Maternal Effects Model Research Articles

Delineating maternal influence in regulation of variance in major economic traits of White Leghorns: Bayesian insights.

Proper variance partitioning and estimation of genetic parameters at appropriate time interval is crucial for understanding the dynamics of trait variance and genetic correlations and for deciding the future breeding strategy of the population. This study was conducted on the same premise to estimate genetic parameters of major economic traits in a White Leghorn strain IWH using Bayesian approach and to identify the role of maternal effects in the regulation of trait variance. Three different models incorporating the direct additive effect (Model 1), direct additive and maternal genetic effect (Model 2) and direct additive, maternal genetic and maternal permanent environmental effects (Model 3) were tried to estimate the genetic parameters for body weight traits (birth weight, body weight at 16, 20, 40 and 52 weeks), Age at sexual maturity (ASM), egg production traits (egg production up to 24, 28, 40, 52, 64 and 72 weeks) and egg weight traits (egg weight at 28, 40 and 52 weeks). Model 2 and Model 3 with maternal effects were found to be the best having the highest accuracy for almost all the traits. The direct additive genetic heritability was moderate for ASM, moderate to high for body weight traits and egg weight traits and low to moderate for egg production traits. Though the maternal heritability (h2mat) and permanent environmental effect (c2mpe) was low (<0.1) for most of the traits, they formed an important component of trait variance. Traits like egg weight at 28 weeks (0.14±0.06) and egg production at 72 weeks (0.13±0.07) reported comparatively higher values for c2mpe and h2mat respectively. Additive genetic correlation was high and positive between body weight traits, between egg weight traits, between consecutive egg production traits and between body weight and egg weight traits. However, a negative genetic correlation existed between egg production and egg weight traits, egg production and body weight traits, ASM and early egg production traits. Overall, a moderate positive genetic correlation was estimated between ASM and body weight traits and ASM and egg weight traits. Based on our findings, we can deduce that maternal effects constitute an important source of variation for all the major economic traits in White Leghorn and should be necessarily considered in genetic evaluation programs.

Estimation of genetic parameters for important traits using a multi-trait model in late-feathering Qingyuan partridge hens in China.

Qingyuan partridge chicken is one of the most well-known Chinese indigenous yellow broilers. In breeding programmes, five traits are usually selected when the chickens are 105 days old, namely body weight (BW), comb height (CH), shank length (SL), shank girth (SG) and feather maturity (FM). The objective of this study was to estimate the genetic parameters of these five traits, especially direct additive genetic correlations, to lay the foundation for balanced selection of Qingyuan partridge chickens. Approximately 9600 records were used for estimation. Variance components for these five traits were estimated using three multi-trait models incorporating different effects via Gibbs sampling. Based on model 1 in which the random effects included direct additive genetic effects and residuals, the estimated direct heritabilities for BW, CH, SL, SG and FM were 0.29 ± 0.04, 0.53 ± 0.04, 0.47 ± 0.04, 0.43 ± 0.05 and 0.18 ± 0.03, respectively. The direct genetic correlations ranged from -0.08 to 0.46. When additionally considering maternal additive genetic effects (model 2), the estimates of direct heritabilities and absolute values of direct additive genetic correlations were smaller. The heritabilities were 0.14 ± 0.04, 0.40 ± 0.02, 0.34 ± 0.05, 0.27 ± 0.05 and 0.12 ± 0.03 for BW, CH, SL, SG and FM, respectively. The direct additive genetic correlations ranged from -0.33 to 0.36. More specifically, the direct additive genetic correlations between BW and CH, SL, SG and FM were 0.19 ± 0.13, 0.15 ± 0.15, 0.36 ± 0.15 and - 0.33 ± 0.21, respectively. The genetic correlations of FM with SL, SG and CH were - 0.15 ± 0.15, -0.08 ± 0.17 and 0.18 ± 0.15, respectively. The direct genetic correlations between CH and SG and SL were - 0.02 ± 0.11 and - 0.20 ± 0.11, respectively, and that between SL and SG was 0.19 ± 0.11. The total heritabilities and maternal additive genetic correlations ranged from 0.16 to 0.44 and from -0.13 to 0.61, respectively. The third model also included the maternal permanent environmental effect for BW. The estimates of direct heritability, direct additive genetic correlation, total heritability and maternal additive genetic correlation were only slightly different from those based on the second model. Therefore, the maternal additive genetic effect has a large effect on the estimation of genetic parameters, and it is better to consider this effect in the genetic evaluation of these five traits. Relatively high direct and maternal additive genetic correlations for most trait pairs suggested that it is better to jointly evaluate these five traits in breeding programmes.

