The contribution of dominance and inbreeding depression in estimating variance components for litter size in Pannon White rabbits

Bayesian analysis of genetic and environmental effects on litter traits in a red fox (Vulpes vulpes) herd under long-term selection

The economic efficiency of fur animal farms is considerably influenced by reproductive performance. The objectives of this study are to determine the effects of individual and maternal inbreeding, birth year, and dam and sire age on litter size at birth (LSB) and at weaning (LSW) and on preweaning mortality (PWM) in a red fox herd under long-term selection, and to determine the heritability of these traits. In total, 37,973 pedigreed individuals were used to calculate the inbreeding coefficients, based on records of 14,527 litters of 3856 dams born from the year 1958 to 2015. Two data sets (all data and data for the Polish variety) were analyzed. The highest heritability was estimated for PWM (0.292, 0.306) and the lowest for LSW (0.114, 0.115). In contrast to paternal and maternal inbreeding, litter inbreeding was found to exert a significant influence. The absence of significant effects of most varieties may suggest relatively large genetic similarity in the world red fox population. This corresponds with the similarity of the results obtained for the total herd and for the Polish variety. Favorable genetic trends were observed for the studied traits, indicating that the selection applied had been a relatively effective approach to improving these traits.

Heritability and genetic correlation estimates of semen production traits with litter traits and pork production traits in purebred Duroc pigs

We estimated heritabilities of semen production traits and their genetic correlations with litter traits and pork production traits in purebred Duroc pigs. Semen production traits were semen volume, sperm concentration, proportion of morphologically normal sperms, total number of sperm, and total number of morphologically normal sperm. Litter traits at farrowing were total number born, number born alive, number stillborn, total litter weight at birth, mean litter weight at birth, and piglet survival rate at birth. Litter traits at weaning were litter size at weaning, total litter weight at weaning, mean litter weight at weaning, and piglet survival rate from birth to weaning. Pork production traits were average daily gain, backfat thickness, and loin muscle area. We analyzed 45,913 semen collection records of 896 boars, 6,950 farrowing performance records of 1,400 sows, 2,237 weaning performance records of 586 sows, and individual growth performance records of 9,550 animals measured at approximately 5 mo of age. Heritabilities were estimated using a single-trait animal model. Genetic correlations were estimated using a 2-trait animal model. Estimated heritabilities of semen production traits ranged from 0.20 for sperm concentration to 0.29 for semen volume and were equal to or higher than those of litter traits, ranging from 0.06 for number stillborn and piglet survival rate at birth to 0.25 for mean litter weight at birth, but lower than those of pork production traits, ranging from 0.50 for average daily gain to 0.63 for backfat thickness. In many cases, the absolute values of estimated genetic correlations between semen production traits and other traits were smaller than 0.3. These estimated genetic parameters provide useful information for establishing a comprehensive pig breeding scheme.

Genetic parameters of 5 semen production traits, 10 litter traits, and 3 pork production traits in purebred Duroc pigs was estimated. Heritabilities of semen production traits ranged from 0.20 for sperm concentration to 0.29 for semen volume and were equal to or higher than those of litter traits, ranging from 0.06 for number stillborn and piglet survival rate at birth to 0.25 for mean litter weight at birth, but lower than those of pork production traits, ranging from 0.50 for average daily gain to 0.63 for backfat thickness. In many cases, the absolute values of genetic correlations between semen production traits and other traits were smaller than 0.3. These estimated genetic parameters provide useful information for establishing a comprehensive pig breeding scheme.

