Consequences of incorrect genetic parameter estimates for single-trait and multi-trait genetic evaluations in honeybees

Genetic and residual variances of traits are important input parameters for best linear unbiased prediction (BLUP) breeding value estimation. In honeybees, estimates of these variances are often associated with large standard errors, entailing a risk to perform genetic evaluations under wrong premises. The consequences hereof have not been sufficiently studied. In particular, there are no adequate investigations on this topic accounting for multi-trait selection or genetic peculiarities of the honeybee. We performed simulation studies and explored the consequences of selection for honeybee populations with a broad range of true and assumed genetic parameters. We found that in single-trait evaluations, the response to selection was barely compromised by assuming erroneous parameters, so that reductions in genetic progress after 20 years never exceeded 21%. Phenotypic selection appeared inferior to BLUP selection, particularly under low heritabilities. Parameter choices for genetic evaluation had great effects on inbreeding development. By wrongly assuming high heritabilities, inbreeding rates were reduced by up to 74%. When parallel selection was performed for two traits, the right choice of genetic parameters appeared considerably more crucial as several incorrect premises yielded inadvertent negative selection for one of the traits. This phenomenon occurred in multiple constellations in which the selection traits expressed a negative genetic correlation. It was not reflected in the estimated breeding values. Our results indicate that breeding efforts heavily rely on detailed knowledge on genetic parameters, particularly when multi-trait selection is performed. Thus, considerable effort should be invested into precise parameter estimations.

Genetic and non-genetic parameter estimates for growth traits and Kleiber ratios in Dorper × indigenous sheep

Genetic improvement programme will only be successful when accompanied by a good understanding of the influence of different environmental factors, knowledge of the genetic parameters and the genetic relationships between the traits of interest. This study aimed to evaluate the influence of non-genetic factors on growth traits and Kleiber ratios and to estimate genetic parameters for early growth traits in Dorper × indigenous crossbred sheep. The effects of fixed factors were analysed by the general linear model procedure of statistical analysis system, while the genetic parameters were estimated using a WOMBAT computer program fitted animal model. The overall least-square mean for birth weight (BRW), weaning weight (3MW), six-month weight, nine-month weight, and yearling weight were 3.03 ± 0.02, 14.5 ± 0.18, 20.4 ± 0.26, 24.8 ± 0.31, and 28.3 ± 0.40 kg, respectively. The overall least-square mean for Kleiber ratio from birth to weaning (KR1), weaning to six months, six to nine months and nine months to yearling age were 16.8 ± 0.10, 6.41 ± 0.17, 4.55 ± 0.21 and 3.38 ± 0.20 g/kg of metabolic weight, respectively. The inclusion of maternal genetic effect had a significant influence on BRW, and it explains 20% of the phenotypic variation. The total heritability estimates for BRW, 3MW, birth to weaning average daily weight gain and KR1 were 0.10, 0.14, 0.16 and 0.12, respectively. The phenotypic correlation varied from -0.11 ± 0.05 to 0.98 ± 0.02, whereas the direct genetic correlation ranged from -0.32 ± 0.40 to 0.98 ± 0.17. The mean inbreeding coefficient was 0.105% with an annual rate of 0.02%. The heritability estimates for growth traits and Kleiber ratio suggest that slow genetic progress would be expected from the selection. However, the integration of selection with crossbreeding programme can enhance genetic gain. Therefore, selection should be conducted based on breeding values estimated from multiple information sources to increase the selection response.

On the modelling of weights of kids to enhance growth in a local goat population under Tunisian arid conditions: the maternal effects