Genetic variation and parameters for growth and feed efficiency traits in Boran beef cattle in Kenya

A major drawback of improving feed efficiency in beef cattle enterprises is to identify measures of feed efficiency which do not require feed intake information on an individual animal basis. Kleiber Index, (KI) and relative growth rate (RGR) are alternative measures which do not need individual measurement of intake and can be used select for improved feed and growth efficiency in relation to their body size. The aim of this study was to estimate genetic parameters for measures of feed efficiency and growth traits for the Boran beef cattle in Kenya. A total of 1348, 2209, 2183 and 2184 weight records were available for birth, weaning, yearling and 550-day weight records, respectively, were available for animals born between 1973 and 2019. The traits derived were growth rates (ADG), adjusted weights (WA), KI and RGR at weaning (205 days), yearling (365 days) and 550 days. Genetic parameters were estimated using a maternal genetic effects model. Direct heritability estimates for direct heritability estimates for ADG ranged from 0.12±0.04 for ADG205-365 to 0.27±0.02 for ADGB-205. Estimates for WA were in range of 0.05±0.05 at to 0.10±0.05 at 550 days. Estimates for KI were 0.13±0.05 at 205 to 0.29±0.05 at 550 days. For RGR estimate direct heritability at 205 was 0.21±0.05, 0.19±0.04 at 365 and 0.33±0.05 at 550 days. The direct-maternal genetic correlations for WA, ADG, KI and RGR at 205 days were -0.30±0.05, -0.30±0.04, 0.90±0.05 and -0.72±0.04, respectively. Alongside growth traits, Kleiber Index and residual growth rate had substantial heritability estimates, implying potential for improvement through selection.

Phenotypic and Genotypic Trends for Body Weights Traits in Romanov Sheep

Data on 820 Romanov lambs progeny of 30 sires it covered the period from 1995 to 2005 were used in this study. Lambs traits studied were birth weight (BW) body weight at one month (BW1), body weight at two months (BW2), weaning weight at three month (WW) and average daily gain from birth to weaning (ADG). Data were analysis by using mixed model. Means of BW, Bw1, BW2, WW and ADG were 2.90 kg, 7.10 kg, 10.50 kg, 13.02 kg and 115.50 g respectively. Sire of lambs, ewes within sires had a highly significant effect on all traits. Season and year of lambing, type of birth and sex had a significant effect on all studied traits, expect the effect 0f year lambing on BW and type of birth on BW1 and WW. Also, inbreeding coefficients had a highly significant effect on all body weight traits studied and decreased as inbreeding coefficient increased. Two animal models were used. Model 1 includes the fixed effects season and year of lambing, type of birth and sex and random effects of direct genetic effect, permanent environmental effect and residual effect. Model 2, is similar to model 1 and added maternal genetic effect and covariance between direct and maternal genetic effect.Determination of direct heritability for body weights traits ranged from 0.17 to 0.39 for model 1 and ranged from 0.13 to 0.29 for model 2. The removal of additive maternal effects and covariance between direct and maternal genetic effects (model 1) increased estimates of direct heritability. Therefore, including maternal effects the model resulted in more accurate estimation of (co) variance and genetic parameters of growth traits. Determination of phenotypic and genetic correlations among growth traits studied were moral and highly significant. While, annual phenotypic and genetic trends for body weights traits were negative.

