Integrated Analysis of Transcriptome and Metabolome Profiles in the Longissimus Dorsi Muscle of Buffalo and Cattle
Guansheng Wu, Xinjun Qiu, Zizhuo Jiao, Weijie Yang, Haoju Pan, Hong Li, Zhengyu Bian, Qiang Geng, Hui Wu, Junming Jiang, Yuanyuan Chen, Yiwen Cheng, Qiaoling Chen, Si Chen, Churiga Man, Li Du, Lianbin Li, Fengyang Wang, Chih-Cheng Lin, Jia-Feng Chang · 2023
Read Integrated Analysis of Transcriptome and Metabolome Profiles in the Longissimus Dorsi Muscle of Buffalo and Cattle by Guansheng Wu, Xinjun Qiu, Zizhuo Jiao, Weijie Yang, Haoju Pan, Hong Li, Zhengyu Bian, Qiang Geng, Hui Wu, Junming Jiang, Yuanyuan Chen, Yiwen Cheng, Qiaoling Chen, Si Chen, Churiga Man, Li Du, Lianbin Li, Fengyang Wang, Chih-Cheng Lin, Jia-Feng Chang (2023) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-10741837.txt.
Description
Guansheng Wu and co-authors published this meat science study in 2023. Buffalo meat is lean and low in cholesterol, but buyers often reject its dark color and toughness. The team compared the back muscle of Xinglong buffalo, a Hainan breed being shifted from farm labor to meat production, against local cattle. They measured meat traits directly, then profiled both gene activity and small-molecule chemistry in the tissue.
Buffalo meat proved redder but tougher, with fewer amino acids than beef. The combined profiles flagged hundreds of differing genes and metabolites. They clustered in pathways handling niacin-related compounds and a few amino acids. Specific genes and molecules tracked closely with color, tenderness, and amino acid content. The authors nominate them as candidate markers for breeding. The work gives buffalo improvers a molecular map for selecting animals whose meat keeps its health appeal while eating better.
Catalog record
| CREATOR | Guansheng Wu, Xinjun Qiu, Zizhuo Jiao, Weijie Yang, Haoju Pan, Hong Li, Zhengyu Bian, Qiang Geng, Hui Wu, Junming Jiang, Yuanyuan Chen, Yiwen Cheng, Qiaoling Chen, Si Chen, Churiga Man, Li Du, Lianbin Li, Fengyang Wang, Chih-Cheng Lin, Jia-Feng Chang |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 34 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |