scholarly journals Recombination load associated with selection for increased recombination

1996 ◽  
Vol 67 (1) ◽  
pp. 27-41 ◽  
Author(s):  
B. Charlesworth ◽  
N. H. Barton
Keyword(s):  
Transposable Elements ◽  
Direct Effect ◽  
Quantitative Traits ◽  
Genetic Variance ◽  
Genetic Recombination ◽  
Additive Genetic Variance ◽  
Directional Selection ◽  
Additive Variance ◽  
Linkage Disequilibria ◽  
Selection For

SummaryExperiments on Drosophila suggest that genetic recombination may result in lowered fitness of progeny (a ‘recombination load’). This has been interpreted as evidence either for a direct effect of recombination on fitness, or for the maintenance of linkage disequilibria by epistatic selection. Here we show that such a recombination load is to be expected even if selection favours increased genetic recombination. This is because of the fact that, although a modifier may suffer an immediate loss of fitness if it increases recombination, it eventually becomes associated with a higher additive genetic variance in fitness, which allows a faster response to directionselection. This argument applies to mutation-selection balance with synergistic epistasis, directional selection on quantitative traits, and ectopic exchange among transposable elements. Further experiments are needed to determine whether the selection against recombination due to trie immediate load is outweighed by the increased additive variance in fitness produced by recombination.

scholarly journals Interactions of selection, linkage and drift in the dynamics of polygenic characters

1996 ◽  
Vol 67 (1) ◽  
pp. 77-87 ◽  
Author(s):  
Frédéric Hospital ◽  
Claude Chevalet
Keyword(s):  
Genetic Variability ◽  
First Generation ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Point Of View ◽  
Quantitative Character ◽  
Recombination Rates ◽  
Additive Variance ◽  
Infinite Population ◽  
Linkage Disequilibria

SummaryWe study the dynamics under directional truncation selection of the genetic variability of a quantitative character controlled by a finite number of possibly linked loci with additive effects. After the first generation of selection, the build-up of linkage disequilibria (Bulmer effect) is analytically demonstrated from a genetical point of view in an infinite population. In the following generations, the dynamics of the system in a finite population are predicted using analytic recurrences under a multi-normal approximation, and computer simulations. The effects of recombination on the dynamics of linkage disequilibria induced by selection and drift, and the consequences for the additive genetic variance are then analysed and discussed from the simulation results. Compared to the rapid exploitation of genetic variability promoted by high recombination rates, low recombination rates promote an early storage of genetic variability in repulsion associations of alleles and a possible late release of genetic variance in the population, so that the variability of the character may be maintained over a longer period of time. In some cases, favourable recombination events in tightly linked systems induce an increase of the additive variance of the character, which may explain some results observed in long-term selection experiments. Our results emphasize that the joint effects of selection, linkage and drift must notbe neglected in theoretical quantitative genetics, and require further investigation.

Genetic analysis in the pasture grass Setaria sphacelata. II. Chemical composition, digestibility and correlations with yield

1981 ◽  
Vol 32 (2) ◽  
pp. 311 ◽  
Author(s):  
RA Bray ◽  
JB Hacker
Keyword(s):  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Seasonal Effects ◽  
In Vitro Digestibility ◽  
High Concentration ◽  
Element Analysis ◽  
Additive Variance ◽  
Setaria Sphacelata ◽  
Calcium And Magnesium ◽  
Selection For

The progeny of a 7 x 7 diallel cross between plants randomly selected from a segregating tetraploid population (Setaria sphacelata var. sericea and var. splendida) was studied at Lawes, south-east Queensland, over a two year period, together with the parent clones. Plants were harvested at 6-week intervals (9-10 weeks in winter), dry weight was recorded, and family rows were bulked for analysis of in vitro digestibility (DMD) and for multi-element analysis. Concentrations of nitrogen, phosphorus, magnesium and calcium tended to be low in summer, and potassium concentration decreased during the two years of the experiment. In contrast magnesium, calcium and sodium increased. Genetic variance for digestibility was detected for only two of 14 harvests. Additive genetic variance was statistically significant, and generally consistent over harvests for nitrogen, potassium, sodium, calcium and magnesium. Family by season and family by year interactions were of a low order, showing that the expression of genetic variance was not strongly influenced by seasonal effects. Additive variance effects were erratic for phosphorus, sulfur, manganese, copper, zinc, silicon, iron, aluminium and boron, and selection for higher or lower concentrations of these elements would be unlikely to be successful. Nitrogen, potassium, calcium, magnesium and sodium were negatively and consistently correlated with dry matter yield. Over all harvests r was - 0.64, - 0.16, - 0.77, - 0.30 and - 0.44 respectively. With the possible exception of potassium, selection for higher concentrations of any of these minerals would result in a decrease in yield. Sodium was negatively correlated genetically with nitrogen, potassium, calcium and magnesium on an individual harvest or a season basis. For the total of all 15 harvests values for rg were -0.76, -0.88, -0.21 and -0.73 respectively. Nitrogen, potassium, calcium and magnesium were consistently positively correlated (for all harvests rg - 0.69 for all combinations), and selection for high concentration of any of these elements would result in an increase in the others, but a decrease in sodium. Significant genetic variation was detected for the mineral ratios K:(Ca + Mg) and calcium: phosphorus. However, these ratios are not known to adversely affect production in setaria pastures, and manipulation by breeding is not warranted. These examples show that there is the potential for breeding for mineral ratios in tropical forages.

