A method for the dynamic management of genetic variability in dairy cattle

Abstract

According to the general approach developed in this paper, dynamic management of genetic variability in selected populations of dairy cattle is carried out for three simultaneous purposes: procreation of young bulls to be further progeny-tested, use of service bulls already selected and approval of recently progeny-tested bulls for use. At each step, the objective is to minimize the average pairwise relationship coefficient in the future population born from programmed matings and the existing population. As a common constraint, the average estimated breeding value of the new population, for a selection goal including many important traits, is set to a desired value. For the procreation of young bulls, breeding costs are additionally constrained. Optimization is fully analytical and directly considers matings. Corresponding algorithms are presented in detail. The efficiency of these procedures was tested on the current Norman population. Comparisons between optimized and real matings, clearly showed that optimization would have saved substantial genetic variability without reducing short-term genetic gains.

Approaches to the management of inbreeding and relationship in the German Holstein dairy cattle population

“…The weighted mean lifetime net merit after adjustment to zero using a cost factor of $23 per 1% inbreeding as proposed by Smith et al (1998) was highest at an intermediate level of inbreeding. Colleau et al (2004) applied optimal mating methods for the procreation of young bulls to be progeny-tested, for the use of service bulls on nonelite cows and in a third distinct step for selection of AI bulls among all progeny tested bulls. At each step, the objective was to minimize the average pairwise relationship coefficient applying dynamically rules in a single step.…”

Use of different sources of information for the recovery and genetic management of endangered populations: Example with the extreme case of Iberian pig Dorado strain

“…These considerations imply the implementation of an explicit process of selection, which is in conflict with the general objective of maintaining the highest levels of genetic diversity. Consequently, selection and maintenance of genetic diversity must be balanced to optimise the conservation programme (Colleau et al, 2004;Grundy et al, 1998;Meuwissen, 1997).…”

Influence of mating systems and selection intensity on the extent of inbreeding and genetic gain in the Slovak Pinzgau cattle

“…This assumption was confirmed by stochastic simulation. The optimization of contributions can be implemented using Lagrangian multipliers (Meuwissen and Luo, 1992;Wray and Goddard, 1994;Brisbane and Gibson, 1995;Colleau et al, 2004). This approach has been shown to offer substantial improvements in genetic gain.…”