Direct Additive Genetic Effects Research Articles

Early growth performance in the Murciano-Granadina goats: insights from genetic and phenotypic analyses

Abstract This study investigates the genetic and phenotypic aspects of early growth performance in the Murciano-Granadina goat breed, using data collected between 2016 and 2022 from a private dairy farm in Ghale-Ganj city, located in the southern area of Kerman province, Iran. Pedigree and data information were collected on several early body weight traits, including birth weight (BW), weaning weight (WW), average daily gain (ADG), Kleiber ratio (KR) and growth efficiency from birth to weaning (GE). Nine univariate animal models included direct additive genetic effects and different combinations of maternal effects were compared by using Akaike information criterion (AIC). Among the tested models, the best genetic analysis model for BW, included direct additive, maternal additive, maternal permanent and maternal temporary environmental effects. The best model for ADG, KR and GE included direct additive, maternal permanent and litter effects. For WW, the best model was determined to be one that included direct additive and maternal additive genetic effects. The estimated direct heritabilities were low values of 0.04, 0.07, 0.08, 0.05 and 0.07 for BW, ADG, KR, GE and WW, respectively. The estimates of genetic correlations among the studied traits were positive and low to high in magnitude which ranged from 0.11 for BW-KR to 0.91 for BW-GE. The phenotypic correlations ranged from 0.03 for KR-WW to 0.87 for ADG-KR. The positive correlations observed among the studied growth traits of the Murciano-Granadina goat breed indicate no negative genetic or phenotypic changes associated with selection for these traits.

78 Estimates of genetic parameters for weight, wool, and carcass traits of Rambouillet sheep

Abstract The Rambouillet sheep breed is the foundation to most western range sheep in the U.S. Through the National Sheep Improvement Program (NSIP), Rambouillet breeders seek to improve economically relevant traits. However, the parameters used in the NSIP genetic evaluation were last estimated two decades ago. Our aim was to re-estimate genetic parameters for body weight (BW), carcass, and wool traits. Data were provided by NSIP, which included BW at birth (BWT; n = 28,817), weaning [WWT; n = 5,633; age: 68 (SD 16) day], early post-weaning [PWTE; n = 23,303; 128 (SD 22) d], late post-weaning [PWTL; n = 7,689; 201 (SD 45) d] and as yearlings [YWT; n = 5,830; 375 (SD 33) d]. Yearling ultrasound scans of 12th rib backfat depth (YCF; n = 2,447) and eye muscle depth (YEMD; n = 2,457) were also available. Yearling wool traits were fiber curvature (YFC; n = 6,009), fiber diameter (YFD; n = 9,880), fiber diameter coefficient of variation (YFDCV; n = 8,803), greasy fleece weight (YGFW; n = 11,859) and staple length (YSL; n = 11,270). The pedigree consisted of 36,297 individuals. Animals with phenotypic records were progeny of 333 sires and 1,727 dams. A succession of univariate animal models was fitted. The most comprehensive model included direct and maternal additive genetic effects, their genetic covariance, and maternal permanent environmental and residual effects. Phenotypes were pre-adjusted for birth-rearing type category and, as covariates, dam age and age at recording. Contemporary group—a concatenation of flock, year, season, management group, sex, and, excluding BWT, recording date—was the only fixed effect fitted in the model. Model selection was based on the log-likelihood ratio test, and Akaike and Bayesian information criteria. The data structure, namely dams and their daughters and granddaughters contributing data, allowed reliable testing of the maternal effect terms. The direct-maternal genetic covariance did not explain variation for any trait (P > 0.18). The most parsimonious model for BW traits included direct and maternal additive genetic, and maternal permanent environmental, effects. For carcass and wool traits, only direct additive genetic effects were included in the final model. Such was unsurprising, as maternal effects often diminish as animals age. For the final models fitted (Table 1), direct heritabilities (± SE) for body weights ranged from 0.14 ± 0.01 (BWT) to 0.38 ± 0.04 (PWTL); the maternal heritabilities ranged from 0.04 ± 0.02 (PWTL; YWT) to 0.13 ± 0.01 (BWT). For carcass traits, direct heritabilities were 0.13 ± 0.04 (YCF) and 0.31 ± 0.05 (YEMD). For wool traits, they ranged from 0.37 ± 0.02 (YSL) to 0.58 ± 0.02 (YFD). These re-estimated parameter values are consistent with those used by NSIP, with the exception of PWTL (greater) and YSL (lower). With genomic data accumulating in Rambouillet, further refinements in parameter estimation are planned.

