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首次对条石鲷复杂生长相关性状进行基因组预测和全基因组关联分析。

First genomic prediction and genome-wide association for complex growth-related traits in Rock Bream ().

作者信息

Gong Jie, Zhao Ji, Ke Qiaozhen, Li Bijun, Zhou Zhixiong, Wang Jiaying, Zhou Tao, Zheng Weiqiang, Xu Peng

机构信息

Fujian Key Laboratory of Genetics and Breeding of Marine Organisms College of Ocean and Earth Sciences Xiamen University Xiamen China.

State Key Laboratory of Large Yellow Croaker Breeding Ningde Fufa Fisheries Company Limited Ningde China.

出版信息

Evol Appl. 2021 Mar 17;15(4):523-536. doi: 10.1111/eva.13218. eCollection 2022 Apr.

Abstract

Rock Bream () is an important aquaculture species for offshore cage aquaculture and fish stocking of marine ranching in East Asia. Genomic selection has the potential to expedite genetic gain for the key target traits of a breeding program, but has not yet been evaluated in . The purposes of the present study were to explore the performance of genomic selection to improve breeding value accuracy through real data analyses using six statistical models and to carry out genome-wide association studies (GWAS) to dissect the genetic architecture of economically vital growth-related traits (body weight, total length, and body depth) in the . population. After quality control, genotypes for 16,162 SNPs were acquired for 455 fish. Heritability was estimated to be moderate for the three traits (0.38 for BW, 0.33 for TL, and 0.24 for BD), and results of GWAS indicated that the underlying genetic architecture was polygenic. Six statistic models (GBLUP, BayesA, BayesB, BayesC, Bayesian Ridge-Regression, and Bayesian LASSO) showed similar performance for the predictability of genomic estimated breeding value (GEBV). The low SNP density (around 1 K selected SNP based on GWAS) is sufficient for accurate prediction on the breeding value for the three growth-related traits in the current studied population, which will provide a good compromise between genotyping costs and predictability in such standard breeding populations advanced. These consequences illustrate that the employment of genomic selection in . breeding could provide advantages for the selection of breeding candidates to facilitate complex economic growth traits.

摘要

真鲷是东亚近海网箱养殖和海洋牧场鱼类放流的重要养殖品种。基因组选择有潜力加快育种计划关键目标性状的遗传进展,但在真鲷中尚未得到评估。本研究的目的是通过使用六种统计模型的实际数据分析来探索基因组选择提高育种值准确性的性能,并进行全基因组关联研究(GWAS)以剖析真鲷群体中与经济重要的生长相关性状(体重、全长和体深)的遗传结构。经过质量控制后,获得了455尾鱼的16,162个单核苷酸多态性(SNP)的基因型。这三个性状的遗传力估计为中等(体重为0.38,全长为0.33,体深为0.24),GWAS结果表明潜在的遗传结构是多基因的。六种统计模型(GBLUP、BayesA、BayesB、BayesC、贝叶斯岭回归和贝叶斯LASSO)在基因组估计育种值(GEBV)的预测能力方面表现相似。低SNP密度(基于GWAS选择约1K个SNP)足以准确预测当前研究群体中三个与生长相关性状的育种值,这将在基因分型成本和此类标准育种群体的预测能力之间提供良好的折衷。这些结果表明,在真鲷育种中采用基因组选择可为选择育种候选个体提供优势,以促进复杂经济生长性状的选育。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef40/9046763/dc00d526cf05/EVA-15-523-g003.jpg

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