Evidence map›Paper›PMID 40799624›Full record

ArticleTranslational animal science2025

Improved genomic prediction accuracy by genetic relatedness using a crossbred pig population.

Euiseo Hong, Yoonji Chung, Suyeon Maeng, In-Cheol Cho, Seung Hwan Lee

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Article in Translational animal science, 2025. 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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5 authors.

Euiseo HongDepartment of Bio-Big Data and Precision Agriculture, Chungnam National University, Daejeon, 34134, Republic of Korea.ORCID https://orcid.org/0000-0003-3078-2560
Yoonji ChungInstitute of Agricultural Science, Chungnam National University, Daejeon, 34134, Republic of Korea.
Suyeon MaengDivision of Animal & Dairy Science, Chungnam National University, Daejeon, 34134, Republic of Korea.ORCID https://orcid.org/0000-0001-9903-3803
In-Cheol ChoSubtropical Livestock Research Institute, National Institute of Animal Science, Rural Development Administration, Jeju, 63242, Republic of Korea.
Seung Hwan LeeDivision of Animal & Dairy Science, Chungnam National University, Daejeon, 34134, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic prediction is crucial in animal breeding because it facilitates the selection of superior individuals based on genotype data. The success of genomic prediction is determined by its accuracy, which depends on the size of the reference population and relatedness between the reference and test populations. However, not all populations have large, highly genetically related reference populations. In this study, we evaluated the genomic prediction accuracy of three crossbreds and seven purebred populations using crossbred animals as a reference population and determined whether crossbred could be used as a reference population for small purebred populations. Genomic prediction accuracy was assessed using the genomic best linear unbiased prediction (GBLUP) for backfat thickness and carcass weight traits. Data from 29 Bisaro, 91 Duroc, 50 Duroc × Korean Native Pig (DK), 36 Iberian, 34 Korean Native Pig (KNP), 85 Landrace, 50 Landrace × Korean Native Pig (LK), 50 Landrace × Yorkshire × Duroc (LYD), 37 Meishan, and 49 Yorkshire pigs were used as test populations, whereas data from 245 DK, 964 LK, and 967 LYD crossbreds were used as the reference population. The findings indicated that the prediction accuracy of purebreds was higher when they were genetically related to the crossbred population, with accuracies ranging from 0.36 to 0.53 for backfat thickness and from 0.26 to 0.46 for carcass weight. In contrast, unrelated breeds showed lower accuracies, ranging from 0.16 to 0.48 for backfat thickness and from 0.13 to 0.40 for carcass weight. These results suggest that using crossbred populations related to the purebred population being predicted can improve prediction accuracy, especially for breeds with limited data. The prediction accuracy increased as the size of the reference population increased, regardless of genetic relatedness. Notably, small reference populations yielded higher accuracy when they were genetically related to the target animals, underscoring the importance of genetic similarity in addition to population size. These results highlight that using crossbred animals for reference populations is advantageous for genomic predictions because large populations can be rapidly established.

Indexed as

crossbreed reference populationgenomic predictiongenomic relatednessreference size

Identifiers

PMID40799624
PMCPMC12342970

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