Maternal genetic effects throughout the life of the dam in Pirenaica beef cattle. A random regression model approach

In beef cattle, dams play a crucial role in shaping the pre- and postnatal environment for the growth of their offspring. Acknowledging the substantial impact of maternal influence on the early development of calves, researchers utilize maternal animal models. These models take into account both maternal genetic and permanent environmental effects, operating under the assumption that these influences remain constant throughout the productive life of the cow. Nevertheless, it cannot be ruled out that these genetic and environmental effects may evolve throughout the lifespan of the cows. Therefore, this study aims to describe the changes in genetic and environmental maternal effects over the productive lifespan of the cows. To accomplish this goal, we utilized random regression models, incorporating the age of the dam effect, maternal genetic effects, and environmental permanent effects using Legendre orthogonal polynomials. Additionaly, the analytical model incorporated a covariate to adjust for the calf’s age at recording, a two-level sex effect, a random herd-year-season effect, and an additive direct genetic effect associated linked to the calf. The dataset comprised information from dams aged between 2 and 16 years, resulting in a final database that comprised weight records of 58 332 calves from 21 673 dams. The average weight at 90 days was 135.0 ± 39.3 kg, and the mean age of the dam at calving was 7.03 ± 3.41 years. We evaluated models incorporating 2, 3, 4, 5, and 6 orthogonal polynomials alongside the standard maternal animal model. Aferward, we selected the model with 5 orthogonal polynomials based on the Akaike Information Criteria (AIC). The Restricted Maximum Likelihood (REML) estimates within this model indicated a direct heritability of around 0.50, and a maternal heritability ranging between 0.15 and 0.25, exhibiting a consistent increase between 4,5 to 13 years. The genetic correlation estimates between direct and maternal genetic effects remained stable at approximately -0.55 across the lifespan of the cows. Furthermore, maternal genetic correlations between different ages of the dam decreased to around 0.7 for more distant age points. The maternal permanent correlations were notably lower, occassionally even reaching negative values, suggesting variability in environmental influence on maternal effects over the productive lifespan of the cow. Finally, the model enables the prediction of breeding values for the maternal genetic effects of the cow across its lifespan, providing opportunities for innovative selection strategies on the maternal side.

Genetic parameters for mesenteric torsion in a pig maternal line

Mesenteric torsion (MT) is a condition characterized by the twisting of intestinal loops, leading to a disruption in blood flow and abdominal distension. Several factors can predispose animals to this condition, which primarily affects healthy, fast-growing pigs and often results in fatal outcomes. Given the absence of studies on the genetic factors associated with this condition, our research aimed to estimate the heritability coefficient for MT and explore the genetic correlations between MT and performance traits in pigs. Our dataset comprised of 43,384 records of pigs from a maternal line from a nucleus farm. These pigs were born between 2010 and 2022 and had recorded information regarding MT status (0 for healthy and 1 for affected animals), weaning weight (WW), as well as pedigree, genotypes, and genomic estimated breeding values (GEBVs) for the following traits: MT status, days to reach 110 kg (D110), feed conversion adjusted to 110 kg (FC110), and backfat thickness adjusted to 110 kg (BT110). In our statistical model, the effects of contemporary group (CG: sex, year, and week of weaning) and the linear covariate WW were considered fixed effects, while the direct additive genetic effect was accounted as random. On average, pigs affected by MT had an age of 104.35 ± 37.75 days, and the condition had an overall herd frequency of 2.46 %. Mesenteric torsion occurred more frequently in female pigs raised in collective pens compared to non-castrated males raised in individual pens. Heritability estimates for MT, using both pedigree (0.13 ± 0.02) and genomic (0.12 ± 0.02) data, were of low magnitude. This suggests that while there is genetic variability associated with MT, a significant portion of this variation is due to environmental variance. The correlation between MT and BT110 GEBVs was of low magnitude (0.05). In contrast, the correlations between GEBVs for MT and both D110 and FC110 were moderate in magnitude (0.22 for both traits). This implies that pigs taking longer to reach 110 kg and those with poorer feed conversion are more likely to develop MT. There is genetic variability for mesenteric torsion in pigs. Selection aimed at improving feed conversion and reducing the age at which pigs reach 110 kg could lead to a decrease in the occurrence of MT within pig populations.

