10 research outputs found
Studies on the value of incorporating the effect of dominance in genetic evaluations of dairy cattle, beef cattle and swine
Nonadditive genetic effects are currently ignored in national genetic evaluations of farm animals because of ignorance of thelevel of dominance variance for traits of interest and the difficult computational problems involved. Potential gains fromincluding the effects of dominance in genetic evaluations include “purification” of additive values and availability ofpredictions of specific combining abilities for each pair of prospective parents. This study focused on making evaluation withdominance effects feasible computationally and on ascertaining benefits of such an evaluation for dairy cattle, beef cattle,and swine. Using iteration on data, computing costs for evaluation with dominance effects included costs could be less thantwice expensive as with only an additive model. With Method Â, variance components could be estimated for problemsinvolving up to 10 millions equations. Dominance effects accounted for up to 10% of phenotypic variance; estimates werelarger for growth traits. As a percentage of additive variance, the estimate of dominance variance reached 78% for 21-d litterweight of swine and 47% for post weaning weight of beef cattle. When dominance effects are ignored, additive evaluationsare “contaminated”; effects are greatest for evaluations of dams in a single large family. These changes in ranking wereimportant for dairy cattle, especially for dams of full-sibs, but were less important for swine. Specific combining abilitiescannot be included in sire evaluations and need to be computed separately for each set of parents. The predictions of specificcombining abilities could be used in computerized mating programs via the Internet. Gains from including the dominanceeffect in genetic evaluations would be moderate but would outweigh expenditures to produce those evaluations
Genotype by environment interaction in Nelore cattle from five Brazilian states
Records from 75,941 Nelore cattle were used to determine the importance of genotype by environment interaction (GEI) in five Brazilian states. (Co)variance components were estimated by single-trait analysis (with yearling weight, W450, considered to be the same trait in all states) and multiple-trait analysis (with the record from each state considered to be a different trait). The direct heritability estimates for yearling weight were 0.51, 0.39, 0.44, 0.37 and 0.41 in the states of Goiás, Mato Grosso, São Paulo, Mato Grosso do Sul and Minas Gerais, respectively. The across-state genetic correlation estimates between Goiás and Mato Grosso, Goiás and Minas Gerais, São Paulo and Minas Gerais, and Mato Grosso do Sul and Minas Gerais ranged from 0.67 to 0.75. These estimates indicate that GEIs are biologically important. No interactions were observed between Goiás and São Paulo, Goiás and Mato Grosso do Sul, Mato Grosso and São Paulo, Mato Grosso and Mato Grosso do Sul, Mato Grosso and Minas Gerais, or São Paulo and Mato Grosso do Sul (0.82 to 0.97). Comparison of single and multiple-trait analyses showed that selection based on the former was less efficient in the presence of GEI, with substantial losses (up to 10%) during selection
Screening of whole genome sequences identified high-impact variants for stallion fertility
Interactive effects of genotype x environment on the live weight of GIFT Nile tilapias
Variance components for body weight in Japanese quails (Coturnix japonica)
The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH) and at 7 (BW07), 14 (BW14), 21 (BW21) and 28 days of age (BW28) of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model). Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch, 7, 14, 21 and 28 days old, respectively. These results indicate that heritability increased with age. On the other hand, after hatch there was a marked reduction in the maternal environment variance proportion of the phenotypic variance, whose estimates were 0.50; 0.11; 0.07; 0.07 and 0.08 for BWH, BW07, BW14, BW21 and BW28, respectively. The genetic correlation between weights at different ages was high, except for those estimates between BWH and weight at other ages. Changes in body weight of quails can be efficiently achieved by selection
Comparison of REML and Gibbs sampling estimates of multi-trait genetic parameters in Scots pine
Bayesian inference on field data for genetic parameters for some reproductive and related traits of Nellore cattle (Bos indicus)
We used Gibbs sampling in single and two-trait animal models to estimate genetic parameters for some reproductive and related traits of Nellore cattle (Bos indicus). Female traits were age at first calving (AFC), cumulative productivity (CP) and adult weight (AW). For males, scrotal circumferences at 365 and 450 days of age were analyzed. Gibbs sampling using the ‘Multiple Trait using Gibbs Sampling under Animal Model’ (MTGSAM) program of Van Tassel and Van Vleck was used to estimate the (co)variance components of the traits and conduct genetic analyses. Heritabilities were AFC = 0.26, AW = 0.36 and CP = 0.25 under the single-trait animal model. The mean, mode and median estimates for genetic parameters obtained from the marginal posterior distributions were similar for all traits except AW, which presented lower values for the mode than the mean and median. However, the marginal posterior distributions for the traits studied presented a tendency toward normality. Favorable, but low, negative genetic correlations were found between male scrotal circumference and female age at first calving. The reproductive traits showed medium-magnitude heritabilities, which indicates that these traits should respond to selection and therefore should be included in genetic improvement programs