The Changes in Genetic and Environmental Variance With Inbreeding in Drosophila melanogaster

Genetics ◽  
1999 ◽  
Vol 152 (1) ◽  
pp. 345-353 ◽  
Author(s):  
Michael C Whitlock ◽  
Kevin Fowler
Keyword(s):  
Drosophila Melanogaster ◽  
Large Scale ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Inbred Lines ◽  
Residual Variance ◽  
Phenotypic Variance ◽  
Population Bottlenecks ◽  
Environmental Variance ◽  
Components Of Variance

Abstract We performed a large-scale experiment on the effects of inbreeding and population bottlenecks on the additive genetic and environmental variance for morphological traits in Drosophila melanogaster. Fifty-two inbred lines were created from the progeny of single pairs, and 90 parent-offspring families on average were measured in each of these lines for six wing size and shape traits, as well as 1945 families from the outbred population from which the lines were derived. The amount of additive genetic variance has been observed to increase after such population bottlenecks in other studies; in contrast here the mean change in additive genetic variance was in very good agreement with classical additive theory, decreasing proportionally to the inbreeding coefficient of the lines. The residual, probably environmental, variance increased on average after inbreeding. Both components of variance were highly variable among inbred lines, with increases and decreases recorded for both. The variance among lines in the residual variance provides some evidence for a genetic basis of developmental stability. Changes in the phenotypic variance of these traits are largely due to changes in the genetic variance.

scholarly journals Effects of stress combinations on the expression of additive genetic variation for fecundity in Drosophila melanogaster

1998 ◽  
Vol 72 (1) ◽  
pp. 13-18 ◽  
Author(s):  
CARLA M. SGRÒ ◽  
ARY A. HOFFMANN
Keyword(s):  
Drosophila Melanogaster ◽  
Genetic Variance ◽  
Cold Shock ◽  
Additive Genetic Variance ◽  
Combined Stress ◽  
Heritable Variation ◽  
Environmental Variance ◽  
Apparent Increase ◽  
Nutrition Environment ◽  
Stress Combinations

To test whether stressful conditions altered levels of heritable variation in fecundity in Drosophila melanogaster, parent–offspring comparisons were undertaken across three generations for flies reared in a combined stress (ethanol, cold shock, low nutrition) environment or a control environment. The stressful conditions did not directly influence fecundity but did lead to a reduced fecundity in the offspring generations, perhaps reflecting cross-generation maternal effects. Both the heritability and evolvability estimates were higher in the combined stress treatment, reflecting an apparent increase in the additive genetic variance under stress. In contrast, there were no consistent changes in the environmental variance across environments.

scholarly journals Longitudinal modeling of genetic and environmental influences on self-reported availability of psychoactive substances: alcohol, cigarettes, marijuana, cocaine and stimulants

2007 ◽  
Vol 37 (7) ◽  
pp. 947-959 ◽  
Author(s):  
NATHAN A. GILLESPIE ◽  
KENNETH S. KENDLER ◽  
CAROL A. PRESCOTT ◽  
STEVEN H. AGGEN ◽  
CHARLES O. GARDNER ◽  
...  
Keyword(s):  
Individual Differences ◽  
Ordinal Data ◽  
Genetic Variance ◽  
Environmental Control ◽  
Additive Genetic Variance ◽  
Social Constraints ◽  
Adult Males ◽  
Environmental Variance ◽  
Components Of Variance ◽  
Over Time

Background. Although an obvious environmental factor influencing drug use, the sources of individual differences in drug availability (DA) are unknown.Method. This report is based on 1788 adult males from the Mid-Atlantic Twin Registry who participated in a structured telephone interview that included retrospective assessments of DA (cigarette, alcohol, marijuana, cocaine and stimulants) between ages 8 and 25. We fitted a biometric dual change score (DCS) model, adapted for ordinal data, to model latent growth and estimate the genetic and environmental components of variance over time.Results. DA, despite being considered an environmental risk factor, is under both genetic and environmental control. For cigarette, alcohol, marijuana and cocaine availability, there was an overall increase in additive genetic variance and a decline in shared environmental variance over time. Non-shared environmental variance remained steady. Stimulant availability did not follow this pattern. Instead, there was an upswing in shared environmental effects with increasing age.Conclusion. We have modeled the genetic and environmental architecture of changes in DA across adolescence. The rise in additive genetic variance over time coincides with acceleration in the expression of individual differences, probably brought on by an increase in personal freedom and a reduction in social constraints. Understanding the etiology of DA is likely to reveal key components, acting directly or indirectly, in the pathway(s) leading to drug initiation, abuse and dependence.

