The struggle to exploit non-additive variation

2005 ◽  
Vol 56 (9) ◽  
pp. 873 ◽  
Author(s):  
Bruce Walsh
Keyword(s):  
Genetic Variation ◽  
Asexual Reproduction ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Epistatic Variance

Whereas animal breeders largely focus on improvement using additive genetic variance, inbreeding and asexual reproduction allow plant breeders to at least partially exploit non-additive genetic variance as well. We briefly review various approaches used by breeders to exploit dominance and epistatic variance, discuss their constraints and limitations, and examine what (if anything) can be done to improve our ability to further use often untapped genetic variation.

scholarly journals How does parental environment influence the potential for adaptation to global change?

2018 ◽  
Vol 285 (1886) ◽  
pp. 20181374 ◽  
Author(s):  
Evatt Chirgwin ◽  
Dustin J. Marshall ◽  
Carla M. Sgrò ◽  
Keyne Monro
Keyword(s):  
Genetic Variation ◽  
Global Change ◽  
Adaptive Capacity ◽  
Genetic Variance ◽  
Life Stage ◽  
Additive Genetic Variance ◽  
Parental Exposure ◽  
Future Warming ◽  
The Mean ◽  
Negative Impacts

Parental environments are regularly shown to alter the mean fitness of offspring, but their impacts on the genetic variation for fitness, which predicts adaptive capacity and is also measured on offspring, are unclear. Consequently, how parental environments mediate adaptation to environmental stressors, like those accompanying global change, is largely unknown. Here, using an ecologically important marine tubeworm in a quantitative-genetic breeding design, we tested how parental exposure to projected ocean warming alters the mean survival, and genetic variation for survival, of offspring during their most vulnerable life stage under current and projected temperatures. Offspring survival was higher when parent and offspring temperatures matched. Across offspring temperatures, parental exposure to warming altered the distribution of additive genetic variance for survival, making it covary across current and projected temperatures in a way that may aid adaptation to future warming. Parental exposure to warming also amplified nonadditive genetic variance for survival, suggesting that compatibilities between parental genomes may grow increasingly important under future warming. Our study shows that parental environments potentially have broader-ranging effects on adaptive capacity than currently appreciated, not only mitigating the negative impacts of global change but also reshaping the raw fuel for evolutionary responses to it.

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

2016 ◽  
Vol 6 (12) ◽  
pp. 3903-3911 ◽  
Author(s):  
Robert M Griffin ◽  
Holger Schielzeth ◽  
Urban Friberg
Keyword(s):  
Drosophila Melanogaster ◽  
Genetic Variation ◽  
X Chromosome ◽  
Dosage Compensation ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Conclusive Evidence ◽  
Substitution Lines ◽  
Chromosome Substitution Lines ◽  
Sexually Antagonistic Selection

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

scholarly journals Genetic variation in varying environments

1981 ◽  
Vol 37 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Trudy F. C. Mackay
Keyword(s):  
Body Weight ◽  
Genetic Variation ◽  
Spatial Heterogeneity ◽  
Temporal Variation ◽  
Genetic Variance ◽  
Environmental Variability ◽  
Additive Genetic Variance ◽  
Environmental Variation ◽  
Heterogeneous Environments ◽  
Varying Environments

SUMMARYIn order to assess the relationship between genetic and environmental variability, a large natural population of Drosophila melanogaster was replicated as eight subpopulations, which were subjected to four different patterns of environmental variation. The environmental variable imposed was presence of 15% ethanol in the culture medium. Experimental treatments of the populations were intended to simulate constant environmental conditions, spatial heterogeneity in the environment, and two patterns of temporal environmental variation with different periodicity (long- and short-term temporal variation). Additive genetic and phenotypic variation in sternopleural and abdominal chaeta number, and body weight, were estimated in two successive years, and measurements were taken of the genotype–environment correlation of body weight and sternopleural bristle score with medium type.Additive genetic variance of sternopleural chaeta number and of body weight was significantly greater in the three populations experiencing environmental heterogeneity than in the control population, but additive genetic variance of abdominal bristle score was not clearly affected by exposing populations to varying environments. Temporal environmental variation was equally, if not more, efficient in promoting the maintenance of genetic variation than spatial heterogeneity, but the cycle length of the temporal variation was of no consequence. Specific genotype–environment interactions were not present, therefore adaptation to heterogeneous environments is by selection of heterozygosity per se, rather than by differential survival of genotypes in the alternate niches.

scholarly journals Paper Birch and European White Birch Vary in Growth and Resistance to Bronze Birch Borer

1991 ◽  
Vol 116 (3) ◽  
pp. 580-584 ◽  
Author(s):  
Raymond O. Miller ◽  
Paul D. Bloese ◽  
James W. Hanover ◽  
Robert A. Haack
Keyword(s):  
Genetic Variation ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Species Variation ◽  
Betula Papyrifera ◽  
Narrow Sense ◽  
White Birch ◽  
Northeastern North America ◽  
Bronze Birch Borer ◽  
Paper Birch