How Depressing Is Inbreeding? A Meta-Analysis of 30 Years of Research on the Effects of Inbreeding in Livestock

Inbreeding depression has been widely documented for livestock and other animal and plant populations. Inbreeding is generally expected to have a stronger unfavorable effect on fitness traits than on other traits. Traditionally, the degree of inbreeding depression in livestock has been estimated as the slope of the linear regression of phenotypic values on pedigree-based inbreeding coefficients. With the increasing availability of SNP-data, pedigree inbreeding can now be replaced by SNP-based measures. We performed a meta-analysis of 154 studies, published from 1990 to 2020 on seven livestock species, and compared the degree of inbreeding depression (1) across different trait groups, and (2) across different pedigree-based and SNP-based measures of inbreeding. Across all studies and traits, a 1% increase in pedigree inbreeding was associated with a median decrease in phenotypic value of 0.13% of a trait’s mean, or 0.59% of a trait’s standard deviation. Inbreeding had an unfavorable effect on all sorts of traits and there was no evidence for a stronger effect on primary fitness traits (e.g., reproduction/survival traits) than on other traits (e.g., production traits or morphological traits). p-values of inbreeding depression estimates were smaller for SNP-based inbreeding measures than for pedigree inbreeding, suggesting more power for SNP-based measures. There were no consistent differences in p-values for percentage of homozygous SNPs, inbreeding based on runs of homozygosity (ROH) or inbreeding based on a genomic relationship matrix. The number of studies that directly compares these different measures, however, is limited and comparisons are furthermore complicated by differences in scale and arbitrary definitions of particularly ROH-based inbreeding. To facilitate comparisons across studies in future, we provide the dataset with inbreeding depression estimates of 154 studies and stress the importance of always reporting detailed information (on traits, inbreeding coefficients, and models used) along with inbreeding depression estimates.

Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods

The aim of this study was to compare the predictive performance of the Genomic Best Linear Unbiased Predictor (GBLUP) and machine learning methods (Random Forest, RF; Support Vector Machine, SVM; Artificial Neural Network, ANN) in simulated populations presenting different levels of dominance effects. Simulated genome comprised 50k SNP and 300 QTL, both biallelic and randomly distributed across 29 autosomes. A total of six traits were simulated considering different values for the narrow and broad-sense heritability. In the purely additive scenario with low heritability (h2 = 0.10), the predictive ability obtained using GBLUP was slightly higher than the other methods whereas ANN provided the highest accuracies for scenarios with moderate heritability (h2 = 0.30). The accuracies of dominance deviations predictions varied from 0.180 to 0.350 in GBLUP extended for dominance effects (GBLUP-D), from 0.06 to 0.185 in RF and they were null using the ANN and SVM methods. Although RF has presented higher accuracies for total genetic effect predictions, the mean-squared error values in such a model were worse than those observed for GBLUP-D in scenarios with large additive and dominance variances. When applied to prescreen important regions, the RF approach detected QTL with high additive and/or dominance effects. Among machine learning methods, only the RF was capable to cover implicitly dominance effects without increasing the number of covariates in the model, resulting in higher accuracies for the total genetic and phenotypic values as the dominance ratio increases. Nevertheless, whether the interest is to infer directly on dominance effects, GBLUP-D could be a more suitable method.

Inbreeding depression for kit survival at birth in a rabbit population under long-term selection

Background

Accumulation of detrimental mutations in small populations leads to inbreeding depression of fitness traits and a higher frequency of genetic defects, thus increasing risk of extinction. Our objective was to quantify the magnitude of inbreeding depression for survival at birth, in a closed rabbit population under long-term selection.

Methods

We used an information theory-based approach and multi-model inference to estimate inbreeding depression and its purging with respect to the trait ‘kit survival at birth’ over a 25-year period in a closed population of Pannon White rabbits, by analysing 22,718 kindling records. Generalised linear mixed models based on the logit link function were applied, which take polygenic random effects into account.

Results

Our results indicated that inbreeding depression occurred during the period 1992–1997, based on significant estimates of the z-standardised classical inbreeding coefficient z.F_L (CI_95% − 0.12 to − 0.03) and of the new inbreeding coefficient of the litter z.F_NEWL (CI_95% − 0.13 to − 0.04) as well as a 59.2% reduction in contributing founders. Inbreeding depression disappeared during the periods 1997–2007 and 2007–2017. For the period 1992–1997, the best model resulted in a significantly negative standardised estimate of the new inbreeding coefficient of the litter and a significantly positive standardised estimate of Kalinowski’s ancestral inbreeding coefficient of the litter (CI_95% 0.01 to 0.17), which indicated purging of detrimental load. Kindling season and parity had effects on survival at birth that differed across the three periods of 1992–1997, 1997–2007 and 2007–2017.