INHERITANCE OF CYCLIC HYDROXAMATES IN Zea mays L.

1981 ◽  
Vol 61 (3) ◽  
pp. 583-593 ◽  
Author(s):  
G. M. DUNN ◽  
B. J. LONG ◽  
D. G. ROUTLEY
Keyword(s):  
Zea Mays ◽  
Genetic Variance ◽  
Zea Mays L ◽  
Additive Genetic Variance ◽  
Hydroxamic Acids ◽  
Phenotypic Variance ◽  
High Concentration ◽  
Components Of Variance ◽  
Rapid Procedure ◽  
Colorimetric Reaction

Hydroxamic acids have been implicated in the resistance of corn (Zea mays L.) to both fungi and insects. In this study, five selected crosses were used among the four inbreds BxBx, bxbx, B49 and B37 to study inheritance of hydroxamates. Hydroxamate concentration in the parental, F1, F2 and backcross generations for each cross was estimated by a rapid procedure based upon the colorimetric reaction of hydroxamates with FeCl3. Components of variance and estimates of heritability were obtained by the procedures of Warner (1952). F2 and backcross data indicated that concentration of hydroxamates is controlled monogenically in the cross bxbx × BxBx and polygenically in the crosses bxbx × B49 and bxbx × B37. Estimates of gene number using the Castle-Wright formula indicated that hydroxamate concentration is conditioned in B49 and B37 by five and two loci, respectively. The addition of BxBx to either B49 or B37 increased the frequency of genotypes in F2 with a high concentration of hydroxamates. Additive genetic variance was the most important component of the phenotypic variance and resulted in estimates of heritability from 0.64 to 0.79. However, the dominance component of variance was considerably higher for crosses involving BxBx than for the crosses bxbx × B49 and bxbx × B37.

scholarly journals Selection on wing allometry in Drosophila melanogaster.

Genetics ◽  
1990 ◽  
Vol 126 (4) ◽  
pp. 975-989 ◽  
Author(s):  
K E Weber
Keyword(s):  
Drosophila Melanogaster ◽  
Additive Genetic Variance ◽  
Bivariate Distribution ◽  
Local Optimum ◽  
Phenotypic Variance ◽  
Isofemale Lines ◽  
Developmental Patterns ◽  
Environmental Regimes ◽  
The Mean ◽  
Lateral Offset

Abstract Five bivariate distributions of wing dimensions of Drosophila melanogaster were measured, in flies 1) subjected to four defined environmental regimes during development, 2) taken directly from nature in seven U.S. states, 3) selected in ten populations for change in wing form, and 4) sampled from 21 long inbred wild-type lines. Environmental stresses during development altered both wing size and the ratios of wing dimensions, but regardless of treatment all wing dimensions fell near a common allometric baseline in each bivariate distribution. The wings of wild-caught flies from seven widely separated localities, and of their laboratory-reared offspring, also fell along the same baselines. However, when flies were selected divergently for lateral offset from these developmental baselines, response to selection was rapid in every case. The mean divergence in offset between oppositely selected lines was 14.68 SD of the base population offset, after only 15 generations of selection at 20%. Measurements of 21 isofemale lines, founded from wild-caught flies and maintained in small populations for at least 22 years, showed large reductions in phenotypic variance of offsets within lines, but a large increase in the variance among lines. The variance of means of isofemale lines within collection localities was ten times the variance of means among localities of newly established wild lines. These observations show that much additive genetic variance exists for individual dimensions within the wing, such that bivariate developmental patterns can be changed in any direction by selection or by drift. The relative invariance of the allometric baselines of wing morphology in nature is most easily explained as the result of continuous natural selection around a local optimum of functional design.

scholarly journals Effects on phenotypic variability of directional selection arising through genetic differences in residual variability

