Evaluation of Linear Programming and Optimal Contribution Selection Approaches for Long-Term Selection on Beef Cattle Breeding
文献类型: 外文期刊
作者: Xu Zheng;Tianzhen Wang;Qunhao Niu;Jiayuan Wu;Zhida Zhao;Huijiang Gao;Junya Li;Lingyang Xu
作者机构:
关键词: average kinship coefficient;cattle breeding;genetic gain;linear programming;optimal contribution selection;simulation
期刊名称: Biology
ISSN: 2079-7737
年卷期: 2023 年 12 卷 9 期
页码:
收录情况: SCIE(2023版)
摘要: The optimized selection method can maximize the genetic gain in offspring under the premise of controlling the inbreeding level of the population. At present, genetic gain has been largely improved by using genomic selection in multiple farm animals. However, the design of the optimal selection method and assessment of its effects during long-term selection in beef cattle breeding are yet to be fully explored. In this study, a simulated beef cattle population was constructed, and 15 generations of simulated breeding were carried out using the linear programming breeding strategy (LP) and optimal contribution selection strategy (OCS), respectively. The truncation selection strategy (TS−I and TS−II) was used as the control. During the breeding process, genetic parameters including genetic gain, average kinship coefficient, QTL effect variance, and average observed heterozygosity were calculated and compared across generations. Our results showed that the LP method can significantly improve the genetic gain in the population, especially the genetic performance of the traits with high heritability and the traits with high weight in the breeding process, but the inbreeding level of the population is higher under LP strategy. Although the genetic gain in the population under the OCS strategy is lower than the TS−II strategy, this method can effectively control the inbreeding level of the population. Our findings also suggest that the LP and OCS method can be used as an effective means to improve genetic gain, while the OCS method is a more ideal method to obtain sustainable genetic gain during long-term selection.
分类号:
- 相关文献
作者其他论文 更多>>
-
An interpretable integrated machine learning framework for genomic selection
作者:Jinbu Wang;Jia Zhang;Wenjie Hao;Wencheng Zong;Mang Liang;Fuping Zhao;Longchao Zhang;Lixian Wang;Huijiang Gao;Ligang Wang
关键词:Dimensionality reduction;Genomic selection;Interpretability;Machine learning;Pig
-
Multiple strategies association revealed functional candidate FASN gene for fatty acid composition in cattle
作者:Bo Zhu;Tianzhen Wang;Qunhao Niu;Zezhao Wang;El Hamidi Hay;Lei Xu;Yan Chen;Lupei Zhang;Xue Gao;Huijiang Gao;Yang Cao;Yumin Zhao;Lingyang Xu;Junya Li
关键词:
-
Genome-Wide Scans for Selection Signatures in Ningxia Angus Cattle Reveal Genetic Variants Associated with Economic and Adaptive Traits
作者:Haiqi Yin;Yuan Feng;Yu Wang;Qiufei Jiang;Juan Zhang;Jie Zhao;Yafei Chen;Yaxuan Wang;Ruiqi Peng;Yahui Wang;Tong Zhao;Caihong Zheng;Lingyang Xu;Xue Gao;Huijiang Gao;Junya Li;Zezhao Wang;Lupei Zhang
关键词:Angus cattle;economic trait;iHS;immune-related gene;selection signatures;whole-genome resequencing
-
Mammary gland multi-omics data reveals new genetic insights into milk production traits in dairy cattle
作者:Wentao Cai;John B. Cole;Michael E. Goddard;Junya Li;Shengli Zhang;Jiuzhou Song
关键词:
-
Deciphering the Population Characteristics of Leiqiong Cattle Using Whole-Genome Sequencing Data
作者:Yingwei Guo;Zhihui Zhao;Fei Ge;Haibin Yu;Chenxiao Lyu;Yuxin Liu;Junya Li;Yan Chen
关键词:genomic characteristics;Leiqiong cattle;population genetics;selective sweep
-
Integrated analyses of genomic and transcriptomic data reveal candidate variants associated with carcass traits in Huaxi cattle
作者:Yapeng Zhang;Wentao Cai;Qi Zhang;Qian Li;Yahui Wang;Ruiqi Peng;Haiqi Yin;Xin Hu;Zezhao Wang;Bo Zhu;Xue Gao;Yan Chen;Huijiang Gao;Lingyang Xu;Junya Li;Lupei Zhang
关键词:beef cattle;eQTL mapping;fine mapping;GWAS;S-predixcan
-
Multi-omics integration analysis reveals the regulatory impact of CNVs for slaughter traits in cattle
作者:Jiayuan Wu;Qunhao Niu;Tianyi Wu;Yingxiao Su;Feng Liu;Zhida Zhao;Huijiang Gao;Junya Li;Lingyang Xu
关键词:alternative splicing;beef cattle;Copy number variation;eQTL;slaughter traits