A test of Michigan half-sib progeny of paper birch (Betula papyrifera Marsh.) and European white birch (B. pendula Roth.) was conducted in Michigan to examine species variation in growth, bark color, and resistance to bronze birch borer (Agrilus anxius Gory). Paper birch was superior to European white birch in height and borer resistance at age 12 years from seed. Families of paper birch were identified that grew exceptionally well, had developed white bark within 6 years, and exhibited borer resistance. The magnitude of additive genetic variance and narrow-sense family heritability estimates for paper birch indicated that sufficient genetic variation and inheritance exist to support selection and breeding for height. Paper birch may be an acceptable substitute for European white birch as a landscape species in northeastern North America.

scholarly journals THE GENETIC STRUCTURE OF NATURAL POPULATIONS OF DROSOPHILA MELANOGASTER. XVIII. CLINAL AND UNIFORM GENETIC VARIATION OVER POPULATIONS

Genetics ◽  
1984 ◽  
Vol 108 (3) ◽  
pp. 617-632
Author(s):  
Shinichi Kusakabe ◽  
Terumi Mukai
Keyword(s):  
Genetic Variation ◽  
Population Size ◽  
Mutation Rate ◽  
Genetic Variance ◽  
Balancing Selection ◽  
Additive Genetic Variance ◽  
Southern Population ◽  
Effective Population ◽  
Northern Population ◽  
The Difference

ABSTRACT It has been reported in the previous papers of this series that in the eastern United States and Japan there is a north-to-south cline of additive genetic variance of viability and that the amount of the additive genetic variance in the northern population can be explained by mutation-selection balance. To determine whether or not the difference in the genetic variation in northern and southern populations can be explained by the differences in mutation rate and/or effective population size, numerical calculations were made using population genetic parameters. In addition, the average heterozygosities of the northern and southern populations at ten of 19 polymorphic structural loci surveyed were estimated in relation to the cline of additive genetic variance of viability, and the following findings were obtained. (1) The changes in mutation rate and population size cannot simultaneously explain the difference in additive genetic variance and inbreeding decline between the northern and southern populations. Thus, the operation of some kind of balancing selection, most likely diversifying selection, was suggested to explain the observed excess of additive genetic variance. (2) Estimates of the average heterozygosities of the southern population were not significantly different from those of the northern population. Thus, it was strongly suggested that the excess of additive genetic variance in the southern population cannot be caused by structural loci, but by factors outside the structural loci, and that protein polymorphisms are selectively neutral or nearly neutral.

Changes in Genetic Variation Induced by Drift

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Genetic Variation ◽  
Variance Components ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Additive Variance

In the absence of the input of new variation, drift eventually removes all of the additive-genetic variance in a population. When nonadditive genetic variance is present, some of this variation can be transiently converted into additive variance, resulting in the latter occasionally increasingly (for a time) under inbreeding. This chapter examines the conditions under which such a conversion can occur, which leads to a discussion of the more complex covariances between inbred relatives, requiring the introduction of several new genetic-variance components to be introduced. It also examines the expected equilibrium levels of additive variance under drift-mutation equilibrium.

scholarly journals Estimation of non-additive genetic variance in human complex traits from a large sample of unrelated individuals

2020 ◽  
Author(s):  
Valentin Hivert ◽  
Julia Sidorenko ◽  
Florian Rohart ◽  
Michael E Goddard ◽  
Jian Yang ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Sampling Variance ◽  
Analysis Model ◽  
Additive Variance ◽  
Snp Data ◽  
Causal Variants ◽  
The Uk ◽  
Epistatic Variance

AbstractNon-additive genetic variance for complex traits is traditionally estimated from data on relatives. It is notoriously difficult to estimate without bias in non-laboratory species, including humans, because of possible confounding with environmental covariance among relatives. In principle, non-additive variance attributable to common DNA variants can be estimated from a random sample of unrelated individuals with genome-wide SNP data. Here, we jointly estimate the proportion of variance explained by additive , dominance and additive-by-additive genetic variance in a single analysis model. We first show by simulations that our model leads to unbiased estimates and provide new theory to predict standard errors estimated using either least squares or maximum likelihood. We then apply the model to 70 complex traits using 254,679 unrelated individuals from the UK Biobank and 1.1M genotyped and imputed SNPs. We found strong evidence for additive variance (average across traits . In contrast, the average estimate of across traits was 0.001, implying negligible dominance variance at causal variants tagged by common SNPs. The average epistatic variance across the traits was 0.058, not significantly different from zero because of the large sampling variance. Our results provide new evidence that genetic variance for complex traits is predominantly additive, and that sample sizes of many millions of unrelated individuals are needed to estimate epistatic variance with sufficient precision.

scholarly journals Fast and flexible linear mixed models for genome-wide genetics

2018 ◽  
Author(s):  
Daniel E Runcie ◽  
Lorin Crawford
Keyword(s):  
Genetic Variation ◽  
Quantitative Genetics ◽  
Mixed Models ◽  
Genetic Variance ◽  
Linear Mixed Models ◽  
Additive Genetic Variance ◽  
Multiple Sources ◽  
Mixed Effect ◽  
Linear Mixed Effect ◽  
Genome Wide