scholarly journals SELECTION FOR BLOOD PRESSURE LEVELS IN MICE

Genetics ◽  
1974 ◽  
Vol 76 (3) ◽  
pp. 537-549
Author(s):  
Gunther Schlager
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Population Bottleneck ◽  
Control Line ◽  
Selected Lines ◽  
High Line ◽  
Selection For ◽  
Random Control

ABSTRACT Response to two-way selection for systolic blood pressure was immediate and continuous for about eight generations. In the twelfth generation, the High males differed from the Low males by 38 mmHG; the females differed by 39 mmHg. There was little overlap between the two lines and they were statistically significant from each other and from the Random control line. There appeared to be no more additive genetic variance in the eleventh and twelfth generations. Causes for the cessation of response are explored. This is probably due to a combination of natural selection acting to reduce litter sizes in the Low line, a higher incidence of sudden deaths in the High line, and loss of favorable alleles as both selection lines went through a population bottleneck in the ninth generation.—In the eleventh generation, the selected lines were used to produce F1, F2, and backcross generations. A genetic analysis yielded significant additive and dominance components in the inheritance of systolic blood pressure.

scholarly journals Evolution of the additive genetic variance–covariance matrix under continuous directional selection on a complex behavioural phenotype

2015 ◽  
Vol 282 (1819) ◽  
pp. 20151119 ◽  
Author(s):  
Vincent Careau ◽  
Matthew E. Wolak ◽  
Patrick A. Carter ◽  
Theodore Garland
Keyword(s):  
Covariance Matrix ◽  
Adaptive Response ◽  
Genetic Variance ◽  
Environmental Changes ◽  
Wheel Running ◽  
Additive Genetic Variance ◽  
Phenotypic Selection ◽  
Directional Selection ◽  
Genetic Covariance ◽  
Variance Covariance Matrix

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance–covariance matrix ( G ). Yet knowledge of G in a population experiencing new or altered selection is not sufficient to predict selection response because G itself evolves in ways that are poorly understood. We experimentally evaluated changes in G when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset ( n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change.

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 Directional selection and the evolution of sex and recombination

1993 ◽  
Vol 61 (3) ◽  
pp. 205-224 ◽  
Author(s):  
Brian Charlesworth
Keyword(s):  
Selection Pressure ◽  
Genetic Variance ◽  
Genetic Recombination ◽  
Directional Selection ◽  
Selection Function ◽  
Light Conditions ◽  
Evolution Of Sex ◽  
Mean Fitness ◽  
Varying Environment ◽  
Additive Genes

SummaryModels of the evolutionary advantages of sex and genetic recombination due to directional selection on a quantitative trait are analysed. The models assume that the trait is controlled by many additive genes. A nor-optimal selection function is used, in which the optimum either moves steadily in one direction, follows an autocorrelated linear Markov process or a random walk, or varies cyclically. The consequences for population mean fitness of a reduction in genetic variance, due to a shift from sexual to asexual reproduction are examined. It is shown that a large reduction in mean fitness can result from such a shift in the case of a steadily moving optimum, under light conditions. The conditions are much more stringent with a cyclical or randomly varying environment, especially if the autocorrelation for a random environment is small. The conditions for spread of a rare modifier affecting the rate of genetic recombination are also examined, and the strength of selection on such a modifier determined. Again, the case of a steadily moving optimum is most favourable for the evolution of increased recombination. The selection pressure on a recombination modifier when a trait is subject to strong truncation selection is calculated, and shown to be large enough to account for observed increases in recombination associated with artificial selection. Theoretical and empirical evidence relevant to evaluating the importance of this model for the evolution of sex and recombination is discussed.

scholarly journals A general model for the evolution of recombination

1995 ◽  
Vol 65 (2) ◽  
pp. 123-144 ◽  
Author(s):  
N. H. Barton
Keyword(s):  
Experimental Test ◽  
General Model ◽  
General Relation ◽  
Directional Selection ◽  
Average Increase ◽  
General Representation ◽  
Additive Variance ◽  
Linkage Disequilibria ◽  
Exact Calculations ◽  
Negative Epistasis

