Optimizing the breeding strategy in Vanaraja female parent line chicken by monitoring the genetic variability for the major performance traits.

ObjectiveA comprehensive study was conducted to study the effects of partition of variance on accuracy of genetic parameters and genetic trends of economic traits in Vanaraja male line/project directorate-1 (PD-1) chicken.MethodsVariance component analysis utilizing restricted maximum likelihood animal model was carried out with five generations data to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits in PD-1 chickens. Genetic trend was estimated by regression of the estimated average breeding values (BV) on generations.ResultsThe body weight (BW) and shank length (SL) varied significantly (p≤0.01) among the generations, hatches and sexes. The least squares mean of SL at six weeks, the primary trait was 77.44±0.05 mm. All the production traits, viz., BWs, age at sexual maturity, egg production (EP) and egg weight were significantly influenced by generation. Model four with additive, maternal permanent environmental and residual effects was the best model for juvenile growth traits, except for zero-day BW. The heritability estimates for BW and SL at six weeks (SL6) were 0.20±0.03 and 0.17±0.03, respectively. The BV of SL6 in the population increased linearly from 0.03 to 3.62 mm due to selection. Genetic trend was significant (p≤0.05) for SL6, BW6, and production traits. The average genetic gain of EP40 for each generation was significant (p≤0.05) with an average increase of 0.38 eggs per generation. The average inbreeding coefficient was 0.02 in PD-1 line.ConclusionThe population was in ideal condition with negligible inbreeding and the selection was quite effective with significant genetic gains in each generation for primary trait of selection. The animal model minimized the over-estimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.

Variance and genetic parameters were estimated for growth and production traits of synthetic broiler female line (PB-2) using REML animal model to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits. The overall least squares mean (LSM) for body weights at 0day (BW0), at 2weeks (BW2), at 4weeks (BW4), at 5weeks (BW5), shank length at 5weeks (SL5), and breast angle at 5weeks (BA5) of age were 40.03g, 207.40g, 589.58g, 828.51g, 76.89cm, and 80.78°, respectively. The overall LSM for egg production up to 40weeks of age (EP40) and egg weight at 40weeks (EW40) were 66.02 eggs and 58.23g, respectively. The heritability estimates using the best model for BW0, BW2, BW4, BW5, SL5, and BA5 were 0.06 ± 0.03, 0.19 ± 0.03, 0.15 ± 0.03, 0.14 ± 0.02, 0.08 ± 0.02, and 0.02 ± 0.01, respectively. The heritability estimates were low to moderate in the magnitude for all early growth traits. The heritability estimate for egg production up to 40weeks (EP40) was 0.30 ± 0.05. The heritability estimates for adult body weights at 20 and 40weeks of age (BW 20 and BW 40), age at sexual maturity (ASM), and egg weight at 40weeks (EW40) were 0.21 ± 0.04, 0.19 ± 0.04, 0.16 ± 0.03, and 0.33 ± 0.05, respectively, and the estimates were moderate to high in magnitude. Model 4 with additive, maternal permanent environmental, residual, and phenotypic effects was the best model for growth traits except for BW0 and BA5. The average genetic gain observed in primary trait (BW5) over the five generations was 13.62g per each generation indicating effective selection. The animal model minimized the overestimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.

