MULTILEVEL SELECTION WITH KIN AND NON‐KIN GROUPS,EXPERIMENTAL RESULTS WITH JAPANESE QUAIL (COTURNIX JAPONICA)

An experiment was conducted comparing multilevel selection in Japanese quail for 43 days weight and survival with birds housed in either kin (K) or random (R) groups. Multilevel selection significantly reduced mortality (6.6% K vs. 8.5% R) and increased weight (1.30 g/MG K vs. 0.13 g/MG R) resulting in response an order of magnitude greater with Kin than Random. Thus, multilevel selection was effective in reducing detrimental social interactions, which contributed to improved weight gain. The observed rates of response did not differ significantly from expected, demonstrating that current theory is adequate to explain multilevel selection response. Based on estimated genetic parameters, group selection would always be superior to any other combination of multilevel selection. Further, near optimal results could be attained using multilevel selection if 20% of the weight was on the group component regardless of group composition. Thus, in nature the conditions for multilevel selection to be effective in bringing about social change maybe common. In terms of a sustainability of breeding programs, multilevel selection is easy to implement and is expected to give near optimal responses with reduced rates of inbreeding as compared to group selection, the only requirement is that animals be housed in kin groups.     

A method to construct confidence interval for expected response to multi-trait selection

Summary Confidence intervals are constructed for the expected responses to three types of multi-trait selection. The influence of numbers of replicates and genotypes used in a progeny test experiment on the precision of response of multi-trait selection is discussed based on the structure of the established intervals. Special attention is paid to the characteristics of the intervals constructed for the conventional least square selection indices.     

Asymmetrical correlated responses to selection under an infinitesimal genetic model

Summary Asymmetry in correlated responses to selection is expected when more than one cycle of selection is practised due to changes in genetic parameters produced by selection. In large populations, under the infinitesimal model these changes are due to linkage disequilibrium generated by selection and not to gene frequency changes. This study examines the conditions under which asymmetrical correlated responses are to be expected when an infinitesimal model is considered. Asymmetrical correlated responses in two traits in respect to which trait is selected are expected if the two traits have different heritabilities. Predicted asymmetry increases with the absolute value of the genetic correlation between the two traits, the difference between the two heritabilities, the intensity of selection and the number of generations of selection. Linkage disequilibrium generated by selection should be taken into account in explaining asymmetrical correlated responses observed in selection experiments.     

Selection in a fluctuating environment leads to decreased genetic variation and facilitates the evolution of phenotypic plasticity

Changes in the environment are expected to induce changes in the quantitative genetic variation, which influences the ability of a population to adapt to environmental change. Furthermore, environmental changes are not constant in time, but fluctuate. Here, we investigate the effect of rapid, continuous and/or fluctuating temperature changes in the seed beetle Callosobruchus maculatus, using an evolution experiment followed by a split-brood experiment. In line with expectations, individuals responded in a plastic way and had an overall higher potential to respond to selection after a rapid change in the environment. After selection in an environment with increasing temperature, plasticity remained unchanged (or decreased) and environmental variation decreased, especially when fluctuations were added; these results were unexpected. As expected, the genetic variation decreased after fluctuating selection. Our results suggest that fluctuations in the environment have major impact on the response of a population to environmental change; in a highly variable environment with low predictability, a plastic response might not be beneficial and the response is genetically and environmentally canalized resulting in a low potential to respond to selection and low environmental sensitivity. Interestingly, we found greater variation for phenotypic plasticity after selection, suggesting that the potential for plasticity to evolve is facilitated after exposure to environmental fluctuations. Our study highlights that environmental fluctuations should be considered when investigating the response of a population to environmental change.     