Evolution of maternal effect senescence

Increased maternal age at reproduction is often associated with decreased offspring performance in numerous species of plants and animals (including humans). Current evolutionary theory considers such maternal effect senescence as part of a unified process of reproductive senescence, which is under identical age-specific selective pressures to fertility. We offer a novel theoretical perspective by combining William Hamilton's evolutionary model for aging with a quantitative genetic model of indirect genetic effects. We demonstrate that fertility and maternal effect senescence are likely to experience different patterns of age-specific selection and thus can evolve to take divergent forms. Applied to neonatal survival, we find that selection for maternal effects is the product of age-specific fertility and Hamilton's age-specific force of selection for fertility. Population genetic models show that senescence for these maternal effects can evolve in the absence of reproductive or actuarial senescence; this implies that maternal effect aging is a fundamentally distinct demographic manifestation of the evolution of aging. However, brief periods of increasingly beneficial maternal effects can evolve when fertility increases with age faster than cumulative survival declines. This is most likely to occur early in life. Our integration of theory provides a general framework with which to model, measure, and compare the evolutionary determinants of the social manifestations of aging. Extension of our maternal effects model to other ecological and social contexts could provide important insights into the drivers of the astonishing diversity of lifespans and aging patterns observed among species.

When to rely on maternal effects and when on phenotypic plasticity?

Existing insight suggests that maternal effects have a substantial impact on evolution, yet these predictions assume that maternal effects themselves are evolutionarily constant. Hence, it is poorly understood how natural selection shapes maternal effects in different ecological circumstances. To overcome this, the current study derives an evolutionary model of maternal effects in a quantitative genetics context. In constant environments, we show that maternal effects evolve to slight negative values that result in a reduction of the phenotypic variance (canalization). By contrast, in populations experiencing abrupt change, maternal effects transiently evolve to positive values for many generations, facilitating the transmission of beneficial maternal phenotypes to offspring. In periodically fluctuating environments, maternal effects evolve according to the autocorrelation between maternal and offspring environments, favoring positive maternal effects when change is slow, and negative maternal effects when change is rapid. Generally, the strongest maternal effects occur for traits that experience very strong selection and for which plasticity is severely constrained. By contrast, for traits experiencing weak selection, phenotypic plasticity enhances the evolutionary scope of maternal effects, although maternal effects attain much smaller values throughout. As weak selection is common, finding substantial maternal influences on offspring phenotypes may be more challenging than anticipated.

Estimativas de parâmetros genéticos para características de crescimento de cordeiros mestiços Suffolk

Objetivou-se estimar os coeficientes de herdabilidade e correlação genética entre os pesos ao nascer (PN) e à desmama (PD) de cordeiros mestiços Suffolk, pertencentes a rebanho experimental. Assim, foram testados quatro modelos, os quais consideraram o efeito genético aditivo direto (Modelo 1), os efeitos genético direto e de ambiente permanente materno (Modelo 2), os efeitos aditivo direto, de ambiente permanente e genético materno (cov a,m=0) (Modelo 3), e no Modelo 4, além daqueles contemplados no Modelo 3, foi considerada cov a,m≠0. Após comparar os modelos por meio do teste de razão de verossimilhança (LRT), observou-se que o 3 foi o mais adequado, sendo que as estimativas de herdabilidade foram de baixa magnitude para PN e PD, iguais a 0,08±0,009 e 0,24±0,17, respectivamente, indicando pequena possibilidade de resposta à seleção direta. Da mesma maneira, o coeficiente de correlação genética entre estas características foi 0,43±0,39, resultado que implica pequena possibilidade de resposta correlacionada. A inclusão dos efeitos maternos é necessária para a estimação adequada de parâmetros genéticos para as características avaliadas.

Effects of maternal nutrition, resource use and multi-predator risk on neonatal white-tailed deer survival.

Growth of ungulate populations is typically most sensitive to survival of neonates, which in turn is influenced by maternal nutritional condition and trade-offs in resource selection and avoidance of predators. We assessed whether resource use, multi-predator risk, maternal nutritional effects, hiding cover, or interactions among these variables best explained variation in daily survival of free-ranging neonatal white-tailed deer (Odocoileus virginianus) during their post-partum period (14 May–31 Aug) in Michigan, USA. We used Cox proportional hazards mixed-effects models to assess survival related to covariates of resource use, composite predation risk of 4 mammalian predators, fawn body mass at birth, winter weather, and vegetation growth phenology. Predation, particularly from coyotes (Canis latrans), was the leading cause of mortality; however, an additive model of non-ideal resource use and maternal nutritional effects explained 71% of the variation in survival. This relationship suggested that dams selected areas where fawns had poor resources, while greater predation in these areas led to additive mortalities beyond those related to resource use alone. Also, maternal nutritional effects suggested that severe winters resulted in dams producing smaller fawns, which decreased their likelihood of survival. Fawn resource use appeared to reflect dam avoidance of lowland forests with poor forage and greater use by wolves (C. lupus), their primary predator. While this strategy led to greater fawn mortality, particularly by coyotes, it likely promoted the life-long reproductive success of dams because many reached late-age (>10 years old) and could have produced multiple generations of fawns. Studies often link resource selection and survival of ungulates, but our results suggested that multiple factors can mediate that relationship, including multi-predator risk. We emphasize the importance of identifying interactions among biological and environmental factors when assessing survival of ungulates.

