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Results for “Models, Genetic”

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PubMed2004

Serial SimCoal: a population genetics model for data from multiple populations and points in time.

UNLABELLED: We present Serial SimCoal, a program that models population genetic data from multiple time points, as with ancient DNA data. An extension of SIMCOAL, it also allows simultaneous modeling of complex demographic histories, and migration between multiple populations. Further, we incorporate a statistical package to calculate relevant summary statistics, which, for the first time allows users to investigate the statistical power provided by, conduct hypothesis-testing with, and explore sample size limitations of ancient DNA data. AVAILABILITY: Source code and Windows/Mac executables at http://www.stanford.edu/group/hadlylab/ssc.html CONTACT: senka@stanford.edu.

Biological Evolution↗

PubMed1994

Murine genetic models of human disease.

Until recently, good animal models of human disease have been available only in limited numbers, largely because of technical difficulties associated with transgenesis. As a consequence of recent rapid advances principally, but not exclusively, focused around the use of embryonic stem cells, it is now theoretically possible to model the genetic lesion underlying any human disease in the mouse. This has led not only to a better understanding of complex disease processes, such as those associated with malignancy, but, as in the cases of cystic fibrosis and duchenne muscular dystrophy, is now allowing the development of novel therapy regimes.

Animals↗

PubMed1992

In vivo insulin action in genetic models of hypertension.

Insulin resistance has been described in nonobese subjects with essential hypertension. At present it is unknown whether hypertension per se may lead to the onset of insulin resistance. To examine this question we studied in vivo insulin action in two rat models of genetic hypertension. Four groups of conscious rats were studied: Milan hypertensive (MHS), Milan normotensive (MNS), spontaneously hypertensive (SHR), and Wistar-Kyoto (WKY). Mean arterial pressure was increased in SHR vs. WKY in both the fed (184 +/- 5 vs. 126 +/- 6 mmHg; P less than 0.001) and fasting (160 +/- 5 vs. 129 +/- 5; P less than 0.001) states. During high-dose insulin clamps, total body glucose uptake (mg.kg-1.min-1) was similar in MNS (28.7 +/- 1.4) vs. MHS (33.6 +/- 3.0) and in WKY (34.6 +/- 1.8) vs. SHR (35.7 +/- 2.4). During low-dose insulin clamps, suppression of hepatic glucose production (3.5 +/- 0.6 vs. 3.0 +/- 0.5 mg.kg-1.min-1) and stimulation of glycolysis (12.9 +/- 0.8 vs. 14.4 +/- 1.5 mg.kg-1.min-1) were similar in WKY vs. SHR, whereas glucose uptake (24.6 +/- 1.9 vs. 18.3 +/- 1.2 mg.kg-1.min-1; P less than 0.01) and muscle glycogenic rate (10.2 +/- 1.1 vs. 6.5 +/- 1.1 mg.kg-1.min-1; P less than 0.05) were increased in SHR vs. WKY. In conclusion, 1) feeding markedly augments blood pressure in hypertensive but not in normotensive rats, and 2) hepatic and muscle insulin sensitivity are normal or increased in two different rat models of genetic hypertension. These results provide evidence that high blood pressure per se does not invariably lead to the development of insulin resistance.

Animals↗

PubMed2006

Fitting genetic models using Markov Chain Monte Carlo algorithms with BUGS.

Maximum likelihood estimation techniques are widely used in twin and family studies, but soon reach computational boundaries when applied to highly complex models (e.g., models including gene-by-environment interaction and gene-environment correlation, item response theory measurement models, repeated measures, longitudinal structures, extended pedigrees). Markov Chain Monte Carlo (MCMC) algorithms are very well suited to fit complex models with hierarchically structured data. This article introduces the key concepts of Bayesian inference and MCMC parameter estimation and provides a number of scripts describing relatively simple models to be estimated by the freely obtainable BUGS software. In addition, inference using BUGS is illustrated using a data set on follicle-stimulating hormone and luteinizing hormone levels with repeated measures. The examples provided can serve as stepping stones for more complicated models, tailored to the specific needs of the individual researcher.

Algorithms↗

PubMed1983

Sex-linked and maternal effects in the Eberhart-Gardner general genetics model.

