对同源基因复制后命运进行分类的严格框架

IF 1.4 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Journal of Computational Biology Pub Date : 2024-09-01 Epub Date: 2024-08-01 DOI:10.1089/cmb.2023.0331
Reza Kalhor, Guillaume Beslon, Manuel Lafond, Celine Scornavacca
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引用次数: 0

摘要

基因复制在进化过程中起着核心作用;然而,人们对复制拷贝的命运、相对频率以及环境条件对它们的影响却知之甚少。此外,对复制基因的命运缺乏严格的定义也阻碍了对这一过程的全面认识。在本文中,我们提出了一个新的框架,旨在描述和正式区分复制基因的命运。我们的框架已通过模拟进行了测试,在模拟过程中,我们使用 aevol(一个硅学实验进化平台)对种群的进化进行了模拟。我们的结果显示了几种模式,这些模式证实了之前研究的一些结论,同时也表现出了新的趋势;这可能为更好地理解重复基因作为进化驱动力的作用开辟了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Rigorous Framework to Classify the Postduplication Fate of Paralogous Genes.

Gene duplication has a central role in evolution; still, little is known on the fates of the duplicated copies, their relative frequency, and on how environmental conditions affect them. Moreover, the lack of rigorous definitions concerning the fate of duplicated genes hinders the development of a global vision of this process. In this paper, we present a new framework aiming at characterizing and formally differentiating the fate of duplicated genes. Our framework has been tested via simulations, where the evolution of populations has been simulated using aevol, an in silico experimental evolution platform. Our results show several patterns that confirm some of the conclusions from previous studies, while also exhibiting new tendencies; this may open up new avenues to better understand the role of duplications as a driver of evolution.

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来源期刊
Journal of Computational Biology
Journal of Computational Biology 生物-计算机:跨学科应用
CiteScore
3.60
自引率
5.90%
发文量
113
审稿时长
6-12 weeks
期刊介绍: Journal of Computational Biology is the leading peer-reviewed journal in computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact. Available only online, this is an essential journal for scientists and students who want to keep abreast of developments in bioinformatics. Journal of Computational Biology coverage includes: -Genomics -Mathematical modeling and simulation -Distributed and parallel biological computing -Designing biological databases -Pattern matching and pattern detection -Linking disparate databases and data -New tools for computational biology -Relational and object-oriented database technology for bioinformatics -Biological expert system design and use -Reasoning by analogy, hypothesis formation, and testing by machine -Management of biological databases
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