Faggion Sara, Bertotto Daniela, Bonfatti Valentina, Freguglia Matteo, Bargelloni Luca, Carnier Paolo
Department of Comparative Biomedicine and Food Science (BCA), University of Padova, 35020 Padua, Italy.
Valle Cà Zuliani Società Agricola S.r.l., 48017 Ravenna, Italy.
Animals (Basel). 2022 Feb 2;12(3):367. doi: 10.3390/ani12030367.
In European sea bass ( L.), the viral nervous necrosis mortality (MORT), post-stress cortisol concentration (HC), antibody titer (AT) against nervous necrosis virus and body weight (BW) show significant heritability, which makes selective breeding a possible option for their improvement. An experimental population (N = 650) generated by a commercial broodstock was phenotyped for the aforementioned traits and genotyped with a genome-wide SNP panel (16,075 markers). We compared the predictive accuracies of three Bayesian models (Bayes B, Bayes C and Bayesian Ridge Regression) and a machine-learning method (Random Forest). The prediction accuracy of the EBV for MORT was approximately 0.90, whereas the prediction accuracies of the EBV and the phenotype were 0.86 and 0.21 for HC, 0.79 and 0.26 for AT and 0.71 and 0.38 for BW. The genomic prediction of the EBV for MORT used to classify the phenotype for the same trait showed moderate classification performance. Genome-wide association studies confirmed the polygenic nature of MORT and demonstrated a complex genetic structure for HC and AT. Genomic predictions of the EBV for MORT could potentially be used to classify the phenotype of the same trait, though further investigations on a larger experimental population are needed.
在欧洲鲈鱼(L.)中,病毒性神经坏死死亡率(MORT)、应激后皮质醇浓度(HC)、针对神经坏死病毒的抗体滴度(AT)和体重(BW)显示出显著的遗传力,这使得选择性育种成为改善这些性状的一种可能选择。由商业亲鱼产生的一个实验群体(N = 650)针对上述性状进行了表型分析,并使用全基因组SNP面板(16,075个标记)进行了基因分型。我们比较了三种贝叶斯模型(贝叶斯B、贝叶斯C和贝叶斯岭回归)和一种机器学习方法(随机森林)的预测准确性。MORT的估计育种值(EBV)的预测准确性约为0.90,而HC的EBV和表型的预测准确性分别为0.86和0.21,AT为0.79和0.26,BW为0.71和0.38。用于对同一性状的表型进行分类的MORT的EBV的基因组预测显示出中等的分类性能。全基因组关联研究证实了MORT的多基因性质,并证明了HC和AT具有复杂的遗传结构。MORT的EBV的基因组预测可能可用于对同一性状的表型进行分类,不过需要在更大的实验群体上进行进一步研究。