nT4X and nT4M: Novel Time Non-reversible Mixture Amino Acid Substitution Models.

IF 2.1 3区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Nguyen Huy Tinh, Cuong Cao Dang, Le Sy Vinh
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引用次数: 0

Abstract

One of the most important and difficult challenges in the research of molecular evolution is modeling the process of amino acid substitutions. Although single-matrix models, such as the LG model, are popular, their capability to properly capture the heterogeneity of the substitution process across sites is still questioned. Several mixture models with multiple matrices have been introduced and shown to offer advantages over single-matrix models. Current general mixture models assume the reversibility of the evolutionary process, implying that substitution rates between any two amino acids are equal in both forward and backward directions. This assumption is not based on biological properties but rather on computational simplicity. The well-known hypothesis is that more realistic models can yield more accurate evolutionary inferences; therefore, our aim is to estimate more biologically realistic models. To this end, we relax the assumption of reversibility and introduce two new general non-reversible 4-matrix mixture models, called nT4M and nT4X. Using alignments from HSSP and TreeBASE databases as data, our newly estimated models outperformed all single-matrix models and almost all reversible mixture models. Moreover, the new non-reversible mixture models enable us to infer rooted trees.

nT4X和nT4M:新的时间不可逆混合物氨基酸取代模型。
分子进化研究中最重要和最困难的挑战之一是氨基酸取代过程的建模。虽然单矩阵模型,如LG模型,很受欢迎,但它们是否能够正确地捕获跨位点替代过程的异质性仍然受到质疑。介绍了几种具有多个矩阵的混合模型,并证明它们比单矩阵模型具有优势。目前的一般混合模型假设进化过程的可逆性,这意味着任意两个氨基酸之间的取代率在正向和反向上都是相等的。这个假设不是基于生物学特性,而是基于计算的简单性。众所周知的假设是,更现实的模型可以产生更准确的进化推断;因此,我们的目标是估计更符合生物学现实的模型。为此,我们放宽了可逆性假设,引入了两种新的通用非可逆4矩阵混合模型nT4M和nT4X。使用来自HSSP和TreeBASE数据库的比对数据,我们的新估计模型优于所有单矩阵模型和几乎所有可逆混合模型。此外,新的不可逆混合模型使我们能够推断出有根树。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Molecular Evolution
Journal of Molecular Evolution 生物-进化生物学
CiteScore
5.50
自引率
2.60%
发文量
36
审稿时长
3 months
期刊介绍: Journal of Molecular Evolution covers experimental, computational, and theoretical work aimed at deciphering features of molecular evolution and the processes bearing on these features, from the initial formation of macromolecular systems through their evolution at the molecular level, the co-evolution of their functions in cellular and organismal systems, and their influence on organismal adaptation, speciation, and ecology. Topics addressed include the evolution of informational macromolecules and their relation to more complex levels of biological organization, including populations and taxa, as well as the molecular basis for the evolution of ecological interactions of species and the use of molecular data to infer fundamental processes in evolutionary ecology. This coverage accommodates such subfields as new genome sequences, comparative structural and functional genomics, population genetics, the molecular evolution of development, the evolution of gene regulation and gene interaction networks, and in vitro evolution of DNA and RNA, molecular evolutionary ecology, and the development of methods and theory that enable molecular evolutionary inference, including but not limited to, phylogenetic methods.
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