Changes In Genetic Variance Research Articles

Genetic Variance Estimation over Time in Broiler Breeding Programmes for Growth and Reproductive Traits.

Monitoring the genetic variance of traits is a key priority to ensure the sustainability of breeding programmes in populations under directional selection, since directional selection can decrease genetic variation over time. Studies monitoring changes in genetic variation have typically used long-term data from small experimental populations selected for a handful of traits. Here, we used a large dataset from a commercial breeding line spread over a period of twenty-three years. A total of 2,059,869 records and 2,062,112 animals in the pedigree were used for the estimations of variance components for the traits: body weight (BWT; 2,059,869 records) and hen-housed egg production (HHP; 45,939 records). Data were analysed with three estimation approaches: sliding overlapping windows, under frequentist (restricted maximum likelihood (REML)) and Bayesian (Gibbs sampling) methods; expected variances using coefficients of the full relationship matrix; and a "double trait covariances" analysis by computing correlations and covariances between the same trait in two distinct consecutive windows. The genetic variance showed marginal fluctuations in its estimation over time. Whereas genetic, maternal permanent environmental, and residual variances were similar for BWT in both the REML and Gibbs methods, variance components when using the Gibbs method for HHP were smaller than the variances estimated when using REML. Large data amounts were needed to estimate variance components and detect their changes. For Gibbs (REML), the changes in genetic variance from 1999-2001 to 2020-2022 were 82.29 to 93.75 (82.84 to 93.68) for BWT and 76.68 to 95.67 (98.42 to 109.04) for HHP. Heritability presented a similar pattern as the genetic variance estimation, changing from 0.32 to 0.36 (0.32 to 0.36) for BWT and 0.16 to 0.15 (0.21 to 0.18) for HHP. On the whole, genetic parameters tended slightly to increase over time. The expected variance estimates were lower than the estimates when using overlapping windows. That indicates the low effect of the drift-selection process on the genetic variance, or likely, the presence of genetic variation sources compensating for the loss. Double trait covariance analysis confirmed the maintenance of variances over time, presenting genetic correlations >0.86 for BWT and >0.82 for HHP. Monitoring genetic variance in broiler breeding programmes is important to sustain genetic progress. Although the genetic variances of both traits fluctuated over time, in some windows, particularly between 2003 and 2020, increasing trends were observed, which warrants further research on the impact of other factors, such as novel mutations, operating on the dynamics of genetic variance.

Temporal and genomic analysis of additive genetic variance in breeding programmes

Genetic variance is a central parameter in quantitative genetics and breeding. Assessing changes in genetic variance over time as well as the genome is therefore of high interest. Here, we extend a previously proposed framework for temporal analysis of genetic variance using the pedigree-based model, to a new framework for temporal and genomic analysis of genetic variance using marker-based models. To this end, we describe the theory of partitioning genetic variance into genic variance and within-chromosome and between-chromosome linkage-disequilibrium, and how to estimate these variance components from a marker-based model fitted to observed phenotype and marker data. The new framework involves three steps: (i) fitting a marker-based model to data, (ii) sampling realisations of marker effects from the fitted model and for each sample calculating realisations of genetic values and (iii) calculating the variance of sampled genetic values by time and genome partitions. Analysing time partitions indicates breeding programme sustainability, while analysing genome partitions indicates contributions from chromosomes and chromosome pairs and linkage-disequilibrium. We demonstrate the framework with a simulated breeding programme involving a complex trait. Results show good concordance between simulated and estimated variances, provided that the fitted model is capturing genetic complexity of a trait. We observe a reduction of genetic variance due to selection and drift changing allele frequencies, and due to selection inducing negative linkage-disequilibrium.

Genetic Consequences of Biologically Altered Environments.

