ArticleBMC genomics2019
Genome-wide association analysis of nutrient traits in the oyster Crassostrea gigas: genetic effect and interaction network.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Genome-wide association study and genomic selection for growth-related traits in Eastern oyster (Crassostrea virginica).BMC genomics · 2025Article
- Genetic Basis of Low-Salinity Tolerance in the Pacific Oyster (Crassostrea gigas) as Revealed by Estimation of Genetic Parameters and Genome-Wide Association Study.Marine biotechnology (New York, N.Y.) · 2025Article
- Network analysis combined with genome-wide association study helps identification of genes related to amino acid contents in soybean.BMC genomics · 2025Article
- Genome-wide association study reveals the underlying regulatory mechanisms of red blood traits in Anadara granosa.BMC genomics · 2024Article
- Genome-wide association analysis explores the genetic loci of amino acid content in duck's breast muscle.BMC genomics · 2024Article
- Molecular cloning, characterisation and molecular modelling of two novel T-synthases from mollusc origin.Glycobiology · 2024Article
- Combined ATAC-seq, RNA-seq, and GWAS analysis reveals glycogen metabolism regulatory network in Jinjiang oyster (Zoological research · 2024Article
- A core of functional complementary bacteria infects oysters in Pacific Oyster Mortality Syndrome.Animal microbiome · 2023Article
- Genome-Wide Association and Genomic Prediction of Growth Traits in the European Flat Oyster (Frontiers in genetics · 2022Article
- MultiGWAS: An integrative tool for Genome Wide Association Studies in tetraploid organisms.Ecology and evolution · 2021Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundOyster 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.
resultsAfter 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.
conclusionOverall, 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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