基于不同密度SNP面板的凡纳滨对虾AHPND抗性基因组预测准确性分析

为评估不同SNP标记密度对凡纳滨对虾AHPND抗性基因组预测准确性的影响,本实验对26个全同胞家系进行Vp AHPND侵染,收集686尾个体的存活时间数据,对其中242尾个体利用液相芯片“黄海芯1号”(55.0 K SNP)进行基因分型,基于A、G和H亲缘关系矩阵估计Vp AHPND侵染后存活时间的遗传参数;采用随机和等距抽取方式,基于55.0K SNP构建了8个低密度SNP面板(40.0、30.0、20.0、10.0、5.0、1.0、0.5和0.1 K),利用GBLUP和ssGBLUP等方法预测Vp AHPND侵染后存活时间的基因组育种值,利用交叉验证方法计算其预测准确性,并与BLUP方法进行对比分析。遗传参数估计结果显示,Vp AHPND侵染后存活时间表现为高遗传力水平,估计值为0.68～0.79。在55.0 K SNP密度下,针对242尾基因分型个体数据集(G242),利用BLUP、GBLUP和ssGBLUP方法获得的预测准确性分别为0.424、0.450和0.452,GBLUP和ssGBLUP比BLUP分别提升了6.13%和6.60%;针对686尾表型测定个体数据集(P686)...

Genomic prediction accuracy analysis of AHPND resistance genome prediction in Litopenaeus vannamei using SNP panels with different densities

To evaluate the influence of SNP panels with different densities on the accuracy of genomic prediction of AHPND resistance of Litopenaeus vannamei, 26 full-sib families were infected with Vp_AHPND, and survival time of 686 individuals were recorded. A total of 242 individuals were genotyped by the liquid chip "Yellow Sea Chip No.1" (55.0 K SNP), and the genetic parameters of survival time after Vp_AHPND infection were estimated using the A, G and H relationship matrices. Eight low-density SNP panels (40.0 K, 30.0 K, 20.0 K, 10.0 K, 5.0 K, 1.0 K, 0.5 K, 0.1 K) were generated based on the 55.0 K SNP panel. GBLUP and ssGBLUP methods were used to predict the GEBV of survival time, and prediction accuracy was calculated by cross-validation method and compared with BLUP method. The estimated heritabilities of survival time after Vp_AHPND infection were high (0.68-0.79). At 55.0 K SNP density, the prediction accuracies obtained by BLUP, GBLUP and ssGBLUP were 0.424, 0.450 and 0.452, respectively, in the data set with 242 genotyped individuals (G242). The accuracy of GBLUP and ssGBLUP was 6.13% and 6.60% higher than BLUP, respectively. For the data set with 686 phenotyped individuals (P686), the prediction accuracies obtained by BLUP and ssGBLUP methods were 0.510 and 0.535, respectively. ssGBLUP showed 4.90% greater accuracy than BLUP. For 8 low-density SNP panels, genomic prediction accuracies were all low (1.1%-1.8%) in G242 and P686 data sets when the SNP density was greater than or equal to 10.0 K. With the decrease of SNP density since 10.0 K, the accuracy of genomic prediction also decreased in the two data sets, The density of 5.0 K decreased by 0.6%-2.6%, 1.0 K decreased by 5.8% -11.0%, 0.5 K decreased by 11.4%-17.2%, and 0.1 K decreased by 38.8%-41.6%. The correlation coefficients of genomic relationship coefficient and GEBV obtained using 10.0 K and 55.0 K SNP panels were all higher than 0.99, which indicates that the relationship between sibling individuals and their GEBVs can be accurately predicted by using the 10.0 K SNP panel. The results showed that the 10.0 K SNP panel could replace 55.0 K SNP panel to perform genetic evaluation for survival time after Vp_AHPND infection,which provided a reference for the design of low density SNP chips.