A reaction norm sire model to study the effect of metabolic challenge in early lactation on the functional longevity of dairy cows. Ha, N., Sharifi, A. R., Heise, J., Schlather, M., Schnyder, U., Gross, J. J., Schmitz-Hsu, F., Bruckmaier, R. M., & Simianer, H. Journal of Dairy Science, 100(5):3742–3753, 2017. doi abstract bibtex Due to the discrepancy of the high energy demand for rapidly increasing milk production and limited feed intake in the transition period around parturition, dairy cows require considerable metabolic adaptations. We hypothesize that some cows are genetically less suited to cope with these metabolic needs than others, leading to adverse follow-up effects on longevity. To test this, we designed a reaction norm model in which functional lifetime was linked to the metabolic challenge in the beginning of the first lactation. As challenge variables, we used either the sum of milk yield or the accumulated fat-to-protein ratio of the first 3 test-days (\textless120 d in milk), pre-adjusted for herd-test-day variance. We defined a random regression sire model, in which a random slope was estimated for each sire to assess whether a bull had robust (neutral or positive slopes) or non-robust (negative slopes) daughters. We fitted the model to data of $∼$580,000 daughters of $∼$5,000 Brown Swiss bulls with suitable observations available ($≥$10 daughters per bull). To validate our proposed model and assess the reliability of the estimated (co)variance components, we conducted an extensive bootstrap approach. For both challenge variables, we found the sire variance for the slope of the random regression to be significantly different from zero, suggesting a genetic component for metabolic adaptability. The results of the study show that the ability to cope with metabolic stress in the transition period has a genetic component, which can be used to breed metabolically robust dairy cows.
@article{Ha2017AReaction,
abstract = {Due to the discrepancy of the high energy demand for rapidly increasing milk production and limited feed intake in the transition period around parturition, dairy cows require considerable metabolic adaptations. We hypothesize that some cows are genetically less suited to cope with these metabolic needs than others, leading to adverse follow-up effects on longevity. To test this, we designed a reaction norm model in which functional lifetime was linked to the metabolic challenge in the beginning of the first lactation. As challenge variables, we used either the sum of milk yield or the accumulated fat-to-protein ratio of the first 3 test-days ({\textless}120 d in milk), pre-adjusted for herd-test-day variance. We defined a random regression sire model, in which a random slope was estimated for each sire to assess whether a bull had robust (neutral or positive slopes) or non-robust (negative slopes) daughters. We fitted the model to data of $\sim$580,000 daughters of $\sim$5,000 Brown Swiss bulls with suitable observations available ($\geq$10 daughters per bull). To validate our proposed model and assess the reliability of the estimated (co)variance components, we conducted an extensive bootstrap approach. For both challenge variables, we found the sire variance for the slope of the random regression to be significantly different from zero, suggesting a genetic component for metabolic adaptability. The results of the study show that the ability to cope with metabolic stress in the transition period has a genetic component, which can be used to breed metabolically robust dairy cows.},
author = {Ha, Ngoc-Thuy and Sharifi, A. R. and Heise, J. and Schlather, M. and Schnyder, U. and Gross, J. J. and Schmitz-Hsu, F. and Bruckmaier, R. M. and Simianer, H.},
year = {2017},
title = {A reaction norm sire model to study the effect of metabolic challenge in early lactation on the functional longevity of dairy cows},
keywords = {gen;postdoc},
pages = {3742--3753},
volume = {100},
number = {5},
journal = {Journal of Dairy Science},
doi = {10.3168/jds.2016-12031},
file = {http://www.ncbi.nlm.nih.gov/pubmed/28284692},
howpublished = {refereed}
}
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