| Literature DB >> 34713569 |
Yujie Yan1,2, Junting Wang2, Xiaoping Dong2, Yisheng Cai2, Yude Wang1, Li Ren1, Chun Zhang1, Min Tao1, Kaikun Luo1, Yong Zeng1,2, Shaojun Liu1.
Abstract
Allotetraploid is a new species produced by distant hybridization between red crucian carp (Carassius auratus red var., abbreviated as RCC) and common carp (Cyprinus carpio L., abbreviated as CC). There is a significant difference in growth rate between allotetraploid and its parents. However, the underlying molecular mechanism is largely unknown. In this study, to find direct evidence associated with metabolism and growth rate in protein level, we performed quantitative proteomics analysis on liver tissues between allotetraploid and its parents. A total of 2502 unique proteins were identified and quantified by SWATH-MS in our proteomics profiling. Subsequently, comprehensive bioinformatics analyses including gene ontology enrichment analysis, pathway and network analysis, and protein-protein interaction analysis (PPI) were conducted based on differentially expressed proteins (DEPs) between allotetraploid and its parents. The results revealed several significant DEPs involved in metabolism pathways in liver. More specifically, the integrative analysis highlighted that the DEPs ACSBG1, OAT, and LDHBA play vital roles in metabolism pathways including "pentose phosphate pathway," "TCA cycle," and "glycolysis and gluconeogenesis." These could directly affect the growth rate in fresh water fishes by regulating the metabolism, utilization, and exchange of substance and energy. Since the liver is the central place for metabolism activity in animals, we firstly established the comprehensive and quantitative proteomics knowledge base for liver tissue from freshwater fishes, our study may serve as an irreplaceable reference for further studies regarding fishes' culture and growth.Entities:
Keywords: SWATH-MS; allotetraploid; liver; metabolism; network analysis
Mesh:
Year: 2021 PMID: 34713569 DOI: 10.1002/pmic.202100115
Source DB: PubMed Journal: Proteomics ISSN: 1615-9853 Impact factor: 3.984