AbstractLinear mixed effect models are powerful tools used to account for population structure in genome-wide association studies (GWASs) and estimate the genetic architecture of complex traits. However, fully-specified models are computationally demanding and common simplifications often lead to reduced power or biased inference. We describe Grid-LMM (https://github.com/deruncie/GridLMM), an extendable algorithm for repeatedly fitting complex linear models that account for multiple sources of heterogeneity, such as additive and non-additive genetic variance, spatial heterogeneity, and genotype-environment interactions. Grid-LMM can compute approximate (yet highly accurate) frequentist test statistics or Bayesian posterior summaries at a genome-wide scale in a fraction of the time compared to existing general-purpose methods. We apply Grid-LMM to two types of quantitative genetic analyses. The first is focused on accounting for spatial variability and non-additive genetic variance while scanning for QTL; and the second aims to identify gene expression traits affected by non-additive genetic variation. In both cases, modeling multiple sources of heterogeneity leads to new discoveries.Author summaryThe goal of quantitative genetics is to characterize the relationship between genetic variation and variation in quantitative traits such as height, productivity, or disease susceptibility. A statistical method known as the linear mixed effect model has been critical to the development of quantitative genetics. First applied to animal breeding, this model now forms the basis of a wide-range of modern genomic analyses including genome-wide associations, polygenic modeling, and genomic prediction. The same model is also widely used in ecology, evolutionary genetics, social sciences, and many other fields. Mixed models are frequently multi-faceted, which is necessary for accurately modeling data that is generated from complex experimental designs. However, most genomic applications use only the simplest form of linear mixed methods because the computational demands for model fitting can be too great. We develop a flexible approach for fitting linear mixed models to genome scale data that greatly reduces their computational burden and provides flexibility for users to choose the best statistical paradigm for their data analysis. We demonstrate improved accuracy for genetic association tests, increased power to discover causal genetic variants, and the ability to provide accurate summaries of model uncertainty using both simulated and real data examples.

GENETICS OF THE BLUE MUSSEL MYTILUS EDULIS (L): NONADDITIVE GENETIC VARIATION IN LARVAL GROWTH RATE

1981 ◽  
Vol 23 (2) ◽  
pp. 349-354 ◽  
Author(s):  
G. F. Newkirk ◽  
L. E. Haley ◽  
J. Dingle
Keyword(s):  
Growth Rate ◽  
Genetic Variation ◽  
Mytilus Edulis ◽  
Genetic Variance ◽  
Blue Mussel ◽  
Additive Genetic Variance ◽  
Larval Growth ◽  
Total Variance ◽  
Dominance Variance ◽  
Larval Growth Rate

Through a series of factorial matings, it has been determined that in one population of the mussel, Mytilus edulis (L), there is some additive genetic variance for larval growth rate, but the predominant genetic component is nonadditive. In two separate experiments the sire-dam interaction which estimates 25% of the dominance variance plus other non-additive components accounted for 9% to 15% of the total variance in larval growth rate.

scholarly journals Standing genetic variation as a major contributor to adaptation in the Virginia chicken lines selection experiment

2015 ◽  
Author(s):  
Zheya Sheng ◽  
Mats E Pettersson ◽  
Christa F Honaker ◽  
Paul B Siegel ◽  
Örjan Carlborg
Keyword(s):  
Body Weight ◽  
Genetic Variation ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Selection Response ◽  
Selective Sweeps ◽  
Base Population ◽  
A Genome ◽  
Wide Scale ◽  
Genomic Regions

Artificial selection has, for decades, provided a powerful approach to study the genetics of adaptation. Using selective-sweep mapping, it is possible to identify genomic regions in populations where the allele-frequencies have diverged during selection. To avoid misleading signatures of selection, it is necessary to show that a sweep has an effect on the selected trait before it can be considered adaptive. Here, we confirm candidate selective-sweeps on a genome-wide scale in one of the longest, on-going bi-directional selection experiments in vertebrates, the Virginia high and low body-weight selected chicken lines. The candidate selective-sweeps represent standing genetic variants originating from the common base-population. Using a deep-intercross between the selected lines, 16 of 99 evaluated regions were confirmed to contain adaptive selective-sweeps based on their association with the selected trait, 56-day body-weight. Although individual additive effects were small, the fixation for alternative alleles in the high and low body-weight lines across these loci contributed at least 40% of the divergence between them and about half of the additive genetic variance present within and between the lines after 40 generations of selection. The genetic variance contributed by the sweeps corresponds to about 85% of the additive genetic variance of the base-population, illustrating that these loci were major contributors to the realised selection-response. Thus, the gradual, continued, long- term selection response in the Virginia lines was likely due to a considerable standing genetic variation in a highly polygenic genetic architecture in the base-population with contributions from a steady release of selectable genetic variation from new mutations and epistasis throughout the course of selection.

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