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At least 19 recordsLinked to original sources
PubMed1992

Genetic Tobit factor analysis: quantitative genetic modeling with censored data.

Parameters of quantitative genetic models have traditionally been estimated by either algebraic manipulation of familial correlations (or familial mean squares), biometric model fitting, or multiple-group covariance structure analysis. With few exceptions, researchers who have used these methods for the analysis of twin data have assumed that their data were multinormal and, consequently, have used normal-theory estimation methods. It is shown that normal-theory methods produce biased genetic and environmental parameter estimates when data are censored. Specifically, with censored data, (1) normal-theory estimates of narrow-sense heritability are either positively or negatively biased, whereas (2) estimates of shared-familial environmental variance are always biased downward. An alternative method for estimating genetic and environmental parameters from censored twin data is proposed. The method is called genetic Tobit factor analysis (GTFA) and is an extension of the Tobit factor analysis model developed by Muthén (Br. J. Math. Stat. Psychol. 42, 241-250, 1989). Using a Monte Carlo design, the performance of GTFA is compared to traditional quantitative genetic methods in both large and small data sets. The results of this study suggest that GTFA is the preferred method for the genetic modeling of censored data obtained from twins.

Genetics, Behavioral↗
PubMed2025

A single-locus quantitative genetic model incorporating DNA methylation.

We describe a single-locus quantitative genetic model that incorporates effects due to DNA methylation. Extending Fisher's decomposition of the genotypic value, we distinguish two quantities to predict an individual's phenotypic or genetic values: the "basic genetic value" and the "expressed genetic value". We show how these quantities relate to the concept of breeding value and derive their corresponding formulas, along with those for phenotypic variance and covariance between relatives. The resulting parameters are influenced by several factors, including the population distribution of DNA methylation levels, the functional relationship between methylation and phenotype, the magnitudes of genetic and methylation effects, and allele frequencies. We show that under the conditions modeled, the presence of DNA methylation does not bias estimated breeding values.

DNA Methylation↗
PubMed1992

Quantitative genetic study on sexual difference in emigration behavior of Drosophila melanogaster in a natural population.

A quantitative genetic analysis was conducted on emigration response behavior using 140 second chromosome lines of Drosophila melanogaster. Fourteen sets of 5 x 5 partial diallel cross experiments were made in the parental generation. The emigration activity per batch of 50 male and 50 female F1 progeny was scored with Sakai's population system. Sexual difference did not appear in the emigration activity in these experiments. A significant genotype x sex x set interaction was detected. The genetic variance components of emigration activity differed between sexes: In males, additive genetic variance of emigration activity was 0.0497 +/- 0.0092 and dominance variance, 0.0018 +/- 0.0046; in females, additive, 0.0373 +/- 0.0076 and dominance, 0.0169 +/- 0.0044. Additive genetic correlation between sexes for the emigration activity was 0.685 +/- 0.150, deviating significantly from unity. These results suggested that the genes affecting emigration activity would operate differently between sexes of D. melanogaster in natural populations.

Animals↗
PubMed2026

Dissecting fluctuating selection: A unified population and quantitative genetics framework.

One of the longstanding debates in evolutionary biology is the effect of fluctuating selection on genetic changes in populations. However, the extent to which these periodic forces influence organisms at both genomic and phenotypic levels remains unclear. Despite the compelling evidence of fluctuating selection from recent studies, there is a disconnect between empirical and theoretical findings concerning the underlying mechanisms due to the limited evidence regarding the scale and processes that generate genome-wide oscillations. This study aims to elucidate how both genetic factors (e.g. heritability, number of causative loci) and ecological factors (e.g. season length, the difference in the phenotypic optima between seasons, population size dynamics) drive fluctuating selection and to identify the parameters that produce consistent oscillatory patterns. We developed a modeling framework integrating quantitative and population genetics to simulate a population under various selection regimes. We applied spectral analysis to detect periodicity, indicating cyclical selective environments. Our simulations highlight the conditions sustaining oscillations in allele frequencies over time. Spectral analysis successfully identifies the periodic patterns from allele frequency trajectories, even under highly complex selection regimes. Not only does our study clarify the conditions that yield oscillatory behaviors, but these parameters can also potentially be estimated in natural populations, providing a possibility of empirically testing these models.

Fluctuating selection↗
PubMed2026

Dissecting fluctuating selection: A unified population and quantitative genetics framework.

