.82). Large substance-specific genetic effects remained for nicotine and caffeine. The pattern of genetic and environmental risk factors for psychoactive substance dependence was similar in males and females. Genetic risk factors for dependence on common psychoactive substances cannot be explained by a single factor. Rather, 2 genetic factors-one predisposing largely to illicit drug dependence, the other primarily to licit drug dependence-are needed. Furthermore, a large proportion of the genetic influences on nicotine and particularly caffeine dependence appear to be specific to those substances.

Periodic Pattern of Genetic and Fitness Diversity during Evolution of an Artificial Cell-Like System.

PubMed

Ichihashi, Norikazu; Aita, Takuyo; Motooka, Daisuke; Nakamura, Shota; Yomo, Tetsuya

2015-12-01

Genetic and phenotypic diversity are the basis of evolution. Despite their importance, however, little is known about how they change over the course of evolution. In this study, we analyzed the dynamics of the adaptive evolution of a simple evolvable artificial cell-like system using single-molecule real-time sequencing technology that reads an entire single artificial genome. We found that the genomic RNA population increases in fitness intermittently, correlating with a periodic pattern of genetic and fitness diversity produced by repeated diversification and domination. In the diversification phase, a genomic RNA population spreads within a genetic space by accumulating mutations until mutants with higher fitness are generated, resulting in an increase in fitness diversity. In the domination phase, the mutants with higher fitness dominate, decreasing both the fitness and genetic diversity. This study reveals the dynamic nature of genetic and fitness diversity during adaptive evolution and demonstrates the utility of a simplified artificial cell-like system to study evolution at an unprecedented resolution. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Comparison of random regression models with Legendre polynomials and linear splines for production traits and somatic cell score of Canadian Holstein cows.

PubMed

Bohmanova, J; Miglior, F; Jamrozik, J; Misztal, I; Sullivan, P G

2008-09-01

A random regression model with both random and fixed regressions fitted by Legendre polynomials of order 4 was compared with 3 alternative models fitting linear splines with 4, 5, or 6 knots. The effects common for all models were a herd-test-date effect, fixed regressions on days in milk (DIM) nested within region-age-season of calving class, and random regressions for additive genetic and permanent environmental effects. Data were test-day milk, fat and protein yields, and SCS recorded from 5 to 365 DIM during the first 3 lactations of Canadian Holstein cows. A random sample of 50 herds consisting of 96,756 test-day records was generated to estimate variance components within a Bayesian framework via Gibbs sampling. Two sets of genetic evaluations were subsequently carried out to investigate performance of the 4 models. Models were compared by graphical inspection of variance functions, goodness of fit, error of prediction of breeding values, and stability of estimated breeding values. Models with splines gave lower estimates of variances at extremes of lactations than the model with Legendre polynomials. Differences among models in goodness of fit measured by percentages of squared bias, correlations between predicted and observed records, and residual variances were small. The deviance information criterion favored the spline model with 6 knots. Smaller error of prediction and higher stability of estimated breeding values were achieved by using spline models with 5 and 6 knots compared with the model with Legendre polynomials. In general, the spline model with 6 knots had the best overall performance based upon the considered model comparison criteria.

Scaling laws and universality for the strength of genetic interactions in yeast

NASA Astrophysics Data System (ADS)

Velenich, Andrea; Dai, Mingjie; Gore, Jeff

2012-02-01

Genetic interactions provide a window to the organization of the thousands of biochemical reactions in living cells. If two mutations affect unrelated cellular functions, the fitness effects of their combination can be easily predicted from the two separate fitness effects. However, because of interactions, for some pairs of mutations their combined fitness effect deviates from the naive prediction. We study genetic interactions in yeast cells by analyzing a publicly available database containing experimental growth rates of 5 million double mutants. We show that the characteristic strength of genetic interactions has a simple power law dependence on the fitness effects of the two interacting mutations and that the probability distribution of genetic interactions is a universal function. We further argue that the strength of genetic interactions depends only on the fitness effects of the interacting mutations and not on their biological origin in terms of single point mutations, entire gene knockouts or even more complicated physiological perturbations. Finally, we discuss the implications of the power law scaling of genetic interactions on the ruggedness of fitness landscapes and the consequent evolutionary dynamics.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle.

PubMed

Bignardi, A B; El Faro, L; Rosa, G J M; Cardoso, V L; Machado, P F; Albuquerque, L G

2012-04-01

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Bacteria Facilitate Enteric Virus Co-infection of Mammalian Cells and Promote Genetic Recombination.

PubMed

Erickson, Andrea K; Jesudhasan, Palmy R; Mayer, Melinda J; Narbad, Arjan; Winter, Sebastian E; Pfeiffer, Julie K

2018-01-10

RNA viruses exist in genetically diverse populations due to high levels of mutations, many of which reduce viral fitness. Interestingly, intestinal bacteria can promote infection of several mammalian enteric RNA viruses, but the mechanisms and consequences are unclear. We screened a panel of 41 bacterial strains as a platform to determine how different bacteria impact infection of poliovirus, a model enteric virus. Most bacterial strains, including those extracted from cecal contents of mice, bound poliovirus, with each bacterium binding multiple virions. Certain bacterial strains increased viral co-infection of mammalian cells even at a low virus-to-host cell ratio. Bacteria-mediated viral co-infection correlated with bacterial adherence to cells. Importantly, bacterial strains that induced viral co-infection facilitated genetic recombination between two different viruses, thereby removing deleterious mutations and restoring viral fitness. Thus, bacteria-virus interactions may increase viral fitness through viral recombination at initial sites of infection, potentially limiting abortive infections. Copyright © 2017 Elsevier Inc. All rights reserved.

Meta-analysis suggests choosy females get sexy sons more than "good genes".

PubMed

Prokop, Zofia M; Michalczyk, Łukasz; Drobniak, Szymon M; Herdegen, Magdalena; Radwan, Jacek

2012-09-01

Female preferences for specific male phenotypes have been documented across a wide range of animal taxa, including numerous species where males contribute only gametes to offspring production. Yet, selective pressures maintaining such preferences are among the major unknowns of evolutionary biology. Theoretical studies suggest that preferences can evolve if they confer genetic benefits in terms of increased attractiveness of sons ("Fisherian" models) or overall fitness of offspring ("good genes" models). These two types of models predict, respectively, that male attractiveness is heritable and genetically correlated with fitness. In this meta-analysis, we draw general conclusions from over two decades worth of empirical studies testing these predictions (90 studies on 55 species in total). We found evidence for heritability of male attractiveness. However, attractiveness showed no association with traits directly associated with fitness (life-history traits). Interestingly, it did show a positive correlation with physiological traits, which include immunocompetence and condition. In conclusion, our results support "Fisherian" models of preference evolution, while providing equivocal evidence for "good genes." We pinpoint research directions that should stimulate progress in our understanding of the evolution of female choice. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

[Analysis of genetic models and gene effects on main agronomy characters in rapeseed].

PubMed

Li, J; Qiu, J; Tang, Z; Shen, L

1992-01-01

According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.

Evolutionary Perspectives on Genetic and Environmental Risk Factors for Psychiatric Disorders.

PubMed

Keller, Matthew C

2018-05-07

Evolutionary medicine uses evolutionary theory to help elucidate why humans are vulnerable to disease and disorders. I discuss two different types of evolutionary explanations that have been used to help understand human psychiatric disorders. First, a consistent finding is that psychiatric disorders are moderately to highly heritable, and many, such as schizophrenia, are also highly disabling and appear to decrease Darwinian fitness. Models used in evolutionary genetics to understand why genetic variation exists in fitness-related traits can be used to understand why risk alleles for psychiatric disorders persist in the population. The usual explanation for species-typical adaptations-natural selection-is less useful for understanding individual differences in genetic risk to disorders. Rather, two other types of models, mutation-selection-drift and balancing selection, offer frameworks for understanding why genetic variation in risk to psychiatric (and other) disorders exists, and each makes predictions that are now testable using whole-genome data. Second, species-typical capacities to mount reactions to negative events are likely to have been crafted by natural selection to minimize fitness loss. The pain reaction to tissue damage is almost certainly such an example, but it has been argued that the capacity to experience depressive symptoms such as sadness, anhedonia, crying, and fatigue in the face of adverse life situations may have been crafted by natural selection as well. I review the rationale and strength of evidence for this hypothesis. Evolutionary hypotheses of psychiatric disorders are important not only for offering explanations for why psychiatric disorders exist, but also for generating new, testable hypotheses and understanding how best to design studies and analyze data.

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 depression. All three spatial animal models estimated small location variance in breeding date, but because relatedness and breeding location were virtually uncorrelated, modelling location variance did not alter the estimated additive genetic variances. Our results show that sex-specific additive genetic effects on breeding date can be strongly positively correlated, which would affect any predicted rates of microevolutionary change in response to sexually antagonistic or congruent selection. Further, we show that inbreeding effects on breeding date can also be sex specific and that genetic effects can exceed phenotypic variation stemming from fine-scale location-based variation within a wild population. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Heritability of refractive error and ocular biometrics: the Genes in Myopia (GEM) twin study.

PubMed

Dirani, Mohamed; Chamberlain, Matthew; Shekar, Sri N; Islam, Amirul F M; Garoufalis, Pam; Chen, Christine Y; Guymer, Robyn H; Baird, Paul N

2006-11-01

A classic twin study was undertaken to assess the contribution of genes and environment to the development of refractive errors and ocular biometrics in a twin population. A total of 1224 twins (345 monozygotic [MZ] and 267 dizygotic [DZ] twin pairs) aged between 18 and 88 years were examined. All twins completed a questionnaire consisting of a medical history, education, and zygosity. Objective refraction was measured in all twins, and biometric measurements were obtained using partial coherence interferometry. Intrapair correlations for spherical equivalent and ocular biometrics were significantly higher in the MZ than in the DZ twin pairs (P < 0.05), when refraction was considered as a continuous variable. A significant gender difference in the variation of spherical equivalent and ocular biometrics was found (P < 0.05). A genetic model specifying an additive, dominant, and unique environmental factor that was sex limited was the best fit for all measured variables. Heritability of spherical equivalents of 88% and 75% were found in the men and women, respectively, whereas, that of axial length was 94% and 92%, respectively. Additive genetic effects accounted for a greater proportion of the variance in spherical equivalent, whereas the variance in ocular biometrics, particularly axial length was explained mostly by dominant genetic effects. Genetic factors, both additive and dominant, play a significant role in refractive error (myopia and hypermetropia) as well as in ocular biometrics, particularly axial length. The sex limitation ADE model (additive genetic, nonadditive genetic, and environmental components) provided the best-fit genetic model for all parameters.

A Multivariate Twin Study of the DSM-IV Criteria for Antisocial Personality Disorder

PubMed Central

Kendler, Kenneth S.; Aggen, Steven H.; Patrick, Christopher J.

2012-01-01

BACKGROUND Many assessment instruments for psychopathy are multidimensional, suggesting that distinguishable factors are needed to effectively capture variation in this personality domain. However, no prior study has examined the factor structure of the DSM-IV criteria for antisocial personality disorder (ASPD). METHODS Self-report questionnaire items reflecting all A criteria for DSM-IV ASPD were available from 4,291 twins (including both members of 1,647 pairs) from the Virginia Adult Study of Psychiatric and Substance Use Disorders. Exploratory factor analysis and twin model fitting were performed using, respectively, Mplus and Mx. RESULTS Phenotypic factor analysis produced evidence for 2 correlated factors: aggressive-disregard and disinhibition. The best-fitting multivariate twin model included two genetic and one unique environmental common factor, along with criteria-specific genetic and environmental effects. The two genetic factors closely resembled the phenotypic factors and varied in their prediction of a range of relevant criterion variables. Scores on the genetic aggressive-disregard factor score were more strongly associated with risk for conduct disorder, early and heavy alcohol use, and low educational status, whereas scores on the genetic disinhibition factor score were more strongly associated with younger age, novelty seeking, and major depression. CONCLUSION From a genetic perspective, the DSM-IV criteria for ASPD do not reflect a single dimension of liability but rather are influenced by two dimensions of genetic risk reflecting aggressive-disregard and disinhibition. The phenotypic structure of the ASPD criteria results largely from genetic and not from environmental influences. PMID:21762879

Genetic Diversity in the Interference Selection Limit

PubMed Central

Good, Benjamin H.; Walczak, Aleksandra M.; Neher, Richard A.; Desai, Michael M.

2014-01-01

Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a “linkage block”). We exploit this insensitivity in a new “coarse-grained” coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability. PMID:24675740

The effect of epistasis on sexually antagonistic genetic variation

PubMed Central

Arnqvist, Göran; Vellnow, Nikolas; Rowe, Locke

2014-01-01

There is increasing evidence of segregating sexually antagonistic (SA) genetic variation for fitness in laboratory and wild populations, yet the conditions for the maintenance of such variation can be restrictive. Epistatic interactions between genes can contribute to the maintenance of genetic variance in fitness and we suggest that epistasis between SA genes should be pervasive. Here, we explore its effect on SA genetic variation in fitness using a two locus model with negative epistasis. Our results demonstrate that epistasis often increases the parameter space showing polymorphism for SA loci. This is because selection in one locus is affected by allele frequencies at the other, which can act to balance net selection in males and females. Increased linkage between SA loci had more marginal effects. We also show that under some conditions, large portions of the parameter space evolve to a state where male benefit alleles are fixed at one locus and female benefit alleles at the other. This novel effect of epistasis on SA loci, which we term the ‘equity effect’, may have important effects on population differentiation and may contribute to speciation. More generally, these results support the suggestion that epistasis contributes to population divergence. PMID:24870040

Genetic and environmental influences on female sexual orientation, childhood gender typicality and adult gender identity.

PubMed

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates--childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation.

Inferring genetic interactions from comparative fitness data

PubMed Central

2017-01-01

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax, the fungus Aspergillus niger, and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations. PMID:29260711

Inferring genetic interactions from comparative fitness data.

PubMed

Crona, Kristina; Gavryushkin, Alex; Greene, Devin; Beerenwinkel, Niko

2017-12-20

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax , the fungus Aspergillus niger , and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.

Genetic analyses of protein yield in dairy cows applying random regression models with time-dependent and temperature x humidity-dependent covariates.

PubMed

Brügemann, K; Gernand, E; von Borstel, U U; König, S

2011-08-01

Data used in the present study included 1,095,980 first-lactation test-day records for protein yield of 154,880 Holstein cows housed on 196 large-scale dairy farms in Germany. Data were recorded between 2002 and 2009 and merged with meteorological data from public weather stations. The maximum distance between each farm and its corresponding weather station was 50 km. Hourly temperature-humidity indexes (THI) were calculated using the mean of hourly measurements of dry bulb temperature and relative humidity. On the phenotypic scale, an increase in THI was generally associated with a decrease in daily protein yield. For genetic analyses, a random regression model was applied using time-dependent (d in milk, DIM) and THI-dependent covariates. Additive genetic and permanent environmental effects were fitted with this random regression model and Legendre polynomials of order 3 for DIM and THI. In addition, the fixed curve was modeled with Legendre polynomials of order 3. Heterogeneous residuals were fitted by dividing DIM into 5 classes, and by dividing THI into 4 classes, resulting in 20 different classes. Additive genetic variances for daily protein yield decreased with increasing degrees of heat stress and were lowest at the beginning of lactation and at extreme THI. Due to higher additive genetic variances, slightly higher permanent environment variances, and similar residual variances, heritabilities were highest for low THI in combination with DIM at the end of lactation. Genetic correlations among individual values for THI were generally >0.90. These trends from the complex random regression model were verified by applying relatively simple bivariate animal models for protein yield measured in 2 THI environments; that is, defining a THI value of 60 as a threshold. These high correlations indicate the absence of any substantial genotype × environment interaction for protein yield. However, heritabilities and additive genetic variances from the random regression model tended to be slightly higher in the THI range corresponding to cows' comfort zone. Selecting such superior environments for progeny testing can contribute to an accurate genetic differentiation among selection candidates. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Cardiorespiratory fitness, BMI, and risk of hypertension: the HYPGENE study.

PubMed

Rankinen, Tuomo; Church, Timothy S; Rice, Treva; Bouchard, Claude; Blair, Steven N

2007-10-01

Cardiorespiratory fitness and regular physical activity are inversely associated with the risk of hypertension, and exercise training has been shown to lower elevated blood pressure (BP). Genetic factors contribute significantly to the interindividual differences in endurance training-induced changes in BP. However, similar data on the genotype-by-fitness interactions on the risk of hypertension are scarce. In 2000, we started a systematic collection of blood samples from all consenting subjects of the Aerobics Center Longitudinal Study (ACLS) with a goal to generate a resource for studies addressing genotype-by-fitness interaction effects on various health-related end points. Here, we introduce the rationale and design of the first study based on the ACLS genetics resource focusing on hypertension as the health outcome (HYPGENE study), and we report the associations of cardiorespiratory fitness and body mass index (BMI) with the risk of hypertension. All HYPGENE subjects (N = 1234) were healthy and normotensive at their first clinic visit. Cases (N = 629) developed hypertension during the follow-up period (mean 8.7 yr), whereas controls (N = 605) remained normotensive (mean follow-up 10.1 yr). Cardiorespiratory fitness was the strongest predictor of the hypertension risk, with each maximal metabolic equivalent unit being associated with a 19% lower risk (95% confidence interval [95% CI], 12-24%). Each baseline BMI unit was associated with a 9% higher hypertension risk (95% CI, 4-13%). However, the association of BMI was greatly attenuated (odds ratio 1.04 [95% CI, 0.99-1.09]) when fitness also was included in the model. The HYPGENE study will provide an excellent resource to address hypotheses regarding the genetic basis of hypertension while taking cardiorespiratory fitness level into account.

Common genetic and environmental contributions to post-traumatic stress disorder and alcohol dependence in young women.

PubMed

Sartor, C E; McCutcheon, V V; Pommer, N E; Nelson, E C; Grant, J D; Duncan, A E; Waldron, M; Bucholz, K K; Madden, P A F; Heath, A C

2011-07-01

The few genetically informative studies to examine post-traumatic stress disorder (PTSD) and alcohol dependence (AD), all of which are based on a male veteran sample, suggest that the co-morbidity between PTSD and AD may be attributable in part to overlapping genetic influences, but this issue has yet to be addressed in females.MethodData were derived from an all-female twin sample (n=3768) ranging in age from 18 to 29 years. A trivariate genetic model that included trauma exposure as a separate phenotype was fitted to estimate genetic and environmental contributions to PTSD and the degree to which they overlap with those that contribute to AD, after accounting for potential confounding effects of heritable influences on trauma exposure. Additive genetic influences (A) accounted for 72% of the variance in PTSD; individual-specific environmental (E) factors accounted for the remainder. An AE model also provided the best fit for AD, for which heritability was estimated to be 71%. The genetic correlation between PTSD and AD was 0.54. The heritability estimate for PTSD in our sample is higher than estimates reported in earlier studies based almost exclusively on an all-male sample in which combat exposure was the precipitating traumatic event. However, our findings are consistent with the absence of evidence for shared environmental influences on PTSD and, most importantly, the substantial overlap in genetic influences on PTSD and AD reported in these investigations. Additional research addressing potential distinctions by gender in the relative contributions of genetic and environmental influences on PTSD is merited.

A New Look at Genetic and Environmental Architecture on Lipids Using Non-Normal Structural Equation Modeling in Male Twins: The NHLBI Twin Study.

PubMed

Wu, Sheng-Hui; Ozaki, Koken; Reed, Terry; Krasnow, Ruth E; Dai, Jun

2017-07-01

This study examined genetic and environmental influences on the lipid concentrations of 1028 male twins using the novel univariate non-normal structural equation modeling (nnSEM) ADCE and ACE models. In the best fitting nnSEM ADCE model that was also better than the nnSEM ACE model, additive genetic factors (A) explained 4%, dominant genetic factors (D) explained 17%, and common (C) and unique (E) environmental factors explained 47% and 33% of the total variance of high-density lipoprotein cholesterol (HDL-C). The percentage of variation explained for other lipids was 0% (A), 30% (D), 34% (C) and 37% (E) for low-density lipoprotein cholesterol (LDL-C); 30, 0, 31 and 39% for total cholesterol; and 0, 31, 12 and 57% for triglycerides. It was concluded that additive and dominant genetic factors simultaneously affected HDL-C concentrations but not other lipids. Common and unique environmental factors influenced concentrations of all lipids.

Abdomen disease diagnosis in CT images using flexiscale curvelet transform and improved genetic algorithm.

PubMed

Sethi, Gaurav; Saini, B S

2015-12-01

This paper presents an abdomen disease diagnostic system based on the flexi-scale curvelet transform, which uses different optimal scales for extracting features from computed tomography (CT) images. To optimize the scale of the flexi-scale curvelet transform, we propose an improved genetic algorithm. The conventional genetic algorithm assumes that fit parents will likely produce the healthiest offspring that leads to the least fit parents accumulating at the bottom of the population, reducing the fitness of subsequent populations and delaying the optimal solution search. In our improved genetic algorithm, combining the chromosomes of a low-fitness and a high-fitness individual increases the probability of producing high-fitness offspring. Thereby, all of the least fit parent chromosomes are combined with high fit parent to produce offspring for the next population. In this way, the leftover weak chromosomes cannot damage the fitness of subsequent populations. To further facilitate the search for the optimal solution, our improved genetic algorithm adopts modified elitism. The proposed method was applied to 120 CT abdominal images; 30 images each of normal subjects, cysts, tumors and stones. The features extracted by the flexi-scale curvelet transform were more discriminative than conventional methods, demonstrating the potential of our method as a diagnostic tool for abdomen diseases.

The developmental association between eating disorders symptoms and symptoms of depression and anxiety in juvenile twin girls.

PubMed

Silberg, Judy L; Bulik, Cynthia M

2005-12-01

We investigated the role of genetic and environmental factors in the developmental association among symptoms of eating disorders, depression, and anxiety syndromes in 8-13-year-old and 14-17-year-old twin girls. Multivariate genetic models were fitted to child-reported longitudinal symptom data gathered from clinical interview on 408 MZ and 198 DZ female twin pairs from the Virginia Twin Study of Adolescent Behavioural Development (VTSABD). Model-fitting revealed distinct etiological patterns underlying the association among symptoms of eating disorders, depression, overanxious disorder (OAD), and separation anxiety disorder (SAD) during the course of development: 1) a common genetic factor influencing liability to all symptoms - of early and later OAD, depression, SAD, and eating symptoms; 2) a distinct genetic factor specifically indexing liability to early eating disorders symptoms; 3) a shared environmental factor specifically influencing early depression and early eating disorders symptoms; and 4) a common environmental factor affecting liability to symptoms of later eating disorders and both early and later separation anxiety. These results suggest a pervasive genetic effect that influences liability to symptoms of over-anxiety, separation anxiety, depression, and eating disorder throughout development, a shared environmental influence on later adolescent eating problems and persistent separation anxiety, genetic influences specific to early eating disorders symptoms, and a shared environmental factor influencing symptoms of early eating and depression.

Genetic background in partitioning of metabolizable energy efficiency in dairy cows.

PubMed

Mehtiö, T; Negussie, E; Mäntysaari, P; Mäntysaari, E A; Lidauer, M H

2018-05-01

The main objective of this study was to assess the genetic differences in metabolizable energy efficiency and efficiency in partitioning metabolizable energy in different pathways: maintenance, milk production, and growth in primiparous dairy cows. Repeatability models for residual energy intake (REI) and metabolizable energy intake (MEI) were compared and the genetic and permanent environmental variations in MEI were partitioned into its energy sinks using random regression models. We proposed 2 new feed efficiency traits: metabolizable energy efficiency (MEE), which is formed by modeling MEI fitting regressions on energy sinks [metabolic body weight (BW 0.75 ), energy-corrected milk, body weight gain, and body weight loss] directly; and partial MEE (pMEE), where the model for MEE is extended with regressions on energy sinks nested within additive genetic and permanent environmental effects. The data used were collected from Luke's experimental farms Rehtijärvi and Minkiö between 1998 and 2014. There were altogether 12,350 weekly MEI records on 495 primiparous Nordic Red dairy cows from wk 2 to 40 of lactation. Heritability estimates for REI and MEE were moderate, 0.33 and 0.26, respectively. The estimate of the residual variance was smaller for MEE than for REI, indicating that analyzing weekly MEI observations simultaneously with energy sinks is preferable. Model validation based on Akaike's information criterion showed that pMEE models fitted the data even better and also resulted in smaller residual variance estimates. However, models that included random regression on BW 0.75 converged slowly. The resulting genetic standard deviation estimate from the pMEE coefficient for milk production was 0.75 MJ of MEI/kg of energy-corrected milk. The derived partial heritabilities for energy efficiency in maintenance, milk production, and growth were 0.02, 0.06, and 0.04, respectively, indicating that some genetic variation may exist in the efficiency of using metabolizable energy for different pathways in dairy cows. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Is my study system good enough? A case study for identifying maternal effects.

PubMed

Holand, Anna Marie; Steinsland, Ingelin

2016-06-01

In this paper, we demonstrate how simulation studies can be used to answer questions about identifiability and consequences of omitting effects from a model. The methodology is presented through a case study where identifiability of genetic and/or individual (environmental) maternal effects is explored. Our study system is a wild house sparrow ( Passer domesticus ) population with known pedigree. We fit pedigree-based (generalized) linear mixed models (animal models), with and without additive genetic and individual maternal effects, and use deviance information criterion (DIC) for choosing between these models. Pedigree and R-code for simulations are available. For this study system, the simulation studies show that only large maternal effects can be identified. The genetic maternal effect (and similar for individual maternal effect) has to be at least half of the total genetic variance to be identified. The consequences of omitting a maternal effect when it is present are explored. Our results indicate that the total (genetic and individual) variance are accounted for. When an individual (environmental) maternal effect is omitted from the model, this only influences the estimated (direct) individual (environmental) variance. When a genetic maternal effect is omitted from the model, both (direct) genetic and (direct) individual variance estimates are overestimated.

BAIAP2 is related to emotional modulation of human memory strength.

PubMed

Luksys, Gediminas; Ackermann, Sandra; Coynel, David; Fastenrath, Matthias; Gschwind, Leo; Heck, Angela; Rasch, Bjoern; Spalek, Klara; Vogler, Christian; Papassotiropoulos, Andreas; de Quervain, Dominique

2014-01-01

Memory performance is the result of many distinct mental processes, such as memory encoding, forgetting, and modulation of memory strength by emotional arousal. These processes, which are subserved by partly distinct molecular profiles, are not always amenable to direct observation. Therefore, computational models can be used to make inferences about specific mental processes and to study their genetic underpinnings. Here we combined a computational model-based analysis of memory-related processes with high density genetic information derived from a genome-wide study in healthy young adults. After identifying the best-fitting model for a verbal memory task and estimating the best-fitting individual cognitive parameters, we found a common variant in the gene encoding the brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2) that was related to the model parameter reflecting modulation of verbal memory strength by negative valence. We also observed an association between the same genetic variant and a similar emotional modulation phenotype in a different population performing a picture memory task. Furthermore, using functional neuroimaging we found robust genotype-dependent differences in activity of the parahippocampal cortex that were specifically related to successful memory encoding of negative versus neutral information. Finally, we analyzed cortical gene expression data of 193 deceased subjects and detected significant BAIAP2 genotype-dependent differences in BAIAP2 mRNA levels. Our findings suggest that model-based dissociation of specific cognitive parameters can improve the understanding of genetic underpinnings of human learning and memory.

The Developmental Association between Eating Disorders Symptoms and Symptoms of Depression and Anxiety in Juvenile Twin Girls

ERIC Educational Resources Information Center

Silberg, Judy L.; Bulik, Cynthia M.

2005-01-01

Objective: We investigated the role of genetic and environmental factors in the developmental association among symptoms of eating disorders, depression, and anxiety syndromes in 8-13-year-old and 14-17-year-old twin girls. Methods: Multivariate genetic models were fitted to child-reported longitudinal symptom data gathered from clinical interview…

Genetic drift and selection in many-allele range expansions.

PubMed

Weinstein, Bryan T; Lavrentovich, Maxim O; Möbius, Wolfram; Murray, Andrew W; Nelson, David R

2017-12-01

We experimentally and numerically investigate the evolutionary dynamics of four competing strains of E. coli with differing expansion velocities in radially expanding colonies. We compare experimental measurements of the average fraction, correlation functions between strains, and the relative rates of genetic domain wall annihilations and coalescences to simulations modeling the population as a one-dimensional ring of annihilating and coalescing random walkers with deterministic biases due to selection. The simulations reveal that the evolutionary dynamics can be collapsed onto master curves governed by three essential parameters: (1) an expansion length beyond which selection dominates over genetic drift; (2) a characteristic angular correlation describing the size of genetic domains; and (3) a dimensionless constant quantifying the interplay between a colony's curvature at the frontier and its selection length scale. We measure these parameters with a new technique that precisely measures small selective differences between spatially competing strains and show that our simulations accurately predict the dynamics without additional fitting. Our results suggest that the random walk model can act as a useful predictive tool for describing the evolutionary dynamics of range expansions composed of an arbitrary number of genotypes with different fitnesses.

Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment.

PubMed

da Fonseca Neto, João Viana; Abreu, Ivanildo Silva; da Silva, Fábio Nogueira

2010-04-01

Toward the synthesis of state-space controllers, a neural-genetic model based on the linear quadratic regulator design for the eigenstructure assignment of multivariable dynamic systems is presented. The neural-genetic model represents a fusion of a genetic algorithm and a recurrent neural network (RNN) to perform the selection of the weighting matrices and the algebraic Riccati equation solution, respectively. A fourth-order electric circuit model is used to evaluate the convergence of the computational intelligence paradigms and the control design method performance. The genetic search convergence evaluation is performed in terms of the fitness function statistics and the RNN convergence, which is evaluated by landscapes of the energy and norm, as a function of the parameter deviations. The control problem solution is evaluated in the time and frequency domains by the impulse response, singular values, and modal analysis.

Measured, modeled, and causal conceptions of fitness

PubMed Central

Abrams, Marshall

2012-01-01

This paper proposes partial answers to the following questions: in what senses can fitness differences plausibly be considered causes of evolution?What relationships are there between fitness concepts used in empirical research, modeling, and abstract theoretical proposals? How does the relevance of different fitness concepts depend on research questions and methodological constraints? The paper develops a novel taxonomy of fitness concepts, beginning with type fitness (a property of a genotype or phenotype), token fitness (a property of a particular individual), and purely mathematical fitness. Type fitness includes statistical type fitness, which can be measured from population data, and parametric type fitness, which is an underlying property estimated by statistical type fitnesses. Token fitness includes measurable token fitness, which can be measured on an individual, and tendential token fitness, which is assumed to be an underlying property of the individual in its environmental circumstances. Some of the paper's conclusions can be outlined as follows: claims that fitness differences do not cause evolution are reasonable when fitness is treated as statistical type fitness, measurable token fitness, or purely mathematical fitness. Some of the ways in which statistical methods are used in population genetics suggest that what natural selection involves are differences in parametric type fitnesses. Further, it's reasonable to think that differences in parametric type fitness can cause evolution. Tendential token fitnesses, however, are not themselves sufficient for natural selection. Though parametric type fitnesses are typically not directly measurable, they can be modeled with purely mathematical fitnesses and estimated by statistical type fitnesses, which in turn are defined in terms of measurable token fitnesses. The paper clarifies the ways in which fitnesses depend on pragmatic choices made by researchers. PMID:23112804

Sexually antagonistic genetic variance for fitness in an ancestral and a novel environment.

PubMed

Delcourt, Matthieu; Blows, Mark W; Rundle, Howard D

2009-06-07

The intersex genetic correlation for fitness , a standardized measure of the degree to which male and female fitness covary genetically, has consequences for important evolutionary processes, but few estimates are available and none have explored how it changes with environment. Using a half-sibling breeding design, we estimated the genetic (co)variance matrix (G) for male and female fitness, and the resulting , in Drosophila serrata. Our estimates were performed in two environments: the laboratory yeast food to which the population was well adapted and a novel corn food. The major axis of genetic variation for fitness in the two environments, accounting for 51.3 per cent of the total genetic variation, was significant and revealed a strong signal of sexual antagonism, loading negatively in both environments on males but positively on females. Consequently, estimates of were negative in both environments (-0.34 and -0.73, respectively), indicating that the majority of genetic variance segregating in this population has contrasting effects on male and female fitness. The possible strengthening of the negative in this novel environment may be a consequence of no history of selection for amelioration of sexual conflict. Additional studies from a diverse range of novel environments will be needed to determine the generality of this finding.

Genetic hitchhiking can promote the initial spread of strong altruism

PubMed Central

2008-01-01

Background The evolutionary origin of strong altruism (where the altruist pays an absolute cost in terms of fitness) towards non-kin has never been satisfactorily explained since no mechanism (except genetic drift) seems to be able to overcome the fitness disadvantage of the individual who practiced altruism in the first place. Results Here we consider a multilocus, single-generation random group model and demonstrate that with low, but realistic levels of recombination and social heterosis (selecting for allelic diversity within groups) altruism can evolve without invoking kin selection, because sampling effects in the formation of temporary groups and selection for complementary haplotypes generate nonrandom associations between alleles at polymorphic loci. Conclusion By letting altruism get off the ground, selection on other genes favourably interferes with the eventual fate of the altruistic trait due to genetic hitchhiking. PMID:18847475

Cannabis and Depression: A Twin Model Approach to Co-morbidity.

PubMed

Smolkina, M; Morley, K I; Rijsdijk, F; Agrawal, A; Bergin, J E; Nelson, E C; Statham, D; Martin, N G; Lynskey, M T

2017-07-01

Cannabis use disorder (CUD) co-occurs with major depressive disorder (MDD) more frequently than would be expected by chance. However, studies to date have not produced a clear understanding of the mechanisms underlying this co-morbidity. Genetically informative studies can add valuable insight to this problem, as they allow the evaluation of competing models of co-morbidity. This study uses data from the Australian Twin Registry to compare 13 co-morbidity twin models initially proposed by Neale and Kendler (Am J Hum Genet 57:935-953, 1995). The analysis sample comprised 2410 male and female monozygotic and dizygotic twins (average age 32) who were assessed on CUD and MDD using the SSAGA-OZ interview. Data were analyzed in OpenMx. Of the 13 different co-morbidity models, two fit equally well: CUD causes MDD and Random Multiformity of CUD. Both fit substantially better than the Correlated Liabilities model. Although the current study cannot differentiate between them statistically, these models, in combination, suggest that CUD risk factors may causally influence the risk to develop MDD, but only when risk for CUD is high.

Modelling and estimating pollen movement in oilseed rape (Brassica napus) at the landscape scale using genetic markers.

PubMed

Devaux, C; Lavigne, C; Austerlitz, F; Klein, E K

2007-02-01

Understanding patterns of pollen movement at the landscape scale is important for establishing management rules following the release of genetically modified (GM) crops. We use here a mating model adapted to cultivated species to estimate dispersal kernels from the genotypes of the progenies of male-sterile plants positioned at different sampling sites within a 10 x 10-km oilseed rape production area. Half of the pollen clouds sampled by the male-sterile plants originated from uncharacterized pollen sources that could consist of both large volunteer and feral populations, and fields within and outside the study area. The geometric dispersal kernel was the most appropriate to predict pollen movement in the study area. It predicted a much larger proportion of long-distance pollination than previously fitted dispersal kernels. This best-fitting mating model underestimated the level of differentiation among pollen clouds but could predict its spatial structure. The estimation method was validated on simulated genotypic data, and proved to provide good estimates of both the shape of the dispersal kernel and the rate and composition of pollen issued from uncharacterized pollen sources. The best dispersal kernel fitted here, the geometric kernel, should now be integrated into models that aim at predicting gene flow at the landscape level, in particular between GM and non-GM crops.

Variable pleiotropic effects from mutations at the same locus hamper prediction of fitness from a fitness component.

PubMed

Pepin, Kim M; Samuel, Melanie A; Wichman, Holly A

2006-04-01

The relationship of genotype, fitness components, and fitness can be complicated by genetic effects such as pleiotropy and epistasis and by heterogeneous environments. However, because it is often difficult to measure genotype and fitness directly, fitness components are commonly used to estimate fitness without regard to genetic architecture. The small bacteriophage X174 enables direct evaluation of genetic and environmental effects on fitness components and fitness. We used 15 mutants to study mutation effects on attachment rate and fitness in six hosts. The mutants differed from our lab strain of X174 by only one or two amino acids in the major capsid protein (gpF, sites 101 and 102). The sites are variable in natural and experimentally evolved X174 populations and affect phage attachment rate. Within the limits of detection of our assays, all mutations were neutral or deleterious relative to the wild type; 11 mutants had decreased host range. While fitness was predictable from attachment rate in most cases, 3 mutants had rapid attachment but low fitness on most hosts. Thus, some mutations had a pleiotropic effect on a fitness component other than attachment rate. In addition, on one host most mutants had high attachment rate but decreased fitness, suggesting that pleiotropic effects also depended on host. The data highlight that even in this simple, well-characterized system, prediction of fitness from a fitness component depends on genetic architecture and environment.

Multivariate modelling of endophenotypes associated with the metabolic syndrome in Chinese twins.

PubMed

Pang, Z; Zhang, D; Li, S; Duan, H; Hjelmborg, J; Kruse, T A; Kyvik, K O; Christensen, K; Tan, Q

2010-12-01

The common genetic and environmental effects on endophenotypes related to the metabolic syndrome have been investigated using bivariate and multivariate twin models. This paper extends the pairwise analysis approach by introducing independent and common pathway models to Chinese twin data. The aim was to explore the common genetic architecture in the development of these phenotypes in the Chinese population. Three multivariate models including the full saturated Cholesky decomposition model, the common factor independent pathway model and the common factor common pathway model were fitted to 695 pairs of Chinese twins representing six phenotypes including BMI, total cholesterol, total triacylglycerol, fasting glucose, HDL and LDL. Performances of the nested models were compared with that of the full Cholesky model. Cross-phenotype correlation coefficients gave clear indication of common genetic or environmental backgrounds in the phenotypes. Decomposition of phenotypic correlation by the Cholesky model revealed that the observed phenotypic correlation among lipid phenotypes had genetic and unique environmental backgrounds. Both pathway models suggest a common genetic architecture for lipid phenotypes, which is distinct from that of the non-lipid phenotypes. The declining performance with model restriction indicates biological heterogeneity in development among some of these phenotypes. Our multivariate analyses revealed common genetic and environmental backgrounds for the studied lipid phenotypes in Chinese twins. Model performance showed that physiologically distinct endophenotypes may follow different genetic regulations.

Random genetic drift, natural selection, and noise in human cranial evolution.

PubMed

Roseman, Charles C

2016-08-01

This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A multivariate twin study of the DSM-IV criteria for antisocial personality disorder.

PubMed

Kendler, Kenneth S; Aggen, Steven H; Patrick, Christopher J

2012-02-01

Many assessment instruments for psychopathy are multidimensional, suggesting that distinguishable factors are needed to effectively capture variation in this personality domain. However, no prior study has examined the factor structure of the DSM-IV criteria for antisocial personality disorder (ASPD). Self-report questionnaire items reflecting all A criteria for DSM-IV ASPD were available from 4291 twins (including both members of 1647 pairs) from the Virginia Adult Study of Psychiatric and Substance Use Disorders. Exploratory factor analysis and twin model fitting were performed using, respectively, Mplus and Mx. Phenotypic factor analysis produced evidence for two correlated factors: aggressive-disregard and disinhibition. The best-fitting multivariate twin model included two genetic and one unique environmental common factor, along with criteria-specific genetic and environmental effects. The two genetic factors closely resembled the phenotypic factors and varied in their prediction of a range of relevant criterion variables. Scores on the genetic aggressive-disregard factor score were more strongly associated with risk for conduct disorder, early and heavy alcohol use, and low educational status, whereas scores on the genetic disinhibition factor score were more strongly associated with younger age, novelty seeking, and major depression. From a genetic perspective, the DSM-IV criteria for ASPD do not reflect a single dimension of liability but rather are influenced by two dimensions of genetic risk reflecting aggressive-disregard and disinhibition. The phenotypic structure of the ASPD criteria results largely from genetic and not from environmental influences. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Shared genetic determinants of axial length and height in children: the Guangzhou twin eye study.

PubMed

Zhang, Jian; Hur, Yoon-Mi; Huang, Wenyong; Ding, Xiaohu; Feng, Ke; He, Mingguang

2011-01-01

To describe the association between axial length (AL) and height and to estimate the extent to which shared genetic or environmental factors influence this covariance. Study participants were recruited from the Guangzhou Twin Registry. Axial length was measured using partial coherence laser interferometry. Height was measured with the participants standing without shoes. We computed twin pairwise correlations and cross-twin cross-trait correlations between AL and height for monozygotic and dizygotic twins and performed model-fitting analyses using a multivariate Cholesky model. The right eye was arbitrarily selected to represent AL of participants. Five hundred sixty-five twin pairs (359 monozygotic and 206 dizygotic) aged 7 to 15 years were available for analysis. Phenotypic correlation between AL and height was 0.46 but decreased to 0.19 after adjusting for age, sex, and age × sex interaction. Bivariate Cholesky model-fitting analyses revealed that 89% of phenotypic correlation was due to shared genetic factors and 11% was due to shared random environmental factors, which includes measurement error. Covariance of AL and height is largely attributable to shared genes. Given that AL is a key determinant of myopia, further work is needed to confirm gene sharing between myopia and stature.

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

PubMed

Smith, Shane R T; Connallon, Tim

2017-05-01

Maternal inheritance of mitochondrial DNA (mtDNA) facilitates the evolutionary accumulation of mutations with sex-biased fitness effects. Whereas maternal inheritance closely aligns mtDNA evolution with natural selection in females, it makes it indifferent to evolutionary changes that exclusively benefit males. The constrained response of mtDNA to selection in males can lead to asymmetries in the relative contributions of mitochondrial genes to female versus male fitness variation. Here, we examine the impact of genetic drift and the distribution of fitness effects (DFE) among mutations-including the correlation of mutant fitness effects between the sexes-on mitochondrial genetic variation for fitness. We show how drift, genetic correlations, and skewness of the DFE determine the relative contributions of mitochondrial genes to male versus female fitness variance. When mutant fitness effects are weakly correlated between the sexes, and the effective population size is large, mitochondrial genes should contribute much more to male than to female fitness variance. In contrast, high fitness correlations and small population sizes tend to equalize the contributions of mitochondrial genes to female versus male variance. We discuss implications of these results for the evolution of mitochondrial genome diversity and the genetic architecture of female and male fitness. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

An Efficient Functional Test Generation Method For Processors Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Hudec, Ján; Gramatová, Elena

2015-07-01

The paper presents a new functional test generation method for processors testing based on genetic algorithms and evolutionary strategies. The tests are generated over an instruction set architecture and a processor description. Such functional tests belong to the software-oriented testing. Quality of the tests is evaluated by code coverage of the processor description using simulation. The presented test generation method uses VHDL models of processors and the professional simulator ModelSim. The rules, parameters and fitness functions were defined for various genetic algorithms used in automatic test generation. Functionality and effectiveness were evaluated using the RISC type processor DP32.

Modeling the Etiology of Individual Differences in Early Reading Development: Evidence for Strong Genetic Influences

PubMed Central

Christopher, Micaela E.; Hulslander, Jacqueline; Byrne, Brian; Samuelsson, Stefan; Keenan, Janice M.; Pennington, Bruce; DeFries, John C.; Wadsworth, Sally J.; Willcutt, Erik; Olson, Richard K.

2012-01-01

We explored the etiology of individual differences in reading development from post-kindergarten to post-4th grade by analyzing data from 487 twin pairs tested in Colorado. Data from three reading measures and one spelling measure were fit to biometric latent growth curve models, allowing us to extend previous behavioral genetic studies of the etiology of early reading development at specific time points. We found primarily genetic influences on individual differences at post-1st grade for all measures. Genetic influences on variance in growth rates were also found, with evidence of small, nonsignificant, shared environmental influences for two measures. We discuss our results, including their implications for educational policy. PMID:24489459

Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort.

PubMed

Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G

2017-08-01

Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.

Concerted evolution of life stage performances signals recent selection on yeast nitrogen use.

PubMed

Ibstedt, Sebastian; Stenberg, Simon; Bagés, Sara; Gjuvsland, Arne B; Salinas, Francisco; Kourtchenko, Olga; Samy, Jeevan K A; Blomberg, Anders; Omholt, Stig W; Liti, Gianni; Beltran, Gemma; Warringer, Jonas

2015-01-01

Exposing natural selection driving phenotypic and genotypic adaptive differentiation is an extraordinary challenge. Given that an organism's life stages are exposed to the same environmental variations, we reasoned that fitness components, such as the lag, rate, and efficiency of growth, directly reflecting performance in these life stages, should often be selected in concert. We therefore conjectured that correlations between fitness components over natural isolates, in a particular environmental context, would constitute a robust signal of recent selection. Critically, this test for selection requires fitness components to be determined by different genetic loci. To explore our conjecture, we exhaustively evaluated the lag, rate, and efficiency of asexual population growth of natural isolates of the model yeast Saccharomyces cerevisiae in a large variety of nitrogen-limited environments. Overall, fitness components were well correlated under nitrogen restriction. Yeast isolates were further crossed in all pairwise combinations and coinheritance of each fitness component and genetic markers were traced. Trait variations tended to map to quantitative trait loci (QTL) that were private to a single fitness component. We further traced QTLs down to single-nucleotide resolution and uncovered loss-of-function mutations in RIM15, PUT4, DAL1, and DAL4 as the genetic basis for nitrogen source use variations. Effects of SNPs were unique for a single fitness component, strongly arguing against pleiotropy between lag, rate, and efficiency of reproduction under nitrogen restriction. The strong correlations between life stage performances that cannot be explained by pleiotropy compellingly support adaptive differentiation of yeast nitrogen source use and suggest a generic approach for detecting selection. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

PubMed

Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

2012-08-01

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

In silico evolution of biochemical networks

NASA Astrophysics Data System (ADS)

Francois, Paul

2010-03-01

We use computational evolution to select models of genetic networks that can be built from a predefined set of parts to achieve a certain behavior. Selection is made with the help of a fitness defining biological functions in a quantitative way. This fitness has to be specific to a process, but general enough to find processes common to many species. Computational evolution favors models that can be built by incremental improvements in fitness rather than via multiple neutral steps or transitions through less fit intermediates. With the help of these simulations, we propose a kinetic view of evolution, where networks are rapidly selected along a fitness gradient. This mathematics recapitulates Darwin's original insight that small changes in fitness can rapidly lead to the evolution of complex structures such as the eye, and explain the phenomenon of convergent/parallel evolution of similar structures in independent lineages. We will illustrate these ideas with networks implicated in embryonic development and patterning of vertebrates and primitive insects.

Understanding Host-Switching by Ecological Fitting

PubMed Central

Araujo, Sabrina B. L.; Braga, Mariana Pires; Brooks, Daniel R.; Agosta, Salvatore J.; Hoberg, Eric P.; von Hartenthal, Francisco W.; Boeger, Walter A.

2015-01-01

Despite the fact that parasites are highly specialized with respect to their hosts, empirical evidence demonstrates that host switching rather than co-speciation is the dominant factor influencing the diversification of host-parasite associations. Ecological fitting in sloppy fitness space has been proposed as a mechanism allowing ecological specialists to host-switch readily. That proposal is tested herein using an individual-based model of host switching. The model considers a parasite species exposed to multiple host resources. Through time host range expansion can occur readily without the prior evolution of novel genetic capacities. It also produces non-linear variation in the size of the fitness space. The capacity for host colonization is strongly influenced by propagule pressure early in the process and by the size of the fitness space later. The simulations suggest that co-adaptation may be initiated by the temporary loss of less fit phenotypes. Further, parasites can persist for extended periods in sub-optimal hosts, and thus may colonize distantly related hosts by a "stepping-stone" process. PMID:26431199

Stable cycling in discrete-time genetic models.

PubMed

Hastings, A

1981-11-01

Examples of stable cycling are discussed for two-locus, two-allele, deterministic, discrete-time models with constant fitnesses. The cases that cycle were found by using numerical techniques to search for stable Hopf bifurcations. One consequence of the results is that apparent cases of directional selection may be due to stable cycling.

Genetic Diversity and Association Studies in US Hispanic/Latino Populations: Applications in the Hispanic Community Health Study/Study of Latinos

PubMed Central

Conomos, Matthew P.; Laurie, Cecelia A.; Stilp, Adrienne M.; Gogarten, Stephanie M.; McHugh, Caitlin P.; Nelson, Sarah C.; Sofer, Tamar; Fernández-Rhodes, Lindsay; Justice, Anne E.; Graff, Mariaelisa; Young, Kristin L.; Seyerle, Amanda A.; Avery, Christy L.; Taylor, Kent D.; Rotter, Jerome I.; Talavera, Gregory A.; Daviglus, Martha L.; Wassertheil-Smoller, Sylvia; Schneiderman, Neil; Heiss, Gerardo; Kaplan, Robert C.; Franceschini, Nora; Reiner, Alex P.; Shaffer, John R.; Barr, R. Graham; Kerr, Kathleen F.; Browning, Sharon R.; Browning, Brian L.; Weir, Bruce S.; Avilés-Santa, M. Larissa; Papanicolaou, George J.; Lumley, Thomas; Szpiro, Adam A.; North, Kari E.; Rice, Ken; Thornton, Timothy A.; Laurie, Cathy C.

2016-01-01

US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a “genetic-analysis group” variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness. PMID:26748518

Bayesian inference of selection in a heterogeneous environment from genetic time-series data.

PubMed

Gompert, Zachariah

2016-01-01

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild. © 2015 John Wiley & Sons Ltd.

Genetic Analysis of Reduced γ-Tocopherol Content in Ethiopian Mustard Seeds.

PubMed

García-Navarro, Elena; Fernández-Martínez, José M; Pérez-Vich, Begoña; Velasco, Leonardo

2016-01-01

Ethiopian mustard (Brassica carinata A. Braun) line BCT-6, with reduced γ-tocopherol content in the seeds, has been previously developed. The objective of this research was to conduct a genetic analysis of seed tocopherols in this line. BCT-6 was crossed with the conventional line C-101 and the F1, F2, and BC plant generations were analyzed. Generation mean analysis using individual scaling tests indicated that reduced γ-tocopherol content fitted an additive-dominant genetic model with predominance of additive effects and absence of epistatic interactions. This was confirmed through a joint scaling test and additional testing of the goodness of fit of the model. Conversely, epistatic interactions were identified for total tocopherol content. Estimation of the minimum number of genes suggested that both γ- and total tocopherol content may be controlled by two genes. A positive correlation between total tocopherol content and the proportion of γ-tocopherol was identified in the F2 generation. Additional research on the feasibility of developing germplasm with high tocopherol content and reduced concentration of γ-tocopherol is required.

SPLICER - A GENETIC ALGORITHM TOOL FOR SEARCH AND OPTIMIZATION, VERSION 1.0 (MACINTOSH VERSION)

NASA Technical Reports Server (NTRS)

Wang, L.

1994-01-01

SPLICER is a genetic algorithm tool which can be used to solve search and optimization problems. Genetic algorithms are adaptive search procedures (i.e. problem solving methods) based loosely on the processes of natural selection and Darwinian "survival of the fittest." SPLICER provides the underlying framework and structure for building a genetic algorithm application. These algorithms apply genetically-inspired operators to populations of potential solutions in an iterative fashion, creating new populations while searching for an optimal or near-optimal solution to the problem at hand. SPLICER 1.0 was created using a modular architecture that includes a Genetic Algorithm Kernel, interchangeable Representation Libraries, Fitness Modules and User Interface Libraries, and well-defined interfaces between these components. The architecture supports portability, flexibility, and extensibility. SPLICER comes with all source code and several examples. For instance, a "traveling salesperson" example searches for the minimum distance through a number of cities visiting each city only once. Stand-alone SPLICER applications can be used without any programming knowledge. However, to fully utilize SPLICER within new problem domains, familiarity with C language programming is essential. SPLICER's genetic algorithm (GA) kernel was developed independent of representation (i.e. problem encoding), fitness function or user interface type. The GA kernel comprises all functions necessary for the manipulation of populations. These functions include the creation of populations and population members, the iterative population model, fitness scaling, parent selection and sampling, and the generation of population statistics. In addition, miscellaneous functions are included in the kernel (e.g., random number generators). Different problem-encoding schemes and functions are defined and stored in interchangeable representation libraries. This allows the GA kernel to be used with any representation scheme. The SPLICER tool provides representation libraries for binary strings and for permutations. These libraries contain functions for the definition, creation, and decoding of genetic strings, as well as multiple crossover and mutation operators. Furthermore, the SPLICER tool defines the appropriate interfaces to allow users to create new representation libraries. Fitness modules are the only component of the SPLICER system a user will normally need to create or alter to solve a particular problem. Fitness functions are defined and stored in interchangeable fitness modules which must be created using C language. Within a fitness module, a user can create a fitness (or scoring) function, set the initial values for various SPLICER control parameters (e.g., population size), create a function which graphically displays the best solutions as they are found, and provide descriptive information about the problem. The tool comes with several example fitness modules, while the process of developing a fitness module is fully discussed in the accompanying documentation. The user interface is event-driven and provides graphic output in windows. SPLICER is written in Think C for Apple Macintosh computers running System 6.0.3 or later and Sun series workstations running SunOS. The UNIX version is easily ported to other UNIX platforms and requires MIT's X Window System, Version 11 Revision 4 or 5, MIT's Athena Widget Set, and the Xw Widget Set. Example executables and source code are included for each machine version. The standard distribution media for the Macintosh version is a set of three 3.5 inch Macintosh format diskettes. The standard distribution medium for the UNIX version is a .25 inch streaming magnetic tape cartridge in UNIX tar format. For the UNIX version, alternate distribution media and formats are available upon request. SPLICER was developed in 1991.

Genetic and Environmental Influences on Female Sexual Orientation, Childhood Gender Typicality and Adult Gender Identity

PubMed Central

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Background Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates – childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Methodology/Principal Findings Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. Conclusions/Significance This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation. PMID:21760939

An alternative covariance estimator to investigate genetic heterogeneity in populations.

PubMed

Heslot, Nicolas; Jannink, Jean-Luc

2015-11-26

For genomic prediction and genome-wide association studies (GWAS) using mixed models, covariance between individuals is estimated using molecular markers. Based on the properties of mixed models, using available molecular data for prediction is optimal if this covariance is known. Under this assumption, adding individuals to the analysis should never be detrimental. However, some empirical studies showed that increasing training population size decreased prediction accuracy. Recently, results from theoretical models indicated that even if marker density is high and the genetic architecture of traits is controlled by many loci with small additive effects, the covariance between individuals, which depends on relationships at causal loci, is not always well estimated by the whole-genome kinship. We propose an alternative covariance estimator named K-kernel, to account for potential genetic heterogeneity between populations that is characterized by a lack of genetic correlation, and to limit the information flow between a priori unknown populations in a trait-specific manner. This is similar to a multi-trait model and parameters are estimated by REML and, in extreme cases, it can allow for an independent genetic architecture between populations. As such, K-kernel is useful to study the problem of the design of training populations. K-kernel was compared to other covariance estimators or kernels to examine its fit to the data, cross-validated accuracy and suitability for GWAS on several datasets. It provides a significantly better fit to the data than the genomic best linear unbiased prediction model and, in some cases it performs better than other kernels such as the Gaussian kernel, as shown by an empirical null distribution. In GWAS simulations, alternative kernels control type I errors as well as or better than the classical whole-genome kinship and increase statistical power. No or small gains were observed in cross-validated prediction accuracy. This alternative covariance estimator can be used to gain insight into trait-specific genetic heterogeneity by identifying relevant sub-populations that lack genetic correlation between them. Genetic correlation can be 0 between identified sub-populations by performing automatic selection of relevant sets of individuals to be included in the training population. It may also increase statistical power in GWAS.

Evidence for heritability of adult men's sexual interest in youth under age 16 from a population-based extended twin design.

