Evidence map›Paper›PMID 38504219›Full record

ArticleGenetics, selection, evolution : GSE2024

The genetics of resilience and its relationships with egg production traits and antibody traits in chickens.

Tom V L Berghof, Nicolas Bedere, Katrijn Peeters, Marieke Poppe, Jeroen Visscher, Han A Mulder

Open access · goldAbstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

6 authors at 5 institutions in 3 countries.

Tom V L BerghofWageningen University & Research Animal Breeding and Genomics, PO Box 338, 6700 AH, Wageningen, The Netherlands. t.berghof@tum.de.ORCID http://orcid.org/0000-0003-4879-6784
Nicolas BederePEGASE, INRAE, Institut Agro, 35590, Saint Gilles, France.
Katrijn PeetersHendrix Genetics B.V., P.O. Box 114, 5830 AC, Boxmeer, The Netherlands.
Marieke PoppeWageningen University & Research Animal Breeding and Genomics, PO Box 338, 6700 AH, Wageningen, The Netherlands.
Jeroen VisscherHendrix Genetics B.V., P.O. Box 114, 5830 AC, Boxmeer, The Netherlands.
Han A MulderWageningen University & Research Animal Breeding and Genomics, PO Box 338, 6700 AH, Wageningen, The Netherlands. han.mulder@wur.nl.
Hendrix Genetics (France) · FRCRV (Netherlands) · NLInstitut Agro Rennes-Angers · FRTechnical University of Munich · DEWageningen University & Research · NL

Funding

Alexander von Humboldt Foundation NLD 1211322 HFST-PNetherlands Organisation for Scientific Research 12208Netherlands Organization for Scientific Research Earth and Life Sciences ALWSA.2016.4SusAn, an ERA-Net co-funded under the European Union's Horizon 2020 research and innovation program 696231
6 · The paper itself

Abstract

backgroundResilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to its initial state before exposure to a disturbance. Resilient livestock are desired because of their improved health and increased economic profit. Genetic improvement of resilience may also lead to trade-offs with production traits. Recently, resilience indicators based on longitudinal data have been suggested, but they need further evaluation to determine whether they are indeed predictive of improved resilience, such as disease resilience. This study investigated different resilience indicators based on deviations between expected and observed egg production (EP) by exploring their genetic parameters, their possible trade-offs with production traits, and their relationships with antibody traits in chickens.

methodsEgg production in a nucleus breeding herd environment based on 1-week-, 2-week-, or 3-week-intervals of two purebred chicken lines, a white egg-laying (33,825 chickens) and a brown egg-laying line (34,397 chickens), were used to determine deviations between observed EP and expected average batch EP, and between observed EP and expected individual EP. These deviations were used to calculate three types of resilience indicators for two life periods of each individual: natural logarithm-transformed variance (ln(variance)), skewness, and lag-one autocorrelation (autocorrelation) of deviations from 25 to 83 weeks of age and from 83 weeks of age to end of life. Then, we estimated their genetic correlations with EP traits and with two antibody traits.

resultsThe most promising resilience indicators were those based on 1-week-intervals, as they had the highest heritability estimates (0.02-0.12) and high genetic correlations (above 0.60) with the same resilience indicators based on longer intervals. The three types of resilience indicators differed genetically from each other, which indicates that they possibly capture different aspects of resilience. Genetic correlations of the resilience indicator traits based on 1-week-intervals with EP traits were favorable or zero, which means that trade-off effects were marginal. The resilience indicator traits based on 1-week-intervals also showed no genetic correlations with the antibody traits, which suggests that they are not informative for improved immunity or vice versa in the nucleus environment.

conclusionsThis paper gives direction towards the evaluation and implementation of resilience indicators, i.e. to further investigate resilience indicator traits based on 1-week-intervals, in breeding programs for selecting genetically more resilient layer chickens.

Indexed as

ChickensResilience, PsychologicalAnimalsAntibodiesOvipositionPhenotypeAntibodies

Identifiers

PMID38504219
PMCPMC10953135
OpenAlexW4392952117

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.