One of the longstanding debates in evolutionary biology is the effect of fluctuating selection on genetic changes in populations. However, the extent to which these periodic forces influence organisms at both genomic and phenotypic levels remains unclear. Despite the compelling evidence of fluctuating selection from recent studies, there is a disconnect between empirical and theoretical findings concerning the underlying mechanisms due to the limited evidence regarding the scale and processes that generate genome-wide oscillations. This study aims to elucidate how both genetic factors (e.g. heritability, number of causative loci) and ecological factors (e.g. season length, the difference in the phenotypic optima between seasons, population size dynamics) drive fluctuating selection and to identify the parameters that produce consistent oscillatory patterns. We developed a modeling framework integrating quantitative and population genetics to simulate a population under various selection regimes. We applied spectral analysis to detect periodicity, indicating cyclical selective environments. Our simulations highlight the conditions sustaining oscillations in allele frequencies over time. Spectral analysis successfully identifies the periodic patterns from allele frequency trajectories, even under highly complex selection regimes. Not only does our study clarify the conditions that yield oscillatory behaviors, but these parameters can also potentially be estimated in natural populations, providing a possibility of empirically testing these models.

Fluctuating selection↗
PubMedDate not supplied

A quantitative genetic analysis of localized morphology in mandibles of inbred mice using finite element scaling analysis.

We analyzed patterns of mandibular genetic and phenotypic morphological integration and the relationship of genealogy to interstrain molecular and morphological differences in ten inbred strains of mice. Positions of mandibular landmarks in two-dimensional space were used to construct a finite element mesh for each individual, then all individuals from the ten strains were compared to the average mandible from a standard strain (SEA/GnJ). Measures of size and shape associated with finite element scaling analysis were then used in a quantitative genetic analysis of mandibular variation. Significant genetic variation for mandibular size and shape was uncovered. Patterns of both genetic and phenotypic correlation for measures of landmark-specific sizes were consistent with models of morphological integration based on the developmental origin of parts of the mandible and on the effects of muscle attachment on mandibular morphology. Shape differences local to particular landmarks did not show these forms of morphological integration. Although interstrain distances based on local shape magnitudes were significantly correlated with genealogical relationship, distances based on local size differences were not. Even higher than the correlation of genealogy with distances based on local shape magnitude was the genealogical-molecular distance correlation. Patterns of morphometric mandibular variation corresponded to expected effects of epigenetic developmental processes. Also, when detailed shape differences were considered, morphology served as a rough guide to genealogy, although molecular distances showed a stronger relationship.

Animals↗
PubMedDate not supplied

Quantitative genetically nonequivalent reciprocal crosses in cultivated plants.

Quantitative expressions of character difference between reciprocal crosses have been studied by different researchers in a number of plant species, such as Epilobium, Zea mays, Oryza sativa, Hordeum sativum, Triticum aestivum, Trifolium hybridum, Linum usitatissimum, Nicotiana rustica, and others. In all cases it was found that the nonequivalence of reciprocal crosses manifested itself beginning with the F1 generation, with the exception of some flax crosses in which reciprocals differed beginning with the F2 generation. The nonequivalence of reciprocal crosses usually manifested itself in the inequality of their F1 and/or F2 or backcross means; however, there were instances in which their means were the same but the variances were different. Both matroclinous and patroclinous inheritances were reported in plants. Because of the casual complexity of reciprocal differences the experimental results often lack a simple explanation.

Cell Nucleus↗
PubMed1992

Quantitative genetic analysis of skin reflectance: a multivariate approach.

Skin color is a polygenically determined quantitative trait. Although it has been used extensively in studies of between-population variation, there have been relatively few studies of the inheritance of skin color. In this article we use measurements on 359 members of the Jirel population of eastern Nepal to assess the heritabilities and additive genetic correlations of three skin reflectance measures. Skin color was measured at the upper inner arm site at three wavelengths. A maximum likelihood approach was used to estimate sex and age effects on skin reflectance, heritabilities, and phenotypic variances at each wavelength and both additive genetic and environmental correlations between wavelengths. This technique incorporated information from 36 pedigrees with 2-25 members and 173 independent individuals. Likelihood ratio tests were used to assess the significance of specific variance/covariance components. The results indicate that skin reflectances are moderately heritable at all three wavelengths. The pairwise phenotypic correlations ranged from 0.76 to 0.88. The observed additive genetic correlations were not significantly different from 1.00, suggesting that the same loci influence variation at each wavelength. This evidence for relatively complete pleiotropy implies that measurements at multiple wavelengths yield little additional genetic information, although they may be useful for reducing measurement error. Based on estimates of the genetic and phenotypic covariance matrices, we determined that skin reflectance measurements are expected to provide only as much information for assessing local between-population genetic variation as a single two-allele polymorphic marker. Therefore microevolutionary studies based on skin color variation should be viewed with caution.

Adolescent↗
PubMed1992

On models of quantitative genetic variability: a stabilizing selection-balance model.

