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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 Meatlinc 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.

Expected increases in genetic merit from using optimized contributions in two livestock populations of beef cattle and sheep1