Literature DB >> 35860946

Genomic dissection of repeatability considering additive and nonadditive genetic effects for semen production traits in beef and dairy bulls.

Rintaro Nagai1, Masashi Kinukawa2, Toshio Watanabe2, Atsushi Ogino2, Kazuhito Kurogi3, Kazunori Adachi3, Masahiro Satoh1, Yoshinobu Uemoto1.   

Abstract

The low heritability and moderate repeatability of semen production traits in beef and dairy bulls suggest that nonadditive genetic effects, such as dominance and epistatic effects, play an important role in semen production and should therefore be considered in genetic improvement programs. In this study, the repeatability of semen production traits in Japanese Black bulls (JB) as beef bulls and Holstein bulls (HOL) as dairy bulls was evaluated by considering additive and nonadditive genetic effects using the Illumina BovineSNP50 BeadChip. We also evaluated the advantage of using more complete models that include nonadditive genetic effects by comparing the rank of genotyped animals and the phenotype prediction ability of each model. In total, 65,463 records for 615 genotyped JB and 48,653 records for 845 genotyped HOL were used to estimate additive and nonadditive (dominance and epistatic) variance components for semen volume (VOL), sperm concentration (CON), sperm motility (MOT), MOT after freeze-thawing (aMOT), and sperm number (NUM). In the model including both additive and nonadditive genetic effects, the broad-sense heritability (0.17 to 0.43) was more than twice as high as the narrow-sense heritability (0.04 to 0.11) for all traits and breeds, and the differences between the broad-sense heritability and repeatability were very small for VOL, NUM, and CON in both breeds. A large proportion of permanent environmental variance was explained by epistatic variance. The epistatic variance as a proportion of total phenotypic variance was 0.07 to 0.33 for all traits and breeds. In addition, heterozygosity showed significant positive relationships with NUM, MOT, and aMOT in JB and NUM in HOL, when the heterozygosity rate was included as a covariate. In a comparison of models, the inclusion of nonadditive genetic effects resulted in a re-ranking of the top genotyped bulls for the additive effects. Adjusting for nonadditive genetic effects could be expected to produce a more accurate breeding value, even if the models have similar fitting. However, including nonadditive genetic effects did not improve the ability of any model to predict phenotypic values for any trait or breed compared with the predictive ability of a model that includes only additive effects. Consequently, although nonadditive genetic effects, especially epistatic effects, play an important role in semen production traits, they do not improve prediction accuracy in beef and dairy bulls.
© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  broad-sense heritability; dominance effects; epistatic effects; genetic parameter estimates; heterozygosity rate

Mesh:

Year:  2022        PMID: 35860946      PMCID: PMC9467033          DOI: 10.1093/jas/skac241

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.338


  30 in total

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4.  Symposium review: The genomic architecture of inbreeding: How homozygosity affects health and performance.

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5.  Genetic parameters of semen quality traits and genetic correlations with service sire nonreturn rate in Nordic Holstein bulls.

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7.  Genome-wide detection of non-additive quantitative trait loci for semen production traits in beef and dairy bulls.

Authors:  R Nagai; M Kinukawa; T Watanabe; A Ogino; K Kurogi; K Adachi; M Satoh; Y Uemoto
Journal:  Animal       Date:  2022-02-23       Impact factor: 3.730

8.  Genetic parameter estimation for beef bull semen attributes.

Authors:  Madison L Butler; Ashley R Hartman; Jennifer M Bormann; Robert L Weaber; David M Grieger; Megan M Rolf
Journal:  J Anim Sci       Date:  2021-02-01       Impact factor: 3.159

9.  SNPchiMp v.3: integrating and standardizing single nucleotide polymorphism data for livestock species.

Authors:  Ezequiel L Nicolazzi; Andrea Caprera; Nelson Nazzicari; Paolo Cozzi; Francesco Strozzi; Cindy Lawley; Ali Pirani; Chandrasen Soans; Fiona Brew; Hossein Jorjani; Gary Evans; Barry Simpson; Gwenola Tosser-Klopp; Rudiger Brauning; John L Williams; Alessandra Stella
Journal:  BMC Genomics       Date:  2015-04-10       Impact factor: 3.969

10.  Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle.

Authors:  Yoshinobu Uemoto; Shinji Sasaki; Takatoshi Kojima; Yoshikazu Sugimoto; Toshio Watanabe
Journal:  BMC Genet       Date:  2015-11-19       Impact factor: 2.797

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