Estimation of additive, maternal and non-additive genetic effects of preweaning growth traits in a multibreed beef cattle project

2003 ◽  
Vol 74 (3) ◽  
pp. 169-179 ◽  
Author(s):  
Mahmoud ABDEL-AZIZ ◽  
Stephan Johannes SCHOEMAN ◽  
Gail F. JORDAAN
Keyword(s):  
Beef Cattle ◽  
Growth Traits ◽  
Genetic Effects ◽  
Additive Genetic Effects

scholarly journals A multivariate analysis with direct additive and inbreeding depression load effects

2019 ◽  
Vol 51 (1) ◽  
Author(s):  
Luis Varona ◽  
Juan Altarriba ◽  
Carlos Moreno ◽  
María Martínez-Castillero ◽  
Joaquim Casellas
Keyword(s):  
Beef Cattle ◽  
Inbreeding Depression ◽  
Negative Correlation ◽  
Simulated Data ◽  
Genetic Effects ◽  
Strong Negative Correlation ◽  
Additive Variance ◽  
Inbreeding Coefficients ◽  
Load Effects ◽  
Additive Genetic Effects

Abstract Background Inbreeding is caused by mating between related individuals and its most common consequence is inbreeding depression. Several studies have detected heterogeneity in inbreeding depression among founder individuals, and recently a procedure for predicting hidden inbreeding depression loads associated with founders and the Mendelian sampling of non-founders has been developed. The objectives of our study were to expand this model to predict the inbreeding loads for all individuals in the pedigree and to estimate the covariance between the inbreeding loads and the additive genetic effects for the trait of interest. We tested the proposed approach with simulated data and with two datasets of records on weaning weight from the Spanish Pirenaica and Rubia Gallega beef cattle breeds. Results The posterior estimates of the variance components with the simulated datasets did not differ significantly from the simulation parameters. In addition, the correlation between the predicted and simulated inbreeding loads were always positive and ranged from 0.27 to 0.82. The beef cattle datasets comprised 35,126 and 75,194 records on weights between 170 and 250 days of age, and pedigrees of 308,836 and 384,434 individual-sire-dam entries for the Pirenaica and Rubia Gallega breeds, respectively. The posterior mean estimates of the variance of inbreeding depression loads were 29,967.8 and 28,222.4 for the Pirenaica and Rubia Gallega breeds, respectively. They were larger than those of the additive variance (695.0 and 439.8 for Pirenaica and Rubia Gallega, respectively), because they should be understood as the variance of the inbreeding depression achieved by a fully inbred (100%) descendant. Therefore, the inbreeding loads have to be rescaled for smaller inbreeding coefficients. In addition, a strong negative correlation (− 0.43 ± 0.10) between additive effects and inbreeding loads was detected in the Pirenaica, but not in the Rubia Gallega breed. Conclusions The results of the simulation study confirmed the ability of the proposed procedure to predict inbreeding depression loads for all individuals in the populations. Furthermore, the results obtained from the two real datasets confirmed the variability in the inbreeding depression loads in both breeds and suggested a negative correlation of the inbreeding loads with the additive genetic effects in the Pirenaica breed.

Estimates of genetic parameters for growth traits of Gobra cattle

1998 ◽  
Vol 66 (2) ◽  
pp. 349-355 ◽  
Author(s):  
M. Diop ◽  
L. D. Van Vleck
Keyword(s):  
Animal Models ◽  
Maternal Effects ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Random Effect ◽  
Random Effect Model ◽  
Genetic Effects ◽  
Breeding Value ◽  
Effect Model ◽  
Additive Genetic Effects

