Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 552482
Title Validation of genomic predictions for body weight in broilers using crossbred information and considering breed-of-origin of alleles
Author(s) Duenk, Pascal; Calus, Mario P.L.; Wientjes, Yvonne C.J.; Breen, Vivian P.; Henshall, John M.; Hawken, Rachel; Bijma, Piter
Source Genetics, Selection, Evolution 51 (2019)1. - ISSN 0999-193X
DOI https://doi.org/10.1186/s12711-019-0481-7
Department(s) Animal Breeding and Genomics
WIAS
Publication type Refereed Article in a scientific journal
Publication year 2019
Abstract

Background: Pig and poultry breeding programs aim at improving crossbred (CB) performance. Selection response may be suboptimal if only purebred (PB) performance is used to compute genomic estimated breeding values (GEBV) because the genetic correlation between PB and CB performance (r-{pc} r pc) is often lower than 1. Thus, it may be beneficial to use information on both PB and CB performance. In addition, the accuracy of GEBV of PB animals for CB performance may improve when the breed-of-origin of alleles (BOA) is considered in the genomic relationship matrix (GRM). Thus, our aim was to compare scenarios where GEBV are computed and validated by using (1) either CB offspring averages or individual CB records for validation, (2) either a PB or CB reference population, and (3) a GRM that either accounts for or ignores BOA in the CB individuals. For this purpose, we used data on body weight measured at around 7 (BW7) or 35 (BW35) days in PB and CB broiler chickens and evaluated the accuracy of GEBV based on the correlation GEBV with phenotypes in the validation population (validation correlation). Results: With validation on CB offspring averages, the validation correlation of GEBV of PB animals for CB performance was lower with a CB reference population than with a PB reference population for BW35 (r-{pc} r pc = 0.96), and about equal for BW7 (r-{pc} r pc = 0.80) when BOA was ignored. However, with validation on individual CB records, the validation correlation was higher with a CB reference population for both traits. The use of a GRM that took BOA into account increased the validation correlation for BW7 but reduced it for BW35. Conclusions: We argue that the benefit of using a CB reference population for genomic prediction of PB animals for CB performance should be assessed either by validation on CB offspring averages, or by validation on individual CB records while using a GRM that accounts for BOA in the CB individuals. With this recommendation in mind, our results show that the accuracy of GEBV of PB animals for CB performance was equal to or higher with a CB reference population than with a PB reference population for a trait with an r-{pc} r pc of 0.8, but lower for a trait with an r-{pc} r pc of 0.96. In addition, taking BOA into account was beneficial for a trait with an r-{pc} r pc of 0.8 but not for a trait with an r-{pc} r pc of 0.96.

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