Research on the genomics of adaptation is rapidly changing. In the last few decades, progress in this area has been driven by methodological advances, not only in the way increasingly large amounts of molecular data are generated (e.g. with high-throughput sequencing), but also in the way these data are analysed. This includes a growing appreciation and quantitative treatment of covariation among units within the same data type (e.g. genes) or across data types (e.g. genes and phenotypes). The development and adoption of more and more integrative tools have resulted in richer and more interesting empirical work. This special issue - comprising methodological, empirical, and review papers - aims to capture a 'snapshot' of this rapidly evolving field. We discuss in particular three important themes in the study of adaptation: the genetic architecture of adaptive variation, protein-coding and regulatory changes, and parallel evolution. We highlight how more traditional key themes in the study of genetic architecture (e.g. the number of loci underlying adaptive traits and the distribution of their effects) are now being complemented by other factors (e.g. how patterns of linkage and number of loci interact to affect the ability to adapt). Similarly, apart from addressing the relative importance of protein-coding and regulatory changes, we now have the tools to look in-depth at specific types of regulatory variation to gain a clearer picture of regulatory networks. Finally, parallel evolution has always been central to the study of adaptation, but now we are often able to address the question of whether - and to what extent - parallelism at the organismal or phenotypic level is matched by parallelism at the genetic level. Perhaps most importantly, we can now determine what mechanisms are driving parallelism (or lack thereof) across levels of biological organization. All these recent methodological developments open up new directions for future studies of adaptive changes across traits, levels of biological organization, demographic contexts and time scales.

中文翻译：

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捕捉快速发展的适应研究。

对适应基因组学的研究正在迅速变化。在过去的几十年中，该领域的进步受到方法学进步的推动，不仅是在生成越来越多的分子数据的方式上（例如使用高通量测序），而且在分析这些数据的方式上。这包括对同一数据类型（例如基因）内或跨数据类型（例如基因和表型）的单位之间的协变的日益重视和定量处理。越来越多的集成工具的开发和采用导致了更丰富和更有趣的实证工作。本期特刊——包括方法论、实证和评论论文——旨在捕捉这个快速发展领域的“快照”。我们特别讨论了适应研究中的三个重要主题：适应性变异、蛋白质编码和调节变化以及平行进化的遗传结构。我们强调了遗传结构研究中更传统的关键主题（例如潜在适应性特征的基因座数量及其影响的分布）现在如何得到其他因素的补充（例如连锁模式和基因座数量如何相互作用以影响适应能力）。同样，除了解决蛋白质编码和监管变化的相对重要性之外，我们现在还有工具可以深入研究特定类型的监管变异，从而更清晰地了解监管网络。最后，平行进化一直是适应研究的核心，但现在我们通常能够解决以下问题：生物体或表型水平的平行性是否与基因水平的平行性相匹配，以及在何种程度上。也许最重要的是，我们现在可以确定是什么机制在生物组织的各个层面上推动了并行性（或缺乏并行性）。所有这些最近的方法学发展为未来研究跨性状、生物组织水平、人口背景和时间尺度的适应性变化开辟了新的方向。