Acta Veterinaria et Zootechnica Sinica ›› 2024, Vol. 55 ›› Issue (9): 3757-3768.doi: 10.11843/j.issn.0366-6964.2024.09.002

• Review • Previous Articles     Next Articles

Research Progress of Genomic Selection in Beef Cattle

Hongxia JIA1,2(), Zaixia LIU1,2, Le ZHOU1,2, Yanchun BAO1,2, Chenxi HUO1,2, Pengpeng ZUO1,2, Mingjuan GU1,2, Risu NA1,2, Wenguang ZHANG1,2,3,*()   

  1. 1. College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China
    2. Inner Mongolia Autonomous Region Agricultural Genome Big Data Engineering Research Center, Hohhot 010018, China
    3. College of Life Science, Inner Mongolia Agricultural University, Hohhot 010018, China
  • Received:2024-02-29 Online:2024-09-23 Published:2024-09-27
  • Contact: Wenguang ZHANG E-mail:jiahongxia0427@163.com;atcgnmbi@aliyun.com

Abstract:

The development of genomic selection has left a profound mark on beef cattle breeding. In China, the multitude of beef cattle breeds with small population sizes has led to a slow pace in genetic breeding efforts. Most studies indicate that purebred beef cattle populations with large reference groups gain little benefit from multi-breed evaluations, while breeds with smaller reference groups can benefit from such evaluations without adversely affecting the assessment of purebred performance. In the field of beef cattle genetic breeding research, the use of genomic information provides an opportunity to enhance the genetic improvement of beef cattle, thereby determining the value of multi-breed reference groups such as hybrid breeds for beef cattle genetic breeding. Multi-breed genomic assessment, as a beneficial tool for increasing the genetic gain of populations, can evaluate the genomes of beef cattle populations using multi-breed models. This review focuses on the perspective of genomic selection in beef cattle, highlighting the use of genomic selection across multi-breed beef cattle breeds, discussing the mechanisms by which genomic selection is applied in beef cattle, with the aim of providing new insights for research into genomic selection in multi-breed beef cattle and exploring the potential applications of genomic selection.

Key words: beef cattle, Multi-species genome selection, Citespace software, visual analysis

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