PubMed

Alanko, Katarina; Salo, Benny; Mokros, Andreas; Santtila, Pekka

2013-04-01

Sexual interest in children resembles sexual gender orientation in terms of early onset and stability across the life span. Although a genetic component to sexual interest in children seems possible, no research has addressed this question to date. Prior research showing familial transmission of pedophilia remains inconclusive about shared environmental or genetic factors. Studies from the domains of sexual orientation and sexually problematic behavior among children pointed toward genetic components. Adult men's sexual interest in youthfulness-related cues may be genetically influenced. The aim of the present study was to test whether male sexual interest in children and youth under age 16 involves a heritable component. The main outcome measure was responses in a confidential survey concerning sexual interest, fantasies, or activity pertaining to children under the age of 16 years during the previous 12 months. The present study used an extended family design within behavioral genetic modeling to estimate the contributions of genetic and environmental factors in the occurrence of adult men's sexual interest in children and youth under age 16. Participants were male twins and their male siblings from a population-based Finnish cohort sample aged 21-43 years (N = 3,967). The incidence of sexual interest in children under age was 3%. Twin correlations were higher for monozygotic than for dizygotic twins. Behavioral genetic model fitting indicated that a model including genetic effects as well as nonshared environmental influences (including measurement error), but not common environmental influences, fits the data best. The amount of variance attributable to nonadditive genetic influences (heritability) was estimated at 14.6%. The present study provides the first indication that genetic influences may play a role in shaping sexual interest toward children and adolescents among adult men. Compared with the variance attributable to nonshared environmental effects (plus measurement error), the contribution of any genetic factors seems comparatively weak. Future research should address the possible interplay of genetic with environmental risk factors, such as own sexual victimization in childhood. © 2013 International Society for Sexual Medicine.

The interplay between the effectiveness of the grass-endophyte mutualism and the genetic variability of the host plant

PubMed Central

Gundel, Pedro E; Omacini, Marina; Sadras, Victor O; Ghersa, Claudio M

2010-01-01

Neotyphodium endophytic fungi, the asexual state of Epichloë species, protect cool-season grasses against stresses. The outcomes of Neotyphodium-grass symbioses are agronomically relevant as they may affect the productivity of pastures. It has been suggested that the mutualism is characteristic of agronomic grasses and that differential rates of gene flow between both partners’ populations are expected to disrupt the specificity of the association and, thus, the mutualism in wild grasses. We propose that compatibility is necessary but not sufficient to explain the outcomes of Neotyphodium-grass symbiosis, and advance a model that links genetic compatibility, mutualism effectiveness, and endophyte transmission efficiency. For endophytes that reproduce clonally and depend on allogamous hosts for reproduction and dissemination, we propose that this symbiosis works as an integrated entity where gene flow promotes its fitness and evolution. Compatibility between the host plant and the fungal endophyte would be high in genetically close parents; however, mutualism effectiveness and transmission efficiency would be low in fitness depressed host plants. Increasing the genetic distance of mating parents would increase mutualism effectiveness and transmission efficiency. This tendency would be broken when the genetic distance between parents is high (out-breeding depression). Our model allows for testable hypotheses that would contribute to understand the coevolutionary origin and future of the endophyte-grass mutualism. PMID:25567945

Convergent functional genomics of psychiatric disorders.

PubMed

Niculescu, Alexander B

2013-10-01

Genetic and gene expression studies, in humans and animal models of psychiatric and other medical disorders, are becoming increasingly integrated. Particularly for genomics, the convergence and integration of data across species, experimental modalities and technical platforms is providing a fit-to-disease way of extracting reproducible and biologically important signal, in contrast to the fit-to-cohort effect and limited reproducibility of human genetic analyses alone. With the advent of whole-genome sequencing and the realization that a major portion of the non-coding genome may contain regulatory variants, Convergent Functional Genomics (CFG) approaches are going to be essential to identify disease-relevant signal from the tremendous polymorphic variation present in the general population. Such work in psychiatry can provide an example of how to address other genetically complex disorders, and in turn will benefit by incorporating concepts from other areas, such as cancer, cardiovascular diseases, and diabetes. © 2013 Wiley Periodicals, Inc.

Genetic architecture of differences between populations of cowpea weevil (Callosobruchus maculatus) evolved in the same environment.

PubMed

Bieri, Jonas; Kawecki, Tadeusz J

2003-02-01

We investigated the genetic architecture underlying differentiation in fitness-related traits between two pairs of populations of the seed beetle Callosobruchus maculatus (Coleoptera: Bruchidae). These populations had geographically distant (> 2000 km) origins but evolved in a uniform laboratory environment for 120 generations. For each pair of populations (Nigeria x Yemen and Cameroon x Uganda) we estimated the means of five fitness-related characters and a measure of fitness (net reproductive rate R0) in each of the parental populations and 12 types of hybrids (two F1 and two F2 lines and eight backcrosses). Models containing up to nine composite genetic parameters were fitted to the means of the 14 lines. The patterns of line means for all traits in the Nigeria x Yemen cross and for four traits (larval survival, developmental rate, female body weight, and fecundity) in the Cameroon x Uganda cross were best explained by models including additive, dominance, and maternal effects, but excluding epistasis. We did not find any evidence for outbreeding depression for any trait. An epistatic component of divergence was detected for egg hatching success and R0 in the Cameroon x Uganda cross, but its sign was opposite to that expected under outbreeding depression, that is, additive x additive epistasis had a positive effect on the performance of F2 hybrids. All traits except fecundity showed a pattern of heterosis. A large difference of egg-hatching success between the two reciprocal F1 lines in that cross was best explained as fertilization incompatibility between Cameroon females and sperm carrying Uganda genes. The results suggest that these populations have not converged to the same life-history phenotype and genetic architecture, despite 120 generations of uniform natural selection. However, the absence of outbreeding depression implies that they did not evolve toward different adaptive peaks.

Universality Classes of Interaction Structures for NK Fitness Landscapes

NASA Astrophysics Data System (ADS)

Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim

2018-07-01

Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.

Universality Classes of Interaction Structures for NK Fitness Landscapes

NASA Astrophysics Data System (ADS)

Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim

2018-02-01

Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.

A Population Genetic Model for the Initial Spread of Partially Resistant Malaria Parasites under Anti-Malarial Combination Therapy and Weak Intrahost Competition

PubMed Central

Kim, Yuseob; Escalante, Ananias A.; Schneider, Kristan A.

2014-01-01

To develop public-health policies that extend the lifespan of affordable anti-malarial drugs as effective treatment options, it is necessary to understand the evolutionary processes leading to the origin and spread of mutations conferring drug resistance in malarial parasites. We built a population-genetic model for the emergence of resistance under combination drug therapy. Reproductive cycles of parasites are specified by their absolute fitness determined by clinical parameters, thus coupling the evolutionary-genetic with population-dynamic processes. Initial mutations confer only partial drug-resistance. Therefore, mutant parasites rarely survive combination therapy and within-host competition is very weak among parasites. The model focuses on the early phase of such unsuccessful recurrent mutations. This ends in the rare event of mutants enriching in an infected individual from which the successful spread of resistance over the entire population is initiated. By computer simulations, the waiting time until the establishment of resistant parasites is analysed. Resistance spreads quickly following the first appearance of a host infected predominantly by mutant parasites. This occurs either through a rare transmission of a resistant parasite to an uninfected host or through a rare failure of drugs in removing “transient” mutant alleles. The emergence of resistance is delayed with lower mutation rate, earlier treatment, higher metabolic cost of resistance, longer duration of high drug dose, and higher drug efficacy causing a stronger reduction in the sensitive and resistant parasites’ fitnesses. Overall, contrary to other studies’ proposition, the current model based on absolute fitness suggests that aggressive drug treatment delays the emergence of drug resistance. PMID:25007207

Genetic and environmental influences on last-year major depression in adulthood: a highly heritable stable liability but strong environmental effects on 1-year prevalence.

PubMed

Kendler, K S; Gardner, C O

2017-07-01

This study seeks to clarify the contribution of temporally stable and occasion-specific genetic and environmental influences on risk for major depression (MD). Our sample was 2153 members of female-female twin pairs from the Virginia Twin Registry. We examined four personal interview waves conducted over an 8-year period with MD in the last year defined by DSM-IV criteria. We fitted a structural equation model to the data using classic Mx. The model included genetic and environmental risk factors for a latent, stable vulnerability to MD and for episodes in each of the four waves. The best-fit model was simple and included genetic and unique environmental influences on the latent liability to MD and unique wave-specific environmental effects. The path from latent liability to MD in the last year was constant over time, moderate in magnitude (+0.65) and weaker than the impact of occasion-specific environmental effects (+0.76). Heritability of the latent stable liability to MD was much higher (78%) than that estimated for last-year MD (32%). Of the total unique environmental influences on MD, 13% reflected enduring consequences of earlier environmental insults, 17% diagnostic error and 70% wave-specific short-lived environmental stressors. Both genetic influences on MD and MD heritability are stable over middle adulthood. However, the largest influence on last-year MD is short-lived environmental effects. As predicted by genetic theory, the heritability of MD is increased substantially by measurement at multiple time points largely through the reduction of the effects of measurement error and short-term environmental risk factors.

Common genetic factors among sexual orientation, gender nonconformity, and number of sex partners in female twins: implications for the evolution of homosexuality.

PubMed

Burri, Andrea; Spector, Tim; Rahman, Qazi

2015-04-01

Homosexuality is a stable population-level trait in humans that lowers direct fitness and yet is substantially heritable, resulting in a so-called Darwinian "paradox." Evolutionary models have proposed that polymorphic genes influencing homosexuality confer a reproductive benefit to heterosexual carriers, thus offsetting the fitness costs associated with persistent homosexuality. This benefit may consist of a "sex typicality" intermediate phenotype. However, there are few empirical tests of this hypothesis using genetically informative data in humans. This study aimed to test the hypothesis that common genetic factors can explain the association between measures of sex typicality, mating success, and homosexuality in a Western (British) sample of female twins. Here, we used data from 996 female twins (498 twin pairs) comprising 242 full dizygotic pairs and 256 full monozygotic pairs (mean age 56.8) and 1,555 individuals whose co-twin did not participate. Measures of sexual orientation, sex typicality (recalled childhood gender nonconformity), and mating success (number of lifetime sexual partners) were completed. Variables were subject to multivariate variance component analysis. We found that masculine women are more likely to be nonheterosexual, report more sexual partners, and, when heterosexual, also report more sexual partners. Multivariate twin modeling showed that common genetic factors explained the relationship between sexual orientation, sex typicality, and mating success through a shared latent factor. Our findings suggest that genetic factors responsible for nonheterosexuality are shared with genetic factors responsible for the number of lifetime sexual partners via a latent sex typicality phenotype in human females. These results may have implications for evolutionary models of homosexuality but are limited by potential mediating variables (such as personality traits) and measurement issues. © 2015 International Society for Sexual Medicine.

Model of head-neck joint fast movements in the frontal plane.

PubMed

Pedrocchi, A; Ferrigno, G

2004-06-01

The objective of this work is to develop a model representing the physiological systems driving fast head movements in frontal plane. All the contributions occurring mechanically in the head movement are considered: damping, stiffness, physiological limit of range of motion, gravitational field, and muscular torques due to voluntary activation as well as to stretch reflex depending on fusal afferences. Model parameters are partly derived from the literature, when possible, whereas undetermined block parameters are determined by optimising the model output, fitting to real kinematics data acquired by a motion capture system in specific experimental set-ups. The optimisation for parameter identification is performed by genetic algorithms. Results show that the model represents very well fast head movements in the whole range of inclination in the frontal plane. Such a model could be proposed as a tool for transforming kinematics data on head movements in 'neural equivalent data', especially for assessing head control disease and properly planning the rehabilitation process. In addition, the use of genetic algorithms seems to fit well the problem of parameter identification, allowing for the use of a very simple experimental set-up and granting model robustness.

The cost of copy number in a selfish genetic element: the 2-μm plasmid of Saccharomyces cerevisiae.

PubMed

Harrison, Ellie; Koufopanou, V; Burt, A; MacLean, R C

2012-11-01

Many autonomously replicating genetic elements exist as multiple copies within the cell. The copy number of these elements is often assumed to have important fitness consequences for both element and host, yet the forces shaping its evolution are not well understood. The 2 μm is a multicopy plasmid of Saccharomyces yeasts, encoding just four genes that are solely involved in plasmid replication. One simple model for the fitness relationship between yeasts and 2 μm is that plasmid copy number evolves as a trade-off between selection for increased vertical transmission, favouring high copy number, and selection for decreased virulence, favouring low copy number. To test this model, we experimentally manipulated the copy number of the plasmid and directly measured the fitness cost, in terms of growth rate reduction, associated with high plasmid copy number. We find that the fitness burden imposed by the 2 μm increases with plasmid copy number, such that each copy imposes a fitness burden of 0.17% (± 0.008%), greatly exceeding the cost expected for it to be stably maintained in yeast populations. Our results demonstrate the crucial importance of copy number in the evolution of yeast per 2 μm associations and pave the way for future studies examining how selection can shape the cost of multicopy elements. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

Cultural transmission and the evolution of human behaviour: a general approach based on the Price equation.

PubMed

El Mouden, C; André, J-B; Morin, O; Nettle, D

2014-02-01

Transmitted culture can be viewed as an inheritance system somewhat independent of genes that is subject to processes of descent with modification in its own right. Although many authors have conceptualized cultural change as a Darwinian process, there is no generally agreed formal framework for defining key concepts such as natural selection, fitness, relatedness and altruism for the cultural case. Here, we present and explore such a framework using the Price equation. Assuming an isolated, independently measurable culturally transmitted trait, we show that cultural natural selection maximizes cultural fitness, a distinct quantity from genetic fitness, and also that cultural relatedness and cultural altruism are not reducible to or necessarily related to their genetic counterparts. We show that antagonistic coevolution will occur between genes and culture whenever cultural fitness is not perfectly aligned with genetic fitness, as genetic selection will shape psychological mechanisms to avoid susceptibility to cultural traits that bear a genetic fitness cost. We discuss the difficulties with conceptualizing cultural change using the framework of evolutionary theory, the degree to which cultural evolution is autonomous from genetic evolution, and the extent to which cultural change should be seen as a Darwinian process. We argue that the nonselection components of evolutionary change are much more important for culture than for genes, and that this and other important differences from the genetic case mean that different approaches and emphases are needed for cultural than genetic processes. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Estimation of fitness from energetics and life-history data: An example using mussels.

PubMed

Sebens, Kenneth P; Sarà, Gianluca; Carrington, Emily

2018-06-01

Changing environments have the potential to alter the fitness of organisms through effects on components of fitness such as energy acquisition, metabolic cost, growth rate, survivorship, and reproductive output. Organisms, on the other hand, can alter aspects of their physiology and life histories through phenotypic plasticity as well as through genetic change in populations (selection). Researchers examining the effects of environmental variables frequently concentrate on individual components of fitness, although methods exist to combine these into a population level estimate of average fitness, as the per capita rate of population growth for a set of identical individuals with a particular set of traits. Recent advances in energetic modeling have provided excellent data on energy intake and costs leading to growth, reproduction, and other life-history parameters; these in turn have consequences for survivorship at all life-history stages, and thus for fitness. Components of fitness alone (performance measures) are useful in determining organism response to changing conditions, but are often not good predictors of fitness; they can differ in both form and magnitude, as demonstrated in our model. Here, we combine an energetics model for growth and allocation with a matrix model that calculates population growth rate for a group of individuals with a particular set of traits. We use intertidal mussels as an example, because data exist for some of the important energetic and life-history parameters, and because there is a hypothesized energetic trade-off between byssus production (affecting survivorship), and energy used for growth and reproduction. The model shows exactly how strong this trade-off is in terms of overall fitness, and it illustrates conditions where fitness components are good predictors of actual fitness, and cases where they are not. In addition, the model is used to examine the effects of environmental change on this trade-off and on both fitness and on individual fitness components.

Genetic influences on the difference in variability of height, weight and body mass index between Caucasian and East Asian adolescent twins.

PubMed

Hur, Y-M; Kaprio, J; Iacono, W G; Boomsma, D I; McGue, M; Silventoinen, K; Martin, N G; Luciano, M; Visscher, P M; Rose, R J; He, M; Ando, J; Ooki, S; Nonaka, K; Lin, C C H; Lajunen, H R; Cornes, B K; Bartels, M; van Beijsterveldt, C E M; Cherny, S S; Mitchell, K

2008-10-01

Twin studies are useful for investigating the causes of trait variation between as well as within a population. The goals of the present study were two-fold: First, we aimed to compare the total phenotypic, genetic and environmental variances of height, weight and BMI between Caucasians and East Asians using twins. Secondly, we intended to estimate the extent to which genetic and environmental factors contribute to differences in variability of height, weight and BMI between Caucasians and East Asians. Height and weight data from 3735 Caucasian and 1584 East Asian twin pairs (age: 13-15 years) from Australia, China, Finland, Japan, the Netherlands, South Korea, Taiwan and the United States were used for analyses. Maximum likelihood twin correlations and variance components model-fitting analyses were conducted to fulfill the goals of the present study. The absolute genetic variances for height, weight and BMI were consistently greater in Caucasians than in East Asians with corresponding differences in total variances for all three body measures. In all 80 to 100% of the differences in total variances of height, weight and BMI between the two population groups were associated with genetic differences. Height, weight and BMI were more variable in Caucasian than in East Asian adolescents. Genetic variances for these three body measures were also larger in Caucasians than in East Asians. Variance components model-fitting analyses indicated that genetic factors contributed to the difference in variability of height, weight and BMI between the two population groups. Association studies for these body measures should take account of our findings of differences in genetic variances between the two population groups.

Genetic influences on the difference in variability of height, weight and body mass index between Caucasian and East Asian adolescent twins

PubMed Central

Hur, Y-M; Kaprio, J; Iacono, WG; Boomsma, DI; McGue, M; Silventoinen, K; Martin, NG; Luciano, M; Visscher, PM; Rose, RJ; He, M; Ando, J; Ooki, S; Nonaka, K; Lin, CCH; Lajunen, HR; Cornes, BK; Bartels, M; van Beijsterveldt, CEM; Cherny, SS; Mitchell, K

2008-01-01

Objective Twin studies are useful for investigating the causes of trait variation between as well as within a population. The goals of the present study were two-fold: First, we aimed to compare the total phenotypic, genetic and environmental variances of height, weight and BMI between Caucasians and East Asians using twins. Secondly, we intended to estimate the extent to which genetic and environmental factors contribute to differences in variability of height, weight and BMI between Caucasians and East Asians. Design Height and weight data from 3735 Caucasian and 1584 East Asian twin pairs (age: 13–15 years) from Australia, China, Finland, Japan, the Netherlands, South Korea, Taiwan and the United States were used for analyses. Maximum likelihood twin correlations and variance components model-fitting analyses were conducted to fulfill the goals of the present study. Results The absolute genetic variances for height, weight and BMI were consistently greater in Caucasians than in East Asians with corresponding differences in total variances for all three body measures. In all 80 to 100% of the differences in total variances of height, weight and BMI between the two population groups were associated with genetic differences. Conclusion Height, weight and BMI were more variable in Caucasian than in East Asian adolescents. Genetic variances for these three body measures were also larger in Caucasians than in East Asians. Variance components model-fitting analyses indicated that genetic factors contributed to the difference in variability of height, weight and BMI between the two population groups. Association studies for these body measures should take account of our findings of differences in genetic variances between the two population groups. PMID:18779828

Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle.

PubMed

Baldi, F; Alencar, M M; Albuquerque, L G

2010-12-01

The objective of this work was to estimate covariance functions using random regression models on B-splines functions of animal age, for weights from birth to adult age in Canchim cattle. Data comprised 49,011 records on 2435 females. The model of analysis included fixed effects of contemporary groups, age of dam as quadratic covariable and the population mean trend taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were modelled through a step function with four classes. The direct and maternal additive genetic effects, and animal and maternal permanent environmental effects were included as random effects in the model. A total of seventeen analyses, considering linear, quadratic and cubic B-splines functions and up to seven knots, were carried out. B-spline functions of the same order were considered for all random effects. Random regression models on B-splines functions were compared to a random regression model on Legendre polynomials and with a multitrait model. Results from different models of analyses were compared using the REML form of the Akaike Information criterion and Schwarz' Bayesian Information criterion. In addition, the variance components and genetic parameters estimated for each random regression model were also used as criteria to choose the most adequate model to describe the covariance structure of the data. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most adequate to describe the covariance structure of the data. Random regression models using B-spline functions as base functions fitted the data better than Legendre polynomials, especially at mature ages, but higher number of parameters need to be estimated with B-splines functions. © 2010 Blackwell Verlag GmbH.

Associations of Fitness, Physical Activity, Strength, and Genetic Risk With Cardiovascular Disease: Longitudinal Analyses in the UK Biobank Study.

PubMed

Tikkanen, Emmi; Gustafsson, Stefan; Ingelsson, Erik

2018-06-12

Observational studies have shown inverse associations among fitness, physical activity, and cardiovascular disease. However, little is known about these associations in individuals with elevated genetic susceptibility for these diseases. We estimated associations of grip strength, objective and subjective physical activity, and cardiorespiratory fitness with cardiovascular events and all-cause death in a large cohort of 502 635 individuals from the UK Biobank (median follow-up, 6.1 years; interquartile range, 5.4-6.8 years). Then we further examined these associations in individuals with different genetic burden by stratifying individuals based on their genetic risk scores for coronary heart disease and atrial fibrillation. We compared disease risk among individuals in different tertiles of fitness, physical activity, and genetic risk using lowest tertiles as reference. Grip strength, physical activity, and cardiorespiratory fitness showed inverse associations with incident cardiovascular events (coronary heart disease: hazard ratio [HR], 0.79; 95% confidence interval [CI], 0.77-0.81; HR, 0.95; 95% CI, 0.93-0.97; and HR, 0.68; 95% CI, 0.63-0.74, per SD change, respectively; atrial fibrillation: HR, 0.75; 95% CI, 0.73-0.76; HR, 0.93; 95% CI, 0.91-0.95; and HR, 0.60; 95% CI, 0.56-0.65, per SD change, respectively). Higher grip strength and cardiorespiratory fitness were associated with lower risk of incident coronary heart disease and atrial fibrillation in each genetic risk score group ( P trend <0.001 in each genetic risk category). In particular, high levels of cardiorespiratory fitness were associated with 49% lower risk for coronary heart disease (HR, 0.51; 95% CI, 0.38-0.69) and 60% lower risk for atrial fibrillation (HR, 0.40; 95%, CI 0.30-0.55) among individuals at high genetic risk for these diseases. Fitness and physical activity demonstrated inverse associations with incident cardiovascular disease in the general population, as well as in individuals with elevated genetic risk for these diseases. © 2018 American Heart Association, Inc.

Repair rather than segregation of damage is the optimal unicellular aging strategy.

PubMed

Clegg, Robert J; Dyson, Rosemary J; Kreft, Jan-Ulrich

2014-08-16

How aging, being unfavourable for the individual, can evolve is one of the fundamental problems of biology. Evidence for aging in unicellular organisms is far from conclusive. Some studies found aging even in symmetrically dividing unicellular species; others did not find aging in the same, or in different, unicellular species, or only under stress. Mathematical models suggested that segregation of non-genetic damage, as an aging strategy, would increase fitness. However, these models failed to consider repair as an alternative strategy or did not properly account for the benefits of repair. We used a new and improved individual-based model to examine rigorously the effect of a range of aging strategies on fitness in various environments. Repair of damage emerges as the best strategy despite its fitness costs, since it immediately increases growth rate. There is an optimal investment in repair that outperforms damage segregation in well-mixed, lasting and benign environments over a wide range of parameter values. Damage segregation becomes beneficial, and only in combination with repair, when three factors are combined: (i) the rate of damage accumulation is high, (ii) damage is toxic and (iii) efficiency of repair is low. In contrast to previous models, our model predicts that unicellular organisms should have active mechanisms to repair damage rather than age by segregating damage. Indeed, as predicted, all organisms have evolved active mechanisms of repair whilst aging in unicellular organisms is absent or minimal under benign conditions, apart from microorganisms with a different ecology, inhabiting short-lived environments strongly favouring early reproduction rather than longevity. Aging confers no fitness advantage for unicellular organisms in lasting environments under benign conditions, since repair of non-genetic damage is better than damage segregation.

Longitudinal stability of cognitive ability from infancy to early childhood: genetic and environmental etiologies.

PubMed

LaBuda, M C; DeFries, J C; Plomin, R; Fulker, D W

1986-10-01

A path model of genetic and shared family environmental transmission was fitted to general cognitive ability data from 1-, 2-, 3-, and 4-year-old adopted and nonadopted children and their parents in order to assess the etiology of longitudinal stability from infancy to early childhood. Stability across years is moderate and is due mainly to influences not predicted by parental IQ. Results of the present study, in conjunction with those of previous twin studies, suggest substantial genetic stability from infancy and early childhood to adulthood.

Genetic parameters for lactose and its correlation with other milk production traits and fitness traits in pasture-based production systems.

PubMed

Haile-Mariam, M; Pryce, J E

2017-05-01

Lactose is a major component of milk (typically around 5% of composition) that is not usually directly considered in national genetic improvement programs of dairy cattle. Daily test-day lactose yields and percentage data from pasture-based seasonal calving herds in Australia were analyzed to assess if lactose content can be used for predicting fitness traits and if an additional benefit is achieved by including lactose yield in selecting for milk yield traits. Data on lactose percentage collected from 2007 to 2014, from about 600 herds, were used to estimated genetic parameters for lactose percentage and lactose yield and correlations with other milk yield traits, somatic cell count (SCC), calving interval (CIV), and survival. Daily test-day data were analyzed using bivariate random regression models. In addition, multi-trait models were also performed mainly to assess the value of lactose to predict fitness traits. The heritability of lactose percentage (0.25 to 0.37) was higher than lactose yield (0.11 to 0.20) in the first parity. Genetically, the correlation of lactose percentage with protein percentage varied from 0.3 at the beginning of lactation to -0.24 at the end of the lactation in the first parity. Similar patterns in genetic correlations were also observed in the second and third parity. At all levels (i.e., genetic, permanent environmental, and residual), the correlation between milk yield and lactose yield was close to 1. The genetic and permanent environmental correlations between lactose percentage and SCC were stronger in the second and third parity and toward the end of the lactation (-0.35 to -0.50) when SCC levels are at their maximum. The genetic correlation between lactose percentage in the first 120 d and CIV (-0.23) was similar to correlation of CIV with protein percentage (-0.28), another component trait with the potential to predict fertility. Furthermore, the correlations of estimated breeding values of lactose percentage and estimated breeding values of traits such as survival, fertility, SCC, and angularity suggest that the value of lactose percentage as a predictor of fitness traits is weak. The results also suggest that including lactose yield as a trait into the breeding objective is of limited value due to the high positive genetic correlation between lactose yield and protein yield, the trait highly emphasized in Australia. However, recording lactose percentage as part of the routine milk recording system will enable the Australian dairy industry to respond quickly to any future changes and market signals. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A predictive relationship between population and genetic sex ratios in clonal species

NASA Astrophysics Data System (ADS)

McLetchie, D. Nicholas; García-Ramos, Gisela

2017-04-01

Sexual reproduction depends on mate availability that is reflected by local sex ratios. In species where both sexes can clonally expand, the population sex ratio describes the proportion of males, including clonally derived individuals (ramets) in addition to sexually produced individuals (genets). In contrast to population sex ratio that accounts for the overall abundance of the sexes, the genetic sex ratio reflects the relative abundance of genetically unique mates, which is critical in predicting effective population size but is difficult to estimate in the field. While an intuitive positive relationship between population (ramet) sex ratio and genetic (genet) sex ratio is expected, an explicit relationship is unknown. In this study, we determined a mathematical expression in the form of a hyperbola that encompasses a linear to a nonlinear positive relationship between ramet and genet sex ratios. As expected when both sexes clonally have equal number of ramets per genet both sex ratios are identical, and thus ramet sex ratio becomes a linear function of genet sex ratio. Conversely, if sex differences in ramet number occur, this mathematical relationship becomes nonlinear and a discrepancy between the sex ratios amplifies from extreme sex ratios values towards intermediate values. We evaluated our predictions with empirical data that simultaneously quantified ramet and genet sex ratios in populations of several species. We found that the data support the predicted positive nonlinear relationship, indicating sex differences in ramet number across populations. However, some data may also fit the null model, which suggests that sex differences in ramet number were not extensive, or the number of populations was too small to capture the curvature of the nonlinear relationship. Data with lack of fit suggest the presence of factors capable of weakening the positive relationship between the sex ratios. Advantages of this model include predicting genet sex ratio using population sex ratios given known sex differences in ramet number, and detecting sex differences in ramet number among populations.

Inferring Causalities in Landscape Genetics: An Extension of Wright's Causal Modeling to Distance Matrices.

PubMed

Fourtune, Lisa; Prunier, Jérôme G; Paz-Vinas, Ivan; Loot, Géraldine; Veyssière, Charlotte; Blanchet, Simon

2018-04-01

Identifying landscape features that affect functional connectivity among populations is a major challenge in fundamental and applied sciences. Landscape genetics combines landscape and genetic data to address this issue, with the main objective of disentangling direct and indirect relationships among an intricate set of variables. Causal modeling has strong potential to address the complex nature of landscape genetic data sets. However, this statistical approach was not initially developed to address the pairwise distance matrices commonly used in landscape genetics. Here, we aimed to extend the applicability of two causal modeling methods-that is, maximum-likelihood path analysis and the directional separation test-by developing statistical approaches aimed at handling distance matrices and improving functional connectivity inference. Using simulations, we showed that these approaches greatly improved the robustness of the absolute (using a frequentist approach) and relative (using an information-theoretic approach) fits of the tested models. We used an empirical data set combining genetic information on a freshwater fish species (Gobio occitaniae) and detailed landscape descriptors to demonstrate the usefulness of causal modeling to identify functional connectivity in wild populations. Specifically, we demonstrated how direct and indirect relationships involving altitude, temperature, and oxygen concentration influenced within- and between-population genetic diversity of G. occitaniae.

Mobile robot dynamic path planning based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

Genomic regions with a history of divergent selection affect fitness of hybrids between two butterfly species.

PubMed

Gompert, Zachariah; Lucas, Lauren K; Nice, Chris C; Fordyce, James A; Forister, Matthew L; Buerkle, C Alex

2012-07-01

Speciation is the process by which reproductively isolated lineages arise, and is one of the fundamental means by which the diversity of life increases. Whereas numerous studies have documented an association between ecological divergence and reproductive isolation, relatively little is known about the role of natural selection in genome divergence during the process of speciation. Here, we use genome-wide DNA sequences and Bayesian models to test the hypothesis that loci under divergent selection between two butterfly species (Lycaeides idas and L. melissa) also affect fitness in an admixed population. Locus-specific measures of genetic differentiation between L. idas and L. melissa and genomic introgression in hybrids varied across the genome. The most differentiated genetic regions were characterized by elevated L. idas ancestry in the admixed population, which occurs in L. idas-like habitat, consistent with the hypothesis that local adaptation contributes to speciation. Moreover, locus-specific measures of genetic differentiation (a metric of divergent selection) were positively associated with extreme genomic introgression (a metric of hybrid fitness). Interestingly, concordance of differentiation and introgression was only partial. We discuss multiple, complementary explanations for this partial concordance. © 2012 The Author(s).

In silico modelling of directed evolution: Implications for experimental design and stepwise evolution.

PubMed

Wedge, David C; Rowe, William; Kell, Douglas B; Knowles, Joshua

2009-03-07

We model the process of directed evolution (DE) in silico using genetic algorithms. Making use of the NK fitness landscape model, we analyse the effects of mutation rate, crossover and selection pressure on the performance of DE. A range of values of K, the epistatic interaction of the landscape, are considered, and high- and low-throughput modes of evolution are compared. Our findings suggest that for runs of or around ten generations' duration-as is typical in DE-there is little difference between the way in which DE needs to be configured in the high- and low-throughput regimes, nor across different degrees of landscape epistasis. In all cases, a high selection pressure (but not an extreme one) combined with a moderately high mutation rate works best, while crossover provides some benefit but only on the less rugged landscapes. These genetic algorithms were also compared with a "model-based approach" from the literature, which uses sequential fixing of the problem parameters based on fitting a linear model. Overall, we find that purely evolutionary techniques fare better than do model-based approaches across all but the smoothest landscapes.

Modeling the Volcanic Source at Long Valley, CA, Using a Genetic Algorithm Technique

NASA Technical Reports Server (NTRS)

Tiampo, Kristy F.

1999-01-01

In this project, we attempted to model the deformation pattern due to the magmatic source at Long Valley caldera using a real-value coded genetic algorithm (GA) inversion similar to that found in Michalewicz, 1992. The project has been both successful and rewarding. The genetic algorithm, coded in the C programming language, performs stable inversions over repeated trials, with varying initial and boundary conditions. The original model used a GA in which the geophysical information was coded into the fitness function through the computation of surface displacements for a Mogi point source in an elastic half-space. The program was designed to invert for a spherical magmatic source - its depth, horizontal location and volume - using the known surface deformations. It also included the capability of inverting for multiple sources.

A genomic perspective on the generation and maintenance of genetic diversity in herbivorous insects

PubMed Central

Gloss, Andrew D.; Groen, Simon C.; Whiteman, Noah K.

2017-01-01

Understanding the processes that generate and maintain genetic variation within populations is a central goal in evolutionary biology. Theory predicts that some of this variation is maintained as a consequence of adapting to variable habitats. Studies in herbivorous insects have played a key role in confirming this prediction. Here, we highlight theoretical and conceptual models for the maintenance of genetic diversity in herbivorous insects, empirical genomic studies testing these models, and pressing questions within the realm of evolutionary and functional genomic studies. To address key gaps, we propose an integrative approach combining population genomic scans for adaptation, genome-wide characterization of targets of selection through experimental manipulations, mapping the genetic architecture of traits influencing fitness, and functional studies. We also stress the importance of studying the maintenance of genetic variation across biological scales—from variation within populations to divergence among populations—to form a comprehensive view of adaptation in herbivorous insects. PMID:28736510

Linear reaction norm models for genetic merit prediction of Angus cattle under genotype by environment interaction.

PubMed

Cardoso, F F; Tempelman, R J

2012-07-01

The objectives of this work were to assess alternative linear reaction norm (RN) models for genetic evaluation of Angus cattle in Brazil. That is, we investigated the interaction between genotypes and continuous descriptors of the environmental variation to examine evidence of genotype by environment interaction (G×E) in post-weaning BW gain (PWG) and to compare the environmental sensitivity of national and imported Angus sires. Data were collected by the Brazilian Angus Improvement Program from 1974 to 2005 and consisted of 63,098 records and a pedigree file with 95,896 animals. Six models were implemented using Bayesian inference and compared using the Deviance Information Criterion (DIC). The simplest model was M(1), a traditional animal model, which showed the largest DIC and hence the poorest fit when compared with the 4 alternative RN specifications accounting for G×E. In M(2), a 2-step procedure was implemented using the contemporary group posterior means of M(1) as the environmental gradient, ranging from -92.6 to +265.5 kg. Moreover, the benefits of jointly estimating all parameters in a 1-step approach were demonstrated by M(3). Additionally, we extended M(3) to allow for residual heteroskedasticity using an exponential function (M(4)) and the best fitting (smallest DIC) environmental classification model (M(5)) specification. Finally, M(6) added just heteroskedastic residual variance to M(1). Heritabilities were less at harsh environments and increased with the improvement of production conditions for all RN models. Rank correlations among genetic merit predictions obtained by M(1) and by the best fitting RN models M(3) (homoskedastic) and M(5) (heteroskedastic) at different environmental levels ranged from 0.79 and 0.81, suggesting biological importance of G×E in Brazilian Angus PWG. These results suggest that selection progress could be optimized by adopting environment-specific genetic merit predictions. The PWG environmental sensitivity of imported North American origin bulls (0.046 ± 0.009) was significantly larger (P < 0.05) than that of local sires (0.012 ± 0.013). Moreover, PWG of progeny of imported sires exceeded that of native sires in medium and superior production levels. On the other hand, Angus cattle locally selected in Brazil tended to be more robust to environmental changes and hence be more suitable when production environments for potential progeny is uncertain.

Measuring aging rates of mice subjected to caloric restriction and genetic disruption of growth hormone signaling

PubMed Central

Koopman, Jacob J.E.; van Heemst, Diana; van Bodegom, David; Bonkowski, Michael S.; Sun, Liou Y.; Bartke, Andrzej

2016-01-01

Caloric restriction and genetic disruption of growth hormone signaling have been shown to counteract aging in mice. The effects of these interventions on aging are examined through age-dependent survival or through the increase in age-dependent mortality rates on a logarithmic scale fitted to the Gompertz model. However, these methods have limitations that impede a fully comprehensive disclosure of these effects. Here we examine the effects of these interventions on murine aging through the increase in age-dependent mortality rates on a linear scale without fitting them to a model like the Gompertz model. Whereas these interventions negligibly and non-consistently affected the aging rates when examined through the age-dependent mortality rates on a logarithmic scale, they caused the aging rates to increase at higher ages and to higher levels when examined through the age-dependent mortality rates on a linear scale. These results add to the debate whether these interventions postpone or slow aging and to the understanding of the mechanisms by which they affect aging. Since different methods yield different results, it is worthwhile to compare their results in future research to obtain further insights into the effects of dietary, genetic, and other interventions on the aging of mice and other species. PMID:26959761

Optimised analytical models of the dielectric properties of biological tissue.

PubMed

Salahuddin, Saqib; Porter, Emily; Krewer, Finn; O' Halloran, Martin

2017-05-01

The interaction of electromagnetic fields with the human body is quantified by the dielectric properties of biological tissues. These properties are incorporated into complex numerical simulations using parametric models such as Debye and Cole-Cole, for the computational investigation of electromagnetic wave propagation within the body. These parameters can be acquired through a variety of optimisation algorithms to achieve an accurate fit to measured data sets. A number of different optimisation techniques have been proposed, but these are often limited by the requirement for initial value estimations or by the large overall error (often up to several percentage points). In this work, a novel two-stage genetic algorithm proposed by the authors is applied to optimise the multi-pole Debye parameters for 54 types of human tissues. The performance of the two-stage genetic algorithm has been examined through a comparison with five other existing algorithms. The experimental results demonstrate that the two-stage genetic algorithm produces an accurate fit to a range of experimental data and efficiently out-performs all other optimisation algorithms under consideration. Accurate values of the three-pole Debye models for 54 types of human tissues, over 500 MHz to 20 GHz, are also presented for reference. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Measuring aging rates of mice subjected to caloric restriction and genetic disruption of growth hormone signaling.

PubMed

Koopman, Jacob J E; van Heemst, Diana; van Bodegom, David; Bonkowski, Michael S; Sun, Liou Y; Bartke, Andrzej

2016-03-01

Caloric restriction and genetic disruption of growth hormone signaling have been shown to counteract aging in mice. The effects of these interventions on aging are examined through age-dependent survival or through the increase in age-dependent mortality rates on a logarithmic scale fitted to the Gompertz model. However, these methods have limitations that impede a fully comprehensive disclosure of these effects. Here we examine the effects of these interventions on murine aging through the increase in age-dependent mortality rates on a linear scale without fitting them to a model like the Gompertz model. Whereas these interventions negligibly and non-consistently affected the aging rates when examined through the age-dependent mortality rates on a logarithmic scale, they caused the aging rates to increase at higher ages and to higher levels when examined through the age-dependent mortality rates on a linear scale. These results add to the debate whether these interventions postpone or slow aging and to the understanding of the mechanisms by which they affect aging. Since different methods yield different results, it is worthwhile to compare their results in future research to obtain further insights into the effects of dietary, genetic, and other interventions on the aging of mice and other species.

Human genetic susceptibility and infection with Leishmania peruviana

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shaw, M.A.; Davis, C.R.; Collins, A.

1995-11-01

Racial differences, familial clustering, and murine studies are suggestive of host genetic control of Leishmania infections. Complex segregation analysis has been carried out by use of the programs POINTER and COMDS and data from a total population survey, comprising 636 nuclear families, from an L. perurviana endemic area. The data support genetic components controlling susceptibility to clinical leishmaniasis, influencing severity of disease and resistance to disease among healthy individuals. A multifactorial model is favored over a sporadic model. Two-locus models provided the best fit to the data, the optimal model being a recessive gene (frequency .57) plus a modifier locus.more » Individuals infected at an early age and with recurrent lesions are genetically more susceptible than those infected with a single episode of disease at a later age. Among people with no lesions, those with a positive skin-test response are genetically less susceptible than those with a negative response. The possibility of the involvement of more than one gene together with environmental effects has implications for the design of future linkage studies. 31 refs., 7 tabs.« less

Selfishness and altruism can coexist when help is subject to diminishing returns.

PubMed

Sibly, R M; Curnow, R N

2011-08-01

Altruism and selfishness are 30-50% heritable in man in both Western and non-Western populations. This genetically based variation in altruism and selfishness requires explanation. In non-human animals, altruism is generally directed towards relatives, and satisfies the condition known as Hamilton's rule. This nepotistic altruism evolves under natural selection only if the ratio of the benefit of receiving help to the cost of giving it exceeds a value that depends on the relatedness of the individuals involved. Standard analyses assume that the benefit provided by each individual is the same but it is plausible in some cases that as more individuals contribute, help is subject to diminishing returns. We analyse this situation using a single-locus two-allele model of selection in a diploid population with the altruistic allele dominant to the selfish allele. The analysis requires calculation of the relationship between the fitnesses of the genotypes and the frequencies of the genes. The fitnesses vary not only with the genotype of the individual but also with the distribution of phenotypes amongst the sibs of the individual and this depends on the genotypes of his parents. These calculations are not possible by direct fitness or ESS methods but are possible using population genetics. Our analysis shows that diminishing returns change the operation of natural selection and the outcome can now be a stable equilibrium between altruistic and selfish alleles rather than the elimination of one allele or the other. We thus provide a plausible genetic model of kin selection that leads to the stable coexistence in the same population of both altruistic and selfish individuals. This may explain reported genetic variation in altruism in man.

Application of artificial neural networks and genetic algorithms to modeling molecular electronic spectra in solution

NASA Astrophysics Data System (ADS)

Lilichenko, Mark; Kelley, Anne Myers

2001-04-01

A novel approach is presented for finding the vibrational frequencies, Franck-Condon factors, and vibronic linewidths that best reproduce typical, poorly resolved electronic absorption (or fluorescence) spectra of molecules in condensed phases. While calculation of the theoretical spectrum from the molecular parameters is straightforward within the harmonic oscillator approximation for the vibrations, "inversion" of an experimental spectrum to deduce these parameters is not. Standard nonlinear least-squares fitting methods such as Levenberg-Marquardt are highly susceptible to becoming trapped in local minima in the error function unless very good initial guesses for the molecular parameters are made. Here we employ a genetic algorithm to force a broad search through parameter space and couple it with the Levenberg-Marquardt method to speed convergence to each local minimum. In addition, a neural network trained on a large set of synthetic spectra is used to provide an initial guess for the fitting parameters and to narrow the range searched by the genetic algorithm. The combined algorithm provides excellent fits to a variety of single-mode absorption spectra with experimentally negligible errors in the parameters. It converges more rapidly than the genetic algorithm alone and more reliably than the Levenberg-Marquardt method alone, and is robust in the presence of spectral noise. Extensions to multimode systems, and/or to include other spectroscopic data such as resonance Raman intensities, are straightforward.

PyRhO: A Multiscale Optogenetics Simulation Platform

PubMed Central

Evans, Benjamin D.; Jarvis, Sarah; Schultz, Simon R.; Nikolic, Konstantin

2016-01-01

Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterize, understand and apply these opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins by automatically fitting a minimal set of experimental data to three-, four-, or six-state kinetic models, (ii) to simulate these models at the channel, neuron and network levels, and (iii) provide functional insights through model selection and virtual experiments in silico. The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences. PMID:27148037

PyRhO: A Multiscale Optogenetics Simulation Platform.

PubMed

Evans, Benjamin D; Jarvis, Sarah; Schultz, Simon R; Nikolic, Konstantin

2016-01-01

Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterize, understand and apply these opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins by automatically fitting a minimal set of experimental data to three-, four-, or six-state kinetic models, (ii) to simulate these models at the channel, neuron and network levels, and (iii) provide functional insights through model selection and virtual experiments in silico. The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences.

Model-based estimation of individual fitness

USGS Publications Warehouse

Link, W.A.; Cooch, E.G.; Cam, E.

2002-01-01

Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw and Caswell, 1996).

Model-based estimation of individual fitness

USGS Publications Warehouse

Link, W.A.; Cooch, E.G.; Cam, E.

2002-01-01

Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla ) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw & Caswell, 1996).

Genetic analysis of partial egg production records in Japanese quail using random regression models.

PubMed

Abou Khadiga, G; Mahmoud, B Y F; Farahat, G S; Emam, A M; El-Full, E A

2017-08-01

The main objectives of this study were to detect the most appropriate random regression model (RRM) to fit the data of monthly egg production in 2 lines (selected and control) of Japanese quail and to test the consistency of different criteria of model choice. Data from 1,200 female Japanese quails for the first 5 months of egg production from 4 consecutive generations of an egg line selected for egg production in the first month (EP1) was analyzed. Eight RRMs with different orders of Legendre polynomials were compared to determine the proper model for analysis. All criteria of model choice suggested that the adequate model included the second-order Legendre polynomials for fixed effects, and the third-order for additive genetic effects and permanent environmental effects. Predictive ability of the best model was the highest among all models (ρ = 0.987). According to the best model fitted to the data, estimates of heritability were relatively low to moderate (0.10 to 0.17) showed a descending pattern from the first to the fifth month of production. A similar pattern was observed for permanent environmental effects with greater estimates in the first (0.36) and second (0.23) months of production than heritability estimates. Genetic correlations between separate production periods were higher (0.18 to 0.93) than their phenotypic counterparts (0.15 to 0.87). The superiority of the selected line over the control was observed through significant (P < 0.05) linear contrast estimates. Significant (P < 0.05) estimates of covariate effect (age at sexual maturity) showed a decreased pattern with greater impact on egg production in earlier ages (first and second months) than later ones. A methodology based on random regression animal models can be recommended for genetic evaluation of egg production in Japanese quail. © 2017 Poultry Science Association Inc.

Reverse engineering the gap gene network of Drosophila melanogaster.

PubMed

Perkins, Theodore J; Jaeger, Johannes; Reinitz, John; Glass, Leon

2006-05-01

A fundamental problem in functional genomics is to determine the structure and dynamics of genetic networks based on expression data. We describe a new strategy for solving this problem and apply it to recently published data on early Drosophila melanogaster development. Our method is orders of magnitude faster than current fitting methods and allows us to fit different types of rules for expressing regulatory relationships. Specifically, we use our approach to fit models using a smooth nonlinear formalism for modeling gene regulation (gene circuits) as well as models using logical rules based on activation and repression thresholds for transcription factors. Our technique also allows us to infer regulatory relationships de novo or to test network structures suggested by the literature. We fit a series of models to test several outstanding questions about gap gene regulation, including regulation of and by hunchback and the role of autoactivation. Based on our modeling results and validation against the experimental literature, we propose a revised network structure for the gap gene system. Interestingly, some relationships in standard textbook models of gap gene regulation appear to be unnecessary for or even inconsistent with the details of gap gene expression during wild-type development.

Genetic Obesity Risk and Attenuation Effect of Physical Fitness in Mexican-Mestizo Population: a Case-Control Study.

PubMed

Costa-Urrutia, Paula; Abud, Carolina; Franco-Trecu, Valentina; Colistro, Valentina; Rodríguez-Arellano, Martha Eunice; Vázquez-Pérez, Joel; Granados, Julio; Seelaender, Marilia

2017-05-01

We analyzed commonly reported European and Asian obesity-related gene variants in a Mexican-Mestizo population through each single nucleotide polymorphism (SNP) and a genetic risk score (GRS) based on 23 selected SNPs. Study subjects were physically active Mexican-Mestizo adults (n  =  608) with body mass index (BMI) values from 18 to 55 kg/m 2 . For each SNP and for the GRS, logistic models were performed to test for simple SNP associations with BMI, fat mass percentage (FMP), waist circumference (WC), and the interaction with VO 2max and muscular endurance (ME). To further understand the SNP or GRS*physical fitness components, generalized linear models were performed. Obesity risk was significantly associated to 6 SNPs (ADRB2 rs1042713, APOB rs512535, PPARA rs1800206, TNFA rs361525, TRHR rs7832552 and rs16892496) after adjustment by gender, age, ancestry, VO 2max , and ME. ME attenuated the influence of APOB rs512535 and TNFA rs361525 on obesity risk in FMP. WC was significantly associated to GRS. Both ME and VO 2max attenuated GRS effect on WC. We report associations for 6 out of 23 SNPs and for the GRS, which confer obesity risk, a novel finding for Mexican-Mestizo physically active population. Also, the importance of including physical fitness components variables in obesity genetic risk studies is highlighted, with special regard to intervention purposes. © 2017 John Wiley & Sons Ltd/University College London.

Dominance Genetic Variance for Traits Under Directional Selection in Drosophila serrata

PubMed Central

Sztepanacz, Jacqueline L.; Blows, Mark W.

2015-01-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait–fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. PMID:25783700

Genetic architecture of learning and delayed recall: a twin study of episodic memory.

PubMed

Panizzon, Matthew S; Lyons, Michael J; Jacobson, Kristen C; Franz, Carol E; Grant, Michael D; Eisen, Seth A; Xian, Hong; Kremen, William S

2011-07-01

Although episodic memory is often conceptualized as consisting of multiple component processes, there is a lack of understanding as to whether these processes are influenced by the same or different genetic determinants. The aim of the present study was to utilize multivariate twin analyses to elucidate the degree to which learning and delayed recall, two critical measures of episodic memory performance, have common or different genetic and environmental influences. Participants from the Vietnam Era Twin Study of Aging (314 monozygotic twin pairs, 259 dizygotic twin pairs, and 47 unpaired twins) were assessed using the second edition of the California Verbal Learning Test. Mean age at the time of the evaluation was 55.4 years (SD = 2.5). Model fitting revealed the presence of a higher-order latent factor influencing learning, short- and long-delay free recall, with a heritability of .36. The best-fitting model also indicated specific genetic influences on learning, which accounted for 10% of the overall variance. Given that learning involves the acquisition and retrieval of information, whereas delayed recall involves only retrieval, we conclude that these specific effects are likely to reflect genes that are specific to acquisition processes. These results demonstrate that even in nonclinical populations, it is possible to differentiate component processes in episodic memory. These different genetic influences may have implications for gene association studies, as well as other genetic studies of cognitive aging and disorders of episodic memory such as Alzheimer's disease or mild cognitive impairment. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Frequency-Dependent Selection: The High Potential for Permanent Genetic Variation in the Diallelic, Pairwise Interaction Model

PubMed Central

Asmussen, M. A.; Basnayake, E.

1990-01-01

A detailed analytic and numerical study is made of the potential for permanent genetic variation in frequency-dependent models based on pairwise interactions among genotypes at a single diallelic locus. The full equilibrium structure and qualitative gene-frequency dynamics are derived analytically for a symmetric model, in which pairwise fitnesses are chiefly determined by the genetic similarity of the individuals involved. This is supplemented by an extensive numerical investigation of the general model, the symmetric model, and nine other special cases. Together the results show that there is a high potential for permanent genetic diversity in the pairwise interaction model, and provide insight into the extent to which various forms of genotypic interactions enhance or reduce this potential. Technically, although two stable polymorphic equilibria are possible, the increased likelihood of maintaining both alleles, and the poor performance of protected polymorphism conditions as a measure of this likelihood, are primarily due to a greater variety and frequency of equilibrium patterns with one stable polymorphic equilibrium, in conjunction with a disproportionately large domain of attraction for stable internal equilibria. PMID:2341034

Emerging prion disease drives host selection in a wildlife population

USGS Publications Warehouse

Robinson, Stacie J.; Samuel, Michael D.; Johnson, Chad J.; Adams, Marie; McKenzie, Debbie I.

2012-01-01

Infectious diseases are increasingly recognized as an important force driving population dynamics, conservation biology, and natural selection in wildlife populations. Infectious agents have been implicated in the decline of small or endangered populations and may act to constrain population size, distribution, growth rates, or migration patterns. Further, diseases may provide selective pressures that shape the genetic diversity of populations or species. Thus, understanding disease dynamics and selective pressures from pathogens is crucial to understanding population processes, managing wildlife diseases, and conserving biological diversity. There is ample evidence that variation in the prion protein gene (PRNP) impacts host susceptibility to prion diseases. Still, little is known about how genetic differences might influence natural selection within wildlife populations. Here we link genetic variation with differential susceptibility of white-tailed deer to chronic wasting disease (CWD), with implications for fitness and disease-driven genetic selection. We developed a single nucleotide polymorphism (SNP) assay to efficiently genotype deer at the locus of interest (in the 96th codon of the PRNP gene). Then, using a Bayesian modeling approach, we found that the more susceptible genotype had over four times greater risk of CWD infection; and, once infected, deer with the resistant genotype survived 49% longer (8.25 more months). We used these epidemiological parameters in a multi-stage population matrix model to evaluate relative fitness based on genotype-specific population growth rates. The differences in disease infection and mortality rates allowed genetically resistant deer to achieve higher population growth and obtain a long-term fitness advantage, which translated into a selection coefficient of over 1% favoring the CWD-resistant genotype. This selective pressure suggests that the resistant allele could become dominant in the population within an evolutionarily short time frame. Our work provides a rare example of a quantifiable disease-driven selection process in a wildlife population, demonstrating the potential for infectious diseases to alter host populations. This will have direct bearing on the epidemiology, dynamics, and future trends in CWD transmission and spread. Understanding genotype-specific epidemiology will improve predictive models and inform management strategies for CWD-affected cervid populations.

Theory of time-averaged neutral dynamics with environmental stochasticity

NASA Astrophysics Data System (ADS)

Danino, Matan; Shnerb, Nadav M.

2018-04-01

Competition is the main driver of population dynamics, which shapes the genetic composition of populations and the assembly of ecological communities. Neutral models assume that all the individuals are equivalent and that the dynamics is governed by demographic (shot) noise, with a steady state species abundance distribution (SAD) that reflects a mutation-extinction equilibrium. Recently, many empirical and theoretical studies emphasized the importance of environmental variations that affect coherently the relative fitness of entire populations. Here we consider two generic time-averaged neutral models; in both the relative fitness of each species fluctuates independently in time but its mean is zero. The first (model A) describes a system with local competition and linear fitness dependence of the birth-death rates, while in the second (model B) the competition is global and the fitness dependence is nonlinear. Due to this nonlinearity, model B admits a noise-induced stabilization mechanism that facilitates the invasion of new mutants. A self-consistent mean-field approach is used to reduce the multispecies problem to two-species dynamics, and the large-N asymptotics of the emerging set of Fokker-Planck equations is presented and solved. Our analytic expressions are shown to fit the SADs obtained from extensive Monte Carlo simulations and from numerical solutions of the corresponding master equations.

Dominance genetic variance for traits under directional selection in Drosophila serrata.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2015-05-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.

Demographic and genetic consequences of disturbed sex determination.

PubMed

Wedekind, Claus

2017-09-19

During sex determination, genetic and/or environmental factors determine the cascade of processes of gonad development. Many organisms, therefore, have a developmental window in which their sex determination can be sensitive to, for example, unusual temperatures or chemical pollutants. Disturbed environments can distort population sex ratios and may even cause sex reversal in species with genetic sex determination. The resulting genotype-phenotype mismatches can have long-lasting effects on population demography and genetics. I review the theoretical and empirical work in this context and explore in a simple population model the role of the fitness v yy of chromosomally aberrant YY genotypes that are a consequence of environmentally induced feminization. Low v yy is mostly beneficial for population growth. During feminization, low v yy reduces the proportion of genetic males and hence accelerates population growth, especially at low rates of feminization and at high fitness costs of the feminization itself (i.e. when feminization would otherwise not affect population dynamics much). When sex reversal ceases, low v yy mitigates the negative effects of feminization and can even prevent population extinction. Little is known about v yy in natural populations. The available models now need to be parametrized in order to better predict the long-term consequences of disturbed sex determination.This article is part of the themed issue 'Adult sex ratios and reproductive decisions: a critical re-examination of sex differences in human and animal societies'. © 2017 The Author(s).