Evolvable traits of organisms can alter the environment those organisms experience. While it is well appreciated that those modified environments can influence natural selection to which organisms are exposed, they can also influence the expression of genetic variances and covariances of traits under selection. When genetic variance and covariance change in response to changes in the evolving, modified environment, rates and outcomes of evolution also change. Here we discuss the basic mechanisms whereby organisms modify their environments, review how those modified environments have been shown to alter genetic variance and covariance, and discuss potential evolutionary consequences of such dynamics. With these dynamics, responses to selection can be more rapid and sustained, leading to more extreme phenotypes, or they can be slower and truncated, leading to more conserved phenotypes. Patterns of correlated selection can also change, leading to greater or less evolutionary independence of traits, or even causing convergence or divergence of traits, even when selection on them is consistent across environments. Developing evolutionary models that incorporate changes in genetic variances and covariances when environments themselves evolve requires developing methods to predict how genetic parameters respond to environments-frequently multifactorial environments. It also requires a population-level analysis of how traits of collections of individuals modify environments for themselves and/or others in a population, possibly in spatially explicit ways. Despite the challenges of elucidating the mechanisms and nuances of these processes, even qualitative predictions of how environment-modifying traits alter evolutionary potential are likely to improve projections of evolutionary outcomes.

Short-term effects of controlled mating and selection on the genetic variance of honeybee populations

Directional selection in a population yields reduced genetic variance due to the Bulmer effect. While this effect has been thoroughly investigated in mammals, it is poorly studied in social insects with biological peculiarities such as haplo-diploidy or the collective expression of traits. In addition to the natural adaptation to climate change, parasites, and pesticides, honeybees increasingly experience artificial selection pressure through modern breeding programs. Besides selection, many honeybee breeding schemes introduce controlled mating. We investigated which individual effects selection and controlled mating have on genetic variance. We derived formulas to describe short-term changes of genetic variance in honeybee populations and conducted computer simulations to confirm them. Thereby, we found that the changes in genetic variance depend on whether the variance is measured between queens (inheritance criterion), worker groups (selection criterion), or both (performance criterion). All three criteria showed reduced genetic variance under selection. In the selection and performance criteria, our formulas and simulations showed an increased genetic variance through controlled mating. This newly described effect counterbalanced and occasionally outweighed the Bulmer effect. It could not be observed in the inheritance criterion. A good understanding of the different notions of genetic variance in honeybees, therefore, appears crucial to interpreting population parameters correctly.

Genotype by environment interaction for gene expression in Drosophila melanogaster

The genetics of phenotypic responses to changing environments remains elusive. Using whole-genome quantitative gene expression as a model, here we study how the genetic architecture of regulatory variation in gene expression changed in a population of fully sequenced inbred Drosophila melanogaster strains when flies developed in different environments (25 °C and 18 °C). We find a substantial fraction of the transcriptome exhibited genotype by environment interaction, implicating environmentally plastic genetic architecture of gene expression. Genetic variance in expression increases at 18 °C relative to 25 °C for most genes that have a change in genetic variance. Although the majority of expression quantitative trait loci (eQTLs) for the gene expression traits in the two environments are shared and have similar effects, analysis of the environment-specific eQTLs reveals enrichment of binding sites for two transcription factors. Finally, although genotype by environment interaction in gene expression could potentially disrupt genetic networks, the co-expression networks are highly conserved across environments. Genes with higher network connectivity are under stronger stabilizing selection, suggesting that stabilizing selection on expression plays an important role in promoting network robustness.

Rapid reversal of a potentially constraining genetic covariance between leaf and flower traits in Silene latifolia.

Genetic covariance between two traits generates correlated responses to selection, and may either enhance or constrain adaptation. Silene latifolia exhibits potentially constraining genetic covariance between specific leaf area (SLA) and flower number in males. Flower number is likely to increase via fecundity selection but the correlated increase in SLA increases mortality, and SLA is under selection to decrease in dry habitats. We selected on trait combinations in two selection lines for four generations to test whether genetic covariance could be reduced without significantly altering trait means. In one selection line, the genetic covariance changed sign and eigenstructure changed significantly, while in the other selection line eigenstructure remained similar to the control line. Changes in genetic variance–covariance structure are therefore possible without the introduction of new alleles, and the responses we observed suggest that founder effects and changes in frequency of alleles of major effect may be acting to produce the changes.