Conclusions

Our results support the existence of inbreeding depression and its purging with respect to kit survival at birth in this Pannon White rabbit population. However, we were unable to exclude possible confounding from the effects of parity and potentially other environmental factors during the study period, thus our results need to be extended and confirmed in other populations.

Estimation of additive and non-additive genetic variance component for growth traits in Adani goats

Non-additive genetic effects are important to increase the accuracy of estimating genetic parameters for growth traits. The aim of this study was to estimate genetic parameters and variance components, specially dominance and epistasis genetic effects, for growth traits (birth weight (BW), weaning weight (WW), 3 (W3), 6 (W6), 9 (W9), and 12 (W12) month weight) in Adani goats. Analyses were carried out using Bayesian method via Gibbs sampler animal model by fitting of 18 different models. All fixed effects (sex, type of birth, age of dam, and year) showed significant effects on BW, WW, W3, and W6, whereas the type of birth and age of dam were not significant on W9 and W12. With the best model, direct heritability estimates were 0.347, 0.178, 0.158, 0.359, 0.278, and 0.281 for BW, WW, W3, W6, W9, and W12 traits, respectively. Maternal permanent environmental effect was significant for BW and WW, but maternal genetic effect was significant only for W3. Dominance and epitasis effects were significant almost for all traits and as a proportion of phenotypic variance were ranged from 0.115 to 0.258 and 0.107 to 0.218, respectively. The range of accuracy of breeding values estimated for growth traits with appropriate evaluation models was from 0.521 to 0.652, 0.616 to 0.694, and 0.548 to 0.684 for the all animals, 10% of the best males and 50% of the best females, respectively. When dominance and epistasis effects added to models, the error variance was reduced and the accuracy of estimated breeding values increased. The accuracy of the best model showed a significant difference with the accuracy of other models (p < 0.01). The result of the present study suggests that non-additive genetic effects should be in genetic evaluation models for goat growth traits because of its effect on accuracy of estimated breeding values.

Inbreeding depression load for litter size in Entrepelado and Retinto Iberian pig varieties1

Individual-specific hidden inbreeding depression load (IDL) can be accounted for in livestock populations by appropriate best linear unbiased prediction approaches. This genetic effect has a recessive pattern and reveals when inherited in terms of identity-by-descent. Nevertheless, IDL inherits as a pure additive genetic background and can be selected using standard breeding values. The main target of this research was to evaluate IDL for litter size in 2 Iberian pig varieties (Entrepelado and Retinto) from a commercial breeding-stock. Analyses were performed on the total number of piglets born (both alive and dead) and used data from 3,200 (8.02 ± 0.04 piglets/litter) Entrepelado and 4,744 Retinto litters (8.40 ± 0.03 piglets/litter). Almost 50% of Entrepelado sows were inbred (1.7% to 25.0%), whereas this percentage reduced to 37.4% in the Retinto variety (0.2% to 25.0%). The analytical model was solved by Bayesian inference and accounted for 2 systematic effects (sow age and breed/variety of the artificial insemination boar), 2 permanent environmental effects (herd-year-season and sow), and 2 genetic effects (IDL and infinitesimal additive). In terms of posterior means (PM), additive genetic and IDL variances were similar in the Entrepelado variety (PM, 0.68 vs. 0.76 piglets2, respectively) and their 95% credibility intervals (95CI) overlapped, although without including zero (0.38 to 0.94 vs. 0.15 to 1.31 piglets2, respectively). The same pattern revealed in the Retinto variety, with IDL variance (PM, 0.41 piglets2; 95CI, 0.07 to 0.88 piglets2) slightly larger than the additive genetic variance (PM, 0.37 piglets2; 95CI, 0.16 to 0.59 piglets2). The relevance of IDL was also checked by a Bayes factor and the deviance information criterion, the model including this effect being clearly favored in both cases. Although the analysis assumed null genetic covariance between IDL and infinitesimal additive effects, a moderate negative correlation (-0.31) was suggested when plotting the PM of breeding values in the Entrepelado variety; a negative genetic trend for IDL was also revealed in this Iberian pig variety (-0.25 piglets for 100% inbred offspring of individuals born in 2014), whereas no trend was detected in Retinto breeding-stock. Those were the first estimates of IDL in a commercial livestock population, they giving evidence of a relevant genetic background with potential consequences on the reproductive performance of Iberian sows.