The uniqueness of protein sequences: molecular territoriality

The number of tripeptides which do not occur and which occur only a small number of times in the existing data bank of protein sequences is much larger than that expected on the basis of random selection (from Monte Carlo analyses). Forty tripeptides are not found in the data bank of 289 500 amino acids while the value expected on the basis of random selection is 8.0 +/- 3.1. Seventy-one tripeptides occur only once with an expected value of 37.1 +/- 6.1. These results suggest that some peptides not found in certain species are reserved for use only in other species. The proposal is made that small peptides serve as species specific markers and function as signals in the recognition process for activation of the immune response.     

Patterns of selection and polymorphism of innate immunity genes in bumblebees (Hymenoptera: Apidae)

In response to on-going biodiversity loss, conservation genetics has established itself as an important branch of biology. Historically concentrating on assessing stochastic processes using neutral loci, there has been a recent surge of interest in understanding and quantifying variation at loci underlying ecologically important traits. To this end, patterns of selection and polymorphism at these loci must be characterized. Loci underlying immunity make good candidates in this context: they are expected to be important for population persistence and may exhibit diversifying or divergent selection. Predictions regarding the pattern of selection expected at immune system loci have been based on their interactions with pathogens, however, published studies report mixed results as to whether these are borne out or not. Here, polymorphism and selection is examined for three innate immune system loci in bumblebees: a peptidoglycan recognition protein, a putative alpha-macroglobulin, and scavenger receptor. Both intra- and inter-specific sequence variation is quantified. Very little polymorphism was encountered, precluding robust tests of selection. However, the lack of inter-specific polymorphisms suggests a lack of positive selection for the regions sequenced. Results are discussed with respect to population genetic predictions and generation of a specific immune response in insects. Alternative loci and methods for studying adaptive genetic variation in a conservation context are considered.     

THE INFLUENCE OF ENVIRONMENTAL VARIATION ON GROUP AND INDIVIDUAL SELECTION IN A CRESS

An experimental study of group and individual selection for leaf area under different patterns of environmental variation is presented. This study, which uses the cress Arabidopsis thaliana, demonstrates that group selection can occur in plants. The response to group selection was always in the expected direction, but surprisingly, the response to individual selection was not. Furthermore the interaction between group and individual selection was significant. Individual selection interfered with the response to group selection whether the two forces were acting in concert or were opposed. The effects of the environmental variation treatments were detected mainly as three-way interactions with group and individual selection. Group selection was more effective in environments that interfered with individual selection, as well as in environments that did not interfere with group selection. These results suggest that the ability of a character to respond to group selection, individual selection, or both will depend on a great many factors and that the relative importance of the different levels of selection can only be determined empirically.     

Estimation of response to selection and utilization of control populations for additional information and accuracy

Problems associated with testing and estimation of response to selection are examined. An alternative procedure with increased power for testing hypotheses is given. The increased power results from a more precise method of estimating the variance about response. The new method is based on a Satterthwaite approximation which combines variance components estimated more precisely by other sources of variation in the analysis of variance. The expected variance about response and expected mean squares for the analysis of variance, used in the Satterthwaite procedure, are given. When intergeneration environmental trends cannot be ruled out, a control population must be used to estimate response to selection. However, if the experimental and control populations do not respond in the same direction and with the same magnitude to common environmental effects, then the usual method of estimating response by deviating the experimental values from the control will result in biased estimates. An alternative procedure, using the control as a covariate to adjust for environmental trends, gives relatively unbiased estimates of response in this situation. Some bias results from measurement error associated with the control. However, this bias is usually minimal.     

Selection in autotetraploids

Summary Theoretical studies indicated that response to selection would always be greater in diploid than in autotetraploid populations when gene frequency was the same in both, and that situations in which little or no response to selection could be expected would be more frequent in autotetraploids. Interpretation of the coefficient of selection in terms of escape from infection in a program of selection for disease or insect resistance indicated that moderate levels of escape from infection can drastically reduce response to selection in some cases.The zygotic constitution of an autotetraploid population will change as it approaches a new random mating equilibrium once selection pressure is relaxed. The changes will result in no change in the population mean if the trait under selection exhibits no dominance, but the mean will decrease slightly if there is dominance.     

