Acta Veterinaria et Zootechnica Sinica ›› 2026, Vol. 57 ›› Issue (1): 1-12.doi: 10.11843/j.issn.0366-6964.2026.01.001

• REVIEW • Previous Articles     Next Articles

Research Status and Prospects of Livestock Single-cell Transcriptomics Databases

WANG Jian1(), LI Ruixing2, LIU Qiaoming3(), LI Yuanfang4,5()   

  1. 1.School of Computer and Information Engineering,Henan University of Economics and Law,Zhengzhou 450000,China
    2.Software College,Henan University,Kaifeng 475000,China
    3.College of Artificial Intelligence,Henan University,Zhengzhou 450000,China
    4.School of Medicine and Health,Harbin Institute of Technology,Harbin 150001,China
    5.Zhengzhou Research Institute,Harbin Institute of Technology,Zhengzhou 450000,China
  • Received:2025-05-19 Online:2026-01-23 Published:2026-01-26
  • Contact: LIU Qiaoming, LI Yuanfang E-mail:goodjian121@126.com;cslqm@henu.edu.cn;yuanfangli1991@163.com

Abstract:

This article aims to elucidate how single-cell omics technologies advance livestock research and provides a systematic review of the construction process, current applications, and major challenges of single-cell transcriptomic databases in domestic animals. It seeks to offer data references and analytical frameworks for researchers, thereby promoting deeper application of this technology in livestock studies. This review conducted a comprehensive review and integrated analysis of existing single-cell transcriptomic database resources for livestock, summarizing their construction methodologies and application pathways, while also discussing current technical bottlenecks. The review demonstrates that single-cell transcriptomics offers novel perspectives and abundant data resources for elucidating mechanisms of livestock diseases, molecular breeding, and health management, while also revealing significant challenges in areas such as data integration and annotation standardization. Future efforts should focus on constructing high-quality databases, developing analysis algorithms tailored to livestock species, and promoting multi-omics integration to fully leverage the potential of single-cell technologies in the development of animal husbandry.

Key words: livestock, single-cell transcriptomics, database

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