Direct Heritability Estimates Research Articles

Bayesian analysis reveals the influence of maternal effect on pre-weaning body weights in Landlly piglets.

The present study was undertaken to estimate the (co)variance components and genetic parameters of body weights recorded in Landlly piglets from birth to weaning at weekly intervals (w0 to w6). The data pertained to body weights of 2462 piglets, born to 91 sires and 159 dams across different generations during a 7-year period from 2014 to 2020. Five animal models (I-V), differentiated by inclusion or exclusion of maternal effects with or without covariance between maternal and direct genetic effects, were fitted on the data using the Bayesian algorithm. The analyses were implemented by Gibbs sampling in the BLUPF90 program and Markov chain Monte Carlo (MCMC) methodology was used to draw samples of posterior distribution pertaining to (co)variance components. Based on deviance information criteria (DIC), model V with inclusion of direct additive genetic, direct maternal genetic and permanent environmental effect of dam as random factors along with covariance between direct additive and maternal effects best fitted the data on pre-weaning traits (w0 to w5). Whereas, model I incorporating only the direct additive genetic effect best fitted the weaning weight (w6) data in Landlly piglets. The posterior mean estimates of direct heritability under the best models for W0 to W6 were 0.13, 0.19, 0.29, 0.13, 0.26, 0.32 and 0.46, respectively. Inclusion of the maternal component helped in better partitioning of variance for different body weights in Landlly piglets. The maternal heritability ranged from 0.06 to 0.14, while the litter heritability ranged from 0.11 to 0.15 for pre-weaning weights (W0 to W5) under the best-fit models. The influence of maternal environment was greater than maternal genetic effect from birth to 4th week of age. The results implied that variations in body weight of Landlly pigs were genetically controlled to moderate levels (especially w2 and w4) with contributions from direct additive and maternal genotype that can be exploited by designing efficient breeding programmes.

Comparison between different selection indices for some productive traits in Friesian cows

Data pertaining to 3,977 records collected over a period of 29 years for Friesian cows were utilized for the present study. Records were analyzed for actual total milk yield (TMY), 305-day milk yield (305d-MY), lactation period (LP) and days open (DO) by VCE 6.0 software while, selection indices (SI) using one phenotypic standard deviation as REV1 and Lamont method as REV2. Estimates of direct heritability were low and ranged from 0.02 to 0.23 while, maternal heritability were low and ranged from 0.03 to 0.028. The correlation coefficients between all studied traits were highly significant and ranged between 0.82 to 0.93. The results indicated that reducing interval of days open (DO) could be brought about by improving the farm managerial aspects. The selection criteria of different indices proved that the index I1which incorporated TMY, 305d-MY, LP and DO was the best (RIH = 0.49) and (RE % = 100.00). This index could effectively anticipate in genetic improvement of all the traits of the study; I1 = 0.144 (TMY) + 0.503 (305day/MY) + 1. 619 (LP) + 1.150 (DO). The application of this index I1 led to a predictive genetic gain of TMY, 305d-MY, LP and DO by 359.4 kg, 279.5 kg, 15.3 days and 3.2 days, respectively. The correlation coefficient between I1 and the total economic value was 0.49 while, the heritability estimate of the index was 0.86. Conclusively, such an index can help the investor in the field of dairy cattle to select the best animals in early lactation and in subsequent generation’s traits as well; which leads to an increase in economic return.

Genetic studies on the estimates of (Co) variance components for growth traits in Barbari goat