Prediction of Selection Response for Threshold Dichotomous Traits

This paper presents a formula to predict expected response to one generation of truncation selection for a dichotomous trait under polygenic additive inheritance. The derivation relies on the threshold liability concept and on the normality assumption of the joint distribution of additive genetic values and their predictors used as selection criteria. This formula accounts for asymmetry of response when both the prevalence of the trait and the selection rate differ from 1/2 via a bivariate normal integral term. The relationship with the classical formula R = iota rho sigma G is explained with a Taylor expansion about a zero value of the correlation factor. Properties are illustrated with an example of sire selection based on progeny test performance which shows a departure from usual predictions up to 15-20% at low (0.05) or high (0.95) selection rates. Univariate approximations and extensions to several paths of genetic change are also discussed.     

Marker-assisted selection based on a multi-trait economic index in chicken: Experimental results and simulation

A method proposed herein allows simultaneous selection for several production traits, taking into consideration their marginal economic values (i.e. the economic value of a trait's additional unit). This economic index-marker assisted selection (EI-MAS) method is based on the calculation of the predicted economic breeding value (BV), using information on DNA markers that have previously been found to be associated with relevant quantitative trait loci. Based on the proposed method, results with real birds showed that sire progeny performance was significantly correlated with expected performance (r = 0.61-0.76; P = 0.03-0.01). Simulation analysis using a computer program written specifically for this purpose suggested that the relative advantage of EI-MAS would be large for traits with low heritability values. As expected, the response to EI-MAS was higher when the map distance between the marker and the quantitative trait gene was small, and vice versa. A large number of distantly located markers, spread 10 cM apart, yielded higher response to selection than a small number of closely located markers spread 3 cM apart. Additionally, the response to EI-MAS was higher when a large number (ca.150) of progeny was used for the prediction equation.     

Why breeding time has not responded to selection for earlier breeding in a songbird population

A crucial assumption underlying the breeders' equation is that selection acts directly on the trait of interest, and not on an unmeasured environmental factor which affects both fitness and the trait. Such an environmentally induced covariance between a trait and fitness has been repeatedly proposed as an explanation for the lack of response to selection on avian breeding time. We tested this hypothesis using a long-term dataset from a Dutch great tit (Parus major) population. Although there was strong selection for earlier breeding in this population, egg-laying dates have changed only marginally over the last decades. Using a so-called animal model, we quantified the additive genetic variance in breeding time and predicted breeding values for females. Subsequently, we compared selection at the phenotypic and genetic levels for two fitness components, fecundity and adult survival. We found no evidence for an environmentally caused covariance between breeding time and fitness or counteracting selection on the different fitness components. Consequently, breeding time should respond to selection but the expected response to selection was too small to be detected.     

The conflict between natural and artificial selection in finite populations

Summary A single locus model of the interaction between natural selection and artificial selection for a quantitative character in a finite population, assuming heterozygote superiority in natural fitness but additive action on the character, has been studied using transition probability matrices.If natural selection is strong enough to create a selection plateau in which genetic variance declines relatively slowly, then the total response to artificial selection prior to the plateau will be much less than that expected in the absence of natural selection, and the half-life of response will be shorter. Such a plateau is likely to have a large proportion, if not all, of the original genetic variance still present. In selection programmes using laboratory animals, it seems likely that the homozygote favoured by artificial selection must be very unfit before such a plateau will occur. A significant decrease in population fitness as a result of artificial selection does not necessarily imply that the metric character is an important adaptive character.These implications of this model of natural selection are very similar to those derived by James (1962) for the optimum model of natural selection. In fact, there seems to be no aspect of the observable response to artificial selection that would enable anyone to distinguish between these two models of natural selection.     