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

Breeding value (BV), genetic parameters and additive genetic, and maternal effects were evaluated on growth and production traits utilizing data from eight generations employing animal model in a rural male parent line (PD-6) chicken at ICAR-Directorate of Poultry Research, Hyderabad, India. The least squares means (LSM) for body weight (BW) and shank length (SL) up to 6weeks of age varied significantly (p≤.01) among the generations and hatches. BW increased significantly (p≤.01) over the generations and decreased with the hatches. Sex also had a significant effect on BW and shank length except for BW at 0day (BW0). LSM for BW (BW6) and Shank length (SL6) at 6weeks of age were 598.84±0.79g and 74.57±0.04mm, respectively. Males recorded significantly (p≤.01) higher BWs and shank length. All the production traits were significantly (p≤.01) influenced by the generation effect. The overall LSM for age at sexual maturity (ASM), egg production at 40weeks (EP40) and egg weight at 40weeks (EW40) were 164.93±0.23days, 74.66±0.40 eggs and 54.79±0.08g, respectively. Model 3 with additive, maternal permanent environmental and residual effects was the appropriate model for BW2, BW4, BW6, SL4 and SL6, whereas Model 4 with maternal effects was the best for BW0. The heritability estimates for BW6 and SL6 were 0.22±0.02 and 0.18±0.02, respectively. Model 1 with additive direct and residual effects was the best appropriate model for all the production traits. The heritability estimates of EP40 and EW40 were 0.16±0.04 and 0.34±0.05, respectively. BW and shank length were highly correlated with significant (p≤.05) positive association from different components. The correlation coefficient from direct additive component between egg production and BW40 was negative, while it was positive with less magnitude between egg production and BW20. The egg production and egg weights had a negative association at different ages. BV of SL6, the primary trait of selection, was significant (p≤.05) across the generations and increased linearly with an average genetic gain of 1.05mm per generation. BV of BW6 was also significant (p≤.05) and increased linearly as correlated response with an average genetic response of 22.34g per generation. BV of EP40 showed an increasing trend with a genetic gain of 0.02 eggs per generation. The EW 40 also increased linearly with an average genetic gain of 0.06g. The average inbreeding coefficient of the population was 0.015. The study concluded that the population was in ideal status with a linearly increasing trend of average BV with negligible inbreeding over the eight generations of selection.

Estimation of Genetic Parameters and Evaluation of Breeding Program Designs with a Focus on Dairy Cattle in Low Input Production Systems

The size and shape of the cockerel comb, ran be regarded as secondary sexual characters or sexual ornaments. Sexual characters are assumed to be costly to express and the expression of a secondary sexual character is suggested to be favourably correlated with the bearer's condition or fitness. The aim of this study was to clarify the effects of selection for male sexual characters, the correlated responses in other male traits and whether selection for sexual characters affects viability. Two selection lines (lines S and H) and a control line was used for 10 generations. Line S was selected for male comb size at 29 weeks of age and from generation six onwards, comb shape (the way the cockerel bear his comb) was added. Line H was selected for high concentration of hyaluronic acid (HA) in the comb at 28 weeks of age. The average number of animals of each sex and;election line was 560 and the randomly mated control line comprised an average of 150 animals of each sex per generation. Traits recorded an analysed were comb size (CS) and body weight (BW) at 29 weeks of age, comb shape (SH) at 32 weeks of age, comb weight (CW) after slaughter and mortality (M). In line S, the genetic and phenotypic trends increased for CS, CW and BW. Both CS and SH are traits involved in the impression of comb size as visualized by females during male choice and by males during male-male competition. With artificial upward selection for the male character CS (line S), CS, CW, BW and M also increased but SH was impaired. When adding SH to the selection criteria in line S, the negative generic trend for SH was changed to positive. As CS approaches its environmental limit, the heritability and genetic progress can be expected to decline. It seems that 10 generations of selection for increased CS is not enough to reach the environmental limit at which CS is expected to stabilize at an optimum size determined by natural selection. (Less)

Variance and covariance components of growth and production traits were analyzed employing REML animal model to assess the Dahlem Red (PD-3) chicken population for direct additive genetic, maternal effects and to estimate the estimated breeding value (EBV), genetic parameters, genetic trends and rate of inbreeding (ΔF) utilizing seven generation’s data. The generation and hatch had significant (P≤0.01) effect on the body weight at 0 day (BW0), 2 (BW2), 4 (BW4) and 6 weeks (BW6) and shank length at six weeks of age (SL6). The average least squares means (LSM) for BW6 and SL6 were 273.93±0.62 g and 53.97±0.05 mm, respectively. All the production traits were significantly (P≤0.01) influenced by generation and hatch. The average LSM for age at sexual maturity (ASM), egg production up to 40 weeks (EP40) and egg mass up to 40 weeks (EM40) were 168.82±0.25 d, 72.60±0.41 eggs and 4.21±0.07 kg, respectively. Model 5 with additive direct, maternal genetic, maternal permanent environmental and residual variance components was the best for BW0, BW2 and BW4 based on the AIC values obtained in WOMBAT. Model 4 was the best model for BW6, SL6, ASM, EP40 and EM40 with additive direct, maternal permanent environmental and residual variance components. Maternal effects were higher during early age, decreased with age, and remained present until 20 weeks of age. The heritability (h2) estimates were low to moderate in magnitude for all the growth traits and ranged from 0.02±0.03 to 0.19±0.03. The maternal heritability was high at hatch (0.35±0.06), decreased gradually until 4th week (0.02±0.01) and ceased afterwards. The heritabilities of EP40 (0.11±0.03) and EM40 (0.12±0.04) were low. The direct additive genetic correlations (ra) between BW2, BW4, BW6 and SL6 were high and positive (P≤ 0.05). The additive genetic and maternal permanent environmental correlation between EP40 and EM40 were high and positive (P≤ 0.05). The EBV of EM40 was significant (P≤ 0.05) with 0.48 kg/generation in PD-3 chicken at the end of the seventh generation. The EBV of EP40 showed an increasing trend with a genetic gain of 1.87 eggs per generation. The average inbreeding coefficient of the population was 0.019 and average ΔF was 0.007 over the last seven generations of selection. The EBV trends for primary and associated traits showed linear trends in the desired direction and negligible inbreeding.