The objectives of the current study were to evaluate the genetic progress and variability for growth traits and also to suggest a suitable direction to the existing breeding program of the Barbari goat population in India. The analysis included 10,648 animals descended from 2697 dams and 420 sires at the ICAR-Central Institute for Research on Goats, Makhdoom between 1993 and 2020 (28 years). The effect of fixed factors such as period and season of kidding, sex of the kid, type of birth, parity of doe, and doe weight at kidding on live weights were significant (P < 0.05). Animal models with average information restricted maximum likelihood (AIREML) approach were used to estimate genetic parameters for growth traits. The mean of inbreeding coefficient for the whole pedigree was 2.16%. For the inbred animals it was 3.32%, indicating within normal estimate for average inbreeding in a nucleus flock. Results suggested that the genetic model for additive direct effects of animal and dam and their covariance, as well as dam's permanent environment, was best for birth weight (BW), weaning weight (WW), weight at six months (6 W), and weight at nine months (9 W), whereas the model with direct effects of animal and dam and their covariance was best for weight at 12 months (12 W). The estimates of direct heritability (h2) for Barbari goat were 0.31 ± 0.04, 0.23 ± 0.03, 0.18 ± 0.03, 0.13 ± 0.03 and 0.21 ± 0.04 for BW, WW, 6 W, 9 W, and 12 W, respectively. However, the estimates were influenced by negative correlation between direct additive effects of animal and dam. We also observed substantial variance for additive maternal effect (0.09–0.15) and maternal permanent environment effect (0.11–0.17) across traits analysed. Pre-weaning growth traits had a significant maternal effect that receded as age advanced. The prospect of selecting Barbari goats for growth traits is indicated by moderate h2 estimates. The positive and desired genetic trend revealed favourable response to selection in the nucleus of the Barbari goat for growth traits. The significant and positive genetic and phenotypic correlation between post-weaning weights (6–9 W= 0.89) suggests scope for early selection of Barbari goats by decreasing the age for selection from 9 to 6 months.

Comparative evaluation of different animal models for genetic analysis of body weight traits in an organized Corriedale sheep population

The present study aimed to evaluate different animal models for their appropriateness to best fit the body weight data of Corriedale lambs at different ages and reared under temperate conditions. Data used in this study consisted of 24,907 body weight records on a total of 6162 lambs of Corriedale sheep population. The data pertained to body weight traits at different ages i.e., at birth (BW), weaning (WW), six months (SW), nine months (NW) and yearling age (YW). The (co)variance components of five traits were estimated using univariate analysis based on restricted maximum likelihood (REML) algorithm in WOMBAT program. Six different univariate animal models, with or without maternal genetic effect, maternal permanent environment effect and covariance between additive genetic and maternal genetic effects, were fitted on the body weight data of the Corriedale sheep population. All univariate animal models incorporated season (winter, spring) and period of lambing (8 periods, each of 5-year duration), and sex of lamb (male, female) as fixed effects. AIC, Log-likelihood and likelihood ratio test results were used to evaluate the best fit models for body weights at different ages. Model I, incorporating additive genetic effect of the individual as random effect, showed the minimum AIC estimate for BW. Model III showed the minimum AIC values for all other traits under consideration i.e., WW, SW, NW and YW. The direct additive genetic heritability for birth weight was 0.025 under the best fit model i.e., model I. The direct heritability estimates for WW, SW, NW and YW were 0.151, 0.216, 0.103 and 0.132, respectively under the best-fit models. Maternal genetic heritability ranged from 0.043 to 0.087 for different body weights, except BW for which model I was the best-fit. Most of the covariance and correlation estimates between direct additive genetic and maternal genetic effects were negative. Low estimates of heritability found in best-fit models in this research are suggestive of the less appropriateness of applying individual selection for this population as it may only result in slow progress for body weight traits in Corriedale sheep. Environmental factors played a significant role in generating the variation in body weight traits in Corriedale sheep.

Estimates of (co)variance components and phenotypic and genetic parameters of growth traits and wool traits in Alpine Merino sheep.

The (co)variance components and corresponding phenotypic and genetic parameters for growth traits and wool traits of economic importance were estimated in the Alpine Merino sheep population maintained at Gansu Provincial Sheep Breeding Technology Extension Station in northwestern China. Data from a maximum of 49,474 animals sired by 526 rams and born from 22,531 ewes over 20years from 2000 to 2019 were used in this study. Birth type, age of dam, birth year, sex and/or management group, and age at measurement were initially fitted as fixed effects in an animal model with various random effects. Genetic groups were defined for all animals by the sire breed and breed genotype interacted with dam-strain flocks and were fitted as one of the random effects. Analyses were conducted using a residual maximum likelihood procedure (ASReml). Seven different animal models were fitted for all traits, and the most appropriate model with relevant random effects was selected through log-likelihood ratio testing. After identifying the appropriate model through single-trait analysis, bivariate analyses were used to obtain the phenotypic and genetic correlations among the traits. The estimates of additive direct heritability for birth weight (BWT), weaning weight (WWT), preweaning growth rate (prwADG), postweaning growth rate (powADG), yearling body weight (YWT), average fibre diameter (AFD), greasy fleece weight (GFW), clean fleece weight (CFW), yield (YLD), yearling wool staple length (YSL), coefficient of variation of average fibre diameter (FDcv) and wool visual fineness counts (VFC) were 0.30, 0.18, 0.18, 0.20, 0.29, 0.20, 0.19, 0.20, 0.35, 0.19, 0.16 and 0.13, respectively, with standard errors ranging from 0.02 to 0.05. The corresponding ratios of genetic group variance to additive genetic variance were significant and, respectively, 0.35, 0.80, 0.62, 0.26, 0.13, 1.06, 0.38, 0.64, 0.09, 0.12, 0.06 and 0.58. These results suggest for these traits that there is potential to exploit both the additive genetic variation and between genetic group variation although for most traits the between group variation was smaller than the variation within groups. Favourable genetic correlations were found among the growth traits, and between growth traits and fleece production traits, and among wool traits GFW, CFW, YSL and YLD. This study provides the required estimates of genetic parameters of both growth and wool traits of the new breed for the design of more effective breeding programmes.