Genotype by environment interactions in fertility traits in New Zealand dairy cows

New Zealand's seasonal dairy farming system entails a condensed calving pattern with cows required to conceive within approximately 12 wk of the planned start of calving. This has resulted in strong selection for fertility through culling of nonpregnant cows and relatively strong emphasis on fertility in Breeding Worth, the national breeding objective that drives sire selection. Despite this, average herd-level fertility is highly variable across New Zealand dairy farms. We studied genotype by environment interaction in fertility-related traits, with the goal of improving selection decisions in different fertility environments. We used data from the New Zealand national dairy database, which contains records on 3,743,862 animals. Herds were classified into high-, mid-, or low-fertility categories or environments based on herd average fertility performance, and data were analyzed in 2 different ways. First, we estimated genetic parameters when the fertility trait was defined specifically for each fertility environment to determine the extent to which genetic correlations between high- and low-fertility environments differed from 1 and the extent of changes in genetic variance across environments. Second, we used simple regression to evaluate the impact of ancestral genetic merit for fertility on cow fertility phenotypes to compare the effect of changes in genetic merit on phenotypic performance between fertility environments. The genetic standard deviations of fertility-related traits were 1.5 to 3.6 times higher in low-fertility herds than in high-fertility herds, and the genetic correlations between the same fertility-related traits between the high- and low-fertility environments were moderate to high, albeit with high standard errors. The high standard errors of the correlations reflected the low heritabilities of the traits and potential problems of culling bias, particularly for traits expressed in later parities. Regression analysis revealed that the bottom 30% of herds (in terms of fertility) could achieve more than twice the benefit from selection for fertility than the top 30% of herds. Although our analyses do not support separate genetic evaluations of fertility in the different environments, they indicate that low-fertility herds could benefit more from targeted selection of sires with higher fertility estimated breeding values than from selection based solely on the multitrait national index. Conversely, high-fertility herds could focus their sire selection on traits other than fertility, provided they avoid very low fertility sires.

Genetic Variances and Heritabilities of Traits of an Early Yellow Maize Population after Cycles of Improvement for Striga Resistance and Drought Tolerance.

Drought and Striga are principal constraints to maize (Zea mays L.) production in sub-Saharan Africa. An early yellow maize population, TZE-Y Pop DT STR, which had undergone five cycles of selection for resistance to Striga, followed by three cycles of improvement for drought tolerance, was investigated for yield gains, changes in genetic variance, and interrelationships among traits under drought stress and optimum environments. Two hundred and forty S1 lines comprising 60 each from the base population and subsequent populations from three selection cycles improved for grain yield and drought tolerance were assessed under drought and optimal environments in Nigeria from 2010 to 2012. Genetic improvements in grain yield of 423 and 518 kg ha–1 cycle–1 were achieved under drought stress and optimal environments. Predicted improvements in selection for yield were 348 and 377 kg ha–1 cycle–1 under drought stress and optimum environments, respectively. The highest yield observed in C3 was accompanied by reduced days to silking and anthesis–silking interval, improved plant aspect and ear aspect, and increased plant height and ears per plant across research environments, as well as improved stay-green characteristic under drought. The level of genetic variability for yield and a few other traits were maintained under drought and optimal environments in the population. The presence of residual genetic variability for yield and other assayed traits in C3 indicated that progress could be made from future selection in the population depending on the ability of breeders to identify outstanding genotypes and the precision level of experimentation. Substantial improvement has been made in yield and drought tolerance in C3 of the population.

