Abstract
BackgroundMilkability, primarily evaluated by measurements of milking speed and time, has an economic impact in milk production of dairy cattle. Recently the Italian Brown Swiss Breeders Association has included milking speed in genetic evaluations. The main objective of this study was to investigate the possibility of implementing genomic selection for milk flow traits in the Italian Brown Swiss population and thereby evaluate the potential of genomic selection for novel traits in medium-sized populations. Predicted breeding values and reliabilities based on genomic information were compared with those obtained from traditional breeding values.MethodsMilk flow measures for total milking time, ascending time, time of plateau, descending time, average milk flow and maximum milk flow were collected on 37 213 Italian Brown Swiss cows. Breeding values for genotyped sires (n = 1351) were obtained from standard BLUP and genome-enhanced breeding value techniques utilizing two-stage and single-step methods. Reliabilities from a validation dataset were estimated and used to compare accuracies obtained from parental averages with genome-enhanced predictions.ResultsGenome-enhanced breeding values evaluated using two-stage methods had similar reliabilities with values ranging from 0.34 to 0.49 for the different traits. Across two-stage methods, the average increase in reliability from parental average was approximately 0.17 for all traits, with the exception of descending time, for which reliability increased to 0.11. Combining genomic and pedigree information in a single-step produced the largest increases in reliability over parent averages: 0.20, 0.24, 0.21, 0.14, 0.20 and 0.21 for total milking time, ascending time, time of plateau, descending time, average milk flow and maximum milk flow, respectively.ConclusionsUsing genomic models increased the accuracy of prediction compared to traditional BLUP methods. Our results show that, among the methods used to predict genome-enhanced breeding values, the single-step method was the most successful at increasing the reliability for most traits. The single-step method takes advantage of all the data available, including phenotypes from non-genotyped animals, and can easily be incorporated into current breeding evaluations.
Highlights
Milkability, primarily evaluated by measurements of milking speed and time, has an economic impact in milk production of dairy cattle
Using a six-trait animal model similar to the model described in Gray et al [5], traditional breeding values and parent averages for the genotyped bulls were predicted for total milking time (TMT), AT, TP, DT, Maximum Milk Flow (MMF) and Average Milk Flow (AVGF) applying the BLUP methodology with
Estimates were low for the milking time traits, except for TP and milk flow traits, which had moderate heritabilities
Summary
Milkability, primarily evaluated by measurements of milking speed and time, has an economic impact in milk production of dairy cattle. Predicted breeding values and reliabilities based on genomic information were compared with those obtained from traditional breeding values. In 2001, Meuwissen et al [1] described how breeding values can be predicted from marker data alone in order to obtain what are commonly known as direct genomic values (DGV). These values are calculated as the sum of the effects of dense genetic markers across the genome, capturing all quantitative trait loci (QTL) that contribute to variation in the trait. Wiggans et al [2] reported an increase in reliabilities of US genomic predictions using an Illumina 50 k panel [3] as compared to predictions of genetic merit based on traditional parental averages
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