Evidence map›Paper›PMID 30390619›Full record

ArticleGenetics, selection, evolution : GSE2018

Benefits of testing in both bio-secure and production environments in genomic selection breeding programs for commercial broiler chicken.

Thinh T Chu, Setegn W Alemu, Elise Norberg, Anders C Sørensen, John Henshall, Rachel Hawken, Just Jensen

Open access · goldAbstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 16% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. The Effect of Preselection on the Level of Bias and Accuracy in a Broiler Breeder Population, a Simulation Study.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 4 countries.

Thinh T ChuDepartment of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark. chu.thinh@mbg.au.dk.ORCID http://orcid.org/0000-0002-7226-3454
Setegn W AlemuDepartment of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark.
Elise NorbergDepartment of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark.
Anders C SørensenDepartment of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark.
John HenshallCobb-Vantress Inc., Siloam Springs, AR, 72761-1030, USA.
Rachel HawkenCobb-Vantress Inc., Siloam Springs, AR, 72761-1030, USA.
Just JensenDepartment of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark.
Aarhus University · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA breeding program for commercial broiler chicken that is carried out under strict biosecure conditions can show reduced genetic gain due to genotype by environment interactions (G × E) between bio-secure (B) and commercial production (C) environments. Accuracy of phenotype-based best linear unbiased prediction of breeding values of selection candidates using sib-testing in C is low. Genomic prediction based on dense genetic markers may improve accuracy of selection. Stochastic simulation was used to explore the benefits of genomic selection in breeding schemes for broiler chicken that include birds in both B and C for assessment of phenotype.

resultsWhen genetic correlations ([Formula: see text]) between traits measured in B and C were equal to 0.5 and 0.7, breeding schemes with 15, 30 and 45% of birds assessed in C resulted in higher genetic gain for performance in C compared to those without birds in C. The optimal proportion of birds phenotyped in C for genetic gain was 30%. When the proportion of birds in C was optimal and genotyping effort was limited, allocating 30% of the genotyping effort to birds in C was also the optimal genotyping strategy for genetic gain. When [Formula: see text] was equal to 0.9, genetic gain for performance in C was not improved with birds in C compared to schemes without birds in C. Increasing the heritability of traits assessed in C increased genetic gain significantly. Rates of inbreeding decreased when the proportion of birds in C increased because of a lower selection intensity among birds retained in B and a reduction in the probability of co-selecting close relatives.

conclusionsIf G × E interactions ([Formula: see text] of 0.5 and 0.7) are strong, a genomic selection scheme in which 30% of the birds hatched are phenotyped in C has larger genetic gain for performance in C compared to phenotyping all birds in B. Rates of inbreeding decreased as the proportion of birds moved to C increased from 15 to 45%.

Indexed as

Gene-Environment InteractionSelection, GeneticAnimal HusbandryAnimalsBreedingChickensModels, GeneticQuantitative Trait, Heritable

Identifiers

PMID30390619
PMCPMC6215651
OpenAlexW2899504714

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.