AbstractEstimates of (co)variance components and genetic parameters were obtained for birth (no. = 3909), weaning (no. = 3425), yearling (no. = 2763), and final weight (no. = 2142) for Gobra cattle at the Centre de Recherches Zootechniques de Dahra (Senegal), using single trait animal models. Data were analysed by restricted maximum likelihood. Four different animal models were fitted for each trait. Model 1 considered the animal as the only random effect. Model 2 included in addition to the additive direct effect of the animal, the environmental effect due to the dam. Model 3 added the maternal additive genetic effects and allowed a covariance between the direct and maternal genetic effects. Model 4 fitted both maternal genetic and permanent environmental effects. Inclusion of both types of maternal effects (genetic and environmental) provided a better fit for birth and weaning weights than models with one maternal effect only. For yearling and final weights, the improvement was not significant. Important maternal effects werefound for all traits. Estimates of direct heritabilities were substantially higher when maternal effects were ignored. Estimates of direct and maternal heritabilities with model 4 were 0·07 (s.e. 0·03) and 0·04 (s.e. 0·02), 0·20 (s.e. 0·05) and 0·21 (s.e. 0.05), 0·24 (s.e. 0·07) and 0·21 (s.e. 0·06), and 0·14 (s.e. 0·06) and 0.16 (s.e. 0·06) for birth, weaning, yearling and final weights, respectively. Correlations between direct and maternal genetic effects were negative for all traits, and large for weaning and yearling weights with estimates of -0·61 (s.e. 0·33) and -0·50 (s.e. 0·31), respectively. There was a significant positive linear phenotypic trend for weaning and yearling weights. Linear trends for additive direct and maternal breeding values were not significant for any trait except maternal breeding value for yearling weight.

Determination of genetic effects of SERPINA3 on important growth traits in beef cattle

2019 ◽  
Vol 31 (2) ◽  
pp. 164-173
Author(s):  
Shi-Zhen Yang ◽  
Hua He ◽  
Zi-Jing Zhang ◽  
Hui Niu ◽  
Fu-Ying Chen ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Growth Traits ◽  
Genetic Effects

GENETIC EFFECTS ON POSTWEANING GROWTH OF THREE-WAY CROSS BEEF CATTLE

1988 ◽  
Vol 68 (3) ◽  
pp. 647-654 ◽  
Author(s):  
G. W. RAHNEFELD ◽  
G. M. WEISS ◽  
H. T. FREDEEN ◽  
J. A. NEWMAN ◽  
J. E. LAWSON
Keyword(s):  
Beef Cattle ◽  
Key Words ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Genetic Effects ◽  
Genetic Interactions ◽  
Cross Breeding ◽  
Terminal Sire ◽  
Daily Gain ◽  
Sire Breed

Genetic effects on postweaning growth traits were evaluated for 3592 crossbred steers and heifers fed at two locations, Brandon, Manitoba and Lacombe, Alberta during a 6-yr period (1973–1978). The calves were sired by Chianina (Chi), Charolais (C), Limousin (L) and Simmental (S) bulls mated to 10 F1 dam-crosses representing the Hereford × Angus (HA) and nine dam-cross combinations produced by mating C, S and L sires with H, A and Shorthorn (N) females. Progeny rankings by terminal sire breed for weight on-test were C = Chi = S > L. For the trait 140-d postweaning average daily gain, progeny rankings were C > Chi = S, C = Chi > L and Chi > S > L. The progeny from the majority of "exotic" cross-dams were heavier on-test, and had higher postweaning average daily gain than progeny from HA dams. Ranking of dam-crosses according to their breed of sire (DS) for the trait weight on-test were S > C > L. The DS comparisons for postweaning average daily gain were C > S > L. The ranking of dam-crosses by breed of dam's dam, for on-test weight and postweaning average daily gain were N > H = A. Genetic interactions (terminal sire by breed cross of dam) were absent. Genotype environment interactions involving breed of terminal sire with year, sex and location were found for weight on-test and postweaning average daily gain. All resulted from changes in the magnitude of breed of sire differences, not from changes in sire rankings. Key words: Cattle, breeds, cross breeding, growth

Evaluation of beef cattle genotypes and estimation of direct and maternal genetic effects in a tropical environment. 1. Growth traits

2003 ◽  
Vol 54 (10) ◽  
pp. 1013 ◽  
Author(s):  
K. C. Prayaga
Keyword(s):  
Beef Cattle ◽  
Least Squares ◽  
Bos Taurus ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Bos Indicus ◽  
Genetic Effects ◽  
Additive Effects ◽  
Weaning Weight ◽  
Final Weight

