Genome-wide association analysis of nutrient traits in the oyster Crassostrea gigas: genetic effect and interaction network

被引:40
作者
Meng, Jie [1 ,4 ,5 ]
Song, Kai [1 ,4 ,5 ]
Li, Chunyan [1 ,4 ,6 ]
Liu, Sheng [1 ,4 ,6 ]
Shi, Ruihui [1 ,4 ,6 ]
Li, Busu [1 ,4 ,6 ]
Wang, Ting [1 ,4 ,6 ]
Li, Ao [1 ,4 ,6 ]
Que, Huayong [1 ,2 ,4 ,5 ]
Li, Li [1 ,3 ,4 ,5 ]
Zhang, Guofan [1 ,2 ,4 ,5 ]
机构
[1] Chinese Acad Sci, Inst Oceanol, Key Lab Expt Marine Biol, Qingdao 266071, Shandong, Peoples R China
[2] Qingdao Natl Lab Marine Sci & Technol, Lab Marine Biol & Biotechnol, Qingdao 266071, Shandong, Peoples R China
[3] Qingdao Natl Lab Marine Sci & Technol, Lab Marine Fisheries & Aquaculture, Qingdao 266071, Shandong, Peoples R China
[4] Natl & Local Joint Engn Lab Ecol Mariculture, Qingdao 266071, Shandong, Peoples R China
[5] Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Shandong, Peoples R China
[6] Univ Chinese Acad Sci, Beijing 100039, Peoples R China
基金
中国国家自然科学基金;
关键词
Oyster; Nutrient traits; Genome resequencing; Population structure; Genome-wide association study; Genetic network; AGRONOMIC TRAITS; COMPLEX TRAITS; FAT-CONTENT; LOCI; SELECTION; YIELD; DOMESTICATION; FRAMEWORK; LINKAGE; PROTEIN;
D O I
10.1186/s12864-019-5971-z
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: Oyster is rich in glycogen and free amino acids and is called "the milk of sea". To understand the main genetic effects of these traits and the genetic networks underlying their correlation, we have conducted the whole genome resequencing with 427 oysters collected from the world-wide scale. Results: After association analysis, 168 clustered significant single nucleotide polymorphism (SNP) loci were identified for glycogen content and 17 SNPs were verified with 288 oyster individuals in another wide populations. These were the most important candidate loci for oyster breeding. Among 24 genes in the 100-kb regions of the leading SNP loci, cytochrome P450 17A1 (CYP17A1) contained a non-synonymous SNP and displayed higher expressions in high glycogen content individuals. This might enhance the gluconeogenesis process by the transcriptionally regulating the expression of phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6-phosphatase (G6Pase). Also, for amino acids content 417 clustered significant SNPs were identified. After genetic network analysis, three node SNP regions were identified to be associated with glycogen, protein, and Asp content, which might explain their significant correlation. Conclusion: Overall, this study provides insights into the genetic correlation among complex traits, which will facilitate future oyster functional studies and breeding through molecular design.
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页数:14
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