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Two scientist developed a way to incorporate this large amount of SNP data in the current methods for the estimation of breeding values of individual animals: Theo Meuwissen (currently professor in Ås, Norway) and Mike Goddard (currently emeritus professor in Melbourne, Australia). Main idea behind genomic selection is that the association between the DNA composition and the performance of animals can add to the estimated breeding value based on phenotypic measurements, or even replace it. ThenIn the latter case, you don’t have to wait until the phenotype can be measured on the animals anymore because you have the associated DNA information. It gives the possibility to select animals already at very early age on their DNA composition and you don’t have to wait until they become adult and you can measure their performance. In a large population of animals with phenotypic data is genotyped for thousands of DNA markers. In this so-called reference population the relation with the markers and the phenotypes is established and used for the prediction for the genotypic values of animals that are only genotyped. This method, called genomic selection, can also be used for traits that are difficult to measure such as disease related traits. The aim would be to prevent diseases in as many animals as possible. It would be highly desirable if you would only need to infect a limited number of animals and measure their response to the infection, link that to their DNA, and use that estimated link to predict the sensitivity of other animals to that disease based on their DNA, without the need to infect them. More about genomic selection later in this book. Meuwissen and Goddard (and co-workers) even take it a step further and already work on methods to incorporate whole genomic sequences, the 3 billion base pairs of an individual (WGS ) in estimating genomic breeding values. The introduction and application of genomic selection had a major impact on the structure of breeding programs.