Spatial ecological genomics of free-ranging Great tits

基因组学革命现在为研究人员提供了关于有机体遗传结构的海量原始数据。这些信息通过识别基因及其功能，通过阐明基因结构及其进化，推动了许多进步，特别是在医学和进化生物学领域。基因组数据集的大小和范围需要专门的专业知识来分析。事实上，由于基因组数据的复杂性和数量，生物信息学的新的定量学科已经出现，以应对涉及对数据提出问题的分析挑战。直到最近几年，基因组数据只可用于模式生物；然而，由于技术进步，这种情况正在迅速改变，一旦基因组数据超出基因组学的范围，基因组数据改善我们对问题的理解的潜在力量现在得到了很好的认识，显然需要跨学科的企业。DNA测序不再是限制更传统的基因组学科以外的基因组分析的主要因素；相反，跨学科的基因组专业知识的转移是限制的主要因素。鉴于需要跨学科的专业知识，我们建议使用生物信息学方法来回答有关自由活动的大山雀种群遗传结构的问题。我们尤其感兴趣的是，就适应的可能性及其对人口动态的影响而言，我们有兴趣了解人口对污染强度的反应。大山雀已经被证明在非常精细的空间尺度上对环境选择做出反应；然而，我们对人类活动如何影响自然种群进化的潜力知之甚少，如果它们确实可以进化的话。如果污染水平为大山雀创造了不适合的栖息地，那么它们也可能影响种群结构。人口密度往往与污染水平的增加有关，而大山雀是常见的城市鸟类。如果低污染地点是个体的净生产者，高污染地点是移民的净接受者，那么尽管城市中持续出现稳定的种群，但更准确地说，高污染区域可能是本质上不可持续的种群，并补充来自高质量栖息地的个体。要识别正在选择的基因组区域并描述高分辨率种群结构，需要高密度基因组数据，这些数据最近才可用于非模式物种，并需要适当分析这些数据的专业知识。如果要将这些有价值的方法与生态学和进化论相结合，这种专业知识的专业性质需要与生物信息学家密切合作。这四个月的帖子将资助一名博士后研究员在世界领先的生物信息学研究小组之一主持的一次交流。通过这样做，我们希望开始弥合与生态和基因组学整合相关的挑战，并启动将持续到未来的长期合作。

The genomics revolution now provides researchers with vast amounts of raw data about the genetic architecture of organisms. This information is fuelling numerous advances, particularly in medicine and evolutionary biology, by identifying genes and their function and by elucidating gene structures and their evolution. The size and scope of genomic data sets require specialised expertise to analyse. Indeed, due to the complexity and volume of genomics data, the new quantitative discipline of bionformatics has arisen to deal with the analytical challenges involved with asking questions of the data. Until very recent years, genomic data was only available for model organisms; however, due to technological advances, this is quickly changing and the potential power of genomic data to refine our understanding of questions once that to be outside the scope of genomics is now well recognised and it is clear that cross-disciplinary enterprise is needed. DNA sequencing is no longer the primary factor limiting genomic analyses outside of the more traditional genomic disciplines; rather the transfer of genomic expertise across disciplines is. Within light of the need for cross-disciplinary expertise we propose to use bioinformatic approaches to answers question about the population genetic structure of a free-ranging population of great tits. Particularly, we are interested in understanding how populations respond to intensity of pollution in terms of the potential for adaptation and its impact on population dynamics. Great tits have been shown to respond to environmental selection at very fine spatial scales; however, we know very little about how human activities affect the potential for natural populations to evolve, if indeed they can evolve at all. Pollution levels may also affect population structure if they create unsuitable habitat for great tits. Human density is often associated with increased pollution levels and great tits are common city birds. If low pollution sites are net producers of individuals and high pollution sites net recipients of immigrants then despite the on-going appearance of stable populations in cities high pollution areas may more accurately be intrinsically unsustainable populations supplemented by individuals from high quality habitat.To identify regions of the genome that are under selection and describe high resolution population structure requires high density genomic data, only recently available for non-model species and the expertise to appropriately analyse these data. The specialist nature of this expertise requires close collaboration with bioinformaticians if these valuable approaches are to be integrated with ecology and evolution. The four months post here will fund an exchange by a postdoctoral fellow to be hosted within one of the leading bioinformatics research groups in the world. By doing so we hope to begin to bridge the challenges associated with integrating ecology and genomics and initiate a long term collaboration that will continue into the future.