Genetic relationship between growth and carcass traits in Large White pigs

Genetic relationships between growth and carcass traits in South African Large White pigs were estimated. Genetic parameters for growth and carcass traits were generated using a maternal effects model in ASREML. Data analysed were on 13 703 pigs from 28 herds tested between 1990 and 2007, and 4 128 carcasses from 21 herds evaluated between 1993 and 2007. The traits included in the study were backfat thickness (BFAT), test period weight gain (TPG), lifetime weight gain (LTG), test period feed conversion ratio (FCR), age at slaughter (AGES), lean percentage (LEAN), drip-free lean percentage (DLEAN), drip loss percentage (DRIP), carcass length (CRLTH), dressing percentage (DRESS), eye muscle area (AREA) and carcass fat (CFAT). Heritability estimates for growth traits ranged from 0.24 ± 0.03 for FCR to 0.45 ± 0.04 for BFAT, while those for carcass traits ranged from 0.14 ± 0.06 for DRIP to 0.55 ± 0.0.08 for AREA. Maternal genetic effects were significant in most traits, and were negatively correlated with direct heritabilities. Genetic correlations among growth traits ranged from –0.14 ± 0.08 between BFAT and LTG to –0.99 ± 0.01 between TPG and FCR, and LTG and AGES. For carcass traits, genetic correlations ranged from –0.02 ± 0.20 between DRIP and CRLTH to 0.99 ± 0.01 between LEAN and DLEAN. There is substantial genetic variation in growth and carcass traits; hence faster genetic improvement may be achieved through selection. Growth performance and carcass characteristics can be improved through selection for reduced backfat thickness and increased daily weight gain. Keywords : Genetic selection, growth traits, carcass traits, correlations

Estimates of (co)variance components and genetic parameters for growth traits in Suffolk lambs

The study aimed to estimate the components of (co)variance and heritability for weights at birth (BW), weaning (WW) and 180 days of age (W180), as well as the average daily gains from birth to weaning (ADG1), birth to 180 days of age (ADG2) and weaning to 180 days of age (ADG3) in Suffolk sheep. Thus, three different single-trait animal models were fitted, considering the direct additive genetic effect (Model 1), the direct additive genetic and maternal permanent environmental effects (Model 2), and in Model 3, in addition to those in Model 2, the maternal additive genetic effect was included. After comparing models through the likelihood ratio test (LRT), model 3 was chosen as the most appropriate to estimate heritability for BW, WW and ADG1. Model 2 was considered as the best to estimate the coefficient of heritability for W180 and ADG2, and model 1 for ADG3. Direct heritability estimates were inflated when maternal effects were ignored. According to the most suitable models, the heritability estimates for BW, WW, W180, ADG1, ADG2 and ADG3 were 0.06, 0.08, 0.09, 0.07, 0.08 and 0.07, respectively, indicating low possibility of genetic gain through individual selection. The results show the importance of including maternal effects in the models to properly estimate genetic parameters even at post-weaning ages.

Evaluating breeding objectives for sow productivity and production traits in Large White Pigs