To provide the local goat population with an adequate breeding scheme under an arid environment, this study aimed to evaluate the use of alternative models attempting to dissect the additive genetic (AG) and permanent environmental (PE) components of direct and maternal effects on weights of kids up to weaning. Records of 903 local kids over a period of 16 years were used in this study. Data were split into four groups corresponding to four periods along weight recording. Periods 1/2/3/4 contained weights in an interval with upper-lower limits of 1-20/25-60/65-120/125-150 days of age. Models including or ignoring maternal genetic or permanent environmental effects were fitted for all traits. For all periods, the best models were those including the AG component for both direct and maternal effects and the direct PE effect. Heritability estimates of both the direct and maternal effects ranged from low (0.02 for maternal heritability in P1) to moderate (0.17 for direct and maternal heritability in P2 and P3). Period 1 showed the lowest values for heritability of both direct and maternal effects, with also the largest estimate of the ratio of residual to total variance (around 0.2) compared with the other periods, with decreasing ratios as age increased (from 0.13 for P2 to 0.07 for P4). Both direct and maternal estimated breeding values (EBVs) showed high correlations for models fitting direct AG and PE (DGP) effects. For direct EBVs (DEBVs), correlations were above 0.99, indicating that the same animals are expected to be selected under any model that includes those components, regardless of the maternal effects included. For maternal EBVs, correlations were also high, but slightly lower than for the DEBVs between models including DGP effects and maternal genetic effects. Overall, our recommendation for genetic evaluations of direct and maternal effects in this population raised in extensive and harsh conditions is to use weight records preferably collected during the period of high milk production of dams, for which direct and maternal effects are expected to show full expression. Complete pedigrees and several generations of dam-progeny recording are needed to obtain a proper separation of environmental and genetic components.

The impact of direct-maternal genetic correlations on international beef cattle evaluations for Limousin weaning weight

In beef cattle maternally influenced traits, estimates of direct-maternal genetic correlations (r_dm) are usually reported to be negative. In international evaluations, r_dm can differ both within countries (r_{dm_WC}) and between countries (r_{dm_BC}). The r_{dm_BC} are difficult to estimate and are assumed to be zero in the current model for international beef cattle evaluations (Interbeef). Our objective was to investigate re-ranking of international estimated breeding values (IEBVs) in international beef cattle evaluations between models that either used estimated values for r_dm or assumed them to be 0. Age-adjusted weaning weights and pedigree data were available for Limousin beef cattle from ten European countries. International EBVs were obtained using a multi-trait animal model with countries modeled as different traits. We compared IEBVs from a model that uses estimated r_{dm_BC} (ranging between −0.14 and +0.14) and r_{dm_WC} (between −0.33 and +0.40) with IEBVs obtained either from the current model that assumes r_{dm_BC} to be 0, or from an alternative model that assumes both r_{dm_BC} and r_{dm_WC} to be 0. Direct and maternal IEBVs were compared across those three scenarios for different groups of animals. The ratio of population accuracies from the linear regression method was used to further investigate the impact of r_dm on international evaluations, for both the whole set of animals in the evaluation and the domestic ones. Ignoring r_{dm_BC}, i.e., replacing estimated values with 0, resulted in no (rank correlations > 0.99) or limited (between 0.98 and 0.99) re-ranking for direct and maternal IEBVs, respectively. Both r_{dm_BC} and r_{dm_WC} had less impact on direct IEBVs than on maternal IEBVs. Re-ranking of maternal IEBVs decreased with increasing reliability. Ignoring r_{dm_BC} resulted in no re-ranking for sires with IEBVs that might be exchanged across countries and limited re-ranking for the top 100 sires. Using estimated r_{dm_BC} values instead of considering them to be 0 resulted in null to limited increases in population accuracy. Ignoring both r_{dm_BC} and r_{dm_WC} resulted in considerable re-ranking of animals’ IEBVs in all groups of animals evaluated. This study showed the limited impact of the current practice of ignoring r_{dm_BC} in international evaluations for Limousin weaning weight, most likely because the estimated r_{dm_BC} was close to 0. We expect that these conclusions can be extended to other traits that have reported r_dm values in the range of r_{dm_WC} values for weaning weight in Limousin.

Maternal effect on body measurement and meat production traits in purebred Duroc pigs

We investigated maternal effect on nine body measurement traits (body height, body length, front width (FW), chest width (CW), hind width (HW), chest depth, chest girth (CHG), front cannon circumference (FCC) and rear cannon circumference (RCC)) measured at the end of performance testing and five meat production traits (ages at the start and end of performance testing (D30 and D105), average daily gain (ADG), backfat thickness and loin muscle area) in purebred Duroc pigs. Genetic parameters for each trait were estimated by using six single-trait models with and without common litter environmental effect, maternal genetic effect and direct-maternal genetic correlation. The value of Akaike's information criterion was lowest with the model including direct additive genetic and common litter environmental effects for 10 traits. The estimated proportion of common litter environmental variance to phenotypic variance was approximately ≥0.1 for D30, D105, ADG, FW, CW, HW, CHG, FCC and RCC. Using a model without common litter environmental effect would overestimate the direct heritability of most traits. Standard errors of estimated genetic parameters tended to be larger in models including maternal genetic effect. The results indicate that a compromise could be made for accurate genetic parameter estimation for body measurement traits, as well as meat production traits, in pigs by considering common litter environmental effect.

