GWAS Enhances Genomic Prediction Accuracy of Caviar Yield, Caviar Color and Body Weight Traits in Sturgeons Using Whole-Genome Sequencing Data
文献类型： 外文期刊
作者： Song, Hailiang 1 ; Dong, Tian 1 ; Wang, Wei 1 ; Yan, Xiaoyu 1 ; Geng, Chenfan 1 ; Bai, Song 1 ; Hu, Hongxia 1 ;
作者机构： 1.Beijing Acad Agr & Forestry Sci, Fisheries Sci Inst, Beijing 100068, Peoples R China
2.Beijing Key Lab Fisheries Biotechnol, Beijing 100068, Peoples R China
3.Minist Agr & Rural Affairs, Key Lab Sturgeon Genet & Breeding, Hangzhou 311799, Peoples R China
4.Natl Innovat Ctr Digital Seed Ind, Beijing 100097, Peoples R China
关键词： sturgeon; whole-genome sequencing; genome-wide association study; candidate gene; genomic prediction
期刊名称：INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES （ 影响因子：4.9； 五年影响因子：5.7 ）
ISSN： 1661-6596
年卷期： 2024 年 25 卷 17 期
页码：
收录情况： SCI
摘要： Caviar yield, caviar color, and body weight are crucial economic traits in sturgeon breeding. Understanding the molecular mechanisms behind these traits is essential for their genetic improvement. In this study, we performed whole-genome sequencing on 673 Russian sturgeons, renowned for their high-quality caviar. With an average sequencing depth of 13.69x, we obtained approximately 10.41 million high-quality single nucleotide polymorphisms (SNPs). Using a genome-wide association study (GWAS) with a single-marker regression model, we identified SNPs and genes associated with these traits. Our findings revealed several candidate genes for each trait: caviar yield: TFAP2A, RPS6KA3, CRB3, TUBB, H2AFX, morc3, BAG1, RANBP2, PLA2G1B, and NYAP1; caviar color: NFX1, OTULIN, SRFBP1, PLEK, INHBA, and NARS; body weight: ACVR1, HTR4, fmnl2, INSIG2, GPD2, ACVR1C, TANC1, KCNH7, SLC16A13, XKR4, GALR2, RPL39, ACVR2A, ADCY10, and ZEB2. Additionally, using the genomic feature BLUP (GFBLUP) method, which combines linkage disequilibrium (LD) pruning markers with GWAS prior information, we improved genomic prediction accuracy by 2%, 1.9%, and 3.1% for caviar yield, caviar color, and body weight traits, respectively, compared to the GBLUP method. In conclusion, this study enhances our understanding of the genetic mechanisms underlying caviar yield, caviar color, and body weight traits in sturgeons, providing opportunities for genetic improvement of these traits through genomic selection.
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