A conceptual framework for the spatial analysis of landscape genetic data
A conceptual framework for the spatial analysis of landscape genetic data
复制标题
景观遗传数据空间分析的概念框架
DOI：
--
复制
发表时间：
2013
影响因子：
2.2
通讯作者：
M. Fortin
中科院分区：
文献类型：
--
作者：
H. Wagner;M. Fortin
了解景观异质性如何限制基因流动和适应性遗传变异的传播对于当前全球变化下的生物保护具有重要意义。然而，种群遗传学、景观生态学和空间统计学的整合在概念和方法层面上仍然是一个跨学科的挑战。我们提出了一个概念性的框架，将遗传变异的空间分布与环境空间异质性所调控的基因流动和适应过程联系起来，同时明确考虑景观，生物及其基因的时空动态。在选择合适的分析方法时，需要考虑多重过程的影响和群体遗传数据的性质。我们的框架涉及关键景观遗传学问题的四个层次的分析：（i）基于节点的方法，从当地的站点特征的采样位置（节点）的等位基因的空间分布模型，这些方法是适合于模拟适应性遗传变异，同时占空间自相关的存在。(ii)链接为基础的方法，这两个补丁（链接）之间的基因流的概率模型和中性分子标记数据景观异质性，这些方法是适合中性遗传变异建模，但受到推理问题，这可能会减轻减少链接的基础上网络模型的人口。(iii)邻域为基础的方法，模型的连接焦点补丁与所有其他补丁在其本地邻域，这些方法提供了一个链接到集合种群理论和景观连接建模，并可能允许集成的节点和链接为基础的信息，但在景观遗传学的应用仍然有限。(iv)边界为基础的方法，划定遗传同质的人口和推断遗传边界的位置，这些方法是适合于测试的障碍效应的景观特征的假设测试框架。我们的结论是，电源检测景观异质性的遗传变异的空间分布的影响，可以增加明确考虑的基本假设和选择一个适当的分析方法，这取决于研究问题。
Understanding how landscape heterogeneity constrains gene flow and the spread of adaptive genetic variation is important for biological conservation given current global change. However, the integration of population genetics, landscape ecology and spatial statistics remains an interdisciplinary challenge at the levels of concepts and methods. We present a conceptual framework to relate the spatial distribution of genetic variation to the processes of gene flow and adaptation as regulated by spatial heterogeneity of the environment, while explicitly considering the spatial and temporal dynamics of landscapes, organisms and their genes. When selecting the appropriate analytical methods, it is necessary to consider the effects of multiple processes and the nature of population genetic data. Our framework relates key landscape genetics questions to four levels of analysis: (i) node-based methods, which model the spatial distribution of alleles at sampling locations (nodes) from local site characteristics; these methods are suitable for modeling adaptive genetic variation while accounting for the presence of spatial autocorrelation. (ii) Link-based methods, which model the probability of gene flow between two patches (link) and relate neutral molecular marker data to landscape heterogeneity; these methods are suitable for modeling neutral genetic variation but are subject to inferential problems, which may be alleviated by reducing links based on a network model of the population. (iii) Neighborhood-based methods, which model the connectivity of a focal patch with all other patches in its local neighborhood; these methods provide a link to metapopulation theory and landscape connectivity modeling and may allow the integration of node- and link-based information, but applications in landscape genetics are still limited. (iv) Boundary-based methods, which delineate genetically homogeneous populations and infer the location of genetic boundaries; these methods are suitable for testing for barrier effects of landscape features in a hypothesis-testing framework. We conclude that the power to detect the effect of landscape heterogeneity on the spatial distribution of genetic variation can be increased by explicit consideration of underlying assumptions and choice of an appropriate analytical approach depending on the research question.
数量性状中的距离隔离。
影响因子：
3.3
作者：
Lande,R
通讯作者：
Lande,R