Population genomics of the killer whale; SNP discovery towards the assessment of population structure at functional genes

自从20世纪70年代加拿大的一个研究项目首次展示了如何使用照片来识别和跟踪单个鲸鱼的联系和运动，如何随着时间的推移跟踪区域虎鲸种群以来，越来越明显的是，这个物种为增进我们对关键进化和生态过程的理解提供了巨大的潜力。尽管它们有巨大的远距离分散的潜力，社会群体在一个季节旅行数千公里，但已识别的相关个体群体(划分为20-50个个体的社会单位)在小地理范围内的中性标记上进行了遗传分化。明显的机制是对当地或季节性栖息地资源的依赖，特别是对猎物资源的依赖。通过这种方式，可以根据逆流鲑鱼猎物的迁徙方向(迁徙到河口的北部或南部)将食肉种群分开，即使在共生关系中，食肉种群也可以与以海洋哺乳动物为食的种群分开。有一种与地理距离相关的分化模式(如许多物种所见)，但仅在一种生态型内。生态型之间的区别是基于生物因素(特别是与觅食和社会结构相关的行为)。虽然区域种群的有效规模可能很小，但有时存在可能与资源开发有关的物理差异(如各种其他斑蝶物种，特别是与口腔形态有关的物种)，这表明了当地的适应。在这项研究中，我们将识别明显处于选择中的基因，并尽可能将它们与生态特征，特别是不同生态型种群生活史的已知方面联系起来。一项关键的成果将是一套广泛的SNP标记，其中一些被确定为可能正在选择中，将用于广泛的人口筛查计划的后续研究。本研究将根据这些SNP标记进行初步评估，作为SNP发现过程的一部分。这是由于所选择的方法使之成为可能。第一步将是对一个样本的全基因组进行测序，以达到足以用作参考支架的质量水平(将通过商业提供商Eurofins MWG/OPON完成)。这将被用于促进RAD标签测序工作和相关的生物信息学(将在CGR利物浦的合作伙伴尼尔·霍尔的监督下进行)。然后，达勒姆的PI将与霍尔教授合作并在RA的协助下对RAD标签数据进行分析。RAD标签序列将允许识别SNP标记，参考基因组将允许识别它们在虎鲸基因组中的位置和联系。对来自5个种群的最初150头鲸鱼的分析将提供用于选择的信号的初步数据和对分化模式的高分辨率评估。将应用贝叶斯和多元回归方法，在环境变量的背景下解释遗传变异，并评估哪些变量解释了遗传变异的最大比例。综上所述，这些分析将促进我们对物种内部和物种之间产生生物多样性的进化过程的理解，促进更有效的生物多样性保护计划，并为进一步推进这些目标的未来研究提供原材料。

Since a Canadian research project in the 1970s first showed how the regional killer whale population could be tracked over time using photographs to identify and follow the associations and movement of individual whales, it has become increasingly apparent that this species offers great potential for advancing our understanding of key evolutionary and ecological processes. Despite their tremendous potential for long-distance dispersion, with social groups travelling 1000s of km in a season, identified populations of associating individuals (divided into social units of 20-50 individuals) are genetically differentiated at neutral markers over small geographic scales. The apparent mechanism is dependence on local or seasonal habitat resources, and in particular, prey resources. In this way picivorous populations can be separated by the direction of migration in their anadromous salmonid prey (migrating north or south of an estuary), and picivorous populations can be isolated from marine-mammal-eating populations even in sympatry. There is a pattern of differentiation associated with geographic distance (as seen for many species), but only within an ecotype. Differentiation among ecotypes is based on biological factors (especially behaviour associated with foraging and social structure). Although the effective size of regional populations is likely small, there are sometimes physical differences that may be associated with resource exploitation (as seen in various other delphinid species, especially associated with buccal morphology), suggesting local adaptation. In this study we will identify genes that are apparently under selection, and associate them where possible with ecological characteristics, especially known aspect of the life history of the different ecotype populations. A key deliverable will be an extensive set of SNP markers, with some identified as likely under selection, to be applied in a follow-on study to an extensive program of population screening. A preliminary assessment based on these SNP markers will be undertaken in the current study as part of the SNP discovery process. This is made possible by the chosen methodology. The initial step will be the sequencing of the full genome for one sample to a quality level sufficient to use as a reference scaffold (to be done through the commercial provider, Eurofins MWG/ Operon). This will then be used to facilitate the RAD-Tag sequencing work and the associated bio-informatics (to be undertaken under the supervision of partner Neil Hall at CGR Liverpool). The RAD-Tag data will then be analysed by the PI in Durham in collaboration with Prof. Hall and with the assistance of the RA. The RAD-Tag sequences will permit the identification of SNP markers, and the reference genome would permit identification of their location and linkage within the killer whale genome. Analysis of an initial 150 whales from 5 populations will provide the preliminary data on signals for selection and a high-resolution assessment of patterns of differentiation. Bayesian and multiple regression methods will be applied to allow interpretation of genetic variation in the context of environmental variables, and to assess which variables explain the largest proportion of the genetic variance. Taken together these analyses will advance our understanding of the evolutionary processes that generate biodiversity within and among species, facilitate more effective programs of biodiversity conservation, and provide the raw material for future studies that will advance these objectives further.