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Genome-wide association study and genomic prediction for resistance against Streptococcus agalactiae in hybrid red tilapia (Oreochromis spp.)

机译:杂交红罗非鱼(OREOCHROMIS SPP)中抗链球菌胆碱抗性的基因组关联研究和基因组预测

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摘要

Streptococcosis is a major disease that causes severe mortality in tilapia aquaculture worldwide. Although the conventional BLUP family selection to enhance disease resistance in a commercial red tilapia stock was successful, the response was low due to the low heritability of the traits. An alternative strategy is the utilization of genomic information to identify the best performing candidates within families. In this study, we performed genome-wide association studies for red tilapia resistance to Streptococcus agalactiae using 11,480 SNPs within 110 families represented by 1020 fish. Nineteen SNP markers were found to explain similar to 10% of the genetic variation. We compared the accuracies of genomic prediction using the pedigree-based (PBLUP), marker-based (GBLUP), and Bayesian models. The prediction accuracy was assessed by performing ten replicates of five-fold cross-validation. In each replicate, approximately 80% of the data (n similar to 816) were sampled for the training set and the remaining data (n similar to 204) were used for the validation. The BayesB model yielded the highest accuracies (0.31 and 0.20) followed by GBLUP (0.25 and 0.15) and PBLUP (0.15 and 0.06) for days to death and binary trait.
机译:链球菌病是一种主要疾病,导致全球罗非鱼水产养殖中严重死亡率。虽然常规的Blup家庭选择在商业红罗非鱼库存中增强抗病性抗性成功,但由于特征的遗传性低,响应率低。另一种策略是利用基因组信息来识别家庭内最好的表现候选人。在这项研究中,我们在1020条鱼类代表的110个家庭内使用11,480个SNP进行了对链球菌急性的红罗非鱼抗性的全基因组关联研究。发现了19个SNP标记,以解释类似于遗传变异的10%。我们使用基于谱系(PBLUP),基于标记(GBLUP)和贝叶斯模型的基因组预测的精度进行了比较。通过执行十倍交叉验证的十个复制来评估预测准确度。在每个复制中,对训练集采样约80%的数据(类似于816的N),剩余数据(类似于204的N)用于验证。贝叶斯模型产生最高的精度(0.31和0.20),然后是GBLUP(0.25和0.15)和PBLUP(0.15和0.06),日死和二进制特征。

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