The effect of index selection on allele frequencies and future genetic gains when traits are correlated

The application of the selection index in the case of an additive two-trait model in which the genetic effect on each trait is determined by a finite number of loci is examined. Simulation results indicate that the direction of change in the frequency of favourable alleles is not necessarily in the positive direction at all loci when index selection is used as the basis for truncation selection. When the genetic correlation was positive (or favourable with respect to the economic weights), there was little difference (<5%) in genetic gain over 20 generations and no difference in the direction of change in allele frequencies or genetic correlation whether or not updated values for the genetic (co)variances were used in constructing the selection index. However, when the genetic correlation was negative or unfavourable, the effect of using genetic parameters which were not updated had unexpected effects on the allele frequencies and genetic correlation and reduced the genetic gain by a greater amount (< 12%).     

Including Dominance Effects in the Genomic BLUP Method for Genomic Evaluation

We evaluated the performance of GBLUP including dominance genetic effect (GBLUP-D) by estimating variances and predicting genetic merits in a computer simulation and 2 actual traits (T4 and T5) in pigs. In simulation data, GBLUP-D explained more than 50% of dominance genetic variance. Moreover, GBLUP-D yielded estimated total genetic effects over 1.2% more accurate than those yielded by GBLUP. In particular, when the dominance genetic variance was large, the accuracy could be substantially improved by increasing the number of markers. The dominance genetic variances in T4 and T5 accounted for 9.6% and 6.3% of the phenotypic variances, respectively. Estimates of such small dominance genetic variances contributed little to the improvement of the accuracies of estimated total genetic effects. In both simulation and pig data, there were nearly no differences in the estimates of additive genetic effects or their variance between GBLUP-D and GBLUP. Therefore, we conclude GBLUP-D is a feasible approach to improve genetic performance in crossbred populations with large dominance genetic variation and identify mating systems with good combining ability.     

A computer simulation evaluation of the role of mutations in finite populations on the response to directional selection: The generations required to attain maximum genetic variance

Summary The role of mutations in finite populations on response to artificial selection was investigated by a computer simulation model designed to mimic the biological model of pupal weight of Tribolium. Given the model, the results showed that with selection about 25–55 generations were needed for genetic variances to reach a maximum value depending on population size, selection intensity, and gene number. When effective population size was larger than 40 or the intensity of selection was high (less than 50% selected), selection had a dramatic effect in reducing the time to approach the maximum point of genetic variance. Furthermore, the genetic variance after that point often declined as a function of selection instead of remaining at a steady state in the subsequent generations.     

Selection of sires to reduce sampling variance in the estimates of heritability by half-sib correlation

Summary Standard methods to estimate heritability by half-sib correlation are biased if selection has operated in the parental generation. In this paper a simple method to correct for selection of animals used as sires is described. By selection of both the top and the bottom ranking sires, the sampling variances of the corrected estimates of heritability are substantially reduced. Algebraic expressions to predict the sampling variance of the estimates of heritability using selected sires are derived. Theoretical predictions were checked by Monte-Carlo simulation. The results may have application in the design of experiments to estimate heritabilities.     

Efficiency of direct selection on quantitative trait loci for a two-trait breeding objective

Selection on known loci affecting quantitative traits (DSQ) was compared to phenotypic selection index for a single and a two-trait selection objective. Two situations were simulated; a single known quantitative locus, and ten identified loci accounting for all the additive genetic variance. Selection efficiency of DSQ relative to traitbased selection was higher for two-trait selection, than was selection on a single trait with the same heritability. The advantage of DSQ was greater when the traits were negatively correlated. Relative selection efficiency (RSE) for a single locus responsible for 0.1 of the genetic variance was 1.11 with heritabilities of 0.45 and 0.2 and zero genetic and phenotypic correlations between the traits. RSE of DSQ for ten known loci was 1.5 to 1.8 in the first 3 generations of selection, but declined in each subsequent generation. With DSQ most loci reached fixation after 7 generations. Response to trait-based selection continued through generation 15 and approached the response obtained with DSQ after 10 generations. The cumulative genetic response after 10 generations of DSQ was only 93% to 97% of the economically optimum genotype because the less favorable allele reached fixation for some loci, generally those with effects in opposite directions on the two traits.     