Selection, load and inbreeding depression in a large metapopulation

The subdivision of a species into local populations causes its response to selection to change, even if selection is uniform across space. Population structure increases the frequency of homozygotes and therefore makes selection on homozygous effects more effective. However, population subdivision can increase the probability of competition among relatives, which may reduce the efficacy of selection. As a result, the response to selection can be either increased or decreased in a subdivided population relative to an undivided one, depending on the dominance coefficient F(ST) and whether selection is hard or soft. Realistic levels of population structure tend to reduce the mean frequency of deleterious alleles. The mutation load tends to be decreased in a subdivided population for recessive alleles, as does the expected inbreeding depression. The magnitude of the effects of population subdivision tends to be greatest in species with hard selection rather than soft selection. Population structure can play an important role in determining the mean fitness of populations at equilibrium between mutation and selection.     

Evolution in a changing environment: a case study with great tit fledging mass

Heritable phenotypic traits under significant and consistent directional selection often fail to show the expected evolutionary response. A potential explanation for this contradiction is that because environmental conditions change constantly, environmental change can mask an evolutionary response to selection. We combined an "animal model" analysis with 36 years of data from a long-term study of great tits (Parus major) to explore selection on and evolution of a morphological trait: body mass at fledging. We found significant heritability of this trait, but despite consistent positive directional selection on both the phenotypic and the additive genetic component of body mass, the population mean phenotypic value declined rather than increased over time. However, the mean breeding value for body mass at fledging increased over time, presumably in response to selection. We show that the divergence between the response to selection observed at the levels of genotype and phenotype can be explained by a change in environmental conditions over time, that is, related both to increased spring temperature before breeding and elevated population density. Our results support the suggestion that measuring phenotypes may not always give a reliable impression of evolutionary trajectories and that understanding patterns of phenotypic evolution in nature requires an understanding of how the environment has itself changed.     

Designing artificial selection experiments for specific objectives

The observed genetic gain (ΔP) from selection in a finite population is the possible expected genetic gain E(Δ G) minus the difference in inbreeding depression effects in the selected and control lines. The inbreeding depression can be avoided by crossing the control and selected ♂ and ♀ parents to unrelated mates and summing the observed gains. The possible expected gain will be reduced by an amount D from the predicted gain because of the effects of the genetic limit and random genetic drift, the magnitude of which is a function of effective population size, N. The expected value of D is zero in unselected control populations and in the first generation for selected populations. Therefore, this source of bias can be reduced by increasing N in the selected populations and can be avoided by selecting for a single generation. To obtain observed responses which are unbiased estimates of the predicted response from which to estimate the realized heritability (or regression) in the zero generation, or to test genetic theory based on infinite population size, single-generation selection with many replications would be most efficient. To measure the "total" effect or genetic efficiency of a selection criterion or method, including the effect of different selection intensities, effective population sizes, and space requirements, more than one generation of selection is required to estimate the expected response in breeding values. The efficiency, in the sense of minimum variance, of estimating the expected breeding values at any generation t will decline as the number of generations t increases. The variance of either the estimated mean gain or the regression of gain on selection differential can be reduced more by increasing the number of replicates K than by increasing the number of generations t. Also the general pattern of the response over t can be estimated if the N's are known. Therefore, two- or not more than three-generation selection experiments with many replications would be most efficient.     

Distinct fast and slow processes contribute to the selection of preferred step frequency during human walking

