本研究旨在提供与太平洋白虾(凡纳滨对虾)的生长和白斑综合症病毒(WSSV)抗性性状相关的遗传参数的精确评估。这是通过控制WSSV攻击测定和五个性状的表型值分析来实现的:体重(BW),总长度(OL),体长(BL),尾长(TL),和感染后存活小时(HPI)。分析包括来自20个家庭的总共1017个人的测试数据,其中293人进行了全基因组重测序,获得18,137,179个高质量SNP位点。三种方法,包括基于谱系的最佳线性无偏预测(pBLUP),基因组最佳线性无偏预测(GBLUP),使用单步基因组BLUP(ssGBLUP)。与pBLUP模型相比,从GBLUP和ssGBLUP获得的生长相关性状的遗传力较低,而WSSV抗性的遗传力较高。GBLUP和ssGBLUP模型均显着提高了预测准确性。具体来说,GBLUP模型提高了BW的预测精度,OL,BL,TL,和HPI下降4.77%,21.93%,19.73%,19.34%,和63.44%,分别。同样,ssGBLUP模型将预测精度提高了10.07%,25.44%,25.72%,19.34%,和122.58%,分别。使用两种基因组预测模型,WSSV抗性性状表现出最显著的增强,其次是体型特征(例如,OL,BL,和TL),BW表现出最小的改善。此外,模型的选择对遗传和表型相关性的评估影响最小.各模型生长性状之间的遗传相关性范围为0.767至0.999,表明高水平的正相关。生长与WSSV抗性性状之间的遗传相关性范围为(-0.198)至(-0.019),表明负相关水平较低。这项研究确保了GBLUP和ssGBLUP模型在凡纳滨对虾生长和WSSV抗性的遗传参数估计方面优于pBLUP模型的显着优势,为进一步的育种计划奠定了基础。
The current study aimed to provide a precise assessment of the genetic parameters associated with growth and white spot syndrome virus (WSSV) resistance traits in Pacific white shrimp (Litopenaeus vannamei). This was achieved through a controlled WSSV challenge assay and the analysis of phenotypic values of five traits: body weight (BW), overall length (OL), body length (BL), tail length (TL), and survival hour post-infection (HPI). The analysis included test data from a total of 1017 individuals belonging to 20 families, of which 293 individuals underwent whole-genome resequencing, resulting in 18,137,179 high-quality SNP loci being obtained. Three methods, including pedigree-based best linear unbiased prediction (pBLUP), genomic best linear unbiased prediction (GBLUP), and single-step genomic BLUP (ssGBLUP) were utilized. Compared to the pBLUP model, the heritability of growth-related traits obtained from GBLUP and ssGBLUP was lower, whereas the heritability of WSSV resistance was higher. Both the GBLUP and ssGBLUP models significantly enhanced prediction accuracy. Specifically, the GBLUP model improved the prediction accuracy of BW, OL, BL, TL, and HPI by 4.77%, 21.93%, 19.73%, 19.34%, and 63.44%, respectively. Similarly, the ssGBLUP model improved prediction accuracy by 10.07%, 25.44%, 25.72%, 19.34%, and 122.58%, respectively. The WSSV resistance trait demonstrated the most substantial enhancement using both genomic prediction models, followed by body size traits (e.g., OL, BL, and TL), with BW showing the least improvement. Furthermore, the choice of models minimally impacted the assessment of genetic and phenotypic correlations. Genetic correlations among growth traits ranged from 0.767 to 0.999 across models, indicating high levels of positive correlations. Genetic correlations between growth and WSSV resistance traits ranged from (-0.198) to (-0.019), indicating low levels of negative correlations. This study assured significant advantages of the GBLUP and ssGBLUP models over the pBLUP model in the genetic parameter estimation of growth and WSSV resistance in L. vannamei, providing a foundation for further breeding programs.