Fast and accurate branch lengths estimation for phylogenomic trees
Fast and accurate branch lengths estimation for phylogenomic trees
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DOI：
10.1186/s12859-015-0821-8
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发表时间：
2016-01-07
影响因子：
3
通讯作者：
Pardi, Fabio
中科院分区：
文献类型：
--
作者：
Binet, Manuel;Gascuel, Olivier;Pardi, Fabio
背景：分支长度是系统发育树的一个重要属性，为进化生物学的许多研究提供了重要信息。然而，当前从基因组信息重建系统发育的方法的一部分（即超级树方法）侧重于系统发育树的拓扑或结构，而不是与之相关的进化分歧。此外，估计分支长度的准确方法（通常基于级联比对的概率分析）受到内存和计算时间的大量需求的限制，并且当数据集太大时可能变得不切实际。结果：在这里，我们提出了一种新颖的基于系统发育距离的方法，名为 ERaBLE（进化速率和分支长度估计），用于估计给定参考拓扑的分支长度以及分析中使用的基因的相对进化速率。 ERaBLE 使用可能非常大的距离矩阵集合作为输入数据，其中每个矩阵都是从不同的基因组区域获得的，或者直接从其序列比对中获得，或者间接从从比对推断的基因树中获得。我们的实验表明，与完成相同任务的其他可能方法相比，ERaBLE 非常快速且相当准确。具体来说，它可以高效、准确地处理大型数据集，例如 OrthoMaM v8 数据库，该数据库由来自多达 40 种哺乳动物的 6,953 个外显子组成。结论：ERaBLE 可以用作超树方法的补充，或者它可以为串联比对的最大似然分析提供有效的替代方案，以根据系统发育数据集估计分支长度。
Background: Branch lengths are an important attribute of phylogenetic trees, providing essential information for many studies in evolutionary biology. Yet, part of the current methodology to reconstruct a phylogeny from genomic information-namely supertree methods-focuses on the topology or structure of the phylogenetic tree, rather than the evolutionary divergences associated to it. Moreover, accurate methods to estimate branch lengths-typically based on probabilistic analysis of a concatenated alignment-are limited by large demands in memory and computing time, and may become impractical when the data sets are too large.Results: Here, we present a novel phylogenomic distance-based method, named ERaBLE (Evolutionary Rates and Branch Length Estimation), to estimate the branch lengths of a given reference topology, and the relative evolutionary rates of the genes employed in the analysis. ERaBLE uses as input data a potentially very large collection of distance matrices, where each matrix is obtained from a different genomic region-either directly from its sequence alignment, or indirectly from a gene tree inferred from the alignment. Our experiments show that ERaBLE is very fast and fairly accurate when compared to other possible approaches for the same tasks. Specifically, it efficiently and accurately deals with large data sets, such as the OrthoMaM v8 database, composed of 6,953 exons from up to 40 mammals.Conclusions: ERaBLE may be used as a complement to supertree methods-or it may provide an efficient alternative to maximum likelihood analysis of concatenated alignments-to estimate branch lengths from phylogenomic data sets.