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利用大型比较序列数据集确定哺乳动物的系统发育。

Confirming the phylogeny of mammals by use of large comparative sequence data sets.

作者信息

Prasad Arjun B, Allard Marc W, Green Eric D

机构信息

Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.

出版信息

Mol Biol Evol. 2008 Sep;25(9):1795-808. doi: 10.1093/molbev/msn104. Epub 2008 May 2.

Abstract

The ongoing generation of prodigious amounts of genomic sequence data from myriad vertebrates is providing unparalleled opportunities for establishing definitive phylogenetic relationships among species. The size and complexities of such comparative sequence data sets not only allow smaller and more difficult branches to be resolved but also present unique challenges, including large computational requirements and the negative consequences of systematic biases. To explore these issues and to clarify the phylogenetic relationships among mammals, we have analyzed a large data set of over 60 megabase pairs (Mb) of high-quality genomic sequence, which we generated from 41 mammals and 3 other vertebrates. All sequences are orthologous to a 1.9-Mb region of the human genome that encompasses the cystic fibrosis transmembrane conductance regulator gene (CFTR). To understand the characteristics and challenges associated with phylogenetic analyses of such a large data set, we partitioned the sequence data in several ways and utilized maximum likelihood, maximum parsimony, and Neighbor-Joining algorithms, implemented in parallel on Linux clusters. These studies yielded well-supported phylogenetic trees, largely confirming other recent molecular phylogenetic analyses. Our results provide support for rooting the placental mammal tree between Atlantogenata (Xenarthra and Afrotheria) and Boreoeutheria (Euarchontoglires and Laurasiatheria), illustrate the difficulty in resolving some branches even with large amounts of data (e.g., in the case of Laurasiatheria), and demonstrate the valuable role that very large comparative sequence data sets can play in refining our understanding of the evolutionary relationships of vertebrates.

摘要

从众多脊椎动物中持续生成的海量基因组序列数据,为确定物种间明确的系统发育关系提供了前所未有的机遇。此类比较序列数据集的规模和复杂性,不仅使较小且更具挑战性的分支得以解析,同时也带来了独特的挑战,包括巨大的计算需求以及系统偏差的负面影响。为探讨这些问题并厘清哺乳动物之间的系统发育关系,我们分析了一个由41种哺乳动物和3种其他脊椎动物生成的超过60兆碱基对(Mb)的高质量基因组序列的大型数据集。所有序列均与人类基因组中包含囊性纤维化跨膜传导调节因子基因(CFTR)的1.9-Mb区域直系同源。为了解与此类大型数据集的系统发育分析相关的特征和挑战,我们以多种方式对序列数据进行了划分,并利用了在Linux集群上并行实现的最大似然法、最大简约法和邻接法算法。这些研究产生了得到充分支持的系统发育树,在很大程度上证实了其他近期的分子系统发育分析。我们的结果支持将胎盘哺乳动物树的根置于非洲兽总目(异关节类和非洲兽类)和北方真兽类(灵长总目和劳亚兽总目)之间,说明了即便有大量数据,解析某些分支仍存在困难(例如在劳亚兽总目的情况下),并证明了非常大的比较序列数据集在完善我们对脊椎动物进化关系的理解方面所能发挥的重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c4d/2638723/1795b7865bdb/molbiolevolmsn104f01_lw.jpg

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