Dynamical behaviour of a discrete selection-migration model with arbitrary dominance

Treesearch

James F. Selgrade; Jordan West Bostic; James H. Roberds

2009-01-01

To study the effects of immigration of genes (possibly transgenic) into a natural population, a one-island selection-migration model with density-dependent regulation is used to track allele frequency and population size. The existence and uniqueness of a polymorphic genetic equilibrium is proved under a general assumption about dominance in fitnesses. Also, conditions...

Genetic parameter estimation for pre- and post-weaning traits in Brahman cattle in Brazil.

PubMed

Vargas, Giovana; Buzanskas, Marcos Eli; Guidolin, Diego Gomes Freire; Grossi, Daniela do Amaral; Bonifácio, Alexandre da Silva; Lôbo, Raysildo Barbosa; da Fonseca, Ricardo; Oliveira, João Ademir de; Munari, Danísio Prado

2014-10-01

Beef cattle producers in Brazil use body weight traits as breeding program selection criteria due to their great economic importance. The objectives of this study were to evaluate different animal models, estimate genetic parameters, and define the most fitting model for Brahman cattle body weight standardized at 120 (BW120), 210 (BW210), 365 (BW365), 450 (BW450), and 550 (BW550) days of age. To estimate genetic parameters, single-, two-, and multi-trait analyses were performed using the animal model. The likelihood ratio test was verified between all models. For BW120 and BW210, additive direct genetic, maternal genetic, maternal permanent environment, and residual effects were considered, while for BW365 and BW450, additive direct genetic, maternal genetic, and residual effects were considered. Finally, for BW550, additive direct genetic and residual effects were considered. Estimates of direct heritability for BW120 were similar in all analyses; however, for the other traits, multi-trait analysis resulted in higher estimates. The maternal heritability and proportion of maternal permanent environmental variance to total variance were minimal in multi-trait analyses. Genetic, environmental, and phenotypic correlations were of high magnitude between all traits. Multi-trait analyses would aid in the parameter estimation for body weight at older ages because they are usually affected by a lower number of animals with phenotypic information due to culling and mortality.

The relationship between parental depressive symptoms and offspring psychopathology: evidence from a children-of-twins study and an adoption study.

PubMed

McAdams, T A; Rijsdijk, F V; Neiderhiser, J M; Narusyte, J; Shaw, D S; Natsuaki, M N; Spotts, E L; Ganiban, J M; Reiss, David; Leve, L D; Lichtenstein, P; Eley, T C

2015-01-01

Parental depressive symptoms are associated with emotional and behavioural problems in offspring. However, genetically informative studies are needed to distinguish potential causal effects from genetic confounds, and longitudinal studies are required to distinguish parent-to-child effects from child-to-parent effects. We conducted cross-sectional analyses on a sample of Swedish twins and their adolescent offspring (n = 876 twin families), and longitudinal analyses on a US sample of children adopted at birth, their adoptive parents, and their birth mothers (n = 361 adoptive families). Depressive symptoms were measured in parents, and externalizing and internalizing problems measured in offspring. Structural equation models were fitted to the data. Results of model fitting suggest that associations between parental depressive symptoms and offspring internalizing and externalizing problems remain after accounting for genes shared between parent and child. Genetic transmission was not evident in the twin study but was evident in the adoption study. In the longitudinal adoption study child-to-parent effects were evident. We interpret the results as demonstrating that associations between parental depressive symptoms and offspring emotional and behavioural problems are not solely attributable to shared genes, and that bidirectional effects may be present in intergenerational associations.

Segmenting by Risk Perceptions: Predicting Young Adults’ Genetic-Belief Profiles with Health and Opinion-Leader Covariates

PubMed Central

Smith, Rachel A.; Greenberg, Marisa; Parrott, Roxanne L.

2014-01-01

With a growing interest in using genetic information to motivate young adults’ health behaviors, audience segmentation is needed for effective campaign design. Using latent class analysis, this study identifies segments based on young adults’ (N = 327) beliefs about genetic threats to their health and personal efficacy over genetic influences on their health. A four-class model was identified. The model indicators fit the risk perception attitude framework (Rimal & Real, 2003), but the covariates (e.g., current health behaviors) did not. In addition, opinion leader qualities covaried with one profile: those in this profile engaged in fewer preventative behaviors and more dangerous treatment options, and also liked to persuade others, making them a particularly salient group for campaign efforts. The implications for adult-onset disorders, like alpha-1 antitrypsin deficiency are discussed. PMID:24111749

Random regression models using Legendre orthogonal polynomials to evaluate the milk production of Alpine goats.

PubMed

Silva, F G; Torres, R A; Brito, L F; Euclydes, R F; Melo, A L P; Souza, N O; Ribeiro, J I; Rodrigues, M T

2013-12-11

The objective of this study was to identify the best random regression model using Legendre orthogonal polynomials to evaluate Alpine goats genetically and to estimate the parameters for test day milk yield. On the test day, we analyzed 20,710 records of milk yield of 667 goats from the Goat Sector of the Universidade Federal de Viçosa. The evaluated models had combinations of distinct fitting orders for polynomials (2-5), random genetic (1-7), and permanent environmental (1-7) fixed curves and a number of classes for residual variance (2, 4, 5, and 6). WOMBAT software was used for all genetic analyses. A random regression model using the best Legendre orthogonal polynomial for genetic evaluation of milk yield on the test day of Alpine goats considered a fixed curve of order 4, curve of genetic additive effects of order 2, curve of permanent environmental effects of order 7, and a minimum of 5 classes of residual variance because it was the most economical model among those that were equivalent to the complete model by the likelihood ratio test. Phenotypic variance and heritability were higher at the end of the lactation period, indicating that the length of lactation has more genetic components in relation to the production peak and persistence. It is very important that the evaluation utilizes the best combination of fixed, genetic additive and permanent environmental regressions, and number of classes of heterogeneous residual variance for genetic evaluation using random regression models, thereby enhancing the precision and accuracy of the estimates of parameters and prediction of genetic values.

Restricted maximum likelihood estimation of genetic principal components and smoothed covariance matrices

PubMed Central

Meyer, Karin; Kirkpatrick, Mark

2005-01-01

Principal component analysis is a widely used 'dimension reduction' technique, albeit generally at a phenotypic level. It is shown that we can estimate genetic principal components directly through a simple reparameterisation of the usual linear, mixed model. This is applicable to any analysis fitting multiple, correlated genetic effects, whether effects for individual traits or sets of random regression coefficients to model trajectories. Depending on the magnitude of genetic correlation, a subset of the principal component generally suffices to capture the bulk of genetic variation. Corresponding estimates of genetic covariance matrices are more parsimonious, have reduced rank and are smoothed, with the number of parameters required to model the dispersion structure reduced from k(k + 1)/2 to m(2k - m + 1)/2 for k effects and m principal components. Estimation of these parameters, the largest eigenvalues and pertaining eigenvectors of the genetic covariance matrix, via restricted maximum likelihood using derivatives of the likelihood, is described. It is shown that reduced rank estimation can reduce computational requirements of multivariate analyses substantially. An application to the analysis of eight traits recorded via live ultrasound scanning of beef cattle is given. PMID:15588566

Inclusion of the fitness sharing technique in an evolutionary algorithm to analyze the fitness landscape of the genetic code adaptability.

PubMed

Santos, José; Monteagudo, Ángel

2017-03-27

The canonical code, although prevailing in complex genomes, is not universal. It was shown the canonical genetic code superior robustness compared to random codes, but it is not clearly determined how it evolved towards its current form. The error minimization theory considers the minimization of point mutation adverse effect as the main selection factor in the evolution of the code. We have used simulated evolution in a computer to search for optimized codes, which helps to obtain information about the optimization level of the canonical code in its evolution. A genetic algorithm searches for efficient codes in a fitness landscape that corresponds with the adaptability of possible hypothetical genetic codes. The lower the effects of errors or mutations in the codon bases of a hypothetical code, the more efficient or optimal is that code. The inclusion of the fitness sharing technique in the evolutionary algorithm allows the extent to which the canonical genetic code is in an area corresponding to a deep local minimum to be easily determined, even in the high dimensional spaces considered. The analyses show that the canonical code is not in a deep local minimum and that the fitness landscape is not a multimodal fitness landscape with deep and separated peaks. Moreover, the canonical code is clearly far away from the areas of higher fitness in the landscape. Given the non-presence of deep local minima in the landscape, although the code could evolve and different forces could shape its structure, the fitness landscape nature considered in the error minimization theory does not explain why the canonical code ended its evolution in a location which is not an area of a localized deep minimum of the huge fitness landscape.

The origin of human complex diversity: Stochastic epistatic modules and the intrinsic compatibility between distributional robustness and phenotypic changeability.

PubMed

Ijichi, Shinji; Ijichi, Naomi; Ijichi, Yukina; Imamura, Chikako; Sameshima, Hisami; Kawaike, Yoichi; Morioka, Hirofumi

2018-01-01

The continuing prevalence of a highly heritable and hypo-reproductive extreme tail of a human neurobehavioral quantitative diversity suggests the possibility that the reproductive majority retains the genetic mechanism for the extremes. From the perspective of stochastic epistasis, the effect of an epistatic modifier variant can randomly vary in both phenotypic value and effect direction among the careers depending on the genetic individuality, and the modifier careers are ubiquitous in the population distribution. The neutrality of the mean genetic effect in the careers warrants the survival of the variant under selection pressures. Functionally or metabolically related modifier variants make an epistatic network module and dozens of modules may be involved in the phenotype. To assess the significance of stochastic epistasis, a simplified module-based model was employed. The individual repertoire of the modifier variants in a module also participates in the genetic individuality which determines the genetic contribution of each modifier in the career. Because the entire contribution of a module to the phenotypic outcome is consequently unpredictable in the model, the module effect represents the total contribution of the related modifiers as a stochastic unit in the simulations. As a result, the intrinsic compatibility between distributional robustness and quantitative changeability could mathematically be simulated using the model. The artificial normal distribution shape in large-sized simulations was preserved in each generation even if the lowest fitness tail was un-reproductive. The robustness of normality beyond generations is analogous to the real situations of human complex diversity including neurodevelopmental conditions. The repeated regeneration of the un-reproductive extreme tail may be inevitable for the reproductive majority's competence to survive and change, suggesting implications of the extremes for others. Further model-simulations to illustrate how the fitness of extreme individuals can be low through generations may be warranted to increase the credibility of this stochastic epistasis model.

Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications

PubMed Central

Bouvet, J-M; Makouanzi, G; Cros, D; Vigneron, Ph

2016-01-01

Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker-based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of-fit, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of-fit and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fitting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information. PMID:26328760

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

PubMed

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Model-Based Linkage Analysis of a Quantitative Trait.

PubMed

Song, Yeunjoo E; Song, Sunah; Schnell, Audrey H

2017-01-01

Linkage Analysis is a family-based method of analysis to examine whether any typed genetic markers cosegregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single-marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it also includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single-marker analysis, and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

How important are direct fitness benefits of sexual selection?

NASA Astrophysics Data System (ADS)

Møller, A. P.; Jennions, M. D.

2001-10-01

Females may choose mates based on the expression of secondary sexual characters that signal direct, material fitness benefits or indirect, genetic fitness benefits. Genetic benefits are acquired in the generation subsequent to that in which mate choice is performed, and the maintenance of genetic variation in viability has been considered a theoretical problem. Consequently, the magnitude of indirect benefits has traditionally been considered to be small. Direct fitness benefits can be maintained without consideration of mechanisms sustaining genetic variability, and they have thus been equated with the default benefits acquired by choosy females. There is, however, still debate as to whether or not males should honestly advertise direct benefits such as their willingness to invest in parental care. We use meta-analysis to estimate the magnitude of direct fitness benefits in terms of fertility, fecundity and two measures of paternal care (feeding rate in birds, hatching rate in male guarding ectotherms) based on an extensive literature survey. The mean coefficients of determination weighted by sample size were 6.3%, 2.3%, 1.3% and 23.6%, respectively. This compares to a mean weighted coefficient of determination of 1.5% for genetic viability benefits in studies of sexual selection. Thus, for several fitness components, direct benefits are only slightly more important than indirect ones arising from female choice. Hatching rate in male guarding ectotherms was by far the most important direct fitness component, explaining almost a quarter of the variance. Our analysis also shows that male sexual advertisements do not always reliably signal direct fitness benefits.

Genome-Wide Gene Expression Analysis of Bordetella pertussis Isolates Associated with a Resurgence in Pertussis: Elucidation of Factors Involved in the Increased Fitness of Epidemic Strains

PubMed Central

King, Audrey J.; van der Lee, Saskia; Mohangoo, Archena; van Gent, Marjolein; van der Ark, Arno; van de Waterbeemd, Bas

2013-01-01

Bordetella pertussis (B. pertussis) is the causative agent of whooping cough, which is a highly contagious disease in the human respiratory tract. Despite vaccination since the 1950s, pertussis remains the most prevalent vaccine-preventable disease in developed countries. A recent resurgence pertussis is associated with the expansion of B. pertussis strains with a novel allele for the pertussis toxin (ptx) promoter ptxP3 in place of resident ptxP1 strains. The recent expansion of ptxP3 strains suggests that these strains carry mutations that have increased their fitness. Compared to the ptxP1 strains, ptxP3 strains produce more Ptx, which results in increased virulence and immune suppression. In this study, we investigated the contribution of gene expression changes of various genes on the increased fitness of the ptxP3 strains. Using genome-wide gene expression profiling, we show that several virulence genes had higher expression levels in the ptxP3 strains compared to the ptxP1 strains. We provide the first evidence that wildtype ptxP3 strains are better colonizers in an intranasal mouse infection model. This study shows that the ptxP3 mutation and the genetic background of ptxP3 strains affect fitness by contributing to the ability to colonize in a mouse infection model. These results show that the genetic background of ptxP3 strains with a higher expression of virulence genes contribute to increased fitness. PMID:23776625

Use of adaptive laboratory evolution to discover key mutations enabling rapid growth of Escherichia coli K-12 MG1655 on glucose minimal medium.

PubMed

LaCroix, Ryan A; Sandberg, Troy E; O'Brien, Edward J; Utrilla, Jose; Ebrahim, Ali; Guzman, Gabriela I; Szubin, Richard; Palsson, Bernhard O; Feist, Adam M

2015-01-01

Adaptive laboratory evolution (ALE) has emerged as an effective tool for scientific discovery and addressing biotechnological needs. Much of ALE's utility is derived from reproducibly obtained fitness increases. Identifying causal genetic changes and their combinatorial effects is challenging and time-consuming. Understanding how these genetic changes enable increased fitness can be difficult. A series of approaches that address these challenges was developed and demonstrated using Escherichia coli K-12 MG1655 on glucose minimal media at 37°C. By keeping E. coli in constant substrate excess and exponential growth, fitness increases up to 1.6-fold were obtained compared to the wild type. These increases are comparable to previously reported maximum growth rates in similar conditions but were obtained over a shorter time frame. Across the eight replicate ALE experiments performed, causal mutations were identified using three approaches: identifying mutations in the same gene/region across replicate experiments, sequencing strains before and after computationally determined fitness jumps, and allelic replacement coupled with targeted ALE of reconstructed strains. Three genetic regions were most often mutated: the global transcription gene rpoB, an 82-bp deletion between the metabolic pyrE gene and rph, and an IS element between the DNA structural gene hns and tdk. Model-derived classification of gene expression revealed a number of processes important for increased growth that were missed using a gene classification system alone. The methods described here represent a powerful combination of technologies to increase the speed and efficiency of ALE studies. The identified mutations can be examined as genetic parts for increasing growth rate in a desired strain and for understanding rapid growth phenotypes. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Use of Adaptive Laboratory Evolution To Discover Key Mutations Enabling Rapid Growth of Escherichia coli K-12 MG1655 on Glucose Minimal Medium

PubMed Central

LaCroix, Ryan A.; Sandberg, Troy E.; O'Brien, Edward J.; Utrilla, Jose; Ebrahim, Ali; Guzman, Gabriela I.; Szubin, Richard; Palsson, Bernhard O.

2014-01-01

Adaptive laboratory evolution (ALE) has emerged as an effective tool for scientific discovery and addressing biotechnological needs. Much of ALE's utility is derived from reproducibly obtained fitness increases. Identifying causal genetic changes and their combinatorial effects is challenging and time-consuming. Understanding how these genetic changes enable increased fitness can be difficult. A series of approaches that address these challenges was developed and demonstrated using Escherichia coli K-12 MG1655 on glucose minimal media at 37°C. By keeping E. coli in constant substrate excess and exponential growth, fitness increases up to 1.6-fold were obtained compared to the wild type. These increases are comparable to previously reported maximum growth rates in similar conditions but were obtained over a shorter time frame. Across the eight replicate ALE experiments performed, causal mutations were identified using three approaches: identifying mutations in the same gene/region across replicate experiments, sequencing strains before and after computationally determined fitness jumps, and allelic replacement coupled with targeted ALE of reconstructed strains. Three genetic regions were most often mutated: the global transcription gene rpoB, an 82-bp deletion between the metabolic pyrE gene and rph, and an IS element between the DNA structural gene hns and tdk. Model-derived classification of gene expression revealed a number of processes important for increased growth that were missed using a gene classification system alone. The methods described here represent a powerful combination of technologies to increase the speed and efficiency of ALE studies. The identified mutations can be examined as genetic parts for increasing growth rate in a desired strain and for understanding rapid growth phenotypes. PMID:25304508

Exploring the fitness landscape of poliovirus

NASA Astrophysics Data System (ADS)

Bianco, Simone; Acevedo, Ashely; Andino, Raul; Tang, Chao

2012-02-01

RNA viruses are known to display extraordinary adaptation capabilities to different environments, due to high mutation rates. Their very dynamical evolution is captured by the quasispecies concept, according to which the viral population forms a swarm of genetic variants linked through mutation, which cooperatively interact at a functional level and collectively contribute to the characteristics of the population. The description of the viral fitness landscape becomes paramount towards a more thorough understanding of the virus evolution and spread. The high mutation rate, together with the cooperative nature of the quasispecies, makes it particularly challenging to explore its fitness landscape. I will present an investigation of the dynamical properties of poliovirus fitness landscape, through both the adoption of new experimental techniques and theoretical models.

Simultaneous parameter optimization of x-ray and neutron reflectivity data using genetic algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Surendra, E-mail: surendra@barc.gov.in; Basu, Saibal

2016-05-23

X-ray and neutron reflectivity are two non destructive techniques which provide a wealth of information on thickness, structure and interracial properties in nanometer length scale. Combination of X-ray and neutron reflectivity is well suited for obtaining physical parameters of nanostructured thin films and superlattices. Neutrons provide a different contrast between the elements than X-rays and are also sensitive to the magnetization depth profile in thin films and superlattices. The real space information is extracted by fitting a model for the structure of the thin film sample in reflectometry experiments. We have applied a Genetic Algorithms technique to extract depth dependentmore » structure and magnetic in thin film and multilayer systems by simultaneously fitting X-ray and neutron reflectivity data.« less

Riding across the selection landscape: fitness consequences of annual variation in reproductive characteristics

PubMed Central

Tremblay, Raymond L.; Ackerman, James D.; Pérez, Maria-Eglée

2010-01-01

Evolutionary models estimating phenotypic selection in character size usually assume that the character is invariant across reproductive bouts. We show that variation in the size of reproductive traits may be large over multiple events and can influence fitness in organisms where these traits are produced anew each season. With data from populations of two orchid species, Caladenia valida and Tolumnia variegata, we used Bayesian statistics to investigate the effect on the distribution in fitness of individuals when the fitness landscape is not flat and when characters vary across reproductive bouts. Inconsistency in character size across reproductive periods within an individual increases the uncertainty of mean fitness and, consequently, the uncertainty in individual fitness. The trajectory of selection is likely to be muddled as a consequence of variation in morphology of individuals across reproductive bouts. The frequency and amplitude of such changes will certainly affect the dynamics between selection and genetic drift. PMID:20047875

The quantitative genetics of maximal and basal rates of oxygen consumption in mice.

PubMed Central

Dohm, M R; Hayes, J P; Garland, T

2001-01-01

A positive genetic correlation between basal metabolic rate (BMR) and maximal (VO(2)max) rate of oxygen consumption is a key assumption of the aerobic capacity model for the evolution of endothermy. We estimated the genetic (V(A), additive, and V(D), dominance), prenatal (V(N)), and postnatal common environmental (V(C)) contributions to individual differences in metabolic rates and body mass for a genetically heterogeneous laboratory strain of house mice (Mus domesticus). Our breeding design did not allow the simultaneous estimation of V(D) and V(N). Regardless of whether V(D) or V(N) was assumed, estimates of V(A) were negative under the full models. Hence, we fitted reduced models (e.g., V(A) + V(N) + V(E) or V(A) + V(E)) and obtained new variance estimates. For reduced models, narrow-sense heritability (h(2)(N)) for BMR was <0.1, but estimates of h(2)(N) for VO(2)max were higher. When estimated with the V(A) + V(E) model, the additive genetic covariance between VO(2)max and BMR was positive and statistically different from zero. This result offers tentative support for the aerobic capacity model for the evolution of vertebrate energetics. However, constraints imposed on the genetic model may cause our estimates of additive variance and covariance to be biased, so our results should be interpreted with caution and tested via selection experiments. PMID:11560903

Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle

PubMed Central

Pirinen, Eija; Canto, Carles; Jo, Young-Suk; Morato, Laia; Zhang, Hongbo; Menzies, Keir; Williams, Evan G.; Mouchiroud, Laurent; Moullan, Norman; Hagberg, Carolina; Li, Wei; Timmers, Silvie; Imhof, Ralph; Verbeek, Jef; Pujol, Aurora; van Loon, Barbara; Viscomi, Carlo; Zeviani, Massimo; Schrauwen, Patrick; Sauve, Anthony; Schoonjans, Kristina; Auwerx, Johan

2014-01-01

SUMMARY We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function. PMID:24814482

Genetic algorithm for nuclear data evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arthur, Jennifer Ann

These are slides on genetic algorithm for nuclear data evaluation. The following is covered: initial population, fitness (outer loop), calculate fitness, selection (first part of inner loop), reproduction (second part of inner loop), solution, and examples.

Quantitative maps of genetic interactions in yeast - comparative evaluation and integrative analysis.

PubMed

Lindén, Rolf O; Eronen, Ville-Pekka; Aittokallio, Tero

2011-03-24

High-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms. Using large-scale data matrices from epistatic miniarray profiling (E-MAP), genetic interaction mapping (GIM), and synthetic genetic array (SGA) approaches, we carried out here a systematic comparative evaluation among these quantitative maps of genetic interactions in yeast. The relatively low association between the original interaction measurements or their customized scores could be improved using a matrix-based modelling framework, which enables the use of single- and double-mutant fitness estimates and measurements, respectively, when scoring genetic interactions. Toward an integrative analysis, we show how the detections from the different screening approaches can be combined to suggest novel positive and negative interactions which are complementary to those obtained using any single screening approach alone. The matrix approximation procedure has been made available to support the design and analysis of the future screening studies. We have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.

Broad Bandwidth or High Fidelity? Evidence from the Structure of Genetic and Environmental Effects on the Facets of the Five Factor Model

PubMed Central

Briley, Daniel A.; Tucker-Drob, Elliot M.

2017-01-01

The Five Factor Model (FFM) of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. Models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets for three of the Big Five domains. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality. PMID:22695681

The Frequency of Fitness Peak Shifts Is Increased at Expanding Range Margins Due to Mutation Surfing

PubMed Central

Burton, Olivia J.; Travis, Justin M. J.

2008-01-01

Dynamic species' ranges, those that are either invasive or shifting in response to environmental change, are the focus of much recent interest in ecology, evolution, and genetics. Understanding how range expansions can shape evolutionary trajectories requires the consideration of nonneutral variability and genetic architecture, yet the majority of empirical and theoretical work to date has explored patterns of neutral variability. Here we use forward computer simulations of population growth, dispersal, and mutation to explore how range-shifting dynamics can influence evolution on rugged fitness landscapes. We employ a two-locus model, incorporating sign epistasis, and find that there is an increased likelihood of fitness peak shifts during a period of range expansion. Maladapted valley genotypes can accumulate at an expanding range front through a phenomenon called mutation surfing, which increases the likelihood that a mutation leading to a higher peak will occur. Our results indicate that most peak shifts occur close to the expanding front. We also demonstrate that periods of range shifting are especially important for peak shifting in species with narrow geographic distributions. Our results imply that trajectories on rugged fitness landscapes can be modified substantially when ranges are dynamic. PMID:18505864

Optimization of Land Use Suitability for Agriculture Using Integrated Geospatial Model and Genetic Algorithms

NASA Astrophysics Data System (ADS)

Mansor, S. B.; Pormanafi, S.; Mahmud, A. R. B.; Pirasteh, S.

2012-08-01

In this study, a geospatial model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the infrastructural preference. The model was developed based on multi-agent genetic algorithm. The model was customized to accommodate the constraint set for the study area, namely the resource saving and environmental-friendly. The model was then applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Menderjan Basin in Iran. The first task was to study the dominant crops and economic suitability evaluation of land. Second task was to determine the fitness function for the genetic algorithms. The third objective was to optimize the land use map using economical benefits. The results has indicated that the proposed model has much better performance for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.

Good genes, genetic compatibility and the evolution of polyandry: use of the diallel cross to address competing hypotheses.

PubMed

Ivy, T M

2007-03-01

Genetic benefits can enhance the fitness of polyandrous females through the high intrinsic genetic quality of females' mates or through the interaction between female and male genes. I used a full diallel cross, a quantitative genetics design that involves all possible crosses among a set of genetically homogeneous lines, to determine the mechanism through which polyandrous female decorated crickets (Gryllodes sigillatus) obtain genetic benefits. I measured several traits related to fitness and partitioned the phenotypic variance into components representing the contribution of additive genetic variance ('good genes'), nonadditive genetic variance (genetic compatibility), as well as maternal and paternal effects. The results reveal a significant variance attributable to both nonadditive and additive sources in the measured traits, and their influence depended on which trait was considered. The lack of congruence in sources of phenotypic variance among these fitness-related traits suggests that the evolution and maintenance of polyandry are unlikely to have resulted from one selective influence, but rather are the result of the collective effects of a number of factors.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models.

PubMed

Mulder, Han A; Rönnegård, Lars; Fikse, W Freddy; Veerkamp, Roel F; Strandberg, Erling

2013-07-04

Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike's information criterion using h-likelihood to select the best fitting model. We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike's information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike's information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

Fitness components and ecological risk of transgenic release: a model using Japanese medaka (Oryzias latipes).

PubMed

Muir, W M; Howard, R D

2001-07-01

Any release of transgenic organisms into nature is a concern because ecological relationships between genetically engineered organisms and other organisms (including their wild-type conspecifics) are unknown. To address this concern, we developed a method to evaluate risk in which we input estimates of fitness parameters from a founder population into a recurrence model to predict changes in transgene frequency after a simulated transgenic release. With this method, we grouped various aspects of an organism's life cycle into six net fitness components: juvenile viability, adult viability, age at sexual maturity, female fecundity, male fertility, and mating advantage. We estimated these components for wild-type and transgenic individuals using the fish, Japanese medaka (Oryzias latipes). We generalized our model's predictions using various combinations of fitness component values in addition to our experimentally derived estimates. Our model predicted that, for a wide range of parameter values, transgenes could spread in populations despite high juvenile viability costs if transgenes also have sufficiently high positive effects on other fitness components. Sensitivity analyses indicated that transgene effects on age at sexual maturity should have the greatest impact on transgene frequency, followed by juvenile viability, mating advantage, female fecundity, and male fertility, with changes in adult viability, resulting in the least impact.

Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation

PubMed Central

Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.

2009-01-01

Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078

The effects of inbreeding, genetic dissimilarity and phenotype on male reproductive success in a dioecious plant

PubMed Central

Austerlitz, Frédéric; Gleiser, Gabriela; Teixeira, Sara; Bernasconi, Giorgina

2012-01-01

Pollen fate can strongly affect the genetic structure of populations with restricted gene flow and significant inbreeding risk. We established an experimental population of inbred and outbred Silene latifolia plants to evaluate the effects of (i) inbreeding depression, (ii) phenotypic variation and (iii) relatedness between mates on male fitness under natural pollination. Paternity analysis revealed that outbred males sired significantly more offspring than inbred males. Independently of the effects of inbreeding, male fitness depended on several male traits, including a sexually dimorphic (flower number) and a gametophytic trait (in vitro pollen germination rate). In addition, full-sib matings were less frequent than randomly expected. Thus, inbreeding, phenotype and genetic dissimilarity simultaneously affect male fitness in this animal-pollinated plant. While inbreeding depression might threaten population persistence, the deficiency of effective matings between sibs and the higher fitness of outbred males will reduce its occurrence and counter genetic erosion. PMID:21561968

Multiple-trait structured antedependence model to study the relationship between litter size and birth weight in pigs and rabbits.

PubMed

David, Ingrid; Garreau, Hervé; Balmisse, Elodie; Billon, Yvon; Canario, Laurianne

2017-01-20

Some genetic studies need to take into account correlations between traits that are repeatedly measured over time. Multiple-trait random regression models are commonly used to analyze repeated traits but suffer from several major drawbacks. In the present study, we developed a multiple-trait extension of the structured antedependence model (SAD) to overcome this issue and validated its usefulness by modeling the association between litter size (LS) and average birth weight (ABW) over parities in pigs and rabbits. The single-trait SAD model assumes that a random effect at time [Formula: see text] can be explained by the previous values of the random effect (i.e. at previous times). The proposed multiple-trait extension of the SAD model consists in adding a cross-antedependence parameter to the single-trait SAD model. This model can be easily fitted using ASReml and the OWN Fortran program that we have developed. In comparison with the random regression model, we used our multiple-trait SAD model to analyze the LS and ABW of 4345 litters from 1817 Large White sows and 8706 litters from 2286 L-1777 does over a maximum of five successive parities. For both species, the multiple-trait SAD fitted the data better than the random regression model. The difference between AIC of the two models (AIC_random regression-AIC_SAD) were equal to 7 and 227 for pigs and rabbits, respectively. A similar pattern of heritability and correlation estimates was obtained for both species. Heritabilities were lower for LS (ranging from 0.09 to 0.29) than for ABW (ranging from 0.23 to 0.39). The general trend was a decrease of the genetic correlation for a given trait between more distant parities. Estimates of genetic correlations between LS and ABW were negative and ranged from -0.03 to -0.52 across parities. No correlation was observed between the permanent environmental effects, except between the permanent environmental effects of LS and ABW of the same parity, for which the estimate of the correlation was strongly negative (ranging from -0.57 to -0.67). We demonstrated that application of our multiple-trait SAD model is feasible for studying several traits with repeated measurements and showed that it provided a better fit to the data than the random regression model.

Spatio-temporal variation in fitness responses to contrasting environments in Arabidopsis thaliana.

PubMed

Exposito-Alonso, Moises; Brennan, Adrian C; Alonso-Blanco, Carlos; Picó, F Xavier

2018-06-27

The evolutionary response of organisms to global climate change is expected to be strongly conditioned by preexisting standing genetic variation. In addition, natural selection imposed by global climate change on fitness-related traits can be heterogeneous over time. We estimated selection of life-history traits of an entire genetic lineage of the plant Arabidopsis thaliana occurring in north-western Iberian Peninsula that were transplanted over multiple years into two environmentally contrasting field sites in southern Spain, as southern environments are expected to move progressively northwards with climate change in the Iberian Peninsula. The results indicated that natural selection on flowering time prevailed over that on recruitment. Selection favored early flowering in six of eight experiments and late flowering in the other two. Such heterogeneity of selection for flowering time might be a powerful mechanism for maintaining genetic diversity in the long run. We also found that north-western A. thaliana accessions from warmer environments exhibited higher fitness and higher phenotypic plasticity for flowering time in southern experimental facilities. Overall, our transplant experiments suggested that north-western Iberian A. thaliana has the means to cope with increasingly warmer environments in the region as predicted by trends in global climate change models. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Genetic variation and co-variation for fitness between intra-population and inter-population backgrounds in the red flour beetle, Tribolium castaneum

PubMed Central

Drury, Douglas W.; Wade, Michael J.

2010-01-01

Hybrids from crosses between populations of the flour beetle, Tribolium castaneum, express varying degrees of inviability and morphological abnormalities. The proportion of allopatric population hybrids exhibiting these negative hybrid phenotypes varies widely, from 3% to 100%, depending upon the pair of populations crossed. We crossed three populations and measured two fitness components, fertility and adult offspring numbers from successful crosses, to determine how genes segregating within populations interact in inter-population hybrids to cause the negative phenotypes. With data from crosses of 40 sires from each of three populations to groups of 5 dams from their own and two divergent populations, we estimated the genetic variance and covariance for breeding value of fitness between the intra- and inter-population backgrounds and the sire × dam-population interaction variance. The latter component of the variance in breeding values estimates the change in genic effects between backgrounds owing to epistasis. Interacting genes with a positive effect, prior to fixation, in the sympatric background but a negative effect in the hybrid background cause reproductive incompatibility in the Dobzhansky-Muller speciation model. Thus, the sire × dam-population interaction provides a way to measure the progress toward speciation of genetically differentiating populations on a trait by trait basis using inter-population hybrids. PMID:21044199

Genetic variation facilitates seedling establishment but not population growth rate of a perennial invader

PubMed Central

Li, Shou-Li; Vasemägi, Anti; Ramula, Satu

2016-01-01

Background and Aims Assessing the demographic consequences of genetic variation is fundamental to invasion biology. However, genetic and demographic approaches are rarely combined to explore the effects of genetic variation on invasive populations in natural environments. This study combined population genetics, demographic data and a greenhouse experiment to investigate the consequences of genetic variation for the population fitness of the perennial, invasive herb Lupinus polyphyllus. Methods Genetic and demographic data were collected from 37 L. polyphyllus populations representing different latitudes in Finland, and genetic variation was characterized based on 13 microsatellite loci. Associations between genetic variation and population size, population density, latitude and habitat were investigated. Genetic variation was then explored in relation to four fitness components (establishment, survival, growth, fecundity) measured at the population level, and the long-term population growth rate (λ). For a subset of populations genetic variation was also examined in relation to the temporal variability of λ. A further assessment was made of the role of natural selection in the observed variation of certain fitness components among populations under greenhouse conditions. Key Results It was found that genetic variation correlated positively with population size, particularly at higher latitudes, and differed among habitat types. Average seedling establishment per population increased with genetic variation in the field, but not under greenhouse conditions. Quantitative genetic divergence (QST) based on seedling establishment in the greenhouse was smaller than allelic genetic divergence (F′ST), indicating that unifying selection has a prominent role in this fitness component. Genetic variation was not associated with average survival, growth or fecundity measured at the population level, λ or its variability. Conclusions The study suggests that although genetic variation may facilitate plant invasions by increasing seedling establishment, it may not necessarily affect the long-term population growth rate. Therefore, established invasions may be able to grow equally well regardless of their genetic diversity. PMID:26420202

Analysis of longitudinal data of beef cattle raised on pasture from northern Brazil using nonlinear models.

PubMed

Lopes, Fernando B; da Silva, Marcelo C; Marques, Ednira G; McManus, Concepta M

2012-12-01

This study was undertaken to aim of estimating the genetic parameters and trends for asymptotic weight (A) and maturity rate (k) of Nellore cattle from northern Brazil. The data set was made available by the Brazilian Association of Zebu Breeders and collected between the years of 1997 and 2007. The Von Bertalanffy, Brody, Gompertz, and logistic nonlinear models were fitted by the Gauss-Newton method to weight-age data of 45,895 animals collected quarterly of the birth to 750 days old. The curve parameters were analyzed using the procedures GLM and CORR. The estimation of (co)variance components and genetic parameters was obtained using the MTDFREML software. The estimated heritability coefficients were 0.21 ± 0.013 and 0.25 ± 0.014 for asymptotic weight and maturity rate, respectively. This indicates that selection for any trait shall results in genetic progress in the herd. The genetic correlation between A and k was negative (-0.57 ± 0.03) and indicated that animals selected for high maturity rate shall result in low asymptotic weight. The Von Bertalanffy function is adequate to establish the mean growth patterns and to predict the adult weight of Nellore cattle. This model is more accurate in predicting the birth weight of these animals and has better overall fit. The prediction of adult weight using nonlinear functions can be accurate when growth curve parameters and their (co)variance components are estimated jointly. The model used in this study can be applied to the prediction of mature weight in herds where a portion of the animals are culled before they reach the adult age.

The effects of intraspecific competition and stabilizing selection on a polygenic trait.

PubMed Central

Bürger, Reinhard; Gimelfarb, Alexander

2004-01-01

The equilibrium properties of an additive multilocus model of a quantitative trait under frequency- and density-dependent selection are investigated. Two opposing evolutionary forces are assumed to act: (i) stabilizing selection on the trait, which favors genotypes with an intermediate phenotype, and (ii) intraspecific competition mediated by that trait, which favors genotypes whose effect on the trait deviates most from that of the prevailing genotypes. Accordingly, fitnesses of genotypes have a frequency-independent component describing stabilizing selection and a frequency- and density-dependent component modeling competition. We study how the equilibrium structure, in particular, number, degree of polymorphism, and genetic variance of stable equilibria, is affected by the strength of frequency dependence, and what role the number of loci, the amount of recombination, and the demographic parameters play. To this end, we employ a statistical and numerical approach, complemented by analytical results, and explore how the equilibrium properties averaged over a large number of genetic systems with a given number of loci and average amount of recombination depend on the ecological and demographic parameters. We identify two parameter regions with a transitory region in between, in which the equilibrium properties of genetic systems are distinctively different. These regions depend on the strength of frequency dependence relative to pure stabilizing selection and on the demographic parameters, but not on the number of loci or the amount of recombination. We further study the shape of the fitness function observed at equilibrium and the extent to which the dynamics in this model are adaptive, and we present examples of equilibrium distributions of genotypic values under strong frequency dependence. Consequences for the maintenance of genetic variation, the detection of disruptive selection, and models of sympatric speciation are discussed. PMID:15280253

Evidence that pairing with genetically similar mates is maladaptive in a monogamous bird

USGS Publications Warehouse

Mulard, Hervé; Danchin, E.; Talbot, S.L.; Ramey, A.M.; Hatch, Shyla A.; White, J.F.; Helfenstein, F.; Wagner, R.H.

2009-01-01

Background. Evidence of multiple genetic criteria of mate choice is accumulating in numerous taxa. In many species, females have been shown to pair with genetically dissimilar mates or with extra-pair partners that are more genetically compatible than their social mates, thereby increasing their offsprings' heterozygosity which often correlates with offspring fitness. While most studies have focused on genetically promiscuous species, few studies have addressed genetically monogamous species, in which mate choice tends to be mutual. Results. Here, we used microsatellite markers to assess individual global heterozygosity and genetic similarity of pairs in a socially and genetically monogamous seabird, the black-legged kittiwake Rissa tridactyla. We found that pairs were more genetically dissimilar than expected by chance. We also identified fitness costs of breeding with genetically similar partners: (i) genetic similarity of pairs was negatively correlated with the number of chicks hatched, and (ii) offspring heterozygosity was positively correlated with growth rate and survival. Conclusion. These findings provide evidence that breeders in a genetically monogamous species may avoid the fitness costs of reproducing with a genetically similar mate. In such species that lack the opportunity to obtain extra-pair fertilizations, mate choice may therefore be under high selective pressure. ?? 2009 Mulard et al; licensee BioMed Central Ltd.

Random Regression Models Are Suitable to Substitute the Traditional 305-Day Lactation Model in Genetic Evaluations of Holstein Cattle in Brazil

PubMed Central

Padilha, Alessandro Haiduck; Cobuci, Jaime Araujo; Costa, Cláudio Napolis; Neto, José Braccini

2016-01-01

The aim of this study was to compare two random regression models (RRM) fitted by fourth (RRM4) and fifth-order Legendre polynomials (RRM5) with a lactation model (LM) for evaluating Holstein cattle in Brazil. Two datasets with the same animals were prepared for this study. To apply test-day RRM and LMs, 262,426 test day records and 30,228 lactation records covering 305 days were prepared, respectively. The lowest values of Akaike’s information criterion, Bayesian information criterion, and estimates of the maximum of the likelihood function (−2LogL) were for RRM4. Heritability for 305-day milk yield (305MY) was 0.23 (RRM4), 0.24 (RRM5), and 0.21 (LM). Heritability, additive genetic and permanent environmental variances of test days on days in milk was from 0.16 to 0.27, from 3.76 to 6.88 and from 11.12 to 20.21, respectively. Additive genetic correlations between test days ranged from 0.20 to 0.99. Permanent environmental correlations between test days were between 0.07 and 0.99. Standard deviations of average estimated breeding values (EBVs) for 305MY from RRM4 and RRM5 were from 11% to 30% higher for bulls and around 28% higher for cows than that in LM. Rank correlations between RRM EBVs and LM EBVs were between 0.86 to 0.96 for bulls and 0.80 to 0.87 for cows. Average percentage of gain in reliability of EBVs for 305-day yield increased from 4% to 17% for bulls and from 23% to 24% for cows when reliability of EBVs from RRM models was compared to those from LM model. Random regression model fitted by fourth order Legendre polynomials is recommended for genetic evaluations of Brazilian Holstein cattle because of the higher reliability in the estimation of breeding values. PMID:26954176

Random Regression Models Are Suitable to Substitute the Traditional 305-Day Lactation Model in Genetic Evaluations of Holstein Cattle in Brazil.

PubMed

Padilha, Alessandro Haiduck; Cobuci, Jaime Araujo; Costa, Cláudio Napolis; Neto, José Braccini

2016-06-01

The aim of this study was to compare two random regression models (RRM) fitted by fourth (RRM4) and fifth-order Legendre polynomials (RRM5) with a lactation model (LM) for evaluating Holstein cattle in Brazil. Two datasets with the same animals were prepared for this study. To apply test-day RRM and LMs, 262,426 test day records and 30,228 lactation records covering 305 days were prepared, respectively. The lowest values of Akaike's information criterion, Bayesian information criterion, and estimates of the maximum of the likelihood function (-2LogL) were for RRM4. Heritability for 305-day milk yield (305MY) was 0.23 (RRM4), 0.24 (RRM5), and 0.21 (LM). Heritability, additive genetic and permanent environmental variances of test days on days in milk was from 0.16 to 0.27, from 3.76 to 6.88 and from 11.12 to 20.21, respectively. Additive genetic correlations between test days ranged from 0.20 to 0.99. Permanent environmental correlations between test days were between 0.07 and 0.99. Standard deviations of average estimated breeding values (EBVs) for 305MY from RRM4 and RRM5 were from 11% to 30% higher for bulls and around 28% higher for cows than that in LM. Rank correlations between RRM EBVs and LM EBVs were between 0.86 to 0.96 for bulls and 0.80 to 0.87 for cows. Average percentage of gain in reliability of EBVs for 305-day yield increased from 4% to 17% for bulls and from 23% to 24% for cows when reliability of EBVs from RRM models was compared to those from LM model. Random regression model fitted by fourth order Legendre polynomials is recommended for genetic evaluations of Brazilian Holstein cattle because of the higher reliability in the estimation of breeding values.

Neutral mutation as the source of genetic variation in life history traits.

PubMed

Brcić-Kostić, Krunoslav

2005-08-01

The mechanism underlying the maintenance of adaptive genetic variation is a long-standing question in evolutionary genetics. There are two concepts (mutation-selection balance and balancing selection) which are based on the phenotypic differences between alleles. Mutation - selection balance and balancing selection cannot properly explain the process of gene substitution, i.e. the molecular evolution of quantitative trait loci affecting fitness. I assume that such loci have non-essential functions (small effects on fitness), and that they have the potential to evolve into new functions and acquire new adaptations. Here I show that a high amount of neutral polymorphism at these loci can exist in real populations. Consistent with this, I propose a hypothesis for the maintenance of genetic variation in life history traits which can be efficient for the fixation of alleles with very small selective advantage. The hypothesis is based on neutral polymorphism at quantitative trait loci and both neutral and adaptive gene substitutions. The model of neutral - adaptive conversion (NAC) assumes that neutral alleles are not neutral indefinitely, and that in specific and very rare situations phenotypic (relative fitness) differences between them can appear. In this paper I focus on NAC due to phenotypic plasticity of neutral alleles. The important evolutionary consequence of NAC could be the increased adaptive potential of a population. Loci responsible for adaptation should be fast evolving genes with minimally discernible phenotypic effects, and the recent discovery of genes with such characteristics implicates them as suitable candidates for loci involved in adaptation.

Evolutionary genetics of plant adaptation.

PubMed

Anderson, Jill T; Willis, John H; Mitchell-Olds, Thomas

2011-07-01

Plants provide unique opportunities to study the mechanistic basis and evolutionary processes of adaptation to diverse environmental conditions. Complementary laboratory and field experiments are important for testing hypotheses reflecting long-term ecological and evolutionary history. For example, these approaches can infer whether local adaptation results from genetic tradeoffs (antagonistic pleiotropy), where native alleles are best adapted to local conditions, or if local adaptation is caused by conditional neutrality at many loci, where alleles show fitness differences in one environment, but not in a contrasting environment. Ecological genetics in natural populations of perennial or outcrossing plants can also differ substantially from model systems. In this review of the evolutionary genetics of plant adaptation, we emphasize the importance of field studies for understanding the evolutionary dynamics of model and nonmodel systems, highlight a key life history trait (flowering time) and discuss emerging conservation issues. Copyright © 2011 Elsevier Ltd. All rights reserved.

Contributions of Genes and Environment to Developmental Change in Alcohol Use.

PubMed

Long, E C; Verhulst, B; Aggen, S H; Kendler, K S; Gillespie, N A

2017-09-01

The precise nature of how genetic and environmental risk factors influence changes in alcohol use (AU) over time has not yet been investigated. Therefore, the aim of the present study is to examine the nature of longitudinal changes in these risk factors to AU from mid-adolescence through young adulthood. Using a large sample of male twins, we compared five developmental models that each makes different predictions regarding the longitudinal changes in genetic and environmental risks for AU. The best-fitting model indicated that genetic influences were consistent with a gradual growth in the liability to AU, whereas unique environmental risk factors were consistent with an accumulation of risks across time. These results imply that two distinct processes influence adolescent AU between the ages of 15-25. Genetic effects influence baseline levels of AU and rates of change across time, while unique environmental effects are more cumulative.

Family conflict interacts with genetic liability in predicting childhood and adolescent depression.

PubMed

Rice, Frances; Harold, Gordon T; Shelton, Katherine H; Thapar, Anita

2006-07-01

To test for gene-environment interaction with depressive symptoms and family conflict. Specifically, to first examine whether the influence of family conflict in predicting depressive symptoms is increased in individuals at genetic risk of depression. Second, to test whether the genetic component of variance in depressive symptoms increases as levels of family conflict increase. A longitudinal twin design was used. Children ages 5 to 16 were reassessed approximately 3 years later to test whether the influence of family conflict in predicting depressive symptoms varied according to genetic liability. The conflict subscale of the Family Environment Scale was used to assess family conflict and the Mood and Feelings Questionnaire was used to assess depressive symptoms. The response rate to the questionnaire at time 1 was 73% and 65% at time 2. Controlling for initial symptoms levels (i.e., internalizing at time 1), primary analyses were conducted using ordinary least-squares multiple regression. Structural equation models, using raw score maximum likelihood estimation, were also fit to the data for the purpose of model fit comparison. Results suggested significant gene-environment interaction specifically with depressive symptoms and family conflict. Genetic factors were of greater importance in the etiology of depressive symptoms where levels of family conflict were high. The effects of family conflict on depressive symptoms were greater in children and adolescents at genetic risk of depression. The present results suggest that children with a family history of depression may be at an increased risk of developing depressive symptoms in response to family conflict. Intervention programs that incorporate one or more family systems may be of benefit in alleviating the adverse effect of negative family factors on children.

Temperature-dependent behaviours are genetically variable in the nematode Caenorhabditis briggsae.

PubMed

Stegeman, Gregory W; de Mesquita, Matthew Bueno; Ryu, William S; Cutter, Asher D

2013-03-01

Temperature-dependent behaviours in Caenorhabditis elegans, such as thermotaxis and isothermal tracking, are complex behavioural responses that integrate sensation, foraging and learning, and have driven investigations to discover many essential genetic and neural pathways. The ease of manipulation of the Caenorhabditis model system also has encouraged its application to comparative analyses of phenotypic evolution, particularly contrasts of the classic model C. elegans with C. briggsae. And yet few studies have investigated natural genetic variation in behaviour in any nematode. Here we measure thermotaxis and isothermal tracking behaviour in genetically distinct strains of C. briggsae, further motivated by the latitudinal differentiation in C. briggsae that is associated with temperature-dependent fitness differences in this species. We demonstrate that C. briggsae performs thermotaxis and isothermal tracking largely similar to that of C. elegans, with a tendency to prefer its rearing temperature. Comparisons of these behaviours among strains reveal substantial heritable natural variation within each species that corresponds to three general patterns of behavioural response. However, intraspecific genetic differences in thermal behaviour often exceed interspecific differences. These patterns of temperature-dependent behaviour motivate further development of C. briggsae as a model system for dissecting the genetic underpinnings of complex behavioural traits.

Genetic algorithm with maximum-minimum crossover (GA-MMC) applied in optimization of radiation pattern control of phased-array radars for rocket tracking systems.

PubMed

Silva, Leonardo W T; Barros, Vitor F; Silva, Sandro G

2014-08-18

In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence.

Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) Applied in Optimization of Radiation Pattern Control of Phased-Array Radars for Rocket Tracking Systems

PubMed Central

Silva, Leonardo W. T.; Barros, Vitor F.; Silva, Sandro G.

2014-01-01

In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence. PMID:25196013

Rare beneficial mutations can halt Muller's ratchet

NASA Astrophysics Data System (ADS)

Balick, Daniel; Goyal, Sidhartha; Jerison, Elizabeth; Neher, Richard; Shraiman, Boris; Desai, Michael

2012-02-01

In viral, bacterial, and other asexual populations, the vast majority of non-neutral mutations are deleterious. This motivates the application of models without beneficial mutations. Here we show that the presence of surprisingly few compensatory mutations halts fitness decay in these models. Production of deleterious mutations is balanced by purifying selection, stabilizing the fitness distribution. However, stochastic vanishing of fitness classes can lead to slow fitness decay (i.e. Muller's ratchet). For weakly deleterious mutations, production overwhelms purification, rapidly decreasing population fitness. We show that when beneficial mutations are introduced, a stable steady state emerges in the form of a dynamic mutation-selection balance. We argue this state is generic for all mutation rates and population sizes, and is reached as an end state as genomes become saturated by either beneficial or deleterious mutations. Assuming all mutations have the same magnitude selective effect, we calculate the fraction of beneficial mutations necessary to maintain the dynamic balance. This may explain the unexpected maintenance of asexual genomes, as in mitochondria, in the presence of selection. This will affect in the statistics of genetic diversity in these populations.

The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits

PubMed Central

Lohmueller, Kirk E.

2014-01-01

Population genetic studies have found evidence for dramatic population growth in recent human history. It is unclear how this recent population growth, combined with the effects of negative natural selection, has affected patterns of deleterious variation, as well as the number, frequency, and effect sizes of mutations that contribute risk to complex traits. Because researchers are performing exome sequencing studies aimed at uncovering the role of low-frequency variants in the risk of complex traits, this topic is of critical importance. Here I use simulations under population genetic models where a proportion of the heritability of the trait is accounted for by mutations in a subset of the exome. I show that recent population growth increases the proportion of nonsynonymous variants segregating in the population, but does not affect the genetic load relative to a population that did not expand. Under a model where a mutation's effect on a trait is correlated with its effect on fitness, rare variants explain a greater portion of the additive genetic variance of the trait in a population that has recently expanded than in a population that did not recently expand. Further, when using a single-marker test, for a given false-positive rate and sample size, recent population growth decreases the expected number of significant associations with the trait relative to the number detected in a population that did not expand. However, in a model where there is no correlation between a mutation's effect on fitness and the effect on the trait, common variants account for much of the additive genetic variance, regardless of demography. Moreover, here demography does not affect the number of significant associations detected. These findings suggest recent population history may be an important factor influencing the power of association tests and in accounting for the missing heritability of certain complex traits. PMID:24875776

Telos, conservation of welfare, and ethical issues in genetic engineering of animals.

PubMed

Rollin, Bernard E

2015-01-01

The most long-lived metaphysics or view of reality in the history of Western thought is Aristotle's teleology, which reigned for almost 2,000 years. Biology was expressed in terms of function or telos, and accorded perfectly with common sense. The rise of mechanistic, Newtonian science vanquished teleological explanations. Understanding and accommodating animal telos was essential to success in animal husbandry, which involved respect for telos, and was presuppositional to our "ancient contract" with domestic animals. Telos was further abandoned with the rise of industrial agriculture, which utilized "technological fixes" to force animal into environments they were unsuited for, while continuing to be productive. Loss of husbandry and respect for telos created major issues for farm animal welfare, and forced the creation of a new ethic demanding respect for telos. As genetic engineering developed, the notion arose of modifying animals to fit their environment in order to avoid animal suffering, rather than fitting them into congenial environments. Most people do not favor changing the animals, rather than changing the conditions under which they are reared. Aesthetic appreciation of husbandry and virtue ethics militate in favor of restoring husbandry, rather than radically changing animal teloi. One, however, does not morally wrong teloi by changing them-one can only wrong individuals. In biomedical research, we do indeed inflict major pain, suffering and disease on animals. And genetic engineering seems to augment our ability to create animals to model diseases, particularly more than 3,000 known human genetic diseases. The disease, known as Lesch-Nyhan's syndrome or HPRT deficiency, which causes self-mutilation and mental retardation, provides us with a real possibility for genetically creating "animal models" of this disease, animals doomed to a life of great and unalleviable suffering. This of course creates a major moral dilemma. Perhaps one can use the very genetic engineering which creates this dilemma to ablate consciousness in such animal models, thereby escaping a moral impasse.

A simple fitness proxy for structured populations with continuous traits, with case studies on the evolution of haplo-diploids and genetic dimorphisms.

PubMed

Metz, J A J; Leimar, O

2011-03-01

For structured populations in equilibrium with everybody born equal, ln(R (0)) is a useful fitness proxy for evolutionarily steady strategy (ESS) and most adaptive dynamics calculations, with R (0) the average lifetime number of offspring in the clonal and haploid cases, and half the average lifetime number of offspring fathered or mothered for Mendelian diploids. When individuals have variable birth states, as is, for example, the case in spatial models, R (0) is itself an eigenvalue, which usually cannot be expressed explicitly in the trait vectors under consideration. In that case, Q(Y| X):=-det (I-L(Y| X)) can often be used as fitness proxy, with L the next-generation matrix for a potential mutant characterized by the trait vector Y in the (constant) environment engendered by a resident characterized by X. If the trait space is connected, global uninvadability can be determined from it. Moreover, it can be used in all the usual local calculations like the determination of evolutionarily singular trait vectors and their local invadability and attractivity. We conclude with three extended case studies demonstrating the usefulness of Q: the calculation of ESSs under haplo-diploid genetics (I), of evolutionarily steady genetic dimorphisms (ESDs) with a priori proportionality of macro- and micro-gametic outputs (an assumption that is generally made but the fulfilment of which is a priori highly exceptional) (II), and of ESDs without such proportionality (III). These case studies should also have some interest in their own right for the spelled out calculation recipes and their underlying modelling methodology.

