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Simianer H, Heise J, Rensing S, Pook T, Geibel J, Reimer C. How economic weights translate into genetic and phenotypic progress, and vice versa. Genet Sel Evol 2023; 55:38. [PMID: 37291496 DOI: 10.1186/s12711-023-00807-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 04/27/2023] [Indexed: 06/10/2023] Open
Abstract
BACKGROUND This paper highlights the relationships between economic weights, genetic progress, and phenotypic progress in genomic breeding programs that aim at generating genetic progress in complex, i.e., multi-trait, breeding objectives via a combination of estimated breeding values for different trait complexes. RESULTS Based on classical selection index theory in combination with quantitative genetic models, we provide a methodological framework for calculating expected genetic and phenotypic progress for all components of a complex breeding objective. We further provide an approach to study the sensitivity of the system to modifications, e.g. to changes in the economic weights. We propose a novel approach to derive the covariance structure of the stochastic errors of estimated breeding values from the observed correlations of estimated breeding values. We define 'realized economic weights' as those weights that would coincide with the observed composition of the genetic trend and show, how they can be calculated. The suggested methodology is illustrated with an index that aims at achieving a breeding goal composed of six trait complexes, that was applied in German Holstein cattle breeding until 2021. CONCLUSIONS Based on the presented results, the main conclusions are (i) the composition of the observed genetic progress matches the expectations well, with predictions being slightly better when the covariance of estimation errors is taken into account; (ii) the composition of the expected phenotypic trend deviates significantly from the expected genetic trend due to the differences in trait heritabilities; and (iii) the realized economic weights derived from the observed genetic trend deviate substantially from the predefined ones, in one case even with a reversed sign. Further results highlight the implications of the change to a modified breeding goal based on the example of a new index comprising eight, partly new, trait complexes, which is used since 2021 in the German Holstein breeding program. The proposed framework and the analytical tools and software provided will be useful to define more rational and generally accepted breeding objectives in the future.
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Affiliation(s)
- Henner Simianer
- Animal Breeding Group, Department of Animal Sciences, Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany.
| | - Johannes Heise
- IT Solutions for Animal Production (vit), Heinrich-Schröder-Weg 1, 27283, Verden/Aller, Germany
| | - Stefan Rensing
- IT Solutions for Animal Production (vit), Heinrich-Schröder-Weg 1, 27283, Verden/Aller, Germany
| | - Torsten Pook
- Animal Breeding Group, Department of Animal Sciences, Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
- Animal Breeding and Genomics Group, Wageningen University & Research, PO Box 338, 6700 AH, Wageningen, The Netherlands
| | - Johannes Geibel
- Animal Breeding Group, Department of Animal Sciences, Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
- Friedrich-Loeffler-Institut, Division of Farm Animal Genetics, Höltystraße 10, 31535, Neustadt, Germany
| | - Christian Reimer
- Animal Breeding Group, Department of Animal Sciences, Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
- Friedrich-Loeffler-Institut, Division of Farm Animal Genetics, Höltystraße 10, 31535, Neustadt, Germany
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