PDF(Pubmed)
Abstract：
Saprolegnia oomycete infection causes serious economic losses and reduces fish health in aquaculture. Genomic selection based on thousands of DNA markers is a powerful tool to improve fish traits in selective breeding programs. Our goal was to develop a single nucleotide polymorphism (SNP) marker panel and to test its use in genomic selection for improved survival against Saprolegnia infection in European whitefish Coregonus lavaretus, the second most important farmed fish species in Finland. We used a double digest restriction site associated DNA (ddRAD) genotyping by sequencing method to produce a SNP panel, and we tested it analyzing data from a cohort of 1,335 fish, which were measured at different times for mortality to Saprolegnia oomycete infection and weight traits. We calculated the genetic relationship matrix (GRM) from the genome-wide genetic data, integrating it in multivariate mixed models used for the estimation of variance components and genomic breeding values (GEBVs), and to carry out Genome-Wide Association Studies for the presence of quantitative trait loci (QTL) affecting the phenotypes in analysis. We identified one major QTL on chromosome 6 affecting mortality to Saprolegnia infection, explaining 7.7% to 51.3% of genetic variance, and a QTL for weight on chromosome 4, explaining 1.8% to 5.4% of genetic variance. Heritability for mortality was 0.20 to 0.43 on the liability scale, and heritability for weight was 0.44 to 0.53. The QTL for mortality showed an additive allelic effect. We tested whether integrating the QTL for mortality as a fixed factor, together with a new GRM calculated excluding the QTL from the genetic data, would improve the accuracy estimation of GEBVs. This test was done through a cross-validation approach, which indicated that the inclusion of the QTL increased the mean accuracy of the GEBVs by 0.28 points, from 0.33 to 0.61, relative to the use of full GRM only. The area under the curve of the receiver-operator curve for mortality increased from 0.58 to 0.67 when the QTL was included in the model. The inclusion of the QTL as a fixed effect in the model increased the correlation between the GEBVs of early mortality with the late mortality, compared to a model that did not include the QTL. These results validate the usability of the produced SNP panel for genomic selection in European whitefish and highlight the opportunity for modeling QTLs in genomic evaluation of mortality due to Saprolegnia infection.
Saprolegnia infection causes serious economic losses and reduces fish health in aquaculture. We created a novel set of genetic markers to use in the selective breeding of European whitefish to reduce mortality due to the fungus. Using genetic markers, we estimated how much different fish traits are determined by genetic variation, and thus what potential traits have to be selected. We observed that resistance to infection was controlled by both a genetic variant with a major effect on mortality and by many other variants with a small effect distributed across the genome. We tested whether we could increase the precision of genomic breeding values used in the selective breeding by explicitly adding the major genetic variant to the analysis, and we observed an increase in precision in our results. We conclude that directly including information about the major genetic variant increases the precision of our predictions, rather than assuming that all genetic variants each explain a small amount of the genetic variation.
Saprolegnia infection causes serious economic losses and reduces fish health in aquaculture. We created a novel set of genetic markers to use in the selective breeding of European whitefish to reduce mortality due to the fungus. Using genetic markers, we estimated how much different fish traits are determined by genetic variation, and thus what potential traits have to be selected. We observed that resistance to infection was controlled by both a genetic variant with a major effect on mortality and by many other variants with a small effect distributed across the genome. We tested whether we could increase the precision of genomic breeding values used in the selective breeding by explicitly adding the major genetic variant to the analysis, and we observed an increase in precision in our results. We conclude that directly including information about the major genetic variant increases the precision of our predictions, rather than assuming that all genetic variants each explain a small amount of the genetic variation.
摘要：
卵菌感染会造成严重的经济损失，并降低水产养殖中的鱼类健康。基于数千个DNA标记的基因组选择是在选择性育种计划中改善鱼类性状的强大工具。我们的目标是开发单核苷酸多态性（SNP）标记组，并测试其在基因组选择中的用途，以改善欧洲白鱼Corregonuslavaretus的Seprolegnia感染的存活率，芬兰第二重要的养殖鱼类。我们使用双消化限制性位点相关DNA（ddRAD）基因分型测序（GBS）方法来产生SNP面板，我们测试了1335条鱼的数据，在不同时间测量卵菌感染的死亡率和体重特征。我们从全基因组遗传数据计算了遗传关系矩阵(GRM)，将其整合到用于估计方差分量和基因组育种值(GEBV)的多元混合模型中，并进行全基因组关联研究（GWAS），以分析影响表型的定量性状基因座（QTL）的存在。我们在6号染色体上确定了一个主要的QTL，它影响了受感染的死亡率，解释7.7-51.3%的遗传变异，和4号染色体上体重的QTL，解释了1.8-5.4％的遗传变异。死亡率的遗传力在责任表上为0.20-0.43，体重的遗传力为0.44-0.53。死亡率的QTL显示出加性等位基因效应。我们测试了是否将死亡率的QTL整合为固定因子，再加上从遗传数据中排除QTL的新GRM，将提高GEBV的精度估计。这个测试是通过交叉验证方法完成的，这表明包含QTL将GEBV的平均准确度提高了0.28点，从0.33到0.61，相对于仅使用完全GRM。当模型中包括QTL时，死亡率的接受者-操作者曲线的曲线下面积（AUC）从0.58增加到0.67。将QTL作为固定效应纳入模型增加了早期死亡率与晚期死亡率的GEBV之间的相关性，与不包括QTL的模型相比。这些结果验证了所产生的SNP面板在欧洲白鱼中进行基因组选择的可用性，并强调了在对由于Sprolegnia感染引起的死亡率的基因组评估中对QTL进行建模的机会。