A model of stabilizing selection on a multilocus character is proposed that allows the maintenance of stable allelic polymorphism and linkage disequilibrium. The model is a generalization of Lerner's model of homeostasis in which heterozygotes are less susceptible to environmental variation and hence are superior to homozygotes under phenotypic stabilizing selection. The analysis is carried out for weak selection with a quadratic-deviation model for the stabilizing selection. The stationary state is characterized by unequal allele frequencies, unequal proportions of complementary gametes, and a reduction of the genetic (and phenotypic) variance by the linkage disequilibrium. The model is compared with Mather's polygenic balance theory, with models that include mutation-selection balance, and others that have been proposed to study the role of linkage disequilibrium in quantitative inheritance.

Alleles↗
PubMed1992

The use of quantitative genetics for estimating the non-inherited and inherited contributions to metastasis formation.

The contribution of both non-inherited (stochastic, random, environmental, and other non-inherited influences) and inherited factors (genetic and inherited epigenetic factors) to the variability of spontaneous lung metastasis formation in over 100 metastatic lines from each of three murine tumors was measured. The contribution of inherited and genetic sources of variability to metastasis formation was significantly greater than 0 in all cases, but only in the lines of sarcoma SANH was it the major influence on metastatic variability. In the sarcoma SA4020 and hepatocarcinoma HCA-1 lines, non-inherited factors accounted for the majority of the variation in spontaneous lung metastasis formation. A similar situation was also observed in the variability of the tumors with respect to the diameter doubling time. In conclusion, both non-inherited and genetic/inherited factors significantly influenced the formation of spontaneous metastases in the tumors examined. The significance of this finding for the cloning of metastatic genes is discussed.

Animals↗
PubMed1992

Quantitative genetic analysis of IQ development in young children: multivariate multiple regression with orthogonal polynomials.

The study of psychological development has recently benefited from innovative analytic methods for estimating and examining the correlates of individual growth curves. These methods are more consistent with a conceptualization of development as an ongoing, continuous process, rather than as increases or decreases in a trait between two discrete time points. Recent developmental behavior genetic models have focused on continuity and change in the genetic and environmental influences underlying phenotypes. In contrast, we present a model for genetic and environmental influences on phenotypic development per se. In this model, we adapted multiple regression methods developed for twin designs (DeFries and Fulker, 1985) to a parent-offspring adoption design and to a multivariate framework in which repeated measurements are decomposed into orthogonal polynomial trends. We applied these analyses to the development of IQ during infancy and early childhood using parent-offspring data from adoptive and nonadoptive families in the Colorado Adoption Project. The results suggested familial environmental influences on children's mean IQ for ages 1-4 but environmental influences specific to fathers' cognitive ability on children's IQ development. We also discuss advantages and disadvantages of the multivariate multiple regression method for studying genetic and environmental influences on development.

Adoption↗
PubMed1992

Quantitative genetic variation in body size of mice from new mutations.

To measure the amount of new genetic variation in 6-week weight of mice arising each generation from mutation, selection lines derived from an initially inbred strain were maintained for 25 generations. An analysis using an animal model with restricted maximum likelihood was applied to estimate a mutational genetic component of variance for the infinitesimal model of many genes of small effect. Assuming that the inbred base population was at a mutation-drift equilibrium, it is estimated that the heritability for body size has increased by 1.0% per generation, with lower and upper confidence limits of 0.6% and 1.6%, respectively. A model which includes a mutational genetic component of variance fits the data much better than one involving only base population genetic variance. A model with no genetic component fits the data very poorly. An environmental covariance of body size of mother and offspring was included in the model and accounts for 10% of the variance. By using information only from the observed response to selection, the estimated increase in heritability from mutation is 0.3% per generation. These values are higher than published estimates for the increase in variance from spontaneous mutations in bristle traits of Drosophila, for which there are extensive data, but similar to estimates for various skeletal traits in mice.

Animals↗
PubMed1977

The nature of quantitative genetic variation in Drosophila. III. Mechanism of dosage compensation for sex-linked abdominal bristle polygenes.

Seventeen lines, each homozygous for a different X chromosome but all with a common autosomal genetic blackground, were constructed and assayed for abdominal bristle number to determine whether dosage compensation operates for sex-linked genes affecting this character. --The regression coefficient of male mean on female mean using a logarithmic scale was 0.90 +/- 0.13 and the genetic regression coefficient 0.92, neither differing significantly from unity. The genetic components of variance in males and females were also very similar (0.000234 or 0.000228, respectively). These results indicate that dosage compensation is complete (or nearly so) for sex-linked genes affecting this character. The bristle scores of females did not differ in reciprocal crosses between these lines, thus dosage compensation does not operate by paternal X inactivation. --The question of an adequate scale for abdominal bristle number had to be examined during the study. A logarithmic scale appeared to be adequate for both genotypic and environmental differences.

Animals↗