Genetic parameter estimates indicate the possibility of genetic gain by selecting for reproductive traits of females from a commercial tilapia population (Oreochromis niloticus)

This study aimed to verify the possibility of obtaining genetic gain by selecting breeders based on genetic parameter estimates for reproductive performance traits of female tilapia (Oreochromis sp.) from a commercial population. The study was conducted using a database containing information on reproductive traits collected from 2009 to 2021. During the breeding period, the animals were stocked in tanks in a 1:3 male: female ratio. Eggs were collected from the mouth of the females every five days, and the collected eggs were measured in 100 mL beakers to estimate the egg volume. To estimate the variance components and genetic parameters (heritability, correlation, and repeatability), a mixed animal model was used with the fixed effects of the production cycle and breeding tanks, in addition to the additive direct genetic and permanent environmental random effects. The heritability values were 0.26 ± 0.14, 0.18 ± 0.10, 0.15 ± 0.09, and 0.13 ± 0.08 for total egg volume, average egg volume, spawning frequency, and average spawning interval, respectively, with repeatability above 0.43 for all analyzed variables, demonstrating the ability of the evaluated breeds to maintain the same production level during the different cycles. The genetic correlations among the variables were high, with a correlation of −0.99 between the total egg volume and the average spawning interval. Thus, selecting for total egg volume, which had the highest heritability, would result in animals that produce a large volume of eggs and have short spawning intervals.

Sex-specific genetic parameter estimates of body weight in Mazandaran indigenous chickens.

Body weight is an economically important trait in poultry that shows sexual dimorphism (SD). In the present study, variation in SD in Mazandaran native chickens was investigated in terms of the (Co) variance components and genetic parameters of body weight between males and females. Studied traits were body weights at hatch (BW1), 8 weeks (BW8) and 12 weeks of age (BW12). Also, for weight at sexual maturity (WSM) covariance components were only estimated in females. Cross-sex direct and maternal correlations were also estimated for studied traits except for WSM. For this purpose, a deep 21-generation pedigree and body weight data (57,576 BW1, 72,925 BW8, 62,727 BW12 and, 42,496 WSM) were used. Evaluation of SD of body weight was performed using six bivariate animal models with and without considering the genetic and permanent maternal environmental effects under the restricted maximum likelihood method in WOMBAT software. Model with direct additive genetic effects and maternal genetic effects without covariance between them was identified as the best model for BW1 and BW8. The Model including direct additive genetic effects and permanent maternal environmental effects was the best model for BW12 and WSM. Direct heritability (h2 ) estimates for BW1, BW8 and, BW12 were, respectively, 0.05 ± 0.013, 0.17 ± 0.02 and, 0.25 ± 0.03 in males and, 0.05 ± 0.012, 0.15 ± 0.01 and 0.21 ± 0.01 in females. Also, the direct heritability of WSM based on univariate analysis in females was estimated to be 0.40 ± 0.01. Maternal heritability ( ) varied from 0.39 ± 0.01 (BW1) to 0.04 ± 0.009 (BW8) in males, and 0.36 ± 0.10 (BW1) to 0.04 ± 0.006 (BW8) in females. The correlation between direct genetic effects between males and females for BW1 was not significantly different from one. The direct genetic correlation between the two sexes for BW8 and BW12 was significantly different from 1 concluding that these traits are dimorphic in terms of direct genetic effects and therefore independent selection in both sexes is possible.

Estimation of (Co) Variance Components and Genetic Parameters for Pre- and Post-Weaning Growth Traits in Dağlıç Sheep.