An automatic scaling method for obtaining the trace and parameters from oblique ionogram based on hybrid genetic algorithm

NASA Astrophysics Data System (ADS)

Song, Huan; Hu, Yaogai; Jiang, Chunhua; Zhou, Chen; Zhao, Zhengyu; Zou, Xianjian

2016-12-01

Scaling oblique ionogram plays an important role in obtaining ionospheric structure at the midpoint of oblique sounding path. The paper proposed an automatic scaling method to extract the trace and parameters of oblique ionogram based on hybrid genetic algorithm (HGA). The extracted 10 parameters come from F2 layer and Es layer, such as maximum observation frequency, critical frequency, and virtual height. The method adopts quasi-parabolic (QP) model to describe F2 layer's electron density profile that is used to synthesize trace. And it utilizes secant theorem, Martyn's equivalent path theorem, image processing technology, and echoes' characteristics to determine seven parameters' best fit values, and three parameter's initial values in QP model to set up their searching spaces which are the needed input data of HGA. Then HGA searches the three parameters' best fit values from their searching spaces based on the fitness between the synthesized trace and the real trace. In order to verify the performance of the method, 240 oblique ionograms are scaled and their results are compared with manual scaling results and the inversion results of the corresponding vertical ionograms. The comparison results show that the scaling results are accurate or at least adequate 60-90% of the time.

Evolutionarily stable disequilibrium: endless dynamics of evolution in a stationary population.

PubMed

Takeuchi, Nobuto; Kaneko, Kunihiko; Hogeweg, Paulien

2016-05-11

Evolution is often conceived as changes in the properties of a population over generations. Does this notion exhaust the possible dynamics of evolution? Life is hierarchically organized, and evolution can operate at multiple levels with conflicting tendencies. Using a minimal model of such conflicting multilevel evolution, we demonstrate the possibility of a novel mode of evolution that challenges the above notion: individuals ceaselessly modify their genetically inherited phenotype and fitness along their lines of descent, without involving apparent changes in the properties of the population. The model assumes a population of primitive cells (protocells, for short), each containing a population of replicating catalytic molecules. Protocells are selected towards maximizing the catalytic activity of internal molecules, whereas molecules tend to evolve towards minimizing it in order to maximize their relative fitness within a protocell. These conflicting evolutionary tendencies at different levels and genetic drift drive the lineages of protocells to oscillate endlessly between high and low intracellular catalytic activity, i.e. high and low fitness, along their lines of descent. This oscillation, however, occurs independently in different lineages, so that the population as a whole appears stationary. Therefore, ongoing evolution can be hidden behind an apparently stationary population owing to conflicting multilevel evolution. © 2016 The Authors.

Direct and social genetic effects on body weight at 270 days and carcass and ham quality traits in heavy pigs.

PubMed

Rostellato, R; Sartori, C; Bonfatti, V; Chiarot, G; Carnier, P

2015-01-01

The aims of this study were to estimate covariance components for BW at 270 d (BW270) and carcass and ham quality traits in heavy pigs using models accounting for social effects and to compare the ability of such models to fit the data relative to models ignoring social interactions. Phenotypic records were from 9,871 pigs sired by 293 purebred boars mated to 456 crossbred sows. Piglets were born and reared at the same farm and randomly assigned at 60 d of age to groups (6.1 pigs per group on average) housed in finishing pens, each having an area of 6 m(2). The average additive genetic relationship among group mates was 0.11. Pigs were slaughtered at 277 ± 3 d of age and 169.7 ± 13.9 kg BW in groups of nearly 70 animals each. Four univariate animal models were compared: a basic model (M1) including only direct additive genetic effects, a model (M2) with nonheritable social group (pen) effects in addition to effects in M1, a model (M3) accounting for litter effects in addition to M2, and a model (M4) accounting for social genetic effects in addition to effects in M3. Restricted maximum likelihood estimates of covariance components were obtained for BW270; carcass backfat depth; carcass lean meat content (CLM); iodine number (IOD); and linoleic acid content (LIA) of raw ham subcutaneous fat; subcutaneous fat depth in the proximity of semimembranosus muscle (SFD1) and quadriceps femoris muscle (SFD2); and linear scores for ham round shape (RS), subcutaneous fat (SF), and marbling. Likelihood ratio tests indicated that, for all traits, M2 fit the data better than M1 and that M3 was superior to M2 except for SFD1 and SFD2. Model M4 was significantly better than M3 for BW270 (P < 0.001) and CLM, IOD, RS, and SF (P < 0.05). The contribution of social genetic effects to the total heritable variance was large for CLM and BW270, ranging from 33.2 to 35%, whereas the one for ham quality traits ranged from 6.8 (RS) to 11.2% (SF). Direct and social genetic effects on BW270 were uncorrelated, whereas there was a negative genetic covariance between direct and social effects on CLM, IOD, RS, and SF, which reduced the total heritable variance. This variance, measured relative to phenotypic variance, ranged from 21 (CLM) to 54% (BW270). Results indicate that social genetic effects affect variation in traits relevant for heavy pigs used in dry-cured hams manufacturing. Such effects should be exploited and taken into account in design of breeding programs for heavy pigs.

Non-proportional odds multivariate logistic regression of ordinal family data.

PubMed

Zaloumis, Sophie G; Scurrah, Katrina J; Harrap, Stephen B; Ellis, Justine A; Gurrin, Lyle C

2015-03-01

Methods to examine whether genetic and/or environmental sources can account for the residual variation in ordinal family data usually assume proportional odds. However, standard software to fit the non-proportional odds model to ordinal family data is limited because the correlation structure of family data is more complex than for other types of clustered data. To perform these analyses we propose the non-proportional odds multivariate logistic regression model and take a simulation-based approach to model fitting using Markov chain Monte Carlo methods, such as partially collapsed Gibbs sampling and the Metropolis algorithm. We applied the proposed methodology to male pattern baldness data from the Victorian Family Heart Study. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PredictABEL: an R package for the assessment of risk prediction models.

PubMed

Kundu, Suman; Aulchenko, Yurii S; van Duijn, Cornelia M; Janssens, A Cecile J W

2011-04-01

The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL ( http://www.genabel.org ) and CRAN ( http://cran.r-project.org/).

Contributions of parental alcoholism, prenatal substance exposure, and genetic transmission to child ADHD risk: a female twin study.

PubMed

Knopik, Valerie S; Sparrow, Elizabeth P; Madden, Pamela A F; Bucholz, Kathleen K; Hudziak, James J; Reich, Wendy; Slutske, Wendy S; Grant, Julia D; McLaughlin, Tara L; Todorov, Alexandre; Todd, Richard D; Heath, Andrew C

2005-05-01

Genetic influences have been shown to play a major role in determining the risk of attention-deficit hyperactivity disorder (ADHD). In addition, prenatal exposure to nicotine and/or alcohol has also been suggested to increase risk of the disorder. Little attention, however, has been directed to investigating the roles of genetic transmission and prenatal exposure simultaneously. Diagnostic telephone interview data from parents of Missouri adolescent female twin pairs born during 1975-1985 were analyzed. Logistic regression models were fitted to interview data from a total of 1936 twin pairs (1091 MZ and 845 DZ pairs) to determine the relative contributions of parental smoking and drinking behavior (both during and outside of pregnancy) as risk factors for DSM-IV ADHD. Structural equation models were fitted to determine the extent of residual genetic and environmental influences on ADHD risk while controlling for effects of prenatal and parental predictors on risk. ADHD was more likely to be diagnosed in girls whose mothers or fathers were alcohol dependent, whose mothers reported heavy alcohol use during pregnancy, and in those with low birth weight. Controlling for other risk factors, risk was not significantly increased in those whose mothers smoked during pregnancy. After allowing for effects of prenatal and childhood predictors, 86% of the residual variance in ADHD risk was attributable to genetic effects and 14% to non-shared environmental influences. Prenatal and parental risk factors may not be important mediators of influences on risk with much of the association between these variables and ADHD appearing to be indirect.

Local area disadvantage and gambling involvement and disorder: Evidence for gene-environment correlation and interaction.

PubMed

Slutske, Wendy S; Deutsch, Arielle R; Statham, Dixie J; Martin, Nicholas G

2015-08-01

Previous research has demonstrated that local area characteristics (such as disadvantage and gambling outlet density) and genetic risk factors are associated with gambling involvement and disordered gambling. These 2 lines of research were brought together in the present study by examining the extent to which genetic contributions to individual differences in gambling involvement and disorder contributed to being exposed to, and were also accentuated by, local area disadvantage. Participants were members of the national community-based Australian Twin Registry who completed a telephone interview in which the past-year frequency of gambling and symptoms of disordered gambling were assessed. Indicators of local area disadvantage were based on census data matched to the participants' postal codes. Univariate biometric model-fitting revealed that exposure to area disadvantage was partially explained by genetic factors. Bivariate biometric model-fitting was conducted to examine the evidence for gene-environment interaction while accounting for gene-environment correlation. These analyses demonstrated that: (a) a small portion of the genetic propensity to gamble was explained by moving to or remaining in a disadvantaged area, and (b) the remaining genetic and unique environmental variation in the frequency of participating in electronic machine gambling (among men and women) and symptoms of disordered gambling (among women) was greater in more disadvantaged localities. As the gambling industry continues to grow, it will be important to take into account the multiple contexts in which problematic gambling behavior can emerge-from genes to geography-as well as the ways in which such contexts may interact with each other. (c) 2015 APA, all rights reserved).

Local Area Disadvantage and Gambling Involvement and Disorder: Evidence for Gene-Environment Correlation and Interaction

PubMed Central

Slutske, Wendy S.; Deutsch, Arielle R.; Statham, Dixie B.; Martin, Nicholas G.

2015-01-01

Previous research has demonstrated that local area characteristics (such as disadvantage and gambling outlet density) and genetic risk factors are associated with gambling involvement and disordered gambling. These two lines of research were brought together in the present study by examining the extent to which genetic contributions to individual differences in gambling involvement and disorder contributed to being exposed to, and were also accentuated by, local area disadvantage. Participants were members of the national community-based Australian Twin Registry who completed a telephone interview in which the past-year frequency of gambling and symptoms of disordered gambling were assessed. Indicators of local area disadvantage were based on census data matched to the participants' postal codes. Univariate biometric model-fitting revealed that exposure to area disadvantage was partially explained by genetic factors. Bivariate biometric model-fitting was conducted to examine the evidence for gene-environment interaction while accounting for gene-environment correlation. These analyses demonstrated that: (a) a small portion of the genetic propensity to gamble was explained by moving to or remaining in a disadvantaged area, and (b) the remaining genetic and unique environmental variation in the frequency of participating in electronic machine gambling (among men and women) and symptoms of disordered gambling (among women) was greater in more disadvantaged localities. As the gambling industry continues to grow, it will be important to take into account the multiple contexts in which problematic gambling behavior can emerge -- from genes to geography -- as well as the ways in which such contexts may interact with each other. PMID:26147321

The structure of genetic and environmental risk factors for phobias in women.

PubMed

Czajkowski, N; Kendler, K S; Tambs, K; Røysamb, E; Reichborn-Kjennerud, T

2011-09-01

To explore the genetic and environmental factors underlying the co-occurrence of lifetime diagnoses of DSM-IV phobia. Female twins (n=1430) from the population-based Norwegian Institute of Public Health Twin Panel were assessed at personal interview for DSM-IV lifetime specific phobia, social phobia and agoraphobia. Comorbidity between the phobias were assessed by odds ratios (ORs) and polychoric correlations and multivariate twin models were fitted in Mx. Phenotypic correlations of lifetime phobia diagnoses ranged from 0.55 (agoraphobia and social phobia, OR 10.95) to 0.06 (animal phobia and social phobia, OR 1.21). In the best fitting twin model, which did not include shared environmental factors, heritability estimates for the phobias ranged from 0.43 to 0.63. Comorbidity between the phobias was accounted for by two common liability factors. The first loaded principally on animal phobia and did not influence the complex phobias (agoraphobia and social phobia). The second liability factor strongly influenced the complex phobias, but also loaded weak to moderate on all the other phobias. Blood phobia was mainly influenced by a specific genetic factor, which accounted for 51% of the total and 81% of the genetic variance. Phobias are highly co-morbid and heritable. Our results suggest that the co-morbidity between phobias is best explained by two distinct liability factors rather than a single factor, as has been assumed in most previous multivariate twin analyses. One of these factors was specific to the simple phobias, while the other was more general. Blood phobia was mainly influenced by disorder specific genetic factors.

The structure of genetic and environmental risk factors for phobias in women

PubMed Central

Czajkowski, N.; Kendler, K. S.; Tambs, K.; Røysamb, E.; Reichborn-Kjennerud, T.

2011-01-01

Background To explore the genetic and environmental factors underlying the co-occurrence of lifetime diagnoses of DSM-IV phobia. Method Female twins (n = 1430) from the population-based Norwegian Institute of Public Health Twin Panel were assessed at personal interview for DSM-IV lifetime specific phobia, social phobia and agoraphobia. Comorbidity between the phobias were assessed by odds ratios (ORs) and polychoric correlations and multivariate twin models were fitted in Mx. Results Phenotypic correlations of lifetime phobia diagnoses ranged from 0.55 (agoraphobia and social phobia, OR 10.95) to 0.06 (animal phobia and social phobia, OR 1.21). In the best fitting twin model, which did not include shared environmental factors, heritability estimates for the phobias ranged from 0.43 to 0.63. Comorbidity between the phobias was accounted for by two common liability factors. The first loaded principally on animal phobia and did not influence the complex phobias (agoraphobia and social phobia). The second liability factor strongly influenced the complex phobias, but also loaded weak to moderate on all the other phobias. Blood phobia was mainly influenced by a specific genetic factor, which accounted for 51% of the total and 81% of the genetic variance. Conclusions Phobias are highly co-morbid and heritable. Our results suggest that the co-morbidity between phobias is best explained by two distinct liability factors rather than a single factor, as has been assumed in most previous multivariate twin analyses. One of these factors was specific to the simple phobias, while the other was more general. Blood phobia was mainly influenced by disorder specific genetic factors. PMID:21211096

I think, therefore I am: a twin study of attributional style in adolescents.

PubMed

Lau, Jennifer Y F; Rijsdijk, Frühling; Eley, Thalia C

2006-07-01

Parenting factors may be important to the development of attributional style in adolescence, which in turn relates to depression symptoms. These relationships have mainly been considered in terms of social risk mechanisms, and little is known about the role of genetic influences. Self-reported measures of attributional style, depression symptoms and parental disciplinary styles were administered to over 1300 adolescent twin and sibling pairs. Model-fitting techniques were used to examine the role of genetic and environmental influences. Moderate genetic influences on attributional style were demonstrated, and furthermore, its association with depression reflected considerable genetic effects. Familial factors were implicated in the association between attributional style and punitive parenting, although genetic from shared environmental causes could not be distinguished. Our results demonstrate that attributional style is influenced by genetic, as well as social factors. Implications for aetiological pathways integrating cognitive, genetic and social factors on adolescent depression are discussed.

Phenotypic and genetic associations between the big five and trait emotional intelligence.

PubMed

Vernon, Philip A; Villani, Vanessa C; Schermer, Julie Aitken; Petrides, K V

2008-10-01

This study reports the first behavioral genetic investigation of the extent to which genetic and/or environmental factors contribute to the relationship between the Big Five personality factors and trait emotional intelligence. 213 pairs of adult monozygotic twins and 103 pairs of same-sex dizygotic twins completed the NEO-PI-R and the Trait Emotional Intelligence Questionnaire (TEIQue). Replicating previous non-twin studies, many significant phenotypic correlations were found between the Big Five factors - especially Neuroticism, Extraversion, and Conscientiousness - and the facets, factors, and global scores derived from the TEIQue. Bivariate behavioral genetic model-fitting analyses revealed that these phenotypic correlations were primarily attributable to correlated genetic factors and secondarily to correlated non-shared environmental factors. The results support the feasibility of incorporating EI as a trait within existing personality taxonomies.

[The importance of physical activity and fitness for human health].

PubMed

Brandes, M

2012-01-01

The decline of physical activity is considered to play an important role in the deterioration of health predictors, such as overweight, and the associated increase of cardiovascular and all-cause mortality. Therefore, most interventional strategies aim for increasing physical activity. Instead of physical activity, some studies use physical fitness as a key variable. Though physical fitness is influenced by genetic factors, physical fitness has to be developed by physical activity. As recent reports demonstrate the prospective associations between physical fitness and health and mortality, these associations are not reported for physical activity. Due to the fact that physical fitness-in contrast to physical activity-is evaluated with standardized laboratory measurements, it appears advisable to assess physical fitness for prospective health perspectives. Although physical fitness is determined by genetics, physical activity is the primary modifiable determinant for increasing physical fitness and should be aimed for to improve physical fitness in interventional strategies.

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

The effect of level of feeding, genetic merit, body condition score and age on biological parameters of a mammary gland model.

PubMed

Bryant, J R; Lopez-Villalobos, N; Holmes, C W; Pryce, J E; Pitman, G D; Davis, S R

2007-03-01

An evolutionary algorithm was applied to a mechanistic model of the mammary gland to find the parameter values that minimised the difference between predicted and actual lactation curves of milk yields in New Zealand Jersey cattle managed at different feeding levels. The effect of feeding level, genetic merit, body condition score at parturition and age on total lactation yields of milk, fat and protein, days in milk, live weight and evolutionary algorithm derived mammary gland parameters was then determined using a multiple regression model. The mechanistic model of the mammary gland was able to fit lactation curves that corresponded to actual lactation curves with a high degree of accuracy. The senescence rate of quiescent (inactive) alveoli was highest at the very low feeding level. The active alveoli population at peak lactation was highest at very low feeding levels, but lower nutritional status at this feeding level prevented high milk yields from being achieved. Genetic merit had a significant linear effect on the active alveoli population at peak and mid to late lactation, with higher values in animals, which had higher breeding values for milk yields. A type of genetic merit × feeding level scaling effect was observed for total yields of milk and fat, and total number of alveoli produced from conception until the end of lactation with the benefits of increases in genetic merit being greater at high feeding levels. A genetic merit × age scaling effect was observed for total lactation protein yields. Initial rates of differentiation of progenitor cells declined with age. Production levels of alveoli from conception to the end of lactation were lowest in 5- to 8-year-old animals; however, in these older animals, quiescent alveoli were reactivated more frequently. The active alveoli population at peak lactation and rates of active alveoli proceeding to quiescence were highest in animals of intermediate body condition scores of 4.0 to 5.0. The results illustrate the potential uses of a mechanistic model of the mammary gland to fit a lactation curve and to quantify the effects of feeding level, genetic merit, body condition score, and age on mammary gland dynamics throughout lactation.

The use (or misuse) of microsatellite allelic distances in the context of inbreeding and conservation genetics.

PubMed

Hansson, Bengt

2010-03-01

In line with inbreeding theory, genetic diversity at a set of molecular markers may explain variation in fitness-associated traits in partially inbred populations, and such associations will appear as 'genotype-fitness correlations'. An individual genetic diversity index specifically used for microsatellites is 'mean d(2)', i.e. the mean squared distance between alleles. The original hypothesis for mean d(2)-fitness correlations assumes that mean d(2) captures fitness effects at both ends of the inbreeding-outbreeding spectrum. This hypothesis received strong criticism from work showing that even a plain diversity estimate such as multi-locus heterozygosity (MLH) outperforms mean d(2) as a predictor of the inbreeding coefficient and fitness in most realistic situations. Despite this critique, the mean d(2)-approach is still used frequently in ecological and evolutionary research, producing results suggesting that mean d(2) sometimes provides a stronger prediction of fitness than does MLH. In light of the critique, such results are unexpected, but potential explanations for them may exist (at least hypothetically), including scenarios based on close linkage and recent admixture. Nevertheless, a major caveat is that it is very difficult to predict a priori if mean d(2) will improve the genotype-fitness correlation, which in turn makes objective interpretations difficult. Mean d(2)-fitness associations are potentially interesting, but the fact that we cannot easily understand them is problematic and should be thoroughly addressed in each study. Therefore, instead of hastily reached interpretations of mean d(2)-fitness correlations, conclusions need support from complementary analyses, e.g. verifying admixture of genetically structured populations.

The genetic correlation between height and IQ: shared genes or assortative mating?

PubMed

Keller, Matthew C; Garver-Apgar, Christine E; Wright, Margaret J; Martin, Nicholas G; Corley, Robin P; Stallings, Michael C; Hewitt, John K; Zietsch, Brendan P

2013-04-01

Traits that are attractive to the opposite sex are often positively correlated when scaled such that scores increase with attractiveness, and this correlation typically has a genetic component. Such traits can be genetically correlated due to genes that affect both traits ("pleiotropy") and/or because assortative mating causes statistical correlations to develop between selected alleles across the traits ("gametic phase disequilibrium"). In this study, we modeled the covariation between monozygotic and dizygotic twins, their siblings, and their parents (total N = 7,905) to elucidate the nature of the correlation between two potentially sexually selected traits in humans: height and IQ. Unlike previous designs used to investigate the nature of the height-IQ correlation, the present design accounts for the effects of assortative mating and provides much less biased estimates of additive genetic, non-additive genetic, and shared environmental influences. Both traits were highly heritable, although there was greater evidence for non-additive genetic effects in males. After accounting for assortative mating, the correlation between height and IQ was found to be almost entirely genetic in nature. Model fits indicate that both pleiotropy and assortative mating contribute significantly and about equally to this genetic correlation.

Genetic pleiotropy explains associations between musical auditory discrimination and intelligence.

PubMed

Mosing, Miriam A; Pedersen, Nancy L; Madison, Guy; Ullén, Fredrik

2014-01-01

Musical aptitude is commonly measured using tasks that involve discrimination of different types of musical auditory stimuli. Performance on such different discrimination tasks correlates positively with each other and with intelligence. However, no study to date has explored these associations using a genetically informative sample to estimate underlying genetic and environmental influences. In the present study, a large sample of Swedish twins (N = 10,500) was used to investigate the genetic architecture of the associations between intelligence and performance on three musical auditory discrimination tasks (rhythm, melody and pitch). Phenotypic correlations between the tasks ranged between 0.23 and 0.42 (Pearson r values). Genetic modelling showed that the covariation between the variables could be explained by shared genetic influences. Neither shared, nor non-shared environment had a significant effect on the associations. Good fit was obtained with a two-factor model where one underlying shared genetic factor explained all the covariation between the musical discrimination tasks and IQ, and a second genetic factor explained variance exclusively shared among the discrimination tasks. The results suggest that positive correlations among musical aptitudes result from both genes with broad effects on cognition, and genes with potentially more specific influences on auditory functions.

Genetic Pleiotropy Explains Associations between Musical Auditory Discrimination and Intelligence

PubMed Central

Mosing, Miriam A.; Pedersen, Nancy L.; Madison, Guy; Ullén, Fredrik

2014-01-01

Musical aptitude is commonly measured using tasks that involve discrimination of different types of musical auditory stimuli. Performance on such different discrimination tasks correlates positively with each other and with intelligence. However, no study to date has explored these associations using a genetically informative sample to estimate underlying genetic and environmental influences. In the present study, a large sample of Swedish twins (N = 10,500) was used to investigate the genetic architecture of the associations between intelligence and performance on three musical auditory discrimination tasks (rhythm, melody and pitch). Phenotypic correlations between the tasks ranged between 0.23 and 0.42 (Pearson r values). Genetic modelling showed that the covariation between the variables could be explained by shared genetic influences. Neither shared, nor non-shared environment had a significant effect on the associations. Good fit was obtained with a two-factor model where one underlying shared genetic factor explained all the covariation between the musical discrimination tasks and IQ, and a second genetic factor explained variance exclusively shared among the discrimination tasks. The results suggest that positive correlations among musical aptitudes result from both genes with broad effects on cognition, and genes with potentially more specific influences on auditory functions. PMID:25419664

A Study of Two Instructional Sequences Informed by Alternative Learning Progressions in Genetics

NASA Astrophysics Data System (ADS)

Duncan, Ravit Golan; Choi, Jinnie; Castro-Faix, Moraima; Cavera, Veronica L.

2017-12-01

Learning progressions (LPs) are hypothetical models of how learning in a domain develops over time with appropriate instruction. In the domain of genetics, there are two independently developed alternative LPs. The main difference between the two progressions hinges on their assumptions regarding the accessibility of classical (Mendelian) versus molecular genetics and the order in which they should be taught. In order to determine the relative difficulty of the different genetic ideas included in the two progressions, and to test which one is a better fit with students' actual learning, we developed two modules in classical and molecular genetics and alternated their sequence in an implementation study with 11th grade students studying biology. We developed a set of 56 ordered multiple-choice items that collectively assessed both molecular and classical genetic ideas. We found significant gains in students' learning in both molecular and classical genetics, with the largest gain relating to understanding the informational content of genes and the smallest gain in understanding modes of inheritance. Using multidimensional item response modeling, we found no statistically significant differences between the two instructional sequences. However, there was a trend of slightly higher gains for the molecular-first sequence for all genetic ideas.

Glyphosate drift promotes changes in fitness and transgene flow in canola (Brassica napus) and hybrids

EPA Science Inventory

1. With the advent of transgenic crops, genetically modified, herbicide resistant B. napus has become a model system for examining the risks of escape of transgenes from cultivation and for evaluating potential ecological consequences of novel genes in wild species. 2. We exam...

Selfish genetic elements and the gene’s-eye view of evolution

PubMed Central

2016-01-01

During the last few decades, we have seen an explosion in the influx of details about the biology of selfish genetic elements. Ever since the early days of the field, the gene’s-eye view of Richard Dawkins, George Williams, and others, has been instrumental to make sense of new empirical observations and to the generation of new hypotheses. However, the close association between selfish genetic elements and the gene’s-eye view has not been without critics and several other conceptual frameworks have been suggested. In particular, proponents of multilevel selection models have used selfish genetic elements to criticize the gene’s-eye view. In this paper, I first trace the intertwined histories of the study of selfish genetic elements and the gene’s-eye view and then discuss how their association holds up when compared with other proposed frameworks. Next, using examples from transposable elements and the major transitions, I argue that different models highlight separate aspects of the evolution of selfish genetic elements and that the productive way forward is to maintain a plurality of perspectives. Finally, I discuss how the empirical study of selfish genetic elements has implications for other conceptual issues associated with the gene’s-eye view, such as agential thinking, adaptationism, and the role of fitness maximizing models in evolution. PMID:29491953

Support from the relationship of genetic and geographic distance in human populations for a serial founder effect originating in Africa

PubMed Central

Ramachandran, Sohini; Deshpande, Omkar; Roseman, Charles C.; Rosenberg, Noah A.; Feldman, Marcus W.; Cavalli-Sforza, L. Luca

2005-01-01

Equilibrium models of isolation by distance predict an increase in genetic differentiation with geographic distance. Here we find a linear relationship between genetic and geographic distance in a worldwide sample of human populations, with major deviations from the fitted line explicable by admixture or extreme isolation. A close relationship is shown to exist between the correlation of geographic distance and genetic differentiation (as measured by FST) and the geographic pattern of heterozygosity across populations. Considering a worldwide set of geographic locations as possible sources of the human expansion, we find that heterozygosities in the globally distributed populations of the data set are best explained by an expansion originating in Africa and that no geographic origin outside of Africa accounts as well for the observed patterns of genetic diversity. Although the relationship between FST and geographic distance has been interpreted in the past as the result of an equilibrium model of drift and dispersal, simulation shows that the geographic pattern of heterozygosities in this data set is consistent with a model of a serial founder effect starting at a single origin. Given this serial-founder scenario, the relationship between genetic and geographic distance allows us to derive bounds for the effects of drift and natural selection on human genetic variation. PMID:16243969

The influence of inherited plumage colour morph on morphometric traits and breeding investment in zebra finches (Taeniopygia guttata).

PubMed

Krause, E Tobias; Krüger, Oliver; Hoffman, Joseph I

2017-01-01

Melanin-based plumage polymorphism occurs in many wild bird populations and has been linked to fitness variation in several species. These fitness differences often arise as a consequence of variation in traits such as behaviour, immune responsiveness, body size and reproductive investment. However, few studies have controlled for genetic differences between colour morphs that could potentially generate artefactual associations between plumage colouration and trait variation. Here, we used zebra finches (Taeniopygia guttata) as a model system in order to evaluate whether life-history traits such as adult body condition and reproductive investment could be influenced by plumage morph. To maximise any potential differences, we selected wild-type and white plumage morphs, which differ maximally in their extent of melanisation, while using a controlled three-generation breeding design to homogenise the genetic background. We found that F2 adults with white plumage colouration were on average lighter and had poorer body condition than wild-type F2 birds. However, they appeared to compensate for this by reproducing earlier and producing heavier eggs relative to their own body mass. Our study thus reveals differences in morphological and life history traits that could be relevant to fitness variation, although further studies will be required to evaluate fitness effects under natural conditions as well as to characterise any potential fitness costs of compensatory strategies in white zebra finches.

The influence of inherited plumage colour morph on morphometric traits and breeding investment in zebra finches (Taeniopygia guttata)

PubMed Central

Krüger, Oliver

2017-01-01

Melanin-based plumage polymorphism occurs in many wild bird populations and has been linked to fitness variation in several species. These fitness differences often arise as a consequence of variation in traits such as behaviour, immune responsiveness, body size and reproductive investment. However, few studies have controlled for genetic differences between colour morphs that could potentially generate artefactual associations between plumage colouration and trait variation. Here, we used zebra finches (Taeniopygia guttata) as a model system in order to evaluate whether life-history traits such as adult body condition and reproductive investment could be influenced by plumage morph. To maximise any potential differences, we selected wild-type and white plumage morphs, which differ maximally in their extent of melanisation, while using a controlled three-generation breeding design to homogenise the genetic background. We found that F2 adults with white plumage colouration were on average lighter and had poorer body condition than wild-type F2 birds. However, they appeared to compensate for this by reproducing earlier and producing heavier eggs relative to their own body mass. Our study thus reveals differences in morphological and life history traits that could be relevant to fitness variation, although further studies will be required to evaluate fitness effects under natural conditions as well as to characterise any potential fitness costs of compensatory strategies in white zebra finches. PMID:29190647

Evolution of haploid-diploid life cycles when haploid and diploid fitnesses are not equal.

PubMed

Scott, Michael F; Rescan, Marie

2017-02-01

Many organisms spend a significant portion of their life cycle as haploids and as diploids (a haploid-diploid life cycle). However, the evolutionary processes that could maintain this sort of life cycle are unclear. Most previous models of ploidy evolution have assumed that the fitness effects of new mutations are equal in haploids and homozygous diploids, however, this equivalency is not supported by empirical data. With different mutational effects, the overall (intrinsic) fitness of a haploid would not be equal to that of a diploid after a series of substitution events. Intrinsic fitness differences between haploids and diploids can also arise directly, for example because diploids tend to have larger cell sizes than haploids. Here, we incorporate intrinsic fitness differences into genetic models for the evolution of time spent in the haploid versus diploid phases, in which ploidy affects whether new mutations are masked. Life-cycle evolution can be affected by intrinsic fitness differences between phases, the masking of mutations, or a combination of both. We find parameter ranges where these two selective forces act and show that the balance between them can favor convergence on a haploid-diploid life cycle, which is not observed in the absence of intrinsic fitness differences. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

High intraspecific genome diversity in the model arbuscular mycorrhizal symbiont Rhizophagus irregularis.

PubMed

Chen, Eric C H; Morin, Emmanuelle; Beaudet, Denis; Noel, Jessica; Yildirir, Gokalp; Ndikumana, Steve; Charron, Philippe; St-Onge, Camille; Giorgi, John; Krüger, Manuela; Marton, Timea; Ropars, Jeanne; Grigoriev, Igor V; Hainaut, Matthieu; Henrissat, Bernard; Roux, Christophe; Martin, Francis; Corradi, Nicolas

2018-01-22

Arbuscular mycorrhizal fungi (AMF) are known to improve plant fitness through the establishment of mycorrhizal symbioses. Genetic and phenotypic variations among closely related AMF isolates can significantly affect plant growth, but the genomic changes underlying this variability are unclear. To address this issue, we improved the genome assembly and gene annotation of the model strain Rhizophagus irregularis DAOM197198, and compared its gene content with five isolates of R. irregularis sampled in the same field. All isolates harbor striking genome variations, with large numbers of isolate-specific genes, gene family expansions, and evidence of interisolate genetic exchange. The observed variability affects all gene ontology terms and PFAM protein domains, as well as putative mycorrhiza-induced small secreted effector-like proteins and other symbiosis differentially expressed genes. High variability is also found in active transposable elements. Overall, these findings indicate a substantial divergence in the functioning capacity of isolates harvested from the same field, and thus their genetic potential for adaptation to biotic and abiotic changes. Our data also provide a first glimpse into the genome diversity that resides within natural populations of these symbionts, and open avenues for future analyses of plant-AMF interactions that link AMF genome variation with plant phenotype and fitness. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Influenza virus drug resistance: a time-sampled population genetics perspective.

PubMed

Foll, Matthieu; Poh, Yu-Ping; Renzette, Nicholas; Ferrer-Admetlla, Anna; Bank, Claudia; Shim, Hyunjin; Malaspinas, Anna-Sapfo; Ewing, Gregory; Liu, Ping; Wegmann, Daniel; Caffrey, Daniel R; Zeldovich, Konstantin B; Bolon, Daniel N; Wang, Jennifer P; Kowalik, Timothy F; Schiffer, Celia A; Finberg, Robert W; Jensen, Jeffrey D

2014-02-01

The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence of drug treatment. Importantly, these approaches re-identify the known oseltamivir resistance site, successfully validating the approaches used. Enticingly, a number of previously unknown variants have also been identified as being positively selected. Results are interpreted in the light of Fisher's Geometric Model, allowing for a quantification of the increased distance to optimum exerted by the presence of drug, and theoretical predictions regarding the distribution of beneficial fitness effects of contending mutations are empirically tested. Further, given the fit to expectations of the Geometric Model, results suggest the ability to predict certain aspects of viral evolution in response to changing host environments and novel selective pressures.

Condition-dependence, genotype-by-environment interactions and the lek paradox.

PubMed

Kokko, Hanna; Heubel, Katja

2008-09-01

The lek paradox states that maintaining genetic variation necessary for 'indirect benefit' models of female choice is difficult, and two interrelated solutions have been proposed. 'Genic capture' assumes condition-dependence of sexual traits, while genotype-by-environment interactions (GEIs) offer an additional way to maintain diversity. However, condition-dependence, particularly with GEIs, implies that environmental variation can blur the relationship between male displays and offspring fitness. These issues have been treated separately in the past. Here we combine them in a population genetic model, and show that predictions change not only in magnitude but also in direction when the timing of dispersal between environments relative to the life cycle is changed. GEIs can dramatically improve the evolution of costly female preferences, but also hamper it if much dispersal occurs between the life history stage where condition is determined and mating. This situation also arises if selection or mutation rates are too high. In general, our results highlight that when evaluating any mechanism promoted as a potential resolution of the lek paradox, it is not sufficient to focus on its effects on genetic variation. It also has to be assessed to what extent the proposed mechanism blurs the association between male attractiveness and offspring fitness; the net balance of these two effects can be positive or negative, and often strongly context-dependent.

Condition-dependence, genotype-by-environment interactions and the lek paradox.

PubMed

Kokko, Hanna; Heubel, Katja

2008-02-01

The lek paradox states that maintaining genetic variation necessary for 'indirect benefit' models of female choice is difficult, and two interrelated solutions have been proposed. 'Genic capture' assumes condition-dependence of sexual traits, while genotype-by-environment interactions (GEIs) offer an additional way to maintain diversity. However, condition-dependence, particularly with GEIs, implies that environmental variation can blur the relationship between male displays and offspring fitness. These issues have been treated separately in the past. Here we combine them in a population genetic model, and show that predictions change not only in magnitude but also in direction when the timing of dispersal between environments relative to the life cycle is changed. GEIs can dramatically improve the evolution of costly female preferences, but also hamper it if much dispersal occurs between the life history stage where condition is determined and mating. This situation also arises if selection or mutation rates are too high. In general, our results highlight that when evaluating any mechanism promoted as a potential resolution of the lek paradox, it is not sufficient to focus on its effects on genetic variation. It also has to be assessed to what extent the proposed mechanism blurs the association between male attractiveness and offspring fitness; the net balance of these two effects can be positive or negative, and often strongly context-dependent.

Genetic and Environmental Influences on Pubertal Development: Longitudinal Data from Finnish Twins at Ages 11 and 14

ERIC Educational Resources Information Center

Mustanski, Brian S.; Viken, Richard J.; Kaprio, Jaakko; Pulkkinen, Lea; Rose, Richard J.

2004-01-01

To study sources of individual differences in pubertal development, the authors fit a sex-limitation common factor model to data reported, at ages 11 and 14 years, by 1,891 twin pairs on items that comprise the Pubertal Development Scale (PDS; A. C. Petersen, L. Crockett, M. Richards, & A. Boxer, 1988). The model divides variation into a general…

Effects of Genetic Drift and Gene Flow on the Selective Maintenance of Genetic Variation

PubMed Central

Star, Bastiaan; Spencer, Hamish G.

2013-01-01

Explanations for the genetic variation ubiquitous in natural populations are often classified by the population–genetic processes they emphasize: natural selection or mutation and genetic drift. Here we investigate models that incorporate all three processes in a spatially structured population, using what we call a construction approach, simulating finite populations under selection that are bombarded with a steady stream of novel mutations. As expected, the amount of genetic variation compared to previous models that ignored the stochastic effects of drift was reduced, especially for smaller populations and when spatial structure was most profound. By contrast, however, for higher levels of gene flow and larger population sizes, the amount of genetic variation found after many generations was greater than that in simulations without drift. This increased amount of genetic variation is due to the introduction of slightly deleterious alleles by genetic drift and this process is more efficient when migration load is higher. The incorporation of genetic drift also selects for fitness sets that exhibit allele-frequency equilibria with larger domains of attraction: they are “more stable.” Moreover, the finiteness of populations strongly influences levels of local adaptation, selection strength, and the proportion of allele-frequency vectors that can be distinguished from the neutral expectation. PMID:23457235

Predicting the evolution of sex on complex fitness landscapes.

PubMed

Misevic, Dusan; Kouyos, Roger D; Bonhoeffer, Sebastian

2009-09-01

Most population genetic theories on the evolution of sex or recombination are based on fairly restrictive assumptions about the nature of the underlying fitness landscapes. Here we use computer simulations to study the evolution of sex on fitness landscapes with different degrees of complexity and epistasis. We evaluate predictors of the evolution of sex, which are derived from the conditions established in the population genetic literature for the evolution of sex on simpler fitness landscapes. These predictors are based on quantities such as the variance of Hamming distance, mean fitness, additive genetic variance, and epistasis. We show that for complex fitness landscapes all the predictors generally perform poorly. Interestingly, while the simplest predictor, Delta Var(HD), also suffers from a lack of accuracy, it turns out to be the most robust across different types of fitness landscapes. Delta Var(HD) is based on the change in Hamming distance variance induced by recombination and thus does not require individual fitness measurements. The presence of loci that are not under selection can, however, severely diminish predictor accuracy. Our study thus highlights the difficulty of establishing reliable criteria for the evolution of sex on complex fitness landscapes and illustrates the challenge for both theoretical and experimental research on the origin and maintenance of sexual reproduction.

Predicting the Evolution of Sex on Complex Fitness Landscapes

PubMed Central

Misevic, Dusan; Kouyos, Roger D.; Bonhoeffer, Sebastian

2009-01-01

Most population genetic theories on the evolution of sex or recombination are based on fairly restrictive assumptions about the nature of the underlying fitness landscapes. Here we use computer simulations to study the evolution of sex on fitness landscapes with different degrees of complexity and epistasis. We evaluate predictors of the evolution of sex, which are derived from the conditions established in the population genetic literature for the evolution of sex on simpler fitness landscapes. These predictors are based on quantities such as the variance of Hamming distance, mean fitness, additive genetic variance, and epistasis. We show that for complex fitness landscapes all the predictors generally perform poorly. Interestingly, while the simplest predictor, ΔVarHD, also suffers from a lack of accuracy, it turns out to be the most robust across different types of fitness landscapes. ΔVarHD is based on the change in Hamming distance variance induced by recombination and thus does not require individual fitness measurements. The presence of loci that are not under selection can, however, severely diminish predictor accuracy. Our study thus highlights the difficulty of establishing reliable criteria for the evolution of sex on complex fitness landscapes and illustrates the challenge for both theoretical and experimental research on the origin and maintenance of sexual reproduction. PMID:19763171

A fitness cost associated with the antibiotic resistance enzyme SME-1 beta-lactamase.

PubMed

Marciano, David C; Karkouti, Omid Y; Palzkill, Timothy

2007-08-01

The bla(TEM-1) beta-lactamase gene has become widespread due to the selective pressure of beta-lactam use and its stable maintenance on transferable DNA elements. In contrast, bla(SME-1) is rarely isolated and is confined to the chromosome of carbapenem-resistant Serratia marcescens strains. Dissemination of bla(SME-1) via transfer to a mobile DNA element could hinder the use of carbapenems. In this study, bla(SME-1) was determined to impart a fitness cost upon Escherichia coli in multiple genetic contexts and assays. Genetic screens and designed SME-1 mutants were utilized to identify the source of this fitness cost. These experiments established that the SME-1 protein was required for the fitness cost but also that the enzyme activity of SME-1 was not associated with the fitness cost. The genetic screens suggested that the SME-1 signal sequence was involved in the fitness cost. Consistent with these findings, exchange of the SME-1 signal sequence for the TEM-1 signal sequence alleviated the fitness cost while replacing the TEM-1 signal sequence with the SME-1 signal sequence imparted a fitness cost to TEM-1 beta-lactamase. Taken together, these results suggest that fitness costs associated with some beta-lactamases may limit their dissemination.

A Fitness Cost Associated With the Antibiotic Resistance Enzyme SME-1 β-Lactamase

PubMed Central

Marciano, David C.; Karkouti, Omid Y.; Palzkill, Timothy

2007-01-01

The blaTEM-1 β-lactamase gene has become widespread due to the selective pressure of β-lactam use and its stable maintenance on transferable DNA elements. In contrast, blaSME-1 is rarely isolated and is confined to the chromosome of carbapenem-resistant Serratia marcescens strains. Dissemination of blaSME-1 via transfer to a mobile DNA element could hinder the use of carbapenems. In this study, blaSME-1 was determined to impart a fitness cost upon Escherichia coli in multiple genetic contexts and assays. Genetic screens and designed SME-1 mutants were utilized to identify the source of this fitness cost. These experiments established that the SME-1 protein was required for the fitness cost but also that the enzyme activity of SME-1 was not associated with the fitness cost. The genetic screens suggested that the SME-1 signal sequence was involved in the fitness cost. Consistent with these findings, exchange of the SME-1 signal sequence for the TEM-1 signal sequence alleviated the fitness cost while replacing the TEM-1 signal sequence with the SME-1 signal sequence imparted a fitness cost to TEM-1 β-lactamase. Taken together, these results suggest that fitness costs associated with some β-lactamases may limit their dissemination. PMID:17565956

Possible roles of mechanical cell elimination intrinsic to growing tissues from the perspective of tissue growth efficiency and homeostasis.

PubMed

Lee, Sang-Woo; Morishita, Yoshihiro

2017-07-01

Cell competition is a phenomenon originally described as the competition between cell populations with different genetic backgrounds; losing cells with lower fitness are eliminated. With the progress in identification of related molecules, some reports described the relevance of cell mechanics during elimination. Furthermore, recent live imaging studies have shown that even in tissues composed of genetically identical cells, a non-negligible number of cells are eliminated during growth. Thus, mechanical cell elimination (MCE) as a consequence of mechanical cellular interactions is an unavoidable event in growing tissues and a commonly observed phenomenon. Here, we studied MCE in a genetically-homogeneous tissue from the perspective of tissue growth efficiency and homeostasis. First, we propose two quantitative measures, cell and tissue fitness, to evaluate cellular competitiveness and tissue growth efficiency, respectively. By mechanical tissue simulation in a pure population where all cells have the same mechanical traits, we clarified the dependence of cell elimination rate or cell fitness on different mechanical/growth parameters. In particular, we found that geometrical (specifically, cell size) and mechanical (stress magnitude) heterogeneities are common determinants of the elimination rate. Based on these results, we propose possible mechanical feedback mechanisms that could improve tissue growth efficiency and density/stress homeostasis. Moreover, when cells with different mechanical traits are mixed (e.g., in the presence of phenotypic variation), we show that MCE could drive a drastic shift in cell trait distribution, thereby improving tissue growth efficiency through the selection of cellular traits, i.e. intra-tissue "evolution". Along with the improvement of growth efficiency, cell density, stress state, and phenotype (mechanical traits) were also shown to be homogenized through growth. More theoretically, we propose a mathematical model that approximates cell competition dynamics, by which the time evolution of tissue fitness and cellular trait distribution can be predicted without directly simulating a cell-based mechanical model.

Possible roles of mechanical cell elimination intrinsic to growing tissues from the perspective of tissue growth efficiency and homeostasis

PubMed Central

2017-01-01

Cell competition is a phenomenon originally described as the competition between cell populations with different genetic backgrounds; losing cells with lower fitness are eliminated. With the progress in identification of related molecules, some reports described the relevance of cell mechanics during elimination. Furthermore, recent live imaging studies have shown that even in tissues composed of genetically identical cells, a non-negligible number of cells are eliminated during growth. Thus, mechanical cell elimination (MCE) as a consequence of mechanical cellular interactions is an unavoidable event in growing tissues and a commonly observed phenomenon. Here, we studied MCE in a genetically-homogeneous tissue from the perspective of tissue growth efficiency and homeostasis. First, we propose two quantitative measures, cell and tissue fitness, to evaluate cellular competitiveness and tissue growth efficiency, respectively. By mechanical tissue simulation in a pure population where all cells have the same mechanical traits, we clarified the dependence of cell elimination rate or cell fitness on different mechanical/growth parameters. In particular, we found that geometrical (specifically, cell size) and mechanical (stress magnitude) heterogeneities are common determinants of the elimination rate. Based on these results, we propose possible mechanical feedback mechanisms that could improve tissue growth efficiency and density/stress homeostasis. Moreover, when cells with different mechanical traits are mixed (e.g., in the presence of phenotypic variation), we show that MCE could drive a drastic shift in cell trait distribution, thereby improving tissue growth efficiency through the selection of cellular traits, i.e. intra-tissue “evolution”. Along with the improvement of growth efficiency, cell density, stress state, and phenotype (mechanical traits) were also shown to be homogenized through growth. More theoretically, we propose a mathematical model that approximates cell competition dynamics, by which the time evolution of tissue fitness and cellular trait distribution can be predicted without directly simulating a cell-based mechanical model. PMID:28704373

Early life stages contribute strongly to local adaptation in Arabidopsis thaliana.

PubMed

Postma, Froukje M; Ågren, Jon

2016-07-05

The magnitude and genetic basis of local adaptation is of fundamental interest in evolutionary biology. However, field experiments usually do not consider early life stages, and therefore may underestimate local adaptation and miss genetically based tradeoffs. We examined the contribution of differences in seedling establishment to adaptive differentiation and the genetic architecture of local adaptation using recombinant inbred lines (RIL) derived from a cross between two locally adapted populations (Italy and Sweden) of the annual plant Arabidopsis thaliana We planted freshly matured, dormant seeds (>180 000) representing >200 RILs at the native field sites of the parental genotypes, estimated the strength of selection during different life stages, mapped quantitative trait loci (QTL) for fitness and its components, and quantified selection on seed dormancy. We found that selection during the seedling establishment phase contributed strongly to the fitness advantage of the local genotype at both sites. With one exception, local alleles of the eight distinct establishment QTL were favored. The major QTL for establishment and total fitness showed evidence of a fitness tradeoff and was located in the same region as the major seed dormancy QTL and the dormancy gene DELAY OF GERMINATION 1 (DOG1). RIL seed dormancy could explain variation in seedling establishment and fitness across the life cycle. Our results demonstrate that genetically based differences in traits affecting performance during early life stages can contribute strongly to adaptive differentiation and genetic tradeoffs, and should be considered for a full understanding of the ecology and genetics of local adaptation.

Genetic variation in adaptability and pleiotropy in budding yeast

PubMed Central

Mitchell, James Kameron; Bloom, Joshua S; Kruglyak, Leonid

2017-01-01

Evolution can favor organisms that are more adaptable, provided that genetic variation in adaptability exists. Here, we quantify this variation among 230 offspring of a cross between diverged yeast strains. We measure the adaptability of each offspring genotype, defined as its average rate of adaptation in a specific environmental condition, and analyze the heritability, predictability, and genetic basis of this trait. We find that initial genotype strongly affects adaptability and can alter the genetic basis of future evolution. Initial genotype also affects the pleiotropic consequences of adaptation for fitness in a different environment. This genetic variation in adaptability and pleiotropy is largely determined by initial fitness, according to a rule of declining adaptability with increasing initial fitness, but several individual QTLs also have a significant idiosyncratic role. Our results demonstrate that both adaptability and pleiotropy are complex traits, with extensive heritable differences arising from naturally occurring variation. PMID:28826486

Genetic variation in adaptability and pleiotropy in budding yeast.

PubMed

Jerison, Elizabeth R; Kryazhimskiy, Sergey; Mitchell, James Kameron; Bloom, Joshua S; Kruglyak, Leonid; Desai, Michael M

2017-08-17

Evolution can favor organisms that are more adaptable, provided that genetic variation in adaptability exists. Here, we quantify this variation among 230 offspring of a cross between diverged yeast strains. We measure the adaptability of each offspring genotype, defined as its average rate of adaptation in a specific environmental condition, and analyze the heritability, predictability, and genetic basis of this trait. We find that initial genotype strongly affects adaptability and can alter the genetic basis of future evolution. Initial genotype also affects the pleiotropic consequences of adaptation for fitness in a different environment. This genetic variation in adaptability and pleiotropy is largely determined by initial fitness, according to a rule of declining adaptability with increasing initial fitness, but several individual QTLs also have a significant idiosyncratic role. Our results demonstrate that both adaptability and pleiotropy are complex traits, with extensive heritable differences arising from naturally occurring variation.

GASAKe: forecasting landslide activations by a genetic-algorithms based hydrological model

NASA Astrophysics Data System (ADS)

Terranova, O. G.; Gariano, S. L.; Iaquinta, P.; Iovine, G. G. R.

2015-02-01

GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is based on genetic-algorithms and allows to obtaining thresholds of landslide activation from the set of historical occurrences and from the rainfall series. GASAKe can be applied to either single landslides or set of similar slope movements in a homogeneous environment. Calibration of the model is based on genetic-algorithms, and provides for families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting from these latter, the corresponding mobility functions (i.e. the predictive tools) can be obtained through convolution with the rain series. The base time of the kernel is related to the magnitude of the considered slope movement, as well as to hydro-geological complexity of the site. Generally, smaller values are expected for shallow slope instabilities with respect to large-scale phenomena. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing recorded or forecasted rainfall series. Example of application of GASAKe to a medium-scale slope movement (the Uncino landslide at San Fili, in Calabria, Southern Italy) and to a set of shallow landslides (in the Sorrento Peninsula, Campania, Southern Italy) are discussed. In both cases, a successful calibration of the model has been achieved, despite unavoidable uncertainties concerning the dates of landslide occurrence. In particular, for the Sorrento Peninsula case, a fitness of 0.81 has been obtained by calibrating the model against 10 dates of landslide activation; in the Uncino case, a fitness of 1 (i.e. neither missing nor false alarms) has been achieved against 5 activations. As for temporal validation, the experiments performed by considering the extra dates of landslide activation have also proved satisfactory. In view of early-warning applications for civil protection purposes, the capability of the model to simulate the occurrences of the Uncino landslide has been tested by means of a progressive, self-adaptive procedure. Finally, a sensitivity analysis has been performed by taking into account the main parameters of the model. The obtained results are quite promising, given the high performance of the model obtained against different types of slope instabilities, characterized by several historical activations. Nevertheless, further refinements are still needed for applications to landslide risk mitigation within early-warning and decision-support systems.

Alteration of Box-Jenkins methodology by implementing genetic algorithm method

NASA Astrophysics Data System (ADS)

Ismail, Zuhaimy; Maarof, Mohd Zulariffin Md; Fadzli, Mohammad

2015-02-01

A time series is a set of values sequentially observed through time. The Box-Jenkins methodology is a systematic method of identifying, fitting, checking and using integrated autoregressive moving average time series model for forecasting. Box-Jenkins method is an appropriate for a medium to a long length (at least 50) time series data observation. When modeling a medium to a long length (at least 50), the difficulty arose in choosing the accurate order of model identification level and to discover the right parameter estimation. This presents the development of Genetic Algorithm heuristic method in solving the identification and estimation models problems in Box-Jenkins. Data on International Tourist arrivals to Malaysia were used to illustrate the effectiveness of this proposed method. The forecast results that generated from this proposed model outperformed single traditional Box-Jenkins model.

Reduced genetic variance among high fitness individuals: inferring stabilizing selection on male sexual displays in Drosophila serrata.

PubMed

Sztepanacz, Jacqueline L; Rundle, Howard D

2012-10-01

Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low- compared to high-fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high- and low-fitness individuals and was greater among the low-fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Positive correlation between genetic diversity and fitness in a large, well-connected metapopulation.

PubMed

Vandewoestijne, Sofie; Schtickzelle, Nicolas; Baguette, Michel

2008-11-05

Theory predicts that lower dispersal, and associated gene flow, leads to decreased genetic diversity in small isolated populations, which generates adverse consequences for fitness, and subsequently for demography. Here we report for the first time this effect in a well-connected natural butterfly metapopulation with high population densities at the edge of its distribution range. We demonstrate that: (1) lower genetic diversity was coupled to a sharp decrease in adult lifetime expectancy, a key component of individual fitness; (2) genetic diversity was positively correlated to the number of dispersing individuals (indicative of landscape functional connectivity) and adult population size; (3) parameters inferred from capture-recapture procedures (population size and dispersal events between patches) correlated much better with genetic diversity than estimates usually used as surrogates for population size (patch area and descriptors of habitat quality) and dispersal (structural connectivity index). Our results suggest that dispersal is a very important factor maintaining genetic diversity. Even at a very local spatial scale in a metapopulation consisting of large high-density populations interconnected by considerable dispersal rates, genetic diversity can be decreased and directly affect the fitness of individuals. From a biodiversity conservation perspective, this study clearly shows the benefits of both in-depth demographic and genetic analyses. Accordingly, to ensure the long-term survival of populations, conservation actions should not be blindly based on patch area and structural isolation. This result may be especially pertinent for species at their range margins, particularly in this era of rapid environmental change.

Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

PubMed

Jafari, Seyed Ali; Jahandideh, Sepideh; Jahandideh, Mina; Asadabadi, Ebrahim Barzegari

2015-01-01

Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial neural network model optimised through Genetic algorithm to predict mortality. In this study, a five-fold cross-validation procedure on a data set containing total of 178 countries was used to verify the performance of models. The best-fit model was selected according to the root mean square errors (RMSE). Genetic algorithm, as a powerful model which has not been introduced in prediction of mortality to this extent in previous studies, showed high performance. The lowest RMSE obtained was 0.0808. Such satisfactory results could be attributed to the use of Genetic algorithm as a powerful optimiser which selects the best input feature set to be fed into the neural networks. Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy. The gained results displayed that our model is very promising and may play a useful role in developing a better method for assessing the influence of road traffic mortality risk factors.

Genetic Complexity of Episodic Memory: A Twin Approach to Studies of Aging

PubMed Central

Kremen, William S.; Spoon, Kelly M.; Jacobson, Kristen C.; Vasilopoulos, Terrie; McCaffery, Jeanne M.; Panizzon, Matthew S.; Franz, Carol E.; Vuoksimaa, Eero; Xian, Hong; Rana, Brinda K.; Toomey, Rosemary; McKenzie, Ruth; Lyons, Michael J.

