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

• Published in: BMC Genomics
• Main Authors: Meng, Jie, Song, Kai, Li, Chunyan, Liu, Sheng, Shi, Ruihui, Li, Busu, Wang, Ting, Li, Ao, Que, Huayong, Li, Li, Zhang, Guofan
• Format: Report
• Language: English
• Published: BMC 2019
• Subjects: Oyster; Nutrient traits; Genome resequencing; Population structure; Genome-wide association study; Genetic network; Biotechnology & Applied Microbiology; Genetics & Heredity; AGRONOMIC TRAITS; COMPLEX TRAITS; FAT-CONTENT; LOCI; SELECTION; YIELD; DOMESTICATION; FRAMEWORK; LINKAGE; PROTEIN; Crassostrea gigas
• Online Access: http://ir.qdio.ac.cn/handle/337002/162755; https://doi.org/10.1186/s12864-019-5971-z

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.