Validation of consistency of Mendelian sampling variance

Experiences from international sire evaluation indicate that the multiple-trait across-country evaluation method is sensitive to changes in genetic variance over time. Top bulls from birth year classes with inflated genetic variance will benefit, hampering reliable ranking of bulls. However, none of the methods available today enable countries to validate their national evaluation models for heterogeneity of genetic variance. We describe a new validation method to fill this gap comprising the following steps: estimating within-year genetic variances using Mendelian sampling and its prediction error variance, fitting a weighted linear regression between the estimates and the years under study, identifying possible outliers, and defining a 95% empirical confidence interval for a possible trend in the estimates. We tested the specificity and sensitivity of the proposed validation method with simulated data using a real data structure. Moderate (M) and small (S) size populations were simulated under 3 scenarios: a control with homogeneous variance and 2 scenarios with yearly increases in phenotypic variance of 2 and 10%, respectively. Results showed that the new method was able to estimate genetic variance accurately enough to detect bias in genetic variance. Under the control scenario, the trend in genetic variance was practically zero in setting M. Testing cows with an average birth year class size of more than 43,000 in setting M showed that tolerance values are needed for both the trend and the outlier tests to detect only cases with a practical effect in larger data sets. Regardless of the magnitude (yearly increases in phenotypic variance of 2 or 10%) of the generated trend, it deviated statistically significantly from zero in all data replicates for both cows and bulls in setting M. In setting S with a mean of 27 bulls in a year class, the sampling error and thus the probability of a false-positive result clearly increased. Still, overall estimated genetic variance was close to the parametric value. Only rather strong trends in genetic variance deviated statistically significantly from zero in setting S. Results also showed that the new method was sensitive to the quality of the approximated reliabilities of breeding values used in calculating the prediction error variance. Thus, we recommend that only animals with a reliability of Mendelian sampling higher than 0.1 be included in the test and that low heritability traits be analyzed using bull data sets only.

Sex-specific selection under environmental stress in seed beetles.

Sexual selection can increase rates of adaptation by imposing strong selection in males, thereby allowing efficient purging of the mutation load on population fitness at a low demographic cost. Indeed, sexual selection tends to be male-biased throughout the animal kingdom, but little empirical work has explored the ecological sensitivity of this sex difference. In this study, we generated theoretical predictions of sex-specific strengths of selection, environmental sensitivities and genotype-by-environment interactions and tested them in seed beetles by manipulating either larval host plant or rearing temperature. Using fourteen isofemale lines, we measured sex-specific reductions in fitness components, genotype-by-environment interactions and the strength of selection (variance in fitness) in the juvenile and adult stage. As predicted, variance in fitness increased with stress, was consistently greater in males than females for adult reproductive success (implying strong sexual selection), but was similar in the sexes in terms of juvenile survival across all levels of stress. Although genetic variance in fitness increased in magnitude under severe stress, heritability decreased and particularly so in males. Moreover, genotype-by-environment interactions for fitness were common but specific to the type of stress, sex and life stage, suggesting that new environments may change the relative alignment and strength of selection in males and females. Our study thus exemplifies how environmental stress can influence the relative forces of natural and sexual selection, as well as concomitant changes in genetic variance in fitness, which are predicted to have consequences for rates of adaptation in sexual populations.

Changes in genetic variances and heritabilities in an early white maize population following S1 selection for grain yield, Striga resistance and drought tolerance

SUMMARYDrought is a major constraint to maize production in West and Central Africa (WCA). Assessment of genetic gain from S1 recurrent selection under drought is crucial for the development of drought tolerance breeding strategies. In an early white population, 60 S1 families each derived from the base population and three cycles of selection were evaluated under drought and well-watered conditions at two locations in Nigeria for 2 years to determine genetic variability, gains from selection and predict response to selection for grain yield and other traits. Genetic variances generally decreased for yield and other traits in advanced cycles under drought and well-watered conditions except yield and ear height under well-watered conditions. Similarly, heritabilities for yield and other traits decreased in advanced cycles under drought but increased in advanced cycles under well-watered conditions. Realized gain for yield was 0·291 t/ha, corresponding to 30·5% per cycle under drought and 0·352 kg/ha with a corresponding gain of 16·7% per cycle under well-watered conditions. Predicted gain based on C3 was 0·282 and 0·583 t/ha under drought and well-watered conditions. Low genetic variances, heritabilities and predicted gain for yield and other traits suggested a need to introgress drought tolerance genes into the population.

Behavioural response to combined insecticide and temperature stress in natural populations of Drosophila melanogaster.