SummaryA general representation of multilocus selection is extended to allow recombination to depend on genotype. The equations simplify if modifier alleles have small effects on recombination. The evolution of such modifiers only depends on how they alter recombination between the selected loci, and does not involve dominance in modifier effects. The net selection on modifiers can be found explicitly if epistasis is weak relative to recombination. This analysis shows that recombination can be favoured in two ways: because it impedes the response to epistasis which fluctuates in sign, or because it facilitates the response to directional selection. The first mechanism is implausible, because epistasis must change sign over periods of a few generations: faster or slower fluctuations favour reduced recombination. The second mechanism requires weak negative epistasis between favourable alleles, which may either be increasing, or held in check by mutation. The selection (si) on recombination modifiers depends on the reduction in additive variance of log (fitness) due to linkage disequilibria (υ1 < 0), and on non-additive variance in log (fitness) (V′2, V′3,.. epistasis between 2, 3.. loci). For unlinked loci and pairwise epistasis, si = − (υ1 + 4V2/3)δr, where δr is the average increase in recombination caused by the modifier. The approximations are checked against exact calculations for three loci, and against Charlesworth's analyses of mutation/selection balance (1990), and directional selection (1993). The analysis demonstrates a general relation between selection on recombination and observable components of fitness variation, which is open to experimental test.

scholarly journals The limits to artificial selection for body weight in the mouse: IV. Sources of new genetic variance—irradiation and outcrossing

1967 ◽  
Vol 9 (1) ◽  
pp. 87-98 ◽  
Author(s):  
R. C. Roberts
Keyword(s):  
Body Weight ◽  
Artificial Selection ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Negative Results ◽  
Selection For ◽  
The Cross

1. Two methods are examined of introducing new genetic variance into a line of mice selected for high 6-week weight which, at its limit, displayed no additive genetic variance.2. The first method—irradiation—gave largely negative results. Any further gain under selection that was achieved could not be clearly distinguished from a possible environmental trend.3. The second method—outcrossing to an unselected strain and then selecting from the cross—resulted in a clear gain over the original limit, but nine generations were required even to recover the original limit.4. Various methods of transcending selection limits are evaluated in terms of their application to livestock improvement.

scholarly journals INTERACTION BETWEEN NATURAL SELECTION FOR HETEROZYGOTES AND DIRECTIONAL SELECTION

Genetics ◽  
1974 ◽  
Vol 76 (1) ◽  
pp. 163-168
Author(s):  
Margrith Wehrli Verghese
Keyword(s):  
Natural Selection ◽  
First Generation ◽  
Genetic Variance ◽  
Selection Response ◽  
Directional Selection ◽  
Simple Function ◽  
Small Populations ◽  
Gene Frequencies ◽  
Selection For

ABSTRACT When directional selection for an additively inherited trait is opposed by natural selection favoring heterozygous genotypes a selection plateau may be reached where genetic variance is present. The amount of response when this plateau is reached is a simple function of the selection response in the first generation and the intensity of natural selection. When selection is practiced in small populations, the sizes of the initial equilibrium gene frequencies are at least as important as the intensity of natural selection in determining the probability of fixing desirable alleles.

scholarly journals Learning from your mistakes: a novel method to predict the response to directional selection

2021 ◽  
Author(s):  
Lisandro Milocco ◽  
Isaac Salazar-Ciudad
Keyword(s):  
Evolutionary Biology ◽  
Genetic Variance ◽  
Learning Algorithm ◽  
Additive Genetic Variance ◽  
Fruit Fly ◽  
Directional Selection ◽  
Prediction Errors ◽  
Evolution Experiment ◽  
Novel Method ◽  
The Mean

Predicting how populations respond to selection is a key goal of evolutionary biology. The field of quantitative genetics provides predictions for the response to directional selection through the breeder’s equation. However, differences between the observed responses to selection and those predicted by the breeder’s equation occur. The sources of these errors include omission of traits under selection, inaccurate estimates of genetic variance, and nonlinearities in the relationship between genetic and phenotypic variation. A key insight from previous research is that the expected value of these prediction errors is often not zero, in which case the predictions are systematically biased. Here, we propose that this prediction bias, rather than being a nuisance, can be used to improve the predictions. We use this to develop a novel method to predict the response to selection, which is built on three key innovations. First, the method predicts change as the breeder’s equation plus a bias term. Second, the method combines information from the breeder’s equation and from the record of past changes in the mean, to estimate the bias and predict change using a Kalman filter. Third, the parameters of the filter are fitted in each generation using a machine-learning algorithm on the record of past changes. We apply the method to data of an artificial selection experiment of the wing of the fruit fly, as well as to an in silico evolution experiment for teeth. We find that the method outperforms the breeder’s equation, and notably provides good predictions even when traits under selection are omitted from the analysis and when additive genetic variance is estimated inaccurately. The proposed method is easy to apply since it only requires recording the mean of the traits over past generations.

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