Data from a crossbreeding experiment conducted during 1992–97 involving 31 genotypes from tropically adapted British (B), Sanga-derived (S), Zebu cross (Zx), Zebu (Z), and Continental (C) beef cattle breed groups were analysed to compare least-squares means, direct and maternal genetic effects, and heterosis estimates for birthweight, weaning weight, yearling weight, final weight (18 months), and pre- and post-weaning average daily gain (ADG). The genotypes were regrouped as Bos taurus (B, S, C)- and Bos indicus (Z, Zx)-derived groups to enable the comparison of direct (dD) and maternal (mD) dominance effects among indicine (II), taurine–indicine (TI), and taurine (TT) crosses. Genotype, contemporary group (year of birth, season of birth, and age of the dam), sex, and genotype × sex interactions were significant (P < 0.01) sources of variation for all the traits. Treatment to control parasites significantly (P < 0.01) affected post-weaning growth traits. In general, crossbred calves performed better than purebred calves. Z dam breeds resulted in lower birthweight, and Z sire breeds and S dam breeds resulted in heavier birthweights. For traits after birth, ZC and ZC crosses with S and Z showed heavier weights and higher gains. Prior to weaning, males weighed significantly more and gained weight at a faster rate than females in most of the crossbreds. Weight gain was relatively low between weaning and yearling age.Direct and maternal additive effects were estimated as a deviation from the British breed group mean for various traits. Direct additive effects of C, Z, and S were high and significantly different from the British mean for all the growth traits. Maternal additive effects of C were low and not significantly different from the British mean. Large negative maternal additive effects of Z and Zx caused lower birthweights of calves from Z and Zx dams. A decrease of maternal additive effect from weaning to final weight and pre-weaning to post-weaning ADG was noticed. The magnitude of dD effects was higher in TI crosses than in II crosses for all the traits except for birthweight, indicating the advantage of Bos taurus × Bos indicus crosses. In TT crosses, dD was only significant for weaning weight (P�<�0.01) and pre-weaning ADG (P < 0.05). Significant (P < 0.01) and positive mD effects observed in TI crosses indicated a better maternal environment provided by crossbred dams. High correlation coefficient estimates (0.92–0.99) between least-squares means and predicted means, observed for a set of F1 genotypes, indicated the prediction of performance of untested genotypes with reasonable accuracy. The per cent heterosis estimates were higher in Zebu × British breed crosses.

Influence of maternal and additive genetic effects on offspring growth traits in Beetal goat

2021 ◽  
Author(s):  
Ankit Magotra ◽  
Yogesh C. Bangar ◽  
Ashish Chauhan ◽  
B.S. Malik ◽  
Z.S. Malik
Keyword(s):  
Growth Traits ◽  
Genetic Effects ◽  
Offspring Growth ◽  
Additive Genetic Effects ◽  
Beetal Goat

32 A Bayesian Hierarchical Model to Integrate Growth Models into Genomic Evaluation of Pigs

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 18-19
Author(s):  
Haipeng Yu ◽  
Jaap Milgen ◽  
Egbert Knol ◽  
Rohan Fernando ◽  
Jack C Dekkers
Keyword(s):  
Genomic Prediction ◽  
Genetic Improvement ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Genetic Effects ◽  
Latent Growth ◽  
Bayesian Hierarchical ◽  
Additive Genetic Effects ◽  
Daily Gain ◽  
Genomic Predictions

Abstract Genomic prediction has advanced genetic improvement by enabling more accurate estimates of breeding values at an early age. Although genomic prediction is efficient in predicting traits dominated by additive genetic effects within common settings, prediction in the presence of non-additive genetic effects and genotype by environmental interactions (GxE) remains a challenge. Previous studies have attempted to address these challenges by statistical modeling, while the augmentation of statistical models with biological information has received relatively little attention. A pig growth model assumes growth performance is a nonlinear functional interaction between the animal’s genetic potential for underlying latent growth traits and environmental factors and has the potential to capture GxE and non-additive genetic effects. The objective of this study was to integrate a nonlinear stable Gompertz function of three latent growth traits and age into genomic prediction models using Bayesian hierarchical modeling. The three latent growth traits were modeled as a linear combination of systematic environmental, marker, and residual effects. The model was applied to daily body weight data from ~83 to ~186 days of age on 4,039 purebred boars that were genotyped for 24K markers. Bias and prediction accuracy of genomic predictions of selection candidates were assessed by extending the linear regression method of predictions based on part and whole data to a non-linear setting. The accuracy (bias) of genomic predictions was 0.58 (0.82), 0.46 (0.90), 0.54 (0.78), and 0.60 (0.84) for the three latent growth traits and average daily gain derived from integrated nonlinear model, respectively, compared to 0.58 (0.87) for genomic predictions of average daily gain using standard linear models. In subsequent work, the growth model will be extended to include daily feed intake and carcass composition data. Resulting models are expected to substantially advance genetic improvement in pigs across environments. Funded by USDA-NIFA grant # 2020-67015-31031.

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