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膜翅目线粒体16S rRNA基因变异的层次分析

Hierarchical analysis of variation in the mitochondrial 16S rRNA gene among Hymenoptera.

作者信息

Whitfield J B, Cameron S A

机构信息

Department of Entomology, University of Arkansas, Fayetteville 72701, USA.

出版信息

Mol Biol Evol. 1998 Dec;15(12):1728-43. doi: 10.1093/oxfordjournals.molbev.a025899.

Abstract

Nucleotide sequences from a 434-bp region of the 16S rRNA gene were analyzed for 65 taxa of Hymenoptera (ants, bees, wasps, parasitoid wasps, sawflies) to examine the patterns of variation within the gene fragment and the taxonomic levels for which it shows maximum utility in phylogeny estimation. A hierarchical approach was adopted in the study through comparison of levels of sequence variation among taxa at different taxonomic levels. As previously reported for many holometabolous insects, the 16S data reported here for Hymenoptera are highly AT-rich and exhibit strong site-to-site variation in substitution rate. More precise estimates of the shape parameter (alpha) of the gamma distribution and the proportion of invariant sites were obtained in this study by employing a reference phylogeny and utilizing maximum-likelihood estimation. The effectiveness of this approach to recovering expected phylogenies of selected hymenopteran taxa has been tested against the use of maximum parsimony. This study finds that the 16S gene is most informative for phylogenetic analysis at two different levels: among closely related species or populations, and among tribes, subfamilies, and families. Maximization of the phylogenetic signal extracted from the 16S gene at higher taxonomic levels may require consideration of the base composition bias and the site-to-site rate variation in a maximum-likelihood framework.

摘要

对膜翅目(蚂蚁、蜜蜂、黄蜂、寄生蜂、叶蜂)65个分类单元的16S rRNA基因434bp区域的核苷酸序列进行了分析,以研究该基因片段内的变异模式以及在系统发育估计中显示出最大效用的分类水平。通过比较不同分类水平的分类单元之间的序列变异水平,在研究中采用了分层方法。正如之前对许多全变态昆虫所报道的那样,这里报道的膜翅目16S数据富含AT,并且在替代率上表现出强烈的位点间变异。通过采用参考系统发育并利用最大似然估计,在本研究中获得了伽马分布形状参数(α)和不变位点比例的更精确估计。针对使用最大简约法,测试了这种方法恢复选定膜翅目分类单元预期系统发育的有效性。本研究发现,16S基因在两个不同水平的系统发育分析中信息最丰富:在密切相关的物种或种群之间,以及在部落、亚科和科之间。在更高分类水平上从16S基因中提取的系统发育信号的最大化可能需要在最大似然框架中考虑碱基组成偏差和位点间速率变异。

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