Table_2_Assessing Accuracy of Genomic Predictions for Resistance to Infectious Hematopoietic Necrosis Virus With Progeny Testing of Selection Candidates in a Commercial Rainbow Trout Breeding Population.XLSX

Infectious hematopoietic necrosis (IHN) is an economically important disease of salmonid fish caused by the IHN virus (IHNV). Under industrial aquaculture settings, IHNV can cause substantial mortality and losses. Actually, there is no confirmed and cost-effective method for IHNV control. Clear Springs Foods, Inc. has been performing family-based selective breeding to increase genetic resistance to IHNV in their rainbow trout breeding program. In an earlier study, we used siblings cross-validation to estimate the accuracy of genomic prediction (GP) for IHNV resistance in this breeding population. In the present report, we used empirical progeny testing data to evaluate whether genomic selection (GS) can improve the accuracy of breeding value predictions over traditional pedigree-based best linear unbiased predictions (PBLUP). We found that the GP accuracy with single-step GBLUP (ssGBLUP) outperformed PBLUP by 15% (from 0.33 to 0.38). Furthermore, we found that ssGBLUP had higher GP accuracy than weighted ssGBLUP (wssGBLUP) and single-step Bayesian multiple regression (ssBMR) models with BayesB and BayesC priors which supports our previous findings that the underlying liability of genetic resistance against IHNV in this breeding population might be polygenic. Our results show that GS can be more effective than either the traditional pedigree-based PBLUP model or the marker-assisted selection approach for improving genetic resistance against IHNV in this commercial rainbow trout population.

传染性造血器官坏死病（Infectious hematopoietic necrosis, IHN）是由IHN病毒（IHNV）引发的鲑科鱼类重要经济病害。在工业化水产养殖场景下，IHNV可造成大规模死亡与经济损失，目前尚无经证实且经济高效的IHNV防控方法。Clear Springs Foods, Inc. 长期在其虹鳟育种项目中推行家系选择性育种，以提升种群对IHNV的遗传抗性。在既往研究中，我们采用同胞交叉验证评估了该育种群体中IHNV抗性的基因组预测（genomic prediction, GP）准确性。本报告借助实证性后代测试数据，探究基因组选择（genomic selection, GS）相比传统基于系谱的最佳线性无偏预测（pedigree-based best linear unbiased predictions, PBLUP）能否优化育种值预测精度。结果显示，单步GBLUP（single-step GBLUP, ssGBLUP）的GP准确性较PBLUP提升15%（从0.33升至0.38）。进一步分析表明，ssGBLUP的GP准确性优于加权单步GBLUP（weighted ssGBLUP, wssGBLUP）以及搭载BayesB和BayesC先验的单步贝叶斯多元回归（single-step Bayesian multiple regression, ssBMR）模型，这一发现支持了我们此前的结论：该育种群体中抗IHNV的遗传潜在易感性可能为多基因调控性状。本研究结果证实，相较于传统基于系谱的PBLUP模型或标记辅助选择方案，基因组选择可更高效地提升商业虹鳟种群对IHNV的遗传抗性。