Rate matrices for analyzing large families of protein sequences
Rate matrices for analyzing large families of protein sequences
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DOI：
10.1089/106652701752236205
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发表时间：
2001-01-01
影响因子：
1.7
通讯作者：
Torrésani, B
中科院分区：
文献类型：
--
作者：
Devauchelle, C;Grossmann, A;Torrésani, B
我们提出并研究了一种分析蛋白质序列家族的新方法。这种方法与系统发育重建中使用的LogDet距离有关;它可以被视为将这些距离嵌入多维框架的尝试。所提出的方法首先将马尔可夫矩阵与从给定的多重比对推导出的每个成对比对相关联。这里考虑的中心对象是这些马尔可夫矩阵的矩阵值矩阵L，它存在于与序列之间相当大的发散相容的条件下。这些算法使我们能够比较来自一个家庭的对齐蛋白质与简单的模型（特别是连续可逆马尔可夫模型）的数据，并测试这些模型的充分性。如果忽略由序列的有限长度引起的波动，则任意树上的具有单个速率矩阵Q的任何连续可逆马尔可夫模型预测所有观察到的矩阵L都是Q的倍数。我们的方法利用了这一事实，而不依赖于任何树估计。我们测试这个预测的一个家庭的蛋白质编码的线粒体基因组的26个多细胞动物，其中包括脊椎动物，节肢动物，棘皮动物，软体动物和线虫。观察矩阵L的主成分分析表明，一个单一的速率模型可以被用来作为一个粗略的近似数据，但从任何这样的模型的系统偏差是明确无误的，并与正在考虑的物种的进化历史。
We propose and study a new approach for the analysis of families of protein sequences. This method is related to the LogDet distances used in phylogenetic reconstructions; it can be viewed as an attempt to embed these distances into a multidimensional framework. The proposed method starts by associating a Markov matrix to each pairwise alignment deduced from a given multiple alignment. The central objects under consideration here are matrix-valued logarithms L of these Markov matrices, which exist under conditions that are compatible with fairly large divergence between the sequences. These logarithms allow us to compare data from a family of aligned proteins with simple models (in particular, continuous reversible Markov models) and to test the adequacy of such models. If one neglects fluctuations arising from the finite length of sequences, any continuous reversible Markov model with a single rate matrix Q over an arbitrary tree predicts that all the observed matrices L are multiples of Q. Our method exploits this fact, without relying on any tree estimation. We test this prediction on a family of proteins encoded by the mitochondrial genome of 26 multicellular animals, which include vertebrates, arthropods, echinoderms, molluscs, and nematodes. A principal component analysis of the observed matrices L shows that a single rate model can be used as a rough approximation to the data, but that systematic deviations from any such model are unmistakable and related to the evolutionary history of the species under consideration.