To deal with differences between reciprocal crosses found in many animal breeding experiments, an extension of the general model for genetic effects, given by Eberhart and Gardner (1966, Biometrics 22, 864-881), is presented. In this extension, reciprocal differences between crosses are defined in terms of several maternal and sex-linked parameters, the latter being expressed as functions of gene values and their frequencies. Models are given for several kinds of crosses. Experimental setups or designs of increasing complexity are presented for the estimation of some of the parameters in the models, particularly the sex-linked and maternal ones, as well as the interpopulation heterotic additive-by-additive epistasis. For prediction purposes, different analyses are suggested for the model with highly correlated variables. If the genetic architecture of a trait in different populations is to be compared, the analysis of variance will provide enough degrees of freedom to allow the investigation of the importance of each kind of genetic effect. An example which uses all possible two-way crosses and a partial set of three-way crosses applied to two quantitative traits in the flour beetle, Tribolium castaneum, is included merely as a guide for computations. Population means given by Eberhart and Gardner are extended to incorporate the inbreeding coefficient.

Animals↗

PubMed2001

Animal genetic models for complex traits of physical capacity.

Animal genetic models for complex traits of physical capacity. Exerc. Sport Sci. Rev., Vol. 29, No. 1, pp 7-14, 2001. Understanding the genetic basis for variance in complex physical traits such as aerobic capacity has become an attainable goal. A starting point is the development or identification of animal genetic models that contrast the low and high values for the trait of interest. Genes that cause natural trait variation can ultimately be determined from animal models via genetic linkage.

Animals↗

PubMed1987

Quantitative genetic models of sexual selection: a review.

Quantitative genetic models of sexual selection have disproven some of the central tenets of both the handicap mechanism and the 'sexy son' hypothesis. These results suggest that the 'good genes' approach to sexual selection may often lead to erroneous results. Runaway sexual selection seems possible under a wide variety of circumstances. Quantitative genetic models have revealed runaway processes for sexually selected attributes expressed in both sexes and for attributes of parental care. Furthermore, the runaway could occur simultaneously in a series of populations that straddle an environmental gradient. While the models support the feasibility of runaway processes, empirical studies are needed to evaluate whether runaways actually happen. Estimates of critical genetic parameters are particularly needed, as well as measures of natural and sexual selection acting on the same population. The models also show that sexual selection has tremendous potential to produce population differentiation, particularly in epigamic traits. Differentiation is promoted by indeterminancy of evolutionary outcome, transient differences among populations during the final slow approach to equilibrium, sampling drift among equilibrium populations, and the tendency of sexual selection to amplify geographic variation arising from spatial differences in natural selection. Recent work with two- and three-locus models of sexual selection has produced results that parallel the results of the polygenic models (Kirkpatrick, 1982, 1985, 1986; Seger, 1985). Thus the feature of indeterminate equilibria (outcome dependent on initial conditions) is common to both types of model.

Animals↗

PubMed1980

A genetic model for the inheritance of the P, P1 and Pk antigens.

A new genetic model of the P blood group system is presented. The system is controlled by two chromosomal loci. The first locus has three allelic genes. The pk gene codes for an alpha galactosyl transferase that converts ceramide dihexoside to ceramide trihexoside (or the pk antigen). The second allele, the pk gene, codes for an alpha galactosyl transferase that converts both ceramide dihexoside to ceramide trihexoside (or the pk antigen) and paragloboside to the P1 antigen. The third allele does not produce an active codes for a beta N-acetyl galactosaminyl transferase that converts ceramide trihexoside to globoside (or the P antigen). The second allele does not produce an active product. The predictions of the model are in agreement with family studies and fibroblast fusion studies. The current model and previous genetic models, however, predict different possible phenotypes from rare 2 x p or p2k x p matings or fibroblast fusions.

Alleles↗

PubMed1994

A developmental-genetic model of alcoholism: implications for genetic research.

The research for biological-genetic markers of alcoholism is discussed in the context of a multifactorial, heterogeneous, developmental model of the disease. It is suggested that the strategies used in both linkage and association studies require modification to accommodate this more complex model. It is also suggested that several extant associations of genetic markers with alcoholism represent true secondary interactive phenomena that alter the outcome of primary alcoholism genotypes at the phenotype level.

Alcoholism↗

PubMed1991

Evaluation of likelihood ratios for complex genetic models.

