Evidence map›Paper›PMID 42033919›Full record

ArticlePoultry science2026

Stochastic simulations to optimize genomic selection for laying hens: Impact of generation interval and genotyping in the context of extended laying period.

Mathilde Doublet, Frédéric Lecerf, Torsten Pook, Hervé Chapuis, Jérôme Raoul, Florian Herry, Sophie Brad-Fudulea, Gwendal Restoux, Florence Phocas, Sophie Allais

Abstract read
In one paragraph

Article in Poultry science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Mathilde DoubletPEGASE, INRAE, Institut Agro, Saint Gilles 35590, France. Electronic address: mathilde.doublet@inrae.fr.
Frédéric LecerfPEGASE, INRAE, Institut Agro, Saint Gilles 35590, France.
Torsten PookWageningen University & Research, Animal Breeding and Genomics Group, Wageningen 6708 PB, the Netherlands.
Hervé ChapuisGenPhySE, Université de Toulouse, INRAE, Castanet-Tolosan, France.
Jérôme RaoulGenPhySE, Université de Toulouse, INRAE, Castanet-Tolosan, France; Institut de l'Elevage, Castanet-Tolosan, France.
Florian HerryGrimaud Frères Sélection, Sèvremoine 49450, France.
Sophie Brad-FuduleaSYSAAF, Station LPGP/INRAE, Campus de Beaulieu, Rennes 35042, France.
Gwendal RestouxUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France.
Florence PhocasUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France.
Sophie AllaisPEGASE, INRAE, Institut Agro, Saint Gilles 35590, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extending the productive lifespan of laying hens is a key objective for sustainable egg production. Achieving this goal requires improving egg production and quality traits expressed late in life. Genomic selection offers opportunities to increase accuracy of selection for such traits, while shorter generation intervals can accelerate genetic progress. However, both strategies may affect inbreeding, and their combined impact in the context of extended laying cycles has not yet been quantified. Stochastic simulations were performed to evaluate seven breeding programs for layers, based on real genotype data and six quantitative traits (egg weight, egg shell strength, and laying rate, each at 60 and 90 weeks). Programs differed by generation interval (L, 60, 45, or 30 weeks) and two selection method were applied to each scenario: single-step GBLUP using male genotypes (ssGBLUPm), or single-step GBLUP using both male and female genotypes (ssGBLUPmf). A control PBLUP based scenario with a 60 weeks L was also performed. Each scenario was replicated 30 times, and results were compared for annual genetic gain (∆G), prediction accuracy (r), and inbreeding rate (∆F). Genomic evaluations using a generation interval of 60 weeks improved both ∆G and ∆F, especially when both sexes were genotyped. Reducing the generation interval to 30 weeks maximized ∆G (up to 1.17 SD/year) but increased ∆F above 1%/year. Overlapping generation schemes (45-week interval) provided an intermediate outcome, improving ∆G compared with conventional 60-week generation interval schemes while limiting ∆F compared with 30-week generation interval schemes. Including female genotypes was particularly beneficial for late-recorded traits at 90 weeks, where accuracy increased by up to 38%. Shortening generation interval and implementing genomic selection substantially increased annual genetic gain, especially for persistency traits expressed late in life. However, these strategies also raised inbreeding, with overlapping generations offering a valuable compromise. Full genotyping of both sexes enhanced accuracy and reduced the increase in ΔF per ΔG unit, highlighting the relevance of genomic selection in breeding programs aiming to extend laying periods sustainably.

Indexed as

Animal HusbandryBreedingChickensReproductionSelection, GeneticAnimalsComputer SimulationFemaleGenotypeInbreedingMaleStochastic ProcessesGeneration intervalGenomic selectionInbreedingLaying hensStochastic simulations

Identifiers

PMID42033919
PMCPMC13126499

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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.