Impact of mother genetic and resource environment on her offspring's growth features in Munjal sheep.

The present study evaluated maternal and additive influences that contribute to phenotypic variation in various growth traits in Munjal sheep. The targeted traits that pertained to 2278 records of 706 lambs were birth weight (BWT), weaning weight (WT3), 6-month body weight (WT6), 12-month body weight (WT12), average daily gain (ADG1: 0-3 months; ADG2: 3-6 months, ADG3: 6-12 months of age) and their corresponding Kleiber ratios designated as KR1, KR2 and KR3. The direct heritability estimates for BWT, WT3, WT6, WT12, ADG1, ADG2, ADG3, KR1, KR2 and KR3 under animal models were 0.20 ± 0.08, 0.28 ± 0.08, 0.17 ± 0.07, 0.47 ± 0.09, 0.33 ± 0.08, 0.09 ± 0.06, 0.36 ± 0.10, 0.33 ± 0.08, 0.09 ± 0.06 and 0.32 ± 0.10, respectively. The estimates of maternal genetic effects contributed significantly and were 8% and 7% for BWT and WT3 traits, respectively, which highlighted the considerable role of maternal effects on early growth traits. Genetic and phenotypic correlations ranged from moderate to high between weaning and post-weaning traits. It was concluded that early selection that considered additive as well as maternal effects at weaning age may be delivered to the desired genetic progress in Munjal sheep.

Genetic study of quantitative traits supports the use of Guzerá as dual-purpose cattle

ObjectiveThe aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle.MethodsThe evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365), and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210.ResultsThe direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative (−0.43 to −0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations.ConclusionThese results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.

Genetic parameters of average daily gain and kleiber ratio in mecheri sheep

The objective of study was to estimate the genetic parameters for average daily gain and feed efficiency in Mecheri sheep in an organized farm. Atotal of 2516 records collected over a period of 10 years (2010 to 2019) were utilised for the study. The least-squares means for average daily gain (ADG) at different periods viz., ADG1, ADG2 and ADG3 were 89.83±1.38, 43.06±1.61 and35.65±1.41 g, respectively and the means for Kleiber ratio (KR) for KR1, KR2 and KR3 were15.20±0.10, 5.63±0.18 and 3.49±0.12, respectively. The direct heritability estimates for ADG1, ADG2, ADG3, KR1, KR2 and KR3 were 0.14±0.05, 0.06±0.04, 0.04±0.04, 0.14±0.05, 0.08±0.05and 0.05±0.04,respectively and the corresponding maternal heritability estimates were 0.03±0.02, 0.01±0.02, 0.05±0.03, 0.02±0.02, 0.01±0.03 and 0.06±0.03, respectively. The geneticcorrelations of ADG1 were highly positive with ADG3 and KR1 and negative with ADG2 (−0.697) and KR2 (−0.843). The genetic correlations of KR1 with other traits ranged between -0.049 and 0.988 and KR2 had high genetic correlation (0.974) with only ADG2. It is crucial to consider any negative relationships between the pre- and post-weaning development characteristics when putting the breeding methods into practice. ADG and KR from birth to three months should be considered, since heritability estimates and the strength of the genetic and phenotypic correlations were strong at this stage of development.

Genetic and non-genetic effects associated with ewe productivity in Harnali sheep.