The goal of this study was to estimate (co) variance components and genetic parameters for pre- and post-weaning growth traits in Dağlıç sheep, considering the direct additive genetic, maternal genetic, and maternal permanent environmental effects, with different statistical models. The information of 21,735 native Dağlıç lambs born between 2011 and 2021 was used to estimate (co) variance components by the Average Information-Restricted Maximum Likelihood algorithm. The results showed that the most suitable model was Model 3 for birth weight (BW), average daily gain (ADG), and weaning weight (WW). Model 4 was the most appropriate for weight at three (W3), weight at six (W6), and weight at twelve months of age (W12). The direct heritabilities for BW, W3, ADG, WW, W6, and W12 were 0.35 ± 0.02, 0.36 ± 0.03, 0.27 ± 0.02, 0.22 ± 0.02, 0.47 ± 0.05, and 0.47 ± 0.05, respectively. Genetic and phenotypic correlations amongst the traits were in the range of 0.103 ± 0.008 to 0.995 ± 0.002. These results can be used for the improvement of growth traits in the Dağlıç breed of sheep through selection.

141 Exploring Alternative Approaches for the National Argentine Angus Cattle Genomic Evaluation Program

Abstract Beef cattle production is a relevant component of the Argentine economy. The Argentine Angus is the most common beef cattle breed, and this population has a large economic and cultural importance for the country. In 2019, a national genomic selection program was implemented in the Argentine Angus population. The objective of this study was to explore alternative approaches for the genomic selection program in Argentinean Angus so that it will better serve the stakeholders. For this study, a total of 9,944 phenotypes for weaning weight from Argentine Angus born in 2018 were used. All animals had pedigree information for at least 3 generations. Genomic information on 1,078 individuals for 150k SNPs was used. The genotyped individuals were connected to the population by pedigree. Weaning weight EPDs were calculated under an animal model considering contemporary group as fixed effects and additive direct and maternal genetic effects as random. Variance components were estimated using AIREMLF90, and EPDs were calculated using BLUPF90. The enhanced EPDs were the genomic estimated breeding values obtained by single-step GBLUP, by including the genomic information into the original model. Validation of the EPDs and enhanced EPDs were made by cross-validation, where a random sample of 70 genotyped individuals with more than 20 progeny was the validation population. The reference breeding values were the EPDs of the validation population with complete data. In a second analysis, the phenotype of the progeny of the validation population was removed. The correlation between the reduced and complete EPDs was the accuracy for this study, according to the LR method. The accuracy obtained by this method was overestimated due to potential relationships between animals in the training and validation population. However, the enhanced EPDs were 4% more accurate than the pedigree EPDs. The next steps of this research are exploring alternative approaches of the validation methodology, which will be accomplished by implementing a forward-in-time cross-validation. Such validation will be performed once more data is included in the model. Additionally, other models will be tested to identify the ideal combination of effects that will yield higher accuracies. Details regarding the construction of the genomic relationship matrix will be tested with the overarching goal of improving convergence without affecting accuracy. Moreover, a weighted single-step GBLUP approach will be tested to verify if prediction accuracy can improve even further. Finally, indirect prediction models will be tested so that the Argentine Angus Association can implement interim enhanced EPDs for young animals. In conclusion, including genomic data into this dataset yielded greater accuracy and such values are expected to improve even further after optimization.

Rapid decline of prenatal maternal effects with age is independent of postnatal environment in a precocial bird.

Maternal effects are an important source of phenotypic variation with potentially large fitness consequences, but how their importance varies with the quality of the environment across an individual's ontogeny is poorly understood. We bred Japanese quail (Coturnix japonica) of known pedigree and experimentally manipulated the quality of offspring diet, to estimate the importance of prenatal maternal effects in shaping variation in body mass from hatching to adulthood. Maternal genetic effects on body mass at hatching were strong, and largely caused by variation in egg mass, but their importance rapidly declined with age. Whereas there was a large effect of diet on growth, this did not affect the decline of maternal effects variance. The importance of additive genetic and residual variance increased with age, with the latter being considerably larger in the poor diet treatment. Hence, we found no evidence for prenatal maternal effect by postnatal environment interactions, and that prenatal maternal effects are rapidly replaced by direct additive genetic and residual effects when offspring start to develop outside the egg. Thereby these results shed new light on the dynamics of the role of maternal versus offspring genes across ontogeny and environments.

