Data from: Genomic predictions and genome-wide association study of resistance against Piscirickettsia salmonis in coho salmon (Oncorhynchus kisutch) using ddRAD sequencing

Piscirickettsia salmonis is one of the main infectious diseases affecting coho salmon (Oncorhynchus kisutch) farming, and current treatments have been ineffective for the control of this disease. Genetic improvement for P. salmonis resistance has been proposed as a feasible alternative for the control of this infectious disease in farmed fish. Genotyping by sequencing (GBS) strategies allow genotyping of hundreds of individuals with thousands of single nucleotide polymorphisms (SNPs), which can be used to perform genome wide association studies (GWAS) and predict genetic values using genome-wide information. We used double-digest restriction-site associated DNA (ddRAD) sequencing to dissect the genetic architecture of resistance against P. salmonis in a farmed coho salmon population and to identify molecular markers associated with the trait. We also evaluated genomic selection (GS) models in order to determine the potential to accelerate the genetic improvement of this trait by means of using genome-wide molecular information. A total of 764 individuals from 33 full-sib families (17 highly resistant and 16 highly susceptible) were experimentally challenged against P. salmonis and their genotypes were assayed using ddRAD sequencing. A total of 9,389 SNPs markers were identified in the population. These markers were used to test genomic selection models and compare different GWAS methodologies for resistance measured as day of death (DD) and binary survival (BIN). Genomic selection models showed higher accuracies than the traditional pedigree-based best linear unbiased prediction (PBLUP) method, for both DD and BIN. The models showed an improvement of up to 95% and 155% respectively over PBLUP. One SNP related with B-cell development was identified as a potential functional candidate associated with resistance to P. salmonis defined as DD.

杀鲑立克次体（Piscirickettsia salmonis）是影响银大麻哈鱼（Oncorhynchus kisutch）养殖的主要传染性病原之一，当前针对该病害的防治手段均收效甚微。通过遗传改良提升养殖鱼类对杀鲑立克次体的抗性，被认为是管控该传染病的可行替代方案。测序分型（Genotyping by Sequencing, GBS）技术可实现对数百个个体的数千个单核苷酸多态性（Single Nucleotide Polymorphisms, SNPs）位点进行分型，该技术可用于开展全基因组关联分析（Genome-Wide Association Studies, GWAS），并基于全基因组信息预测遗传育种值。本研究采用双酶切限制性位点相关DNA测序（Double-digest Restriction-site Associated DNA sequencing, ddRAD）技术，解析了养殖银大麻哈鱼种群对杀鲑立克次体的抗性遗传结构，并筛选与该抗性性状相关的分子标记。同时，本研究评估了基因组选择（Genomic Selection, GS）模型，以探究利用全基因组分子信息加速该性状遗传改良的潜力。本研究对来自33个全同胞家系（17个高抗家系、16个高感家系）的共计764尾个体开展了杀鲑立克次体人工感染试验，并通过ddRAD测序完成了其基因型分型检测，最终在该种群中鉴定得到9389个SNP标记。利用上述标记，本研究针对以死亡天数（Day of Death, DD）和二元存活性状（Binary Survival, BIN）量化的抗性性状，开展了基因组选择模型测试，并对比了不同GWAS分析方法的效果。结果显示，相较于传统的基于系谱的最佳线性无偏预测（Pedigree-based Best Linear Unbiased Prediction, PBLUP）方法，基因组选择模型在DD和BIN两个性状上均展现出更高的预测精度，分别较PBLUP提升最高可达95%和155%。本研究还鉴定到一个与B细胞发育相关的SNP标记，该标记可作为以DD量化的杀鲑立克次体抗性的潜在功能候选标记。