Quantifying the effective contribution of phenotypic records to genetic evaluations: a case study on enteric methane emissions
Abstract
In the context of data sharing for genetic evaluation, such as enteric methane emissions in cattle, quantifying the effective contributions of phenotypic records to genetic evaluations is essential. This research introduces a framework for estimating the effective contribution of phenotypic records to genetic evaluations, using the concept of effective record contributions (ERCs). Our three-step approach involves: 1) computing reliabilities of a pedigree-based genetic evaluation using phenotypic information, 2) approximating ERCs due to own records, free of contributions due to relationships, from reliabilities of phenotyped animals using a reverse reliability algorithm, and 3) calculating the total effective contribution of phenotypic records as the sum of ERCs associated with all phenotyped animals. We apply this approach to a Dutch dataset comprising 187 219 records of weekly enteric methane emissions from 8 668 Holstein cows measured between March 2019 and April 2024. The pedigree spans five generations. Estimated heritability and repeatability were 0.18 and 0.47, respectively. We evaluate the effective contribution of weekly enteric methane emission records using: 1) the entire dataset, 2) a subset spanning until October 2023, instead of April 2024, 3) a dataset reduced by over 30% and limited to 20 records per animal, and 4) the entire dataset but considering the weekly enteric methane trait as an indicator trait genetically correlated to an hypothetical trait of interest with an heritability of 0.20 and a genetic correlation of 0.80. Results show that the entire dataset corresponds to 12 671 ERCs for the weekly enteric methane emission trait, which remains similar after reducing the number of weekly records by over 30%. The subset spanning until October 2023 corresponds to 10 870 ERCs. The reduction of ERCs can be explained by a smaller amount of records, but also by a smaller amount of recorded animals. Finally, when calculating the effective contribution to a correlated trait of interest, the entire dataset with weekly methane emission records corresponds to only 3 286 ERCs. Our approach provides a flexible framework for quantifying the effective contribution of phenotypic records to genetic evaluations. The proposed framework can be extended for optimizing data collection schemes when aiming to optimize the accuracy of genetic evaluations.
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