Analysis of the impact of cytoplasmic and mitochondrial inheritance on litter size and carcass in rabbits

<p>The effects of mitogenome variation on economically important traits have been reported in a number of domestic animal species. In this study, the first of its kind on rabbits, we have performed the estimation of the contribution of cytoplasmic and D-loop mitochondrial DNA (mtDNA) sequence effects on the litter size and carcass traits in three Pannon rabbit breeds (Pannon Ka, Pannon Large and Pannon White). The observed effects of both estimates, coming from cytoplasmic or D-loop mtDNA variation, were negligible. The most likely explanation for the results obtained is the lack of mitogenome polymorphism in all three populations, as suggested from the analysis performed on the D-loop mtDNA sequence, here assigned to the two most frequent rabbit haplotypes. The extent of potential benefits of the introduction, or alteration, of mitogenome variation in rabbit breeding remains an open question for future research.</p>

Detecting the dominance component of heritability in isolated and outbred human populations

Inconsistencies between published estimates of dominance heritability between studies of human genetic isolates and human outbred populations incite investigation into whether such differences result from particular trait architectures or specific population structures. We analyse simulated datasets, characteristic of genetic isolates and of unrelated individuals, before analysing the isolate of Cilento for various commonly studied traits. We show the strengths of using genetic relationship matrices for variance decomposition over identity-by-descent based methods in a population isolate and that heritability estimates in isolates will avoid the downward biases that may occur in studies of samples of unrelated individuals; irrespective of the simulated distribution of causal variants. Yet, we also show that precise estimates of dominance in isolates are demonstrably problematic in the presence of shared environmental effects and such effects should be accounted for. Nevertheless, we demonstrate how studying isolates can help determine the existence or non-existence of dominance for complex traits, and we find strong indications of non-zero dominance for low-density lipoprotein level in Cilento. Finally, we recommend future study designs to analyse trait variance decomposition from ensemble data across multiple population isolates.

Genomic selection models for directional dominance: an example for litter size in pigs

Background

The quantitative genetics theory argues that inbreeding depression and heterosis are founded on the existence of directional dominance. However, most procedures for genomic selection that have included dominance effects assumed prior symmetrical distributions. To address this, two alternatives can be considered: (1) assume the mean of dominance effects different from zero, and (2) use skewed distributions for the regularization of dominance effects. The aim of this study was to compare these approaches using two pig datasets and to confirm the presence of directional dominance.

Results

Four alternative models were implemented in two datasets of pig litter size that consisted of 13,449 and 11,581 records from 3631 and 2612 sows genotyped with the Illumina PorcineSNP60 BeadChip. The models evaluated included (1) a model that does not consider directional dominance (Model SN), (2) a model with a covariate b for the average individual homozygosity (Model SC), (3) a model with a parameter λ that reflects asymmetry in the context of skewed Gaussian distributions (Model AN), and (4) a model that includes both b and λ (Model Full). The results of the analysis showed that posterior probabilities of a negative b or a positive λ under Models SC and AN were higher than 0.99, which indicate positive directional dominance. This was confirmed with the predictions of inbreeding depression under Models Full, SC and AN, that were higher than in the SN Model. In spite of differences in posterior estimates of variance components between models, comparison of models based on LogCPO and DIC indicated that Model SC provided the best fit for the two datasets analyzed.

Conclusions

Our results confirmed the presence of positive directional dominance for pig litter size and suggested that it should be taken into account when dominance effects are included in genomic evaluation procedures. The consequences of ignoring directional dominance may affect predictions of breeding values and can lead to biased prediction of inbreeding depression and performance of potential mates. A model that assumes Gaussian dominance effects that are centered on a non-zero mean is recommended, at least for datasets with similar features to those analyzed here.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0374-1) contains supplementary material, which is available to authorized users.

