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Expected increases in genetic merit from using optimized contributions in two livestock populations of beef cattle and sheep

机译:通过在两个肉牛和绵羊的牲畜群体中使用优化的贡献,预期的遗传价值增加

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摘要

The expected benefits from optimized selection in real livestock populations were evaluated by applying dynamic selection algorithms to two livestock populations of sheep (Meatlinc) and beef cattle (Aberdeen Angus). In addition, the effects of introducing BLUP evaluations on the population structure, genetic gain, and inbreeding were investigated. The use of BLUP-EBV accelerated the rates of gain in the Meatlinc, but the effects of BLUP evaluations on Aberdeen Angus are not as evident. Although steady increases in the average coefficient of inbreeding (F) were observed, the inbreeding rates (DeltaF) before and after the introduction of BLUP evaluations were not significantly different. The observed DeltaF in the last generation was 1.0% for Meatline and 0.2% for Aberdeen Angus. The application of the dynamic selection algorithms for maximizing genetic gain at a fixed DeltaF led to important expected increases in the rate of genetic gain (DeltaG). When DeltaF was restricted to the value observed in both populations, increments per year in DeltaG of 4.6 (i.e., 17%) index units for Meatlinc and 3.5 (i.e., 30%) index units for Aberdeen Angus were found in comparison to the DeltaG expected from conventional truncation BLUP selection. More relaxed constraints on DeltaF allowed even higher expected increases in DeltaG in both populations. This study demonstrates that the optimization tools constitute a potentially highly effective way of managing gain and inbreeding under a broad range of schemes in terms of scale and inbreeding level. No losses in genetic gain were associated with the use of dynamic optimization selection when schemes were compared at the same DeltaF.
机译:通过将动态选择算法应用于绵羊(Meatlinc)和肉牛(Aberdeen Angus)的两个牲畜种群,评估了在实际牲畜种群中优化选择的预期收益。此外,还研究了引入BLUP评估对种群结构,遗传增益和近交的影响。 BLUP-EBV的使用加速了Meatlinc中的增益速率,但是BLUP评估对阿伯丁安格斯的影响并不明显。尽管观察到的平均近亲繁殖系数(F)稳定增加,但引入BLUP评估前后的近亲繁殖率(DeltaF)并无显着差异。上一代产品中观察到的DeltaF为Meatline为1.0%,阿伯丁安格斯为0.2%。动态选择算法用于在固定的DeltaF上最大化遗传增益的应用导致遗传增益(DeltaG)的重要预期增加。当将DeltaF限制为在两个种群中观察到的值时,与预期的DeltaG相比,发现Meatlinc的DeltaG每年增加4.6(即17%)个指标单位,而阿伯丁安格斯的DeltaG每年增加3.5(即30%)个指标单位。从常规截断BLUP选择。对DeltaF的更宽松的限制使得两个人群中DeltaG的预期增长更高。这项研究表明,在规模和近亲水平方面,优化工具构成了一种在范围广泛的方案下管理收益和近亲的潜在高效方法。当在相同的DeltaF上比较方案时,使用动态优化选择不会导致遗传增益损失。

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