Insecticide resistance evolves extremely rapidly, providing an illuminating model for the study of adaptation. With climate change reshaping species distribution, pest and disease vector control needs rethinking to include the effects of environmental variation and insect stress physiology. Here, we assessed how both long-term adaptation of populations to temperature and immediate temperature variation affect the genetic architecture of DDT insecticide response in Drosophila melanogaster. Mortality assays and behavioural assays based on continuous activity monitoring were used to assess the interaction between DDT and temperature on three field-derived populations from climate extremes (Raleigh for warm temperate, Tasmania for cold oceanic and Queensland for hot tropical). The Raleigh population showed the highest mortality to DDT, whereas the Queensland population, epicentre for derived alleles of the resistance gene Cyp6g1, showed the lowest. Interaction between insecticide and temperature strongly affected mortality, particularly for the Tasmanian population. Activity profiles analysed using self-organizing maps show that the insecticide promoted an early response, whereas elevated temperature promoted a later response. These distinctive early or later activity phases revealed similar responses to temperature and DDT dose alone but with more or less genetic variance depending on the population. This change in genetic variance among populations suggests that selection particularly depleted genetic variance for DDT response in the Queensland population. Finally, despite similar (co)variation between traits in benign conditions, the genetic responses across population differed under stressful conditions. This showed how stress-responsive genetic variation only reveals itself in specific conditions and thereby escapes potential trade-offs in benign environments.

Ontogenetic changes in genetic variances of age-dependent plasticity along a latitudinal gradient.

The expression of phenotypic plasticity may differ among life stages of the same organism. Age-dependent plasticity can be important for adaptation to heterogeneous environments, but this has only recently been recognized. Whether age-dependent plasticity is a common outcome of local adaptation and whether populations harbor genetic variation in this respect remains largely unknown. To answer these questions, we estimated levels of additive genetic variation in age-dependent plasticity in six species of damselflies sampled from 18 populations along a latitudinal gradient spanning 3600 km. We reared full sib larvae at three temperatures and estimated genetic variances in the height and slope of thermal reaction norms of body size at three points in time during ontogeny using random regression. Our data show that most populations harbor genetic variation in growth rate (reaction norm height) in all ontogenetic stages, but only some populations and ontogenetic stages were found to harbor genetic variation in thermal plasticity (reaction norm slope). Genetic variances in reaction norm height differed among species, while genetic variances in reaction norm slope differed among populations. The slope of the ontogenetic trend in genetic variances of both reaction norm height and slope increased with latitude. We propose that differences in genetic variances reflect temporal and spatial variation in the strength and direction of natural selection on growth trajectories and age-dependent plasticity. Selection on age-dependent plasticity may depend on the interaction between temperature seasonality and time constraints associated with variation in life history traits such as generation length.

Plant RNA virus fitness predictability: contribution of genetic and environmental factors

Forecasting plant virus emergence depends on identifying the factors that determine the distribution of genetic variants within the primary host as well as across potential new hosts. It is crucial to determine: (i) the distribution of mutational fitness effects (DMFE) on the primary host, (ii) how it changes on different hosts, (iii) the way in which multiple mutations interact in determining viral fitness in the primary host, and (iv) whether this interaction is host‐dependent. To illustrate points (i) and (ii), this paper reviews recent reports showing that the DMFE for a potyvirus markedly differs between natural and non‐natural hosts. Changes in genetic variance for fitness are the main cause of the observed pattern among related hosts, whereas sign pleiotropy mainly explains differences observed among unrelated hosts. To illustrate point (iii), comments are made on experiments showing significant epistasis among random pairs of mutations in the potyvirus genome. A large fraction of the interactions correspond to the reciprocal sign epistasis, meaning that the sign of the effects of mutations at two loci are mutually dependent. Finally, to illustrate point (iv), evidence is presented that epistatic interactions for an RNA virus varied among hosts, with magnitude epistasis being stronger in the primary host but becoming weaker as host's taxonomic relatedness decreased. The existence of all these interactions jeopardizes the prediction of the fitness and evolutionary fate of a given mutation, as it will depend on the genetic background but also on the host wherein the virus replicates.