Directional Selection and Variation in Finite Populations

Predictions are made of the equilibrium genetic variances and responses in a metric trait under the joint effects of directional selection, mutation and linkage in a finite population. The "infinitesimal model" is analyzed as the limiting case of many mutants of very small effect, otherwise Monte Carlo simulation is used. If the effects of mutant genes on the trait are symmetrically distributed and they are unlinked, the variance of mutant effects is not an important parameter. If the distribution is skewed, unless effects or the population size is small, the proportion of mutants that have increasing effect is the critical parameter. With linkage the distribution of genotypic values in the population becomes skewed downward and the equilibrium genetic variance and response are smaller as disequilibrium becomes important. Linkage effects are greater when the mutational variance is contributed by many genes of small effect than few of large effect, and are greater when the majority of mutants increase rather than decrease the trait because genes that are of large effect or are deleterious do not segregate for long. The most likely conditions for "Muller's ratchet" are investigated.     

Estimates of direct and maternal covariance functions for growth of Australian beef calves from birth to weaning

Records for birth and subsequent, monthly weights until weaning on beef calves of two breeds in a selection experiment were analysed fitting random regression models. Independent variables were orthogonal (Legendre) polynomials of age at weighing in days. Orders of polynomial fit up to 6 were considered. Analyses were carried out fitting sets of random regression coefficients due to animals'' direct and maternal, additive genetic and permanent environmental effects, with changes in variances due to temporary environmental effects modelled through a variance function, estimating up to 67 parameters. Results identified similar patterns of variation for both breeds, with maternal effects considerably more important in purebred Polled Herefords than a four-breed synthetic, the so-called Wokalups. Conversely, repeatabilities were higher for the latter. For both breeds, heritabilities decreased after birth, being lowest when maternal effects were most important around 100 days of age. Estimates at birth and weaning were consistent with previous, univariate results.     

Genetic correlation and response to selection in simulated populations

Summary Effects of truncation selection of a primary trait upon genetic correlation with a secondary trait were examined over 30 generations in genetic populations simulated by computer. Populations were 24 males and 24 females mated randomly with replacement; number of offspring was determined by intensity of selection. Each trait was controlled by 48 loci segregating independently, effects were equal at every locus, and gene frequency was arbitrarily set at 0.5 at each locus in the initial generation. All combinations of three genetic correlations, three intensities of selection, and three environmental variances were simulated. Gene action was additive. Genetic correlation was set by number of loci which affected both traits and was measured each generation as the product-moment correlation of genotypic values and estimated by two methods of combining phenotypic covariances between parent and offspring.Genetic correlations in each offspring generation remained consistently near initial correlations for all environmental variances when fraction of offspring saved as parents was as large as one-half. When the fraction of offspring saved was as small as one-fifth, genetic correlations decreased but most rapidly with heritability high and after the 15th generation of selection. Truncation selection caused genetic correlation to decrease in those offspring selected to become parents of the next generation. Amount of reduction depended on heritability of the selected trait rather than on degree of truncation selection. Estimates of genetic correlation from phenotypic covariances between parent and offspring fluctuated markedly from real correlations in the small populations simulated.Michigan Agricultural Experiment Station Journal Article 4836. Part of North Central Regional Project NC-2.     

Selection for environmental variation: a statistical analysis and power calculations to detect response

Data from uterine capacity in rabbits (litter size) were analyzed to determine whether the environmental variance was partly genetically determined. The fit of a classical homogeneous variance mixed linear (HOM) model and that of a genetically structured heterogeneous variance mixed linear (HET) model were compared. Various methods to assess the quality of fit favor the HET model. The posterior mean (95% posterior interval) of the additive genetic variance affecting the environmental variance was 0.16 (0.10; 0.25) and the corresponding number for the coefficient of correlation between genes affecting mean and variance was -0.74 (-0.90;-0.52). It is argued that stronger support for the HET model than that derived from statistical analysis of data would be provided by a successful selection experiment designed to modify the environmental variance. A simple selection criterion is suggested (average squared deviation from the mean of repeated records within individuals) and its predicted response and variance under the HET model are derived. This is used to determine the appropriate size and length of a selection experiment designed to change the environmental variance. Results from the analytical expressions are compared with those obtained using simulation. There is good agreement provided selection intensity is not intense.     