The objective of the current study was to estimate the genetic parameters for ewe productivity traits of Harnali sheep by examining non-genetic effects. The data records of 440 animals born to 85 sires and 259 dams were collected with respect to various traits such as litter size at birth (LSB), litter weight at birth (LWB), litter size at weaning (LSW), litter weight at weaning (LWW) and age at first lambing (AFL) for the period of 2001 to 2020. Genetic parameters were estimated by fitting a series of animal models using an average information restricted maximum likelihood (REML) algorithm in WOMBAT software. Least-squares analysis revealed significant (P < 0.05) influences of period of lambing, age and weight of ewe at lambing on the studied traits. These results indicated that heavier ewes had significantly higher (P < 0.05) values of litter weight traits than their counterparts. On the basis of likelihood ratio test, the estimates of direct heritability under best model for AFL, LSB, LWB, LSW and LWW were 0.06, 0.18, 0.09, 0.07 and 0.16, respectively. Maternal permanent environment effect made a significant contribution to the LSB trait (0.20). The genetic correlation between litter size and LWW was negative, while the remaining correlations were positive. The present results suggest that selection based on ewe productivity traits will result in low genetic progress and therefore the management role is more important for better gains.

Genetic parameters and genetic trends for growth traits of the Red Maasai sheep and its crosses to Dorper sheep under extensive production system in Kenya

The Red Maasai are indigenous sheep breeds known for their adaptability in arid and semi-arid environments while the Dorper is known for its good mutton production. A field experiment cross breeding program for the two breeds was set up in 2003 to exploit these traits. In this paper, we present the genetic parameters for birth weight (BWT), weaning weight (WWT) and weight at nine months (MWT) for pure Red Maasai (RRRR), pure Dorper (DDDD), 75% Dorper (DDDR) and 50% Dorper (DDRR) breeds. The genetic parameters were estimated by fitting four different multivariate animal models while ignoring or including maternal effects. The model with the lowest Akaike’s Information Criterion (AIC) was chosen as the best model for the estimation of genetic parameters. The average annual genetic gain of the studied traits for each breed group was estimated by regressing the estimated breeding values on year of birth. Records from 5442 lambs recorded over a period of 17 years (2003-2019) were used in this analysis. The breed group, sex, type of birth, season of birth and age of the dam significantly (P < 0.001) affected the weights of the animals. The direct heritability estimates for BWT, WWT and MWT were highest in the RRRR (0.40 ± 0.08, 0.39 ± 0.08, 0.45 ± 0.08 respectively). Direct heritability was lowest for BWT in the DDDR (0.18 ± 0.06), and for WWT and MWT in the DDDD (0.10 ± 0.07, 0.08 ± 0.06 respectively). The maternal heritability estimates were highest in BWT for DDRR (0.12 ± 0.05) and at WWT for DDDD (0.05 ± 0.03), and lowest in BWT for DDDR (0.03 ± 0.03) and at WWT for DDRR (0.00 ± 0.01). The maternal heritability for MWT for all the breed groups was close to zero. Genetic and phenotypic correlations between the traits were all high and positive across all breed groups. The phenotypic correlations ranged from 0.41 to 0.73 while the genetic correlations ranged from 0.40 to 0.99. The pure Red Maasai had an average annual genetic gain of 0.012 ± 0.005 kg, 0.144 ± 0.037 kg and 0.170 ± 0.047 kg for BWT, WWT and MWT respectively while the pure Dorper had an average annual genetic gain of 0.006 ± 0.006 for BWT, 0.047 ± 0.033 for WWT and 0.069 ± 0.044 for MWT. Between the crosses, the 50% Dorper had higher annual genetic gains for all the traits. The observed genetic gains demonstrate that selective breeding based on estimated breeding values can lead to significant genetic improvement in the Red Maasai sheep and its crosses.

Phenotypic and genetic parameters of productive traits in Rahmani and Romanov sheep and crossbreds.