the objective of the study was to develop and evaluate different breeding objectives for sow productivity and for production traits, using economic selection indices. Genetic parameters were generated using a repeated records model for sow productivity traits and a maternal effects model for production traits, in ASREML. Stochastic simulation models based on a hypothetical 100-sow model were performed for each line, i.e., a dam line and a terminal sire line, respectively, to derive economic values. The traits included in the study were number born alive (NBA), 21-day litter size (D21LS), 21-day litter weight (D21LWT), average daily gain (ADG), feed conversion ratio (FCR), age at slaughter (AGES), dressing percentage (DRESS), lean content (LEAN) and backfat thickness (BFAT). The economic values for LEAN and BFAT were derived using the partial differentiation of the profit function, while those for the other traits were derived using the partial budget approach. An economic value of a trait was the change in profit per unit genetic change in that trait. Breeding objectives were developed with a corresponding selection index, for improvement of that objective. Three combinations of breeding objectives and selection indices were developed for sow productivity traits, while there were 15 combinations for production traits. Responses to selection and economic return were computed for each combination to determine the most appropriate combination for the improvement of the breeding objective traits. The most appropriate index to improve sow productivity consisted of NBA and D21LWT. For production traits, the combination that consisted of a selection index with AGES, DRESS and BFAT, and the breeding objective ADG, DRESS, FCR and LEAN, was considered the most appropriate. Age at slaughter and BFAT were, respectively, included as indicator traits for ADG and LEAN. The recommended breeding objectives were sensitive to changes in economic values, indicating that economic values for breeding goal traits should be updated periodically to ensure proper weighting of traits, hence maximization of economic return.

A THEORETICAL MODEL OF THE EVOLUTION OF MATERNAL EFFECTS UNDER PARENT-OFFSPRING CONFLICT

The evolution of maternal effects on offspring phenotype should depend on the extent of parent-offspring conflict and costs and constraints associated with maternal and offspring strategies. Here, we develop a model of maternal effects on offspring dispersal phenotype under parent-offspring conflict to evaluate such dependence. In the absence of evolutionary constraints and costs, offspring evolve dispersal rates from different patch types that reflect their own, rather than the maternal, optima. This result also holds true when offspring are unable to assess their own environment because the maternal phenotype provides an additional source of information. Consequently, maternal effects on offspring diapause, dispersal, and other traits that do not necessarily represent costly resource investment are more likely to maximize offspring than maternal fitness. However, when trait expression was costly, the evolutionarily stable dispersal rates tended to deviate from those under both maternal and offspring control. We use our results to (re)interpret some recent work on maternal effects and their adaptive value and provide suggestions for future work.

POPULATION CYCLES IN THE PINE LOOPER MOTH: DYNAMICAL TESTS OF MECHANISTIC HYPOTHESES

The forest insect pest Bupalus piniarius (pine looper moth) is a classic example of a natural population cycle. As is typical for populations that exhibit regular oscillations in density, there are several biological mechanisms that are hypothesized to be responsible for the cycles; but despite several decades of detailed study there has been no definite conclusion as to which mechanism is most important. We evaluated three hypotheses for which there was direct experimental evidence: (1) food quality (nutritional value of pine needles affected by defoliation); (2) parasitoids (trophic interactions with specialist parasitoids); and (3) maternal effects (maternal body size affects the performance of offspring). We reviewed the empirical evidence for each of these hypotheses and expressed each hypothesis in the form of a mechanistic dynamic model. We used a nonlinear forecasting approach to fit each model to three long‐term population time series in Britain that exhibit some degree of regular cycling, and we used parametric bootstrap to evaluate the significance of differences between models in their goodness of fit to the data. The results differed among the three forests: at Culbin, the parasitoid and maternal effects models fit equally well; at Roseisle, the food quality and maternal effects models fit equally well; and at Tentsmuir, the parasitoid model fit best. However, the best‐fit parasitism models required that the parasitism rate vary between nearly 0 and nearly 1 during a cycle, greatly exceeding the range of parasitism rates that have been observed in the field. In contrast, the required variation in the observable maternal quality variable (pupal mass) was within the range of empirical observations. Under mild constraints on the parasitism rate (though allowing a much wider range than has been measured in B. piniarius at any location), the fit of the parasitism model fell off dramatically. The maternal effects model then had uniformly strong support, outperforming the constrained parasitism model at all three sites and the food quality model at two; it performed slightly better than the food quality model at the remaining site. This represents the first system in which the maternal effects hypothesis for population cycles has been supported by both strong biological and dynamical evidence.

