Evidence map›Paper›PMID 42184289›Full record

ArticleJournal of animal science2026

Genetic heterogeneity of residual variance for growth traits in American angus Cattle.

Sabrina T Amorim, Kelli J Retallick, André Garcia, Noelia Ibañez-Escriche, Gota Morota

Abstract read
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Article in Journal of animal 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.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Sabrina T AmorimSchool of Animal Sciences, Virginia Tech, Blacksburg, VA 24061, United States.ORCID 0000-0003-4130-2040
Kelli J RetallickAngus Genetics Inc., American Angus Association, Saint Joseph, MO 64506, United States.
André GarciaAngus Genetics Inc., American Angus Association, Saint Joseph, MO 64506, United States.
Noelia Ibañez-EscricheInstitute for Animal Science and Technology, Universitat Politècnica de València, València 46022, Spain.ORCID 0000-0002-6221-3576
Gota MorotaSchool of Animal Sciences, Virginia Tech, Blacksburg, VA 24061, United States.ORCID 0000-0002-3567-6911

Funding

Virginia Tech and the University of Tokyo
6 · The paper itself

Abstract

Economic incentives have increased the demand for uniformity in beef production, making it a valuable phenotype for genetic studies. Genetic heterogeneity of residual variance suggests that variability around the mean may have a genetic component and could potentially respond to selection. However, evidence for genetic control of residual variance in beef cattle remains limited. The objectives of this study were to 1) investigate genetic heterogeneity of residual variances for birth weight (BW), weaning weight (WW), and yearling weight (YW) in American Angus cattle, and 2) compare models for genetic homogeneity (M1) versus genetic heterogeneity of residual variance, including a double hierarchical generalized linear model (DHGLM, M2) and a genetically structured environmental variance model (M3). A total of 75,000 BW, 74,975 WW, and 49,803 YW records were analyzed. Genetic parameters were estimated using average information restricted maximum likelihood for models M1 and M2, whereas model M3 employed Markov chain Monte Carlo within a Bayesian framework. We found evidence of genetic variation in residual variance for all traits, although the heritability estimates for residual variance were low, ranging from 0.004 to 0.01. Estimates of the genetic coefficient of variation for residual variance ranged from 0.38 to 0.62 for BW, 0.09 to 0.25 for WW, and 0.07 to 0.25 for YW, indicating potential for selection to reduce variability. Genetic correlations between mean and residual variance were negative for BW (-0.48 in M2 and -0.49 in M3) and positive for WW and YW. These findings indicate that the implications of selection for uniformity are trait-specific. Body weight should be maintained within an optimal range, whereas selection for increased WW and YW may lead to greater variability unless residual variance is incorporated into selection decisions. Overall, our results indicate the feasibility of reducing variability through selection, representing a first step in integrating growth trait uniformity into breeding goals for beef cattle.

Indexed as

Body WeightGenetic VariationAnimalsBayes TheoremBirth WeightCattleFemaleMaleModels, Geneticbeef cattlegenetic parameterresilienceselectionuniformity

Identifiers

PMID42184289
PMCPMC13283484

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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.