Effects of Recurrent Selection for Grain Yield and Striga Resistance in an Extra‐Early Maize Population

ABSTRACTStriga hermonthica (Del.) Benth threatens maize (Zea mays L.) production in sub‐Saharan Africa. In an extra‐early population, S1 families derived from four cycles of recurrent selection for grain yield and Striga resistance were evaluated with and without Striga infestation at three locations in Nigeria for 2 yr to determine relative changes in genetic variances, heritabilities, and genetic correlations for yield and other traits. Under infestation, yield was not correlated with other traits at C0 but was significantly correlated with ears per plant (EPP), Striga damage, and emerged Striga plants in advanced cycles. Genetic correlations between yield and most traits were significant in C0 when Striga‐free but was reduced in advanced cycles. Genetic variances and heritabilities for yield and ear aspect increased in advanced cycles. Genetic variances decreased with selection for emerged Striga counts and EPP under infestation. A response to selection for improved yield, Striga emergence and EPP is expected in subsequent cycles. Low genetic variances and heritabilities for Striga damage and low predicted gain cycle−1 for all traits except numbers of emerged Striga plants suggest a need to introgress novel resistance genes into the population for faster progress from selection for increased yield.

Ontogenetic Change in Genetic Variance in Size Depends on Growth Environment

Within populations, the amount of environmental and genetic variation present may differ greatly among traits measured at multiple times over ontogeny. Brief periods of food deprivation are often followed by a period of accelerated (compensatory) growth. Early laboratory studies likewise reported a contraction of genetic variance in size as maturation approached. However, studies of wild populations often contradict these laboratory results. One possibility is that environmentally imposed stress is exposing genetic variance not seen in the laboratory. We tested the effect of rearing environment (high or low food) on genetic variance in size traits measured at two ages in the ladybird beetle Harmonia axyridis. A substantial amount of genetic variance was present in all combinations of rearing environment by ontogenetic stage among males. The pattern of change in male variance in mass over ontogeny was of opposite sign in the two food treatments, which may reflect cryptic genetic variance that is apparent only under stress. The proportion of overall variance that was due to additive genetic effects was much lower in females than in males, which suggests that the underlying genetics of female growth trajectories differs from that males. Our experimental design afforded an initial exploration of the genetics of compensatory growth.

Associations Among Descriptors of Herd Management and Phenotypic and Genetic Levels of Health and Fertility

The objective of this paper was to investigate the association of descriptors of herd environment with phenotypic levels and breeding values of fertility and health traits. Analyses were performed for 82,080 first-lactation heifers and 173,787 multiparous cows. Fourteen environmental parameters were defined that described herd environment, such as average protein production, average somatic cell score (SCS), average calving interval, and average body condition score (BCS). Herds with lower average SCS had, in general, more desirable values for almost all analyzed traits (i.e., days to first service was 7 d shorter), as did herds with lower average calving interval (i.e., 2.8% lower incidence of predicted mastitis). Herds with higher average protein production had slightly poorer fertility but more desirable values for all other analyzed traits (i.e., 5.1% less predicted mastitis, 0.4 lower SCS, and 0.6 higher BCS). Variance components and breeding values of sires were estimated by applying a random regression on the environmental parameters. In general, genetic variances varied generally only slightly across environments. However, based on data exclusively for heifers, the genetic variance for number of inseminations was 4.1 times higher in herds with a higher number of inseminations, 1.9 times higher for survival in herds with higher fat to protein ratio, and 1.7 times higher for predicted mastitis in herds with higher number of inseminations. Based on the heifer data, the lowest estimated genetic correlation across environments was 0.76 (SE 0.21) for first-service conception between herds with differing average BCS. The minimum based on the cow data was 0.65 (SE 0.10) for survival between herds with differing average ages at calving. The relative importance of some fertility traits compared with yield traits doubled across environments. Possible reranking of individual animals within a population and the changes in genetic variance across environments suggests that environment-specific breeding values should be estimated for use in customized selection indices.