Genetic Susceptibility to Neospora caninum Infection in Holstein Cattle in Ontario

Neospora caninum has been reported to be an important cause of endemic fetal loss and occasional abortion epidemics in cattle around the world. This study examined 12,016 sera collected from 9723 Holstein cows on 125 herds across Ontario in 1998, 1999, and 2000. An enzyme-linked immunosorbent assay was used to examine the sera for antibodies to N. caninum. The overall prevalence of N. caninum antibodies in the cattle was 11.2% and the prevalence in individual herds varied from 0 to 70.4%. Among 3109 daughter-dam pairs, 619 positive dams had 252 positive daughters, giving a detected vertical transmission rate of 40.7%. In contrast, there were only 6.7% positive daughters from negative dams (167 of 2490). Pedigree edits left 8031 cows with 1463 sires for estimation of heritability. Five genetic models (sire model, animal model, sire-dam model, a sire-maternal grandsire model, and a maternal effects model) with fixed effects of bleeding year-month, age of the animals, and herd were fitted to the data. The estimated heritability of susceptibility to N. caninum ranged between 0.084 and 0.124. The sire-maternal grandsire model and the maternal effects model provided better fit than the other models because the maternal genetic variance was much greater than the direct genetic variance. To reduce the incidence of N. caninum infection, more emphasis should be placed on management practices than on genetic selection.

Comparison of models including cytoplasmic effects for traits of Rambouillet sheep

The objective was to determine appropriate analytical models considering cytoplasmic inheritance for birth weight (BWT, n=35,604), weaning weight (WWT, n=34,114), fleece weight (FWT, n=38,113) and number born (NB, n=39,029) for Rambouillet sheep. For BWT, models that included dam by year, dam by number born, and sire by dam effects, in addition to direct and maternal effects, were significantly better than the basic maternal effects model. For WWT, variances due to direct, maternal, and maternal permanent environmental effects (0.05 of variance) were not zero. For FWT, heritability was 0.55 for all models, but models with dam by year (0.02), sire by dam (0.05), and sire by cytoplasmic line (0.02) were jointly significantly better than models with permanent environmental effects. For NB, only direct heritability (0.08) and relative permanent environmental variance (0.04) were not zero. No trait showed evidence of variation due to cytoplasmic effects. Adding seldom considered effects to the model did not change estimates of variance due to direct and maternal genetic effects. Variance due to dominance effects may be important for BWT and FWT. The basic direct–maternal effects model seems sufficient for genetic evaluations for WWT and FWT but models for BWT and NB may need to include other effects.

Genetic Relationship between Milk Production, Calving Ease and Days Open at First Parity in Holstein Cows

Data containing 14,188 lactation and reproductive records of Korean Holstein cows at first parity distributed across 3,734 herd-year-season groups were analyzed to get genetic (co)variance estimates for milk yield, fat yield, calving ease, and days open. Milk and Fat yields were adjusted to 305 d. Heritabilities and genetic correlations were estimated in two different animal models on which were included direct genetic effects (Model 1) and direct+maternal genetic effects (Model 2) using REML algorithms. Milk and fat yields were affected by age at first calving as linear and quadratic. Heritability estimates of direct effects were 0.25 for milk yield, 0.17 for fat yield, 0.03 for calving ease and 0.03 for days open in Model 2. These estimates for maternal effects were 0.05, 0.08, 0.04 and less than 0.01 for each corresponding trait. Milk productions at first lactation were to show genetically favorable correlation with calving ease and days open for direct genetic effects (-0.24 - -0.11). Moreover, calving ease was correlated with days open of 0.30 for direct genetic effects. Correlations between direct and maternal effects for each trait were negatively correlated (-0.63 - -0.32). This study suggested that maternal additive genetic variance would be not ignorable for genetic evaluation of milk production as well as reproductive traits such as calving ease and days open at first parity. Furthermore, difficult calving would genetically influence the next conception.

The effect of the nurturant bonding system on child security of attachment and dependency.

This paper uses a biopsychosocial theory of human bonding to explore the intergenerational transmission of bonding traits. More specifically, it examines how the nurturant bonding system of the mother affects the succorant bonding system of the young child. In the first section of the paper, we take the bonding framework proposed by Miller and Rodgers (2001) and elaborate its implications for mother-child dyads. Next, we describe the collection of data from 78 mothers prior to their pregnancy with an index child and again when that child is between the ages of two and four and a half. These data allow the creation of a number of mother and child variables that are derived from the bonding framework. Using these variables, we construct a temporally organized, structural equation model of maternal effects on the child, with the two main outcome variables being child security of attachment and child dependency. We then test the model using LISREL. Although the results are tentative and require further confirmatory research, they lend support to three broad hypotheses derived from the bonding framework. In particular, the results support the construct of a motivational substrate that affects both maternal childbearing and her child-rearing behaviors. They also indicate the importance of child temperament in the formation of the succorant bond. Finally, they demonstrate that the preconception nurturant characteristics of the mother have multiple effects on the two main outcome variables, child security of attachment and dependency. Two submodels based on predictors of these two outcomes reveal a number of pathways along which these effects take place. We conclude with a brief discussion of the lessons learned that might strengthen future studies of mother-child bonding and, more generally, the intergenerational transmission of bonding traits.