2004 ◽  
Vol 83 (2) ◽  
pp. 121-132 ◽  
Author(s):  
WILLIAM G. HILL ◽  
XU-SHENG ZHANG
Keyword(s):  
Genetic Variance ◽  
Environmental Variability ◽  
Phenotypic Variability ◽  
Additive Genetic Variance ◽  
Directional Selection ◽  
Frequency Change ◽  
Phenotypic Variance ◽  
Additive Effects ◽  
Genetic Covariance ◽  
Mean And Variance

In standard models of quantitative traits, genotypes are assumed to differ in mean but not variance of the trait. Here we consider directional selection for a quantitative trait for which genotypes also confer differences in variability, viewed either as differences in residual phenotypic variance when individual loci are concerned or as differences in environmental variability when the whole genome is considered. At an individual locus with additive effects, the selective value of the increasing allele is given by ia/σ+½ixb/σ2, where i is the selection intensity, x is the standardized truncation point, σ2 is the phenotypic variance, and a/σ and b/σ2 are the standardized differences in mean and variance respectively between genotypes at the locus. Assuming additive effects on mean and variance across loci, the response to selection on phenotype in mean is iσAm2/σ+½ixcovAmv/σ2 and in variance is icovAmv/σ+½ixσ2Av/σ2, where σAm2 is the (usual) additive genetic variance of effects of genes on the mean, σ2Av is the corresponding additive genetic variance of their effects on the variance, and covAmv is the additive genetic covariance of their effects. Changes in variance also have to be corrected for any changes due to gene frequency change and for the Bulmer effect, and relevant formulae are given. It is shown that effects on variance are likely to be greatest when selection is intense and when selection is on individual phenotype or within family deviation rather than on family mean performance. The evidence for and implications of such variability in variance are discussed.

scholarly journals Variance component analysis for viability in an isolated population of Drosophila melanogaster

1983 ◽  
Vol 42 (2) ◽  
pp. 207-217 ◽  
Author(s):  
Hidenori Tachida ◽  
Muneo Matsuda ◽  
Shin-Ichi Kusakabe ◽  
Terumi Mukai
Keyword(s):  
Drosophila Melanogaster ◽  
Genetic Variance ◽  
Balancing Selection ◽  
Additive Genetic Variance ◽  
Diallel Cross ◽  
Variance Component Analysis ◽  
Logarithmic Scale ◽  
Dominance Variance ◽  
Diversifying Selection ◽  
Partial Diallel

SUMMARYUsing the 602 second chromosome lines extracted from the Ishigakijima population of Drosophila melanogaster in Japan, partial diallel cross experiments (Design II of Comstock & Robinson, 1952) were carried out, and the additive genetic variance and the dominance variance of viability were estimated. The estimated value of the additive genetic variance is 0·01754±0·00608, and the dominance variance 0·00151±0·00114, using a logarithmic scale. Since the value of the additive genetic variance is much larger than expected under mutation–selection balance although the dominance variance is compatible with it, we speculate that in the Ishigakijima population some type of balancing selection must be operating to maintain the genetic variability with respect to viability at a minority of loci. As candidates for such selection, overdominance, frequency-dependent selection, and diversifying selection are considered, and it is suggested that diversifying selection is the most probable candidate for increasing the additive genetic variance.

scholarly journals ESTİMATİON OF GENETİC AND ENVİRONMENTAL PARAMETERS AFFECTİNG PRODUCTİVİTY İN MORKARAMAN SHEEP AND ECONOMİC EVALUATİON OF PARAMETERS

2021 ◽  
pp. 155-161
Author(s):  
Ufuk Karadavut ◽  
Burhan Bahadır ◽  
Volkan Karadavut ◽  
Galip Şimşek ◽  
Hakan İnci
Keyword(s):  
Genetic Parameters ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Environmental Parameters ◽  
Error Variance ◽  
Economic Importance ◽  
Phenotypic Variance ◽  
Economic Aspects ◽  
Evaluation Of Parameters ◽  
The Relationship

