Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency
文献类型： 外文期刊
作者： Wu, Jie 1 ; Ye, Yong 1 ; Quan, Jianping 1 ; Ding, Rongrong 1 ; Wang, Xingwang 1 ; Zhuang, Zhanwei 1 ; Zhou, Shenping 1 ;
作者机构： 1.South China Agr Univ, Coll Anim Sci, Guangzhou 510642, Peoples R China
2.South China Agr Univ, Natl Engn Res Ctr Breeding Swine Ind, Guangzhou 510642, Peoples R China
3.Guangdong Prov Lab Lingnan Modern Agr Sci & Techn, Guangzhou 510642, Peoples R China
4.State Key Lab Conservat & Utilizat Subtrop Agrobi, Guangzhou 510642L, Peoples R China
5.Guangdong Prov Key Lab Agroanim Genom & Mol Breed, Guangzhou 510642, Peoples R China
关键词： Feed efficiency; Pig; LC-MS; WGCNA
期刊名称：PORCINE HEALTH MANAGEMENT （ 影响因子：3.048； 五年影响因子：3.572 ）
ISSN：
年卷期： 2021 年 7 卷 1 期
页码：
收录情况： SCI
摘要： Background Improving feed efficiency is economically and environmentally beneficial in the pig industry. A deeper understanding of feed efficiency is essential on many levels for its highly complex nature. The aim of this project is to explore the relationship between fecal metabolites and feed efficiency-related traits, thereby identifying metabolites that may assist in the screening of the feed efficiency of pigs. Results We performed fecal metabolomics analysis on 50 individuals selected from 225 Duroc x (Landrace x Yorkshire) (DLY) commercial pigs, 25 with an extremely high feed efficiency and 25 with an extremely low feed efficiency. A total of 6749 and 5644 m/z features were detected in positive and negative ionization modes by liquid chromatography-mass spectrometry (LC/MS). Regrettably, the PCA could not classify the the samples accurately. To improve the classification, OPLS-DA was introduced. However, the predictive ability of the OPLS-DA model did not perform well. Then, through weighted coexpression network analysis (WGCNA), we found that one module in each positive and negative mode was related to residual feed intake (RFI), and six and three metabolites were further identified. The nine metabolites were found to be involved in multiple metabolic pathways, including lipid metabolism (primary bile acid synthesis, linoleic acid metabolism), vitamin D, glucose metabolism, and others. Then, Lasso regression analysis was used to evaluate the importance of nine metabolites obtained by the annotation process. Conclusions Altogether, this study provides new insights for the subsequent evaluation of commercial pig feed efficiency through small molecule metabolites, but also provide a reference for the development of new feed additives.
- 相关文献
作者其他论文 更多>>
-
A deep learning-based approach for fully automated segmentation and quantitative analysis of muscle fibers in pig skeletal muscle
作者：Yao, Zekai;Li, Hao;Li, Xinxin;Li, Jianhao;Luo, Yizhi;Meng, Fanming;Yao, Zekai;Zheng, Enqin;Yang, Jie;Li, Hao;Li, Xinxin;Wang, Ting;Fan, Zhenfei;Zhan, Yuexin;Yang, Yingshan;Wu, Zhenfang;Yao, Zekai;Zheng, Enqin;Yang, Jie;Li, Hao;Li, Xinxin;Wang, Ting;Fan, Zhenfei;Zhan, Yuexin;Yang, Yingshan;Wu, Zhenfang;Wo, Jingjie;Yin, Ling;Wu, Zhenfang;Luo, Yizhi;Zheng, Enqin;Yang, Jie;Wu, Zhenfang
关键词：Pigs; Skeletal muscle; Deep learning; Image segmentation; Quantitative analysis
-
Multi-omic characterization of allele-specific regulatory variation in hybrid pigs