Estimation of genetic parameters for milking temperament in Holstein-Gyr cows

IntroductionDairy cattle with poor temperament can cause several inconveniences during milking, leading to labor difficulties, increasing the risk of accidents with animals and workers, and compromising milk yield and quality. This study aimed to estimate variance components and genetic parameters for milking temperament and its genetic correlations with milk yield in crossbred Holstein-Gyr cattle.MethodsData were collected at three commercial farms, resulting in 5,904 records from 1,212 primiparous and multiparous lactating cows. Milking temperament (MT), measured as the milking temperament of each cow, was assessed during pre-milking udder preparation (RP) and when fitting the milking cluster (RF) by ascribing scores from 1 (cow stands quietly) to 8 (the cow is very agitated, with vigorous movements and frequent kicking). The number of steps and kicks were also recorded during pre-milking udder preparation (SRP and KRP, respectively) and when fitting the milking cluster (SRF and KRF, respectively). Milk yield (MY) was obtained from each farm database. In two of them, MY was recorded during the monthly milk control (that could or could not coincide with the date when the milking temperament assessments were carried out) and in the remaining farm, MY was recorded on the same day that the milking temperament assessments were made. Genetic parameters were estimated using the THRGibbs1f90 program applying a threshold model, which included 89 contemporary groups as fixed effects, animal age at the assessment day and the number of days in milking as covariates, and direct additive genetic and residual effects as random effects.Results and discussionsThe heritability estimates were MT= 0.14 ± 0.03 (for both, MRP and MRF), MY= 0.11 ± 0.08, SRP= 0.05 ± 0.03, KRP= 0.14 ± 0.05, SRF= 0.10 ± 0.05, and KRF= 0.32 ± 0.16. The repeatability estimates were 0.38 ± 0.05, 0.42 ± 0.02, and 0.84 ± 0.006 for MTRP, MTRF, and MY, respectively; and 0.38 ± 0.02, 0.30 ± 0.07, 0.52 ± 0.02, and 0.46 ± 0.15 for SRP, KRP, SRF, and KRF, respectively. The estimates of most genetic correlation coefficients between MTRP-MTRF were all strong and positive (MTRR-MTRF= 0.63 ± 0.10, MTRP-SRP= 0.65 ± 0.12, MTRP-KRP= 0.56 ± 0.16, MTRF-SRF= 0.77 ± 0.06, and MTRF-KRF= 0.56 ± 0.34) except for MY (MTRP-MY= 0.26 ± 0.26 and MTRF-MY= 0.21 ± 0.23). Despite the low magnitude of MT heritability, it can be included as a selection trait in the breeding program of Holsteins-Gyr cattle, although its genetic progress will be seen only in the long term. Due to the low accuracy of the genetic correlation estimates between MT and MY and the high range of the 95% posterior density interval, it cannot be affirmed by this study that the selection of a milking temperament trait will infer on milk yield. More data is therefore needed per cow and more cows need to be observed and measured to increase the reliability of the estimation of these correlations to be able to accurately interpret the results.

Comparison of non-linear models and genetic parameter estimation for growth curve traits in the Murciano-Granadina goat breed

In this study, we analyzed 50,238 records of the body weight of the Murciano-Granadina goat breed from birth to 360 days of age. The data were collected from a private dairy farm located in Ghale-Ganj city, which is in the southern part of Kerman province, in the south of Iran. The records were collected between 2016 and 2022. Our goal was to evaluate the suitability of non-linear models for characterizing growth curves from birth to 360 days of age and to estimate genetic parameters for these growth curve traits. Five non-linear mathematical models namely Brody, Negative exponential, von Bertalanffy, Logistic, and Gompertz were compared by using Akaike's information criterion (AIC), root mean square error (RMSE), and Durbin-Watson statistic (DW) to determine the most suitable function for characterizing the growth curve. Among the investigated models, the von Bertalanffy model exhibited the lowest values for both AIC and RMSE. Additionally, we observed positive autocorrelations among residuals for all of the investigated non-linear models, with the lowest value being observed for the von Bertalanffy model. As a result, we selected the von Bertalanffy as the most suitable model for characterizing the growth curve of the Murciano-Granadina goat breed. To estimate genetic parameters for the growth curve traits, including parameters A (estimated mature weight), B (an integration constant related to initial animal weight), K (maturation rate), inflection age (IA), and inflection weight (IW), we utilized a Bayesian multivariate animal model that accounted only for direct additive genetic effects. The posterior means for heritabilities of A, B, K, IA, and IW were significant values of 0.11, 0.13, 0.03, 0.11, and 0.17, respectively. Parameter A had significant and positive genetic and phenotypic correlations with parameters B, IA, and IW. The posterior means for genetic and phenotypic correlations between parameters A and K were negative estimates of − 0.58 and − 0.17, respectively, implying that the kids with slower maturation rates had higher mature weights. Positive and medium estimates were obtained for posterior means of phenotypic (0.04) and genetic (0.29) correlations between parameters B and K. Both posterior means for phenotypic and genetic correlations of B with IA were 0.32 while those of B with IW were 0.51 and 0.50, respectively. We found high and positive genetic (0.51) and phenotypic (0.50) correlations between IA and IW. However, we observed low levels of additive genetic variation for all of the studied growth curve traits. In conclusion, our analysis suggests that the growth curve traits of the Murciano-Granadina goat breed are highly influenced by non-additive genetic and environmental effects. Therefore, it is essential to consider these effects when designing strategies to improve these traits and develop an appropriate breeding scheme that can achieve the desired shape of the growth curve.

Direct additive genetics and maternal effect contribute to the risk of Tourette disorder

BackgroundRisk for Tourette disorder, and chronic motor or vocal tic disorders (referenced here inclusively as CTD), arise from a combination of genetic and environmental factors. While multiple studies have demonstrated...

Genetic parameter estimates for litter traits in Jakhrana breed of Indian goat

The litter size and litter weight are the most important indicators of growth production system in goats as they are directly related to the survival and growth of the kids. The present attempt was made to estimate genetic parameters of litter traits such as litter size at birth (LSB), litter size at weaning (LSW), litter weight at birth (LWB) and litter weight at weaning (LWW) of Jakhrana breed of Indian goat. These traits were subjected to study variation due to direct additive genetic effects by adjusting non-genetic factors under linear mixed model. The data of litter records of 101 Jakhrana goats including pedigree information were processed and the results showed that the least-square means for LSB, LSW, LWB and LWW were 1.20 ± 0.05, 1.19 ± 0.05, 3.08 ± 0.11 and 12.11 ± 0.49, respectively. The direct heritability estimates for LSB, LSW, LWB and LWW were 0.17, 0.01, 0.001 and 0.10, respectively. The genetic (0.70–0.97) and phenotypic (0.61–0.92) correlation estimates among litter traits were high and positive. This study indicated that the additive variation among the early reproductive traits was low in range which does not provide a warrant for the improvement through selection. However, the evaluation of these traits has provided the current state of litter performance of Jakhrana goat which may be upgraded by managerial practices specially care and feeding of pregnant goats.

GENETIC EVALUATION BIRTH WEIGHT AND WEANING WEIGHT OF GARUT SHEEP IN UPTD-BPPTD MARGAWATI GARUT

This research was conducted at Unit Pelaksana Teknis Daerah Balai Pengembangan Perbibitan Ternak Domba (UPTD BPPTD) Margawati Garut on February 2014. The aim of this research was to evaluate Garut sheep genetic trait with description genetic parameter is heritability and breeding value birth weight and weaning weight of Garut Sheep in UPTD-BPPTD Margawati Garut. Data collection technique is purposive sampling. Data collected were 4128 records from 1650 dams, 78 sires, and 2064 Garut sheep, during 2005 to 2013. Variety components and the heritability value were suspected by Restricted Maximum Likelihood (REML) method used Animal Model pattern of direct additive genetic effect, maternal genetic effect and permanent environmant and Breeding Value estimated byBest Linier Unbiased Prediction (BLUP). Fix effect were used sex and birth type. The result of this research was heritability value of birth weight and weaning weight with direct additve genetic effect was 0.33 and 0.32 included in large category, with maternal genetic effect was 0.26 and 0.28 included in medium category. the maternal genetic value with same trait 0.12 and 0.57.heritability birth weigt and weaning weight for permanent environment was 0.23 and 0.25 wit permanent environment value 0.32 and 0.35 included in medium category. Estimated Breeding value for the three best ID number 3680, 1496, and 1138

Genetic parameters for mouth size and their influence on growth traits in pasture-raised Nelore cattle.