This study was carried out to protect the continuity of productivity in morkaraman sheep raised in Turkey and determine their economic importance. Morkaraman sheep are concentrated in the Eastern Regions of the country. The province of Bingöl, where the study was conducted, is located in this region and has an important morkaraman population. The study was carried out between 2008-2018. Sixty-eight morkaraman sheep were used during the study period out of 317 lambing lambs. In the study, the total number of lambs born per sheep (TNLBS), the number of weaned lambs (NWL), the weights of the lambs weaned per sheep (WLWS) and the total weight of the lambs weaned in the first period (TWLWFP) were determined. In addition, Additive genetic variance, Error variance, Phenotypic variance, Heritability and Ratio of error variation were determined for these variables. As a result, the correlation between the examined variables was significant and positive, except for the relationship between TNLBS and TWLWFP. The relationship between these two variables was significant but negative. Significant changes were also observed in terms of genetic parameters. It was concluded that the economic aspects of the examined variables should not be ignored in terms of sustainability. Keywords: Sheep, morkaraman, sustainability, genotypic and phenotypic variance.

scholarly journals A guide to using a multiple-matrix animal model to disentangle genetic and nongenetic causes of phenotypic variance

2018 ◽  
Author(s):  
Caroline E. Thomson ◽  
Isabel S. Winney ◽  
Oceane C. Salles ◽  
Benoit Pujol
Keyword(s):  
Animal Model ◽  
Genetic Variance ◽  
Genetic Relatedness ◽  
Additive Genetic Variance ◽  
Phenotypic Traits ◽  
Phenotypic Variance ◽  
Data Types ◽  
Evolutionary Potential ◽  
Recent Developments

AbstractNon-genetic influences on phenotypic traits can affect our interpretation of genetic variance and the evolutionary potential of populations to respond to selection, with consequences for our ability to predict the outcomes of selection. Long-term population surveys and experiments have shown that quantitative genetic estimates are influenced by nongenetic effects, including shared environmental effects, epigenetic effects, and social interactions. Recent developments to the “animal model” of quantitative genetics can now allow us to calculate precise individual-based measures of non-genetic phenotypic variance. These models can be applied to a much broader range of contexts and data types than used previously, with the potential to greatly expand our understanding of nongenetic effects on evolutionary potential. Here, we provide the first practical guide for researchers interested in distinguishing between genetic and nongenetic causes of phenotypic variation in the animal model. The methods use matrices describing individual similarity in nongenetic effects, analogous to the additive genetic relatedness matrix. In a simulation of various phenotypic traits, accounting for environmental, epigenetic, or cultural resemblance between individuals reduced estimates of additive genetic variance, changing the interpretation of evolutionary potential. These variances were estimable for both direct and parental nongenetic variances. Our tutorial outlines an easy way to account for these effects in both wild and experimental populations. These models have the potential to add to our understanding of the effects of genetic and nongenetic effects on evolutionary potential. This should be of interest both to those studying heritability, and those who wish to understand nongenetic variance.

QUANTITATIVE GENETICS OF DROSOPHILA MELANOGASTER. I. SEXUAL DIMORPHISM IN GENETIC PARAMETERS FOR WING TRAITS

Genetics ◽  
1986 ◽  
Vol 114 (2) ◽  
pp. 549-566
Author(s):  
David E Cowley ◽  
William R Atchley ◽  
J J Rutledge
Keyword(s):  
Drosophila Melanogaster ◽  
Sexual Dimorphism ◽  
Dosage Compensation ◽  
Genetic Parameters ◽  
Genetic Model ◽  
Genetic Correlations ◽  
Error Variance ◽  
Minor Effect ◽  
Phenotypic Variance ◽  
Environmental Variance

ABSTRACT Sexual dimorphism in genetic parameters is examined for wing dimensions of Drosophila melanogaster. Data are fit to a quantitative genetic model where phenotypic variance is a linear function of additive genetic autosomal variance (common to both sexes), additive genetic X-linked variances distinct for each sex, variance due to common rearing environment of families, residual environmental variance, random error variance due to replication, and variance due to measurement error and developmental asymmetry (left vs. right sides). Polygenic dosage compensation and its effect on genetic variances and covariances between sexes is discussed. Variance estimates for wing length and other wing dimensions highly correlated with length support the hypothesis that the Drosophila system of dosage compensation will cause male X-linked genetic variance to be substantially larger than female X-linked variance. Results for various wing dimensions differ, suggesting that the level of dosage compensation may differ for different traits. Genetic correlations between sexes for the same trait are presented. Total additive genetic correlations are near unity for most wing traits; this indicates that selection in the same direction in both sexes would have a minor effect on changing the magnitude of difference between sexes. Additive X-linked correlations suggest some genotype × sex interactions for X-linked effects.

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