Comparison of the simple breeding value model and the maternal effects model for genetic evaluation of Segureña lambs

AbstractWeaning weight in a single flock of 600 ewes and 40 rams was simulated through 30 consecutive lambings. The objective was to compare the simple breeding value model with the maternal effects model for lamb evaluation under the Segureña selection scheme. Three selection strategies were tested: selection on breeding values estimated by a simple breeding value model that ignores maternal effects (method 1), selection on direct additive values only (method 2) or on the sum of direct and maternal additive values (method 3), both latter methods utilizing a maternal effects model. Average values obtained in the last lamb crop were about 18 kg for the phenotypic mean, about 5 kg for direct additive values and about -1 kg for maternal additive values, for all three methods. Average inbreeding coefficient of the last crop was more than 0·13 in method 1 but was less than 0·12 in the others. All differences were not statistically significant (P &gt; 0·05). Consequently, the simple breeding value model can be used for the genetic evaluation of weaning weight of candidates for selection in the Segureña scheme. The effect of variation in the magnitude of parameters was evaluated through four sets of parameters. Results showed that with a higher additive maternal component, method (3) would become increasingly necessary. The need for method (3) is accentuated with more negative additive covariance between direct and maternal effects. Thus, for higher maternal effects or more negative additive correlation, the use of the complete model (with maternal effects) becomes unavoidable. Varying population size, however, affects only the inbreeding accumulated, as long as the same methods of selection are used.

Estimation of nonadditive genetic variances for a total-merit model including maternal effects

Henderson described a method to reduce the number of mixed-model equations when estimating additive and nonadditive genetic variances or predicting additive and nonadditive genetic merits. The extension to a maternal effects model is straight-forward. When maternal genetic effects are strictly additive, an algebraic identity was found that reduces by a factor of two the order of a matrix that must be inverted each round to account for the genetic covariances among direct and maternal genetic effects. An algorithm for derivative-free restricted maximum likelihood was developed based on Henderson's total-merit model that is the basis for a reduced number of equations. The same values for the logarithm of the likelihood can be calculated from components of the equations for the total-merit model and from components of the equations for the individual effects model. The computational properties of the equations for the total-merit model, however, do not lend themselves to sparse-matrix methods. Both memory and time requirements were much greater for the total-merit model than for the individual-effects model for a data set of 871 animals and a model with additive, dominance, and additive x additive direct and additive maternal genetic effects. Approximately 14 times more memory was required, although the number of equations decreased from 3,773 to 2,031. Computing time per round increased by a factor of 50.

QUANTITATIVE GENETIC MODELS FOR DEVELOPMENT, EPIGENETIC SELECTION, AND PHENOTYPIC EVOLUTION.

Herein we describe a general multivariate quantitative genetic model that incorporates two potentially important developmental phenomena, maternal effects and epigenetic effects. Maternal and epigenetic effects are defined as partial regression coefficients and phenotypic variances are derived in terms of age-specific genetic and environmental variances. As a starting point, the traditional quantitative genetic model of additive gene effects and random environmental effects is cast in a developmental time framework. From this framework, we first extend a maternal effects model to include multiple developmental ages for the occurrence of maternal effects. An example of maternal effects occurring at multiple developmental ages is prenatal and postnatal maternal effects in mammals. Subsequently, a model of intrinsic and epigenetic effects in the absence of maternal effects is described. It is shown that genetic correlations can arise through epigenetic effects, and in the absence of other developmental effects, epigenetic effects are in general confounded with age-specific intrinsic genetic effects. Finally, the two effects are incorporated into the basic quantitative genetic model. For this more biologically realistic model combining maternal and epigenetic effects, it is shown that the phenotypic regressions of offspring on mother and offspring on father can be used in some cases to estimate simultaneously maternal effects and epigenetic effects.