Stinchcombe J R, Hoekstra H E
Department of Ecology and Evolutionary Biology, Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario, Canada.
Heredity (Edinb). 2008 Feb;100(2):158-70. doi: 10.1038/sj.hdy.6800937. Epub 2007 Feb 21.
A central challenge in evolutionary biology is to identify genes underlying ecologically important traits and describe the fitness consequences of naturally occurring variation at these loci. To address this goal, several novel approaches have been developed, including 'population genomics,' where a large number of molecular markers are scored in individuals from different environments with the goal of identifying markers showing unusual patterns of variation, potentially due to selection at linked sites. Such approaches are appealing because of (1) the increasing ease of generating large numbers of genetic markers, (2) the ability to scan the genome without measuring phenotypes and (3) the simplicity of sampling individuals without knowledge of their breeding history. Although such approaches are inherently applicable to non-model systems, to date these studies have been limited in their ability to uncover functionally relevant genes. By contrast, quantitative genetics has a rich history, and more recently, quantitative trait locus (QTL) mapping has had some success in identifying genes underlying ecologically relevant variation even in novel systems. QTL mapping, however, requires (1) genetic markers that specifically differentiate parental forms, (2) a focus on a particular measurable phenotype and (3) controlled breeding and maintenance of large numbers of progeny. Here we present current advances and suggest future directions that take advantage of population genomics and quantitative genetic approaches - in both model and non-model systems. Specifically, we discuss advantages and limitations of each method and argue that a combination of the two provides a powerful approach to uncovering the molecular mechanisms responsible for adaptation.
进化生物学的一个核心挑战是识别对生态具有重要意义的性状背后的基因，并描述这些基因座上自然发生的变异所产生的适应性后果。为了实现这一目标，人们开发了几种新方法，包括“群体基因组学”，即在来自不同环境的个体中对大量分子标记进行评分，目的是识别显示出异常变异模式的标记，这可能是由于连锁位点的选择所致。这些方法之所以具有吸引力，是因为：（1）生成大量遗传标记越来越容易；（2）无需测量表型就能扫描基因组；（3）在不了解个体繁殖历史的情况下对个体进行采样很简单。尽管这些方法本质上适用于非模式生物系统，但迄今为止，这些研究在揭示功能相关基因方面的能力有限。相比之下，数量遗传学有着丰富的历史，最近，数量性状位点（QTL）定位在识别即使在新系统中与生态相关变异背后的基因方面也取得了一些成功。然而，QTL定位需要：（1）能够特异性区分亲本类型的遗传标记；（2）专注于特定的可测量表型；（3）对大量后代进行受控繁殖和饲养。在这里，我们介绍当前的进展，并提出利用群体基因组学和数量遗传学方法的未来方向——在模式生物和非模式生物系统中都是如此。具体来说，我们讨论了每种方法的优缺点，并认为将两者结合起来提供了一种强大的方法来揭示负责适应性的分子机制。