Long‐term responses, changes in genetic variances and inbreeding depression from 122 generations of selection on increased litter size in mice

Data on mice selected for litter size over 122 generations have been analysed in order to reveal the effect of long-term selection on responses and changes in variances over a long selection period. Originally, three lines were established from the same base population, namely an H line selected for large litter size, an L line selected for small litter size and a K line without selection. In generation 122, the mean number of pups born alive (NBA) was 22 for the H line and 11 for the K line. Phenotypic response to selection is reduced over generations, but crossing of plateaued lines increased responses and realized heritabilities. Both realized heritabilities and heritabilities from residual maximal likelihood (REML) analyses were, in general, calculated from generation (-1)-44 (period 1), 45-70 (period 2) and 71-122 (period 3) separately. Realized heritabilities were in general smaller than heritabilities estimated from mixed model analysis. An overall estimate of heritability for NBA was found to be 0.19 (+/- 0.01) by REML analysis. Additive variance is constant over all periods in the high line and the control line, but is reduced over periods in the low line. The reduction of additive variance in the low line could probably be explained by changes in gene frequencies. In all lines, environmental variances increased over periods. Inbreeding reduced the mean litter size by 0.72 (+/- 0.10) pups per 10% increase in inbreeding, with substantial variance between periods and lines.

Effect of captivity on genetic variance for five traits in the large milkweed bug (Oncopeltus fasciatus).

Understanding the changes in genetic variance which may occur as populations move from nature into captivity has been considered important when populations in captivity are used as models of wild ones. However, the inherent significance of these changes has not previously been appreciated in a conservation context: are the methods aimed at founding captive populations with gene diversity representative of natural populations likely also to capture representative quantitative genetic variation? Here, I investigate changes in heritability and a less traditional measure, evolvability, between nature and captivity for the large milkweed bug, Oncopeltus fasciatus, to address this question. Founders were collected from a 100-km transect across the north-eastern US, and five traits (wing colour, pronotum colour, wing length, early fecundity and later fecundity) were recorded for founders and for their offspring during two generations in captivity. Analyses reveal significant heritable variation for some life history and morphological traits in both environments, with comparable absolute levels of evolvability across all traits (0-30%). Randomization tests show that while changes in heritability and total phenotypic variance were highly variable, additive genetic variance and evolvability remained stable across the environmental transition in the three morphological traits (changing 1-2% or less), while they declined significantly in the two life-history traits (5-8%). Although it is unclear whether the declines were due to selection or gene-by-environment interactions (or both), such declines do not appear inevitable: captive populations with small numbers of founders may contain substantial amounts of the evolvability found in nature, at least for some traits.

Changes in Genetic Variance during Advanced Cycle Breeding in Maize

Advanced cycle breeding in crops aims to develop newer, improved versions of inbreds from crosses among current, elite inbreds. Although genetic gains in many crops have been achieved through advanced cycle breeding, this breeding process systematically leads to a narrow germplasm base. Our objectives were to estimate the loss, if any, in genetic variance during advanced cycle breeding in maize (Zea mays L.), and to compare these genetic variance estimates with those expected under a testcross additive model. We evaluated the Iowa Stiff Stalk Synthetic (BSSS), B73 × B37, and Lo904 × Lo916 populations, which have a common genetic background but have different levels of genetic variance expected from the testcross additive model; that is, 100% in BSSS, 82% in B73 × B37, and 45% in Lo904 × Lo916. Contrary to expectations, testcross additive variances (VTA) for grain yield did not significantly differ among the three populations. As expected, VTA for grain moisture, stalk lodging, plant height, and ear height were significantly lower in B73 × B37 than in BSSS. The decreases in VTA for these traits were not significant from B73 × B37 to Lo904 × Lo916. Fitting a testcross epistatic model did not result in positive estimates of both VTA and testcross additive‐by‐additive variance (VTAA) for any trait. In summary, genetic variance, except for grain yield, was lost during advanced cycle breeding and the amount of loss was greater than expected.