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Reconstruction of highly heterogeneous gene-content evolution across the three domains of life

机译:重构生命三个领域中高度异质的基因含量进化

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摘要

Motivation: Reconstruction of gene-content evolutionary history is fundamental in studying the evolution of genomes and biological systems. To reconstruct plausible evolutionary history, rates of gene gain/loss should be estimated by considering the high level of heterogeneity: e. g. genome duplication and parasitization, respectively, result in high rates of gene gain and loss. Gene-content evolution reconstruction methods that consider this heterogeneity and that are both effective in estimating the rates of gene gain and loss and sufficiently efficient to analyze abundant genomic data had not been developed. Results: An effective and efficient method for reconstructing heterogeneous gene-content evolution was developed. This method comprises analytically integrable modeling of gene-content evolution, analytical formulation of expectation-maximization and efficient calculation of marginal likelihood using an inside-outsidelike algorithm. Simulation tests on the scale of hundreds of genomes showed that both the gene gain/ loss rates and evolutionary history were effectively estimated within a few days of computational time. Subsequently, this algorithm was applied to an actual data set of nearly 200 genomes to reconstruct the heterogeneous gene-content evolution across the three domains of life. The reconstructed history, which contained several features consistent with biological observations, showed that the trends of gene-content evolution were not only drastically different between prokaryotes and eukaryotes, but were highly variable within each form of life. The results suggest that heterogeneity should be considered in studies of the evolution of gene content, genomes and biological systems.
机译:动机:重建基因含量的进化史是研究基因组和生物系统进化的基础。为了重建合理的进化史,应该通过考虑高度异质性来估算基因得失率。 G。基因组复制和寄生化分别导致高频率的基因获得和丧失。尚未考虑到这种异质性的基因内容进化重建方法,该方法既可以有效地估计基因的得失率,又可以有效地分析丰富的基因组数据。结果:开发了一种有效的重建异质基因含量进化的方法。该方法包括基因内容进化的分析可集成建模,期望最大化的分析公式以及使用内外相似算法的边际可能性的有效计算。在数百个基因组规模上进行的模拟测试表明,在几天的计算时间内即可有效估计基因的得失率和进化史。随后,将该算法应用于近200个基因组的实际数据集,以重构跨生命三个域的异质基因含量进化。重建的历史包含与生物学观察一致的几个特征,表明基因含量进化的趋势不仅在原核生物和真核生物之间存在显着差异,而且在每种生命形式中差异很大。结果表明,在研究基因含量,基因组和生物系统的进化时应考虑异质性。

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