Data of 651 lambs (68 Romanov, 49 Rahmani, 151 [♀1/2 Rahmani X ♂1/2 Romanov) and 383 (♀3/4 Rahmani and 1/4♂ Romanov]) were collected from Mehalet Mousa Farm, belonging to Animal Production Research Institute from the period of 2009 to 2016 to estimate phenotypic and genetic parameters. The traits studied were birth weight (BW), body weight at four week (BW4), body weight at eight weeks (BW8) and body weight at twelve weeks (BW12) or weaning weight. Least squares analysis of variance shows significance of the effects of breed groups, gender of lambs, birth type; month of birth and year of birth on all traits studied. Rahmani lambs had heavier BW, BW4, BW8 and BW12 while Romanov lambs had the lowest ones. The first generation (♀1/2 Rhamani X ♂1/2 Romanov) had heavier body weights than Romanov and the second generation (♀3/4 Rahmani X ♂1/4 Roamnov). Gender of lambs had highly significant effect on body weights. Males were significantly (p < 0.01) heavier than females for all traits studied. Least square means of BW, BW4, BW8 and BW12 for single lambs were 2.69, 10.43, 13.53 and 16.10 kg, respectively. Least square means of BW, BW4, BW8 and BW12 for twin lambs were 2.50, 9.37, 12.5 and 15.16 kg, respectively, while least square means of BW, BW4, BW8 and BW12 for triple lambs were 2.09, 7.86, 10.83 and 13.67 kg, respectively. Estimates of direct heritability measured by single trait animal model were 0.14, 0.23, 0.25 and 0.26 for BW, BW4, BW8 and BW12, respectively, and the corresponding measured by multi trait animal model were 0.17, 0.24, 0.32 and 0.36 for the same traits, respectively. All genetic and phenotypic correlations among different traits studied are positive and significant.

PSXI-9 Heterotic and breed effects in crossbred lambs

Abstract Given its benefits on animal performance, crossbreeding is common commercially. Genetic evaluation of sheep in the U.S. is performed within breed type (terminal, maternal wool, range, hair). While incorporating crossbred records may improve assessment of purebreds, it requires accounting for heterotic and breed effects in the evaluation. The objectives were to i) determine the generalized effects of direct and maternal heterosis on growth traits of crossbred lambs, and ii) estimate covariance components for direct and maternal additive, and uncorrelated maternal environmental, effects among those traits. Data included body weights (BW) at birth (BN; n = 14395), pre-weaning (WN; n = 9298), weaning (WW; n = 9230), and post-weaning (PW; n = 1593). Mean (SD) BW were 5.3 (1.1), 22.2 (8.7), 39.1 (7.2), and 54.2 (8.7) kg for BN, WN, WW, and PW, respectively. Estimates of heterotic effects and covariance components were obtained using a multiple trait animal model. Genetic effects based on founders’ breeds were included, being significant. Estimates of direct heterosis were 3.04 ± 0.61, 2.62 ± 0.64, 3.99 ± 0.54, and 5.97 ± 0.86%, and estimates of maternal heterosis were 1.86 ± 0.87, 4.42 ± 0.79, 3.69 ± 0.66, and 3.77 ± 0.90%, for BN, WN, WW, and PW, respectively. Direct heritability estimates were 0.17 ± 0.02, 0.13 ± 0.02, 0.18 ± 0.02, and 0.47 ± 0.04 for BN, WN, WW, and PW, respectively. Additive maternal effects defined trivial variation in PW. For BN, WN, and WW, respectively, maternal heritability estimates were 0.17 ± 0.02, 0.10 ± 0.02, and 0.07 ± 0.02. Uncorrelated maternal effects defined little variation in any trait. Direct and maternal heterosis had considerable impact on growth traits, emphasizing the value of crossbreeding and the need to account for heterosis, in addition to breed effects, if crossbred lamb information is included in genetic evaluation.

PSI-17 Genetic analysis of weaning weight in Hungarian Simmental cattle

Abstract The aim of the study was to partition the total phenotypic variation in the weaning weight of Hungarian Simmental calves into their various causal components. The data used was provided by the Association of Hungarian Simmental Breeders. The dataset comprised of the weaning weight records of 44,278 calves (sire = 879, dam = 14,811) born from 1975 to 2020. A total of six models were fitted to the weaning weight data. Herd, birth year, calving order and sex were included as fixed effects in the models. Model 1 had direct genetic effect as the only random effect. Model 2 had a permanent maternal environment as an additional random effect. Model 3 had both direct and maternal genetic effects, with their covariance is being zero. Model 4 was similar to Model 3 but with non-zero direct-maternal genetic covariance. Model 5 had direct, maternal genetic and permanent environmental effects and a zero direct-maternal genetic covariance. Model 6 was similar to model 5 but the direct-maternal genetic effect was assumed to be correlated. Variance components and genetic parameters were estimated using restricted maximum likelihood method with the Wombat software. The best fit model was determined using the Log likelihood ratio test. Inclusion of direct maternal genetic covariance increased the variance components estimates dramatically which resulted in a corresponding increase in the direct and maternal heritability estimates. The best fitted model (Model 4) had direct and maternal genetic effects as the only random effects with a non-zero direct-maternal genetic covariance. The direct heritability, maternal heritability and direct-maternal genetic correlation estimate of the best model was 0.57, 0.16 and -0.78, respectively. Our result suggests the problem of (co)sampling variation in the partitioning of additive genetic effect into direct and maternal components.

