Investigation of Host Genetic Resistance to Oyster Herpes Virus using a High Density SNP Array

太平洋牡蛎（Crassostreagigas）是世界上最重要的水产养殖品种之一，年产量超过6亿吨。由于其高生长速率和广泛的环境耐受性，C。吉格斯在世界上大多数地区都有养殖，包括英国。然而，牡蛎疱疹病毒（OsHV-1）-一种双链DNA病毒-已成为C.千兆种的养殖，往往造成巨大的损失，被称为“夏季死亡综合症”的养殖种群。病毒爆发对牡蛎生产的负面影响因出现更具致病性的形式而恶化;即OsHV-1微变体。虽然限制受感染种群的流动和其他生物安全措施在控制疫情方面取得的成功有限，但最近的研究表明，牡蛎对病毒的抵抗力存在遗传变异。虽然有许多基因组工具和资源用于C。尽管如此，目前还没有一个高密度的基因分型平台适合于对复杂性状的遗传学进行详细研究，例如抗病性。单核苷酸多态性（SNP）基因芯片技术已广泛应用于陆地养殖畜禽和鱼类重要经济性状的遗传控制研究。遗传标记信息可用于预测哪些动物适合育种计划以改善这些性状。此外，这些SNP阵列允许管理群体的多样性，以及对感兴趣的物种进行进化遗传学研究。因此，拟议项目的两个主要目标是：第一，开发和测试第一个高密度SNP基因分型阵列的牡蛎和;第二，量化的遗传变异的牡蛎疱疹病毒的抗性，并确定这种变化是否包括基因座的主要影响。第一个目标将通过对大量牡蛎的基因组进行测序并挖掘SNPs的序列数据来实现。SNP数据将用于开发一种微阵列，其中包含分布在牡蛎基因组中的约50，000个SNP检测。第二个目标将通过杂交30个来自根西岛牡蛎生产商的个体亲本牡蛎来实现，并用校准剂量的微型疱疹病毒对后代进行攻击。然后将采集牡蛎样本，用于估计每只牡蛎的感染水平，并提取DNA。该DNA将使用新的SNP阵列进行基因分型，并将分析全基因组标记数据，以确定病毒抗性的遗传变异程度，并绘制牡蛎基因组内的任何主要抗性位点。根据该项目的结果，将有可能使用遗传标记来预测单个牡蛎是否可能对疱疹病毒具有抵抗力或易感性。这些信息可以被纳入选择性育种计划，以帮助解决这一重大疾病的威胁。通过对牡蛎基因组中影响抗性的位点进行定位，可以在未来的项目中鉴定和研究重要的抗性基因。此外，开发的SNP阵列工具将在牡蛎遗传学方面具有广泛的应用，包括管理遗传多样性或区分牡蛎物种。作为该项目的最终成果，我们将鼓励在保护或生态遗传学方面进行合作研究，比较不同的野生牡蛎种群;我们预计该项目将提供多余的阵列，我们将免费提供给感兴趣的合作者。

Pacific oyster (Crassostrea gigas) is one of the most important aquaculture species in the world, with an annual production of >0.6 billion tonnes. Due to its high growth rate and tolerance of a wide range of environments, C. gigas is farmed in most regions of the world, including the UK. However, Oyster herpes virus (OsHV-1) - a double-stranded DNA virus - has become the primary concern for C. gigas farming, often causing huge losses to farmed stocks in what is known as 'summer mortality syndrome'. The negative impact of the viral outbreaks on oyster production has been worsened by the emergence of a more pathogenic form; namely OsHV-1 micro variant. While restricting the movement of infected stocks and other biosecurity measures have had limited success in controlling outbreaks, recent studies suggest that there is genetic variation in the resistance of the oyster to the virus. While many genomic tools and resources exist for C. gigas, there is not yet a high density genotyping platform suitable for detailed studies into the genetics of complex traits, such as disease resistance. Single nucleotide polymorphism (SNP) arrays are widely used in farmed terrestrial livestock and fish to research the genetic control of economically important traits. The genetic marker information can be applied to predict which animals are suitable for breeding programs to improve these traits. Additionally, these SNP arrays allow management of the diversity of population, and evolutionary genetic studies in species of interest. Therefore, the two major aims of the proposed project are; firstly, to develop and test the first high-density SNP genotyping array for oysters and; secondly, to quantify the genetic variation in the resistance of oysters to herpes virus and determine whether this variation includes loci of major effect. The first aim will be achieved by sequencing the genomes of a wide panel of oysters and mining the sequence data for SNPs. The SNP data will be used to develop a microarray containing approximately 50,000 individual SNP assays dispersed across the oyster genome. The second aim will be achieved by crossing 30 individual parent oysters taken from an oyster producer in Guernsey and challenging the offspring with a calibrated dose of the micro form of herpes virus. Samples of the oysters will then be taken and used for estimating the level of infection for each oyster and also for extracting DNA. This DNA will be genotyped using the new SNP array and the genome-wide marker data will be analysed to determine how much variation in viral resistance is genetic, and to map any major resistance loci within the oyster genome. From the results of this project, it will be possible to use genetic markers to predict whether an individual oyster is likely to be resistant or susceptible to herpes virus. This information can be incorporated into selective breeding programs to help tackle this major disease threat. By mapping the loci affecting resistance to the genome of the oyster, important resistance genes may be identified and studied in future projects. Additionally, the SNP array tool developed will have wide applications for oyster genetics, including managing genetic diversity or differentiating between oyster species. As a final output from the project, we will encourage collaborative research in conservation or ecological genetics comparing different wild oyster populations; we anticipate having excess arrays available from this project and we will offer these at no cost to interested collaborators.