Comparative metabolomics analysis shows key metabolites as potential biomarkers for selection of beef fat colour
文献类型: 外文期刊
作者: Tian, Rugang 1 ; Kharrati-Koopaee, Hamed 2 ; Nanaie, Hojjat Asadollahpour 1 ; Wang, Xiao 1 ; Zhao, Meng 1 ; Li, Hui 1 ; Li, Yuan 1 ; Zhang, Hao 1 ; Esmailizadeh, Ali 3 ; Bottema, Cynthia D. K. 4 ;
作者机构: 1.Inner Mongolia Acad Agr & Anim Husb Sci, Hohhot, Inner Mongolia, Peoples R China
2.Shiraz Univ, Inst Biotechnol, Shiraz, Iran
3.Shahid Bahonar Univ Kerman, Fac Agr, Dept Anim Sci, Kerman, Iran
4.Univ Adelaide, Sch Anim & Vet Sci, Adelaide, SA, Australia
关键词: adipose; beef; bovine; cattle; fat color; meat; metabolites; phenotype
期刊名称:ANIMAL PRODUCTION SCIENCE ( 影响因子:1.4; 五年影响因子:1.5 )
ISSN: 1836-0939
年卷期: 2023 年 63 卷 11 期
页码:
收录情况: SCI
摘要: Context. Fat colour is one of the most important economic traits in the marketing of beef. There are many factors that affect fat colour, such as breed, age, diet and gender. Fat colour is observed in different ranges of colours, including white, yellow and brown. The main issue with improving fat colour is that consumer preferences of fat colour vary across the globe. Therefore, investigating the metabolic mechanisms of fat colour may provide new biomarkers for phenotyping, so as to develop effective selection strategies to achieve the locally desired fat colour. Aims. This study aimed to perform a comparative metabolic analysis between white and yellow fat from crossbred cattle so as to identify potential biomarkers for the selection of fat colour and to better understand the metabolism of white and yellow fat depots. Methods. Carcass samples of subcutaneous fat were collected from crossbred cattle (Simmental x Mongolian cattle) and scored for fat colour. Liquid chromatography-mass spectrophotometry analysis of extracted metabolites from the subcutaneous fat of six animals with white fat and six animals with yellow fat was performed. Key results. The comparison between metabolites of white and yellow fat colour samples indicated that there were five categories of 235 significant metabolites, which included hydrocarbons, lipids and lipid-like molecules, organic acids and their derivatives, organic oxygen compounds and organoheterocyclic compounds. The principal-component analysis illustrated that yellow and white fat samples can be classified in groups; however, the metabolites of white fat samples showed greater variation than those in the yellow fat. In the white fat, there were 163 metabolites that had a higher relative abundance than in yellow fat and 72 that had a lower relative abundance than in yellow fat. 3-Hydroxyoctanoic acid, anethofuran, 9,10-DiHODE, furanoeremophilane, pregeijerene, N-glycolylneuraminic acid, and glycocholic acid were identified as the metabolites that differed the most in abundance between the white and yellow fat samples. Conclusions. This study has provided insights into the metabolic differences between white and yellow fat depots and identified key metabolites associated with beef fat colour. Implications. This study has provided potential biomarkers that may be useful for selection of beef fat colour in live animals.
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