Long-term directional selection in a population can severely reduce the additive genetic variability for the desired trait. Therefore, it is really important to assess the genetic parameters of a population at definite time intervals for designing effective breeding programmes. The present study was designed for the genetic evaluation of a White Leghorn strain (IWI) which has been intensely selected for higher egg numbers up to 64 weeks of age at ICAR-Directorate of Poultry Research, Hyderabad, Telangana, India. The genetic parameters were estimated for egg production up to 24 (EP24), 32 (EP32), 40 (EP40), 52 (EP52), 64 (EP64) and 72 (EP72) weeks of age along with other traits (egg weight, reproductive and body weight traits) utilising six models with different random effects in a Bayesian framework. The normalised mean value for the primary selection trait, EP64, was 218.16 ± 1.24 eggs while the total egg production up to 72 weeks was 242.85 ± 1.72. Comparative evaluation of different models based on Deviance Information Criterion (DIC) revealed that model 6 (including direct additive, maternal genetic and maternal permanent environment effects) was the most accurate for early production traits like EP24, whereas model 3 (including direct additive and maternal genetic effects) was the best-fitted for egg production traits like EP32 and EP40. The trait variance for late egg production traits like EP52, EP64 and EP72 was best defined by model 1, which only included the direct additive effect. Furthermore, it was found that the posterior mean additive heritability of egg production traits declined as the laying cycle progressed. Particularly, for later traits like egg production up to 52 (EP52), 64 (EP64) and 72 (EP72) weeks, the direct additive heritability estimate was very low (0.02 ± 0.009; 0.04 ± 0.01 and 0.02 ± 0.0009 respectively). Subsequently, posterior genetic correlations (rG) were estimated between late egg production traits and the rest of the traits. It was found that there was a highly negative rG between egg weight at 40 weeks (EW40), body weight at 52 weeks (BW52) and the later egg production traits (EP52, EP64 and EP72). Therefore, depending on the trait correlations, multivariate analysis was done for improving the accuracy of evaluations. Posterior estimates of direct additive heritability for EP52 increased to 0.08 ± 0.05 when analysed together with EW40 and BW52 traits in a multivariate model, whereas the corresponding estimate for EP64 increased to 0.11 ± 0.05 when analysed with EW40 and BW52. Based on these results, we can conclude that although the additive genetic variability for the selection trait is very low in the population, multitrait evaluations can be more effective for making selection decisions for higher egg production in White Leghorns.

Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the lamb (birth and weaning weight and survival). Fixed effects were sex, birth status, year and age of dam. Weaning weights were pre-adjusted to a 100-day equivalent. For reproduction traits (considered as traits of the ewe), which included number and weight of lambs born and weaned, repeatability models were fitted. The random part consisted of direct additive and ewe and sire permanent environmental effects. Direct and maternal heritability estimates were 0.13 and 0.23 for birth weight and 0.07 and 0.09 for weaning weight. Corresponding proportions of total phenotypic variance due to maternal permanent and temporary environment were 0.09 and 0.28 and 0.06 and 0.22 respectively. The genetic correlation between animal effects was -0.23 in the case of birth weight. The results showed that temporary environment (full sibs within a year) generally has a major effect on all pre-weaning traits. The direct heritability estimate of survival was 0.02 while the temporary maternal environmental variance as a proportion of phenotypic variance was 0.10. The estimates obtained for number and weight of lambs born and weaned were generally low, ranging from 0.03 for number of lambs born to 0.11 for total weight at birth. The permanent environmental effect of the ewe accounted for 6-7% of the total phenotypic variance. Genetic correlations of total weight of lamb weaned with the other reproduction traits were generally high (0.64 to 0.92) with low standard errors. The corresponding phenotypic, environmental and ewe permanent environmental correlations were all medium to high and estimated with a fair deal of accuracy according to low standard errors. The genetic relationship between weaning weight of the ewe and her lifetime reproduction (accumulated over four lambing chances) ranged between 0.40 and 0.67. Correlations between number of lambs weaned per ewe and weight of lamb weaned per ewe were particularly high (0.8 - 0.9). It was concluded that the maternal environmental effect should be partitioned into two components (permanent and temporary) when data sets involving multiple births over many generations are considered. Keywords: Dormer sheep, Genetic parameters, Temporary and permanent environmental effects, Early growth, Survival and reproduction traits South African Journal of Animal Science Vol.33(4) 2003: 213-222

Genetic parameters and trends in the average daily gain (ADG), backfat thickness (BF), loin muscle area (LMA), lean percentage (LP), and age at 90kg (D90) were estimated for populations of Landrace and Yorkshire pigs. Additionally, the correlations between these production traits and litter traits were estimated. Litter traits included total born (TB) and number born alive (NBA). The data used for this study were obtained from eight farms during 1999 to 2016. Analyses were carried out with a multivariate animal model to estimate genetic parameters for production traits while bivariate analyses were performed to estimate the correlations between production and litter traits. The heritability estimates were 0.52 and 0.43 for ADG; 0.54 and 0.45 for BF; 0.25 and 0.26 for LMA; 0.54 and 0.48 for LP; and 0.56 and 0.46 for D90 in the Landrace and Yorkshire breeds, respectively. The ADG and D90 showed low genetic correlation with BF and LP. The LMA had -0.40, -0.32, 0.49, and 0.39 genetic correlations with ADG, BF, LP, and D90, respectively. Genetic correlations between production and litter traits were generally low, except for the correlations between LMA and TB (-0.23) in Landrace and ADG and TB (-0.16), ADG and NBA (-0.18), D90 and TB (0.19), and D90 and NBA (0.20) in Yorkshire. Genetic trends in production traits were all favorable except for LMA.

A total of 1979 lactation records from 550 selected crossbred dairy cows that born between 1974 and 2005 were used to estimate annual genetic and environmental trends in milk production and reproduction traits at Holetta Agricultural Research Center, Ethiopia. Annual genetic and environmental trends were estimated by regressing BLUP estimated breeding value on year of birth. Variance components and genetic parameters were estimated using univariate analysis of individual animal model based on restricted maximum likelihood procedures. Annual genetic trends were -3.384 days, -8.00 kg and -5.96 kg, -0.26 months, -0.29 months and -0.88 days, for lactation length (LL), lactation milk yield (LMY), adjusted 305 milk yield (305-days MY), age at puberty (APU), age at first calving (AFC) and calving interval (CI), respectively. Environmental trends for LMY was positive (6.717 kg) and was in the desired direction. Heritability estimates were 0.14, 0.44, 0.39, 0.38, 0.40 and 0.17 for LL, LMY, 305-d MY, APU, AFC and CI, respectively. Negative genetic trends in all milk production traits reflect ineffective selection program and/or lack of using sires that have positive breeding values. The result from the environmental trends shows substantial improvement in the management practices over time. Contrasting directions in genetic and environmental trends reflect ineffective breeding objectives. This warrants reconsideration of the existing breeding program in the country. Key words: Genetic trends, environmental trends, genetic parameters, breeding objectives, variance components.