Humans spontaneously select a step frequency that minimizes the energy expenditure of walking. This selection might be embedded within the neural circuits that generate gait so that the optimum is pre-programmed for a given walking speed. Or perhaps step frequency is directly optimized, based on sensed feedback of energy expenditure. Direct optimization is expected to be slow due to the compounded effect of delays and iteration, whereas a pre-programmed mechanism presumably allows for faster step frequency selection, albeit dependent on prior experience. To test for both pre-programmed selection and direct optimization, we applied perturbations to treadmill walking to elicit transient changes in step frequency. We found that human step frequency adjustments (n = 7) occurred with two components, the first dominating the response (66 ± 10% of total amplitude change; mean ± SD) and occurring quite quickly (1.44 ± 1.14 s to complete 95% of total change). The other component was of smaller amplitude (35 ± 10% of total change) and took tens of seconds (27.56 ± 16.18 s for 95% completion). The fast process appeared to be too fast for direct optimization and more indicative of a pre-programmed response. It also persisted even with unusual closed-loop perturbations that conflicted with prior experience and rendered the response energetically suboptimal. The slow process was more consistent with the timing expected for direct optimization. Our interpretation of these results is that humans may rely heavily on pre-programmed gaits to rapidly select their preferred step frequency and then gradually fine-tune that selection with direct optimization.     

Effect of selection intensity and population size on percent oil in maize,Zea mays L

Summary The effect of selection intensity and population size on the response to selection for percent oil in the grain of maize (Zea mays L.) was evaluated in a replicated experiment over ten cycles of selection. An open-pollinated variety, Armel's Reid Yellow Dent, was divided into subpopulations of 6,10 and 50 plants. Selection proportions of 17% and 5% were imposed upon each subpopulation. Selection was based on the percentage of oil in individual kernels as determined by wide-line nuclear magnetic resonance spectroscopy. As expected, total response to selection increased with larger population sizes and selection intensities. The concave shape of the response curves suggested that an appreciable part of the genetic variance can be attributed to additive genes at high initial frequencies, dominance genes at low initial frequencies, or to the generation of negative linkage disequilibrium due to selection. The consistently greater loss of vigor experienced by the more intensely selected populations reflects the enhancement of inbreeding due to artificial selection, an effect that increases with the intensity of selection. The results indicate that combined selection, based on kernels and using within- and amongfamily information, will be more efficient than other conventional selection procedures, including the normal combined scheme where selection is based on plants.Deceased     

A note on mate allocation for dominance handling in genomic selection

Estimation of non-additive genetic effects in animal breeding is important because it increases the accuracy of breeding value prediction and the value of mate allocation procedures. With the advent of genomic selection these ideas should be revisited. The objective of this study was to quantify the efficiency of including dominance effects and practising mating allocation under a whole-genome evaluation scenario. Four strategies of selection, carried out during five generations, were compared by simulation techniques. In the first scenario (MS), individuals were selected based on their own phenotypic information. In the second (GSA), they were selected based on the prediction generated by the Bayes A method of whole-genome evaluation under an additive model. In the third (GSD), the model was expanded to include dominance effects. These three scenarios used random mating to construct future generations, whereas in the fourth one (GSD + MA), matings were optimized by simulated annealing. The advantage of GSD over GSA ranges from 9 to 14% of the expected response and, in addition, using mate allocation (GSD + MA) provides an additional response ranging from 6% to 22%. However, mate selection can improve the expected genetic response over random mating only in the first generation of selection. Furthermore, the efficiency of genomic selection is eroded after a few generations of selection, thus, a continued collection of phenotypic data and re-evaluation will be required.     

A molecular selection index method based on eigenanalysis

The traditional molecular selection index (MSI) employed in marker-assisted selection maximizes the selection response by combining information on molecular markers linked to quantitative trait loci (QTL) and phenotypic values of the traits of the individuals of interest. This study proposes an MSI based on an eigenanalysis method (molecular eigen selection index method, MESIM), where the first eigenvector is used as a selection index criterion, and its elements determine the proportion of the trait's contribution to the selection index. This article develops the theoretical framework of MESIM. Simulation results show that the genotypic means and the expected selection response from MESIM for each trait are equal to or greater than those from the traditional MSI. When several traits are simultaneously selected, MESIM performs well for traits with relatively low heritability. The main advantages of MESIM over the traditional molecular selection index are that its statistical sampling properties are known and that it does not require economic weights and thus can be used in practical applications when all or some of the traits need to be improved simultaneously.