作者：Quan, Jianping;Wang, Xingwang;Cai, Gengyuan;Ding, Rongrong;Zhuang, Zhanwei;Zhou, Shenping;Ruan, Donglin;Wu, Jiajin;Zheng, Enqin;Zhang, Zebin;Liu, Langqing;Meng, Fanming;Wu, Jie;Xu, Cineng;Qiu, Yibin;Wang, Shiyuan;Lin, Meng;Li, Shaoyun;Ye, Yong;Zhou, Fuchen;Lin, Danyang;Li, Xuehua;Deng, Shaoxiong;Zhang, Yuling;Yao, Zekai;Yang, Yingshan;Liu, Yiyi;Zhan, Yuexin;Zhang, Jiaming;Ma, Fucai;Yang, Jifei;Chen, Qiaoer;Yang, Jisheng;Gu, Ting;Huang, Sixiu;Xu, Zheng;Li, Zicong;Yang, Jie;Wu, Zhenfang;Quan, Jianping;Ding, Rongrong;Tan, Suxu;Huang, Wen;Quan, Jianping;Cai, Gengyuan;Wu, Jiajin;Zheng, Enqin;Zhang, Zebin;Liu, Langqing;Lin, Meng;Huang, Sixiu;Yang, Jie;Quan, Jianping;Ding, Rongrong;Ye, Jian;Dong, Linsong;Wu, Zhenfang;Yang, Ming;Gao, Xin;Liu, Zhihong;Yang, Ming;Ding, Rongrong;Ye, Jian;Dong, Linsong;Wu, Zhenfang;Wang, Xingwang;Cai, Gengyuan;Zhuang, Zhanwei;Zhou, Shenping;Ruan, Donglin;Wu, Jiajin;Zheng, Enqin;Zhang, Zebin;Liu, Langqing;Wu, Jie;Xu, Cineng;Qiu, Yibin;Wang, Shiyuan;Li, Shaoyun;Ye, Yong;Zhou, Fuchen;Lin, Danyang;Li, Xuehua;Deng, Shaoxiong;Zhang, Yuling;Yao, Zekai;Yang, Yingshan;Liu, Yiyi;Zhan, Yuexin;Zhang, Jiaming;Ma, Fucai;Yang, Jifei;Gu, Ting;Xu, Zheng;Li, Zicong;Yang, Jie;Meng, Fanming
关键词：
-
Protein Dynamic Landscape during Mouse Mammary Gland Development from Virgin to Pregnant, Lactating, and Involuting Stages
作者：Wang, Wenjing;Wang, Shunbo;Wang, Hao;Zheng, Enqin;Wu, Zhenfang;Li, Zicong;Wang, Wenjing;Wang, Shunbo;Wang, Hao;Zheng, Enqin;Wu, Zhenfang;Li, Zicong;Wu, Zhenfang;Li, Zicong
关键词：development; mammary gland; mouse; DIA-based quantitativeproteomics; EGF
-
DIA-based quantitative proteomic analysis of porcine endometrium in the peri-implantation phase
作者：Zhou, Chen;Wang, Yongzhong;He, Simin;Lin, Shifei;Cheng, Jie;Hu, Qun;Gu, Ting;Cai, Gengyuan;Li, Zicong;Wu, Zhenfang;Hong, Linjun;Zhou, Chen;Wang, Yongzhong;He, Simin;Lin, Shifei;Cheng, Jie;Hu, Qun;Gu, Ting;Cai, Gengyuan;Li, Zicong;Wu, Zhenfang;Hong, Linjun;Zhou, Chen;Wang, Yongzhong;He, Simin;Lin, Shifei;Cheng, Jie;Hu, Qun;Cai, Gengyuan;Li, Zicong;Wu, Zhenfang;Hong, Linjun;Meng, Fanming;Wu, Zhenfang;Wu, Zhenfang;Hong, Linjun
关键词：DIA-based quantitative proteomics; Yorkshire; Endometrium; Peri-implantation; FGL2
-
Protein Dynamic Landscape of Pig Embryos during Peri-Implantation Development
作者：Zang, Xupeng;Huang, Qiuying;Gan, Jianyu;Jiang, Lei;Gu, Ting;Cai, Gengyuan;Li, Zicong;Wu, Zhenfang;Hong, Linjun;Zang, Xupeng;Huang, Qiuying;Gan, Jianyu;Jiang, Lei;Gu, Ting;Cai, Gengyuan;Li, Zicong;Wu, Zhenfang;Hong, Linjun;Meng, Fanming;Gu, Ting;Cai, Gengyuan;Li, Zicong;Wu, Zhenfang;Hong, Linjun;Gu, Ting;Cai, Gengyuan;Li, Zicong;Wu, Zhenfang;Hong, Linjun
关键词：development; implantation; peri-implantationembryo; pig; proteome
-
The effects of boar seminal plasma extracellular vesicles on sperm fertility
作者：Xu, Zhiqian;Xie, Yanshe;Wu, Changhua;Gu, Ting;Zhang, Xianwei;Yang, Jie;Yang, Huaqiang;Zheng, Enqin;Huang, Sixiu;Xu, Zheng;Li, Zicong;Cai, Gengyuan;Liu, Dewu;Hong, Linjun;Wu, Zhenfang;Xu, Zhiqian;Xie, Yanshe;Wu, Changhua;Gu, Ting;Zhang, Xianwei;Yang, Jie;Yang, Huaqiang;Zheng, Enqin;Huang, Sixiu;Xu, Zheng;Li, Zicong;Cai, Gengyuan;Liu, Dewu;Hong, Linjun;Wu, Zhenfang;Xu, Zhiqian;Wu, Zhenfang;Hong, Linjun;Wu, Zhenfang
关键词：Seminal plasma extracellular vesicles; Proteomics; EZRIN; Sperm; Fertility
-
Genome-wide association studies for loin muscle area, loin muscle depth and backfat thickness in DLY pigs
作者：Zhao, Xiang;Qiu, Yibin;Zhuang, Zhanwei;Ruan, Donglin;Wu, Jie;Ma, Fucai;Zheng, Enqin;Cai, Gengyuan;Yang, Jie;Wu, Zhenfang;Zhao, Xiang;Qiu, Yibin;Zhuang, Zhanwei;Ruan, Donglin;Wu, Jie;Ma, Fucai;Zheng, Enqin;Cai, Gengyuan;Yang, Jie;Wu, Zhenfang;Meng, Fanming;Zheng, Enqin;Cai, Gengyuan;Yang, Jie;Wu, Zhenfang;Cai, Gengyuan;Yang, Ming;Yang, Ming;Wu, Zhenfang
关键词：backfat thickness; genome-wide association study; loin muscle area; loin muscle depth; SNP
