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

太平洋牡蛎（Crassostrea gigas）是世界上最重要的水产养殖品种之一，年产量为600亿吨。由于其高生长速度和对各种环境的耐受性，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——已经成为巨牡蛎养殖的主要问题，经常给养殖种群造成巨大损失，这就是所谓的“夏季死亡综合征”。病毒爆发对牡蛎生产的负面影响因一种致病性更强的形式的出现而恶化；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了有限的成功，但最近的研究表明，牡蛎对该病毒的抵抗力存在遗传变异。虽然存在许多用于巨噬线虫的基因组工具和资源，但目前还没有适合于详细研究复杂性状（如抗病性）遗传学的高密度基因分型平台。单核苷酸多态性（SNP）阵列广泛应用于养殖陆生牲畜和鱼类，用于研究重要经济性状的遗传控制。遗传标记信息可用于预测哪些动物适合进行育种计划以改善这些性状。此外，这些SNP阵列允许对种群多样性进行管理，并对感兴趣的物种进行进化遗传研究。因此，拟议项目的两个主要目标是；首先，开发并测试了首个牡蛎高密度SNP基因分型阵列；其次，量化牡蛎对疱疹病毒抗性的遗传变异，并确定这种变异是否包括主要影响的位点。第一个目标将通过对大量牡蛎的基因组进行测序，并从序列数据中挖掘snp来实现。SNP数据将用于开发一个微阵列，其中包含分散在牡蛎基因组中的约50,000个个体SNP分析。第二个目标将通过杂交从根西岛的一个牡蛎生产商那里获得的30只亲本牡蛎，并用校准剂量的微型疱疹病毒挑战后代来实现。然后将采集牡蛎样本，用于估计每只牡蛎的感染程度，并提取DNA。该DNA将使用新的SNP阵列进行基因分型，并分析全基因组标记数据，以确定病毒抗性的变异有多少是遗传的，并绘制牡蛎基因组中的任何主要抗性位点。从这个项目的结果来看，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抗性或易感性。这些信息可以纳入选择性育种计划，以帮助解决这一主要疾病威胁。通过绘制影响牡蛎基因组抗性的基因位点，可以在未来的项目中鉴定和研究重要的抗性基因。此外，所开发的SNP阵列工具将在牡蛎遗传多样性管理或牡蛎物种之间的区分方面具有广泛的应用。作为该项目的最终成果，我们将鼓励在比较不同野生牡蛎种群的保护或生态遗传学方面进行合作研究；我们预计从这个项目中有多余的阵列可用，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.