Estimation of genetic parameters for early reproduction traits in Beetal goat

SummaryThe evaluation of early reproduction traits in Beetal goat was performed for possible effects of genetic and non-genetic factors on litter size at birth (LSB), litter size at weaning (LSW), litter weight at birth (LWB), litter weight at weaning (LWW) and age at first kidding (AFK). The data records consisted of information of pedigree and targeted traits pertained to 223 does born to 25 sires and 122 dams between the years 2004 to 2019. A general linear model was used for assessment of non-genetic factors such as period of birth, type of birth and dam’s weight at kidding on studied traits. Genetic evaluation of targeted traits was done to estimate variance components and genetic parameters under dyadic mixed modelling. The estimates of least-square means for LSB, LSW, LWB, LWW and AFK were observed as 1.27 ± 0.03, 1.25 ± 0.03, 3.24 ± 0.07 kg, 13.08 ± 0.30 kg and 27.56 ± 0.58 months, respectively. Only the period of birth showed significant (P &lt; 0.05) effects for targeted traits in this study. The estimates of direct heritability for LSB, LSW, LWB, LWW and AFK were low in magnitude as 0.08, 0.03, 0.10, 0.03 and 0.06, respectively. The moderate to high genetic and phenotypic correlations among litter traits indicate simultaneous improvement for these traits. It was concluded that low ranged direct heritability estimates for targeted traits indicated modest scope for genetic improvement of reproductive efficiency in Beetal goat through selection and, therefore, adoption of improved managerial practices is necessary to improve reproductive efficiency of Beetal goat.

Evaluating animal models comprising direct and maternal effects associated with growth rates and the Kleiber ratio in Harnali sheep.

The present work evaluated animal models comprising direct and maternal effects to estimate (co)variance components and genetic parameters of growth rates and Kleiber ratio in Harnali sheep. The information on pedigree and targeted traits of 1862 lambs born to 144 sires and 591 dams was collected for the period from 1998 to 2018. The traits studied were average daily gain from birth to 3 months of age (ADG1), 3 months to 6 months of age (ADG2), and 6 months to 12 months of age (ADG3) and their corresponding Kleiber ratios as KR1, KR2 and KR3, respectively. The statistical methods included the general linear model for analyzing the effects of fixed factors and animal models for deriving variance components for targeted traits. According to best model evaluated on the basis of likelihood ratio test, the estimated direct heritability was low in magnitude and ranged from 0.04 to 0.14. Direct heritability estimates for ADG1, ADG2, ADG3, KR1, KR2 and KR3 were 0.06, 0.14, 0.05, 0.04, 0.11 and 0.05, respectively. The maternal genetic effects contributed (4-7%) significantly for ADG1, KR1 and KR2 traits. The genetic correlations ranged from -0.35 ± 0.11 (ADG1-KR2) to 0.98 ± 0.01 (ADG2-KR2 and ADG3-KR3) and phenotypic correlations ranged from -0.36 ± 0.02 to 0.98 ± 0.01 for ADG1-KR2 and ADG2-KR2, respectively. The significant maternal effects along with low levels of direct effects for average daily gain and Kleiber ratio at different age group should be considered while setting selection and managerial strategies to achieve anticipated growth rates in Harnali sheep.

Phenotypic and genetic parameter estimates for early growth, growth rate and growth efficiency-related traits of Fogera cattle in Ethiopia.

