Genetic parameters and genomic prediction of egg production traits in ducks

Egg production traits are critical in duck breeding. Although genomic selection (GS) has been widely applied in livestock breeding, limited research has focused on predicting duck egg production traits, particularly across different physiological stages. In this study, we systematically explored the...

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Main Authors: Chengming Han, Linxi Zhu, Mengdie Wang, Jian Hu, Qinglei Yang, Zhenlin Liu, Zhengkui Zhou, Cong Li, Shuisheng Hou, Wentao Cai
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Poultry Science
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Online Access:http://www.sciencedirect.com/science/article/pii/S0032579125007539
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author Chengming Han
Linxi Zhu
Mengdie Wang
Jian Hu
Qinglei Yang
Zhenlin Liu
Zhengkui Zhou
Cong Li
Shuisheng Hou
Wentao Cai
author_facet Chengming Han
Linxi Zhu
Mengdie Wang
Jian Hu
Qinglei Yang
Zhenlin Liu
Zhengkui Zhou
Cong Li
Shuisheng Hou
Wentao Cai
author_sort Chengming Han
collection DOAJ
description Egg production traits are critical in duck breeding. Although genomic selection (GS) has been widely applied in livestock breeding, limited research has focused on predicting duck egg production traits, particularly across different physiological stages. In this study, we systematically explored the genetic parameters of egg production traits and evaluated the performance of GS in a commercial Pekin duck population. Analysis of 8,455 laying ducks showed that the heritability of cumulative egg production at 210, 280, and 300 days was 0.35, 0.37, and 0.48, respectively. Heritability during the early, peak, and post stages of cumulative egg production was 0.32, 0.15, and 0.24. The heritability of the egg laying rate from 25 to 60 weeks was 0.25. The cumulative egg production traits exhibited very strong mutual genetic correlations (≥ 0.95), while genetic correlations among egg laying stage traits ranged from 0.03 to 0.74. In the comparison between the pedigree-based best linear unbiased prediction (BLUP) and the genomic BLUP (GBLUP), using five-fold cross-validation, GBLUP outperformed the traditional pedigree BLUP model, with an average predictive reliability of 0.154, which was 0.029 higher than the predictive reliability of BLUP. In forward prediction, GBLUP also outperformed BLUP for all traits, with an average reliability of 0.097, which was 0.111 higher than the predictive reliability of BLUP. We also assessed the impact of linkage disequilibrium (LD) filtering on predictive reliability, which improved predictive reliability by 0.022 when the LD threshold was set to 0.14. In the comparison between GBLUP and Bayesian models utilizing a genotype with an LD pruning threshold of 0.14, GBLUP showed higher reliability than BayesB and BayesN in five-fold cross-validation, but lower than BayesCπ. In forward prediction, GBLUP demonstrated more robust performance, outperforming BayesB, BayesCπ, and BayesN, with improvements of 0.03, 0.019, and 0.05, respectively. This study provides a foundation for the application of GS in duck egg production and offers practical insights for improving predictive reliability in egg production.
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publisher Elsevier
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series Poultry Science
spelling doaj-art-ea84f3adaa21405b9f9beec28313f8f62025-08-20T03:51:30ZengElsevierPoultry Science0032-57912025-10-011041010551010.1016/j.psj.2025.105510Genetic parameters and genomic prediction of egg production traits in ducksChengming Han0Linxi Zhu1Mengdie Wang2Jian Hu3Qinglei Yang4Zhenlin Liu5Zhengkui Zhou6Cong Li7Shuisheng Hou8Wentao Cai9Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; College of Animal Science and Technology, Northwest A&F University, 712100, ChinaInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; College of Animal Science and Technology, Northwest A&F University, 712100, ChinaInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; College of Animal Science and Technology, Shanxi Agricultural University, 030031, ChinaInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, ChinaShandong Zhongxin Food Group Co., Ltd., 250100, ChinaShandong Zhongxin Food Group Co., Ltd., 250100, ChinaInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, ChinaCollege of Animal Science and Technology, Northwest A&F University, 712100, ChinaInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, ChinaInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; Corresponding author.Egg production traits are critical in duck breeding. Although genomic selection (GS) has been widely applied in livestock breeding, limited research has focused on predicting duck egg production traits, particularly across different physiological stages. In this study, we systematically explored the genetic parameters of egg production traits and evaluated the performance of GS in a commercial Pekin duck population. Analysis of 8,455 laying ducks showed that the heritability of cumulative egg production at 210, 280, and 300 days was 0.35, 0.37, and 0.48, respectively. Heritability during the early, peak, and post stages of cumulative egg production was 0.32, 0.15, and 0.24. The heritability of the egg laying rate from 25 to 60 weeks was 0.25. The cumulative egg production traits exhibited very strong mutual genetic correlations (≥ 0.95), while genetic correlations among egg laying stage traits ranged from 0.03 to 0.74. In the comparison between the pedigree-based best linear unbiased prediction (BLUP) and the genomic BLUP (GBLUP), using five-fold cross-validation, GBLUP outperformed the traditional pedigree BLUP model, with an average predictive reliability of 0.154, which was 0.029 higher than the predictive reliability of BLUP. In forward prediction, GBLUP also outperformed BLUP for all traits, with an average reliability of 0.097, which was 0.111 higher than the predictive reliability of BLUP. We also assessed the impact of linkage disequilibrium (LD) filtering on predictive reliability, which improved predictive reliability by 0.022 when the LD threshold was set to 0.14. In the comparison between GBLUP and Bayesian models utilizing a genotype with an LD pruning threshold of 0.14, GBLUP showed higher reliability than BayesB and BayesN in five-fold cross-validation, but lower than BayesCπ. In forward prediction, GBLUP demonstrated more robust performance, outperforming BayesB, BayesCπ, and BayesN, with improvements of 0.03, 0.019, and 0.05, respectively. This study provides a foundation for the application of GS in duck egg production and offers practical insights for improving predictive reliability in egg production.http://www.sciencedirect.com/science/article/pii/S0032579125007539Genomic predictionHeritabilityGenetic correlationForward predictionEgg production
spellingShingle Chengming Han
Linxi Zhu
Mengdie Wang
Jian Hu
Qinglei Yang
Zhenlin Liu
Zhengkui Zhou
Cong Li
Shuisheng Hou
Wentao Cai
Genetic parameters and genomic prediction of egg production traits in ducks
Poultry Science
Genomic prediction
Heritability
Genetic correlation
Forward prediction
Egg production
title Genetic parameters and genomic prediction of egg production traits in ducks
title_full Genetic parameters and genomic prediction of egg production traits in ducks
title_fullStr Genetic parameters and genomic prediction of egg production traits in ducks
title_full_unstemmed Genetic parameters and genomic prediction of egg production traits in ducks
title_short Genetic parameters and genomic prediction of egg production traits in ducks
title_sort genetic parameters and genomic prediction of egg production traits in ducks
topic Genomic prediction
Heritability
Genetic correlation
Forward prediction
Egg production
url http://www.sciencedirect.com/science/article/pii/S0032579125007539
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