Suppr超能文献

AFLPs 支持蛇鮈科(鲈形目:鮈亚科)中的深关系,与形态假说一致。

AFLPs support deep relationships among darters (Percidae: Etheostomatinae) consistent with morphological hypotheses.

机构信息

Department of Biological Sciences, University of Maryland-Baltimore County, 1000 Hilltop Citcle, Baltimore, MD 21250, USA.

出版信息

Heredity (Edinb). 2011 Dec;107(6):579-88. doi: 10.1038/hdy.2011.50. Epub 2011 Jun 29.

Abstract

Recent attention has focused on the efficacy of amplified fragment length polymorphisms (AFLPs) for resolving deep evolutionary relationships. Here we show that AFLPs provide resolution of deep relationships within the family Percidae that are more consistent with previous morphological hypotheses than are relationships proposed by previous molecular analyses. Despite in silico predictions, we were able to resolve relatively ancient divergences, estimated at >25 MA. We show that the most distantly related species share the fewest fragments, but suggest that large data sets and extensive taxon sampling are sufficient to overcome this obstacle of the AFLP technique for deep divergences. We compare genetic distances estimated from mitochondrial DNA with those from AFLPs and contrast traditional PAUP(*) Nei-Li AFLP genetic distances with a recently proposed method utilizing the Dice equation with constraining nucleotides.

摘要

最近的研究重点集中在扩增片段长度多态性(AFLPs)在解决深层进化关系上的功效。在这里,我们表明 AFLPs 提供了更符合先前形态学假设的 Percidae 家族内部的深层关系分辨率,而不是先前分子分析提出的关系。尽管进行了计算机预测,但我们能够解决估计超过 2500 万年的相对古老的分歧。我们表明,最遥远相关的物种共享的片段最少,但我们建议,大数据集和广泛的分类群采样足以克服 AFLP 技术在深层分歧方面的这一障碍。我们比较了从线粒体 DNA 估计的遗传距离与 AFLP 的遗传距离,并对比了传统的 PAUP(*) Nei-Li AFLP 遗传距离与最近提出的利用限制核苷酸的 Dice 方程的方法。

相似文献

本文引用的文献

5
Deeper AFLPs.更深层次的扩增片段长度多态性(AFLPs)
Heredity (Edinb). 2009 Aug;103(2):99. doi: 10.1038/hdy.2009.52. Epub 2009 May 13.
9
jModelTest: phylogenetic model averaging.jModelTest:系统发育模型平均法。
Mol Biol Evol. 2008 Jul;25(7):1253-6. doi: 10.1093/molbev/msn083. Epub 2008 Apr 8.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验