Evaluating traits that allow breeders to increase production efficiency in beef production systems is important. The mouth size score is a trait easily measured and implemented by breeders. Bite size is related to mouth size in beef cattle and is a determinant of daily feed intake of pasture-raised animals, influencing their growth. The aim of this study was to estimate genetic parameters for mouth size (MS), weaning weight (WW) and postweaning weight gain (PWG) of Nelore cattle and to evaluate the influence of the interaction between MS and WW on PWG. Phenotypic records of 134,282 Nelore animals born between 1995 and 2019 were used. Variance components were estimated using multi-trait animal model with the Bayesian method. The model included the contemporary group as fixed effect, age at measurement of the trait as linear covariate, and direct additive genetic and residual effects as random effects. For WW, random maternal and maternal permanent environmental effects were added to the model. A Bayesian approach was used to analyze the interaction between WW clusters and MS. The heritability estimates were 0.24, 0.15 and 0.23 for MS, WW and PWG, respectively. The genetic correlation between variables studied ranged from 0.24 to 0.46. The results suggest that animals with a larger mouth tend to have greater PWG, demonstrating the positive influence of MS score on the postweaning performance of cattle. The direct heritability estimates confirm the possibility of selecting animals for the traits studied.

Heritability and genetic trend of body weight in dogs of different breeds in Sweden.

High body weight (BW) in dogs has been associated with developmental as well as degenerative diseases, but the heritability of BW in dog breeds is largely unknown. The aim of the current study was to estimate heritability and genetic change (genetic trend) for BW in a range of dog breeds in Sweden. Body weight registrations from 19 dog breeds (with n ranging from 412 to 4,710) of varying body size, type and usage were collected from 2007 to 2016. The average BW of the breeds was 8 to 56 kg. The BW registrations were performed when the dogs were 12 to 24 mo of age (18 to 30 mo for one large-sized breed) in connection with an official radiographic screening program for hip dysplasia. Collected weight records were used to estimate heritability and genetic trends for BW. Several statistical models were used. The preliminary model included the fixed effects of breed (P < 0.001), sex (P < 0.001), year of screening (P < 0.001), litter size (P = 0.06), parity of the dam (P = 0.03) and linear regression on age at screening (P < 0.001), the latter five effects all nested within breed, and the random effects of litter and dam. Season of birth and the quadratic effect of age were also tested, but were not significant (P > 0.10). For the genetic analysis, various mixed linear models were tested within breed with different combinations of random effects; the most complex model included random effects of litter, direct additive, and maternal genetic effects, and maternal permanent environmental effects. The average heritability for BW over all 19 breeds was 51%, with a range of 35% to 70%, and the additive genetic coefficient of variance was around 9%. Maternal heritability was 5% to 9% and litter variance was below 10% with one exception (15% in Shetland Sheepdogs). For nine breeds, there was a genetic trend of increasing BW, whereas seven breeds had a genetic trend of decreasing BW. The largest absolute genetic change over a 10-yr period was around 0.6 kg or about 2% of the mean. In conclusion, given the small genetic changes in spite of the high heritability, it seems that there is generally a very weak selection, if any, for BW in the included dog breeds.

Genetic analysis of post-weaning growth traits in a simple crossbreeding experiment between Gabali and Hyplus line rabbits

A simple crossbreeding experiment between Gabali (G) bucks and Hyplus (H) does was performed to estimate crossbreeding effects for post-weaning growth traits (body weight at 5 (BW5), 7 (BW7), 9 (BW9), 11 (BW11), and 13 (BW13) weeks of age and daily weight gains (DG) during (DG5-7), (DG7-9), (DG9-11), (DG11-13) and (DG5-13), weeks of age). Estimates of heritability were mostly low or moderate for growth traits and ranged from 0.12 to 0.35 for body weights and 0.05 to 0.66 for daily weight gains. The percentages of direct additive genetic effects on body weights favored (p ≤ 0.01) the Gabali breed by 22.1, 31.2, 32.8, 31.1, and 25.2% at 5, 7, 9, 11, and 13 weeks and by 35.4, 38.1, 21.9, 3.7, and 27% for DG5-7, DG7-9, DG9-11, DG11-13, and DG5-13, respectively. The percentages of maternal effects ranged from 22 to 34.8% for body weights and ranged from 4.7 to 43.4% for daily weight gains. The percentages of direct heterosis were significantly positive by 11, 19.1, 20.3, 19.7, and 16.5% for body weights at 5, 7, 9, 11, and 13 weeks and by 25.6, 27.2, 17.3, 3.5, and 17.9% for DG5-7, DG7-9, DG9-11, DG11-13, and DG5-13, respectively. These results suggest that the Gabali breed could be used as a sire-group and the Hyplus line could be used as a dam-group to create new high growth rabbit lines in Egypt.