Estimates of variance components and heritability using different animal models for growth, backfat, litter size, and healthy birth ratio in Large White pigs

This study compared the estimates of variance components using various animal models for Large White pigs. The traits included three production traits, birth weight (BW), age at 100 kg (Age_100), and backfat thickness at 100 kg (BF_100), and two reproduction traits, number of total born (NTB) and the ratio of healthy births (RHB). Five models including or ignoring common litter environmental effects, maternal effects, and the direct-maternal covariance (σam) were used for this study. The results showed that the model including all terms, or including all terms except σam, yielded the best-fitting result. The direct variance and heritability were overestimated when the model ignored all previously listed effects, especially for production traits. When all terms were modeled, the direct heritability estimates ([Formula: see text] ± standard error) were 0.038 ± 0.008, 0.216 ± 0.022, 0.416 ± 0.023, 0.066 ± 0.013, and 0.049 ± 0.007 for BW, Age_100, BF_100, NTB, and RHB, respectively. The common litter effects reached statistical significance for all traits, and maternal heritability reached statistical significance for three production traits. The direct-maternal correlations were negative for all traits but only reached statistical significance for BW. These results indicate that using a more complex model may result in more accurate estimation of variance components in Large White pigs.

The importance of controlled mating in honeybee breeding

BACKGROUND

Controlled mating procedures are widely accepted as a key aspect of successful breeding in almost all animal species. In honeybees, however, controlled mating is hard to achieve. Therefore, there have been several attempts to breed honeybees using free-mated queens. In such breeding schemes, selection occurs only on the maternal path since the drone sires are random samples of the population. The success rates of breeding approaches without controlled mating have so far not been investigated on a theoretical or simulation-based level.

METHODS

Stochastic simulation studies were carried out to examine the chances of success in honeybee breeding with and without controlled mating. We investigated the influence of different sizes of breeding populations (500, 1000, 2000 colonies per year) and unselected passive populations (0, 500, 1000, 2000, infinitely many colonies per year) on selection for a maternally (queen) and directly (worker group) influenced trait with moderate ([Formula: see text]) or strong ([Formula: see text]) negative correlation between the two effects. The simulations described 20 years of selection.

RESULTS

Our simulations showed a reduction of breeding success between 47 and 99% if mating was not controlled. In the most drastic cases, practically no genetic gain could be generated without controlled mating. We observed that in the trade-off between selection for direct or maternal effects, the absence of mating control leads to a shift in favor of maternal effects. Moreover, we describe the implications of different breeding strategies on the unselected passive population that benefits only indirectly via the transfer of queens or drones from the breeding population. We show that genetic gain in the passive population develops parallel to that of the breeding population. However, we found a genetic lag that became significantly smaller as more breeding queens served as dams of queens in the passive population.

CONCLUSIONS

We conclude that even when unwanted admixture of subspecies can be excluded in natural matings, controlled mating is imperative for successful breeding efforts. This is especially highlighted by the strong positive impact that controlled mating in the breeding population has on the unselected passive population.

Genetic variances and covariances of live weight traits in Charolais cattle by multi-trait analysis

Live weight traits are economically important for beef cattle production systems. Genetic analysis of live weight traits frequently presents a problem due to animal records, in that matter, not all the animals have complete records as many young animals leave the herd because of sale, transfer to another herd, or culling reasons. Therefore, the use of multi-trait genetic analysis might be of assistance to help overcome any possible loss of information for those animals with incomplete records. In this study, genetic variances and covariances were obtained to estimate genetic parameters for birth (BW), weaning (WW), and yearling (YW) live weights in a registered Charolais beef cattle population using a multivariate model, where a considerable reduction of data from birth weight to year weight was observed. Direct and maternal heritabilities for BW, WW, and YW were 0.50, 0.30, and 0.28, and 0.31, 0.25, and 0.14, respectively. Direct and maternal genetic correlations were negative in all live weight traits. Genetic correlations among direct BW with direct WW and YW were low, while genetic correlations among maternal traits were medium or high (r>0.39). Comparison between univariate and multi-trait models with substantial reduction of information revealed important differences, implying that multi-trait analysis is better for the structure of data allowing a better fitting of genetic effects by covariance among evaluated traits. Results support multi-trait analysis implementation for genetic evaluations for live weight traits of Charolais cattle.