Joint effect of selection, linkage and partial inbreeding on additive genetic variance in an infinite population

Under the inifinitesimal model of gene effects, selection reduces the additive genetic variance by inducing negative linkage disequilibrium among selected genes. If the selected genes are linked, the decay of linkage disequilibrium is delayed, and the reduction of additive genetic variance is enhanced. Inbreeding in an infinite population also alters the additive genetic variance through the generation of positive association among genes within a locus. In the present study, the joint effect of selection, linkage and partial inbreeding (partial selfing or partial full-sib mating) on the additive genetic variance was modeled. The recurrence relations of the additive genetic variance between successive generations and the prediction equation of the asymptotic additive genetic variance were derived. Numerical computation showed that although partially inbred populations initially maintain larger genetic variances, the accumulated effect of selection overrides the effect of inbreeding. Stochastic simulation was carried out to check the precision of prediction, showing that the obtained equations give a satisfactory prediction during initial generations. However, the predicted values always overestimate the simulated values, especially in later generations. Based on these results, possible extensions and perspectives of the assumed model were discussed.     

Estimates of genetic variance in an F2 maize population

Maize (Zea mays L.) breeders have used several genetic-statistical models to study the inheritance of quantitative traits. These models provide information on the importance of additive, dominance, and epistatic genetic variance for a quantitative trait. Estimates of genetic variances are useful in understanding heterosis and determining the response to selection. The objectives of this study were to estimate additive and dominance genetic variances and the average level of dominance for an F2 population derived from the B73 x Mo17 hybrid and use weighted least squares to determine the importance of digenic epistatic variances relative to additive and dominance variances. Genetic variances were estimated using Design III and weighted least squares analyses. Both analyses determined that dominance variance was more important than additive variance for grain yield. For other traits, additive genetic variance was more important than dominance variance. The average level of dominance suggests either overdominant gene effects were present for grain yield or pseudo-overdominance because of linkage disequilibrium in the F2 population. Epistatic variances generally were not significantly different from zero and therefore were relatively less important than additive and dominance variances. For several traits estimates of additive by additive epistatic variance decreased estimates of additive genetic variance, but generally the decrease in additive genetic variance was not significant.     

Selection theory for selfed progenies

Summary The purpose of this article was to extend the model used to predict selection response with selfed progeny from 2 alleles per locus to a model which is general for number and frequency of alleles at loci. To accomplish this, 4 areas had to be dealt with: 1) simplification of the derivation and calculation of the condensed coefficients of identity; 2) presentation of the genetic variances expressed among and within selfed progenies as linear function of 5 population parameters; 3) presentation of selection response equations for selfed progenies as functions of these 5 population parameters; and 4) to identify a set of progeny to evaluate, such that one might be able to estimate these 5 population parameters.The five population parameters used in predicting gains were the additive genetic variance, the dominance variance, the covariance of additive and homozygous dominance deviations, the variance of the homozygous dominance deviations and a squared inbreeding depression term.Contribution from the Missouri Agricultural Experiment Station. Journal Series No. 9971     

