Evidence map›Paper›PMID 40691763›Full record

ArticleGenetics, selection, evolution : GSE2025

Towards assessing indirect genetic effects in dairy cattle.

Ida Hansson, Piter Bijma, Freddy Fikse, Lars Rönnegård

Abstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Ida HanssonDepartment of Animal Biosciences, Swedish University of Agricultural Sciences, Box 7023, 750 07, Uppsala, Sweden. ida.hansson@slu.se.ORCID http://orcid.org/0000-0001-7877-4135
Piter BijmaAnimal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands.
Freddy FikseVäxa, Swedish University of Agricultural Sciences, Ulls Väg 26, 756 51, Uppsala, Sweden.
Lars RönnegårdDepartment of Animal Biosciences, Swedish University of Agricultural Sciences, Box 7023, 750 07, Uppsala, Sweden.

Funding

Svenska Forskningsrådet Formas 2019-02111Svenska Forskningsrådet Formas 2019-02276
6 · The paper itself

Abstract

backgroundSocial interactions in a dairy herd may impact an individual's production, e.g., milk yield. These interactions can have a genetic component, so-called indirect genetic effects (IGE). IGEs contribute to heritable variation in other species, but studies on IGEs in cows are limited. Knowledge is needed on appropriate methods to monitor social interactions in cows. We evaluated with simulations whether we can estimate IGEs in cows. We used milk yield as an example trait, and we assessed how herd size, direct and indirect genetic correlations, and magnitude of IGE affected the variance component estimations and breeding value accuracies. We investigated the importance of knowing the contact intensity and direction by either including or ignoring them in the estimation model. Additionally, we investigated how random noise added to the intensities would affect the estimates and breeding values.

resultsThe estimated variance components were unbiased and precise for scenarios with different herd sizes of 50, 100, or 200 cows and direct and indirect genetic correlations of either - 0.6, 0, or 0.6. The IGE breeding value accuracies were 0.55-0.65 for cows when the IGE explained 30% of the phenotypic variance. When the magnitude of the IGE became smaller, the precision of the estimated variances became lower. The IGE breeding value accuracies were 0.16-0.52 for cows when the IGE explained 1.5-15% of the phenotypic variance. Using imprecise intensities or ignoring the contact direction underestimated the variance of the indirect effects, and the breeding value accuracies became lower. Ignoring the variation in intensities in the model led to unbiased variance component estimates but a larger residual variance and lower breeding value accuracies than if we used imprecise intensities.

conclusionsWe could estimate IGE in dairy cattle with high accuracy and precision in a simulated population of 10,000 phenotyped cows distributed over 50-200 herds. A smaller IGE variance led to less precise estimates and lower breeding value accuracies. Ignoring information about the intensity of contact in the model would be worse than using imprecise intensities, and using technology that also monitors the direction of contact may be beneficial to estimate variance components of IGE.

Indexed as

Models, GeneticAnimalsBreedingCattleComputer SimulationDairyingFemaleGenetic VariationLactationMilkPhenotypeQuantitative Trait, Heritable

Identifiers

PMID40691763
PMCPMC12278552

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.