Guidelines to measure individual feed intake of dairy cows for genomic and genetic evaluations
R.F. Veerkamp, Y. de Haas, J.E. Pryce, M.P. Coffey, D.M. Spurlock, M.J. VandeHaar
Abstract
R.F. Veerkamp, Y. de Haas, J.E. Pryce, M.P. Coffey, D.M. Spurlock, M.J. VandeHaar
Abstract
The widespread use of genomic information in dairy cattle breeding programs haspresented the opportunity to select for feed intake and feed efficiency. This is becauseanimals from research herds can be used as a reference population to calibrate a genomicprediction equation, which is then used to predict the breeding value for selectioncandidates based on their own genotype. To implement genomic prediction and performgenetic analysis for feed intake, several partners have brought together their expertiseand existing feed intake records. Based on this experience we aim to provide someguidelines on the recording and handling of feed intake records. The consortium used amixture of standardised experimental data coming from larger genetic experiments orseveral smaller nutritional studies. The latter has provided some statistical challenges.Also, data was combined across countries, experimental herds and feeding systems. Despitethe perceived roughness of such data, it has proven to be very successful for genomicprediction, with proper statistical modelling. Ideally the whole lifetime of all cows shouldbe measured, but this is unrealistic. Often, animals are recorded for part of one (or more)lactation(s) only. Guidelines on the proper statistical modelling and usefulness of existingdata are needed. Selection index theory can help to establish the optimal recording periodacross and within lactation. It is also critical to identify how many records are requiredand what are the most informative animals for measuring feed intake. Geneticrelationships with the selection candidates are an important criterion. Finally, since(residual) feed intake is only part of the breeding goal, it is important to consider recordingof other traits as well, and the genetic parameters are needed to define the breeding goalsproperly.
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The widespread use of genomic information in dairy cattle breeding programs haspresented the opportunity to select for feed intake and feed efficiency. This is becauseanimals from research herds can be used as a reference population to calibrate a genomicprediction equation, which is then used to predict the breeding value for selectioncandidates based on their own genotype. To implement genomic prediction and performgenetic analysis for feed intake, several partners have brought together their expertiseand existing feed intake records. Based on this experience we aim to provide someguidelines on the recording and handling of feed intake records. The consortium used amixture of standardised experimental data coming from larger genetic experiments orseveral smaller nutritional studies. The latter has provided some statistical challenges.Also, data was combined across countries, experimental herds and feeding systems. Despitethe perceived roughness of such data, it has proven to be very successful for genomicprediction, with proper statistical modelling. Ideally the whole lifetime of all cows shouldbe measured, but this is unrealistic. Often, animals are recorded for part of one (or more)lactation(s) only. Guidelines on the proper statistical modelling and usefulness of existingdata are needed. Selection index theory can help to establish the optimal recording periodacross and within lactation. It is also critical to identify how many records are requiredand what are the most informative animals for measuring feed intake. Geneticrelationships with the selection candidates are an important criterion. Finally, since(residual) feed intake is only part of the breeding goal, it is important to consider recordingof other traits as well, and the genetic parameters are needed to define the breeding goalsproperly.
Key concepts: Genomic selection, Selection (genetic algorithm), Residual feed intake, Herd, Population, Dairy cattle, Statistics, Biotechnology