Genome-wide association study and genomic prediction for growth traits in spotted sea bass (Lateolabrax maculatus) using insertion and deletion markers

Chong Zhang, Yonghang Zhang, Cong Liu, Lingyu Wang, Yani Dong, Donglei Sun, Haishen Wen, Kaiqiang Zhang, Xin Qi, Yun Li
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Abstract

Spotted sea bass (Lateolabrax maculatus) is a species of significant economic importance in aquaculture. However, genetic degeneration, such as declining growth performance, has severely impeded industry development, necessitating urgent genetic improvement. Here, we conducted a genome-wide association study (GWAS) and genomic prediction for growth traits using insertion and deletion (InDel) markers, and systematically compared the results with our previous studies using single nucleotide polymorphism (SNP) markers. A total of 97 significant InDels including a 6 bp insertion in an exon region were identified. It is worth noting that only 5 and 1 candidate genes for DY and TS populations were also detected in previous GWAS using SNPs, and numerous novel genes including c4b, fgf4, and dnajb9 were identified as vital candidate genes. Moreover, several novel growth-related procedures, such as the growth and development of the bone and muscle, were also detected. These findings indicated that InDel-based GWAS can provide valuable complement to SNP-based studies. The comparison of genomic predictive performance for total length trait under different marker selection strategies and genomic selection models indicated that GWAS selection strategy exhibits more stable predictive performance compared to the evenly selection strategy. Additionally, support vector machine model demonstrated better predictive accuracy and efficiency than traditional best linear unbiased prediction and Bayes models. Furthermore, the superior predictive performance using InDel markers compared to SNP markers highlighted the potential of InDels to enhance genomic predictive accuracy and efficiency. Our results carry significant implications for dissecting genetic mechanisms and contributing genetic improvement of growth traits in spotted sea bass through genomic resources.

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利用插入和缺失标记对斑点海鲈(Lateolabrax maculatus)生长性状进行全基因组关联研究和基因组预测
斑点叉尾鲈(Lateolabrax maculatus)是水产养殖业中具有重要经济意义的物种。然而,生长性能下降等遗传退化问题严重阻碍了产业发展,迫切需要进行遗传改良。在此,我们利用插入和缺失(InDel)标记物进行了生长性状的全基因组关联研究(GWAS)和基因组预测,并将结果与之前利用单核苷酸多态性(SNP)标记物进行的研究进行了系统比较。共鉴定出 97 个重要的 InDel,包括一个外显子区域的 6 bp 插入。值得注意的是,在之前使用 SNP 进行的 GWAS 研究中,DY 和 TS 群体的候选基因分别只有 5 个和 1 个,而包括 c4b、fgf4 和 dnajb9 在内的许多新基因被确定为重要的候选基因。此外,还发现了一些与生长相关的新程序,如骨骼和肌肉的生长发育。这些发现表明,基于 InDel 的 GWAS 可以为基于 SNP 的研究提供有价值的补充。在不同的标记选择策略和基因组选择模型下,总长度性状的基因组预测性能比较表明,与均匀选择策略相比,GWAS 选择策略表现出更稳定的预测性能。此外,与传统的最佳线性无偏预测和贝叶斯模型相比,支持向量机模型表现出更好的预测精度和效率。此外,与 SNP 标记相比,使用 InDel 标记的预测性能更优,这凸显了 InDel 在提高基因组预测准确性和效率方面的潜力。我们的研究结果对于通过基因组资源剖析遗传机制并促进斑点叉尾鲈生长性状的遗传改良具有重要意义。
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Issue Information Animal biotech breeding and reproduction: A new engine for high-quality development of animal husbandry The Duck 1000 Genomes Project: Achievements and perspectives The paradigm of genomic selection: Does it need an update? Genome-wide association study and genomic prediction for growth traits in spotted sea bass (Lateolabrax maculatus) using insertion and deletion markers
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