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Vet Med Sci ; 9(1): 380-390, 2023 01.
Article in English | MEDLINE | ID: mdl-36507777

ABSTRACT

BACKGROUND: There is large variation in genetic parameters in literature for growth traits in sheep. Reliable estimation of genetic parameters is required for developing breeding programmes. OBJECTIVES: The aim of this study was to aggregate results of different studies by meta-analysis to improve reliability of estimated parameters. METHODS: In the current study, 221 papers that have been published between 1995 and 2021 were reviewed. Using a random-effects model in the Comprehensive Meta-Analysis software, direct and maternal heritabilities, as well as, genetic and phenotypic correlations between growth traits were estimated in meat (M), wool (W) and dual-purpose (D) sheep breeds. The growth traits in this study were birth weight, 3-month weight, 6-month weight, 9-month weight and yearling weight. RESULTS: The combined direct heritability was the lowest for birth weight (0.190 ± 0.004, 0.198 ± 0.003 and 0.196 ± 0.004 for M, W and D breeds, respectively) and the highest for yearling weight (0.264 ± 0.010, 0.304 ± 0.005 and 0.285 ± 0.020 for M, W and D breeds, respectively). The maternal heritability was the lowest for yearling weight (0.085 ± 0.003, 0.055 ± 0.002 and 0.052 ± 0.005 for M, W and D breeds, respectively) and the highest for 6-month weight (0.240 ± 0.088, 0.164 ± 0.001 and 0.162 ± 0.006 for M, W and D breeds, respectively). The phenotypic and genetic correlations were lower between the weights measured at more distant intervals. The lowest genetic correlation was observed between birth weight and yearling weight (0.290 ± 0.051 for W breeds). CONCLUSIONS: The small standard errors could indicate that the aggregation of results from different studies improved the reliability of estimated parameters and reduced range of 95% confidence intervals. Hence, the results could be used with greater level of confidence in sheep breeding programmes.


Subject(s)
Meat , Wool , Sheep/genetics , Animals , Birth Weight/genetics , Reproducibility of Results , Phenotype
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