BackgroundUnderstanding the phenotypic and genetic parameter estimates of growth traits is important for an effective livestock genetic improvement programme.ObjectivesIn this study, we evaluated the phenotypic performances and estimated genetic parameters for birthweight (BWT), weaning weight (WWT), pre‐weaning average daily gain (PADG), pre‐weaning Kleiber ratio (PKR), pre‐weaning growth efficiency (PGE) and pre‐weaning relative growth rate (PRGR) of Fogera cattle in Ethiopia.MethodsGrowth data collected from 2000 to 2018 in Andassa Livestock Research Center were used for the study. General linear model of SAS 9.1 was used to estimate the least squares mean (LSM) ± standard error (SE) for phenotypic performances, and AI‐REML of Wombat software combined with a series of five single‐trait animal models to estimate phenotypic variance and its direct, maternal and residual components. Calf sex, calf birth season and calf birth year were the fixed effects considered.ResultsThe overall LSM ± SE BWT, WWT, PADG, PKR, PGE and PRGR were 21.28 ± 0.05 kg, 97.99 ± 0.67 kg, 320.29 ± 2.79 g, 10.10 ± 0.04, 3.51 ± 0.35 and 1.95 ± 0.00, respectively. All the fixed effects considered significantly (p < 0.001) affected all the traits. The direct heritability estimates for BWT, WWT, PADG, PKR, PGE and PRGR were 0.21 ± 0.07, 0.26 ± 0.01, 0.55 ± 0.19, 0.53 ± 0.18, 0.33 ± 0.00 and 0.50 ± 0.00, respectively. The genetic correlations among the traits ranged from negative (−0.20 ± 0.04; BWT‐PKR) to positive (0.99 ± 0.00; BW‐PGE, BW‐GR, WWT‐PGE, WWT‐PGR, ADG‐PGR, PKR‐PGR, PKR‐PGE and PGE‐PGR). Similarly, the phenotypic correlations ranged from −0.03 ± 0.20 to 0.99 ± 0.01; BWT‐PGE, BWT‐PRGR, WWT‐PGE, WWT‐PRGR, PKR‐PGE, PKR‐PRGR and PGE‐PRGR).ConclusionThe positive and larger phenotypic and genetic correlations between most of the traits implied that selection based on one trait could improve the other traits. However, the negative phenotypic and genetic correlation between BWT‐PKRA implies that selection of Fogera calves based on either of the traits has an adverse effect on the other. Therefore, caution should be taken when designing the selection criteria for growth improvement.

Estimation of additive and non-additive genetic variances of average daily gain traits in Adani goats

• Dominance and epistasis effects are important for the average daily gain traits and could be added to evaluation models. • Adding the non-additive genetic effects to models led to increase the accuracy of estimated breeding values. • The adgbww3 and adgbww6 traits can be the basis of selection for the next generation. Considering the dominance and epistasis effects in the analysis can increase the accuracy of estimating breeding values. The objective of this study was to fit the best model for each average daily gain trait (average daily gain from birth to weaning (adgbwww), from birth to 3 months (adgbww3), from birth to 6 months (adgbww6), from weaning to 3 months (adgwww3), from 3 to 6 months (adgw3w6), from 6 to 9 months (adgw6w9), and from 9 to 12 months (adgw9w12)) and the estimation of the genetic parameters and variance components, especially non-additive genetic effects, in Adani goats. Analyses were carried out using the Bayesian method via the Gibbs sampler animal model by fitting 18 different models. With the best model, direct heritability estimates were 0.093, 0.250, 0.256, 0.084, 0.036, 0.048, and 0.151 for adgbwww, adgbww3, adgbww6, adgwww3, adgw3w6, adgw6w9 and adgw9w12 traits, respectively. Maternal genetic and maternal permanent environmental effects were significant only for adgbwww trait. Dominance and epistasis effects were significant almost for all traits and as a proportion of phenotypic variance was the range from 0.068 to 0.221 and 0.106 to 0.237, respectively. Adding dominance and epistasis effects to models reduced the error variance and the accuracy of estimating breeding values was increased. The accuracy of breeding values of these traits with the best models ranged from 0.456 to 0.674, 0.493 to 0.656, and 0.424 to 0.674 for all animals, 10 % of best males and 50 % of the best females, respectively. The result of the present study suggests that dominance and epistasis effect was important for average daily gain traits of Adani goats and should be included in evaluation models.