2016-01-01

Episodic memory change is a central issue in cognitive aging, and understanding that process will require elucidation of its genetic underpinnings. A key limiting factor in genetically informed research on memory has been lack of attention to genetic and phenotypic complexity, as if “memory is memory” and all well-validated assessments are essentially equivalent. Here we applied multivariate twin models to data from late-middle-aged participants in the Vietnam Era Twin Study of Aging to examine the genetic architecture of 6 measures from 3 standard neuropsychological tests: the California Verbal Learning Test-2, and Wechsler Memory Scale-III Logical Memory (LM) and Visual Reproductions (VR). An advantage of the twin method is that it can estimate the extent to which latent genetic influences are shared or independent across different measures before knowing which specific genes are involved. The best-fitting model was a higher order common pathways model with a heritable higher order general episodic memory factor and three test-specific subfactors. More importantly, substantial genetic variance was accounted for by genetic influences that were specific to the latent LM and VR subfactors (28% and 30%, respectively) and independent of the general factor. Such unique genetic influences could partially account for replication failures. Moreover, if different genes influence different memory phenotypes, they could well have different age-related trajectories. This approach represents an important step toward providing critical information for all types of genetically informative studies of aging and memory. PMID:24956007

The Genetic Covariation between Fear Conditioning and Self-Report Fears

PubMed Central

Hettema, John M.; Annas, Peter; Neale, Michael C.; Fredrikson, Mats; Sci, Dr Med; Kendler, Kenneth S.

2008-01-01

Background Fear conditioning is a traditional model for the acquisition of phobias, while behavioral therapies utilize processes underlying extinction to treat phobic and other anxiety disorders. Furthermore, fear conditioning has been proposed as an endophenotype for genetic studies of anxiety disorders. While prior studies have demonstrated that fear conditioning and self-report fears are heritable, no studies have determined whether they share a common genetic basis. Methods We obtained fear conditioning data from 173 twin pairs from the Swedish Twin Registry who also provided self-report ratings of 16 common fears. Using multivariate structural equation modeling, we analyzed factor-derived scores for the subjective fear ratings together with the electrophysiologic skin conductance responses during habituation, acquisition, and extinction to determine the extent of their genetic covariation. Results Phenotypic correlations between experimental and self-report fear measures were modest and, and counter-intuitively, negative; that is, subjects who reported themselves as more fearful had smaller electrophysiologic responses. Best-fit models estimated a significant (negative) genetic correlation between them, although genetic factors underlying fear conditioning accounted for only 9% of individual differences in self-report fears. Conclusions Experimentally-derived fear conditioning measures share only a small portion of the genetic factors underlying individual differences in subjective fears, cautioning against relying too heavily on the former as an endophenotype for genetic studies of phobic disorders. PMID:17698042

Combining Quantitative Genetic Footprinting and Trait Enrichment Analysis to Identify Fitness Determinants of a Bacterial Pathogen

PubMed Central

Wiles, Travis J.; Norton, J. Paul; Russell, Colin W.; Dalley, Brian K.; Fischer, Kael F.; Mulvey, Matthew A.

2013-01-01

Strains of Extraintestinal Pathogenic Escherichia c oli (ExPEC) exhibit an array of virulence strategies and are a major cause of urinary tract infections, sepsis and meningitis. Efforts to understand ExPEC pathogenesis are challenged by the high degree of genetic and phenotypic variation that exists among isolates. Determining which virulence traits are widespread and which are strain-specific will greatly benefit the design of more effective therapies. Towards this goal, we utilized a quantitative genetic footprinting technique known as transposon insertion sequencing (Tn-seq) in conjunction with comparative pathogenomics to functionally dissect the genetic repertoire of a reference ExPEC isolate. Using Tn-seq and high-throughput zebrafish infection models, we tracked changes in the abundance of ExPEC variants within saturated transposon mutant libraries following selection within distinct host niches. Nine hundred and seventy bacterial genes (18% of the genome) were found to promote pathogen fitness in either a niche-dependent or independent manner. To identify genes with the highest therapeutic and diagnostic potential, a novel Trait Enrichment Analysis (TEA) algorithm was developed to ascertain the phylogenetic distribution of candidate genes. TEA revealed that a significant portion of the 970 genes identified by Tn-seq have homologues more often contained within the genomes of ExPEC and other known pathogens, which, as suggested by the first axiom of molecular Koch's postulates, is considered to be a key feature of true virulence determinants. Three of these Tn-seq-derived pathogen-associated genes—a transcriptional repressor, a putative metalloendopeptidase toxin and a hypothetical DNA binding protein—were deleted and shown to independently affect ExPEC fitness in zebrafish and mouse models of infection. Together, the approaches and observations reported herein provide a resource for future pathogenomics-based research and highlight the diversity of factors required by a single ExPEC isolate to survive within varying host environments. PMID:23990803

Genetic and environmental structure of DSM-IV criteria for Antisocial Personality Disorder: a twin study

PubMed Central

Rosenström, Tom; Ystrom, Eivind; Torvik, Fartein Ask; Czajkowski, Nikolai Olavi; Gillespie, Nathan A.; Aggen, Steven H.; Krueger, Robert F.; Kendler, Kenneth S; Reichborn-Kjennerud, Ted

2017-01-01

Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI = 40–67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct. PMID:28108863

Genetic and Environmental Structure of DSM-IV Criteria for Antisocial Personality Disorder: A Twin Study.

PubMed

Rosenström, Tom; Ystrom, Eivind; Torvik, Fartein Ask; Czajkowski, Nikolai Olavi; Gillespie, Nathan A; Aggen, Steven H; Krueger, Robert F; Kendler, Kenneth S; Reichborn-Kjennerud, Ted

2017-05-01

Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI 40-67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct.

Application of genetic algorithm for the simultaneous identification of atmospheric pollution sources

NASA Astrophysics Data System (ADS)

Cantelli, A.; D'Orta, F.; Cattini, A.; Sebastianelli, F.; Cedola, L.

2015-08-01

A computational model is developed for retrieving the positions and the emission rates of unknown pollution sources, under steady state conditions, starting from the measurements of the concentration of the pollutants. The approach is based on the minimization of a fitness function employing a genetic algorithm paradigm. The model is tested considering both pollutant concentrations generated through a Gaussian model in 25 points in a 3-D test case domain (1000m × 1000m × 50 m) and experimental data such as the Prairie Grass field experiments data in which about 600 receptors were located along five concentric semicircle arcs and the Fusion Field Trials 2007. The results show that the computational model is capable to efficiently retrieve up to three different unknown sources.

[Demographic consequences of genetic load: a model of the origin of the incest taboo].

PubMed

Buzin, A Iu

1987-12-01

The prohibition of copulations among near relatives may raise the fitness of population. This effect being irregular and insignificant for a distinct generation, becomes apparent in evolutionary time intervals through the natural selection of populations with incest-taboo. The "characteristic selection time" theta depends on typical population size, genetic damage and the mean rate of population growth. The estimation obtained for theta permit us to assert that the model describes the phenomenon of "socio-cultural selection" in prehistory. The model shows the demographic specificity of small populations. The problem of the number of consanguineous marriages is considered in detail. New explanation for deviation of the observed frequency of consanguineous marriages from classical estimations is proposed.

The hitchhiker's guide to altruism: gene-culture coevolution, and the internalization of norms.

PubMed

Gintis, Herbert

2003-02-21

An internal norm is a pattern of behavior enforced in part by internal sanctions, such as shame, guilt and loss of self-esteem, as opposed to purely external sanctions, such as material rewards and punishment. The ability to internalize norms is widespread among humans, although in some so-called "sociopaths", this capacity is diminished or lacking. Suppose there is one genetic locus that controls the capacity to internalize norms. This model shows that if an internal norm is fitness enhancing, then for plausible patterns of socialization, the allele for internalization of norms is evolutionarily stable. This framework can be used to model Herbert Simon's (1990) explanation of altruism, showing that altruistic norms can "hitchhike" on the general tendency of internal norms to be personally fitness-enhancing. A multi-level selection, gene-culture coevolution argument then explains why individually fitness-reducing internal norms are likely to be prosocial as opposed to socially harmful.

Genetic variation facilitates seedling establishment but not population growth rate of a perennial invader.

PubMed

Li, Shou-Li; Vasemägi, Anti; Ramula, Satu

2016-01-01

Assessing the demographic consequences of genetic variation is fundamental to invasion biology. However, genetic and demographic approaches are rarely combined to explore the effects of genetic variation on invasive populations in natural environments. This study combined population genetics, demographic data and a greenhouse experiment to investigate the consequences of genetic variation for the population fitness of the perennial, invasive herb Lupinus polyphyllus. Genetic and demographic data were collected from 37 L. polyphyllus populations representing different latitudes in Finland, and genetic variation was characterized based on 13 microsatellite loci. Associations between genetic variation and population size, population density, latitude and habitat were investigated. Genetic variation was then explored in relation to four fitness components (establishment, survival, growth, fecundity) measured at the population level, and the long-term population growth rate (λ). For a subset of populations genetic variation was also examined in relation to the temporal variability of λ. A further assessment was made of the role of natural selection in the observed variation of certain fitness components among populations under greenhouse conditions. It was found that genetic variation correlated positively with population size, particularly at higher latitudes, and differed among habitat types. Average seedling establishment per population increased with genetic variation in the field, but not under greenhouse conditions. Quantitative genetic divergence (Q(ST)) based on seedling establishment in the greenhouse was smaller than allelic genetic divergence (F'(ST)), indicating that unifying selection has a prominent role in this fitness component. Genetic variation was not associated with average survival, growth or fecundity measured at the population level, λ or its variability. The study suggests that although genetic variation may facilitate plant invasions by increasing seedling establishment, it may not necessarily affect the long-term population growth rate. Therefore, established invasions may be able to grow equally well regardless of their genetic diversity. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Autonomous Modelling of X-ray Spectra Using Robust Global Optimization Methods

NASA Astrophysics Data System (ADS)

Rogers, Adam; Safi-Harb, Samar; Fiege, Jason

2015-08-01

The standard approach to model fitting in X-ray astronomy is by means of local optimization methods. However, these local optimizers suffer from a number of problems, such as a tendency for the fit parameters to become trapped in local minima, and can require an involved process of detailed user intervention to guide them through the optimization process. In this work we introduce a general GUI-driven global optimization method for fitting models to X-ray data, written in MATLAB, which searches for optimal models with minimal user interaction. We directly interface with the commonly used XSPEC libraries to access the full complement of pre-existing spectral models that describe a wide range of physics appropriate for modelling astrophysical sources, including supernova remnants and compact objects. Our algorithm is powered by the Ferret genetic algorithm and Locust particle swarm optimizer from the Qubist Global Optimization Toolbox, which are robust at finding families of solutions and identifying degeneracies. This technique will be particularly instrumental for multi-parameter models and high-fidelity data. In this presentation, we provide details of the code and use our techniques to analyze X-ray data obtained from a variety of astrophysical sources.

How well can captive breeding programs conserve biodiversity? A review of salmonids

PubMed Central

Fraser, Dylan J

2008-01-01

Captive breeding programs are increasingly being initiated to prevent the imminent extinction of endangered species and/or populations. But how well can they conserve genetic diversity and fitness, or re-establish self-sustaining populations in the wild? A review of these complex questions and related issues in salmonid fishes reveals several insights and uncertainties. Most programs can maintain genetic diversity within populations over several generations, but available research suggests the loss of fitness in captivity can be rapid, its magnitude probably increasing with the duration in captivity. Over the long-term, there is likely tremendous variation between (i) programs in their capacity to maintain genetic diversity and fitness, and (ii) species or even intraspecific life-history types in both the severity and manner of fitness-costs accrued. Encouragingly, many new theoretical and methodological approaches now exist for current and future programs to potentially reduce these effects. Nevertheless, an unavoidable trade-off exists between conserving genetic diversity and fitness in certain instances, such as when captive-bred individuals are temporarily released into the wild. Owing to several confounding factors, there is also currently little evidence that captive-bred lines of salmonids can or cannot be reintroduced as self-sustaining populations. Most notably, the root causes of salmonid declines have not been mitigated where captive breeding programs exist. Little research has also addressed under what conditions an increase in population abundance due to captive-rearing might offset fitness reductions induced in captivity. Finally, more empirical investigation is needed to evaluate the genetic/fitness benefits and risks associated with (i) maintaining captive broodstocks as either single or multiple populations within one or more facilities, (ii) utilizing cryopreservation or surrogate broodstock technologies, and (iii) adopting other alternatives to captive-rearing such as translocations to new habitats. Management recommendations surrounding these issues are proposed, with the aim of facilitating meta-analyses and more general principles or guidelines for captive-breeding. These include the need for the following: (i) captive monitoring to involve, a priori, greater application of hypothesis testing through the use of well-designed experiments and (ii) improved documentation of procedures adopted by specific programs for reducing the loss of genetic diversity and fitness. PMID:25567798

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

PubMed Central

2013-01-01

Background Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring. PMID:23827014

Global optimization and reflectivity data fitting for x-ray multilayer mirrors by means of genetic algorithms

NASA Astrophysics Data System (ADS)

Sanchez del Rio, Manuel; Pareschi, Giovanni

2001-01-01

The x-ray reflectivity of a multilayer is a non-linear function of many parameters (materials, layer thicknesses, densities, roughness). Non-linear fitting of experimental data with simulations requires to use initial values sufficiently close to the optimum value. This is a difficult task when the space topology of the variables is highly structured, as in our case. The application of global optimization methods to fit multilayer reflectivity data is presented. Genetic algorithms are stochastic methods based on the model of natural evolution: the improvement of a population along successive generations. A complete set of initial parameters constitutes an individual. The population is a collection of individuals. Each generation is built from the parent generation by applying some operators (e.g. selection, crossover, mutation) on the members of the parent generation. The pressure of selection drives the population to include 'good' individuals. For large number of generations, the best individuals will approximate the optimum parameters. Some results on fitting experimental hard x-ray reflectivity data for Ni/C multilayers recorded at the ESRF BM5 are presented. This method could be also applied to the help in the design of multilayers optimized for a target application, like for an astronomical grazing-incidence hard X-ray telescopes.

Estimating selection through male fitness: three complementary methods illuminate the nature and causes of selection on flowering time

PubMed Central

Austen, Emily J.; Weis, Arthur E.

2016-01-01

Our understanding of selection through male fitness is limited by the resource demands and indirect nature of the best available genetic techniques. Applying complementary, independent approaches to this problem can help clarify evolution through male function. We applied three methods to estimate selection on flowering time through male fitness in experimental populations of the annual plant Brassica rapa: (i) an analysis of mating opportunity based on flower production schedules, (ii) genetic paternity analysis, and (iii) a novel approach based on principles of experimental evolution. Selection differentials estimated by the first method disagreed with those estimated by the other two, indicating that mating opportunity was not the principal driver of selection on flowering time. The genetic and experimental evolution methods exhibited striking agreement overall, but a slight discrepancy between the two suggested that negative environmental covariance between age at flowering and male fitness may have contributed to phenotypic selection. Together, the three methods enriched our understanding of selection on flowering time, from mating opportunity to phenotypic selection to evolutionary response. The novel experimental evolution method may provide a means of examining selection through male fitness when genetic paternity analysis is not possible. PMID:26911957

Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits.

PubMed

Aliloo, Hassan; Pryce, Jennie E; González-Recio, Oscar; Cocks, Benjamin G; Hayes, Ben J

2016-02-01

Dominance effects may contribute to genetic variation of complex traits in dairy cattle, especially for traits closely related to fitness such as fertility. However, traditional genetic evaluations generally ignore dominance effects and consider additive genetic effects only. Availability of dense single nucleotide polymorphisms (SNPs) panels provides the opportunity to investigate the role of dominance in quantitative variation of complex traits at both the SNP and animal levels. Including dominance effects in the genomic evaluation of animals could also help to increase the accuracy of prediction of future phenotypes. In this study, we estimated additive and dominance variance components for fertility and milk production traits of genotyped Holstein and Jersey cows in Australia. The predictive abilities of a model that accounts for additive effects only (additive), and a model that accounts for both additive and dominance effects (additive + dominance) were compared in a fivefold cross-validation. Estimates of the proportion of dominance variation relative to phenotypic variation that is captured by SNPs, for production traits, were up to 3.8 and 7.1 % in Holstein and Jersey cows, respectively, whereas, for fertility, they were equal to 1.2 % in Holstein and very close to zero in Jersey cows. We found that including dominance in the model was not consistently advantageous. Based on maximum likelihood ratio tests, the additive + dominance model fitted the data better than the additive model, for milk, fat and protein yields in both breeds. However, regarding the prediction of phenotypes assessed with fivefold cross-validation, including dominance effects in the model improved accuracy only for fat yield in Holstein cows. Regression coefficients of phenotypes on genetic values and mean squared errors of predictions showed that the predictive ability of the additive + dominance model was superior to that of the additive model for some of the traits. In both breeds, dominance effects were significant (P < 0.01) for all milk production traits but not for fertility. Accuracy of prediction of phenotypes was slightly increased by including dominance effects in the genomic evaluation model. Thus, it can help to better identify highly performing individuals and be useful for culling decisions.

Implications of sex-specific selection for the genetic basis of disease.

PubMed

Morrow, Edward H; Connallon, Tim

2013-12-01

Mutation and selection are thought to shape the underlying genetic basis of many common human diseases. However, both processes depend on the context in which they occur, such as environment, genetic background, or sex. Sex has widely known effects on phenotypic expression of genotype, but an analysis of how it influences the evolutionary dynamics of disease-causing variants has not yet been explored. We develop a simple population genetic model of disease susceptibility and evaluate it using a biologically plausible empirically based distribution of fitness effects among contributing mutations. The model predicts that alleles under sex-differential selection, including sexually antagonistic alleles, will disproportionately contribute to genetic variation for disease predisposition, thereby generating substantial sexual dimorphism in the genetic architecture of complex (polygenic) diseases. This is because such alleles evolve into higher population frequencies for a given effect size, relative to alleles experiencing equally strong purifying selection in both sexes. Our results provide a theoretical justification for expecting a sexually dimorphic genetic basis for variation in complex traits such as disease. Moreover, they suggest that such dimorphism is interesting - not merely something to control for - because it reflects the action of natural selection in molding the evolution of common disease phenotypes.

Tolerance to deer herbivory and resistance to insect herbivores in the common evening primrose (Oenothera biennis).

PubMed

Puentes, A; Johnson, M T J

2016-01-01

The evolution of plant defence in response to herbivory will depend on the fitness effects of damage, availability of genetic variation and potential ecological and genetic constraints on defence. Here, we examine the potential for evolution of tolerance to deer herbivory in Oenothera biennis while simultaneously considering resistance to natural insect herbivores. We examined (i) the effects of deer damage on fitness, (ii) the presence of genetic variation in tolerance and resistance, (iii) selection on tolerance, (iv) genetic correlations with resistance that could constrain evolution of tolerance and (v) plant traits that might predict defence. In a field experiment, we simulated deer damage occurring early and late in the season, recorded arthropod abundances, flowering phenology and measured growth rate and lifetime reproduction. Our study showed that deer herbivory has a negative effect on fitness, with effects being more pronounced for late-season damage. Selection acted to increase tolerance to deer damage, yet there was low and nonsignificant genetic variation in this trait. In contrast, there was substantial genetic variation in resistance to insect herbivores. Resistance was genetically uncorrelated with tolerance, whereas positive genetic correlations in resistance to insect herbivores suggest there exists diffuse selection on resistance traits. In addition, growth rate and flowering time did not predict variation in tolerance, but flowering phenology was genetically correlated with resistance. Our results suggest that deer damage has the potential to exert selection because browsing reduces plant fitness, but limited standing genetic variation in tolerance is expected to constrain adaptive evolution in O. biennis. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Estimating time since infection in early homogeneous HIV-1 samples using a poisson model

PubMed Central

2010-01-01

Background The occurrence of a genetic bottleneck in HIV sexual or mother-to-infant transmission has been well documented. This results in a majority of new infections being homogeneous, i.e., initiated by a single genetic strain. Early after infection, prior to the onset of the host immune response, the viral population grows exponentially. In this simple setting, an approach for estimating evolutionary and demographic parameters based on comparison of diversity measures is a feasible alternative to the existing Bayesian methods (e.g., BEAST), which are instead based on the simulation of genealogies. Results We have devised a web tool that analyzes genetic diversity in acutely infected HIV-1 patients by comparing it to a model of neutral growth. More specifically, we consider a homogeneous infection (i.e., initiated by a unique genetic strain) prior to the onset of host-induced selection, where we can assume a random accumulation of mutations. Previously, we have shown that such a model successfully describes about 80% of sexual HIV-1 transmissions provided the samples are drawn early enough in the infection. Violation of the model is an indicator of either heterogeneous infections or the initiation of selection. Conclusions When the underlying assumptions of our model (homogeneous infection prior to selection and fast exponential growth) are met, we are under a very particular scenario for which we can use a forward approach (instead of backwards in time as provided by coalescent methods). This allows for more computationally efficient methods to derive the time since the most recent common ancestor. Furthermore, the tool performs statistical tests on the Hamming distance frequency distribution, and outputs summary statistics (mean of the best fitting Poisson distribution, goodness of fit p-value, etc). The tool runs within minutes and can readily accommodate the tens of thousands of sequences generated through new ultradeep pyrosequencing technologies. The tool is available on the LANL website. PMID:20973976

Evidence of major genes affecting stress response in rainbow trout using Bayesian methods of complex segregation analysis

USDA-ARS?s Scientific Manuscript database

As a first step towards the genetic mapping of quantitative trait loci (QTL) affecting stress response variation in rainbow trout, we performed complex segregation analyses (CSA) fitting mixed inheritance models of plasma cortisol using Bayesian methods in large full-sib families of rainbow trout. ...

Estimating population genetic parameters and comparing model goodness-of-fit using DNA sequences with error

PubMed Central

Liu, Xiaoming; Fu, Yun-Xin; Maxwell, Taylor J.; Boerwinkle, Eric

2010-01-01

It is known that sequencing error can bias estimation of evolutionary or population genetic parameters. This problem is more prominent in deep resequencing studies because of their large sample size n, and a higher probability of error at each nucleotide site. We propose a new method based on the composite likelihood of the observed SNP configurations to infer population mutation rate θ = 4Neμ, population exponential growth rate R, and error rate ɛ, simultaneously. Using simulation, we show the combined effects of the parameters, θ, n, ɛ, and R on the accuracy of parameter estimation. We compared our maximum composite likelihood estimator (MCLE) of θ with other θ estimators that take into account the error. The results show the MCLE performs well when the sample size is large or the error rate is high. Using parametric bootstrap, composite likelihood can also be used as a statistic for testing the model goodness-of-fit of the observed DNA sequences. The MCLE method is applied to sequence data on the ANGPTL4 gene in 1832 African American and 1045 European American individuals. PMID:19952140

Overuse Injury Assessment Model

DTIC Science & Technology

2003-06-01

initial physical fitness level foot type lower extremity alignment altered gait pretest anthropometry diet and nutrition genetics endocrine status and...using published anthropometry values. Assuming that these forces are the primary loads that cause the tibia to undergo shear and bending, the maximal...both the model and in vivo results suggest that the ratio of walking to running bone stress is 0.54. Table 3-3 Estimated walk/march and run tensile

Socializing with MYC: cell competition in development and as a model for premalignant cancer.

PubMed

Johnston, Laura A

2014-04-01

Studies in Drosophila and mammals have made it clear that genetic mutations that arise in somatic tissues are rapidly recognized and eliminated, suggesting that cellular fitness is tightly monitored. During development, damaged, mutant, or otherwise unfit cells are prevented from contributing to the tissue and are instructed to die, whereas healthy cells benefit and populate the animal. This cell selection process, known as cell competition, eliminates somatic genetic heterogeneity and promotes tissue fitness during development. Yet cell competition also has a dark side. Super competition can be exploited by incipient cancers to subvert cellular cooperation and promote selfish behavior. Evidence is accumulating that MYC plays a key role in regulation of social behavior within tissues. Given the high number of tumors with deregulated MYC, studies of cell competition promise to yield insight into how the local environment yields to and participates in the early stages of tumor formation.

Heterozygosity-fitness correlations in a wild mammal population: accounting for parental and environmental effects.

PubMed

Annavi, Geetha; Newman, Christopher; Buesching, Christina D; Macdonald, David W; Burke, Terry; Dugdale, Hannah L

2014-06-01

HFCs (heterozygosity-fitness correlations) measure the direct relationship between an individual's genetic diversity and fitness. The effects of parental heterozygosity and the environment on HFCs are currently under-researched. We investigated these in a high-density U.K. population of European badgers (Meles meles), using a multimodel capture-mark-recapture framework and 35 microsatellite loci. We detected interannual variation in first-year, but not adult, survival probability. Adult females had higher annual survival probabilities than adult males. Cubs with more heterozygous fathers had higher first-year survival, but only in wetter summers; there was no relationship with individual or maternal heterozygosity. Moist soil conditions enhance badger food supply (earthworms), improving survival. In dryer years, higher indiscriminate mortality rates appear to mask differential heterozygosity-related survival effects. This paternal interaction was significant in the most supported model; however, the model-averaged estimate had a relative importance of 0.50 and overlapped zero slightly. First-year survival probabilities were not correlated with the inbreeding coefficient (f); however, small sample sizes limited the power to detect inbreeding depression. Correlations between individual heterozygosity and inbreeding were weak, in line with published meta-analyses showing that HFCs tend to be weak. We found support for general rather than local heterozygosity effects on first-year survival probability, and g2 indicated that our markers had power to detect inbreeding. We emphasize the importance of assessing how environmental stressors can influence the magnitude and direction of HFCs and of considering how parental genetic diversity can affect fitness-related traits, which could play an important role in the evolution of mate choice.

Empirical complexities in the genetic foundations of lethal mutagenesis.

PubMed

Bull, James J; Joyce, Paul; Gladstone, Eric; Molineux, Ian J

2013-10-01

From population genetics theory, elevating the mutation rate of a large population should progressively reduce average fitness. If the fitness decline is large enough, the population will go extinct in a process known as lethal mutagenesis. Lethal mutagenesis has been endorsed in the virology literature as a promising approach to viral treatment, and several in vitro studies have forced viral extinction with high doses of mutagenic drugs. Yet only one empirical study has tested the genetic models underlying lethal mutagenesis, and the theory failed on even a qualitative level. Here we provide a new level of analysis of lethal mutagenesis by developing and evaluating models specifically tailored to empirical systems that may be used to test the theory. We first quantify a bias in the estimation of a critical parameter and consider whether that bias underlies the previously observed lack of concordance between theory and experiment. We then consider a seemingly ideal protocol that avoids this bias-mutagenesis of virions-but find that it is hampered by other problems. Finally, results that reveal difficulties in the mere interpretation of mutations assayed from double-strand genomes are derived. Our analyses expose unanticipated complexities in testing the theory. Nevertheless, the previous failure of the theory to predict experimental outcomes appears to reside in evolutionary mechanisms neglected by the theory (e.g., beneficial mutations) rather than from a mismatch between the empirical setup and model assumptions. This interpretation raises the specter that naive attempts at lethal mutagenesis may augment adaptation rather than retard it.

A unified genetic association test robust to latent population structure for a count phenotype.

PubMed

Song, Minsun

2018-06-04

Confounding caused by latent population structure in genome-wide association studies has been a big concern despite the success of genome-wide association studies at identifying genetic variants associated with complex diseases. In particular, because of the growing interest in association mapping using count phenotype data, it would be interesting to develop a testing framework for genetic associations that is immune to population structure when phenotype data consist of count measurements. Here, I propose a solution for testing associations between single nucleotide polymorphisms and a count phenotype in the presence of an arbitrary population structure. I consider a classical range of models for count phenotype data. Under these models, a unified test for genetic associations that protects against confounding was derived. An algorithm was developed to efficiently estimate the parameters that are required to fit the proposed model. I illustrate the proposed approach using simulation studies and an empirical study. Both simulated and real-data examples suggest that the proposed method successfully corrects population structure. Copyright © 2018 John Wiley & Sons, Ltd.

General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

PubMed

de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

2016-11-01

Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

Optimal sensor placement for spatial lattice structure based on genetic algorithms

NASA Astrophysics Data System (ADS)

Liu, Wei; Gao, Wei-cheng; Sun, Yi; Xu, Min-jian

2008-10-01

Optimal sensor placement technique plays a key role in structural health monitoring of spatial lattice structures. This paper considers the problem of locating sensors on a spatial lattice structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterized. Based on the criterion of optimal sensor placement for modal test, an improved genetic algorithm is introduced to find the optimal placement of sensors. The modal strain energy (MSE) and the modal assurance criterion (MAC) have been taken as the fitness function, respectively, so that three placement designs were produced. The decimal two-dimension array coding method instead of binary coding method is proposed to code the solution. Forced mutation operator is introduced when the identical genes appear via the crossover procedure. A computational simulation of a 12-bay plain truss model has been implemented to demonstrate the feasibility of the three optimal algorithms above. The obtained optimal sensor placements using the improved genetic algorithm are compared with those gained by exiting genetic algorithm using the binary coding method. Further the comparison criterion based on the mean square error between the finite element method (FEM) mode shapes and the Guyan expansion mode shapes identified by data-driven stochastic subspace identification (SSI-DATA) method are employed to demonstrate the advantage of the different fitness function. The results showed that some innovations in genetic algorithm proposed in this paper can enlarge the genes storage and improve the convergence of the algorithm. More importantly, the three optimal sensor placement methods can all provide the reliable results and identify the vibration characteristics of the 12-bay plain truss model accurately.

Narrow Bottlenecks Affect Pea Seedborne Mosaic Virus Populations during Vertical Seed Transmission but not during Leaf Colonization

PubMed Central

Johansen, Elisabeth Ida; Simon, Vincent; Jacquemond, Mireille; Senoussi, Rachid

2014-01-01

The effective size of populations (Ne) determines whether selection or genetic drift is the predominant force shaping their genetic structure and evolution. Populations having high Ne adapt faster, as selection acts more intensely, than populations having low Ne, where random effects of genetic drift dominate. Estimating Ne for various steps of plant virus life cycle has been the focus of several studies in the last decade, but no estimates are available for the vertical transmission of plant viruses, although virus seed transmission is economically significant in at least 18% of plant viruses in at least one plant species. Here we study the co-dynamics of two variants of Pea seedborne mosaic virus (PSbMV) colonizing leaves of pea plants (Pisum sativum L.) during the whole flowering period, and their subsequent transmission to plant progeny through seeds. Whereas classical estimators of Ne could be used for leaf infection at the systemic level, as virus variants were equally competitive, dedicated stochastic models were needed to estimate Ne during vertical transmission. Very little genetic drift was observed during the infection of apical leaves, with Ne values ranging from 59 to 216. In contrast, a very drastic genetic drift was observed during vertical transmission, with an average number of infectious virus particles contributing to the infection of a seedling from an infected mother plant close to one. A simple model of vertical transmission, assuming a cumulative action of virus infectious particles and a virus density threshold required for vertical transmission to occur fitted the experimental data very satisfactorily. This study reveals that vertically-transmitted viruses endure bottlenecks as narrow as those imposed by horizontal transmission. These bottlenecks are likely to slow down virus adaptation and could decrease virus fitness and virulence. PMID:24415934

A study of changes in genetic and environmental influences on weight and shape concern across adolescence.

PubMed

Wade, Tracey D; Hansell, Narelle K; Crosby, Ross D; Bryant-Waugh, Rachel; Treasure, Janet; Nixon, Reginald; Byrne, Susan; Martin, Nicholas G

2013-02-01

The goal of the current study was to examine whether genetic and environmental influences on an important risk factor for disordered eating, weight and shape concern, remained stable over adolescence. This stability was assessed in 2 ways: whether new sources of latent variance were introduced over development and whether the magnitude of variance contributing to the risk factor changed. We examined an 8-item WSC subscale derived from the Eating Disorder Examination (EDE) using telephone interviews with female adolescents. From 3 waves of data collected from female-female same-sex twin pairs from the Australian Twin Registry, a subset of the data (which included 351 pairs at Wave 1) was used to examine 3 age cohorts: 12 to 13, 13 to 15, and 14 to 16 years. The best-fitting model contained genetic and environmental influences, both shared and nonshared. Biometric model fitting indicated that nonshared environmental influences were largely specific to each age cohort, and results suggested that latent shared environmental and genetic influences that were influential at 12 to 13 years continued to contribute to subsequent age cohorts, with independent sources of both emerging at ages 13 to 15. The magnitude of all 3 latent influences could be constrained to be the same across adolescence. Ages 13 to 15 were indicated as a time of risk for the development of high levels of WSC, given that most specific environmental risk factors were significant at this time (e.g., peer teasing about weight, adverse life events), and indications of the emergence of new sources of latent genetic and environmental variance over this period. 2013 APA, all rights reserved

Understanding the nature of wealth and its effects on human fitness

PubMed Central

Mulder, Monique Borgerhoff; Beheim, Bret A.

2011-01-01

Studying fitness consequences of variable behavioural, physiological and cognitive traits in contemporary populations constitutes the specific contribution of human behavioural ecology to the study of human diversity. Yet, despite 30 years of evolutionary anthropological interest in the determinants of fitness, there exist few principled investigations of the diverse sources of wealth that might reveal selective forces during recent human history. To develop a more holistic understanding of how selection shapes human phenotypic traits, be these transmitted by genetic or cultural means, we expand the conventional focus on associations between socioeconomic status and fitness to three distinct types of wealth—embodied, material and relational. Using a model selection approach to the study of women's success in raising offspring in an African horticultural population (the Tanzanian Pimbwe), we find that the top performing models consistently include relational and material wealth, with embodied wealth as a less reliable predictor. Specifically, child mortality risk is increased with few household assets, parent nonresidency, child legitimacy, and one or more parents having been accused of witchcraft. The use of multiple models to test various hypotheses greatly facilitates systematic comparative analyses of human behavioural diversity in wealth accrual and investment across different kinds of societies. PMID:21199839

A General Definition of the Heritable Variation That Determines the Potential of a Population to Respond to Selection

PubMed Central

Bijma, Piter

2011-01-01

Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population’s intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection. PMID:21926298

A general definition of the heritable variation that determines the potential of a population to respond to selection.

PubMed

Bijma, Piter

2011-12-01

Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population's intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection.

Exploring the use of random regression models with legendre polynomials to analyze measures of volume of ejaculate in Holstein bulls.

PubMed

Carabaño, M J; Díaz, C; Ugarte, C; Serrano, M

2007-02-01

Artificial insemination centers routinely collect records of quantity and quality of semen of bulls throughout the animals' productive period. The goal of this paper was to explore the use of random regression models with orthogonal polynomials to analyze repeated measures of semen production of Spanish Holstein bulls. A total of 8,773 records of volume of first ejaculate (VFE) collected between 12 and 30 mo of age from 213 Spanish Holstein bulls was analyzed under alternative random regression models. Legendre polynomial functions of increasing order (0 to 6) were fitted to the average trajectory, additive genetic and permanent environmental effects. Age at collection and days in production were used as time variables. Heterogeneous and homogeneous residual variances were alternatively assumed. Analyses were carried out within a Bayesian framework. The logarithm of the marginal density and the cross-validation predictive ability of the data were used as model comparison criteria. Based on both criteria, age at collection as a time variable and heterogeneous residuals models are recommended to analyze changes of VFE over time. Both criteria indicated that fitting random curves for genetic and permanent environmental components as well as for the average trajector improved the quality of models. Furthermore, models with a higher order polynomial for the permanent environmental (5 to 6) than for the genetic components (4 to 5) and the average trajectory (2 to 3) tended to perform best. High-order polynomials were needed to accommodate the highly oscillating nature of the phenotypic values. Heritability and repeatability estimates, disregarding the extremes of the studied period, ranged from 0.15 to 0.35 and from 0.20 to 0.50, respectively, indicating that selection for VFE may be effective at any stage. Small differences among models were observed. Apart from the extremes, estimated correlations between ages decreased steadily from 0.9 and 0.4 for measures 1 mo apart to 0.4 and 0.2 for most distant measures for additive genetic and phenotypic components, respectively. Further investigation to account for environmental factors that may be responsible for the oscillating observations of VFE is needed.

Prisoner's dilemma posed by fitness-associated recombination strategies.

PubMed

Wexler, Ydo; Rokhlenko, Oleg

2007-07-07

Genetic recombination is a central and repeated topic of study in the evolution of life. However, along with the influence of recombination on evolution, we understand surprisingly little of how selection shapes the nature of recombination. One explanation for recombination is that it allows organisms to escape from perilous situations where they experience very low fitness. As a corollary, it has been suggested that selection should favor recombination at low fitness and not at high fitness (fitness-associated recombination, FAR), and theory suggests that such strategies can indeed be selected. Here we develop models to further investigate the evolution of FAR. Consistent with previous works, we find that FAR can invade and dominate over a strategy of uniform recombination that is independent of fitness. However, our simulation results suggest that extreme FAR strategies, known as group-elitism, are not necessarily superior to other FAR strategies. Moreover, we argue that FAR domination will often occur with a net loss of mean population fitness. Interestingly, this suggests that the strategy of not recombining at high fitness will sometimes be analogous to a defector strategy from the famous "prisoner's dilemma" game: a selfish strategy that is selected but leads to a loss of mean fitness for all players.

Carrying photosynthesis genes increases ecological fitness of cyanophage in silico.

PubMed

Hellweger, Ferdi L

2009-06-01

Several viruses infecting marine cyanobacteria carry photosynthesis genes (e.g. psbA, hli) that are expressed, yield proteins (D1, HLIP) and help maintain the cell's photosynthesis apparatus during the latent period. This increases energy and speeds up virus production, allowing for a reduced latent period (a fitness benefit), but it also increases the DNA size, which slows down new virus production and reduces burst size (a fitness cost). How do these genes affect the net ecological fitness of the virus? Here, this question is explored using a combined systems biology and systems ecology ('systems bioecology') approach. A novel agent-based model simulates individual cyanobacteria cells and virus particles, each with their own genes, transcripts, proteins and other properties. The effect of D1 and HLIP proteins is explicitly considered using a mechanistic photosynthesis component. The model is calibrated to the available database for Prochlorococcus ecotype MED4 and podovirus P-SSP7. Laboratory- and field-scale in silico survival, competition and evolution (gene packaging error) experiments with wild type and genetically engineered viruses are performed to develop vertical survival and fitness profiles, and to determine the optimal gene content. The results suggest that photosynthesis genes are nonessential, increase fitness in a manner correlated with irradiance, and that the wild type has an optimal gene content.

Positive correlation between genetic diversity and fitness in a large, well-connected metapopulation

PubMed Central

Vandewoestijne, Sofie; Schtickzelle, Nicolas; Baguette, Michel

2008-01-01

Background Theory predicts that lower dispersal, and associated gene flow, leads to decreased genetic diversity in small isolated populations, which generates adverse consequences for fitness, and subsequently for demography. Here we report for the first time this effect in a well-connected natural butterfly metapopulation with high population densities at the edge of its distribution range. Results We demonstrate that: (1) lower genetic diversity was coupled to a sharp decrease in adult lifetime expectancy, a key component of individual fitness; (2) genetic diversity was positively correlated to the number of dispersing individuals (indicative of landscape functional connectivity) and adult population size; (3) parameters inferred from capture-recapture procedures (population size and dispersal events between patches) correlated much better with genetic diversity than estimates usually used as surrogates for population size (patch area and descriptors of habitat quality) and dispersal (structural connectivity index). Conclusion Our results suggest that dispersal is a very important factor maintaining genetic diversity. Even at a very local spatial scale in a metapopulation consisting of large high-density populations interconnected by considerable dispersal rates, genetic diversity can be decreased and directly affect the fitness of individuals. From a biodiversity conservation perspective, this study clearly shows the benefits of both in-depth demographic and genetic analyses. Accordingly, to ensure the long-term survival of populations, conservation actions should not be blindly based on patch area and structural isolation. This result may be especially pertinent for species at their range margins, particularly in this era of rapid environmental change. PMID:18986515

Strong fluctuations in aboveground population size do not limit genetic diversity in populations of an endangered biennial species.

PubMed

Münzbergová, Zuzana; Šurinová, Maria; Husáková, Iveta; Brabec, Jiří

2018-04-26

Assessing genetic diversity within populations of rare species and understanding its determinants are crucial for effective species protection. While a lot is known about the relationships between genetic diversity, fitness, and current population size, very few studies explored the effects of past population size. Knowledge of past population size may, however, improve our ability to predict future population fates. We studied Gentianella praecox subsp. bohemica, a biennial species with extensive seed bank. We tested the effect of current, past minimal and maximal population size, and harmonic mean of population sizes within the last 15 years on genetic diversity and fitness. Maximum population size over the last 15 years was the best predictor of expected heterozygosity of the populations and was significantly related to current population size and management. Plant fitness was significantly related to current as well as maximum population size and expected heterozygosity. The results suggested that information on past population size may improve our understanding of contemporary genetic diversity across populations. They demonstrated that despite the strong fluctuations in population size, large reductions in population size do not result in immediate loss of genetic diversity and reduction of fitness within the populations. This is likely due to the seed bank of the species serving as reservoir of the genetic diversity of the populations. From a conservation point of view, this suggests that the restoration of small populations of short-lived species with permanent seed bank is possible as these populations may still be genetically diverse.

GENES AS INSTRUMENTS FOR STUDYING RISK BEHAVIOR EFFECTS: AN APPLICATION TO MATERNAL SMOKING AND OROFACIAL CLEFTS

PubMed Central

Jugessur, Astanand; Murray, Jeffrey C.; Moreno, Lina; Wilcox, Allen; Lie, Rolv T.

2011-01-01

This study uses instrumental variable (IV) models with genetic instruments to assess the effects of maternal smoking on the child’s risk of orofacial clefts (OFC), a common birth defect. The study uses genotypic variants in neurotransmitter and detoxification genes relateded to smoking as instruments for cigarette smoking before and during pregnancy. Conditional maximum likelihood and two-stage IV probit models are used to estimate the IV model. The data are from a population-level sample of affected and unaffected children in Norway. The selected genetic instruments generally fit the IV assumptions but may be considered “weak” in predicting cigarette smoking. We find that smoking before and during pregnancy increases OFC risk substantially under the IV model (by about 4–5 times at the sample average smoking rate). This effect is greater than that found with classical analytic models. This may be because the usual models are not able to consider self-selection into smoking based on unobserved confounders, or it may to some degree reflect limitations of the instruments. Inference based on weak-instrument robust confidence bounds is consistent with standard inference. Genetic instruments may provide a valuable approach to estimate the “causal” effects of risk behaviors with genetic-predisposing factors (such as smoking) on health and socioeconomic outcomes. PMID:22102793

FitSearch: a robust way to interpret a yeast fitness profile in terms of drug's mode-of-action.

PubMed

Lee, Minho; Han, Sangjo; Chang, Hyeshik; Kwak, Youn-Sig; Weller, David M; Kim, Dongsup

2013-01-01

Yeast deletion-mutant collections have been successfully used to infer the mode-of-action of drugs especially by profiling chemical-genetic and genetic-genetic interactions on a genome-wide scale. Although tens of thousands of those profiles are publicly available, a lack of an accurate method for mining such data has been a major bottleneck for more widespread use of these useful resources. For general usage of those public resources, we designed FitRankDB as a general repository of fitness profiles, and developed a new search algorithm, FitSearch, for identifying the profiles that have a high similarity score with statistical significance for a given fitness profile. We demonstrated that our new repository and algorithm are highly beneficial to researchers who attempting to make hypotheses based on unknown modes-of-action of bioactive compounds, regardless of the types of experiments that have been performed using yeast deletion-mutant collection in various types of different measurement platforms, especially non-chip-based platforms. We showed that our new database and algorithm are useful when attempting to construct a hypothesis regarding the unknown function of a bioactive compound through small-scale experiments with a yeast deletion collection in a platform independent manner. The FitRankDB and FitSearch enhance the ease of searching public yeast fitness profiles and obtaining insights into unknown mechanisms of action of drugs. FitSearch is freely available at http://fitsearch.kaist.ac.kr.

FitSearch: a robust way to interpret a yeast fitness profile in terms of drug's mode-of-action

PubMed Central

2013-01-01

Background Yeast deletion-mutant collections have been successfully used to infer the mode-of-action of drugs especially by profiling chemical-genetic and genetic-genetic interactions on a genome-wide scale. Although tens of thousands of those profiles are publicly available, a lack of an accurate method for mining such data has been a major bottleneck for more widespread use of these useful resources. Results For general usage of those public resources, we designed FitRankDB as a general repository of fitness profiles, and developed a new search algorithm, FitSearch, for identifying the profiles that have a high similarity score with statistical significance for a given fitness profile. We demonstrated that our new repository and algorithm are highly beneficial to researchers who attempting to make hypotheses based on unknown modes-of-action of bioactive compounds, regardless of the types of experiments that have been performed using yeast deletion-mutant collection in various types of different measurement platforms, especially non-chip-based platforms. Conclusions We showed that our new database and algorithm are useful when attempting to construct a hypothesis regarding the unknown function of a bioactive compound through small-scale experiments with a yeast deletion collection in a platform independent manner. The FitRankDB and FitSearch enhance the ease of searching public yeast fitness profiles and obtaining insights into unknown mechanisms of action of drugs. FitSearch is freely available at http://fitsearch.kaist.ac.kr. PMID:23368702

Metabolism, growth, and the energetic definition of fitness: a quantitative genetic study in the land snail Cornu aspersum.

PubMed

Bruning, Andrea; Gaitán-Espitia, Juan Diego; González, Avia; Bartheld, José Luis; Nespolo, Roberto F

2013-01-01

Life-history evolution-the way organisms allocate time and energy to reproduction, survival, and growth-is a central question in evolutionary biology. One of its main tenets, the allocation principle, predicts that selection will reduce energy costs of maintenance in order to divert energy to survival and reproduction. The empirical support for this principle is the existence of a negative relationship between fitness and metabolic rate, which has been observed in some ectotherms. In juvenile animals, a key function affecting fitness is growth rate, since fast growers will reproduce sooner and maximize survival. In principle, design constraints dictate that growth rate cannot be reduced without affecting maintenance costs. Hence, it is predicted that juveniles will show a positive relationship between fitness (growth rate) and metabolic rate, contrarily to what has been observed in adults. Here we explored this problem using land snails (Cornu aspersum). We estimated the additive genetic variance-covariance matrix for growth and standard metabolic rate (SMR; rate of CO2 production) using 34 half-sibling families. We measured eggs, hatchlings, and juveniles in 208 offspring that were isolated right after egg laying (i.e., minimizing maternal and common environmental variance). Surprisingly, our results showed that additive genetic effects (narrow-sense heritabilities, h(2)) and additive genetic correlations (rG) were small and nonsignificant. However, the nonadditive proportion of phenotypic variances and correlations (rC) were unexpectedly large and significant. In fact, nonadditive genetic effects were positive for growth rate and SMR ([Formula: see text]; [Formula: see text]), supporting the idea that fitness (growth rate) cannot be maximized without incurring maintenance costs. Large nonadditive genetic variances could result as a consequence of selection eroding the additive genetic component, which suggests that past selection could have produced nonadditive genetic correlation. It is predicted that this correlation is reduced when adulthood is attained and selection starts to promote the reduction in metabolic rate.

Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

PubMed

Blanquart, François; Wymant, Chris; Cornelissen, Marion; Gall, Astrid; Bakker, Margreet; Bezemer, Daniela; Hall, Matthew; Hillebregt, Mariska; Ong, Swee Hoe; Albert, Jan; Bannert, Norbert; Fellay, Jacques; Fransen, Katrien; Gourlay, Annabelle J; Grabowski, M Kate; Gunsenheimer-Bartmeyer, Barbara; Günthard, Huldrych F; Kivelä, Pia; Kouyos, Roger; Laeyendecker, Oliver; Liitsola, Kirsi; Meyer, Laurence; Porter, Kholoud; Ristola, Matti; van Sighem, Ard; Vanham, Guido; Berkhout, Ben; Kellam, Paul; Reiss, Peter; Fraser, Christophe

2017-06-01

HIV-1 set-point viral load-the approximately stable value of viraemia in the first years of chronic infection-is a strong predictor of clinical outcome and is highly variable across infected individuals. To better understand HIV-1 pathogenesis and the evolution of the viral population, we must quantify the heritability of set-point viral load, which is the fraction of variation in this phenotype attributable to viral genetic variation. However, current estimates of heritability vary widely, from 6% to 59%. Here we used a dataset of 2,028 seroconverters infected between 1985 and 2013 from 5 European countries (Belgium, Switzerland, France, the Netherlands and the United Kingdom) and estimated the heritability of set-point viral load at 31% (CI 15%-43%). Specifically, heritability was measured using models of character evolution describing how viral load evolves on the phylogeny of whole-genome viral sequences. In contrast to previous studies, (i) we measured viral loads using standardized assays on a sample collected in a strict time window of 6 to 24 months after infection, from which the viral genome was also sequenced; (ii) we compared 2 models of character evolution, the classical "Brownian motion" model and another model ("Ornstein-Uhlenbeck") that includes stabilising selection on viral load; (iii) we controlled for covariates, including age and sex, which may inflate estimates of heritability; and (iv) we developed a goodness of fit test based on the correlation of viral loads in cherries of the phylogenetic tree, showing that both models of character evolution fit the data well. An overall heritability of 31% (CI 15%-43%) is consistent with other studies based on regression of viral load in donor-recipient pairs. Thus, about a third of variation in HIV-1 virulence is attributable to viral genetic variation.

Parasites and deleterious mutations: interactions influencing the evolutionary maintenance of sex.

PubMed

Park, A W; Jokela, J; Michalakis, Y

2010-05-01

The restrictive assumptions associated with purely genetic and purely ecological mechanisms suggest that neither of the two forces, in isolation, can offer a general explanation for the evolutionary maintenance of sex. Consequently, attention has turned to pluralistic models (i.e. models that apply both ecological and genetic mechanisms). Existing research has shown that combining mutation accumulation and parasitism allows restrictive assumptions about genetic and parasite parameter values to be relaxed while still predicting the maintenance of sex. However, several empirical studies have shown that deleterious mutations and parasitism can reduce fitness to a greater extent than would be expected if the two acted independently. We show how interactions between these genetic and ecological forces can completely reverse predictions about the evolution of reproductive modes. Moreover, we demonstrate that synergistic interactions between infection and deleterious mutations can render sex evolutionarily stable even when there is antagonistic epistasis among deleterious mutations, thereby widening the conditions for the evolutionary maintenance of sex.

Effective utilization of genetic information for athletes and coaches: focus on ACTN3 R577X polymorphism

PubMed Central

Kikuchi, Naoki; Nakazato, Koichi

2015-01-01

Training variants (type, intensity, and duration of exercise) can be selected according to individual aims and fitness assessment. Recently, various methods of resistance and endurance training have been used for muscle hypertrophy and VO2max improvement. Although several genetic variants are associated with elite athletic performance and muscle phenotypes, genetic background has not been used as variant for physical training. ACTN3 R577X is a well-studied genetic polymorphism. It is the only genotype associated with elite athletic performance in multiple cohorts. This association is strongly supported by mechanistic data from an Actn3-knockout mouse model. In this review, possible guidelines are discussed for effective utilization of ACTN3 R577X polymorphism for physical training. PMID:26526670

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

PubMed

Yang, Ye; Christensen, Ole F; Sorensen, Daniel

2011-02-01

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

Genetic and environmental bases of the interplay between magical ideation and personality.

PubMed

Brambilla, Paolo; Fagnani, Corrado; Cecchetto, Filippo; Medda, Emanuela; Bellani, Marcella; Salemi, Miriam; Picardi, Angelo; Stazi, Maria Antonietta

2014-02-28

Sub-threshold psychotic symptoms are quite commonly present in general population. Among these, Magical Ideation (MI) has been proved to be a valid predictor of psychosis. However, the genetic and environmental influences on the interplay between MI and personality have not fully been explored. A total of 534 adult twins from the population-based Italian Twin Register were assessed for MI using the MI Scale (MIS) and for personality with the temperament and character inventory (TCI). A Multivariate Cholesky model was applied with Mx statistical program. The best-fitting model showed that additive genetic and unshared environmental factors explain approximately the same proportion of variance in MI, whereas a less strong genetic influence on personality traits emerged. Relevant correlations between MI and specific personality traits (novelty seeking, cooperativeness, self-directedness, self-transcendence) were found, suggesting shared influences for MI and these traits. Both genetic and environmental factors explained these correlations, with genetic factors playing a predominant role. Moderate-to-substantial genetic effects on MI and personality were found. Shared genetic and environmental effects underlie the phenotypic correlation between MI (psychosis-proneness) and personality traits, i.e. self-directedness (negative association) and self-transcendence (positive association), potentially representing predictive markers of psychosis liability related to schizotypy and personality. © 2013 Published by Elsevier Ireland Ltd.

Artificial Neural Network Modeling and Genetic Algorithm Optimization for Cadmium Removal from Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron (nZVI/rGO) Composites

PubMed Central

Fan, Mingyi; Li, Tongjun; Hu, Jiwei; Cao, Rensheng; Wei, Xionghui; Shi, Xuedan; Ruan, Wenqian

2017-01-01

Reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) composites were synthesized in the present study by chemical deposition method and were then characterized by various methods, such as Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). The nZVI/rGO composites prepared were utilized for Cd(II) removal from aqueous solutions in batch mode at different initial Cd(II) concentrations, initial pH values, contact times, and operating temperatures. Response surface methodology (RSM) and artificial neural network hybridized with genetic algorithm (ANN-GA) were used for modeling the removal efficiency of Cd(II) and optimizing the four removal process variables. The average values of prediction errors for the RSM and ANN-GA models were 6.47% and 1.08%. Although both models were proven to be reliable in terms of predicting the removal efficiency of Cd(II), the ANN-GA model was found to be more accurate than the RSM model. In addition, experimental data were fitted to the Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) isotherms. It was found that the Cd(II) adsorption was best fitted to the Langmuir isotherm. Examination on thermodynamic parameters revealed that the removal process was spontaneous and exothermic in nature. Furthermore, the pseudo-second-order model can better describe the kinetics of Cd(II) removal with a good R2 value than the pseudo-first-order model. PMID:28772901

Artificial Neural Network Modeling and Genetic Algorithm Optimization for Cadmium Removal from Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron (nZVI/rGO) Composites.

PubMed

Fan, Mingyi; Li, Tongjun; Hu, Jiwei; Cao, Rensheng; Wei, Xionghui; Shi, Xuedan; Ruan, Wenqian

2017-05-17

Reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) composites were synthesized in the present study by chemical deposition method and were then characterized by various methods, such as Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). The nZVI/rGO composites prepared were utilized for Cd(II) removal from aqueous solutions in batch mode at different initial Cd(II) concentrations, initial pH values, contact times, and operating temperatures. Response surface methodology (RSM) and artificial neural network hybridized with genetic algorithm (ANN-GA) were used for modeling the removal efficiency of Cd(II) and optimizing the four removal process variables. The average values of prediction errors for the RSM and ANN-GA models were 6.47% and 1.08%. Although both models were proven to be reliable in terms of predicting the removal efficiency of Cd(II), the ANN-GA model was found to be more accurate than the RSM model. In addition, experimental data were fitted to the Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) isotherms. It was found that the Cd(II) adsorption was best fitted to the Langmuir isotherm. Examination on thermodynamic parameters revealed that the removal process was spontaneous and exothermic in nature. Furthermore, the pseudo-second-order model can better describe the kinetics of Cd(II) removal with a good R² value than the pseudo-first-order model.

Discrete mixture modeling to address genetic heterogeneity in time-to-event regression

PubMed Central

Eng, Kevin H.; Hanlon, Bret M.

