Summary of Study ST002210
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001411. The data can be accessed directly via it's Project DOI: 10.21228/M8BB0F This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
Study ID | ST002210 |
Study Title | Revealing the Social Biomarkers of Residual Feed Intake by Using 16s rRNA and LC-MS/MS in Duroc Pig |
Study Summary | Feed efficiency (FE) is a typical social affected trait. However, the mechanisms involved are not fully elucidated. According to the rank of residual feed intake (RFI)’s the social genetic effect (SGE), ten high and low pigs were selected, named LRI and HRI groups. The sampling of jejunal chyme after slaughter. 16S rRNA and LC-MS/MS were conducted to investigate the relationship between the gut microbiome or metabolites and the SGE of RFI. The results showed significant differences between HRI and LRI groups. Compared with the HRI group, Escherichia, Eubacterium, and Gemmiger were enriched in the LRI group (P < 0.01), whereas the abundance of Fusobacterium, Eubacterium, and Desulfovibrio in the HRI group were significantly higher than that in the LRI group (P < 0.01). In the metabolome, we found that Glycine, L-lysine, and L-tryptophan were positively correlated with RFI’s SGE. KEGG pathway analysis revealed that most differential metabolites were involved in amino acid metabolism. The Pearson correlation analysis of the candidate social biomarkers was carried out. Amino acid metabolites were discovered to have significant correlations with Escherichia and Fusobacterium. Therefore, Escherichia and Fusobacterium may influence the SGE of RFI through amino acid metabolism, thereby affecting feed efficiency. |
Institute | Sichuan Agricultural University |
Department | animal science and technology |
Laboratory | Guoqing Tang Group |
Last Name | Wang |
First Name | Shujie |
Address | Huimin Road, Chengdu, Sichuan, China |
670186296@qq.com | |
Phone | 15680993607 |
Submit Date | 2022-07-02 |
Raw Data Available | Yes |
Raw Data File Type(s) | raw(Thermo) |
Analysis Type Detail | LC-MS |
Release Date | 2022-07-11 |
Release Version | 1 |
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Project:
Project ID: | PR001411 |
Project DOI: | doi: 10.21228/M8BB0F |
Project Title: | Revealing the Social Biomarkers of Residual Feed Intake by Using 16s rRNA and LC-MS/MS in Duroc Pig |
Project Summary: | Feed efficiency (FE) is a typical social affected trait. However, the mechanisms involved are not fully elucidated. According to the rank of residual feed intake (RFI)’s the social genetic effect (SGE), ten high and low pigs were selected, named LRI and HRI groups. The sampling of jejunal chyme after slaughter. 16S rRNA and LC-MS/MS were conducted to investigate the relationship between the gut microbiome or metabolites and the SGE of RFI. The results showed significant differences between HRI and LRI groups. Compared with the HRI group, Escherichia, Eubacterium, and Gemmiger were enriched in the LRI group (P < 0.01), whereas the abundance of Fusobacterium, Eubacterium, and Desulfovibrio in the HRI group were significantly higher than that in the LRI group (P < 0.01). In the metabolome, we found that Glycine, L-lysine, and L-tryptophan were positively correlated with RFI’s SGE. KEGG pathway analysis revealed that most differential metabolites were involved in amino acid metabolism. The Pearson correlation analysis of the candidate social biomarkers was carried out. Amino acid metabolites were discovered to have significant correlations with Escherichia and Fusobacterium. Therefore, Escherichia and Fusobacterium may influence the SGE of RFI through amino acid metabolism, thereby affecting feed efficiency. |
Institute: | Sichuan Agricultural University |
Last Name: | Wang |
First Name: | Shujie |
Address: | Huimin Road, Chengdu, Sichuan, China |
Email: | 670186296@qq.com |
Phone: | 15680993607 |