Major Advances in Genetic Evaluation Techniques

摘要

The past quarter-century in genetic evaluation of dairy cattle has been marked by evolution in methodology and computer capacity, expansion in the array of evaluated traits, and globalization. Animal models replaced sire and sire-maternal grandsire models and, more recently, application of Bayesian theory has become standard. Individual test-day observations have been used more effectively in estimation of lactation yield or directly as input to evaluation models. Computer speed and storage are less limiting in choosing procedures. The increased capabilities have supported evaluation of additional traits that affect the net profitability of dairy cows. The importance of traits other than yield has increased, in a few cases due to an antagonistic relationship with yield. National evaluations combined internationally provide evaluations for bulls from all participating countries on each of the national scales, facilitating choices from among many more bulls. Selection within countries has increased inbreeding and the use of similar genetics across countries reduces the previously available outcross population. Concern about inbreeding has prompted changes in evaluation methodology and mating practices, and has promoted interest in crossbreeding. In just the past decade, distribution of genetic evaluations has gone from mailed paper or computer tapes for a limited audience to publicly accessible, request-driven distribution via the Internet. Among the distributed information is a choice of economic indices that combine an increasing array of traits into numbers reflecting breeding goals under different milk-pricing conditions. Considerable progress in genomics and the mapping of the bovine genome have identified markers for some deleterious recessive genes, but broader benefits of marker-assisted selection are still in the future. A possible exception is the proprietary use of DNA testing by semen producers to select among potential progeny test bulls. The collection and analysis of industry-wide data to evaluate ge- netic merit will continue to be the most important tool for genetic progress into the foreseeable future.