Let Them Fall Where They May: Congruence Analysis in Massive Phylogenetically Messy Data Sets
Let Them Fall Where They May: Congruence Analysis in Massive Phylogenetically Messy Data Sets
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DOI：
10.1093/molbev/msr110
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发表时间：
2011-10-01
影响因子：
10.7
通讯作者：
Bapteste, Eric
中科院分区：
文献类型：
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作者：
Leigh, Jessica W.;Schliep, Klaus;Bapteste, Eric
在系统发育数据的一致性的兴趣主要集中在影响多细胞生物，特别是动物的问题，其中的不一致性的水平预计是相对较低的。此外，过去开发的评估方法是针对数量相当少的基因座设计的，并且对于较大的数据集扩展性较差。然而，目前有超过一千个完整的基因组序列可供进化生物学家使用，这些序列主要来自微生物，其分子进化比多细胞生命形式的树状进化要少得多。因此，预计这些数据的不一致程度很高。我们提出了一个全等方法，可容纳非常大量的基因和高度的不一致。我们的方法使用聚类算法来识别基于系统发育信号相似性的基因子集。它只涉及每个基因的单一系统发育分析，因此，计算时间与数据集中的基因数量几乎呈线性关系。我们表明，我们的方法表现得非常好，在各种条件下模拟的序列比对集。此外，我们提出了一个分析的核心基因的原核生物，通常被认为是在很大程度上垂直遗传，在其中我们确定了两个高度不一致的基因类。这一结果与复杂性假设是一致的。
Interest in congruence in phylogenetic data has largely focused on issues affecting multicellular organisms, and animals in particular, in which the level of incongruence is expected to be relatively low. In addition, assessment methods developed in the past have been designed for reasonably small numbers of loci and scale poorly for larger data sets. However, there are currently over a thousand complete genome sequences available and of interest to evolutionary biologists, and these sequences are predominantly from microbial organisms, whose molecular evolution is much less frequently treelike than that of multicellular life forms. As such, the level of incongruence in these data is expected to be high. We present a congruence method that accommodates both very large numbers of genes and high degrees of incongruence. Our method uses clustering algorithms to identify subsets of genes based on similarity of phylogenetic signal. It involves only a single phylogenetic analysis per gene, and therefore, computation time scales nearly linearly with the number of genes in the data set. We show that our method performs very well with sets of sequence alignments simulated under a wide variety of conditions. In addition, we present an analysis of core genes of prokaryotes, often assumed to have been largely vertically inherited, in which we identify two highly incongruent classes of genes. This result is consistent with the complexity hypothesis.