The Identification of Genes and Metabolic Networks: Unlocking Dairy Livestock Production

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal Genetics and Genomics".

Deadline for manuscript submissions: 15 November 2024 | Viewed by 2396

Special Issue Editors

College of Animal Sciences, Zhejiang University, Hangzhou, China
Interests: mammary gland development; fatty acid metabolism; gene function verification; signal pathway
College of Animal Science and Technology, Jilin Agricultural University, Changchun, China
Interests: dairy production; lactation physiology; nutriomics; precision nutritional ma-nipulation; signal pathway
College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
Interests: milk fat traits; gene regulation network construction; gene expression; epigenetic; circRNA; lincRNA miRNA; mRNA
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Special Issue Information

Dear Colleagues,

With the continuous growth of the global population, the worldwide demand for milk production increases constantly. An important goal in this field is the improvement of the production performance of dairy animals using the advantages of precise nutritional manipulation and genetic breeding. It is this challenge and consumer demand that have facilitated the identification of genes and networks that improve the production of dairy livestock. Recent evidence has shown that lipid metabolism, amino acid metabolism, and carbohydrate metabolism modify the development and lactation process of dairy livestock. A number of genes, proteins, and molecular compounds that can regulate the production performance of these animals have been reported on, though the identification of the genes and networks involved in the production performance improvement of dairy livestock are unclear.

This Special Issue aims to attract original research and review articles dealing with the genes and metabolic networks involved in the production performance improvement of dairy livestock. Those revealing new information on gene function, new gene identification, gene networks related to metabolism, and the development of the mammary gland in dairy livestock are also welcome.

Dr. Hengbo Shi
Dr. Tao Wang
Dr. Zhi Chen
Guest Editor

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Keywords

  • dairy livestock
  • omics
  • milk performance
  • milk synthesis
  • fatty acid metabolism
  • amino acid metabolism
  • glucose metabolism
  • gene function
  • gene identification
  • mammary gland
  • nutritional regulation
  • network
  • molecular compound

Published Papers (1 paper)

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Research

17 pages, 5121 KiB  
Article
Proteomics Insights into the Gene Network of cis9, trans11-Conjugated Linoleic Acid Biosynthesis in Bovine Mammary Gland Epithelial Cells
by Liying Peng, Ge Bai, Chunzheng Wang, Jianan Dong, Yongjun Liu, Zhe Sun, Yuguo Zhen, Guixin Qin, Xuefeng Zhang, Natnael Demelash and Tao Wang
Animals 2022, 12(13), 1718; https://doi.org/10.3390/ani12131718 - 2 Jul 2022
Cited by 2 | Viewed by 1916
Abstract
The objective of the study was to elucidate the stearoyl-coenzyme A desaturase (SCD1)-dependent gene network of c9, t11-CLA biosynthesis in MAC-T cells from an energy metabolism perspective. The cells were divided into the CAY group (firstly incubated with CAY10566, a chemical inhibitor of [...] Read more.
The objective of the study was to elucidate the stearoyl-coenzyme A desaturase (SCD1)-dependent gene network of c9, t11-CLA biosynthesis in MAC-T cells from an energy metabolism perspective. The cells were divided into the CAY group (firstly incubated with CAY10566, a chemical inhibitor of SCD1, then incubated with trans-11-octadecenoic acid, (TVA)), the TVA group (only TVA), and the control group (without CAY, TVA). The c9, t11-CLA, and TVA contents were determined by gas chromatography. The mRNA levels of SCD1 and candidate genes were analyzed via real-time PCR. Tandem mass tag (TMT)-based quantitative proteomics, bioinformatic analysis, parallel reaction monitoring (PRM), and small RNA interference were used to explore genes involved in the SCD1-dependent c9, t11-CLA biosynthesis. The results showed that the SCD1 deficiency led by CAY10566 blocked the biosynthesis of c9, t11-CLA. In total, 60 SCD1-related proteins mainly involved in energy metabolism pathways were primarily screened by TMT-based quantitative proteomics analysis. Moreover, 17 proteins were validated using PRM analysis. Then, 11 genes were verified to have negative relationships with SCD1 after the small RNA interference analysis. Based on the above results, we concluded that genes involved in energy metabolism pathways have an impact on the SCD1-dependent molecular mechanism of c9, t11-CLA biosynthesis. Full article
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