Dong Linsong, Xiao Shijun, Chen Junwei, Wan Liang, Wang Zhiyong
Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture, Jimei University, Xiamen, Fujian, People's Republic of China.
Academy of Animal Science and Technology, Collaborative Innovation Center for Aquatic Efficient Health Production of Fisheries, Hunan Agricultural University, Changsha, Hunan, People's Republic of China.
Mar Biotechnol (NY). 2016 Oct;18(5):575-583. doi: 10.1007/s10126-016-9718-4. Epub 2016 Oct 4.
Genomic selection (GS) is an effective method to improve predictive accuracies of genetic values. However, high cost in genotyping will limit the application of this technology in some species. Therefore, it is necessary to find some methods to reduce the genotyping costs in genomic selection. Large yellow croaker is one of the most commercially important marine fish species in southeast China and Eastern Asia. In this study, genotyping-by-sequencing was used to construct the libraries for the NGS sequencing and find 29,748 SNPs in the genome. Two traits, eviscerated weight (EW) and the ratio between eviscerated weight and whole body weight (REW), were chosen to study. Two strategies to reduce the costs were proposed as follows: selecting extreme phenotypes (EP) for genotyping in reference population or pre-selecting SNPs to construct low-density marker panels in candidates. Three methods of pre-selection of SNPs, i.e., pre-selecting SNPs by absolute effects (SE), by single marker analysis (SMA), and by fixed intervals of sequence number (EL), were studied. The results showed that using EP was a feasible method to save the genotyping costs in reference population. Heritability did not seem to have obvious influences on the predictive abilities estimated by EP. Using SMA was the most feasible method to save the genotyping costs in candidates. In addition, the combination of EP and SMA in genomic selection also showed good results, especially for trait of REW. We also described how to apply the new methods in genomic selection and compared the genotyping costs before and after using the new methods. Our study may not only offer a reference for aquatic genomic breeding but also offer a reference for genomic prediction in other species including livestock and plants, etc.
基因组选择(GS)是提高遗传值预测准确性的有效方法。然而,基因分型的高成本将限制该技术在某些物种中的应用。因此,有必要找到一些方法来降低基因组选择中的基因分型成本。大黄鱼是中国东南部和东亚最重要的商业海洋鱼类之一。在本研究中,采用简化基因组测序技术构建用于二代测序的文库,并在基因组中发现了29748个单核苷酸多态性(SNP)。选择了两个性状进行研究,即去内脏重量(EW)和去内脏重量与全鱼重量之比(REW)。提出了两种降低成本的策略如下:在参考群体中选择极端表型(EP)进行基因分型,或在候选群体中预先选择SNP构建低密度标记面板。研究了三种SNP预先选择方法,即按绝对效应(SE)、单标记分析(SMA)和按序列号固定间隔(EL)预先选择SNP。结果表明,使用EP是在参考群体中节省基因分型成本的可行方法。遗传力似乎对EP估计的预测能力没有明显影响。使用SMA是在候选群体中节省基因分型成本的最可行方法。此外,EP和SMA在基因组选择中的组合也显示出良好的效果,特别是对于REW性状。我们还描述了如何在基因组选择中应用新方法,并比较了使用新方法前后的基因分型成本。我们的研究不仅可为水产基因组育种提供参考,也可为包括家畜和植物等其他物种的基因组预测提供参考。