Pedigree-based estimation of covariance between dominance deviations and additive genetic effects in closed rabbit lines considering inbreeding and using a computationally simpler equivalent model

Inbreeding generates covariances between additive and dominance effects (breeding values and dominance deviations). In this work, we developed and applied models for estimation of dominance and additive genetic variances and their covariance, a model that we call "full dominance," from pedigree and phenotypic data. Estimates with this model such as presented here are very scarce both in livestock and in wild genetics. First, we estimated pedigree-based condensed probabilities of identity using recursion. Second, we developed an equivalent linear model in which variance components can be estimated using closed-form algorithms such as REML or Gibbs sampling and existing software. Third, we present a new method to refer the estimated variance components to meaningful parameters in a particular population, i.e., final partially inbred generations as opposed to outbred base populations. We applied these developments to three closed rabbit lines (A, V and H) selected for number of weaned at the Polytechnic University of Valencia. Pedigree and phenotypes are complete and span 43, 39 and 14 generations, respectively. Estimates of broad-sense heritability are 0.07, 0.07 and 0.05 at the base versus 0.07, 0.07 and 0.09 in the final generations. Narrow-sense heritability estimates are 0.06, 0.06 and 0.02 at the base versus 0.04, 0.04 and 0.01 at the final generations. There is also a reduction in the genotypic variance due to the negative additive-dominance correlation. Thus, the contribution of dominance variation is fairly large and increases with inbreeding and (over)compensates for the loss in additive variation. In addition, estimates of the additive-dominance correlation are -0.37, -0.31 and 0.00, in agreement with the few published estimates and theoretical considerations.

Role of inbreeding depression, non-inbred dominance deviations and random year-season effect in genetic trends for prolificacy in closed rabbit lines

In closed rabbit lines selected for prolificacy at the Polytechnic University of Valencia, genetic responses are predicted using BLUP. With a standard additive BLUP model and year-season (YS) effects fitted as fixed, genetic trends were overestimated compared to responses estimated using control populations obtained from frozen embryos. In these lines, there is a confounding between genetic trend, YS effects and inbreeding, and the role of dominance is uncertain. This is a common situation in data from reproductively closed selection lines. This paper fits different genetic evaluation models to data of these lines, aiming to identify the source of these biases: dominance, inbreeding depression and/or an ill-conditioned model due to the strong collinearity between YS, inbreeding and genetic trend. The study involved three maternal lines (A, V and H) and analysed two traits, total born (TB) and the number of kits at weaning (NW). Models fitting YS effect as fixed or random were implemented, in addition to additive genetic, permanent environment effects and non-inbred dominance deviations effects. When YS was fitted as a fixed effect, the genetic trends were overestimated compared to control populations, inbreeding had an apparent positive effect on litter size and the environmental trends were negative. When YS was fitted as random, the genetic trends were compatible with control populations results, inbreeding had a negative effect (lower prolificacy) and environmental trends were flat. The model fitting random YS, inbreeding and non-inbred dominance deviations yielded the following ratios of additive and dominance variances to total variance for NW: 0.06 and 0.01 for line A, 0.06 and 0.00 for line V and 0.01 and 0.08 for line H. Except for line H, dominance deviations seem to be of low relevance. When it is confounded with inbreeding as in these lines, fitting YS effect as random allows correct estimation of genetic trends.

Inbreeding impact on litter size and survival in selected canine breeds

Data obtained from the French Kennel Club and the Fichier National Canin were used to estimate the effect of inbreeding on average litter size and survival in seven French breeds of dog. Depending on the breed, litter sizes were 3.5-6.3 puppies and longevities were 7.7-12.2 years. Estimated heritabilities were 6.0-10.9% for litter size and 6.1-10.1% for survival at 2 years of age. Regression coefficients indicated a negative effect of inbreeding on both individual survival and litter size. Although the impact of baseline inbreeding within breeds appears to be limited, the improper mating of close relatives will reduce biological fitness through significant reduction of litter size and longevity.