The mutation matrix and the evolution of evolvability

Evolvability is a key characteristic of any evolving system, and the concept of evolvability serves as a unifying theme in a wide range of disciplines related to evolutionary theory. The field of quantitative genetics provides a framework for the exploration of evolvability with the promise to produce insights of global importance. With respect to the quantitative genetics of biological systems, the parameters most relevant to evolvability are the G-matrix, which describes the standing additive genetic variances and covariances for a suite of traits, and the M-matrix, which describes the effects of new mutations on genetic variances and covariances. A population's immediate response to selection is governed by the G-matrix. However, evolvability is also concerned with the ability of mutational processes to produce adaptive variants, and consequently the M-matrix is a crucial quantitative genetic parameter. Here, we explore the evolution of evolvability by using analytical theory and simulation-based models to examine the evolution of the mutational correlation, r(mu), the key parameter determining the nature of genetic constraints imposed by M. The model uses a diploid, sexually reproducing population of finite size experiencing stabilizing selection on a two-trait phenotype. We assume that the mutational correlation is a third quantitative trait determined by multiple additive loci. An individual's value of the mutational correlation trait determines the correlation between pleiotropic effects of new alleles when they arise in that individual. Our results show that the mutational correlation, despite the fact that it is not involved directly in the specification of an individual's fitness, does evolve in response to selection on the bivariate phenotype. The mutational variance exhibits a weak tendency to evolve to produce alignment of the M-matrix with the adaptive landscape, but is prone to erratic fluctuations as a consequence of genetic drift. The interpretation of this result is that the evolvability of the population is capable of a response to selection, and whether this response results in an increase or decrease in evolvability depends on the way in which the bivariate phenotypic optimum is expected to move. Interestingly, both analytical and simulation results show that the mutational correlation experiences disruptive selection, with local fitness maxima at -1 and +1. Genetic drift counteracts the tendency for the mutational correlation to persist at these extreme values, however. Our results also show that an evolving M-matrix tends to increase stability of the G-matrix under most circumstances. Previous studies of G-matrix stability, which assume nonevolving M-matrices, consequently may overestimate the level of instability of G relative to what might be expected in natural systems. Overall, our results indicate that evolvability can evolve in natural systems in a way that tends to result in alignment of the G-matrix, the M-matrix, and the adaptive landscape, and that such evolution tends to stabilize the G-matrix over evolutionary time.     

On Treating the Chromosome as the Unit of Selection

A simple method is presented for approximating the behavior of a multiple genetic system under the action of selection and linkage. The effects of genetic drift and mutation are left out. It is found that the results are close to those obtained from a computer simulation of the same problem by Franklin and Lewontin (1970). It is possible to describe the system in terms of a correlation length on the chromosome which measures the degree to which the different parts are bound by linkage. There is also a brief discussion about the higher order correlation coefficients as a measure of the interaction effects.     

Estimating variance components and heritabilities in the wild: a case study using the ‘animal model’ approach

Using a genealogy containing over 1800 dams and nearly 400 sires (estimated by genetic paternity techniques), combined with maximum likelihood procedures and an ‘animal model’, we have estimated the heritabilities, genetic correlations and variance components of three morphometric traits in the Soay sheep (Ovis aries) on St Kilda, Scotland. This approach allows heritabilities to be estimated in natural populations that violate the assumptions of offspring–parent regression methods. Maternal (or paternal) effects can also be estimated under natural conditions. We demonstrate that all the traits, body weight, hind leg length and incisor arcade breadth, have low but significant heritabilities. Body weight, the trait that experiences the strongest selection, had the lowest heritability but the highest additive genetic coefficient of variation. An evolutionary response to selection is predicted. When maternal effects were not taken into consideration heritabilities were over‐estimated, although this effect was only significant in female offspring.     

Genetic drift and polygenic inheritance

The interaction of random gene drift and selection was studied by computer simulation for two quantitative traits, which were considered to approximate stature and skin color differences in human populations. The expected effects of gene drift, fixation of alleles and reduction of genotypic and phenotypic variances, were found in the simulation. Stabilizing selection, which seems to be the type of selection operating on these traits, was found to increase the effects of gene drift. Since there seems to be no evidence of reduction in phenotypic and presumably genotypic variability in small human populations, the applicability of these simple genetic models to human traits raises problems for which several possible solutions exist.     

A reappraisal of Bateman's classic study of intrasexual selection

Bateman's (1948) study showing greater variances in number of mates and reproductive success in male than female Drosophila melanogaster is a foundational paper in sexual selection. Here we show for the first time that his methods had flaws, including the elimination of genetic variance, sampling biases, miscalculations of fitness variances, statistical pseudo-replication, and selective presentation of data. We conclude that Bateman's results are unreliable, his conclusions are questionable, and his observed variances are similar to those expected under random mating. Despite our analysis, we do not intend this article as a criticism of Bateman; he accomplished his work without modern computational tools, and his approach was groundbreaking emphasizing the significance of fitness variance for sexual selection. However, this reanalysis has implications for what counts as evidence for sexual selection and we believe that our concerns should be of interest to contemporary students of sexual selection. We call for repetitions of Bateman's study using modern statistical and molecular methods.     

