Recent Advances in Animal Breeding Theory

Abstract

Recent developments in animal breeding theory have been driven largely by computer science and molecular biology. Several of the theories designed for practical application to animal breeding are heavy computing requirements. The development of computer hardware and of many algorithms for constructing and solving mixed model equations (MME) has enabled breeding values to be estimated from data on a huge number of animals by best linear unbiased prediction (BLUP) procedures. It has also enabled genetic parameters to be estimated by restricted maximum likelihood (REML). However, because the size of the MME that can be analyzed by REML depends on the genetic model and the numbers of traits and animals, all kinds of data cannot be used to estimate genetic parameters by even the latest supercomputers. For this reason, traditional theories are still being improved and new theories studied for practical applications to animal breeding. Traditional quantitative genetics theory has been based almost exclusively on the assumption that genetic variation in quantitative traits of interest is controlled by polygenes. On the other hand, molecular genetics techniques have made it possible to estimate individual genotypes. Because DNA marker information can be obtained by using these molecular biological techniques, theoretical studies of linkage mapping, detection of quantitative trait loci (QTLs), and the potential for marker-assisted or genotype selection have been developed in the last decade. Information on QTLs with large effects will be used for the genetic improvement of animals in the near future. These new technologies will not replace existing animal breeding practices, but will be blended with them through the use of breeding program design and genetic evaluation methods that cover both known and unknown QTLs

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