Research Report

Transcriptomic and Metabolomic Analysis of Feed Efficiency in Chickens  

Xinghao Li , Jia Xuan
Institute of Life Sciences, Jiyang Colloge of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China
Author    Correspondence author
International Journal of Molecular Zoology, 2025, Vol. 15, No. 1   doi: 10.5376/ijmz.2025.15.0002
Received: 10 Dec., 2024    Accepted: 14 Jan., 2025    Published: 24 Jan., 2025
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This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

Li X.H., and Xuan J., 2025, Transcriptomic and metabolomic analysis of feed efficiency in chickens, International Journal of Molecular Zoology, 15(1): 10-19 (doi: 10.5376/ijmz.2025.15.0002)

Abstract

Feed efficiency is an important trait in poultry breeding and farming. It is related to the utilization of resources and can also help farmers reduce costs. This study summarizes the application of transcriptomics and metabolomics in the research of chicken feed efficiency in recent years, and introduces the methods of multi-omics integration. These methods can help identify candidate genes and screen molecular markers, which are of great reference value for improving the feed conversion rate of poultry in the future, conducting molecular breeding and nutritional regulation. The research results show that feed efficiency is influenced by many factors. In high-efficiency and low-efficiency chickens, the gene expression and metabolic products in the liver and intestines are different. Changes in fat and sugar metabolism, as well as the immune system, may be important ways to affect feed efficiency. This study aims to provide a reference framework for molecular improvement and nutritional intervention to enhance the conversion efficiency of poultry feed in the future.

Keywords
Feed efficiency; Transcriptomics; Metabolomics; Non-coding RNA; Multi-omics integration
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