Suppr超能文献

鉴定趋同特征的丛集:鸬鹚和海鸦的协同进化。

Identifying cliques of convergent characters: concerted evolution in the cormorants and shags.

机构信息

Institute of Fundamental Sciences, Massey University, Private Bag 11 222, Palmerston North 4442, New Zealand.

出版信息

Syst Biol. 2010 Jul;59(4):433-45. doi: 10.1093/sysbio/syq023. Epub 2010 May 14.

Abstract

A phylogenetic tree comprising clades with high bootstrap values or other strong measures of statistical support is usually interpreted as providing a good estimate of the true phylogeny. Convergent evolution acting on groups of characters in concert, however, can lead to highly supported but erroneous phylogenies. Identifying such groups of phylogenetically misleading characters is obviously desirable. Here we present a procedure that uses an independent data source to identify sets of characters that have undergone concerted convergent evolution. We examine the problematic case of the cormorants and shags, for which trees constructed using osteological and molecular characters both have strong statistical support and yet are fundamentally incongruent. We find that the osteological characters can be separated into those that fit the phylogenetic history implied by the molecular data set and those that do not. Moreover, these latter nonfitting osteological characters are internally consistent and form groups of mutually compatible characters or "cliques," which are significantly larger than cliques of shuffled characters. We suggest, therefore, that these cliques of characters are the result of similar selective pressures and are a signature of concerted convergence.

摘要

一个包含具有高自举值或其他强有力统计支持措施的分支的系统发育树通常被解释为提供了对真实系统发育的良好估计。然而,协同作用于字符组的趋同进化会导致高度支持但错误的系统发育。显然,识别这种具有系统发育误导性的字符组是可取的。在这里,我们提出了一种使用独立数据源来识别经历协同趋同进化的字符集的过程。我们研究了鸬鹚和海鸥的问题案例,使用骨骼学和分子特征构建的树都具有很强的统计支持,但从根本上却是不一致的。我们发现,骨骼学特征可以分为那些符合分子数据集暗示的系统发育历史的特征和那些不符合的特征。此外,这些不适应的骨骼学特征在内部是一致的,并形成相互兼容的特征或“团”,这些团比随机排列的特征团大得多。因此,我们认为这些字符团是相似选择压力的结果,是协同趋同的特征。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验