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每日翻译20190530

已有 317 次阅读 2019-5-30 07:27 |个人分类:翻译作品|系统分类:科研笔记| 发育树, 单倍型网络, 种内谱系

#编者信息

熊荣川

明湖实验室

xiongrongchuan@126.com

http://blog.sciencenet.cn/u/Bearjazz

Intraspecific gene evolution cannot   always be represented by a bifurcating tree. Rather, population genealogies   are often multifurcated, descendant genes coexist with persistent ancestors   and recombination events produce reticulate relationships. Whereas traditional   phylogenetic methods assume bifurcating trees, several networking approaches   have recently been developed to estimate intraspecific genealogies that take   into account these population level phenomena.

During the past decade, the explosion of   molecular techniques has led to the accumulation of a considerable amount of   comparative genetic information at the population level. At the same time, recent   advances in population genetics theory, especially coalescent theory, have   generated powerful tools for the analysis of intraspecific data. These two developments   have converted intraspecific phylogenies into useful tools for testing a   variety of evolutionary and population genetic hypotheses. Several   phylogenetic methods, especially NETWORK (see Glossary) approaches, have been   developed to take advantage of the unique characteristics of intraspecific   data. In this article, we summarize some population genetics principles,   explain why networks are appropriate representations of intraspecific genetic   variation, describe and compare available methods and software for network   estimation, and give examples of their application

 

种内基因进化不总能用分叉树来表示。相反,种群谱系通常是多歧分叉的,后代基因与长寿的祖先共存,重组事件产生网状关系。传统的系统发育方法假设树是分叉的,最近已经开发出几种网络方法来估计种内谱系,将这些种群级别现象考虑进去。不是这些人口层面的现象。

在过去的十年中,分子技术的爆炸性发展导致了在种群水平上积累了大量的比较遗传信息。与此同时,群体遗传学理论的最新进展,特别是溯祖理论,为分析特定种内数据提供了强有力的工具。这两个进步已将种内系统发育转化为检验各种进化变异和种群遗传假说的有用工具。几种系统发育方法,特别是NETWORK(见词汇表)方法,已被开发出来,以利用种内特定数据的独特特征。在本文中,我们总结了一些群体遗传学原理,解释了为什么网络是种内遗传变异的适当表示,描述并比较了现有的网络估计方法和软件,并举例说明了它们的应用。

Posada D , Crandall K A . Intraspecific   gene genealogies: trees grafting into networks[J]. Trends in Ecology and   Evolution, 2001, 16(1):0-45.




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