A Perspective on the Past and Future of Genetic Evaluations for Economically Important Traits in Cattle
A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal Genetics and Genomics".
Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 17029
Special Issue Editor
Special Issue Information
Dear Colleagues,
Over the last half-century, genetic evaluations have undergone steady progress in animal breeding programs. The development of methodological in terms of genetic theory and statistics along with technological advances in computing has resulted in analyses with high power and performance. The application and development of genetic evaluations have played a pivotal role in successful and progressive selection in many important traits in the cattle industry. In the pre-genomic era, traditional selection using information on phenotypes and pedigree to predict breeding values were considered by long generation intervals. With the introduction of high-density SNP chips and the use of genomic information, breeding schemes are undergoing major restructuring worldwide. Additionally, the application of genomic evaluation has led to the inclusion of more traits in the selection indices so that there is growing interest in the introduction of novel traits. Therefore, the possibilities of recording phenotypic performance, breeding goals, and breeding programs need to be reassessed. Further, more studies are necessary to determine whether the genetic architecture of the traits of interest and the population structure can be influenced to improve genomic prediction accuracy. In this issue, we will describe the application of genetic evaluation when a trait in a population is evaluated for the first time; for this, it is important to compare the accuracy of predictions from several genomic models to those obtained with a pedigree-based model, and how these changes will affect the future of the cattle industry.
Prof. Dr. Deukhwan Lee
Guest Editor
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Keywords
- genomic selection
- cattle
- breeding scheme
- prediction accuracy
- genetic parameters
- heritability
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