Evidence map›Paper›PMID 31286857›Full record

ArticleGenetics, selection, evolution : GSE2019

Validation of genomic predictions for body weight in broilers using crossbred information and considering breed-of-origin of alleles.

Pascal Duenk, Mario P L Calus, Yvonne C J Wientjes, Vivian P Breen, John M Henshall, Rachel Hawken, Piter Bijma

Erratum issuedAbstract readComparative StudyValidation Study
In one paragraph

Article in Genetics, selection, evolution : GSE, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Pascal DuenkAnimal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands. pascal.duenk@wur.nl.ORCID http://orcid.org/0000-0001-8403-968X
Mario P L CalusAnimal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands.
Yvonne C J WientjesAnimal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands.
Vivian P BreenCobb-vantress Inc., Siloam Springs, AR, 72761-1030, USA.
John M HenshallCobb-vantress Inc., Siloam Springs, AR, 72761-1030, USA.
Rachel HawkenCobb-vantress Inc., Siloam Springs, AR, 72761-1030, USA.
Piter BijmaAnimal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPig 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 ([Formula: see text]) 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).

resultsWith 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 ([Formula: see text] = 0.96), and about equal for BW7 ([Formula: see text] = 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.

conclusionsWe 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 [Formula: see text] of 0.8, but lower for a trait with an [Formula: see text] of 0.96. In addition, taking BOA into account was beneficial for a trait with an [Formula: see text] of 0.8 but not for a trait with an [Formula: see text] of 0.96.

Indexed as

BreedingAllelesAnimalsBody WeightChickensFemaleGenomicsGenotypeMalePhenotypeReference Values

Identifiers

PMID31286857
PMCPMC6613268

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.