Estimating direct genetic and maternal effects affecting rabbit growth and feed efficiency with a factorial design

The aim of this experiment was to evaluate the significance of neonatal environment on feed efficiency. For that purpose, rabbits from a line selected for residual feed intake (RFI) during 10 generations (G10 kits) were cross-fostered with non-selected control does (i.e., G0 line), and reciprocally. In parallel, sibs were fostered by mothers from their original line. Nine hundred animals were raised in individual (N = 456) or collective (N = 320) cages. Traits analysed in this study were body weight at 32 days and at 63 days, average daily gain (ADG), feed intake between weaning and 63 days (FI), feed conversion ratio (FCR) and RFI. The maternal environment offered by does from the line selected for RFI deteriorated the FCR of the kits, independently of their line of origin, during fattening (+0.08 ± 0.02) compared to FCR of kits nursed by G0 does. The line, the type of housing and the batch were significant effects for all the measured traits: G10 kits were lighter than their G0 counterparts at 32 days (-82.9 ± 9 g, p < 0.0001) and at 63 days (-161 ± 16 g, p < 0.0001). They also had a lower ADG (-2.36 ± 0.36 g/day, p < 0.0001), RFI (-521 ± 24 g/day, p < 0.0001) and a lower FI (-855 ± 31 g, p < 0.0001), resulting in a more desirable feed efficiency (FCR: -0.35 ± 0.02). There was no significant difference in the contrast of G10 and G0 performances between collective and individual/digestive cages (p > 0.22): -2.35 g/day versus 2.94 g/day for ADG, -0.39 versus -0.40 for FCR, -577 g versus -565 g for RFI and -879 g versus -859 g for FI, respectively). Thus, no genotype-by-environment (housing) interaction is expected at the commercial level, that is, no re-ranking of the animals due to collective housing.

Genetic Parameters for Resistance to Non-specific Diseases and Production Traits Measured in Challenging and Selection Environments; Application to a Rabbit Case

Breeding for disease resistance is a challenging but increasingly necessary objective to overcome the issues with the reduced use of antibiotics and growing concern for animal welfare while limiting economic losses. However, implementing such strategies is a complex process because animals face numerous diseases, and the environments on selection farms differ from those on commercial farms. We evaluated whether selection for resistance to non-specific diseases based on a single visual record in selection (S) and challenging (Ch) environments is possible. Records from 23,773 purebred rabbits born between 2012 and 2016 were used in this study. After weaning (at 32 days of age), 17,712 rabbits were raised in the S environment and 6,061 sibs were raised in the Ch environment. Clinical signs of disease were recorded for all animals at the end of the test, at a single time point, at 70 or 80 days of age. The causes of mortality occurring before the end of the test were also recorded. Three disease traits were analyzed: signs of respiratory disease, signs of digestive disease, and a composite trait (Resist) taking into account signs of digestive, respiratory and various infectious diseases. This latter composite trait is proposed to capture the global resistance to disease. All disease traits were binary, with 0 being the absence of symptoms. Two production traits were also recorded: the number of kits born alive (4,121 litters) and the weaning weight (13,090 rabbits). Disease traits were analyzed with animal threshold models, assuming that traits are different in the two environments. Bivariate analyses were carried out using linear animal models. The heritabilities of the disease traits ranged from 0.04 ± 0.01 to 0.11 ± 0.03. The genetic correlations between disease traits in both environments were below unity (≤ 0.84), indicating genotype by environment interactions. Most of the genetic correlations between disease and production traits were not significantly different from zero, except between the weaning weight and Resist_S, with a favorable correlation of -0.34 ± 0.12. Given these genetic parameters, for the same level of exposure of rabbits to pathogens, the expected response to selection is a reduction of disease incidence of 4-6% per generation.