Genetic parameters and trends for daughters of imported and Thai Holstein sires for age at first calving and milk yield

Milkability is an important functional trait, which is directly related to milking costs and udder health. There are no milkability traits incorporated in the South African dairy cattle breeding objectives and genetic parameter estimates for these traits are not available in this population. The main objective of the study was, therefore, to estimate the genetic parameters for milkability traits and its correlation with somatic cell scores in South African Holstein cattle. Data consisted of production and milkability records of 2719 Holstein cows, from ten herds, collected from 2016 to 2018. Genetic parameters were estimated by a multi-trait animal model using the restricted maximum likelihood (REML) procedure. Means for milking time (MT), average milk flow (AMF), maximum milk flow (MMF), and somatic cell score (SCS) were 5.20min, 1.91kg/min, 2.99kg/min, and 2.06, respectively. The heritability estimates were low to moderate from 0.19 ± 0.07, 0.24 ± 0.06, 0.36 ± 0.11, and 0.41 ± 0.12, respectively, for SCS, AMF, MT, and MMF. The genetic correlations were significant (P < 0.05) among the three milkability traits ranged from - 0.31 ± 0.05 between AMF and MT to 0.85 ± 0.02 between AMF and MMF. Positive genetic correlations were observed between AMF and MMF, while the correlations for MT with the remaining milkability traits were negative. Genetic correlations of SCS with AMF, MMF, and MT were - 0.13 ± 0.04, 0.13 ± 0.04, and - 0.25 ± 0.12, respectively. The mean estimated breeding value (EBV) was estimated using cattle birth dates, and there was an increase in AMF of 0.0001kg/min EBV per year on cattle born during the period 2002 to 2014. Maximum milk flow also showed an increasing genetic trend of 0.0003kg/min per year over the same period. On the other hand, the genetic trend for MT was undesirable, as it increased by 0.0003kg/min per year. The moderate to high heritability estimates for milkability traits showed that selection for improvement was possible in South African Holstein cattle. High genetic correlation between AMF and MMF implied that these two may be regarded as the same trait. Milking time can contribute towards improving the accuracy of estimating EBVs for SCS in a multi-trait analysis, and vice versa, due to the moderate correlation between the two traits. The marginal genetic trend in milkability traits may be an interrelated response to selection of other traits already under selection in the population such as SCS. Results of the current study provided a basis for including milkability traits of South African Holstein cattle in the breeding objectives.

Short term selection response for egg mass at 52 weeks of age (EM52), the primary trait of selection and the correlated response of other production traits was evaluated utilizing the last five generations data of Vanaraja female line (PD-2) at ICAR-Directorate of Poultry Research, Hyderabad. The phenotypic and genetic response for EM52 was significant with a magnitude of 341.9 and 237.4 g per generation, respectively. The correlated response of egg production at 52 weeks was also significant with 5.68 and 4.37 eggs per generation on genetic and phenotypic scale, respectively. The age at sexual maturity reduced over the generation in a desired direction. The least square means (LSMs) for production traits (EM52, EP52, EW52, EP 40 and ASM) varied significantly across the generations. The LSMs of EM52 (7898±2.01 g) and EP52 (138.60±0.03 eggs) were significantly higher in S-5 generation. Selection intensity (i) ranged from 0.44 to 1.10 and the rate of inbreeding was 0.003. Realized and estimated heritabilities of EM52 were 0.04 and 0.11, respectively. The significant improvement in primary trait and other important correlated traits indicated the effectiveness of Osborn index selection in PD-2 line, which will contribute to the improvement in egg production and egg weight in terminal cross Vanaraja chicken variety.

Aim: This study investigates the genetic parameters and trends in production traits of Murrah buffaloes over a 24-year period (1996-2019) at a farm in Hisar, Haryana. Data on key production traits including 305 days milk yield (305DMY), peak yield (PY), lactation length (LL), dry period (DP), lactation milk yield (LMY), and wet average (WA) were collected from 614 Murrah buffaloes. Methodology: Utilizing a univariate animal model, the average estimated breeding values for the production traits were computed: 2148.05 kg for 305DMY, 10.74 kg/day for PY, 319.19 days for LL, 117.88 days for DP, 2288.80 kg for LMY, and 7.12 kg/day for WA. Results: The study revealed a minimum genetic correlation of -0.81 and a phenotypic correlation of -0.32 between LL and WA. Heritability estimates for 305DMY, PY, LL, DP, LMY, and WA ranged from 0.13 to 0.48, while repeatability estimates varied from 0.35 to 0.54. The genetic trends were positive for all production traits except LL and DP, while phenotypic trends had positive values for all traits except DP. Conclusion: From this study, it can be inferred that selecting based on peak yield as a benchmark would be more fit for achieving correlated improvements in other production traits.