Multivariate Animal Model-based Analysis of Fiber Traits in Kashmir Merino Sheep

ABSTRACT An attempt was made in the present study to elucidate the (co)variance components and genetic parameters of fiber traits in Kashmir Merino sheep population using multivariate animal model. The data pertained to a total of 6836 sheep lambs born over a period of 21 years (1997–2017) and included information on different fiber traits [greasy fleece weight at first (GFW1) and second (GFW2) clips; and fiber diameter (FD) and staple length (SL) at second clip]. Genetic analysis was undertaken using average information restricted maximum likelihood (AI-REML) algorithm in WOMBAT program. The model incorporated six fixed (sex of lamb, season and period of birth, farm of origin, breed and type of birth) and two random effects (direct additive genetic and maternal genetic effects without any covariance between them) in it. The additive genetic heritability estimates for fiber traits were 0.300 ± 0.031; 0.289 ± 0.022; 0.254 ± 0.029 and 0.189 ± 0.028 for GFW1, GFW2, FD, and SL, respectively. The maternal genetic heritability estimates were very low for all traits under study. The genetic correlation between different traits was positive and estimates ranged from moderate to high. The results from present study imply that the variation in these traits has genetic basis which can be exploited in the selection programmes for their improvement. The correlation between different fiber traits was found to be favorable, which can lead to indirect selection response upon formulation of efficient breeding programmes.

Case Study on Increasing Breeding Value Estimation Reliability of Reproductive Traits in Serbian Highly Prolific Large White and Landrace Sows.

Simple SummaryIn the Republic of Serbia, pig selection in recent decades has been based on genetic improvement of growth and carcass quality traits. Genetic improvement of reproductive traits of pigs was based on the so-called phenotypic selection. The introduction of modern information systems and the availability larger dataset have opened the possibility to perform genetic estimation of reproductive traits within the main breeding programme of the Republic of Serbia. Using the methods of gene flow and connectedness evaluation, our study investigated the possibility of improving the reliability of estimating the breeding value of reproductive traits in highly productive sows. We believe that these methods could lead to a systematic improvement of the genetic value of reproductive traits in sows. Thus far, none of the methods for estimating the degree of connectedness between herds in pigs has been used in the preparation of the National Breeding Programme of the Republic of Serbia.This study investigated the influence of the degree of connectedness on the reliability of the estimated breeding values (EBVs). The focal trait in the study was the number of piglets born alive (NBA) from sows of the highly prolific Large White and Landrace sows. An analysis included total of 58,043 farrowing’s during the 2008–2020 period. BLUP procedure was used to estimate the breeding values for NBA for the three herds separately and after merging all three herds into one herd. The model for EBV estimation included the following fixed factors: parity, genotype, seasons, litter sire, herds, sow age at farrowing, weaning-conception interval, length of previous lactation, and the following random effects: common litter environment, permanent litter environment, and direct additive genetic effect of animal. Heritability values for NBA ranged from 0.048 to 0.097, depending on the data included in the analysis. The connectedness between herds was analysed using the connectedness rating (CR) and the gene flow (GF) methods. CR among the observed herds ranged from 0.245 to 0.994%, depending on the data included. The exchange of genetic material between all three herds was determined using GF method. The high degree of connectedness determined by the CR and GF method had a strong effect on EBV reliability. The average EBV reliability ranged from 0.520 to 0.867, depending on the data included. The increase in average reliability was observed in both cases when the data were added, both in the analysis of average reliability for purebred animals and when crossbreeds were added, where an increase in this value was also observed. The increase in average EBV reliability is a consequence of the greater amount of information included in the joint evaluation. In conclusion, we believe that our research will improve EBV reliability and help in further selection work in the Republic of Serbia.

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.