收藏切换
Enhancing genomic prediction for key production traits in chickens through ultrasound phenotyping and multi-model comparative analysis
收藏切换
PDF
Ranran Zhu1, 2, Yuxiang Jiang1, 2, Wanyi Xiong1, 2, Yu Zhang1, 2, Ziyi Lian1, 2, Danni Gou1, 2, Zhandeng Li3, Xiuping Wang3, Xuemei Deng1, 2, *
Journal of Animal Science and Biotechnology | 2026, 17(4) : 1958 - 1974
Less
收藏切换
Journal of Animal Science and Biotechnology | 2026, 17(4): 1958-1974
ANIMAL GENETICS AND BREEDING
Enhancing genomic prediction for key production traits in chickens through ultrasound phenotyping and multi-model comparative analysis
Full
Ranran Zhu1, 2, Yuxiang Jiang1, 2, Wanyi Xiong1, 2, Yu Zhang1, 2, Ziyi Lian1, 2, Danni Gou1, 2, Zhandeng Li3, Xiuping Wang3, Xuemei Deng1, 2, *
Affiliations
  • 1Sanya Institute, China Agricultural University, Sanya 572025, China
  • 2State Key Laboratory of Animal Biotech Breeding, Beijing Key Laboratory for Animal Genetic Improvement and Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
  • 3Hainan (Tanniu) Wenchang Chicken Co., Ltd., Haikou 570100, China
Published: 2026-08-15 doi: 10.1186/s40104-026-01384-0
Outline
收藏切换
Background

Growth performance and carcass traits are economically vital in poultry breeding. In Wenchang chickens, reducing excessive abdominal fat represents a critical breeding objective. However, as a typical carcass trait, abdominal fat thickness has traditionally been measurable only post-slaughter, resulting in inefficient and costly selection processes that hinder genetic progress for these traits. To overcome this limitation, we developed an integrated approach combining non-invasive ultrasound phenotyping and multi-model genomic selection to evaluate growth and fat-related traits in Wenchang chickens.

Results

We genotyped 3,737 chickens using the "Jingxin No.1" 55K SNP array and performed longitudinal measurement of abdominal fat thickness (AFT) via ultrasound imaging. A comprehensive evaluation of genomic prediction models revealed that WGBLUP (informed by wssGWAS), and GBLUP models based on LD-pruned whole-genome sequencing (WGS) data significantly outperformed standard GBLUP, with accuracy gains of 5.25% and 6.58%-15.30%, respectively. Among the machine learning algorithms tested, kernel ridge regression (KRR) and support vector regression (SVR) achieved the highest predictive improvement (3.00%-4.15%) while maintaining superior computational efficiency, whereas ensemble methods provide no consistent advantage.

Conclusions

Our work established ultrasound imaging as a scalable, non-invasive phenotyping platform for poultry breeding. Results demonstrated that integrating wssGWAS-derived biological priors with WGS data substantially improves genomic prediction accuracy for complex traits. This integration, enhanced by computationally efficient machine learning algorithms, provides a powerful and practical strategy to accelerate genetic gain.

Genomic prediction  /  Machine learning  /  Ultrasound phenotyping  /  Wenchang chicken  /  Whole-genome sequencing
Ranran Zhu, Yuxiang Jiang, Wanyi Xiong, Yu Zhang, Ziyi Lian, Danni Gou, Zhandeng Li, Xiuping Wang, Xuemei Deng. Enhancing genomic prediction for key production traits in chickens through ultrasound phenotyping and multi-model comparative analysis[J]. Journal of Animal Science and Biotechnology, 2026 , 17 (4) : 1958 -1974 . DOI: 10.1186/s40104-026-01384-0
  • National Key Research and Development Program of China(2023YFF1001100)
  • Hainan Seed Industry Laboratory(B23CJ0521; B21HJ0506)
  • Independent Research Project of State Key Laboratory of Animal Biotech Breeding(2023SKLAB1-7)
  • PhD Scientific Research and Innovation Foundation of The Education Department of Hainan Province Joint Project of Sanya Ya zhou Bay Science and Technology City(HSPHDSRF-2024-05-002)
  • 2115 Talent Development program of China Agricultural
Year 2026 volume 17 Issue 4
PDF
46
10
Cite this Article
BibTeX
Article Info
doi: 10.1186/s40104-026-01384-0
  • Receive Date:2025-11-05
  • Online Date:2026-08-13
  • Published:2026-08-15
Article Data
Affiliations
History
  • Received:2025-11-05
  • Accepted:2026-02-26
Funding
National Key Research and Development Program of China(2023YFF1001100)
Hainan Seed Industry Laboratory(B23CJ0521; B21HJ0506)
Independent Research Project of State Key Laboratory of Animal Biotech Breeding(2023SKLAB1-7)
PhD Scientific Research and Innovation Foundation of The Education Department of Hainan Province Joint Project of Sanya Ya zhou Bay Science and Technology City(HSPHDSRF-2024-05-002)
2115 Talent Development program of China Agricultural
Affiliations
    1Sanya Institute, China Agricultural University, Sanya 572025, China
    2State Key Laboratory of Animal Biotech Breeding, Beijing Key Laboratory for Animal Genetic Improvement and Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
    3Hainan (Tanniu) Wenchang Chicken Co., Ltd., Haikou 570100, China

Corresponding:

* Xuemei Deng
References
Share
https://castjournals.cast.org.cn/joweb/jasb/EN/10.1186/s40104-026-01384-0
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT