Evidence map›Paper›PMID 23902427›Full record

ArticleGenetics, selection, evolution : GSE2013

Efficiency of genomic selection in an established commercial layer breeding program.

Florian Sitzenstock, Florence Ytournel, Ahmad R Sharifi, David Cavero, Helge Täubert, Rudolf Preisinger, Henner Simianer

Abstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
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  5. Sustainable high-yield farming is essential for bending the curve of biodiversity loss.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. A survey of functional genomic variation in domesticated chickens.Genetics, selection, evolution : GSE · 2018
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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.

Florian SitzenstockDepartment of Animal Sciences, University of Göttingen, 37075 Göttingen, Germany. fsitzen@gwdg.de
Florence Ytournel
Ahmad R Sharifi
David Cavero
Helge Täubert
Rudolf Preisinger
Henner Simianer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn breeding programs for layers, selection of hens and cocks is based on recording phenotypic data from hens in different housing systems. Genomic information can provide additional information for selection and/or allow for a strong reduction in the generation interval. In this study, a typical conventional layer breeding program using a four-line cross was modeled and the expected genetic progress was derived deterministically with the software ZPLAN+. This non-genomic reference scenario was compared to two genomic breeding programs to determine the best strategy for implementing genomic information in layer breeding programs.

resultsIn scenario I, genomic information was used in addition to all other information available in the conventional breeding program, so the generation interval was the same as in the reference scenario, i.e. 14.5 months. Here, we assumed that either only young cocks or young cocks and hens were genotyped as selection candidates. In scenario II, we assumed that breeders of both sexes were used at the biologically earliest possible age, so that at the time of selection only performance data of the parent generation and genomic information of the selection candidates were available. In this case, the generation interval was reduced to eight months. In both scenarios, the number of genotyped male selection candidates was varied between 800 and 4800 males and two sizes of the calibration set (500 or 2000 animals) were considered. All genomic scenarios increased the expected genetic gain and the economic profit of the breeding program. In scenario II, the increase was much more pronounced and even in the most conservative implementation led to a 60% improvement in genetic gain and economic profit. This increase was in all cases associated with higher breeding costs.

conclusionsWhile genomic selection is shown to have the potential to improve genetic gain in layer breeding programs, its implementation remains a business decision of the breeding company; the possible extra profit for the breeding company depends on whether the customers of breeding stock are willing to pay more for improved genetic quality.

Indexed as

BreedingGenomeGenomicsPolymorphism, Single NucleotideAnimalsChickensCost-Benefit AnalysisFemaleHybridization, GeneticMaleModels, GeneticQuantitative Trait, HeritableSoftware

Identifiers

PMID23902427
PMCPMC3750290

What OpenQuestion holds

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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.