2014-01-01

Motivation: Time-to-event regression models are a critical tool for associating survival time outcomes with molecular data. Despite mounting evidence that genetic subgroups of the same clinical disease exist, little attention has been given to exploring how this heterogeneity affects time-to-event model building and how to accommodate it. Methods able to diagnose and model heterogeneity should be valuable additions to the biomarker discovery toolset. Results: We propose a mixture of survival functions that classifies subjects with similar relationships to a time-to-event response. This model incorporates multivariate regression and model selection and can be fit with an expectation maximization algorithm, we call Cox-assisted clustering. We illustrate a likely manifestation of genetic heterogeneity and demonstrate how it may affect survival models with little warning. An application to gene expression in ovarian cancer DNA repair pathways illustrates how the model may be used to learn new genetic subsets for risk stratification. We explore the implications of this model for censored observations and the effect on genomic predictors and diagnostic analysis. Availability and implementation: R implementation of CAC using standard packages is available at https://gist.github.com/programeng/8620b85146b14b6edf8f Data used in the analysis are publicly available. Contact: kevin.eng@roswellpark.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24532723

Sexually Antagonistic Selection in Human Male Homosexuality

PubMed Central

Camperio Ciani, Andrea; Cermelli, Paolo; Zanzotto, Giovanni

2008-01-01

Several lines of evidence indicate the existence of genetic factors influencing male homosexuality and bisexuality. In spite of its relatively low frequency, the stable permanence in all human populations of this apparently detrimental trait constitutes a puzzling ‘Darwinian paradox’. Furthermore, several studies have pointed out relevant asymmetries in the distribution of both male homosexuality and of female fecundity in the parental lines of homosexual vs. heterosexual males. A number of hypotheses have attempted to give an evolutionary explanation for the long-standing persistence of this trait, and for its asymmetric distribution in family lines; however a satisfactory understanding of the population genetics of male homosexuality is lacking at present. We perform a systematic mathematical analysis of the propagation and equilibrium of the putative genetic factors for male homosexuality in the population, based on the selection equation for one or two diallelic loci and Bayesian statistics for pedigree investigation. We show that only the two-locus genetic model with at least one locus on the X chromosome, and in which gene expression is sexually antagonistic (increasing female fitness but decreasing male fitness), accounts for all known empirical data. Our results help clarify the basic evolutionary dynamics of male homosexuality, establishing this as a clearly ascertained sexually antagonistic human trait. PMID:18560521

Comparative Study on Prediction Effects of Short Fatigue Crack Propagation Rate by Two Different Calculation Methods

NASA Astrophysics Data System (ADS)

Yang, Bing; Liao, Zhen; Qin, Yahang; Wu, Yayun; Liang, Sai; Xiao, Shoune; Yang, Guangwu; Zhu, Tao

2017-05-01

To describe the complicated nonlinear process of the fatigue short crack evolution behavior, especially the change of the crack propagation rate, two different calculation methods are applied. The dominant effective short fatigue crack propagation rates are calculated based on the replica fatigue short crack test with nine smooth funnel-shaped specimens and the observation of the replica films according to the effective short fatigue cracks principle. Due to the fast decay and the nonlinear approximation ability of wavelet analysis, the self-learning ability of neural network, and the macroscopic searching and global optimization of genetic algorithm, the genetic wavelet neural network can reflect the implicit complex nonlinear relationship when considering multi-influencing factors synthetically. The effective short fatigue cracks and the dominant effective short fatigue crack are simulated and compared by the Genetic Wavelet Neural Network. The simulation results show that Genetic Wavelet Neural Network is a rational and available method for studying the evolution behavior of fatigue short crack propagation rate. Meanwhile, a traditional data fitting method for a short crack growth model is also utilized for fitting the test data. It is reasonable and applicable for predicting the growth rate. Finally, the reason for the difference between the prediction effects by these two methods is interpreted.

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models.

PubMed

Chen, Han; Wang, Chaolong; Conomos, Matthew P; Stilp, Adrienne M; Li, Zilin; Sofer, Tamar; Szpiro, Adam A; Chen, Wei; Brehm, John M; Celedón, Juan C; Redline, Susan; Papanicolaou, George J; Thornton, Timothy A; Laurie, Cathy C; Rice, Kenneth; Lin, Xihong

2016-04-07

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM's constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genetic Architecture of Nest Building in Mice LG/J × SM/J

PubMed Central

Sauce, Bruno; de Brito, Reinaldo Alves; Peripato, Andrea Cristina

2012-01-01

Maternal care is critical to offspring growth and survival, which is greatly improved by building an effective nest. Some suggest that genetic variation and underlying genetic effects differ between fitness-related traits and other phenotypes. We investigated the genetic architecture of a fitness-related trait, nest building, in F2 female mice intercrossed from inbred strains SM/J and LG/J using a QTL analysis for six related nest phenotypes (Presence and Structure pre- and postpartum, prepartum Material Used and postpartum Temperature). We found 15 direct-effect QTLs explaining from 4 to 13% of the phenotypic variation in nest building, mostly with non-additive effect. Epistatic analyses revealed 71 significant epistatic interactions which together explain from 28.4 to 75.5% of the variation, indicating an important role for epistasis in the adaptive process of nest building behavior in mice. Our results suggest a genetic architecture with small direct effects and a larger number of epistatic interactions as expected for fitness-related phenotypes. PMID:22654894

Tests of species-specific models reveal the importance of drought in postglacial range shifts of a Mediterranean-climate tree: insights from integrative distributional, demographic and coalescent modelling and ABC model selection.

PubMed

Bemmels, Jordan B; Title, Pascal O; Ortego, Joaquín; Knowles, L Lacey

2016-10-01

Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species-specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade-offs in functional traits, and local-scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade-off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common. © 2016 John Wiley & Sons Ltd.

The effects of variable biome distribution on global climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noever, D.A.; Brittain, A.; Matsos, H.C.

1996-12-31

In projecting climatic adjustments to anthropogenically elevated atmospheric carbon dioxide, most global climate models fix biome distribution to current geographic conditions. The authors develop a model that examines the albedo-related effects of biome distribution on global temperature. The model was tested on historical biome changes since 1860 and the results fit both the observed trend and order of magnitude change in global temperature. Once backtested in this way on historical data, the model is then used to generate an optimized future biome distribution which minimizes projected greenhouse effects on global temperature. Because of the complexity of this combinatorial search anmore » artificial intelligence method, the genetic algorithm, was employed. The genetic algorithm assigns various biome distributions to the planet, then adjusts their percentage area and albedo effects to regulate or moderate temperature changes.« less

The etiology of associations between negative emotionality and childhood externalizing disorders.

PubMed

Singh, Amber L; Waldman, Irwin D

2010-05-01

Despite consistent documentation of associations between childhood negative emotionality and externalizing psychopathology, few genetically informative studies have investigated the etiology of that association. The goal of the current study was to delineate the etiology of the covariation of negative emotionality and childhood externalizing problems (e.g., oppositional defiant disorder, conduct disorder, inattention, and hyperactivity/impulsivity). Twin families were recruited from Georgia state birth records and completed parental report questionnaires of negative emotionality and common Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000) child psychiatric disorders. Results suggest both genetic and environmental influences underlying negative emotionality and each externalizing symptom dimension, with additional evidence for sibling competition/rater contrast effects for inattention and hyperactivity/impulsivity. Bivariate model-fitting analyses indicated that a portion of the additive (43%-75%) and nonadditive (26%-100%) genetic influences underlying each symptom dimension was accounted for by the genetic influences underlying negative emotionality. Finally, an independent pathways model examining the etiology of the association between negative emotionality and the externalizing dimensions indicated that a substantial portion of the additive genetic, nonadditive genetic, and nonshared environmental influences underlying externalizing behavior is shared with negative emotionality.

Interactive evolution of camouflage.

PubMed

Reynolds, Craig

2011-01-01

This article presents an abstract computation model of the evolution of camouflage in nature. The 2D model uses evolved textures for prey, a background texture representing the environment, and a visual predator. A human observer, acting as the predator, is shown a cohort of 10 evolved textures overlaid on the background texture. The observer clicks on the five most conspicuous prey to remove ("eat") them. These lower-fitness textures are removed from the population and replaced with newly bred textures. Biological morphogenesis is represented in this model by procedural texture synthesis. Nested expressions of generators and operators form a texture description language. Natural evolution is represented by genetic programming (GP), a variant of the genetic algorithm. GP searches the space of texture description programs for those that appear least conspicuous to the predator.

The effects of quantitative fecundity in the haploid stage on reproductive success and diploid fitness in the aquatic peat moss Sphagnum macrophyllum

PubMed Central

Johnson, M G; Shaw, A J

2016-01-01

A major question in evolutionary biology is how mating patterns affect the fitness of offspring. However, in animals and seed plants it is virtually impossible to investigate the effects of specific gamete genotypes. In bryophytes, haploid gametophytes grow via clonal propagation and produce millions of genetically identical gametes throughout a population. The main goal of this research was to test whether gamete identity has an effect on the fitness of their diploid offspring in a population of the aquatic peat moss Sphagnum macrophyllum. We observed a heavily male-biased sex ratio in gametophyte plants (ramets) and in multilocus microsatellite genotypes (genets). There was a steeper relationship between mating success (number of different haploid mates) and fecundity (number of diploid offspring) for male genets compared with female genets. At the sporophyte level, we observed a weak effect of inbreeding on offspring fitness, but no effect of brood size (number of sporophytes per maternal ramet). Instead, the identities of the haploid male and haploid female parents were significant contributors to variance in fitness of sporophyte offspring in the population. Our results suggest that intrasexual gametophyte/gamete competition may play a role in determining mating success in this population. PMID:26905464

The effects of quantitative fecundity in the haploid stage on reproductive success and diploid fitness in the aquatic peat moss Sphagnum macrophyllum.

PubMed

Johnson, M G; Shaw, A J

2016-06-01

A major question in evolutionary biology is how mating patterns affect the fitness of offspring. However, in animals and seed plants it is virtually impossible to investigate the effects of specific gamete genotypes. In bryophytes, haploid gametophytes grow via clonal propagation and produce millions of genetically identical gametes throughout a population. The main goal of this research was to test whether gamete identity has an effect on the fitness of their diploid offspring in a population of the aquatic peat moss Sphagnum macrophyllum. We observed a heavily male-biased sex ratio in gametophyte plants (ramets) and in multilocus microsatellite genotypes (genets). There was a steeper relationship between mating success (number of different haploid mates) and fecundity (number of diploid offspring) for male genets compared with female genets. At the sporophyte level, we observed a weak effect of inbreeding on offspring fitness, but no effect of brood size (number of sporophytes per maternal ramet). Instead, the identities of the haploid male and haploid female parents were significant contributors to variance in fitness of sporophyte offspring in the population. Our results suggest that intrasexual gametophyte/gamete competition may play a role in determining mating success in this population.

Mitochondrial Variation among the Aymara and the Signatures of Population Expansion in the Central Andes

PubMed Central

BATAI, KEN; WILLIAMS, SLOAN R.

2015-01-01

Objectives The exploitation of marine resources and intensive agriculture led to a marked population increase early in central Andean prehistory. Constant historic and prehistoric population movements also characterize this region. These features undoubtedly affected regional genetic variation, but the exact nature of these effects remains uncertain. Methods Mitochondrial DNA (mtDNA) hypervariable region I sequence variation in 61 Aymara individuals from La Paz, Bolivia, was analyzed and compared to sequences from 47 other South American populations to test hypotheses of whether increased female effective population size and gene flow influenced the mtDNA variation among central Andean populations. Results The Aymara and Quechua were genetically diverse showing evidence of population expansion and large effective population size, and a demographic expansion model fits the mtDNA variation found among central Andean populations well. Estimated migration rates and the results of AMOVA and multidimensional scaling analysis suggest that female gene flow was also an important factor, influencing genetic variation among the central Andeans as well as lowland populations from western South America. mtDNA variation in south central Andes correlated better with geographic proximity than with language, and fit a population continuity model. Conclusion The mtDNA data suggests that the central Andeans experienced population expansion, most likely because of rapid demographic expansion after introduction of intensive agriculture, but roles of female gene flow need to be further explored. PMID:24449040

Evidence of opposing fitness effects of parental heterozygosity and relatedness in a critically endangered marine turtle?

PubMed

Phillips, K P; Jorgensen, T H; Jolliffe, K G; Richardson, D S

2017-11-01

How individual genetic variability relates to fitness is important in understanding evolution and the processes affecting populations of conservation concern. Heterozygosity-fitness correlations (HFCs) have been widely used to study this link in wild populations, where key parameters that affect both variability and fitness, such as inbreeding, can be difficult to measure. We used estimates of parental heterozygosity and genetic similarity ('relatedness') derived from 32 microsatellite markers to explore the relationship between genetic variability and fitness in a population of the critically endangered hawksbill turtle, Eretmochelys imbricata. We found no effect of maternal MLH (multilocus heterozygosity) on clutch size or egg success rate, and no single-locus effects. However, we found effects of paternal MLH and parental relatedness on egg success rate that interacted in a way that may result in both positive and negative effects of genetic variability. Multicollinearity in these tests was within safe limits, and null simulations suggested that the effect was not an artefact of using paternal genotypes reconstructed from large samples of offspring. Our results could imply a tension between inbreeding and outbreeding depression in this system, which is biologically feasible in turtles: female-biased natal philopatry may elevate inbreeding risk and local adaptation, and both processes may be disrupted by male-biased dispersal. Although this conclusion should be treated with caution due to a lack of significant identity disequilibrium, our study shows the importance of considering both positive and negative effects when assessing how variation in genetic variability affects fitness in wild systems. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

The Relationship Between the Genetic and Environmental Influences on Common Externalizing Psychopathology and Mental Wellbeing

PubMed Central

Kendler, Kenneth S.; Myers, John M.; Keyes, Corey L. M.

2012-01-01

To determine the relationship between the genetic and environmental risk factors for externalizing psychopathology and mental wellbeing, we examined detailed measures of emotional, social and psychological wellbeing, and a history of alcohol-related problems and smoking behavior in the last year in 1,386 individual twins from same-sex pairs from the MIDUS national US sample assessed in 1995. Cholesky decomposition analyses were performed with the Mx program. The best fit model contained one highly heritable common externalizing psychopathology factor for both substance use/abuse measures, and one strongly heritable common factor for the three wellbeing measures. Genetic and environmental risk factors for externalizing psychopathology were both negatively associated with levels of mental wellbeing and accounted for, respectively, 7% and 21% of its genetic and environmental influences. Adding internalizing psychopathology assessed in the last year to the model, genetic risk factors unique for externalizing psychopathology were now positively related to levels of mental wellbeing, although accounting for only 5% of the genetic variance. Environmental risk factors unique to externalizing psychopathology continued to be negatively associated with mental wellbeing, accounting for 26% of the environmental variance. When both internalizing psychopathology and externalizing psychopathology are associated with mental wellbeing, the strongest risk factors for low mental wellbeing are genetic factors that impact on both internalizing psychopathology and externalizing psychopathology, and environmental factors unique to externalizing psychopathology. In this model, genetic risk factors for externalizing psychopathology predict, albeit weakly, higher levels of mental wellbeing. PMID:22506307

Genetic and environmental influences on individual differences in emotion regulation and its relation to working memory in toddlerhood.

PubMed

Wang, Manjie; Saudino, Kimberly J

2013-12-01

This is the first study to explore genetic and environmental contributions to individual differences in emotion regulation in toddlers, and the first to examine the genetic and environmental etiology underlying the association between emotion regulation and working memory. In a sample of 304 same-sex twin pairs (140 MZ, 164 DZ) at age 3, emotion regulation was assessed using the Behavior Rating Scale of the Bayley Scales of Infant Development (BRS; Bayley, 1993), and working memory was measured by the visually cued recall (VCR) task (Zelazo, Jacques, Burack, & Frye, 2002) and several memory tasks from the Mental Scale of the BSID. Based on model-fitting analyses, both emotion regulation and working memory were significantly influenced by genetic and nonshared environmental factors. Shared environmental effects were significant for working memory, but not for emotion regulation. Only genetic factors significantly contributed to the covariation between emotion regulation and working memory.

Genetic and Environmental Influences on Individual Differences in Emotion Regulation and Its Relation to Working Memory in Toddlerhood

PubMed Central

Wang, Manjie; Saudino, Kimberly J.

2014-01-01

This is the first study to explore genetic and environmental contributions to individual differences in emotion regulation in toddlers, and the first to examine the genetic and environmental etiology underlying the association between emotion regulation and working memory. In a sample of 304 same-sex twin pairs (140 MZ, 164 DZ) at age 3, emotion regulation was assessed using the Behavior Rating Scale of the Bayley Scales of Infant Development (BRS; Bayley, 1993), and working memory was measured by the visually cued recall (VCR) task (Zelazo et al., 2002) and several memory tasks from the Mental Scale of BSID. Based on model-fitting analyses, both emotion regulation and working memory were significantly influenced by genetic and nonshared environmental factors. Shared environmental effects were significant for working memory, but not for emotion regulation. Only genetic factors significantly contributed to the covariation between emotion regulation and working memory. PMID:24098922

Gene flow from domesticated species to wild relatives: migration load in a model of multivariate selection.

PubMed

Tufto, Jarle

2010-01-01

Domesticated species frequently spread their genes into populations of wild relatives through interbreeding. The domestication process often involves artificial selection for economically desirable traits. This can lead to an indirect response in unknown correlated traits and a reduction in fitness of domesticated individuals in the wild. Previous models for the effect of gene flow from domesticated species to wild relatives have assumed that evolution occurs in one dimension. Here, I develop a quantitative genetic model for the balance between migration and multivariate stabilizing selection. Different forms of correlational selection consistent with a given observed ratio between average fitness of domesticated and wild individuals offsets the phenotypic means at migration-selection balance away from predictions based on simpler one-dimensional models. For almost all parameter values, correlational selection leads to a reduction in the migration load. For ridge selection, this reduction arises because the distance the immigrants deviates from the local optimum in effect is reduced. For realistic parameter values, however, the effect of correlational selection on the load is small, suggesting that simpler one-dimensional models may still be adequate in terms of predicting mean population fitness and viability.

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to that of the complex model including epistatic effects. Conclusions This simulation study showed that the fBayesB approach is convenient for genetic value prediction. Jointly estimating additive and non-additive effects (especially dominance) has reasonable impact on the accuracy of prediction and the proportion of genetic variation assigned to the additive genetic source. PMID:21867519

The role of crossover operator in evolutionary-based approach to the problem of genetic code optimization.

PubMed

Błażej, Paweł; Wnȩtrzak, Małgorzata; Mackiewicz, Paweł

2016-12-01

One of theories explaining the present structure of canonical genetic code assumes that it was optimized to minimize harmful effects of amino acid replacements resulting from nucleotide substitutions and translational errors. A way to testify this concept is to find the optimal code under given criteria and compare it with the canonical genetic code. Unfortunately, the huge number of possible alternatives makes it impossible to find the optimal code using exhaustive methods in sensible time. Therefore, heuristic methods should be applied to search the space of possible solutions. Evolutionary algorithms (EA) seem to be ones of such promising approaches. This class of methods is founded both on mutation and crossover operators, which are responsible for creating and maintaining the diversity of candidate solutions. These operators possess dissimilar characteristics and consequently play different roles in the process of finding the best solutions under given criteria. Therefore, the effective searching for the potential solutions can be improved by applying both of them, especially when these operators are devised specifically for a given problem. To study this subject, we analyze the effectiveness of algorithms for various combinations of mutation and crossover probabilities under three models of the genetic code assuming different restrictions on its structure. To achieve that, we adapt the position based crossover operator for the most restricted model and develop a new type of crossover operator for the more general models. The applied fitness function describes costs of amino acid replacement regarding their polarity. Our results indicate that the usage of crossover operators can significantly improve the quality of the solutions. Moreover, the simulations with the crossover operator optimize the fitness function in the smaller number of generations than simulations without this operator. The optimal genetic codes without restrictions on their structure minimize the costs about 2.7 times better than the canonical genetic code. Interestingly, the optimal codes are dominated by amino acids characterized by polarity close to its average value for all amino acids. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Modeling the two-locus architecture of divergent pollinator adaptation: how variation in SAD paralogs affects fitness and evolutionary divergence in sexually deceptive orchids.

PubMed

Xu, Shuqing; Schlüter, Philipp M

2015-01-01

Divergent selection by pollinators can bring about strong reproductive isolation via changes at few genes of large effect. This has recently been demonstrated in sexually deceptive orchids, where studies (1) quantified the strength of reproductive isolation in the field; (2) identified genes that appear to be causal for reproductive isolation; and (3) demonstrated selection by analysis of natural variation in gene sequence and expression. In a group of closely related Ophrys orchids, specific floral scent components, namely n-alkenes, are the key floral traits that control specific pollinator attraction by chemical mimicry of insect sex pheromones. The genetic basis of species-specific differences in alkene production mainly lies in two biosynthetic genes encoding stearoyl-acyl carrier protein desaturases (SAD) that are associated with floral scent variation and reproductive isolation between closely related species, and evolve under pollinator-mediated selection. However, the implications of this genetic architecture of key floral traits on the evolutionary processes of pollinator adaptation and speciation in this plant group remain unclear. Here, we expand on these recent findings to model scenarios of adaptive evolutionary change at SAD2 and SAD5, their effects on plant fitness (i.e., offspring number), and the dynamics of speciation. Our model suggests that the two-locus architecture of reproductive isolation allows for rapid sympatric speciation by pollinator shift; however, the likelihood of such pollinator-mediated speciation is asymmetric between the two orchid species O. sphegodes and O. exaltata due to different fitness effects of their predominant SAD2 and SAD5 alleles. Our study not only provides insight into pollinator adaptation and speciation mechanisms of sexually deceptive orchids but also demonstrates the power of applying a modeling approach to the study of pollinator-driven ecological speciation.

Genetic structured antedependence and random regression models applied to the longitudinal feed conversion ratio in growing Large White pigs.

PubMed

Huynh-Tran, V H; Gilbert, H; David, I

2017-11-01

The objective of the present study was to compare a random regression model, usually used in genetic analyses of longitudinal data, with the structured antedependence (SAD) model to study the longitudinal feed conversion ratio (FCR) in growing Large White pigs and to propose criteria for animal selection when used for genetic evaluation. The study was based on data from 11,790 weekly FCR measures collected on 1,186 Large White male growing pigs. Random regression (RR) using orthogonal polynomial Legendre and SAD models was used to estimate genetic parameters and predict FCR-based EBV for each of the 10 wk of the test. The results demonstrated that the best SAD model (1 order of antedependence of degree 2 and a polynomial of degree 2 for the innovation variance for the genetic and permanent environmental effects, i.e., 12 parameters) provided a better fit for the data than RR with a quadratic function for the genetic and permanent environmental effects (13 parameters), with Bayesian information criteria values of -10,060 and -9,838, respectively. Heritabilities with the SAD model were higher than those of RR over the first 7 wk of the test. Genetic correlations between weeks were higher than 0.68 for short intervals between weeks and decreased to 0.08 for the SAD model and -0.39 for RR for the longest intervals. These differences in genetic parameters showed that, contrary to the RR approach, the SAD model does not suffer from border effect problems and can handle genetic correlations that tend to 0. Summarized breeding values were proposed for each approach as linear combinations of the individual weekly EBV weighted by the coefficients of the first or second eigenvector computed from the genetic covariance matrix of the additive genetic effects. These summarized breeding values isolated EBV trajectories over time, capturing either the average general value or the slope of the trajectory. Finally, applying the SAD model over a reduced period of time suggested that similar selection choices would result from the use of the records from the first 8 wk of the test. To conclude, the SAD model performed well for the genetic evaluation of longitudinal phenotypes.

Choosing Fitness-Enhancing Innovations Can Be Detrimental under Fluctuating Environments

PubMed Central

Xue, Julian Z.; Costopoulos, Andre; Guichard, Frederic

2011-01-01

The ability to predict the consequences of one's behavior in a particular environment is a mechanism for adaptation. In the absence of any cost to this activity, we might expect agents to choose behaviors that maximize their fitness, an example of directed innovation. This is in contrast to blind mutation, where the probability of becoming a new genotype is independent of the fitness of the new genotypes. Here, we show that under environments punctuated by rapid reversals, a system with both genetic and cultural inheritance should not always maximize fitness through directed innovation. This is because populations highly accurate at selecting the fittest innovations tend to over-fit the environment during its stable phase, to the point that a rapid environmental reversal can cause extinction. A less accurate population, on the other hand, can track long term trends in environmental change, keeping closer to the time-average of the environment. We use both analytical and agent-based models to explore when this mechanism is expected to occur. PMID:22125601

The dynamics of sex ratio evolution: from the gene perspective to multilevel selection.

PubMed

Argasinski, Krzysztof

2013-01-01

The new dynamical game theoretic model of sex ratio evolution emphasizes the role of males as passive carriers of sex ratio genes. This shows inconsistency between population genetic models of sex ratio evolution and classical strategic models. In this work a novel technique of change of coordinates will be applied to the new model. This will reveal new aspects of the modelled phenomenon which cannot be shown or proven in the original formulation. The underlying goal is to describe the dynamics of selection of particular genes in the entire population, instead of in the same sex subpopulation, as in the previous paper and earlier population genetics approaches. This allows for analytical derivation of the unbiased strategic model from the model with rigorous non-simplified genetics. In effect, an alternative system of replicator equations is derived. It contains two subsystems: the first describes changes in gene frequencies (this is an alternative unbiased formalization of the Fisher-Dusing argument), whereas the second describes changes in the sex ratios in subpopulations of carriers of genes for each strategy. An intriguing analytical result of this work is that the fitness of a gene depends on the current sex ratio in the subpopulation of its carriers, not on the encoded individual strategy. Thus, the argument of the gene fitness function is not constant but is determined by the trajectory of the sex ratio among carriers of that gene. This aspect of the modelled phenomenon cannot be revealed by the static analysis. Dynamics of the sex ratio among gene carriers is driven by a dynamic "tug of war" between female carriers expressing the encoded strategic trait value and random partners of male carriers expressing the average population strategy (a primary sex ratio). This mechanism can be called "double-level selection". Therefore, gene interest perspective leads to multi-level selection.

Genome dynamics and its impact on evolution of Escherichia coli.

PubMed

Dobrindt, Ulrich; Chowdary, M Geddam; Krumbholz, G; Hacker, J

2010-08-01

The Escherichia coli genome consists of a conserved part, the so-called core genome, which encodes essential cellular functions and of a flexible, strain-specific part. Genes that belong to the flexible genome code for factors involved in bacterial fitness and adaptation to different environments. Adaptation includes increase in fitness and colonization capacity. Pathogenic as well as non-pathogenic bacteria carry mobile and accessory genetic elements such as plasmids, bacteriophages, genomic islands and others, which code for functions required for proper adaptation. Escherichia coli is a very good example to study the interdependency of genome architecture and lifestyle of bacteria. Thus, these species include pathogenic variants as well as commensal bacteria adapted to different host organisms. In Escherichia coli, various genetic elements encode for pathogenicity factors as well as factors, which increase the fitness of non-pathogenic bacteria. The processes of genome dynamics, such as gene transfer, genome reduction, rearrangements as well as point mutations contribute to the adaptation of the bacteria into particular environments. Using Escherichia coli model organisms, such as uropathogenic strain 536 or commensal strain Nissle 1917, we studied mechanisms of genome dynamics and discuss these processes in the light of the evolution of microbes.

The effect of newly induced mutations on the fitness of genotypes and populations of yeast (Saccharomyces cerevisiae).

PubMed

Orthen, E; Lange, P; Wöhrmann, K

1984-12-01

This paper analyses the fate of artificially induced mutations and their importance to the fitness of populations of the yeast, Saccharomyces cerevisiae, an increasingly important model organism in population genetics. Diploid strains, treated with UV and EMS, were cultured asexually for approximately 540 generations and under conditions where the asexual growth was interrupted by a sexual phase. Growth rates of 100 randomly sampled diploid clones were estimated at the beginning and at the end of the experiment. After the induction of sporulation the growth rates of 100 randomly sampled spores were measured. UV and EMS treatment decreases the average growth rate of the clones significantly but increases the variability in comparison to the untreated control. After selection over approximately 540 generations, variability in growth rates was reduced to that of the untreated control. No increase in mean population fitness was observed. However, the results show that after selection there still exists a large amount of hidden genetic variability in the populations which is revealed when the clones are cultivated in environments other than those in which selection took place. A sexual phase increased the reduction of the induced variability.

Genetically distinct populations of northern shrimp, Pandalus borealis, in the North Atlantic: adaptation to different temperatures as an isolation factor.

PubMed

Jorde, Per Erik; Søvik, Guldborg; Westgaard, Jon-Ivar; Albretsen, Jon; André, Carl; Hvingel, Carsten; Johansen, Torild; Sandvik, Anne Dagrun; Kingsley, Michael; Jørstad, Knut Eirik

2015-04-01

The large-scale population genetic structure of northern shrimp, Pandalus borealis, was investigated over the species' range in the North Atlantic, identifying multiple genetically distinct groups. Genetic divergence among sample localities varied among 10 microsatellite loci (range: FST = -0.0002 to 0.0475) with a highly significant average (FST = 0.0149; P < 0.0001). In contrast, little or no genetic differences were observed among temporal replicates from the same localities (FST = 0.0004; P = 0.33). Spatial genetic patterns were compared to geographic distances, patterns of larval drift obtained through oceanographic modelling, and temperature differences, within a multiple linear regression framework. The best-fit model included all three factors and explained approximately 29% of all spatial genetic divergence. However, geographic distance and larval drift alone had only minor effects (2.5-4.7%) on large-scale genetic differentiation patterns, whereas bottom temperature differences explained most (26%). Larval drift was found to promote genetic homogeneity in parts of the study area with strong currents, but appeared ineffective across large temperature gradients. These findings highlight the breakdown of gene flow in a species with a long pelagic larval phase (up to 3 months) and indicate a role for local adaptation to temperature conditions in promoting evolutionary diversification and speciation in the marine environment. © 2015 John Wiley & Sons Ltd.

QTL affecting fitness of hybrids between wild and cultivated soybeans in experimental fields

PubMed Central

Kuroda, Yosuke; Kaga, Akito; Tomooka, Norihiko; Yano, Hiroshi; Takada, Yoshitake; Kato, Shin; Vaughan, Duncan

2013-01-01

The objective of this study was to identify quantitative trait loci (QTL) affecting fitness of hybrids between wild soybean (Glycine soja) and cultivated soybean (Glycine max). Seed dormancy and seed number, both of which are important for fitness, were evaluated by testing artificial hybrids of G. soja × G. max in a multiple-site field trial. Generally, the fitness of the F1 hybrids and hybrid derivatives from self-pollination was lower than that of G. soja due to loss of seed dormancy, whereas the fitness of hybrid derivatives with higher proportions of G. soja genetic background was comparable with that of G. soja. These differences were genetically dissected into QTL for each population. Three QTLs for seed dormancy and one QTL for total seed number were detected in the F2 progenies of two diverse cross combinations. At those four QTLs, the G. max alleles reduced seed number and severely reduced seed survival during the winter, suggesting that major genes acquired during soybean adaptation to cultivation have a selective disadvantage in natural habitats. In progenies with a higher proportion of G. soja genetic background, the genetic effects of the G. max alleles were not expressed as phenotypes because the G. soja alleles were dominant over the G. max alleles. Considering the highly inbreeding nature of these species, most hybrid derivatives would disappear quickly in early self-pollinating generations in natural habitats because of the low fitness of plants carrying G. max alleles. PMID:23919159

A Segregating Inversion Generates Fitness Variation in Yellow Monkeyflower (Mimulus guttatus)

PubMed Central

Fishman, Lila; Kelly, John K.; Willis, John H.

2016-01-01

Polymorphic chromosomal rearrangements can bind hundreds of genes into single genetic loci with diverse effects. Rearrangements are often associated with local adaptation and speciation and may also be an important component of genetic variation within populations. We genetically and phenotypically characterize a segregating inversion (inv6) in the Iron Mountain (IM) population of Mimulus guttatus (yellow monkeyflower). We initially mapped inv6 as a region of recombination suppression in three F2 populations resulting from crosses among IM plants. In each case, the F1 parent was heterozygous for a derived haplotype, homogenous across markers spanning over 5 Mb of chromsome 6. In the three F2 populations, inv6 reduced male and female fitness components. In addition, inv6 carriers suffered an ∼30% loss of pollen viability in the field. Despite these costs, inv6 exists at moderate frequency (∼8%) in the natural population, suggesting counterbalancing fitness benefits that maintain the polymorphism. Across 4 years of monitoring in the field, inv6 had an overall significant positive effect on seed production (lifetime female fitness) of carriers. This benefit was particularly strong in harsh years and may be mediated (in part) by strong positive effects on flower production. These data suggest that opposing fitness effects maintain an intermediate frequency, and as a consequence, inv6 generates inbreeding depression and high genetic variance. We discuss these findings in relation to the theory of inbreeding depression and the maintenance of fitness variation. PMID:26868767

Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

PubMed

van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

2014-03-01

For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (< 3 km), we calculated several measures of landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

Utility of genetic and non-genetic risk factors in predicting coronary heart disease in Singaporean Chinese.

PubMed

Chang, Xuling; Salim, Agus; Dorajoo, Rajkumar; Han, Yi; Khor, Chiea-Chuen; van Dam, Rob M; Yuan, Jian-Min; Koh, Woon-Puay; Liu, Jianjun; Goh, Daniel Yt; Wang, Xu; Teo, Yik-Ying; Friedlander, Yechiel; Heng, Chew-Kiat

2017-01-01

Background Although numerous phenotype based equations for predicting risk of 'hard' coronary heart disease are available, data on the utility of genetic information for such risk prediction is lacking in Chinese populations. Design Case-control study nested within the Singapore Chinese Health Study. Methods A total of 1306 subjects comprising 836 men (267 incident cases and 569 controls) and 470 women (128 incident cases and 342 controls) were included. A Genetic Risk Score comprising 156 single nucleotide polymorphisms that have been robustly associated with coronary heart disease or its risk factors ( p < 5 × 10 -8 ) in at least two independent cohorts of genome-wide association studies was built. For each gender, three base models were used: recalibrated Adult Treatment Panel III (ATPIII) Model (M 1 ); ATP III model fitted using Singapore Chinese Health Study data (M 2 ) and M 3 : M 2 + C-reactive protein + creatinine. Results The Genetic Risk Score was significantly associated with incident 'hard' coronary heart disease ( p for men: 1.70 × 10 -10 -1.73 × 10 -9 ; p for women: 0.001). The inclusion of the Genetic Risk Score in the prediction models improved discrimination in both genders (c-statistics: 0.706-0.722 vs. 0.663-0.695 from base models for men; 0.788-0.790 vs. 0.765-0.773 for women). In addition, the inclusion of the Genetic Risk Score also improved risk classification with a net gain of cases being reclassified to higher risk categories (men: 12.4%-16.5%; women: 10.2% (M 3 )), while not significantly reducing the classification accuracy in controls. Conclusions The Genetic Risk Score is an independent predictor for incident 'hard' coronary heart disease in our ethnic Chinese population. Inclusion of genetic factors into coronary heart disease prediction models could significantly improve risk prediction performance.

A longitudinal twin study of physical aggression during early childhood: evidence for a developmentally dynamic genome.

PubMed

Lacourse, E; Boivin, M; Brendgen, M; Petitclerc, A; Girard, A; Vitaro, F; Paquin, S; Ouellet-Morin, I; Dionne, G; Tremblay, R E

2014-09-01

Physical aggression (PA) tends to have its onset in infancy and to increase rapidly in frequency. Very little is known about the genetic and environmental etiology of PA development during early childhood. We investigated the temporal pattern of genetic and environmental etiology of PA during this crucial developmental period. Participants were 667 twin pairs, including 254 monozygotic and 413 dizygotic pairs, from the ongoing longitudinal Quebec Newborn Twin Study. Maternal reports of PA were obtained from three waves of data at 20, 32 and 50 months. These reports were analysed using a biometric Cholesky decomposition and linear latent growth curve model. The best-fitting Cholesky model revealed developmentally dynamic effects, mostly genetic attenuation and innovation. The contribution of genetic factors at 20 months substantially decreased over time, while new genetic effects appeared later on. The linear latent growth curve model revealed a significant moderate increase in PA from 20 to 50 months. Two separate sets of uncorrelated genetic factors accounted for the variation in initial level and growth rate. Non-shared and shared environments had no effect on the stability, initial status and growth rate in PA. Genetic factors underlie PA frequency and stability during early childhood; they are also responsible for initial status and growth rate in PA. The contribution of shared environment is modest, and perhaps limited, as it appears only at 50 months. Future research should investigate the complex nature of these dynamic genetic factors through genetic-environment correlation (r GE) and interaction (G×E) analyses.

Learning genetic inquiry through the use, revision, and justification of explanatory models

NASA Astrophysics Data System (ADS)

Cartier, Jennifer Lorraine

Central to the process of inquiry in science is the construction and assessment of models that can be used to explain (and in some cases, predict) natural phenomena. This dissertation is a qualitative study of student learning in a high school biology course that was designed to give students opportunities to learn about genetic inquiry in part by providing them with authentic experiences doing inquiry in the discipline. With the aid of a computer program that generates populations of "fruit flies", the students in this class worked in groups structured like scientific communities to build, revise, and defend explanatory models for various inheritance phenomena. Analysis of the ways in which the first cohort of students assessed their inheritance models revealed that all students assessed models based upon empirical fit (data/model match). However, in contrast to the practice of scientists and despite explicit instruction, students did not consistently apply conceptual assessment criteria to their models. That is, they didn't seek consistency between underlying concepts or processes in their models and those of other important genetic models, such as meiosis. This is perhaps in part because they lacked an understanding of models as conceptual rather than physical entities. Subsequently, the genetics curriculum was altered in order to create more opportunities for students to address epistemological issues associated with model assessment throughout the course. The second cohort of students' understanding of models changed over the nine-week period: initially the majority of students equated scientific models with "proof" (generally physical) of "theories"; at the end of the course, most students demonstrated understanding of the conceptual nature of scientific models and the need to justify such knowledge according to both its empirical utility and conceptual consistency. Through model construction and assessment (i.e. scientific inquiry), students were able to come to a rich understanding of both the central concepts of transmission genetics and important epistemological aspects of genetic practice.

A better coefficient of determination for genetic profile analysis.

PubMed

Lee, Sang Hong; Goddard, Michael E; Wray, Naomi R; Visscher, Peter M

2012-04-01

Genome-wide association studies have facilitated the construction of risk predictors for disease from multiple Single Nucleotide Polymorphism markers. The ability of such "genetic profiles" to predict outcome is usually quantified in an independent data set. Coefficients of determination (R(2) ) have been a useful measure to quantify the goodness-of-fit of the genetic profile. Various pseudo-R(2) measures for binary responses have been proposed. However, there is no standard or consensus measure because the concept of residual variance is not easily defined on the observed probability scale. Unlike other nongenetic predictors such as environmental exposure, there is prior information on genetic predictors because for most traits there are estimates of the proportion of variation in risk in the population due to all genetic factors, the heritability. It is this useful ability to benchmark that makes the choice of a measure of goodness-of-fit in genetic profiling different from that of nongenetic predictors. In this study, we use a liability threshold model to establish the relationship between the observed probability scale and underlying liability scale in measuring R(2) for binary responses. We show that currently used R(2) measures are difficult to interpret, biased by ascertainment, and not comparable to heritability. We suggest a novel and globally standard measure of R(2) that is interpretable on the liability scale. Furthermore, even when using ascertained case-control studies that are typical in human disease studies, we can obtain an R(2) measure on the liability scale that can be compared directly to heritability. © 2012 Wiley Periodicals, Inc.

Reproductive isolation and local adaptation quantified for a chromosome inversion in a malaria mosquito.

PubMed

Ayala, Diego; Guerrero, Rafael F; Kirkpatrick, Mark

2013-04-01

Chromosome inversions have long been thought to be involved in speciation and local adaptation. We have little quantitative information, however, about the effects that inversion polymorphisms have on reproductive isolation and viability. Here we provide the first estimates from any organism for the total amount of reproductive isolation associated with an inversion segregating in natural populations. We sampled chromosomes from 751 mosquitoes of the malaria vector Anopheles funestus along a 1421 km transect in Cameroon that traverses savannah, highland, and rainforest ecological zones. We then developed a series of population genetic models that account for selection, migration, and assortative mating, and fit the models to the data using likelihood. Results from the best-fit models suggest there is strong local adaptation, with relative viabilities of homozygotes ranging from 25% to 130% compared to heterozygotes. Viabilities vary qualitatively between regions: the inversion is underdominant in the savannah, whereas in the highlands it is overdominant. The inversion is also implicated in strong assortative mating. In the savannah, the two homozygote forms show 92% reproductive isolation, suggesting that this one inversion can generate most of the genetic barriers needed for speciation. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Evolution of social versus individual learning in a subdivided population revisited: comparative analysis of three coexistence mechanisms using the inclusive-fitness method.

PubMed

Kobayashi, Yutaka; Ohtsuki, Hisashi

2014-03-01

Learning abilities are categorized into social (learning from others) and individual learning (learning on one's own). Despite the typically higher cost of individual learning, there are mechanisms that allow stable coexistence of both learning modes in a single population. In this paper, we investigate by means of mathematical modeling how the effect of spatial structure on evolutionary outcomes of pure social and individual learning strategies depends on the mechanisms for coexistence. We model a spatially structured population based on the infinite-island framework and consider three scenarios that differ in coexistence mechanisms. Using the inclusive-fitness method, we derive the equilibrium frequency of social learners and the genetic load of social learning (defined as average fecundity reduction caused by the presence of social learning) in terms of some summary statistics, such as relatedness, for each of the three scenarios and compare the results. This comparative analysis not only reconciles previous models that made contradictory predictions as to the effect of spatial structure on the equilibrium frequency of social learners but also derives a simple mathematical rule that determines the sign of the genetic load (i.e. whether or not social learning contributes to the mean fecundity of the population). Copyright © 2013 Elsevier Inc. All rights reserved.

Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

PubMed

Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

2018-06-02

Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

Predicting phenotypes of asthma and eczema with machine learning

PubMed Central

2014-01-01

Background There is increasing recognition that asthma and eczema are heterogeneous diseases. We investigated the predictive ability of a spectrum of machine learning methods to disambiguate clinical sub-groups of asthma, wheeze and eczema, using a large heterogeneous set of attributes in an unselected population. The aim was to identify to what extent such heterogeneous information can be combined to reveal specific clinical manifestations. Methods The study population comprised a cross-sectional sample of adults, and included representatives of the general population enriched by subjects with asthma. Linear and non-linear machine learning methods, from logistic regression to random forests, were fit on a large attribute set including demographic, clinical and laboratory features, genetic profiles and environmental exposures. Outcome of interest were asthma, wheeze and eczema encoded by different operational definitions. Model validation was performed via bootstrapping. Results The study population included 554 adults, 42% male, 38% previous or current smokers. Proportion of asthma, wheeze, and eczema diagnoses was 16.7%, 12.3%, and 21.7%, respectively. Models were fit on 223 non-genetic variables plus 215 single nucleotide polymorphisms. In general, non-linear models achieved higher sensitivity and specificity than other methods, especially for asthma and wheeze, less for eczema, with areas under receiver operating characteristic curve of 84%, 76% and 64%, respectively. Our findings confirm that allergen sensitisation and lung function characterise asthma better in combination than separately. The predictive ability of genetic markers alone is limited. For eczema, new predictors such as bio-impedance were discovered. Conclusions More usefully-complex modelling is the key to a better understanding of disease mechanisms and personalised healthcare: further advances are likely with the incorporation of more factors/attributes and longitudinal measures. PMID:25077568

Genetic and environmental (physical fitness and sedentary activity) interaction effects on cardiometabolic risk factors in Mexican American children and adolescents.

PubMed

Arya, Rector; Farook, Vidya S; Fowler, Sharon P; Puppala, Sobha; Chittoor, Geetha; Resendez, Roy G; Mummidi, Srinivas; Vanamala, Jairam; Almasy, Laura; Curran, Joanne E; Comuzzie, Anthony G; Lehman, Donna M; Jenkinson, Christopher P; Lynch, Jane L; DeFronzo, Ralph A; Blangero, John; Hale, Daniel E; Duggirala, Ravindranath; Diego, Vincent P

2018-06-01

Knowledge on genetic and environmental (G × E) interaction effects on cardiometabolic risk factors (CMRFs) in children is limited.  The purpose of this study was to examine the impact of G × E interaction effects on CMRFs in Mexican American (MA) children (n = 617, ages 6-17 years). The environments examined were sedentary activity (SA), assessed by recalls from "yesterday" (SAy) and "usually" (SAu) and physical fitness (PF) assessed by Harvard PF scores (HPFS). CMRF data included body mass index (BMI), waist circumference (WC), fat mass (FM), fasting insulin (FI), homeostasis model of assessment-insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), systolic (SBP) and diastolic (DBP) blood pressure, and number of metabolic syndrome components (MSC). We examined potential G × E interaction in the phenotypic expression of CMRFs using variance component models and likelihood-based statistical inference. Significant G × SA interactions were identified for six CMRFs: BMI, WC, FI, HOMA-IR, MSC, and HDL, and significant G × HPFS interactions were observed for four CMRFs: BMI, WC, FM, and HOMA-IR. However, after correcting for multiple hypothesis testing, only WC × SAy, FM × SAy, and FI × SAu interactions became marginally significant. After correcting for multiple testing, most of CMRFs exhibited significant G × E interactions (Reduced G × E model vs. Constrained model). These findings provide evidence that genetic factors interact with SA and PF to influence variation in CMRFs, and underscore the need for better understanding of these relationships to develop strategies and interventions to effectively reduce or prevent cardiometabolic risk in children. © 2018 WILEY PERIODICALS, INC.

Direct benefits of choosing a high-fitness mate can offset the indirect costs associated with intralocus sexual conflict.

PubMed

Pischedda, Alison; Chippindale, Adam K

2017-06-01

Intralocus sexual conflict generates a cost to mate choice: high-fitness partners transmit genetic variation that confers lower fitness to offspring of the opposite sex. Our earlier work in the fruit fly, Drosophila melanogaster, revealed that these indirect genetic costs were sufficient to reverse potential "good genes" benefits of sexual selection. However, mate choice can also confer direct fitness benefits by inducing larger numbers of progeny. Here, we consider whether direct benefits through enhanced fertility could offset the costs associated with intralocus sexual conflict in D. melanogaster. Using hemiclonal analysis, we found that females mated to high-fitness males produced 11% more offspring compared to those mated to low-fitness males, and high-fitness females produced 34% more offspring than low-fitness females. These direct benefits more than offset the reduction in offspring fitness caused by intralocus sexual conflict, creating a net fitness benefit for each sex to pairing with a high-fitness partner. Our findings highlight the need to consider both direct and indirect effects when investigating the fitness impacts of mate choice. Direct fitness benefits may shelter sexually antagonistic alleles from selection, suggesting a novel mechanism for the maintenance of fitness variation. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Robust discovery of genetic associations incorporating gene-environment interaction and independence.

PubMed

Tchetgen Tchetgen, Eric

2011-03-01

This article considers the detection and evaluation of genetic effects incorporating gene-environment interaction and independence. Whereas ordinary logistic regression cannot exploit the assumption of gene-environment independence, the proposed approach makes explicit use of the independence assumption to improve estimation efficiency. This method, which uses both cases and controls, fits a constrained retrospective regression in which the genetic variant plays the role of the response variable, and the disease indicator and the environmental exposure are the independent variables. The regression model constrains the association of the environmental exposure with the genetic variant among the controls to be null, thus explicitly encoding the gene-environment independence assumption, which yields substantial gain in accuracy in the evaluation of genetic effects. The proposed retrospective regression approach has several advantages. It is easy to implement with standard software, and it readily accounts for multiple environmental exposures of a polytomous or of a continuous nature, while easily incorporating extraneous covariates. Unlike the profile likelihood approach of Chatterjee and Carroll (Biometrika. 2005;92:399-418), the proposed method does not require a model for the association of a polytomous or continuous exposure with the disease outcome, and, therefore, it is agnostic to the functional form of such a model and completely robust to its possible misspecification.

Sexually antagonistic selection on genetic variation underlying both male and female same-sex sexual behavior.

PubMed

Berger, David; You, Tao; Minano, Maravillas R; Grieshop, Karl; Lind, Martin I; Arnqvist, Göran; Maklakov, Alexei A

2016-05-13

Intralocus sexual conflict, arising from selection for different alleles at the same locus in males and females, imposes a constraint on sex-specific adaptation. Intralocus sexual conflict can be alleviated by the evolution of sex-limited genetic architectures and phenotypic expression, but pleiotropic constraints may hinder this process. Here, we explored putative intralocus sexual conflict and genetic (co)variance in a poorly understood behavior with near male-limited expression. Same-sex sexual behaviors (SSBs) generally do not conform to classic evolutionary models of adaptation but are common in male animals and have been hypothesized to result from perception errors and selection for high male mating rates. However, perspectives incorporating sex-specific selection on genes shared by males and females to explain the expression and evolution of SSBs have largely been neglected. We performed two parallel sex-limited artificial selection experiments on SSB in male and female seed beetles, followed by sex-specific assays of locomotor activity and male sex recognition (two traits hypothesized to be functionally related to SSB) and adult reproductive success (allowing us to assess fitness consequences of genetic variance in SSB and its correlated components). Our experiments reveal both shared and sex-limited genetic variance for SSB. Strikingly, genetically correlated responses in locomotor activity and male sex-recognition were associated with sexually antagonistic fitness effects, but these effects differed qualitatively between male and female selection lines, implicating intralocus sexual conflict at both male- and female-specific genetic components underlying SSB. Our study provides experimental support for the hypothesis that widespread pleiotropy generates pervasive intralocus sexual conflict governing the expression of SSBs, suggesting that SSB in one sex can occur due to the expression of genes that carry benefits in the other sex.

Multiple mechanisms influencing the relationship between alcohol consumption and peer alcohol use.

PubMed

Edwards, Alexis C; Maes, Hermine H; Prescott, Carol A; Kendler, Kenneth S

2015-02-01

Alcohol consumption is typically correlated with the alcohol use behaviors of one's peers. Previous research has suggested that this positive relationship could be due to social selection, social influence, or a combination of both processes. However, few studies have considered the role of shared genetic and environmental influences in conjunction with causal processes. This study uses data from a sample of male twins (N = 1,790) who provided retrospective reports of their own alcohol consumption and their peers' alcohol-related behaviors, from adolescence into young adulthood (ages 12 to 25). Structural equation modeling was employed to compare 3 plausible models of genetic and environmental influences on the relationship between phenotypes over time. Model fitting indicated that one's own alcohol consumption and the alcohol use of one's peers are related through both genetic and shared environmental factors and through unique environmental causal influences. The relative magnitude of these factors, and their contribution to covariation, changed over time, with genetic factors becoming more meaningful later in development. Peers' alcohol use behaviors and one's own alcohol consumption are related through a complex combination of genetic and environmental factors that act via correlated factors and the complementary causal mechanisms of social selection and influence. Understanding these processes can inform risk assessment as well as improve our ability to model the development of alcohol use. Copyright © 2015 by the Research Society on Alcoholism.

Multiple mechanisms influencing the relationship between alcohol consumption and peer alcohol use

PubMed Central

Edwards, Alexis C.; Maesr, Hermine H.; Prescott, Carol A.; Kendler, Kenneth S.

2014-01-01

Background Alcohol consumption is typically correlated with the alcohol use behaviors of one’s peers. Previous research has suggested that this positive relationship could be due to social selection, social influence, or a combination of both processes. However, few studies have considered the role of shared genetic and environmental influences in conjunction with causal processes. Methods The current study uses data from a sample of male twins (N=1790) who provided retrospective reports of their own alcohol consumption and their peers’ alcohol related behaviors, from adolescence into young adulthood (ages 12–25). Structural equation modeling was employed to compare three plausible models of genetic and environmental influences on the relationship between phenotypes over time. Results Model fitting indicated that one’s own alcohol consumption and the alcohol use of one’s peers are related through both genetic and shared environmental factors and through unique environmental causal influences. The relative magnitude of these factors, and their contribution to covariation, changed over time, with genetic factors becoming more meaningful later in development. Conclusions Peers’ alcohol use behaviors and one’s own alcohol consumption are related through a complex combination of genetic and environmental factors that act via correlated factors and the complementary causal mechanisms of social selection and influence. Understanding these processes can inform risk assessment as well as improve our ability to model the development of alcohol use. PMID:25597346

Feasibility of waveform inversion of Rayleigh waves for shallow shear-wave velocity using a genetic algorithm

USGS Publications Warehouse

Zeng, C.; Xia, J.; Miller, R.D.; Tsoflias, G.P.

2011-01-01

Conventional surface wave inversion for shallow shear (S)-wave velocity relies on the generation of dispersion curves of Rayleigh waves. This constrains the method to only laterally homogeneous (or very smooth laterally heterogeneous) earth models. Waveform inversion directly fits waveforms on seismograms, hence, does not have such a limitation. Waveforms of Rayleigh waves are highly related to S-wave velocities. By inverting the waveforms of Rayleigh waves on a near-surface seismogram, shallow S-wave velocities can be estimated for earth models with strong lateral heterogeneity. We employ genetic algorithm (GA) to perform waveform inversion of Rayleigh waves for S-wave velocities. The forward problem is solved by finite-difference modeling in the time domain. The model space is updated by generating offspring models using GA. Final solutions can be found through an iterative waveform-fitting scheme. Inversions based on synthetic records show that the S-wave velocities can be recovered successfully with errors no more than 10% for several typical near-surface earth models. For layered earth models, the proposed method can generate one-dimensional S-wave velocity profiles without the knowledge of initial models. For earth models containing lateral heterogeneity in which case conventional dispersion-curve-based inversion methods are challenging, it is feasible to produce high-resolution S-wave velocity sections by GA waveform inversion with appropriate priori information. The synthetic tests indicate that the GA waveform inversion of Rayleigh waves has the great potential for shallow S-wave velocity imaging with the existence of strong lateral heterogeneity. ?? 2011 Elsevier B.V.

Incompatibility and competitive exclusion of genomic segments between sibling Drosophila species.

PubMed

Fang, Shu; Yukilevich, Roman; Chen, Ying; Turissini, David A; Zeng, Kai; Boussy, Ian A; Wu, Chung-I

2012-06-01

The extent and nature of genetic incompatibilities between incipient races and sibling species is of fundamental importance to our view of speciation. However, with the exception of hybrid inviability and sterility factors, little is known about the extent of other, more subtle genetic incompatibilities between incipient species. Here we experimentally demonstrate the prevalence of such genetic incompatibilities between two young allopatric sibling species, Drosophila simulans and D. sechellia. Our experiments took advantage of 12 introgression lines that carried random introgressed D. sechellia segments in different parts of the D. simulans genome. First, we found that these introgression lines did not show any measurable sterility or inviability effects. To study if these sechellia introgressions in a simulans background contained other fitness consequences, we competed and genetically tracked the marked alleles within each introgression against the wild-type alleles for 20 generations. Strikingly, all marked D. sechellia introgression alleles rapidly decreased in frequency in only 6 to 7 generations. We then developed computer simulations to model our competition results. These simulations indicated that selection against D. sechellia introgression alleles was high (average s = 0.43) and that the marker alleles and the incompatible alleles did not separate in 78% of the introgressions. The latter result likely implies that most introgressions contain multiple genetic incompatibilities. Thus, this study reveals that, even at early stages of speciation, many parts of the genome diverge to a point where introducing foreign elements has detrimental fitness consequences, but which cannot be seen using standard sterility and inviability assays.

Why are hyperactivity and academic achievement related?

PubMed

Saudino, Kimberly J; Plomin, Robert

2007-01-01

Although a negative association between hyperactivity and academic achievement is well documented, little is known about the genetic and/or environmental mechanisms responsible for the association. The present study explored links between parent and teacher ratings of hyperactive behavior problems and teacher-assessed achievement in a sample of 1,876 twin pairs (mean age 7.04 years). The results did not differ across rater, nor were there significant differences between males or females or for twins in the same or different classrooms. Hyperactivity was significantly correlated with achievement. Multivariate model-fitting analyses revealed significant genetic and nonshared environmental covariance between the two phenotypes. In addition, bivariate heritabilities were substantial, indicating that the phenotypic correlations between hyperactivity and achievement were largely mediated by genetic influences.

Genetic rescue in an inbred Arctic fox (Vulpes lagopus) population.

