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会议综述:揭示适应性变化的遗传基础:景观基因组学与理论种群遗传学的交叉点。

Meeting review. Uncovering the genetic basis of adaptive change: on the intersection of landscape genomics and theoretical population genetics.

出版信息

Mol Ecol. 2013 Jul;22(14):3659-65. doi: 10.1111/mec.12352.

Abstract

A workshop recently held at the École Polytechnique Fédérale de Lausanne (EPFL, Switzerland) was dedicated to understanding the genetic basis of adaptive change, taking stock of the different approaches developed in theoretical population genetics and landscape genomics and bringing together knowledge accumulated in both research fields. Indeed, an important challenge in theoretical population genetics is to incorporate effects of demographic history and population structure. But important design problems (e.g. focus on populations as units, focus on hard selective sweeps, no hypothesis-based framework in the design of the statistical tests) reduce their capability of detecting adaptive genetic variation. In parallel, landscape genomics offers a solution to several of these problems and provides a number of advantages (e.g. fast computation, landscape heterogeneity integration). But the approach makes several implicit assumptions that should be carefully considered (e.g. selection has had enough time to create a functional relationship between the allele distribution and the environmental variable, or this functional relationship is assumed to be constant). To address the respective strengths and weaknesses mentioned above, the workshop brought together a panel of experts from both disciplines to present their work and discuss the relevance of combining these approaches, possibly resulting in a joint software solution in the future.

摘要

一个研讨会最近在瑞士洛桑联邦理工学院(EPFL)举行,致力于理解适应性变化的遗传基础,评估理论种群遗传学和景观基因组学中不同方法的发展,并汇集两个研究领域积累的知识。事实上,理论种群遗传学的一个重要挑战是纳入人口历史和结构的影响。但是,重要的设计问题(例如,将关注点放在群体作为单位上、关注硬选择骤变、在统计测试的设计中没有基于假设的框架)降低了它们检测适应性遗传变异的能力。同时,景观基因组学为解决其中的一些问题提供了一种解决方案,并具有许多优势(例如,快速计算、景观异质性整合)。但是,该方法做出了几个应仔细考虑的隐含假设(例如,选择已经有足够的时间在等位基因分布和环境变量之间创建功能关系,或者假设这种功能关系是恒定的)。为了解决上述各自的优缺点,研讨会召集了来自两个学科的专家小组,介绍他们的工作并讨论结合这些方法的相关性,未来可能会产生一个联合软件解决方案。

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