Although methods for computing likelihoods for simple genetic models on large and complex pedigrees have been known for some time, and although methods for evaluating likelihoods for complex genetic models on small pedigrees have likewise been well known, likelihood evaluation for complex models given data on extended pedigrees has remained an intractable problem. The Gibbs sampler provides a method of Monte Carlo evaluation of likelihood ratios for complex models on extended and/or complex pedigrees. With increasing computer speeds, this approach provides a tractable and efficient approach to many such likelihood evaluation problems in linkage and segregation analysis. In this paper, however, the authors restrict attention to two basic building-blocks of the overall process. The first is the sequential computation of Gaussian likelihoods for multiple random-effects models on extended pedigrees. The second is the use of this in the Monte Carlo evaluation of likelihoods for the classical mixed model of segregation analysis. The implementation of the Gibbs sampler on pedigrees that permits this Monte Carlo evaluation is detailed. An example is then presented, and finally, in the context of this same example, it is also shown how linkage analysis for a quantitative trait falls within this same framework.

Female↗

PubMed2004

An empirical comparison of information-theoretic selection criteria for multivariate behavior genetic models.

Information theory provides an attractive basis for statistical inference and model selection. However, little is known about the relative performance of different information-theoretic criteria in covariance structure modeling, especially in behavioral genetic contexts. To explore these issues, information-theoretic fit criteria were compared with regard to their ability to discriminate between multivariate behavioral genetic models under various model, distribution, and sample size conditions. Results indicate that performance depends on sample size, model complexity, and distributional specification. The Bayesian Information Criterion (BIC) is more robust to distributional misspecification than Akaike's Information Criterion (AIC) under certain conditions, and outperforms AIC in larger samples and when comparing more complex models. An approximation to the Minimum Description Length (MDL; Rissanen, J. (1996). IEEE Transactions on Information Theory 42:40-47, Rissanen, J. (2001). IEEE Transactions on Information Theory 47:1712-1717) criterion, involving the empirical Fisher information matrix, exhibits variable patterns of performance due to the complexity of estimating Fisher information matrices. Results indicate that a relatively new information-theoretic criterion, Draper's Information Criterion (DIC; Draper, 1995), which shares features of the Bayesian and MDL criteria, performs similarly to or better than BIC. Results emphasize the importance of further research into theory and computation of information-theoretic criteria.

Bayes Theorem↗

PubMed1999

Isolation by distance in a continuous population: reconciliation between spatial autocorrelation analysis and population genetics models.

Analysis of the spatial genetic structure within continuous populations in their natural habitat can reveal acting evolutionary processes. Spatial autocorrelation statistics are often used for this purpose, but their relationships with population genetics models have not been thoroughly established. Moreover, it has been argued that the dependency of these statistics on variation in mutation rates among loci strongly limits their interest for inferential purposes. In the context of an isolation by distance process, we describe relationships between a descriptor of the spatial genetic structure used in empirical studies, Moran's I statistic and population genetics parameters. In particular, we point out that, when Moran's I statistic is used to describe correlation in allele frequencies at the individual level, it provides an estimator of Wright's coefficient of relationship. We also show that the latter parameter, as a descriptor of genetic structure, is not influenced by selfing rate or ploidy level. Under specific finite population models, numerical simulations show that values of Moran's I statistic can be predicted from analytical theory. These simulations are also used to estimate the time taken to approach a structure at equilibrium. Finally, we discuss the conditions under which spatial autocorrelation statistics are little influenced by variation in mutation rates, so that they could be used to estimate gene dispersal parameters.

Genetics, Population↗

PubMed1994

Developmental quantitative genetic models of evolutionary change.

Discussions about evolutionary change in developmental processes or morphological structures are predicated on specific quantitative genetic models whose parameters predict whether evolutionary change can occur, its relative rate and direction, and if correlated change will occur in other related and unrelated structures. The appropriate genetic model should reflect the relevant genetical and developmental biology of the organisms, yet be simple enough in its parameters so that deductions can be made and hypotheses tested. As a consequence, the choice of the most appropriate genetic model for polygenically controlled traits is a complex tissue and the eventual choice of model is often a compromise between completeness of the model and computational expediency. Herein, we discuss several developmental quantitative genetic models for the evolution of development and morphology. The models range from the classical direct effects model to complex epigenetic models. Further, we demonstrate the algebraic equivalency of the Cowley and Atchley epigenetic model and Wagner's developmental mapping model. Finally, we propose a new multivariate model for continuous growth trajectories. The relative efficacy of these various models for understanding evolutionary change in developmental and morphological traits is discussed.

Animals↗

PubMed1987

The "battle of the sexes": a genetic model with limit cycle behavior.

A two-locus genetic model, based on Dawkins "sex war" game, with the fitness of the genotypes at each locus depending on the gene frequencies at the other, is shown to give rise to a stable limit cycle. The mathematical analysis involves averaging techniques and elliptic integrals.