Genetic evaluation for reproductive and productive traits in Brahman cattle

Our objectives were to estimate genetic parameters for male and female reproductive traits and their genetic correlations with body weight and carcass traits, evaluate the genetic trends over the years, and verify the effect of inbreeding on the phenotypes of Brahman cattle. The traits evaluated were body weights at 120, 210, 365, and 450 days of age (W120, W210, W365, and W450); scrotal circumference at 365 and 450 days of age (SC365 and SC450), age at first calving (AFC), gestation length (GL), stayability (STAY), ribeye area (REA), backfat thickness (BFT), and rump fat thickness (RFT). Direct heritability estimates ranged from 0.10 ± 0.03 (AFC) to 0.43 ± 0.06 (GL). Maternal heritability estimates for body weights, scrotal circumferences, and GL ranged from 0.07 ± 0.02 to 0.15 ± 0.03. The proportion of the maternal permanent environment for W120 and W210 was equal to 0.11 ± 0.02. Genetic correlations varied between −0.60 ± 0.25 (STAY and BFT) to 0.97 ± 0.01 (W365 and W450). Except for AFC, all genetic trends were significant (p < 0.05) and presented favorable annual genetic gains. Unfavorable effects due to the increase of inbreeding coefficients were observed for body weights and AFC, suggesting greater attention be paid to the applied mating systems to control inbreeding. Reproductive traits, such as AFC and STAY, could be assisted indirectly by scrotal circumference selection. The emphasis applied to body weight selection, especially at W210, may assist REA. The BFT and RFT traits presented genetic variability and have responded to selection, although not included in the Brahman selection index.

Investigating pig survival in different production phases using genomic models.

Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population as well as to investigate the benefit of including genomic information through single-step genomic best linear unbiased prediction (ssGBLUP) on the prediction accuracy of survival traits compared with results from traditional BLUP. Individual survival records on, at most, 64,894 crossbred piglets were evaluated under two multi-trait threshold models. The first model included farrowing, lactation, and combined postweaning survival, whereas the second model included nursery and finishing survival. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods. Furthermore, prediction accuracy, bias, and dispersion were accessed using the linear regression validation method. Direct heritability estimates for survival in all studied phases were low (from 0.02 to 0.08). Survival in preweaning phases (farrowing and lactation) was controlled by the dam and piglet additive genetic effects, although the maternal side was more important. Postweaning phases (nursery, finishing, and the combination of both) showed the same or higher direct heritabilities compared with preweaning phases. The genetic correlations between survival traits within preweaning and postweaning phases were favorable and strong, but correlations between preweaning and postweaning phases were moderate. The prediction accuracy of survival traits was low, although it increased by including genomic information through ssGBLUP compared with the prediction accuracy from BLUP. Direct and maternal breeding values were similarly accurate with BLUP, but direct breeding values benefited more from genomic information. Overall, a slight increase in bias was observed when genomic information was included, whereas dispersion of breeding values was greatly reduced. Combined postweaning survival presented higher direct heritability than in the preweaning phases and the highest prediction accuracy among all evaluated production phases, therefore standing out as a candidate trait for improving survival. Survival is a complex trait with low heritability; however, important genetic gains can still be obtained, especially under a genomic prediction framework.

Genotype by environment interactions for body weight in Mediterranean buffaloes using reaction norm models

Background: Buffalo breeding has significantly increased in Brazil over recent years. However, few genetic evaluations have been conducted. Objective: To assess Genotype x Environment Interactions in the Mediterranean Water Buffalo in Brazil, for weight at 205 days of age, using reaction norm models via random regression. Methods: Data for buffaloes born between 1990 and 2014 were collected from five farms ascribed to the Brazilian Buffaloe Improvement Program, located in the North (1), Northeast (1), South (2) and Southeast (1) regions of Brazil. The initial database consisted of 5,280 observations at 205 days of age (W205). We assessed fit using two hierarchical reaction norm models: a two-step (HRNM2s) and a one-step (HRNM1s). Model fit was estimated using the Deviance Information Criterion, Deviance Based on Bayes Factors and Deviance based on Conditional Predictive Ordinate. The environmental descriptors were created to group individuals into common production environments based on year, season, herd and sex. Results: The best fit was obtained for the hierarchical reaction norm model with one-step (HRNM1s). Direct heritability estimates for this model ranged from 0.17 to 0.67 and the maternal heritability from 0.02 to 0.11 with increasing environmental gradient. Lower correlations among the sire classifications were obtained in comparison with HRNM1s in environments with low and high management, confirming the presence of genotype x environment interactions. Conclusion: We recommend a wider application of genetic evaluation in buffalo aimed at identifying optimal genotypes within specific environments.