GENETIC COMPONENTS OF VARIATION IN ENERGY STORAGE IN DROSOPHILA MELANOGASTER

One approach to examining the underlying genetic structure of the variation in a continuous phenotype is to measure a set of possibly mechanistically related traits and determine the quantitative genetic aspects of their transmission. In this study the quantities of stored triacylglycerol and glycogen were measured along with the activities of 10 enzymes in related metabolic pathways in a set of 1,157 half-sib families of Drosophila melanogaster. The families were structured with each male being mated to 10 females and two offspring were scored from each female. Parents and offspring were scored for the phenotypes, and the components of variance (additive, dominance, and environmental) were estimated in three ways, including analysis of variance on offspring alone, parent-offspring regression, and maximum likelihood methods. While there were differences among the estimates made by the three methods, a consistent result was that substantial additive genetic variation was detected for all the traits. Consistent with models for the quantitative genetics of enzyme kinetics, the genetic variances of global properties were largely additive. Previous studies with extracted chromosome lines had indicated several significant genetic correlations among these characters, and much of the correlation was attributable to additive effects. The results imply that there is substantial opportunity for natural or artificial selection to act on quantities of stored lipid and carbohydrate, and that the response to selection is likely to be in part mediated by changes in the kinetics of the enzymes targeted in this study.     

Selection,structure and the heritability of behaviour

Characters which are closely linked to fitness often have low heritabilities (V_A/V_P). Low heritabilities could be because of low additive genetic variation (V_A), that had been depleted by directional selection. Alternatively, low heritabilities may be caused by large residual variation (V_R=V_P – V_A) compounded at a disproportionately higher rate than V_A across integrated characters. Both hypotheses assume that each component of quantitative variation has an independent effect on heritability. However, V_A and V_R may also covary, in which case differences in heritability cannot be fully explained by the independent effects of elimination‐selection or compounded residual variation. We compared the central tendency of published behavioural heritabilities (mean=0.31, median=0.23) with morphological and life history data collected by 26 ). Average behavioural heritability was not significantly different from average life history heritability, but both were smaller than average morphological heritability. We cross‐classified behavioural traits to test whether variation in heritability was related to selection (dominance, domestic/wild) or variance compounding (integration level). There was a significant three‐way interaction between indices of selection and variance compounding, related to the absence of either effect at the highest integration level. At lower integration levels, high dominance variance indicated effects of selection. It was also indicated by the low CV_A of domestic species. At the same time CV_R increased disproportionately faster than CV_A across integration levels, demonstrating variance compounding. However, neither CV_R nor CV_A had a predominant effect on heritability. The partial regression coefficients of CV_R and CV_A on heritability were similar and a path analysis indicated that their (positive) correlation was also necessary to explain variation in heritability. These results suggest that relationships between additive genetic and residual components of quantitative genetic variation can constrain their independent direct effects on behavioural heritability.     

The Effects of Disruptive and Stabilizing Selection on Body Size in DROSOPHILA MELANOGASTER. II. Analysis of Responses in the Thorax Selection Lines

An analysis was made of changes in mean and variance in some thorax selection lines. The decrease of mean thorax length in the stabilizing selection lines (S) was a consequence of a directional selection component, caused by the skewness of the frequency distributions. The slight or temporary increase of the phenotypic variance and the large increase of the mean value in the disruptive selection lines with random mating (D(R)) could be attributed to differences in reproduction between small and large flies (egg production and mating success). Phenotypic variability was high in two disruptive selection lines with compulsory mating of opposite extremes (D(-)). The mechanism of the change in variability was different in these replicate lines. In D(-)-1 the change was obtained by an increase of the environmental and the nonadditive genetic components of the variance. In D(-)-2 almost exclusively an increase of additive genetic variance occurred.