Animals↗

PubMed1992

Genetic models of absence epilepsy, with emphasis on the WAG/Rij strain of rats.

In this review, the main characteristics of genetic models of absence epilepsy, in particular with respect to WAG/Rij rats, are presented. Genetic models are important and relevant, since evidence exists that these models mimic spontaneously occurring human epilepsy more than models in which epilepsy is artificially induced. Genetic models can be divided into models in which seizures are elicited and into those in which epilepsy appears without any sensory stimulation. The majority of genetic models show that absence type of epilepsy; during the last few years, we and others have noticed that rats of various strains exhibit spontaneously occurring spike-wave discharges in the EEG. Among the strains highly affected is the WAG/Rij strain, which is a fully inbred strain. Individuals are homozygous and because of this property, genetic studies are meaningful. Electrophysiological studies have indicated that abnormal discharges in the cortical EEG are generalized and that the hippocampus is not involved. Parts of the thalamus, together with the thalamic reticular nucleus, apparently act as a pacemaker for the abnormal discharges. There is a circadian modulation in the number of spike-wave discharges. Discharges mainly occur during intermediate levels of vigilance such as passive wakefulness and light slow-wave sleep and at transitions of sleep states. Pharmacological studies with clinically effective antiepileptic drugs have shown a close agreement in seizure response between man and rat. Studies with new compounds have emphasized the role of the GABAergic and glutamatergic system in this type of epilepsy. Particularly striking is the role of the GABAergic system. GABA agonists enhance and GABA antagonists reduce the occurrence of spike-wave discharges, which deviates from the effects of GABAergic drugs in non-convulsive epilepsy. Even more striking is the role of the benzodiazepines, generally seen as GABA agonists; these drugs do not act as such in absence epilepsy since they reduce spike-wave discharges. Also good evidence for an involvement of other neurotransmitters such as noradrenaline, dopamine and opioid peptides exists in absence epilepsy. Genetic data obtained from the WAG/Rij model for absence epilepsy show a relatively simple pattern of inheritance with one gene determining whether an individual is epileptic or not, and with other genes regulating the number and duration of seizures. This is in good agreement with the more restricted human data. Cognitive studies have shown two important features of epilepsy in the WAG/Rij strain: modulation of the number of spike-wave discharges by mental or physical activity and on the other hand, the disruption of cognitive activity by spike-wave discharges.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMedDate not supplied

Genetic models for the natural history of smoking: evidence for a genetic influence on smoking persistence.

We reanalyze data from the 1981 mailed questionnaire survey of the Australian twin register, to test for a genetic effect on smoking persistence (whether or not a smoker quits smoking). In the young cohort, aged 18-30 years, there are too few ex-smokers to permit resolution of genetic and non-genetic models. In the older cohort, we find a significant and substantial genetic effect on smoking persistence, accounting for 53% of the variance. This genetic effect on smoking persistence is independent of genetic effects on smoking initiation.

Adolescent↗

PubMed2000

A genetic model: analysis and application to MAXSAT.

In this paper, a genetic model based on the operations of recombination and mutation is studied and applied to combinatorial optimization problems. Results are: 1. The equations of the deterministic dynamics in the thermodynamic limit (infinite populations) are derived and, for a sufficiently small mutation rate, the attractors are characterized; 2. A general approximation algorithm for combinatorial optimization problems is designed. The algorithm is applied to the Max Ek-Sat problem, and the quality of the solution is analyzed. It is proved to be optimal for k > or = 3 with respect to the worst case analysis; for Max E3-Sat the average case performances are experimentally compared with other optimization techniques.

Algorithms↗

PubMedDate not supplied

Genetic models for plant pathosystems.

Deterministic, discrete time, genetics models for a resistant plant host and a virulent pathogen are developed and analyzed. The original model was developed by Leonard in 1977 for a single gene with haploid pathogens and diploid hosts [Ann. N.Y. Acad. Sci. 287 (1977) 207]. The original model is generalized to diploid hosts and pathogens with incomplete dominance of the heterozygote. In addition, the single gene model is extended to two genes and a stochastic model with random selection values is formulated and simulated. It is shown using local stability properties that stability of the polymorphic equilibrium is indeterminant; the equilibrium is non-hyperbolic. The original model of Leonard has this same property. However, with random selection values, solutions tend to converge toward the polymorphic equilibrium.

Models, Genetic↗