Genetic trends and trade-offs between growth and reproductive traits in a Nellore herd

The knowledge of genetic trends and trade-offs between growth and reproductive traits might be useful to understand the evolution of these traits in livestock and natural populations of animals. We estimated the genetic trends and trade-offs between pre-weaning growth and calving intervals of Nellore animals from a commercial farm. Two-trait animal models were used to estimate covariance components and breeding values (EBV) for direct and maternal genetic effects of pre-weaning growth and direct genetic effects of calving intervals. Regression analyses were performed to examine the relationship between direct and maternal EBV of pre-weaning growth and direct EBV of calving intervals (dependent variables) and the coefficient of generation of each animal (independent variable). We also performed regression analyses to examine the relationship between direct EBV of calving intervals (dependent variables) and direct and maternal EBV of pre-weaning growth (independent variables). The genetic trends for direct and maternal genetic effect for pre-weaning growth were significant and presented genetic evolution in the studied Nellore herd. The genetic trends for the reproductive traits were also significant but indicated genetic changes in an unfavorable way. The genetic correlations between direct effects of pre-weaning growth and calving intervals traits and the genetic correlations between maternal effects of pre-weaning growth traits and direct effects of calving interval traits were not different from zero. The presence of trade-offs between the direct effects of growth and reproductive traits were confirmed through regression from direct EBV of calving intervals over EBV of pre-weaning growth traits. In addition, regression analyses showed that selection to increase pre-weaning growth also increased calving intervals. Our results showed that pre-weaning growth and calving intervals are increasing over generations and that trade-offs occurred between those traits in the studied Nellore herd.

The phenotypic correlates and quantitative genetics of masculinization in the rodent, Octodon degus

In some mammals, female characteristics have been shown to depend, in part, on the intrauterine position during development of female fetuses relative to male fetuses. Females developing in close proximity to males show behavioral, physiological and life history characteristics that are masculinized. With the exception of one inconclusive study, nothing is known of the genetic basis of this phenomenon. In this paper, we reported an analysis of the quantitative genetic basis of masculinization, as indicated by the anogenital distance (AGD) at birth and weaning, in the rodent Octodon degus. Because AGD is related to weight, we included a genetic analysis of pup weight at birth and weaning. Pairwise correlations showed that AGD at birth varied negatively with litter size and parturition number but positively with weaning AGD, birth weight, dam AGD and percentage of males in the litter. AGD at weaning varied similarly except that it tended to vary positively with litter size. Genetic (co)variances of AGD at birth and weight at birth differed in females and males. In females, the best genetic model included substantial effects of direct additive, additive maternal and a negative additive genetic covariance between these two. In males, variances were small and there was difficulty in discriminating between additive maternal and common environmental variances. By weaning, genetic (co)variances had somewhat declined in weight and were not statistically significant in AGD in either sex. This paper showed the occurrence of both phenotypic and genetic components in masculinization with effects being greater in females.

Bayesian inference of genetic parameters for ultrasound scanning traits of Kivircik lambs

Ultrasound scanning traits have been adapted in selection programs in many countries to improve carcass traits for lean meat production. As the genetic parameters of the traits interested are important for breeding programs, the estimation of these parameters was aimed at the present investigation. The estimated parameters were direct and maternal heritability as well as genetic correlations between the studied traits. The traits were backfat thickness (BFT), skin+backfat thickness (SBFT), eye muscle depth (MD) and live weights at the day of scanning (LW). The breed investigated was Kivircik, which has a high quality of meat. Six different multi-trait animal models were fitted to determine the most suitable model for the data using Bayesian approach. Based on deviance information criterion, a model that includes direct additive genetic effects, maternal additive genetic effects, direct maternal genetic covariance and maternal permanent environmental effects revealed to be the most appropriate for the data, and therefore, inferences were built on the results of that model. The direct heritability estimates for BFT, SBFT, MD and LW were 0.26, 0.26, 0.23 and 0.09, whereas the maternal heritability estimates were 0.27, 0.27, 0.24 and 0.20, respectively. Negative genetic correlations were obtained between direct and maternal effects for BFT, SBFT and MD. Both direct and maternal genetic correlations between traits were favorable, whereas BFT-MD and SBFT-MD had negligible direct genetic correlation. The highest direct and maternal genetic correlations were between BFT and SBFT (0.39) and between MD and LW (0.48), respectively. Our results, in general, indicated that maternal effects should be accounted for in estimation of genetic parameters of ultrasound scanning traits in Kivircik lambs, and SBFT can be used as a selection criterion to improve BFT.