PubMed

Hasselgren, Malin; Angerbjörn, Anders; Eide, Nina E; Erlandsson, Rasmus; Flagstad, Øystein; Landa, Arild; Wallén, Johan; Norén, Karin

2018-03-28

Isolation of small populations can reduce fitness through inbreeding depression and impede population growth. Outcrossing with only a few unrelated individuals can increase demographic and genetic viability substantially, but few studies have documented such genetic rescue in natural mammal populations. We investigate the effects of immigration in a subpopulation of the endangered Scandinavian arctic fox ( Vulpes lagopus ), founded by six individuals and isolated for 9 years at an extremely small population size. Based on a long-term pedigree (105 litters, 543 individuals) combined with individual fitness traits, we found evidence for genetic rescue. Natural immigration and gene flow of three outbred males in 2010 resulted in a reduction in population average inbreeding coefficient ( f ), from 0.14 to 0.08 within 5 years. Genetic rescue was further supported by 1.9 times higher juvenile survival and 1.3 times higher breeding success in immigrant first-generation offspring compared with inbred offspring. Five years after immigration, the population had more than doubled in size and allelic richness increased by 41%. This is one of few studies that has documented genetic rescue in a natural mammal population suffering from inbreeding depression and contributes to a growing body of data demonstrating the vital connection between genetics and individual fitness. © 2018 The Author(s).

Impact of fitting dominance and additive effects on accuracy of genomic prediction of breeding values in layers.

PubMed

Heidaritabar, M; Wolc, A; Arango, J; Zeng, J; Settar, P; Fulton, J E; O'Sullivan, N P; Bastiaansen, J W M; Fernando, R L; Garrick, D J; Dekkers, J C M

2016-10-01

Most genomic prediction studies fit only additive effects in models to estimate genomic breeding values (GEBV). However, if dominance genetic effects are an important source of variation for complex traits, accounting for them may improve the accuracy of GEBV. We investigated the effect of fitting dominance and additive effects on the accuracy of GEBV for eight egg production and quality traits in a purebred line of brown layers using pedigree or genomic information (42K single-nucleotide polymorphism (SNP) panel). Phenotypes were corrected for the effect of hatch date. Additive and dominance genetic variances were estimated using genomic-based [genomic best linear unbiased prediction (GBLUP)-REML and BayesC] and pedigree-based (PBLUP-REML) methods. Breeding values were predicted using a model that included both additive and dominance effects and a model that included only additive effects. The reference population consisted of approximately 1800 animals hatched between 2004 and 2009, while approximately 300 young animals hatched in 2010 were used for validation. Accuracy of prediction was computed as the correlation between phenotypes and estimated breeding values of the validation animals divided by the square root of the estimate of heritability in the whole population. The proportion of dominance variance to total phenotypic variance ranged from 0.03 to 0.22 with PBLUP-REML across traits, from 0 to 0.03 with GBLUP-REML and from 0.01 to 0.05 with BayesC. Accuracies of GEBV ranged from 0.28 to 0.60 across traits. Inclusion of dominance effects did not improve the accuracy of GEBV, and differences in their accuracies between genomic-based methods were small (0.01-0.05), with GBLUP-REML yielding higher prediction accuracies than BayesC for egg production, egg colour and yolk weight, while BayesC yielded higher accuracies than GBLUP-REML for the other traits. In conclusion, fitting dominance effects did not impact accuracy of genomic prediction of breeding values in this population. © 2016 Blackwell Verlag GmbH.

Sexually antagonistic polymorphism in simultaneous hermaphrodites

PubMed Central

Jordan, Crispin Y.; Connallon, Tim

2015-01-01

In hermaphrodites, pleiotropic genetic tradeoffs between female and male reproductive functions can lead to sexually antagonistic (SA) selection, where individual alleles have conflicting fitness effects on each sex function. While an extensive theory of SA selection exists for dioecious species, these results have not been generalized to hermaphrodites. We develop population genetic models of SA selection in simultaneous hermaphrodites, and evaluate effects of dominance, selection on each sex function, self-fertilization, and population size, on the maintenance of polymorphism. Under obligate outcrossing, hermaphrodite model predictions converge exactly with those of dioecious populations. Self-fertilization in hermaphrodites generates three points of divergence with dioecious theory. First, opportunities for stable polymorphism decline sharply and become less sensitive to dominance with increased selfing. Second, selfing introduces an asymmetry in the relative importance of selection through male versus female reproductive functions, expands the parameter space favorable for the evolutionary invasion of female-beneficial alleles, and restricts invasion criteria for male-beneficial alleles. Finally, contrary to models of unconditionally beneficial alleles, selfing decreases genetic hitchhiking effects of invading SA alleles, and should therefore decrease these population genetic signals of SA polymorphisms. We discuss implications of SA selection in hermaphrodites, including its potential role in the evolution of “selfing syndromes”. PMID:25311368

Multivariate Cholesky models of human female fertility patterns in the NLSY.

PubMed

Rodgers, Joseph Lee; Bard, David E; Miller, Warren B

2007-03-01

Substantial evidence now exists that variables measuring or correlated with human fertility outcomes have a heritable component. In this study, we define a series of age-sequenced fertility variables, and fit multivariate models to account for underlying shared genetic and environmental sources of variance. We make predictions based on a theory developed by Udry [(1996) Biosocial models of low-fertility societies. In: Casterline, JB, Lee RD, Foote KA (eds) Fertility in the United States: new patterns, new theories. The Population Council, New York] suggesting that biological/genetic motivations can be more easily realized and measured in settings in which fertility choices are available. Udry's theory, along with principles from molecular genetics and certain tenets of life history theory, allow us to make specific predictions about biometrical patterns across age. Consistent with predictions, our results suggest that there are different sources of genetic influence on fertility variance at early compared to later ages, but that there is only one source of shared environmental influence that occurs at early ages. These patterns are suggestive of the types of gene-gene and gene-environment interactions for which we must account to better understand individual differences in fertility outcomes.

Mate choice theory and the mode of selection in sexual populations.

PubMed

Carson, Hampton L

2003-05-27

Indirect new data imply that mate and/or gamete choice are major selective forces driving genetic change in sexual populations. The system dictates nonrandom mating, an evolutionary process requiring both revised genetic theory and new data on heritability of characters underlying Darwinian fitness. Successfully reproducing individuals represent rare selections from among vigorous, competing survivors of preadult natural selection. Nonrandom mating has correlated demographic effects: reduced effective population size, inbreeding, low gene flow, and emphasis on deme structure. Characters involved in choice behavior at reproduction appear based on quantitative trait loci. This variability serves selection for fitness within the population, having only an incidental relationship to the origin of genetically based reproductive isolation between populations. The claim that extensive hybridization experiments with Drosophila indicate that selection favors a gradual progression of "isolating mechanisms" is flawed, because intra-group random mating is assumed. Over deep time, local sexual populations are strong, independent genetic systems that use rich fields of variable polygenic components of fitness. The sexual reproduction system thus particularizes, in small subspecific populations, the genetic basis of the grand adaptive sweep of selective evolutionary change, much as Darwin proposed.

Limits of neutral drift: lessons from the in vitro evolution of two ribozymes.

PubMed

Petrie, Katherine L; Joyce, Gerald F

2014-10-01

The relative contributions of adaptive selection and neutral drift to genetic change are unknown but likely depend on the inherent abundance of functional genotypes in sequence space and how accessible those genotypes are to one another. To better understand the relative roles of selection and drift in evolution, local fitness landscapes for two different RNA ligase ribozymes were examined using a continuous in vitro evolution system under conditions that foster the capacity for neutral drift to mediate genetic change. The exploration of sequence space was accelerated by increasing the mutation rate using mutagenic nucleotide analogs. Drift was encouraged by carrying out evolution within millions of separate compartments to exploit the founder effect. Deep sequencing of individuals from the evolved populations revealed that the distribution of genotypes did not escape the starting local fitness peak, remaining clustered around the sequence used to initiate evolution. This is consistent with a fitness landscape where high-fitness genotypes are sparse and well isolated, and suggests, at least in this context, that neutral drift alone is not a primary driver of genetic change. Neutral drift does, however, provide a repository of genetic variation upon which adaptive selection can act.

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle.

PubMed

Eaglen, Sophie A E; Coffey, Mike P; Woolliams, John A; Wall, Eileen

2012-07-28

The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle. Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (-maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models. On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (-maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (-maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence. For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (-maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

PubMed Central

2012-01-01

Background The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle. Methods Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models. Results and discussion On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence. Conclusions For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions. PMID:22839757

Mitochondrial Recombination Reveals Mito-Mito Epistasis in Yeast.

PubMed

Wolters, John F; Charron, Guillaume; Gaspary, Alec; Landry, Christian R; Fiumera, Anthony C; Fiumera, Heather L

2018-05-01

Genetic variation in mitochondrial DNA (mtDNA) provides adaptive potential although the underlying genetic architecture of fitness components within mtDNAs is not known. To dissect functional variation within mtDNAs, we first identified naturally occurring mtDNAs that conferred high or low fitness in Saccharomyces cerevisiae by comparing growth in strains containing identical nuclear genotypes but different mtDNAs. During respiratory growth under temperature and oxidative stress conditions, mitotype effects were largely independent of nuclear genotypes even in the presence of mito-nuclear interactions. Recombinant mtDNAs were generated to determine fitness components within high- and low-fitness mtDNAs. Based on phenotypic distributions of isogenic strains containing recombinant mtDNAs, we found that multiple loci contributed to mitotype fitness differences. These mitochondrial loci interacted in epistatic, nonadditive ways in certain environmental conditions. Mito-mito epistasis ( i.e. , nonadditive interactions between mitochondrial loci) influenced fitness in progeny from four different crosses, suggesting that mito-mito epistasis is a widespread phenomenon in yeast and other systems with recombining mtDNAs. Furthermore, we found that interruption of coadapted mito-mito interactions produced recombinant mtDNAs with lower fitness. Our results demonstrate that mito-mito epistasis results in functional variation through mitochondrial recombination in fungi, providing modes for adaptive evolution and the generation of mito-mito incompatibilities. Copyright © 2018 by the Genetics Society of America.

Variance-based selection may explain general mating patterns in social insects.

PubMed

Rueppell, Olav; Johnson, Nels; Rychtár, Jan

2008-06-23

Female mating frequency is one of the key parameters of social insect evolution. Several hypotheses have been suggested to explain multiple mating and considerable empirical research has led to conflicting results. Building on several earlier analyses, we present a simple general model that links the number of queen matings to variance in colony performance and this variance to average colony fitness. The model predicts selection for multiple mating if the average colony succeeds in a focal task, and selection for single mating if the average colony fails, irrespective of the proximate mechanism that links genetic diversity to colony fitness. Empirical support comes from interspecific comparisons, e.g. between the bee genera Apis and Bombus, and from data on several ant species, but more comprehensive empirical tests are needed.

Teaching and Learning Activity Sequencing System using Distributed Genetic Algorithms

NASA Astrophysics Data System (ADS)

Matsui, Tatsunori; Ishikawa, Tomotake; Okamoto, Toshio

The purpose of this study is development of a supporting system for teacher's design of lesson plan. Especially design of lesson plan which relates to the new subject "Information Study" is supported. In this study, we developed a system which generates teaching and learning activity sequences by interlinking lesson's activities corresponding to the various conditions according to the user's input. Because user's input is multiple information, there will be caused contradiction which the system should solve. This multiobjective optimization problem is resolved by Distributed Genetic Algorithms, in which some fitness functions are defined with reference models on lesson, thinking and teaching style. From results of various experiments, effectivity and validity of the proposed methods and reference models were verified; on the other hand, some future works on reference models and evaluation functions were also pointed out.

Seven-parameter statistical model for BRDF in the UV band.

PubMed

Bai, Lu; Wu, Zhensen; Zou, Xiren; Cao, Yunhua

2012-05-21

A new semi-empirical seven-parameter BRDF model is developed in the UV band using experimentally measured data. The model is based on the five-parameter model of Wu and the fourteen-parameter model of Renhorn and Boreman. Surface scatter, bulk scatter and retro-reflection scatter are considered. An optimizing modeling method, the artificial immune network genetic algorithm, is used to fit the BRDF measurement data over a wide range of incident angles. The calculation time and accuracy of the five- and seven-parameter models are compared. After fixing the seven parameters, the model can well describe scattering data in the UV band.

The fitness effects of outcrossing in Calylophus serrulatus, a permanent translocation heterozygote.

PubMed

Heiser, David A; Shaw, Ruth G

2006-01-01

Small and relatively isolated populations that occupy fragmented habitat are at risk of local extinction. However, fitness consequences of fragmentation related to mating distance, such as inbreeding depression following increased self- and near-neighbor mating, may not follow standard expectations in species with specialized genetic systems. We investigated the effect of mating distance on progeny fitness in Calylophus serrulatus, a primarily autogamous, permanent translocation heterozygote that is restricted to prairie fragments in the North American tallgrass prairie region. We pollinated flowers by hand in the field with pollen sampled at various distances from the maternal parent within and between three populations in southeastern Minnesota. We raised the progeny in a greenhouse and measured fitness-related characters. Because their genetic system prevents loss of heterozygosity throughout much of the genome, regardless of inbreeding, permanent translocation heterozygotes are not expected to exhibit inbreeding depression. Consistent with this expectation, in no case did progeny of self matings suffer significantly reduced mean fitness compared to progeny from crosses between plants. Crosses between plants in the two closely situated (2 km) populations yielded progeny with fitness intermediate to their parents, but crosses between each of those populations and the more distant (20 km) population yielded progeny with reduced fitness, suggesting outbreeding depression at this largest spatial scale. Similarly, fitness of self-pollinated progeny and progeny from "near" crosses (<2 m) within populations tended to be higher than "mid" (10-25 m) and "far" (>35 m) cross-progeny fitness. Under the current conditions of fragmentation, it seems likely that the distant matings that produce outbreeding depression are rare. It appears that mean fitness in this species is maintained in the context of severe fragmentation of its populations, largely because of its genetic system.

Hybridization at an ecotone: ecological and genetic barriers between three Iberian vipers.

PubMed

Tarroso, Pedro; Pereira, Ricardo J; Martínez-Freiría, Fernando; Godinho, Raquel; Brito, José C

2014-03-01

The formation of stable genetic boundaries between emerging species is often diagnosed by reduced hybrid fitness relative to parental taxa. This reduced fitness can arise from endogenous and/or exogenous barriers to gene flow. Although detecting exogenous barriers in nature is difficult, we can estimate the role of ecological divergence in driving species boundaries by integrating molecular and ecological niche modelling tools. Here, we focus on a three-way secondary contact zone between three viper species (Vipera aspis, V. latastei and V. seoanei) to test for the contribution of ecological divergence to the development of reproductive barriers at several species traits (morphology, nuclear DNA and mitochondrial DNA). Both the nuclear and mitochondrial data show that all taxa are genetically distinct and that the sister species V. aspis and V. latastei hybridize frequently and backcross over several generations. We find that the three taxa have diverged ecologically and meet at a hybrid zone coincident with a steep ecotone between the Atlantic and Mediterranean biogeographical provinces. Integrating landscape and genetic approaches, we show that hybridization is spatially restricted to habitats that are suboptimal for parental taxa. Together, these results suggest that niche separation and adaptation to an ecological gradient confer an important barrier to gene flow among taxa that have not achieved complete reproductive isolation. © 2014 John Wiley & Sons Ltd.

High migration rates shape the postglacial history of amphi-Atlantic bryophytes.

PubMed

Désamoré, Aurélie; Patiño, Jairo; Mardulyn, Patrick; Mcdaniel, Stuart F; Zanatta, Florian; Laenen, Benjamin; Vanderpoorten, Alain

2016-11-01

Paleontological evidence and current patterns of angiosperm species richness suggest that European biota experienced more severe bottlenecks than North American ones during the last glacial maximum. How well this pattern fits other plant species is less clear. Bryophytes offer a unique opportunity to contrast the impact of the last glacial maximum in North America and Europe because about 60% of the European bryoflora is shared with North America. Here, we use population genetic analyses based on approximate Bayesian computation on eight amphi-Atlantic species to test the hypothesis that North American populations were less impacted by the last glacial maximum, exhibiting higher levels of genetic diversity than European ones and ultimately serving as a refugium for the postglacial recolonization of Europe. In contrast with this hypothesis, the best-fit demographic model involved similar patterns of population size contractions, comparable levels of genetic diversity and balanced migration rates between European and North American populations. Our results thus suggest that bryophytes have experienced comparable demographic glacial histories on both sides of the Atlantic. Although a weak, but significant genetic structure was systematically recovered between European and North American populations, evidence for migration from and towards both continents suggests that amphi-Atlantic bryophyte population may function as a metapopulation network. Reconstructing the biogeographic history of either North American or European bryophyte populations therefore requires a large, trans-Atlantic geographic framework. © 2016 John Wiley & Sons Ltd.

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

PubMed

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Genomics and Genetics in the Biology of Adaptation to Exercise

PubMed Central

Bouchard, Claude; Rankinen, Tuomo; Timmons, James A.

2014-01-01

This chapter is devoted to the role of genetic variation and gene-exercise interactions in the biology of adaptation to exercise. There is evidence from genetic epidemiology research that DNA sequence differences contribute to human variation in physical activity level, cardiorespiratory fitness in the untrained state, cardiovascular and metabolic response to acute exercise, and responsiveness to regular exercise. Methodological and technological advances have made it possible to undertake the molecular dissection of the genetic component of complex, multifactorial traits, such as those of interest to exercise biology, in terms of tissue expression profile, genes, and allelic variants. The evidence from animal models and human studies is considered. Data on candidate genes, genome-wide linkage results, genome-wide association findings, expression arrays, and combinations of these approaches are reviewed. Combining transcriptomic and genomic technologies has been shown to be more powerful as evidenced by the development of a recent molecular predictor of the ability to increase VO2max with exercise training. For exercise as a behavior and physiological fitness as a state to be major players in public health policies will require that that the role of human individuality and the influence of DNA sequence differences be understood. Likewise, progress in the use of exercise in therapeutic medicine will depend to a large extent on our ability to identify the favorable responders for given physiological properties to a given exercise regimen. PMID:23733655

Wetlands explain most in the genetic divergence pattern of Oncomelania hupensis.

PubMed

Liang, Lu; Liu, Yang; Liao, Jishan; Gong, Peng

2014-10-01

Understanding the divergence patterns of hosts could shed lights on the prediction of their parasite transmission. No effort has been devoted to understand the drivers of genetic divergence pattern of Oncomelania hupensis, the only intermediate host of Schistosoma japonicum. Based on a compilation of two O. hupensis gene datasets covering a wide geographic range in China and an array of geographical distance and environmental dissimilarity metrics built from earth observation data and ecological niche modeling, we conducted causal modeling analysis via simple, partial Mantel test and local polynomial fitting to understand the interactions among isolation-by-distance, isolation-by-environment, and genetic divergence. We found that geography contributes more to genetic divergence than environmental isolation, and among all variables involved, wetland showed the strongest correlation with the genetic pairwise distances. These results suggested that in China, O. hupensis dispersal is strongly linked to the distribution of wetlands, and the current divergence pattern of both O. hupensis and schistosomiasis might be altered due to the changed wetland pattern with the accomplishment of the Three Gorges Dam and the South-to-North water transfer project. Copyright © 2014 Elsevier B.V. All rights reserved.

Coalescence and genetic diversity in sexual populations under selection.

PubMed

Neher, Richard A; Kessinger, Taylor A; Shraiman, Boris I

2013-09-24

In sexual populations, selection operates neither on the whole genome, which is repeatedly taken apart and reassembled by recombination, nor on individual alleles that are tightly linked to the chromosomal neighborhood. The resulting interference between linked alleles reduces the efficiency of selection and distorts patterns of genetic diversity. Inference of evolutionary history from diversity shaped by linked selection requires an understanding of these patterns. Here, we present a simple but powerful scaling analysis identifying the unit of selection as the genomic "linkage block" with a characteristic length, , determined in a self-consistent manner by the condition that the rate of recombination within the block is comparable to the fitness differences between different alleles of the block. We find that an asexual model with the strength of selection tuned to that of the linkage block provides an excellent description of genetic diversity and the site frequency spectra compared with computer simulations. This linkage block approximation is accurate for the entire spectrum of strength of selection and is particularly powerful in scenarios with many weakly selected loci. The latter limit allows us to characterize coalescence, genetic diversity, and the speed of adaptation in the infinitesimal model of quantitative genetics.

Genetic parameters for test day somatic cell score in Brazilian Holstein cattle.

PubMed

Costa, C N; Santos, G G; Cobuci, J A; Thompson, G; Carvalheira, J G V

2015-12-29

Selection for lower somatic cell count has been included in the breeding objectives of several countries in order to increase resistance to mastitis. Genetic parameters of somatic cell scores (SCS) were estimated from the first lactation test day records of Brazilian Holstein cows using random-regression models with Legendre polynomials (LP) of the order 3-5. Data consisted of 87,711 TD produced by 10,084 cows, sired by 619 bulls calved from 1993 to 2007. Heritability estimates varied from 0.06 to 0.14 and decreased from the beginning of the lactation up to 60 days in milk (DIM) and increased thereafter to the end of lactation. Genetic correlations between adjacent DIM were very high (>0.83) but decreased to negative values, obtained with LP of order four, between DIM in the extremes of lactation. Despite the favorable trend, genetic changes in SCS were not significant and did not differ among LP. There was little benefit of fitting an LP of an order >3 to model animal genetic and permanent environment effects for SCS. Estimates of variance components found in this study may be used for breeding value estimation for SCS and selection for mastitis resistance in Holstein cattle in Brazil.

Impact of Pathogen Population Heterogeneity and Stress-Resistant Variants on Food Safety.

PubMed

Abee, T; Koomen, J; Metselaar, K I; Zwietering, M H; den Besten, H M W

2016-01-01

This review elucidates the state-of-the-art knowledge about pathogen population heterogeneity and describes the genotypic and phenotypic analyses of persister subpopulations and stress-resistant variants. The molecular mechanisms underlying the generation of persister phenotypes and genetic variants are identified. Zooming in on Listeria monocytogenes, a comparative whole-genome sequence analysis of wild types and variants that enabled the identification of mutations in variants obtained after a single exposure to lethal food-relevant stresses is described. Genotypic and phenotypic features are compared to those for persistent strains isolated from food processing environments. Inactivation kinetics, models used for fitting, and the concept of kinetic modeling-based schemes for detection of variants are presented. Furthermore, robustness and fitness parameters of L. monocytogenes wild type and variants are used to model their performance in food chains. Finally, the impact of stress-resistant variants and persistence in food processing environments on food safety is discussed.

Heterosis and outbreeding depression: A multi-locus model and an application to salmon production

USGS Publications Warehouse

Emlen, John M.

1991-01-01

Both artificial propagation and efforts to preserve or augment natural populations sometimes involve, wittingly or unwittingly, the mixing of different gene pools. The advantages of such mixing vis-à-vis the alleviation of inbreeding depression are well known. Acknowledged, but less well understood, are the complications posed by outbreeding depression. This paper derives a simple model of outbreeding depression and demonstrates that it is reasonably possible to predict the generation-to-generation fitness course of hybrids derived from parents from different origins. Genetic difference, or distance between parental types, is defined by the drop in fitness experienced by one type reared at the site to which the other is locally adapted. For situations where decisions involving stock mixing must be made in the absence of complete information, a sensitivity analysis-based conflict resolution method (the Good-Bad-Ugly model) is described.

A bottom-up characterization of transfer functions for synthetic biology designs: lessons from enzymology

PubMed Central

Carbonell-Ballestero, Max; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard; Macía, Javier; Rodríguez-Caso, Carlos

2014-01-01

Within the field of synthetic biology, a rational design of genetic parts should include a causal understanding of their input-output responses—the so-called transfer function—and how to tune them. However, a commonly adopted strategy is to fit data to Hill-shaped curves without considering the underlying molecular mechanisms. Here we provide a novel mathematical formalization that allows prediction of the global behavior of a synthetic device by considering the actual information from the involved biological parts. This is achieved by adopting an enzymology-like framework, where transfer functions are described in terms of their input affinity constant and maximal response. As a proof of concept, we characterize a set of Lux homoserine-lactone-inducible genetic devices with different levels of Lux receptor and signal molecule. Our model fits the experimental results and predicts the impact of the receptor's ribosome-binding site strength, as a tunable parameter that affects gene expression. The evolutionary implications are outlined. PMID:25404136

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models.

PubMed

Bignardi, A B; El Faro, L; Cardoso, V L; Machado, P F; Albuquerque, L G

2009-09-01

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

IBSEM: An Individual-Based Atlantic Salmon Population Model.

PubMed

Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A

2015-01-01

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a 'wild' genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors.

Ridge, Lasso and Bayesian additive-dominance genomic models.

PubMed

Azevedo, Camila Ferreira; de Resende, Marcos Deon Vilela; E Silva, Fabyano Fonseca; Viana, José Marcelo Soriano; Valente, Magno Sávio Ferreira; Resende, Márcio Fernando Ribeiro; Muñoz, Patricio

2015-08-25

A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated with narrow sense heritabilities of 0.20 and 0.35, respectively) and two genetic architectures for traits (the first consisting of small gene effects and the second consisting of a mixed inheritance model with five major genes). G-REML/G-BLUP and a modified Bayesian/Lasso (called BayesA*B* or t-BLASSO) method performed best in the prediction of genomic breeding as well as the total genotypic values of individuals in all four scenarios (two heritabilities x two genetic architectures). The BayesA*B*-type method showed a better ability to recover the dominance variance/additive variance ratio. Decomposition of genomic heritability and accuracy revealed the following descending importance order of information: LD, CS and PR not captured by markers, the last two being very close. Amongst the 10 models/methods evaluated, the G-BLUP, BAYESA*B* (-2,8) and BAYESA*B* (4,6) methods presented the best results and were found to be adequate for accurately predicting genomic breeding and total genotypic values as well as for estimating additive and dominance in additive-dominance genomic models.

Metabolic basis for the self-referential genetic code.

PubMed

Guimarães, Romeu Cardoso

2011-08-01

An investigation of the biosynthesis pathways producing glycine and serine was necessary to clarify an apparent inconsistency between the self-referential model (SRM) for the formation of the genetic code and the model of coevolution of encodings and of amino acid biosynthesis routes. According to the SRM proposal, glycine was the first amino acid encoded, followed by serine. The coevolution model does not state precisely which the first encodings were, only presenting a list of about ten early assignments including the derivation of glycine from serine-this being derived from the glycolysis intermediate glycerate, which reverses the order proposed by the self-referential model. Our search identified the glycine-serine pathway of syntheses based on one-carbon sources, involving activities of the glycine decarboxylase complex and its associated serine hydroxymethyltransferase, which is consistent with the order proposed by the self-referential model and supports its rationale for the origin of the genetic code: protein synthesis was developed inside an early metabolic system, serving the function of a sink of amino acids; the first peptides were glycine-rich and fit for the function of building the early ribonucleoproteins; glycine consumption in proteins drove the fixation of the glycine-serine pathway.

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel.

PubMed

Noble, Luke M; Chelo, Ivo; Guzella, Thiago; Afonso, Bruno; Riccardi, David D; Ammerman, Patrick; Dayarian, Adel; Carvalho, Sara; Crist, Anna; Pino-Querido, Ania; Shraiman, Boris; Rockman, Matthew V; Teotónio, Henrique

2017-12-01

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans , the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor ([Formula: see text]), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms. Copyright © 2017 by the Genetics Society of America.

Virus fitness differences observed between two naturally occurring isolates of Ebola virus Makona variant using a reverse genetics approach.

PubMed

Albariño, César G; Guerrero, Lisa Wiggleton; Chakrabarti, Ayan K; Kainulainen, Markus H; Whitmer, Shannon L M; Welch, Stephen R; Nichol, Stuart T

2016-09-01

During the large outbreak of Ebola virus disease that occurred in Western Africa from late 2013 to early 2016, several hundred Ebola virus (EBOV) genomes have been sequenced and the virus genetic drift analyzed. In a previous report, we described an efficient reverse genetics system designed to generate recombinant EBOV based on a Makona variant isolate obtained in 2014. Using this system, we characterized the replication and fitness of 2 isolates of the Makona variant. These virus isolates are nearly identical at the genetic level, but have single amino acid differences in the VP30 and L proteins. The potential effects of these differences were tested using minigenomes and recombinant viruses. The results obtained with this approach are consistent with the role of VP30 and L as components of the EBOV RNA replication machinery. Moreover, the 2 isolates exhibited clear fitness differences in competitive growth assays. Published by Elsevier Inc.

GENETIC STRUCTURE OF TRIATOMA INFESTANS POPULATIONS IN RURAL COMMUNITIES OF SANTIAGO DEL ESTERO, NORTHERN ARGENTINA

PubMed Central

Marcet, PL; Mora, MS; Cutrera, AP; Jones, L; Gürtler, RE; Kitron, U; Dotson, EM

2008-01-01

To gain an understanding of the genetic structure and dispersal dynamics of T. infestans populations, we analyzed the multilocus genotype of 10 microsatellite loci for 352 T. infestans collected in 21 houses of 11 rural communities in October 2002. Genetic structure was analyzed at the community and house compound levels. Analysis revealed that vector control actions affected the genetic structure of T. infestans populations. Bug populations from communities under sustained vector control (core area) were highly structured and genetic differentiation between neighboring house compounds was significant. In contrast, bug populations from communities with sporadic vector control actions were more homogeneous and lacked defined genetic clusters. Genetic differentiation between population pairs did not fit a model of isolation by distance at the microgeographical level. Evidence consistent with flight or walking bug dispersal was detected within and among communities, dispersal was more female-biased in the core area and results suggested that houses received immigrants from more than one source. Putative sources and mechanisms of re-infestation are described. These data may be use to design improved vector control strategies PMID:18773972

Heritable variation in host tolerance and resistance inferred from a wild host-parasite system.

PubMed

Mazé-Guilmo, Elise; Loot, Géraldine; Páez, David J; Lefèvre, Thierry; Blanchet, Simon

2014-03-22

Hosts have evolved two distinct defence strategies against parasites: resistance (which prevents infection or limit parasite growth) and tolerance (which alleviates the fitness consequences of infection). However, heritable variation in resistance and tolerance and the genetic correlation between these two traits have rarely been characterized in wild host populations. Here, we estimate these parameters for both traits in Leuciscus burdigalensis, a freshwater fish parasitized by Tracheliastes polycolpus. We used a genetic database to construct a full-sib pedigree in a wild L. burdigalensis population. We then used univariate animal models to estimate inclusive heritability (i.e. all forms of genetic and non-genetic inheritance) in resistance and tolerance. Finally, we assessed the genetic correlation between these two traits using a bivariate animal model. We found significant heritability for resistance (H = 17.6%; 95% CI: 7.2-32.2%) and tolerance (H = 18.8%; 95% CI: 4.4-36.1%), whereas we found no evidence for the existence of a genetic correlation between these traits. Furthermore, we confirm that resistance and tolerance are strongly affected by environmental effects. Our results demonstrate that (i) heritable variation exists for parasite resistance and tolerance in wild host populations, and (ii) these traits can evolve independently in populations.

Computational design of hepatitis C vaccines using empirical fitness landscapes and population dynamics

NASA Astrophysics Data System (ADS)

Hart, Gregory; Ferguson, Andrew

Hepatitis C virus (HCV) afflicts 170 million people and kills 350,000 annually. Vaccination offers the most realistic and cost effective hope of controlling this epidemic. Despite 25 years of research, no vaccine is available. A major obstacle is the virus' extreme genetic variability and rapid mutational escape from immune pressure. Improvements in the vaccine design process are urgently needed. Coupling data mining and maximum entropy inference, we have developed a computational approach to translate sequence databases into empirical fitness landscapes. These landscapes explicitly connect viral genotype to phenotypic fitness and reveal vulnerable targets that can be exploited to rationally design vaccines. These landscapes represent the mutational ''playing field'' over which the virus evolves. We have integrated them with agent-based models of the viral mutational and host immune response, establishing a data-driven multi-scale immune simulator. We have used this simulator to perform in silico screening of HCV immunogens to rationally design vaccines to both cripple viral fitness and block escape. By systematically identifying a small number of promising vaccine candidates, these models can accelerate the search for a vaccine by massively reducing the experimental search space.

Sensitivity of blackbody effective emissivity to wavelength and temperature: By genetic algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ejigu, E. K.; Liedberg, H. G.

A variable-temperature blackbody (VTBB) is used to calibrate an infrared radiation thermometer (pyrometer). The effective emissivity (ε{sub eff}) of a VTBB is dependent on temperature and wavelength other than the geometry of the VTBB. In the calibration process the effective emissivity is often assumed to be constant within the wavelength and temperature range. There are practical situations where the sensitivity of the effective emissivity needs to be known and correction has to be applied. We present a method using a genetic algorithm to investigate the sensitivity of the effective emissivity to wavelength and temperature variation. Two matlab® programs are generated:more » the first to model the radiance temperature calculation and the second to connect the model to the genetic algorithm optimization toolbox. The effective emissivity parameter is taken as a chromosome and optimized at each wavelength and temperature point. The difference between the contact temperature (reading from a platinum resistance thermometer or liquid in glass thermometer) and radiance temperature (calculated from the ε{sub eff} values) is used as an objective function where merit values are calculated and best fit ε{sub eff} values selected. The best fit ε{sub eff} values obtained as a solution show how sensitive they are to temperature and wavelength parameter variation. Uncertainty components that arise from wavelength and temperature variation are determined based on the sensitivity analysis. Numerical examples are considered for illustration.« less

Genetic parameters for linear type traits and milk, fat, and protein production in holstein cows in Brazil.

PubMed

Campos, Rafael Viegas; Cobuci, Jaime Araujo; Kern, Elisandra Lurdes; Costa, Cláudio Napolis; McManus, Concepta Margaret

2015-04-01

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (-0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd.

Genetic Parameters for Linear Type Traits and Milk, Fat, and Protein Production in Holstein Cows in Brazil

PubMed Central

Campos, Rafael Viegas; Cobuci, Jaime Araujo; Kern, Elisandra Lurdes; Costa, Cláudio Napolis; McManus, Concepta Margaret

2015-01-01

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (−0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd. PMID:25656190

On Cellular Darwinism: Mitochondria.

PubMed

Bull, Larry

2016-01-01

The significant role of mitochondria within cells is becoming increasingly clear. This letter uses the NKCS model of coupled fitness landscapes to explore aspects of organelle-nucleus coevolution. The phenomenon of mitochondrial diversity is allowed to emerge under a simple intracellular evolutionary process, including varying the relative rate of evolution by the organelle. It is shown how the conditions for the maintenance of more than one genetic variant of mitochondria are similar to those previously suggested as needed for the original symbiotic origins of the relationship using the NKCS model.

Structural Plasticity and Rapid Evolution in a Viral RNA Revealed by In Vivo Genetic Selection▿ †

PubMed Central

Guo, Rong; Lin, Wai; Zhang, Jiuchun; Simon, Anne E.; Kushner, David B.

2009-01-01

Satellite RNAs usually lack substantial homology with their helper viruses. The 356-nucleotide satC of Turnip crinkle virus (TCV) is unusual in that its 3′-half shares high sequence similarity with the TCV 3′ end. Computer modeling, structure probing, and/or compensatory mutagenesis identified four hairpins and three pseudoknots in this TCV region that participate in replication and/or translation. Two hairpins and two pseudoknots have been confirmed as important for satC replication. One portion of the related 3′ end of satC that remains poorly characterized corresponds to juxtaposed TCV hairpins H4a and H4b and pseudoknot ψ3, which are required for the TCV-specific requirement of translation (V. A. Stupina et al., RNA 14:2379-2393, 2008). Replacement of satC H4a with randomized sequence and scoring for fitness in plants by in vivo genetic selection (SELEX) resulted in winning sequences that contain an H4a-like stem-loop, which can have additional upstream sequence composing a portion of the stem. SELEX of the combined H4a and H4b region in satC generated three distinct groups of winning sequences. One group models into two stem-loops similar to H4a and H4b of TCV. However, the selected sequences in the other two groups model into single hairpins. Evolution of these single-hairpin SELEX winners in plants resulted in satC that can accumulate to wild-type (wt) levels in protoplasts but remain less fit in planta when competed against wt satC. These data indicate that two highly distinct RNA conformations in the H4a and H4b region can mediate satC fitness in protoplasts. PMID:19004956

A framework for evolutionary systems biology

PubMed Central

Loewe, Laurence

2009-01-01

Background Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. Results Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. Conclusion EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications. PMID:19239699

Males and Females Contribute Unequally to Offspring Genetic Diversity in the Polygynandrous Mating System of Wild Boar

PubMed Central

Pérez-González, Javier; Costa, Vânia; Santos, Pedro; Slate, Jon; Carranza, Juan; Fernández-Llario, Pedro; Zsolnai, Attila; Monteiro, Nuno M.; Anton, István; Buzgó, József; Varga, Gyula; Beja-Pereira, Albano

2014-01-01

The maintenance of genetic diversity across generations depends on both the number of reproducing males and females. Variance in reproductive success, multiple paternity and litter size can all affect the relative contributions of male and female parents to genetic variation of progeny. The mating system of the wild boar (Sus scrofa) has been described as polygynous, although evidence of multiple paternity in litters has been found. Using 14 microsatellite markers, we evaluated the contribution of males and females to genetic variation in the next generation in independent wild boar populations from the Iberian Peninsula and Hungary. Genetic contributions of males and females were obtained by distinguishing the paternal and maternal genetic component inherited by the progeny. We found that the paternally inherited genetic component of progeny was more diverse than the maternally inherited component. Simulations showed that this finding might be due to a sampling bias. However, after controlling for the bias by fitting both the genetic diversity in the adult population and the number of reproductive individuals in the models, paternally inherited genotypes remained more diverse than those inherited maternally. Our results suggest new insights into how promiscuous mating systems can help maintain genetic variation. PMID:25541986

APOE polymorphism as a potential determinant of functional fitness in the elderly regardless of nutritional status.

PubMed

Snejdrlova, Michaela; Kalvach, Zdenek; Topinkova, Eva; Vrablik, Michal; Prochazkova, Renata; Kvasilova, Marie; Lanska, Vera; Zlatohlavek, Lukas; Prusikova, Martina; Ceska, Richard

2011-01-01

Life expectancy is determined by a combination of genetic predisposition (~25%) and environmental influences (~75%). Nevertheless a stronger genetic influence is anticipated in long-living individuals. Apolipoprotein E (APOE) gene belongs among the most studied candidate genes of longevity. We evaluated the relation of APOE polymorphism and fitness status in the elderly. We examined a total number of 128 subjects, over 80 years of age. Using a battery of functional tests their fitness status was assessed and the subjects were stratified into 5 functional categories according to Spirduso´s classification. Biochemistry analysis was performed by enzymatic method using automated analyzers. APOE gene polymorphism was analysed performed using PCR-RFLP. APOE4 allele carriers had significantly worse fitness status compared to non-carriers (p=0.025). Multiple logistic regression analysis showed the APOE4 carriers had higher risk (p=0.05) of functional unfitness compared to APOE2/E3 individuals. APOE gene polymorphism seems be an important genetic contributor to frailty development in the elderly. While APOE2 carriers tend to remain functionally fit till higher age, the functional status of APOE4 carriers deteriorates more rapidly. © 2011 Neuroendocrinology Letters

Modelling the impact of the long-term use of insecticide-treated bed nets on Anopheles mosquito biting time.

PubMed

Ferreira, Claudia P; Lyra, Silas P; Azevedo, Franciane; Greenhalgh, David; Massad, Eduardo

2017-09-15

Evidence of changing in biting and resting behaviour of the main malaria vectors has been mounting up in recent years as a result of selective pressure by the widespread and long-term use of insecticide-treated bed nets (ITNs), and indoor residual spraying. The impact of resistance behaviour on malaria intervention efficacy has important implications for the epidemiology and malaria control programmes. In this context, a theoretical framework is presented to understand the mechanisms determining the evolution of feeding behaviour under the pressure of use of ITNs. An agent-based stochastic model simulates the impact of insecticide-treated bed nets on mosquito fitness by reducing the biting rates, as well as increasing mortality rates. The model also incorporates a heritability function that provides the necessary genetic plasticity upon which natural selection would act to maximize the fitness under the pressure of the control strategy. The asymptotic equilibrium distribution of mosquito population versus biting time is shown for several daily uses of ITNs, and the expected disruptive selection on this mosquito trait is observed in the simulations. The relative fitness of strains that bite at much earlier time with respect to the wild strains, when a threshold of about 50% of ITNs coverage highlights the hypothesis of a behaviour selection. A sensitivity analysis has shown that the top three parameters that play a dominant role on the mosquito fitness are the proportion of individuals using bed nets and its effectiveness, the impact of bed nets on mosquito oviposition, and the mosquito genetic plasticity related to changing in biting time. By taking the evolutionary aspect into account, the model was able to show that the long-term use of ITNs, although representing an undisputed success in reducing malaria incidence and mortality in many affected areas, is not free of undesirable side effects. From the evolutionary point of view of the parasite virulence, it should be expected that plasmodium parasites would be under pressure to reduce their virulence. This speculative hypothesis can eventually be demonstrated in the medium to long-term use of ITNs.

Similarity selection and the evolution of sex: revisiting the red queen.

PubMed

Agrawal, Aneil F

2006-08-01

For over 25 years, many evolutionary ecologists have believed that sexual reproduction occurs because it allows hosts to change genotypes each generation and thereby evade their coevolving parasites. However, recent influential theoretical analyses suggest that, though parasites can select for sex under some conditions, they often select against it. These models assume that encounters between hosts and parasites are completely random. Because of this assumption, the fitness of a host depends only on its own genotype ("genotypic selection"). If a host is even slightly more likely to encounter a parasite transmitted by its mother than expected by random chance, then the fitness of a host also depends on its genetic similarity to its mother ("similarity selection"). A population genetic model is presented here that includes both genotypic and similarity selection, allowing them to be directly compared in the same framework. It is shown that similarity selection is a much more potent force with respect to the evolution of sex than is genotypic selection. Consequently, similarity selection can drive the evolution of sex even if it is much weaker than genotypic selection with respect to fitness. Examination of explicit coevolutionary models reveals that even a small degree of mother-offspring parasite transmission can cause parasites to favor sex rather than oppose it. In contrast to previous predictions, the model shows that weakly virulent parasites are more likely to favor sex than are highly virulent ones. Parasites have figured prominently in discussions of the evolution of sex, but recent models suggest that parasites often select against sex rather than for it. With the inclusion of small and realistic exposure biases, parasites are much more likely to favor sex. Though parasites alone may not provide a complete explanation for sex, the results presented here expand the potential for parasites to contribute to the maintenance of sex rather than act against it.

Divergent selection on, but no genetic conflict over, female and male timing and rate of reproduction in a human population

PubMed Central

Bolund, Elisabeth; Bouwhuis, Sandra; Pettay, Jenni E.; Lummaa, Virpi

2013-01-01

The sexes often have different phenotypic optima for important life-history traits, and because of a largely shared genome this can lead to a conflict over trait expression. In mammals, the obligate costs of reproduction are higher for females, making reproductive timing and rate especially liable to conflict between the sexes. While studies from wild vertebrates support such sexual conflict, it remains unexplored in humans. We used a pedigreed human population from preindustrial Finland to estimate sexual conflict over age at first and last reproduction, reproductive lifespan and reproductive rate. We found that the phenotypic selection gradients differed between the sexes. We next established significant heritabilities in both sexes for all traits. All traits, except reproductive rate, showed strongly positive intersexual genetic correlations and were strongly genetically correlated with fitness in both sexes. Moreover, the genetic correlations with fitness were almost identical in men and women. For reproductive rate, the intersexual correlation and the correlation with fitness were weaker but again similar between the sexes. Thus, in this population, an apparent sexual conflict at the phenotypic level did not reflect an underlying genetic conflict over the studied reproductive traits. These findings emphasize the need for incorporating genetic perspectives into studies of human life-history evolution. PMID:24107531

Divergent selection on, but no genetic conflict over, female and male timing and rate of reproduction in a human population.

PubMed

Bolund, Elisabeth; Bouwhuis, Sandra; Pettay, Jenni E; Lummaa, Virpi

2013-12-07

The sexes often have different phenotypic optima for important life-history traits, and because of a largely shared genome this can lead to a conflict over trait expression. In mammals, the obligate costs of reproduction are higher for females, making reproductive timing and rate especially liable to conflict between the sexes. While studies from wild vertebrates support such sexual conflict, it remains unexplored in humans. We used a pedigreed human population from preindustrial Finland to estimate sexual conflict over age at first and last reproduction, reproductive lifespan and reproductive rate. We found that the phenotypic selection gradients differed between the sexes. We next established significant heritabilities in both sexes for all traits. All traits, except reproductive rate, showed strongly positive intersexual genetic correlations and were strongly genetically correlated with fitness in both sexes. Moreover, the genetic correlations with fitness were almost identical in men and women. For reproductive rate, the intersexual correlation and the correlation with fitness were weaker but again similar between the sexes. Thus, in this population, an apparent sexual conflict at the phenotypic level did not reflect an underlying genetic conflict over the studied reproductive traits. These findings emphasize the need for incorporating genetic perspectives into studies of human life-history evolution.

Improved modeling of GaN HEMTs for predicting thermal and trapping-induced-kink effects

NASA Astrophysics Data System (ADS)

Jarndal, Anwar; Ghannouchi, Fadhel M.

2016-09-01

In this paper, an improved modeling approach has been developed and validated for GaN high electron mobility transistors (HEMTs). The proposed analytical model accurately simulates the drain current and its inherent trapping and thermal effects. Genetic-algorithm-based procedure is developed to automatically find the fitting parameters of the model. The developed modeling technique is implemented on a packaged GaN-on-Si HEMT and validated by DC and small-/large-signal RF measurements. The model is also employed for designing and realizing a switch-mode inverse class-F power amplifier. The amplifier simulations showed a very good agreement with RF large-signal measurements.

Genetic aspect of Alzheimer disease: Results of complex segregation analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadonvick, A.D.; Lee, I.M.L.; Bailey-Wilson, J.E.

1994-09-01

The study was designed to evaluate the possibility that a single major locus will explain the segregation of Alzheimer disease (AD). The data were from the population-based AD Genetic Database and consisted of 402 consecutive, unrelated probands, diagnosed to have either `probable` or `autopsy confirmed` AD and their 2,245 first-degree relatives. In this analysis, a relative was considered affected with AD only when there were sufficient medical/autopsy data to support diagnosis of AD being the most likely cause of the dementia. Transmission probability models allowing for a genotype-dependent and logistically distributed age-of-onset were used. The program REGTL in the S.A.G.E.more » computer program package was used for a complex segregation analysis. The models included correction for single ascertainment. Regressive familial effects were not estimated. The data were analyzed to test for single major locus (SML), random transmission and no transmission (environmental) hypotheses. The results of the complex segregation analysis showed that (1) the SML was the best fit, and (2) the non-genetic models could be rejected.« less

Importance and pitfalls of molecular analysis to parasite epidemiology.

PubMed

Constantine, Clare C

2003-08-01

Molecular tools are increasingly being used to address questions about parasite epidemiology. Parasites represent a diverse group and they might not fit traditional population genetic models. Testing hypotheses depends equally on correct sampling, appropriate tool and/or marker choice, appropriate analysis and careful interpretation. All methods of analysis make assumptions which, if violated, make the results invalid. Some guidelines to avoid common pitfalls are offered here.

Heterogeneity among Isolates Reveals that Fitness in Low Oxygen Correlates with Aspergillus fumigatus Virulence.

PubMed

Kowalski, Caitlin H; Beattie, Sarah R; Fuller, Kevin K; McGurk, Elizabeth A; Tang, Yi-Wei; Hohl, Tobias M; Obar, Joshua J; Cramer, Robert A

2016-09-20

Previous work has shown that environmental and clinical isolates of Aspergillus fumigatus represent a diverse population that occupies a variety of niches, has extensive genetic diversity, and exhibits virulence heterogeneity in a number of animal models of invasive pulmonary aspergillosis (IPA). However, mechanisms explaining differences in virulence among A. fumigatus isolates remain enigmatic. Here, we report a significant difference in virulence of two common lab strains, CEA10 and AF293, in the murine triamcinolone immunosuppression model of IPA, in which we previously identified severe low oxygen microenvironments surrounding fungal lesions. Therefore, we hypothesize that the ability to thrive within these lesions of low oxygen promotes virulence of A. fumigatus in this model. To test this hypothesis, we performed in vitro fitness and in vivo virulence analyses in the triamcinolone murine model of IPA with 14 environmental and clinical isolates of A. fumigatus Among these isolates, we observed a strong correlation between fitness in low oxygen in vitro and virulence. In further support of our hypothesis, experimental evolution of AF293, a strain that exhibits reduced fitness in low oxygen and reduced virulence in the triamcinolone model of IPA, results in a strain (EVOL20) that has increased hypoxia fitness and a corresponding increase in virulence. Thus, the ability to thrive in low oxygen correlates with virulence of A. fumigatus isolates in the context of steroid-mediated murine immunosuppression. Aspergillus fumigatus occupies multiple environmental niches, likely contributing to the genotypic and phenotypic heterogeneity among isolates. Despite reports of virulence heterogeneity, pathogenesis studies often utilize a single strain for the identification and characterization of virulence and immunity factors. Here, we describe significant variation between A. fumigatus isolates in hypoxia fitness and virulence, highlighting the advantage of including multiple strains in future studies. We also illustrate that hypoxia fitness correlates strongly with increased virulence exclusively in the nonleukopenic murine triamcinolone immunosuppression model of IPA. Through an experimental evolution experiment, we observe that chronic hypoxia exposure results in increased virulence of A. fumigatus We describe here the first observation of a model-specific virulence phenotype correlative with in vitro fitness in hypoxia and pave the way for identification of hypoxia-mediated mechanisms of virulence in the fungal pathogen A. fumigatus. Copyright © 2016 Kowalski et al.

Association between stressful life events and psychotic experiences in adolescence: evidence for gene-environment correlations.

PubMed

Shakoor, Sania; Zavos, Helena M S; Haworth, Claire M A; McGuire, Phillip; Cardno, Alastair G; Freeman, Daniel; Ronald, Angelica

2016-06-01

Stressful life events (SLEs) are associated with psychotic experiences. SLEs might act as an environmental risk factor, but may also share a genetic propensity with psychotic experiences. To estimate the extent to which genetic and environmental factors influence the relationship between SLEs and psychotic experiences. Self- and parent reports from a community-based twin sample (4830 16-year-old pairs) were analysed using structural equation model fitting. SLEs correlated with positive psychotic experiences (r = 0.12-0.14, all P<0.001). Modest heritability was shown for psychotic experiences (25-57%) and dependent SLEs (32%). Genetic influences explained the majority of the modest covariation between dependent SLEs and paranoia and cognitive disorganisation (bivariate heritabilities 74-86%). The relationship between SLEs and hallucinations and grandiosity was explained by both genetic and common environmental effects. Further to dependent SLEs being an environmental risk factor, individuals may have an underlying genetic propensity increasing their risk of dependent SLEs and positive psychotic experiences. © The Royal College of Psychiatrists 2016.

Mathematical Ability of 10-Year-Old Boys and Girls: Genetic and Environmental Etiology of Typical and Low Performance

PubMed Central

Kovas, Yulia; Haworth, Claire M. A.; Petrill, Stephen A.; Plomin, Robert

2009-01-01

The genetic and environmental etiologies of 3 aspects of low mathematical performance (math disability) and the full range of variability (math ability) were compared for boys and girls in a sample of 5,348 children age 10 years (members of 2,674 pairs of same-sex and opposite-sex twins) from the United Kingdom (UK). The measures, which we developed for Web-based testing, included problems from 3 domains of mathematics taught as part of the UK National Curriculum. Using quantitative genetic model-fitting analyses, similar results were found for math disabilities and abilities for all 3 measures: Moderate genetic influence and environmental influence were mainly due to nonshared environmental factors that were unique to the individual, with little influence from shared environment. No sex differences were found in the etiologies of math abilities and disabilities. We conclude that low mathematical performance is the quantitative extreme of the same genetic and environmental factors responsible for variation throughout the distribution. PMID:18064980

The Genetic and Environmental Etiologies of Individual Differences in Early Reading Growth in Australia, the United States, and Scandinavia

PubMed Central

Christopher, Micaela E.; Hulslander, Jacqueline; Byrne, Brian; Samuelsson, Stefan; Keenan, Janice M.; Pennington, Bruce; DeFries, John C.; Wadsworth, Sally J.; Willcutt, Erik; Olson, Richard K.

2013-01-01

This first cross-country twin study of individual differences in reading growth from post-kindergarten to post-2nd grade analyzed data from 487 twin pairs from the United States, 267 pairs from Australia, and 280 pairs from Scandinavia. Data from two reading measures were fit to biometric latent growth models. Individual differences for the reading measures at post-kindergarten in the U.S. and Australia were due primarily to genetic influences, and to both genetic and shared environmental influences in Scandinavia. In contrast, individual differences in growth generally had large genetic influences in all countries. These results suggest that genetic influences are largely responsible for individual differences in early reading development. In addition, the timing of the start of formal literacy instruction may affect the etiology of individual differences in early reading development, but have only limited influence on the etiology of individual differences in growth. PMID:23665180

The Unique and Shared Genetic and Environmental Contributions to Fear, Anger, and Sadness in Childhood

PubMed Central

Clifford, Sierra; Lemery-Chalfant, Kathryn; Goldsmith, H. Hill

2015-01-01

This study examined the extent to which subordinate dimensions of negative emotionality were genetically and environmentally distinct in a sample of 1316 twins (51% female, 85.8% Caucasian, primarily middle class, mean age = 7.87 years, SD = .93), recruited from Wisconsin hospital birth records between 1989 and 2004. Cholesky, independent pathway, and common pathway models were fitted for mother-report, father-report, and in-home observation of temperament. Although findings support the use of negative emotionality, there were heritable aspects of anger and fear not explained by a common genetic factor, and shared environmental influences common to anger and sadness but not fear. Observed fear was independent from observed anger and sadness. Distinctions support specificity in measurement when considering implications for child development. PMID:26182850

Older fathers' children have lower evolutionary fitness across four centuries and in four populations

PubMed Central

Willführ, Kai P.; Frans, Emma M.; Verweij, Karin J. H.; Bürkner, Paul-Christian; Myrskylä, Mikko; Voland, Eckart; Zietsch, Brendan P.; Penke, Lars

2017-01-01

Higher paternal age at offspring conception increases de novo genetic mutations. Based on evolutionary genetic theory we predicted older fathers' children, all else equal, would be less likely to survive and reproduce, i.e. have lower fitness. In sibling control studies, we find support for negative paternal age effects on offspring survival and reproductive success across four large populations with an aggregate N > 1.4 million. Three populations were pre-industrial (1670–1850) Western populations and showed negative paternal age effects on infant survival and offspring reproductive success. In twentieth-century Sweden, we found minuscule paternal age effects on survival, but found negative effects on reproductive success. Effects survived tests for key competing explanations, including maternal age and parental loss, but effects varied widely over different plausible model specifications and some competing explanations such as diminishing paternal investment and epigenetic mutations could not be tested. We can use our findings to aid in predicting the effect increasingly older parents in today's society will have on their children's survival and reproductive success. To the extent that we succeeded in isolating a mutation-driven effect of paternal age, our results can be understood to show that de novo mutations reduce offspring fitness across populations and time periods. PMID:28904145

Detecting consistent patterns of directional adaptation using differential selection codon models.

PubMed

Parto, Sahar; Lartillot, Nicolas

2017-06-23

Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

A twin study of cardiac reactivity and its relationship to parental blood pressure.

PubMed

Carroll, D; Hewitt, J K; Last, K A; Turner, J R; Sims, J

1985-01-01

The cardiac reactivity of 40 monozygotic and 40 dizygotic pairs of young male twins was monitored during psychological challenge, as afforded by a video game. The observed pattern of variation could not be accounted for solely by environmental factors. In fact, a simple genetic model that implicated additive genetic effects, along with those stemming from individual environments, best fitted the data. In addition, cardiac reactions were substantially greater for subjects whose parents both had relatively elevated blood pressure. Overall, these data suggest individual differences in cardiac reactivity have a heritable component, and that high reactivity may be a precursor of elevated blood pressure.

Competitive fitness of influenza B viruses with neuraminidase inhibitor-resistant substitutions in a coinfection model of the human airway epithelium.

