Elucidating the relationship between heterozygosity and fitness in a natural vertebrate population

在自然种群中，许多重要的适合性性状，包括抗寄生虫性、存活率和繁殖成功，往往与杂合性相关。在有文献记载的地方，这种杂合性适应相关性(HFC)有可能影响病原体与其宿主之间的相互作用和配偶选择的进化。然而，由于大多数研究只使用了大约10个微卫星标记，我们还不知道两种可能的机制中哪一种最重要，也不知道涉及的基因类型。幸运的是，下一代测序技术允许开发针对基因的单核苷酸多态(SNPs)，如果在一个可以收集高质量适合度衡量标准的物种中进行筛选，应该第一次允许在适合度和数千个基因的杂合性之间建立直接联系。我将利用这样一个系统，南极毛海豹(Arctocephalus Gazella)，在这个系统中，一项非常详细的长期研究已经揭示了大量HFC。通过在1500只雌性海豹中筛选6000个SNP，并获得详细的健康数据，我将区分两个提出的解释HFC的主要假设。在一般效应假说下，HFC被归因于近交抑制，标记杂合度提供了个体近交系数f的替代度量。在这里，额外的标记将改善f的估计，适合度与平均标记杂合度之间的关系将得到加强。在另一种局部效应模型下，调用单个标记和经历平衡选择的基因之间的偶然性链接，基因座之间的杂合性是不相关的，因此如果有什么不同的话，更多的标记将降低HFC强度，因为任何一个标记的贡献逐渐被稀释。在实践中，即使涉及近亲繁殖抑制，局部效应也可能存在，但就像主要机制一样，这些影响很少被理解。例如，潜在的基因是不同的，还是主要与免疫或生长有关？为了探索这些和相关的问题，通过与狗的基因组进行比较而确定的特定基因类别中的SNPs将被单独分析，并作为单倍型与适应性相关联。然后，通过构建第一个海洋哺乳动物连锁图谱，并通过与狗的比较基因组学来确定涉及哪些基因组区域以及它们包含哪些特定基因，将对局部效应进行精细绘制。由此产生的超过9000000个SNP基因型的数据集将提供一个前所未有的窗口，了解遗传变异性如何影响自然哺乳动物群体中的关键适应特征。

Many important fitness traits including parasite resistance, survivorship and reproductive success often correlate with heterozygosity in natural populations. Where documented, such heterozygosity fitness correlations (HFCs) have the potential to influence interactions between pathogens and their hosts and the evolution of mate choice. However, because most studies use only around ten microsatellite markers, we do not yet know which of two possible mechanisms is most important nor the types of gene involved. Fortunately, Next Generation Sequencing technologies allow the development of gene-targeted Single Nucleotide Polymorphisms (SNPs) which, if screened in a species where high-quality fitness measures can be gathered, should for the first time allow direct links to be made between fitness and the heterozygosity of literally thousands of genes. I will exploit just such a system, the Antarctic fur seal (Arctocephalus gazella), in which an exceptionally detailed long term study has already revealed HFCs for numerous traits.By screening 6000 SNPs in 1500 female seals for which detailed fitness data are available, I will distinguish between two primary hypotheses proposed to explain HFCs. Under the general effects hypothesis, HFCs are ascribed to inbreeding depression, with marker heterozygosity providing a surrogate measure of an individual inbreeding coefficient f. Here, additional markers should improve the estimate of f and the relationship between fitness and average marker heterozygosity will strengthen. Under the alternative local effect model, which invokes chance linkage between individual markers and genes experiencing balancing selection, heterozygosity is uncorrelated among loci such that more markers will if anything reduce HFC strength as the contribution of any one marker becomes progressively diluted.In practice, local effects are likely to be present even if inbreeding depression is involved, but as with the primary mechanism these are poorly understood. For example, are the underlying genes diverse or mostly related to immunity or growth? To explore these and related questions, SNPs targeted within specific classes of genes identified by comparison with the dog genome will be analysed individually and as haplotypes for associations with fitness. Local effects will then be fine-mapped, by constructing the first marine mammal linkage map and through comparative genomics with the dog, to determine which genomic regions are involved and what specific genes they contain. The resulting dataset of over 9000000 SNP genotypes will thereby provide an unprecedented window on how genetic variability impacts key fitness traits in a natural mammalian population.