中国畜牧兽医 ›› 2025, Vol. 52 ›› Issue (12): 5600-5613.doi: 10.16431/j.cnki.1671-7236.2025.12.007

• 营养与饲料 • 上一篇    

转录组学和代谢组学技术在牛肉质性状研究中的应用

志莉1,2, 戴思凡1, 刘雪琴3, 陈泉贞3, 俞英3, 毛华明1   

  1. 1. 云南农业大学动物科学与技术学院, 昆明 650201;
    2. 西昌学院动物科学学院, 西昌 615000;
    3. 中国农业大学动物科学与技术学院, 北京 100193
  • 收稿日期:2025-03-17 发布日期:2025-11-28
  • 通讯作者: 毛华明 E-mail:mhuaming@sina.com
  • 作者简介:志莉,E-mail:573247676@qq.com。
  • 基金资助:
    云南省鹤庆县奶牛产业科技特派团(202204BI090005)

Application of Transcriptomics and Metabolomics Technologies in Beef Quality Traits Research

ZHI Li1,2, DAI Sifan1, LIU Xueqin3, CHEN Quanzhen3, YU Ying3, MAO Huaming1   

  1. 1. Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China;
    2. Faculty of Animal Science, Xichang University, Xichang 615000, China;
    3. College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
  • Received:2025-03-17 Published:2025-11-28

摘要: 随着生活水平的不断提高,消费者对牛肉品质的关注日益增强。转录组学(transcriptomics)和代谢组学(metabolomics)技术凭借其高通量、高灵敏度和系统性的优势,已成为研究牛肉质性状的强大工具。转录组学通过转录组测序(RNA-sequencing,RNA-Seq)技术并结合生物信息学方法揭示了基因的表达模式与肉质性状之间的关系。代谢组学的研究对象是生物体内分子质量<1 500 u的内源性小分子,通过核磁共振(NMR)、气相色谱-质谱(GC-MS)和液相色谱-质谱(LC-MS)等技术对代谢物进行检测,并运用多变量技术、机器学习(ML)和功能分析等方法分析代谢物丰度和肉质性状之间的关系。转录组学和代谢组学联合分析可通过整合差异表达基因和差异代谢物进而研究基因表达模式与代谢物丰度之间的关系,利用基因-代谢物网络、两者共同富集的KEGG通路等方法全面解释肉质形成的内在差异及复杂性状背后的分子机制。文章系统综述了转录组学和代谢组学的技术原理、工作流程,以及两者在牛肉质性状研究中的应用现状,并探讨了当前研究所面临的挑战与未来发展的方向,以期为筛选优质肉牛分子育种标记、制定精准营养干预策略提供科学参考。

关键词: 转录组学; 代谢组学; 联合分析; 肉品质

Abstract: With the continuous improvement of living standards,consumers’ concern regarding beef quality has been increasing.Transcriptomics and metabolomics,with their advantages of high-throughput,high sensitivity,and systematicity,have become powerful tools for studying beef quality traits.Transcriptomics,through RNA-sequencing (RNA-Seq) technology combined with bioinformatics methods,has revealed the relationship between gene expression patterns and meat quality traits.Metabolomics focuses on endogenous small molecules with molecular weights below 1 500 u within biological systems.It employs techniques such as nuclear magnetic resonance (NMR),gas chromatography-mass spectrometry (GC-MS),and liquid chromatography-mass spectrometry (LC-MS) to detect metabolites,and utilizes multivariate analysis,machine learning (ML),and functional analysis to investigate the correlation between metabolite abundance and meat quality traits.The integrated analysis of transcriptomics and metabolomics can study the relationship between gene expression patterns and metabolite abundance by integrating differentially expressed genes and differentially abundant metabolites.Methods such as gene-metabolite networks and shared KEGG pathway enrichment between the two can comprehensively elucidate the intrinsic differences in meat quality formation and the molecular mechanisms underlying complex traits.This review systematically summarizes the technical principles and workflows of transcriptomics and metabolomics,as well as their current applications in beef quality research.It also discusses the challenges faced by current research and the directions for future development,aiming to provide scientific references for screening molecular breeding markers for high-quality beef cattle and formulating precise nutritional intervention strategies.

Key words: transcriptomics; metabolomics; integrated analysis; meat quality

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