PubMed

Burnham, Andrew J; Armstrong, Jianling; Lowen, Anice C; Webster, Robert G; Govorkova, Elena A

2015-04-01

Influenza A and B viruses are human pathogens that are regarded to cause almost equally significant disease burdens. Neuraminidase (NA) inhibitors (NAIs) are the only class of drugs available to treat influenza A and B virus infections, so the development of NAI-resistant viruses with superior fitness is a public health concern. The fitness of NAI-resistant influenza B viruses has not been widely studied. Here we examined the replicative capacity and relative fitness in normal human bronchial epithelial (NHBE) cells of recombinant influenza B/Yamanashi/166/1998 viruses containing a single amino acid substitution in NA generated by reverse genetics (rg) that is associated with NAI resistance. The replication in NHBE cells of viruses with reduced inhibition by oseltamivir (recombinant virus with the E119A mutation generated by reverse genetics [rg-E119A], rg-D198E, rg-I222T, rg-H274Y, rg-N294S, and rg-R371K, N2 numbering) or zanamivir (rg-E119A and rg-R371K) failed to be inhibited by the presence of the respective NAI. In a fluorescence-based assay, detection of rg-E119A was easily masked by the presence of NAI-susceptible virus. We coinfected NHBE cells with NAI-susceptible and -resistant viruses and used next-generation deep sequencing to reveal the order of relative fitness compared to that of recombinant wild-type (WT) virus generated by reverse genetics (rg-WT): rg-H274Y > rg-WT > rg-I222T > rg-N294S > rg-D198E > rg-E119A ≫ rg-R371K. Based on the lack of attenuated replication of rg-E119A in NHBE cells in the presence of oseltamivir or zanamivir and the fitness advantage of rg-H274Y over rg-WT, we emphasize the importance of these substitutions in the NA glycoprotein. Human infections with influenza B viruses carrying the E119A or H274Y substitution could limit the therapeutic options for those infected; the emergence of such viruses should be closely monitored. Influenza B viruses are important human respiratory pathogens contributing to a significant portion of seasonal influenza virus infections worldwide. The development of resistance to a single class of available antivirals, the neuraminidase (NA) inhibitors (NAIs), is a public health concern. Amino acid substitutions in the NA glycoprotein of influenza B virus not only can confer antiviral resistance but also can alter viral fitness. Here we used normal human bronchial epithelial (NHBE) cells, a model of the human upper respiratory tract, to examine the replicative capacities and fitness of NAI-resistant influenza B viruses. We show that virus with an E119A NA substitution can replicate efficiently in NHBE cells in the presence of oseltamivir or zanamivir and that virus with the H274Y NA substitution has a relative fitness greater than that of the wild-type NAI-susceptible virus. This study is the first to use NHBE cells to determine the fitness of NAI-resistant influenza B viruses. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Ecogeography, genetics, and the evolution of human body form.

PubMed

Roseman, Charles C; Auerbach, Benjamin M

2015-01-01

Genetic resemblances among groups are non-randomly distributed in humans. This population structure may influence the correlations between traits and environmental drivers of natural selection thus complicating the interpretation of the fossil record when modern human variation is used as a referential model. In this paper, we examine the effects of population structure and natural selection on postcranial traits that reflect body size and shape with application to the more general issue of how climate - using latitude as a proxy - has influenced hominin morphological variation. We compare models that include terms reflecting population structure, ascertained from globally distributed microsatellite data, and latitude on postcranial phenotypes derived from skeletal dimensions taken from a large global sample of modern humans. We find that models with a population structure term fit better than a model of natural selection along a latitudinal cline in all cases. A model including both latitude and population structure terms is a good fit to distal limb element lengths and bi-iliac breadth, indicating that multiple evolutionary forces shaped these morphologies. In contrast, a model that included only a population structure term best explained femoral head diameter and the crural index. The results demonstrate that population structure is an important part of human postcranial variation, and that clinally distributed natural selection is not sufficient to explain among-group differentiation. The distribution of human body form is strongly influenced by the contingencies of modern human origins, which calls for new ways to approach problems in the evolution of human variation, past and present. Copyright © 2014 Elsevier Ltd. All rights reserved.

Adapting to a Changing Environment: Modeling the Interaction of Directional Selection and Plasticity.

PubMed

Nunney, Leonard

2016-01-01

Human-induced habitat loss and fragmentation constrains the range of many species, making them unable to respond to climate change by moving. For such species to avoid extinction, they must respond with some combination of phenotypic plasticity and genetic adaptation. Haldane's "cost of natural selection" limits the rate of adaptation, but, although modeling has shown that in very large populations long-term adaptation can be maintained at rates substantially faster than Haldane's suggested limit, maintaining large populations is often an impossibility, so phenotypic plasticity may be crucial in enhancing the long-term survival of small populations. The potential importance of plasticity is in "buying time" for populations subject to directional environmental change: if genotypes can encompass a greater environmental range, then populations can maintain high fitness for a longer period of time. Alternatively, plasticity could be detrimental by lessening the effectiveness of natural selection in promoting genetic adaptation. Here, I modeled a directionally changing environment in which a genotype's adaptive phenotypic plasticity is centered around the environment where its fitness is highest. Plasticity broadens environmental tolerance and, provided it is not too costly, is favored by natural selection. However, a paradoxical result of the individually advantageous spread of plasticity is that, unless the adaptive trait is determined by very few loci, the long-term extinction risk of a population increases. This effect reflects a conflict between the short-term individual benefit of plasticity and a long-term detriment to population persistence, adding to the multiple threats facing small populations under conditions of climate change. © The American Genetic Association. 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Critical Buckling Pressure in Mouse Carotid Arteries with Altered Elastic Fibers

PubMed Central

Luetkemeyer, Callan M.; James, Rhys H.; Devarakonda, Siva Teja; Le, Victoria P.; Liu, Qin; Han, Hai-Chao; Wagenseil, Jessica E.

2015-01-01

Arteries can buckle axially under applied critical buckling pressure due to a mechanical instability. Buckling can cause arterial tortuosity leading to flow irregularities and stroke. Genetic mutations in elastic fiber proteins are associated with arterial tortuosity in humans and mice, and may be the result of alterations in critical buckling pressure. Hence, the objective of this study is to investigate how genetic defects in elastic fibers affect buckling pressure. We use mouse models of human disease with reduced amounts of elastin (Eln+/−) and with defects in elastic fiber assembly due to the absence of fibulin-5 (Fbln5−/−). We find that Eln+/− arteries have reduced buckling pressure compared to their wild-type controls. Fbln5−/− arteries have similar buckling pressure to wild-type at low axial stretch, but increased buckling pressure at high stretch. We fit material parameters to mechanical test data for Eln+/−, Fbln5−/− and wild-type arteries using Fung and four-fiber strain energy functions. Fitted parameters are used to predict theoretical buckling pressure based on equilibrium of an inflated, buckled, thick-walled cylinder. In general, the theoretical predictions underestimate the buckling pressure at low axial stretch and overestimate the buckling pressure at high stretch. The theoretical predictions with both models replicate the increased buckling pressure at high stretch for Fbln5−/− arteries, but the four-fiber model predictions best match the experimental trends in buckling pressure changes with axial stretch. This study provides experimental and theoretical methods for further investigating the influence of genetic mutations in elastic fibers on buckling behavior and the development of arterial tortuosity. PMID:25771258

Genetic divergence in the common bush-tanager Chlorospingus ophthalmicus (Aves: Emberizidae) throughout Mexican cloud forests: The role of geography, ecology and Pleistocene climatic fluctuations.

PubMed

Maldonado-Sánchez, Denisse; Gutiérrez-Rodríguez, Carla; Ornelas, Juan Francisco

2016-06-01

By integrating mitochondrial DNA (mtDNA), microsatellites and ecological niche modelling (ENM), we investigated the phylogeography of Mexican populations of the common bush-tanager Chlorospingus ophthalmicus to examine the relative role of geographical and ecological features, as well as Pleistocene climatic oscillations in driving the diversification. We sequenced mtDNA of individuals collected throughout the species range in Mexico and genotyped them at seven microsatellite loci. Phylogeographic, population genetics and coalescent methods were used to assess patterns of genetic structure, gene flow and demographic history. ENM was used to infer contractions and expansions at different time periods as well as differences in climatic conditions among lineages. The retrieved mitochondrial and microsatellite groups correspond with the fragmented cloud forest distribution in mountain ranges and morphotectonic provinces. Differing climatic conditions between mountain ranges were detected, and palaeodistribution modelling as well as demographic history analyses, indicated recent population expansions throughout the Sierra Madre Oriental (SMO). The marked genetic structure of C. ophthalmicus was promoted by the presence of ecological and geographical barriers that restricted the movement of individuals among mountain ranges. The SMO was mainly affected by Pleistocene climatic oscillations, with the moist forests model best fitting the displayed genetic patterns of populations in this mountain range. Copyright © 2016 Elsevier Inc. All rights reserved.

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.

PubMed

Shaw, Ruth G; Etterson, Julie R

2012-09-01

Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Model predictive control of attitude maneuver of a geostationary flexible satellite based on genetic algorithm

NASA Astrophysics Data System (ADS)

TayyebTaher, M.; Esmaeilzadeh, S. Majid

2017-07-01

This article presents an application of Model Predictive Controller (MPC) to the attitude control of a geostationary flexible satellite. SIMO model has been used for the geostationary satellite, using the Lagrange equations. Flexibility is also included in the modelling equations. The state space equations are expressed in order to simplify the controller. Naturally there is no specific tuning rule to find the best parameters of an MPC controller which fits the desired controller. Being an intelligence method for optimizing problem, Genetic Algorithm has been used for optimizing the performance of MPC controller by tuning the controller parameter due to minimum rise time, settling time, overshoot of the target point of the flexible structure and its mode shape amplitudes to make large attitude maneuvers possible. The model included geosynchronous orbit environment and geostationary satellite parameters. The simulation results of the flexible satellite with attitude maneuver shows the efficiency of proposed optimization method in comparison with LQR optimal controller.

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models

PubMed Central

Chen, Han; Wang, Chaolong; Conomos, Matthew P.; Stilp, Adrienne M.; Li, Zilin; Sofer, Tamar; Szpiro, Adam A.; Chen, Wei; Brehm, John M.; Celedón, Juan C.; Redline, Susan; Papanicolaou, George J.; Thornton, Timothy A.; Laurie, Cathy C.; Rice, Kenneth; Lin, Xihong

2016-01-01

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM’s constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. PMID:27018471

Genetic Programming Transforms in Linear Regression Situations

NASA Astrophysics Data System (ADS)

Castillo, Flor; Kordon, Arthur; Villa, Carlos

The chapter summarizes the use of Genetic Programming (GP) inMultiple Linear Regression (MLR) to address multicollinearity and Lack of Fit (LOF). The basis of the proposed method is applying appropriate input transforms (model respecification) that deal with these issues while preserving the information content of the original variables. The transforms are selected from symbolic regression models with optimal trade-off between accuracy of prediction and expressional complexity, generated by multiobjective Pareto-front GP. The chapter includes a comparative study of the GP-generated transforms with Ridge Regression, a variant of ordinary Multiple Linear Regression, which has been a useful and commonly employed approach for reducing multicollinearity. The advantages of GP-generated model respecification are clearly defined and demonstrated. Some recommendations for transforms selection are given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistical model building by MLR.

Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe

PubMed Central

Wymant, Chris; Cornelissen, Marion; Gall, Astrid; Bakker, Margreet; Bezemer, Daniela; Hall, Matthew; Hillebregt, Mariska; Ong, Swee Hoe; Albert, Jan; Bannert, Norbert; Fellay, Jacques; Fransen, Katrien; Gourlay, Annabelle J.; Grabowski, M. Kate; Gunsenheimer-Bartmeyer, Barbara; Günthard, Huldrych F.; Kivelä, Pia; Kouyos, Roger; Laeyendecker, Oliver; Liitsola, Kirsi; Meyer, Laurence; Porter, Kholoud; Ristola, Matti; van Sighem, Ard; Vanham, Guido; Berkhout, Ben; Kellam, Paul; Reiss, Peter; Fraser, Christophe

2017-01-01

HIV-1 set-point viral load—the approximately stable value of viraemia in the first years of chronic infection—is a strong predictor of clinical outcome and is highly variable across infected individuals. To better understand HIV-1 pathogenesis and the evolution of the viral population, we must quantify the heritability of set-point viral load, which is the fraction of variation in this phenotype attributable to viral genetic variation. However, current estimates of heritability vary widely, from 6% to 59%. Here we used a dataset of 2,028 seroconverters infected between 1985 and 2013 from 5 European countries (Belgium, Switzerland, France, the Netherlands and the United Kingdom) and estimated the heritability of set-point viral load at 31% (CI 15%–43%). Specifically, heritability was measured using models of character evolution describing how viral load evolves on the phylogeny of whole-genome viral sequences. In contrast to previous studies, (i) we measured viral loads using standardized assays on a sample collected in a strict time window of 6 to 24 months after infection, from which the viral genome was also sequenced; (ii) we compared 2 models of character evolution, the classical “Brownian motion” model and another model (“Ornstein–Uhlenbeck”) that includes stabilising selection on viral load; (iii) we controlled for covariates, including age and sex, which may inflate estimates of heritability; and (iv) we developed a goodness of fit test based on the correlation of viral loads in cherries of the phylogenetic tree, showing that both models of character evolution fit the data well. An overall heritability of 31% (CI 15%–43%) is consistent with other studies based on regression of viral load in donor–recipient pairs. Thus, about a third of variation in HIV-1 virulence is attributable to viral genetic variation. PMID:28604782

Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

NASA Astrophysics Data System (ADS)

Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

Relatedness in spatially structured populations with empty sites: An approach based on spatial moment equations.

PubMed

Lion, Sébastien

2009-09-07

Taking into account the interplay between spatial ecological dynamics and selection is a major challenge in evolutionary ecology. Although inclusive fitness theory has proven to be a very useful tool to unravel the interactions between spatial genetic structuring and selection, applications of the theory usually rely on simplifying demographic assumptions. In this paper, I attempt to bridge the gap between spatial demographic models and kin selection models by providing a method to compute approximations for relatedness coefficients in a spatial model with empty sites. Using spatial moment equations, I provide an approximation of nearest-neighbour relatedness on random regular networks, and show that this approximation performs much better than the ordinary pair approximation. I discuss the connection between the relatedness coefficients I define and those used in population genetics, and sketch some potential extensions of the theory.

The Effect and Relative Importance of Neutral Genetic Diversity for Predicting Parasitism Varies across Parasite Taxa

PubMed Central

Ruiz-López, María José; Monello, Ryan J.; Gompper, Matthew E.; Eggert, Lori S.

2012-01-01

Understanding factors that determine heterogeneity in levels of parasitism across individuals is a major challenge in disease ecology. It is known that genetic makeup plays an important role in infection likelihood, but the mechanism remains unclear as does its relative importance when compared to other factors. We analyzed relationships between genetic diversity and macroparasites in outbred, free-ranging populations of raccoons (Procyon lotor). We measured heterozygosity at 14 microsatellite loci and modeled the effects of both multi-locus and single-locus heterozygosity on parasitism using an information theoretic approach and including non-genetic factors that are known to influence the likelihood of parasitism. The association of genetic diversity and parasitism, as well as the relative importance of genetic diversity, differed by parasitic group. Endoparasite species richness was better predicted by a model that included genetic diversity, with the more heterozygous hosts harboring fewer endoparasite species. Genetic diversity was also important in predicting abundance of replete ticks (Dermacentor variabilis). This association fit a curvilinear trend, with hosts that had either high or low levels of heterozygosity harboring fewer parasites than those with intermediate levels. In contrast, genetic diversity was not important in predicting abundance of non-replete ticks and lice (Trichodectes octomaculatus). No strong single-locus effects were observed for either endoparasites or replete ticks. Our results suggest that in outbred populations multi-locus diversity might be important for coping with parasitism. The differences in the relationships between heterozygosity and parasitism for the different parasites suggest that the role of genetic diversity varies with parasite-mediated selective pressures. PMID:23049796

Genetic analysis of longitudinal measurements of performance traits in selection lines for residual feed intake in Yorkshire swine.

PubMed

Cai, W; Kaiser, M S; Dekkers, J C M

2011-05-01

A 5-generation selection experiment in Yorkshire pigs for feed efficiency consists of a line selected for low residual feed intake (LRFI) and a random control line (CTRL). The objectives of this study were to use random regression models to estimate genetic parameters for daily feed intake (DFI), BW, backfat (BF), and loin muscle area (LMA) along the growth trajectory and to evaluate the effect of LRFI selection on genetic curves for DFI and BW. An additional objective was to compare random regression models using polynomials (RRP) and spline functions (RRS). Data from approximately 3 to 8 mo of age on 586 boars and 495 gilts across 5 generations were used. The average number of measurements was 85, 14, 5, and 5 for DFI, BW, BF, and LMA. The RRP models for these 4 traits were fitted with pen × on-test group as a fixed effect, second-order Legendre polynomials of age as fixed curves for each generation, and random curves for additive genetic and permanent environmental effects. Different residual variances were used for the first and second halves of the test period. The RRS models were fitted with the same fixed effects and residual variance structure as the RRP models and included genetic and permanent environmental random effects for both splines and linear Legendre polynomials of age. The RRP model was used for further analysis because the RRS model had erratic estimates of phenotypic variance and heritability, despite having a smaller Bayesian information criterion than the RRP model. From 91 to 210 d of age, estimates of heritability from the RRP model ranged from 0.10 to 0.37 for boars and 0.14 to 0.26 for gilts for DFI, from 0.39 to 0.58 for boars and 0.55 to 0.61 for gilts for BW, from 0.48 to 0.61 for boars and 0.61 to 0.79 for gilts for BF, and from 0.46 to 0.55 for boars and 0.63 to 0.81 for gilts for LMA. In generation 5, LRFI pigs had lower average genetic curves than CTRL pigs for DFI and BW, especially toward the end of the test period; estimated line differences (CTRL-LRFI) for DFI were 0.04 kg/d for boars and 0.12 kg/d for gilts at 105 d and 0.20 kg/d for boars and 0.24 kg/d for gilts at 195 d. Line differences for BW were 0.17 kg for boars and 0.69 kg for gilts at 105 d and 3.49 kg for boars and 8.96 kg for gilts at 195 d. In conclusion, selection for LRFI has resulted in a lower feed intake curve and a lower BW curve toward maturity.

Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach

USGS Publications Warehouse

Row, Jeff R; Oyler-McCance, Sara J.; Fike, Jennifer; O'Donnell, Michael; Doherty, Kevin E.; Aldridge, Cameron L.; Bowen, Zachary H.; Fedy, Brad C.

2015-01-01

Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.

Population-genetic models of sex-limited genomic imprinting.

PubMed

Kelly, S Thomas; Spencer, Hamish G

2017-06-01

Genomic imprinting is a form of epigenetic modification involving parent-of-origin-dependent gene expression, usually the inactivation of one gene copy in some tissues, at least, for some part of the diploid life cycle. Occurring at a number of loci in mammals and flowering plants, this mode of non-Mendelian expression can be viewed more generally as parentally-specific differential gene expression. The effects of natural selection on genetic variation at imprinted loci have previously been examined in a several population-genetic models. Here we expand the existing one-locus, two-allele population-genetic models of viability selection with genomic imprinting to include sex-limited imprinting, i.e., imprinted expression occurring only in one sex, and differential viability between the sexes. We first consider models of complete inactivation of either parental allele and these models are subsequently generalized to incorporate differential expression. Stable polymorphic equilibrium was possible without heterozygote advantage as observed in some prior models of imprinting in both sexes. In contrast to these latter models, in the sex-limited case it was critical whether the paternally inherited or maternally inherited allele was inactivated. The parental origin of inactivated alleles had a different impact on how the population responded to the different selection pressures between the sexes. Under the same fitness parameters, imprinting in the other sex altered the number of possible equilibrium states and their stability. When the parental origin of imprinted alleles and the sex in which they are inactive differ, an allele cannot be inactivated in consecutive generations. The system dynamics became more complex with more equilibrium points emerging. Our results show that selection can interact with epigenetic factors to maintain genetic variation in previously unanticipated ways. Copyright © 2017 Elsevier Inc. All rights reserved.

Theory of prokaryotic genome evolution.

PubMed

Sela, Itamar; Wolf, Yuri I; Koonin, Eugene V

2016-10-11

Bacteria and archaea typically possess small genomes that are tightly packed with protein-coding genes. The compactness of prokaryotic genomes is commonly perceived as evidence of adaptive genome streamlining caused by strong purifying selection in large microbial populations. In such populations, even the small cost incurred by nonfunctional DNA because of extra energy and time expenditure is thought to be sufficient for this extra genetic material to be eliminated by selection. However, contrary to the predictions of this model, there exists a consistent, positive correlation between the strength of selection at the protein sequence level, measured as the ratio of nonsynonymous to synonymous substitution rates, and microbial genome size. Here, by fitting the genome size distributions in multiple groups of prokaryotes to predictions of mathematical models of population evolution, we show that only models in which acquisition of additional genes is, on average, slightly beneficial yield a good fit to genomic data. These results suggest that the number of genes in prokaryotic genomes reflects the equilibrium between the benefit of additional genes that diminishes as the genome grows and deletion bias (i.e., the rate of deletion of genetic material being slightly greater than the rate of acquisition). Thus, new genes acquired by microbial genomes, on average, appear to be adaptive. The tight spacing of protein-coding genes likely results from a combination of the deletion bias and purifying selection that efficiently eliminates nonfunctional, noncoding sequences.

A precision medicine approach for psychiatric disease based on repeated symptom scores.

PubMed

Fojo, Anthony T; Musliner, Katherine L; Zandi, Peter P; Zeger, Scott L

2017-12-01

For psychiatric diseases, rich information exists in the serial measurement of mental health symptom scores. We present a precision medicine framework for using the trajectories of multiple symptoms to make personalized predictions about future symptoms and related psychiatric events. Our approach fits a Bayesian hierarchical model that estimates a population-average trajectory for all symptoms and individual deviations from the average trajectory, then fits a second model that uses individual symptom trajectories to estimate the risk of experiencing an event. The fitted models are used to make clinically relevant predictions for new individuals. We demonstrate this approach on data from a study of antipsychotic therapy for schizophrenia, predicting future scores for positive, negative, and general symptoms, and the risk of treatment failure in 522 schizophrenic patients with observations over 8 weeks. While precision medicine has focused largely on genetic and molecular data, the complementary approach we present illustrates that innovative analytic methods for existing data can extend its reach more broadly. The systematic use of repeated measurements of psychiatric symptoms offers the promise of precision medicine in the field of mental health. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment.

PubMed

Bourret, A; Garant, D

2017-03-01

Quantitative genetics approaches, and particularly animal models, are widely used to assess the genetic (co)variance of key fitness related traits and infer adaptive potential of wild populations. Despite the importance of precision and accuracy of genetic variance estimates and their potential sensitivity to various ecological and population specific factors, their reliability is rarely tested explicitly. Here, we used simulations and empirical data collected from an 11-year study on tree swallow (Tachycineta bicolor), a species showing a high rate of extra-pair paternity and a low recruitment rate, to assess the importance of identity errors, structure and size of the pedigree on quantitative genetic estimates in our dataset. Our simulations revealed an important lack of precision in heritability and genetic-correlation estimates for most traits, a low power to detect significant effects and important identifiability problems. We also observed a large bias in heritability estimates when using the social pedigree instead of the genetic one (deflated heritabilities) or when not accounting for an important cause of resemblance among individuals (for example, permanent environment or brood effect) in model parameterizations for some traits (inflated heritabilities). We discuss the causes underlying the low reliability observed here and why they are also likely to occur in other study systems. Altogether, our results re-emphasize the difficulties of generalizing quantitative genetic estimates reliably from one study system to another and the importance of reporting simulation analyses to evaluate these important issues.

Low extraversion and high neuroticism as indices of genetic and environmental risk for social phobia, agoraphobia, and animal phobia.

PubMed

Bienvenu, O Joseph; Hettema, John M; Neale, Michael C; Prescott, Carol A; Kendler, Kenneth S

2007-11-01

The authors examined the extent to which two major personality dimensions (extraversion and neuroticism) index the genetic and environmental risk for three phobias (social phobia, agoraphobia, and animal phobia) in twins ascertained from a large, population-based registry. Lifetime phobias and personality traits were assessed through diagnostic interview and self-report questionnaire, respectively, in 7,800 twins from female-female, male-male, and opposite-sex pairs. Sex-limited trivariate Cholesky structural equation models were used to decompose the correlations among extraversion, neuroticism, and each phobia. In the best-fitting models, genetic correlations were moderate and negative between extraversion and both social phobia and agoraphobia, and that between extraversion and animal phobia was effectively zero. Genetic correlations were high and positive between neuroticism and both social phobia and agoraphobia, and that between neuroticism and animal phobia was moderate. All of the genetic risk factors for social phobia and agoraphobia were shared with those that influence extraversion and neuroticism; in contrast, only a small proportion of the genetic risk factors for animal phobia (16%) was shared with those that influence personality. Shared environmental experiences were not a source of correlations between personality traits and phobias, and unique environmental correlations were relatively modest. Genetic factors that influence individual variation in extraversion and neuroticism appear to account entirely for the genetic liability to social phobia and agoraphobia, but not animal phobia. These findings underline the importance of both introversion (low extraversion) and neuroticism in some psychiatric disorders.

The evolution of sexes: A specific test of the disruptive selection theory.

PubMed

da Silva, Jack

2018-01-01

The disruptive selection theory of the evolution of anisogamy posits that the evolution of a larger body or greater organismal complexity selects for a larger zygote, which in turn selects for larger gametes. This may provide the opportunity for one mating type to produce more numerous, small gametes, forcing the other mating type to produce fewer, large gametes. Predictions common to this and related theories have been partially upheld. Here, a prediction specific to the disruptive selection theory is derived from a previously published game-theoretic model that represents the most complete description of the theory. The prediction, that the ratio of macrogamete to microgamete size should be above three for anisogamous species, is supported for the volvocine algae. A fully population genetic implementation of the model, involving mutation, genetic drift, and selection, is used to verify the game-theoretic approach and accurately simulates the evolution of gamete sizes in anisogamous species. This model was extended to include a locus for gamete motility and shows that oogamy should evolve whenever there is costly motility. The classic twofold cost of sex may be derived from the fitness functions of these models, showing that this cost is ultimately due to genetic conflict.

Applying ecological models to communities of genetic elements: the case of neutral theory.

PubMed

Linquist, Stefan; Cottenie, Karl; Elliott, Tyler A; Saylor, Brent; Kremer, Stefan C; Gregory, T Ryan

2015-07-01

A promising recent development in molecular biology involves viewing the genome as a mini-ecosystem, where genetic elements are compared to organisms and the surrounding cellular and genomic structures are regarded as the local environment. Here, we critically evaluate the prospects of ecological neutral theory (ENT), a popular model in ecology, as it applies at the genomic level. This assessment requires an overview of the controversy surrounding neutral models in community ecology. In particular, we discuss the limitations of using ENT both as an explanation of community dynamics and as a null hypothesis. We then analyse a case study in which ENT has been applied to genomic data. Our central finding is that genetic elements do not conform to the requirements of ENT once its assumptions and limitations are made explicit. We further compare this genome-level application of ENT to two other, more familiar approaches in genomics that rely on neutral mechanisms: Kimura's molecular neutral theory and Lynch's mutational-hazard model. Interestingly, this comparison reveals that there are two distinct concepts of neutrality associated with these models, which we dub 'fitness neutrality' and 'competitive neutrality'. This distinction helps to clarify the various roles for neutral models in genomics, for example in explaining the evolution of genome size. © 2015 John Wiley & Sons Ltd.

Validation of test-day models for genetic evaluation of dairy goats in Norway.

PubMed

Andonov, S; Ødegård, J; Boman, I A; Svendsen, M; Holme, I J; Adnøy, T; Vukovic, V; Klemetsdal, G

2007-10-01

Test-day data for daily milk yield and fat, protein, and lactose content were sampled from the years 1988 to 2003 in 17 flocks belonging to 2 genetically well-tied buck circles. In total, records from 2,111 to 2,215 goats for content traits and 2,371 goats for daily milk yield were included in the analysis, averaging 2.6 and 4.8 observations per goat for the 2 groups of traits, respectively. The data were analyzed by using 4 test-day models with different modeling of fixed effects. Model [0] (the reference model) contained a fixed effect of year-season of kidding with regression on Ali-Schaeffer polynomials nested within the year-season classes, and a random effect of flock test-day. In model [1], the lactation curve effect from model [0] was replaced by a fixed effect of days in milk (in 3-d periods), the same for all year-seasons of kidding. Models [2] and [3] were obtained from model [1] by removing the fixed year-season of kidding effect and considering the flock test-day effect as either fixed or random, respectively. The models were compared by using 2 criteria: mean-squared error of prediction and a test of bias affecting the genetic trend. The first criterion indicated a preference for model [3], whereas the second criterion preferred model [1]. Mean-squared error of prediction is based on model fit, whereas the second criterion tests the ability of the model to produce unbiased genetic evaluation (i.e., its capability of separating environmental and genetic time trends). Thus, a fixed structure with year (year, year-season, or possibly flock-year) was indicated to appropriately separate time trends. Heritability estimates for daily milk yield and milk content were 0.26 and 0.24 to 0.27, respectively.

A population based twin study of DSM-5 maladaptive personality domains.

PubMed

South, Susan C; Krueger, Robert F; Knudsen, Gun Peggy; Ystrom, Eivind; Czajkowski, Nikolai; Aggen, Steven H; Neale, Michael C; Gillespie, Nathan A; Kendler, Kenneth S; Reichborn-Kjennerud, Ted

2017-10-01

Personality disorders (PDs) can be partly captured by dimensional traits, a viewpoint reflected in the most recent Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) Alternative (Section III) Model for PD classification. The current study adds to the literature on the Alternative Model by examining the magnitude of genetic and environmental influences on 6 domains of maladaptive personality: negative emotionality, detachment, antagonism, disinhibition, compulsivity, and psychoticism. In a large, population-based sample (N = 2,293) of Norwegian male and female twin pairs, we investigated (a) if the domains demonstrated measurement invariance across gender at the phenotypic level, meaning that the relationships between the items and the latent factor were equivalent in men and women; and (b) if genetic and environmental influences on variation in these domains were equivalent across gender. Multiple group confirmatory factor modeling provided evidence that all 6 domain scale measurement models were gender-invariant. The best fitting biometric model for 4 of the 6 domains (negative emotionality, detachment, disinhibition, and compulsivity) was one in which genetic and environmental influences could be set invariant across gender. Evidence for sex differences in psychoticism was mixed, but the only clear evidence for quantitative sex differences was for the antagonism scale, with greater genetic influences found for men than women. Genetic influences across domains were moderate overall (19-37%), in line with previous research using symptom-based measures of PDs. This study adds to the very limited knowledge currently existing on the etiology of maladaptive personality traits. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The PX-EM algorithm for fast stable fitting of Henderson's mixed model

PubMed Central

Foulley, Jean-Louis; Van Dyk, David A

2000-01-01

This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence) are obtained for PX-EM relative to the basic EM algorithm in the random regression. PMID:14736399

Evolutionary Determinants of Genetic Variation in Susceptibility to Infectious Diseases in Humans

PubMed Central

Baker, Christi; Antonovics, Janis

2012-01-01

Although genetic variation among humans in their susceptibility to infectious diseases has long been appreciated, little focus has been devoted to identifying patterns in levels of variation in susceptibility to different diseases. Levels of genetic variation in susceptibility associated with 40 human infectious diseases were assessed by a survey of studies on both pedigree-based quantitative variation, as well as studies on different classes of marker alleles. These estimates were correlated with pathogen traits, epidemiological characteristics, and effectiveness of the human immune response. The strongest predictors of levels of genetic variation in susceptibility were disease characteristics negatively associated with immune effectiveness. High levels of genetic variation were associated with diseases with long infectious periods and for which vaccine development attempts have been unsuccessful. These findings are consistent with predictions based on theoretical models incorporating fitness costs associated with the different types of resistance mechanisms. An appreciation of these observed patterns will be a valuable tool in directing future research given that genetic variation in disease susceptibility has large implications for vaccine development and epidemiology. PMID:22242158

Environmental Sensing of Expert Knowledge in a Computational Evolution System for Complex Problem Solving in Human Genetics

NASA Astrophysics Data System (ADS)

Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.

The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.

Longitudinal trends in climate drive flowering time clines in North American Arabidopsis thaliana.

PubMed

Samis, Karen E; Murren, Courtney J; Bossdorf, Oliver; Donohue, Kathleen; Fenster, Charles B; Malmberg, Russell L; Purugganan, Michael D; Stinchcombe, John R

2012-06-01

Introduced species frequently show geographic differentiation, and when differentiation mirrors the ancestral range, it is often taken as evidence of adaptive evolution. The mouse-ear cress (Arabidopsis thaliana) was introduced to North America from Eurasia 150-200 years ago, providing an opportunity to study parallel adaptation in a genetic model organism. Here, we test for clinal variation in flowering time using 199 North American (NA) accessions of A. thaliana, and evaluate the contributions of major flowering time genes FRI, FLC, and PHYC as well as potential ecological mechanisms underlying differentiation. We find evidence for substantial within population genetic variation in quantitative traits and flowering time, and putatively adaptive longitudinal differentiation, despite low levels of variation at FRI, FLC, and PHYC and genome-wide reductions in population structure relative to Eurasian (EA) samples. The observed longitudinal cline in flowering time in North America is parallel to an EA cline, robust to the effects of population structure, and associated with geographic variation in winter precipitation and temperature. We detected major effects of FRI on quantitative traits associated with reproductive fitness, although the haplotype associated with higher fitness remains rare in North America. Collectively, our results suggest the evolution of parallel flowering time clines through novel genetic mechanisms.

Reproductive fitness and dietary choice behavior of the genetic model organism Caenorhabditis elegans under semi-natural conditions.

PubMed

Freyth, Katharina; Janowitz, Tim; Nunes, Frank; Voss, Melanie; Heinick, Alexander; Bertaux, Joanne; Scheu, Stefan; Paul, Rüdiger J

2010-10-01

Laboratory breeding conditions of the model organism C. elegans do not correspond with the conditions in its natural soil habitat. To assess the consequences of the differences in environmental conditions, the effects of air composition, medium and bacterial food on reproductive fitness and/or dietary-choice behavior of C. elegans were investigated. The reproductive fitness of C. elegans was maximal under oxygen deficiency and not influenced by a high fractional share of carbon dioxide. In media approximating natural soil structure, reproductive fitness was much lower than in standard laboratory media. In seminatural media, the reproductive fitness of C. elegans was low with the standard laboratory food bacterium E. coli (γ-Proteobacteria), but significantly higher with C. arvensicola (Bacteroidetes) and B. tropica (β-Proteobacteria) as food. Dietary-choice experiments in semi-natural media revealed a low preference of C. elegans for E. coli but significantly higher preferences for C. arvensicola and B. tropica (among other bacteria). Dietary-choice experiments under quasi-natural conditions, which were feasible by fluorescence in situ hybridization (FISH) of bacteria, showed a high preference of C. elegans for Cytophaga-Flexibacter-Bacteroides, Firmicutes, and β-Proteobacteria, but a low preference for γ-Proteobacteria. The results show that data on C. elegans under standard laboratory conditions have to be carefully interpreted with respect to their biological significance.

Heterosis, the catapult effect and establishment success of a colonizing bird

PubMed Central

Drake, John M

2006-01-01

The genetic basis of population colonization is poorly understood, particularly in animals. Here, I introduce the idea of a ‘catapult effect’ to explain how the effects of transient increases in fitness can be retained in population demography diminishing the chance of extinction. I tested this idea using information on historical introductions of hybrid and non-hybrid pheasants in the United States. I found that hybrid pheasants were 2.2 times more likely to establish than non-hybrid strains. Analysis of fitness components failed to support the alternative that the increased odds of establishment resulted from increased genetic variation conferring permanent fitness benefits through directional selection or by purging deleterious alleles. These results show that even ephemeral increases in fitness can affect the persistence of small populations. PMID:17148389

Individual Differences in Exercise Behavior: Stability and Change in Genetic and Environmental Determinants From Age 7 to 18.

PubMed

Huppertz, Charlotte; Bartels, Meike; de Zeeuw, Eveline L; van Beijsterveldt, Catharina E M; Hudziak, James J; Willemsen, Gonneke; Boomsma, Dorret I; de Geus, Eco J C

2016-09-01

Exercise behavior during leisure time is a major source of health-promoting physical activity and moderately tracks across childhood and adolescence. This study aims to investigate the absolute and relative contribution of genes and the environment to variance in exercise behavior from age 7 to 18, and to elucidate the stability and change of genetic and shared environmental factors that underlie this behavior. The Netherlands Twin Register collected data on exercise behavior in twins aged approximately 7, 10, 12, 14, 16 and 18 years (N = 27,332 twins; 48 % males; 47 % with longitudinal assessments). Three exercise categories (low, middle, high) were analyzed by means of liability threshold models. First, a univariate model was fitted using the largest available cross-sectional dataset with linear and quadratic effects of age as modifiers on the means and variance components. Second, a simplex model was fitted on the longitudinal dataset. Heritability was low in 7-year-olds (14 % in males and 12 % in females), but gradually increased up to age 18 (79 % in males and 49 % in females), whereas the initially substantial relative influence of the shared environment decreased with age (from 80 to 4 % in males and from 80 to 19 % in females). This decrease was due to a large increase in the genetic variance. The longitudinal model showed the genetic effects in males to be largely stable and to accumulate from childhood to late adolescence, whereas in females, they were marked by both transmission and innovation at all ages. The shared environmental effects tended to be less stable in both males and females. In sum, the clear age-moderation of exercise behavior implies that family-based interventions might be useful to increase this behavior in children, whereas individual-based interventions might be better suited for adolescents. We showed that some determinants of individual differences in exercise behavior are stable across childhood and youth, whereas others come into play at specific ages. In view of the many benefits of regular exercise, identifying these determinants at specific ages should be a public health priority.

Limited hatchery introgression into wild brook trout (Salvelinus fontinalis) populations despite reoccurring stocking

USGS Publications Warehouse

White, Shannon L.; Miller, William L.; Dowell, Stephanie A.; Bartron, Meredith L.; Wagner, Tyler

2018-01-01

Due to increased anthropogenic pressures on many fish populations, supplementing wild populations with captive‐raised individuals has become an increasingly common management practice. Stocking programs can be controversial due to uncertainty about the long‐term fitness effects of genetic introgression on wild populations. In particular, introgression between hatchery and wild individuals can cause declines in wild population fitness, resiliency, and adaptive potential, and contribute to local population extirpation. However, low survival and fitness of captive‐raised individuals can minimize the long‐term genetic consequences of stocking in wild populations, and to date the prevalence of introgression in actively stocked ecosystems has not been rigorously evaluated. We quantified the extent of introgression in 30 populations of wild brook trout (Salvelinus fontinalis) in a Pennsylvania watershed, and examined the correlation between introgression and 11 environmental covariates. Genetic assignment tests were used to determine the origin (wild vs. captive‐raised) for 1742 wild‐caught and 300 hatchery brook trout. To avoid assignment biases, individuals were assigned to two simulated populations that represented the average allele frequencies in wild and hatchery groups. Fish with intermediate probabilities of wild ancestry were classified as introgressed, with threshold values determined through simulation. Even with reoccurring stocking at most sites, over 93% of wild‐caught individuals probabilistically assigned to wild origin, and only 5.6% of wild‐caught fish assigned to introgressed. Models examining environmental drivers of introgression explained less than 3% of the among‐population variability, and all estimated effects were highly uncertain. This was not surprising given overall low introgression observed in this study. Our results suggest that introgression of hatchery‐derived genotypes can occur at low rates, even in actively stocked ecosystems and across a range of habitats. However, a cautious approach to stocking may still be warranted, as the potential effects of stocking on wild population fitness and the mechanisms limiting introgression are not known.

Analysis of mutational resistance to trimethoprim in Staphylococcus aureus by genetic and structural modelling techniques.

PubMed

Vickers, Anna A; Potter, Nicola J; Fishwick, Colin W G; Chopra, Ian; O'Neill, Alex J

2009-06-01

This study sought to expand knowledge on the molecular mechanisms of mutational resistance to trimethoprim in Staphylococcus aureus, and the fitness costs associated with resistance. Spontaneous trimethoprim-resistant mutants of S. aureus SH1000 were recovered in vitro, resistance genotypes characterized by DNA sequencing of the gene encoding the drug target (dfrA) and the fitness of mutants determined by pair-wise growth competition assays with SH1000. Novel resistance genotypes were confirmed by ectopic expression of dfrA alleles in a trimethoprim-sensitive S. aureus strain. Molecular models of S. aureus dihydrofolate reductase (DHFR) were constructed to explore the structural basis of trimethoprim resistance, and to rationalize the observed in vitro fitness of trimethoprim-resistant mutants. In addition to known amino acid substitutions in DHFR mediating trimethoprim resistance (F(99)Y and H(150)R), two novel resistance polymorphisms (L(41)F and F(99)S) were identified among the trimethoprim-resistant mutants selected in vitro. Molecular modelling of mutated DHFR enzymes provided insight into the structural basis of trimethoprim resistance. Calculated binding energies of the substrate (dihydrofolate) for the mutant and wild-type enzymes were similar, consistent with apparent lack of fitness costs for the resistance mutations in vitro. Reduced susceptibility to trimethoprim of DHFR enzymes carrying substitutions L(41)F, F(99)S, F(99)Y and H(150)R appears to result from structural changes that reduce trimethoprim binding to the enzyme. However, the mutations conferring trimethoprim resistance are not associated with fitness costs in vitro, suggesting that the survival of trimethoprim-resistant strains emerging in the clinic may not be subject to a fitness disadvantage.

Genetic constraints on adaptation: a theoretical primer for the genomics era.

PubMed

Connallon, Tim; Hall, Matthew D

2018-06-01

Genetic constraints are features of inheritance systems that slow or prohibit adaptation. Several population genetic mechanisms of constraint have received sustained attention within the field since they were first articulated in the early 20th century. This attention is now reflected in a rich, and still growing, theoretical literature on the genetic limits to adaptive change. In turn, empirical research on constraints has seen a rapid expansion over the last two decades in response to changing interests of evolutionary biologists, along with new technologies, expanding data sets, and creative analytical approaches that blend mathematical modeling with genomics. Indeed, one of the most notable and exciting features of recent progress in genetic constraints is the close connection between theoretical and empirical research. In this review, we discuss five major population genetic contexts of genetic constraint: genetic dominance, pleiotropy, fitness trade-offs between types of individuals of a population, sign epistasis, and genetic linkage between loci. For each, we outline historical antecedents of the theory, specific contexts where constraints manifest, and their quantitative consequences for adaptation. From each of these theoretical foundations, we discuss recent empirical approaches for identifying and characterizing genetic constraints, each grounded and motivated by this theory, and outline promising areas for future work. © 2018 New York Academy of Sciences.

Fold or hold: experimental evolution in vitro

PubMed Central

Collins, S; Rambaut, A; Bridgett, S J

2013-01-01

We introduce a system for experimental evolution consisting of populations of short oligonucleotides (Oli populations) evolving in a modified quantitative polymerase chain reaction (qPCR). It is tractable at the genetic, genomic, phenotypic and fitness levels. The Oli system uses DNA hairpins designed to form structures that self-prime under defined conditions. Selection acts on the phenotype of self-priming, after which differences in fitness are amplified and quantified using qPCR. We outline the methodological and bioinformatics tools for the Oli system here and demonstrate that it can be used as a conventional experimental evolution model system by test-driving it in an experiment investigating adaptive evolution under different rates of environmental change. PMID:24003997

A COUPLED 2 × 2D BABCOCK–LEIGHTON SOLAR DYNAMO MODEL. I. SURFACE MAGNETIC FLUX EVOLUTION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lemerle, Alexandre; Charbonneau, Paul; Carignan-Dugas, Arnaud, E-mail: lemerle@astro.umontreal.ca, E-mail: paulchar@astro.umontreal.ca

The need for reliable predictions of the solar activity cycle motivates the development of dynamo models incorporating a representation of surface processes sufficiently detailed to allow assimilation of magnetographic data. In this series of papers we present one such dynamo model, and document its behavior and properties. This first paper focuses on one of the model’s key components, namely surface magnetic flux evolution. Using a genetic algorithm, we obtain best-fit parameters of the transport model by least-squares minimization of the differences between the associated synthetic synoptic magnetogram and real magnetographic data for activity cycle 21. Our fitting procedure also returnsmore » Monte Carlo-like error estimates. We show that the range of acceptable surface meridional flow profiles is in good agreement with Doppler measurements, even though the latter are not used in the fitting process. Using a synthetic database of bipolar magnetic region (BMR) emergences reproducing the statistical properties of observed emergences, we also ascertain the sensitivity of global cycle properties, such as the strength of the dipole moment and timing of polarity reversal, to distinct realizations of BMR emergence, and on this basis argue that this stochasticity represents a primary source of uncertainty for predicting solar cycle characteristics.« less

IBSEM: An Individual-Based Atlantic Salmon Population Model

PubMed Central

Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A.

2015-01-01

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a ‘wild’ genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors. PMID:26383256

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

PubMed

Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

2017-01-01

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

PubMed

Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner

2015-07-01

Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.

Combining population genomics and fitness QTLs to identify the genetics of local adaptation in Arabidopsis thaliana.

PubMed

Price, Nicholas; Moyers, Brook T; Lopez, Lua; Lasky, Jesse R; Monroe, J Grey; Mullen, Jack L; Oakley, Christopher G; Lin, Junjiang; Ågren, Jon; Schrider, Daniel R; Kern, Andrew D; McKay, John K

2018-05-08

Evidence for adaptation to different climates in the model species Arabidopsis thaliana is seen in reciprocal transplant experiments, but the genetic basis of this adaptation remains poorly understood. Field-based quantitative trait locus (QTL) studies provide direct but low-resolution evidence for the genetic basis of local adaptation. Using high-resolution population genomic approaches, we examine local adaptation along previously identified genetic trade-off (GT) and conditionally neutral (CN) QTLs for fitness between locally adapted Italian and Swedish A. thaliana populations [Ågren J, et al. (2013) Proc Natl Acad Sci USA 110:21077-21082]. We find that genomic regions enriched in high F ST SNPs colocalize with GT QTL peaks. Many of these high F ST regions also colocalize with regions enriched for SNPs significantly correlated to climate in Eurasia and evidence of recent selective sweeps in Sweden. Examining unfolded site frequency spectra across genes containing high F ST SNPs suggests GTs may be due to more recent adaptation in Sweden than Italy. Finally, we collapse a list of thousands of genes spanning GT QTLs to 42 genes that likely underlie the observed GTs and explore potential biological processes driving these trade-offs, from protein phosphorylation, to seed dormancy and longevity. Our analyses link population genomic analyses and field-based QTL studies of local adaptation, and emphasize that GTs play an important role in the process of local adaptation. Copyright © 2018 the Author(s). Published by PNAS.

Combining genetic and evolutionary engineering to establish C4 metabolism in C3 plants.

PubMed

Li, Yuanyuan; Heckmann, David; Lercher, Martin J; Maurino, Veronica G

2017-01-01

To feed a world population projected to reach 9 billion people by 2050, the productivity of major crops must be increased by at least 50%. One potential route to boost the productivity of cereals is to equip them genetically with the 'supercharged' C 4 type of photosynthesis; however, the necessary genetic modifications are not sufficiently understood for the corresponding genetic engineering programme. In this opinion paper, we discuss a strategy to solve this problem by developing a new paradigm for plant breeding. We propose combining the bioengineering of well-understood traits with subsequent evolutionary engineering, i.e. mutagenesis and artificial selection. An existing mathematical model of C 3 -C 4 evolution is used to choose the most promising path towards this goal. Based on biomathematical simulations, we engineer Arabidopsis thaliana plants that express the central carbon-fixing enzyme Rubisco only in bundle sheath cells (Ru-BSC plants), the localization characteristic for C 4 plants. This modification will initially be deleterious, forcing the Ru-BSC plants into a fitness valley from where previously inaccessible adaptive steps towards C 4 photosynthesis become accessible through fitness-enhancing mutations. Mutagenized Ru-BSC plants are then screened for improved photosynthesis, and are expected to respond to imposed artificial selection pressures by evolving towards C 4 anatomy and biochemistry. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Monogamy and high relatedness do not preferentially favor the evolution of cooperation.

PubMed

Nonacs, Peter

2011-03-04

Phylogenetic analyses strongly associate nonsocial ancestors of cooperatively-breeding or eusocial species with monogamy. Because monogamy creates high-relatedness family groups, kin selection has been concluded to drive the evolution of cooperative breeding (i.e., the monogamy hypothesis). Although kin selection is criticized as inappropriate for modeling and predicting the evolution of cooperation, there are no examples where specific inclusive fitness-based predictions are intrinsically wrong. The monogamy hypothesis may be the first case of such a flawed calculation. A simulation model mutated helping alleles into non-cooperative populations where females mated either once or multiply. Although multiple mating produces sibling broods of lower relatedness, it also increases the likelihood that one offspring will adopt a helper role. Examining this tradeoff showed that under a wide range of conditions polygamy, rather than monogamy, allowed helping to spread more rapidly through populations. Further simulations with mating strategies as heritable traits confirmed that multiple-mating is selectively advantageous. Although cooperation evolves similarly regardless of whether dependent young are close or more distant kin, it does not evolve if they are unrelated. The solitary ancestral species to cooperative breeders may have been predominantly monogamous, but it cannot be concluded that monogamy is a predisposing state for the evolution of helping behavior. Monogamy may simply be coincidental to other more important life history characteristics such as nest defense or sequential provisioning of offspring. The differing predictive outcome from a gene-based model also supports arguments that inclusive fitness formulations poorly model some evolutionary questions. Nevertheless, cooperation only evolves when benefits are provided for kin: helping alleles did not increase in frequency in the absence of potential gains in indirect fitness. The key question, therefore, is not whether kin selection occurs, but how best to elucidate the differing evolutionary advantages of genetic relatedness versus genetic diversity.

Monogamy and high relatedness do not preferentially favor the evolution of cooperation

PubMed Central

2011-01-01

Background Phylogenetic analyses strongly associate nonsocial ancestors of cooperatively-breeding or eusocial species with monogamy. Because monogamy creates high-relatedness family groups, kin selection has been concluded to drive the evolution of cooperative breeding (i.e., the monogamy hypothesis). Although kin selection is criticized as inappropriate for modeling and predicting the evolution of cooperation, there are no examples where specific inclusive fitness-based predictions are intrinsically wrong. The monogamy hypothesis may be the first case of such a flawed calculation. Results A simulation model mutated helping alleles into non-cooperative populations where females mated either once or multiply. Although multiple mating produces sibling broods of lower relatedness, it also increases the likelihood that one offspring will adopt a helper role. Examining this tradeoff showed that under a wide range of conditions polygamy, rather than monogamy, allowed helping to spread more rapidly through populations. Further simulations with mating strategies as heritable traits confirmed that multiple-mating is selectively advantageous. Although cooperation evolves similarly regardless of whether dependent young are close or more distant kin, it does not evolve if they are unrelated. Conclusions The solitary ancestral species to cooperative breeders may have been predominantly monogamous, but it cannot be concluded that monogamy is a predisposing state for the evolution of helping behavior. Monogamy may simply be coincidental to other more important life history characteristics such as nest defense or sequential provisioning of offspring. The differing predictive outcome from a gene-based model also supports arguments that inclusive fitness formulations poorly model some evolutionary questions. Nevertheless, cooperation only evolves when benefits are provided for kin: helping alleles did not increase in frequency in the absence of potential gains in indirect fitness. The key question, therefore, is not whether kin selection occurs, but how best to elucidate the differing evolutionary advantages of genetic relatedness versus genetic diversity. PMID:21375755

Attention-deficit/hyperactivity disorder dimensionality: the reliable 'g' and the elusive 's' dimensions.

PubMed

Wagner, Flávia; Martel, Michelle M; Cogo-Moreira, Hugo; Maia, Carlos Renato Moreira; Pan, Pedro Mario; Rohde, Luis Augusto; Salum, Giovanni Abrahão

2016-01-01

The best structural model for attention-deficit/hyperactivity disorder (ADHD) symptoms remains a matter of debate. The objective of this study is to test the fit and factor reliability of competing models of the dimensional structure of ADHD symptoms in a sample of randomly selected and high-risk children and pre-adolescents from Brazil. Our sample comprised 2512 children aged 6-12 years from 57 schools in Brazil. The ADHD symptoms were assessed using parent report on the development and well-being assessment (DAWBA). Fit indexes from confirmatory factor analysis were used to test unidimensional, correlated, and bifactor models of ADHD, the latter including "g" ADHD and "s" symptom domain factors. Reliability of all models was measured with omega coefficients. A bifactor model with one general factor and three specific factors (inattention, hyperactivity, impulsivity) exhibited the best fit to the data, according to fit indices, as well as the most consistent factor loadings. However, based on omega reliability statistics, the specific inattention, hyperactivity, and impulsivity dimensions provided very little reliable information after accounting for the reliable general ADHD factor. Our study presents some psychometric evidence that ADHD specific ("s") factors might be unreliable after taking common ("g" factor) variance into account. These results are in accordance with the lack of longitudinal stability among subtypes, the absence of dimension-specific molecular genetic findings and non-specific effects of treatment strategies. Therefore, researchers and clinicians might most effectively rely on the "g" ADHD to characterize ADHD dimensional phenotype, based on currently available symptom items.

On 4-degree-of-freedom biodynamic models of seated occupants: Lumped-parameter modeling

NASA Astrophysics Data System (ADS)

Bai, Xian-Xu; Xu, Shi-Xu; Cheng, Wei; Qian, Li-Jun

2017-08-01

It is useful to develop an effective biodynamic model of seated human occupants to help understand the human vibration exposure to transportation vehicle vibrations and to help design and improve the anti-vibration devices and/or test dummies. This study proposed and demonstrated a methodology for systematically identifying the best configuration or structure of a 4-degree-of-freedom (4DOF) human vibration model and for its parameter identification. First, an equivalent simplification expression for the models was made. Second, all of the possible 23 structural configurations of the models were identified. Third, each of them was calibrated using the frequency response functions recommended in a biodynamic standard. An improved version of non-dominated sorting genetic algorithm (NSGA-II) based on Pareto optimization principle was used to determine the model parameters. Finally, a model evaluation criterion proposed in this study was used to assess the models and to identify the best one, which was based on both the goodness of curve fits and comprehensive goodness of the fits. The identified top configurations were better than those reported in the literature. This methodology may also be extended and used to develop the models with other DOFs.

An experimental test of alternative population augmentation scenarios.

PubMed

Kronenberger, John A; Gerberich, Jill C; Fitzpatrick, Sarah W; Broder, E Dale; Angeloni, Lisa M; Funk, W Chris

2018-01-19

Human land use is fragmenting habitats worldwide and inhibiting dispersal among previously connected populations of organisms, often leading to inbreeding depression and reduced evolutionary potential in the face of rapid environmental change. To combat this augmentation of isolated populations with immigrants is sometimes used to facilitate demographic and genetic rescue. Augmentation with immigrants that are genetically and adaptively similar to the target population effectively increases population fitness, but if immigrants are very genetically or adaptively divergent, augmentation can lead to outbreeding depression. Despite well-cited guidelines for the best practice selection of immigrant sources, often only highly divergent populations remain, and experimental tests of these riskier augmentation scenarios are essentially nonexistent. We conducted a mesocosm experiment with Trinidadian guppies (Poecilia reticulata) to test the multigenerational demographic and genetic effects of augmenting 2 target populations with 3 types of divergent immigrants. We found no evidence of demographic rescue, but we did observe genetic rescue in one population. Divergent immigrant treatments tended to maintain greater genetic diversity, abundance, and hybrid fitness than controls that received immigrants from the source used to seed the mesocosms. In the second population, divergent immigrants had a slightly negative effect in one treatment, and the benefits of augmentation were less apparent overall, likely because this population started with higher genetic diversity and a lower reproductive rate that limited genetic admixture. Our results add to a growing consensus that gene flow can increase population fitness even when immigrants are more highly divergent and may help reduce uncertainty about the use of augmentation in conservation. © 2018 Society for Conservation Biology.