Bases-dependent Rapid Phylogenetic Clustering (Bd-RPC) enables precise and efficient phylogenetic estimation in viruses.

IF 5.5 2区 医学 Q1 VIROLOGY Virus Evolution Pub Date : 2024-01-27 eCollection Date: 2024-01-01 DOI:10.1093/ve/veae005
Bin Ma, Huimin Gong, Qianshuai Xu, Yuan Gao, Aohan Guan, Haoyu Wang, Kexin Hua, Rui Luo, Hui Jin
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Abstract

Understanding phylogenetic relationships among species is essential for many biological studies, which call for an accurate phylogenetic tree to understand major evolutionary transitions. The phylogenetic analyses present a major challenge in estimation accuracy and computational efficiency, especially recently facing a wave of severe emerging infectious disease outbreaks. Here, we introduced a novel, efficient framework called Bases-dependent Rapid Phylogenetic Clustering (Bd-RPC) for new sample placement for viruses. In this study, a brand-new recoding method called Frequency Vector Recoding was implemented to approximate the phylogenetic distance, and the Phylogenetic Simulated Annealing Search algorithm was developed to match the recoded distance matrix with the phylogenetic tree. Meanwhile, the indel (insertion/deletion) was heuristically introduced to foreign sequence recognition for the first time. Here, we compared the Bd-RPC with the recent placement software (PAGAN2, EPA-ng, TreeBeST) and evaluated it in Alphacoronavirus, Alphaherpesvirinae, and Betacoronavirus by using Split and Robinson-Foulds distances. The comparisons showed that Bd-RPC maintained the highest precision with great efficiency, demonstrating good performance in new sample placement on all three virus genera. Finally, a user-friendly website (http://www.bd-rpc.xyz) is available for users to classify new samples instantly and facilitate exploration of the phylogenetic research in viruses, and the Bd-RPC is available on GitHub (http://github.com/Bin-Ma/bd-rpc).

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依赖碱基的快速系统进化聚类(Bd-RPC)可对病毒进行精确、高效的系统进化估算。
了解物种之间的系统发育关系对许多生物研究至关重要,这些研究需要准确的系统发育树来了解重大的进化转变。系统发育分析在估算准确性和计算效率方面是一个重大挑战,尤其是最近面临着严重的新发传染病爆发的浪潮。在此,我们引入了一种名为 "依赖碱基的快速系统发育聚类(Bd-RPC)"的新型高效框架,用于病毒的新样本定位。在这项研究中,我们采用了一种名为频率矢量重编码(Frequency Vector Recoding)的全新重编码方法来逼近系统发育距离,并开发了系统发育模拟退火搜索算法(Phylogenetic Simulated Annealing Search algorithm)来匹配重编码距离矩阵与系统发育树。同时,首次在外来序列识别中启发式地引入了吲哚(插入/缺失)。在此,我们将 Bd-RPC 与最近的定位软件(PAGAN2、EPA-ng、TreeBeST)进行了比较,并通过使用 Split 和 Robinson-Foulds 距离在 Alphacoronavirus、Alphaherpesvirinae 和 Betacoronavirus 中对其进行了评估。比较结果表明,Bd-RPC 保持了最高的精确度和极高的效率,在所有三个病毒属的新样本定位中都表现出了良好的性能。最后,一个用户友好型网站(http://www.bd-rpc.xyz)可供用户即时对新样本进行分类,并为探索病毒的系统发育研究提供了便利,Bd-RPC 可在 GitHub 上下载(http://github.com/Bin-Ma/bd-rpc)。
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
Virus Evolution
Virus Evolution Immunology and Microbiology-Microbiology
CiteScore
10.50
自引率
5.70%
发文量
108
审稿时长
14 weeks
期刊介绍: Virus Evolution is a new Open Access journal focusing on the long-term evolution of viruses, viruses as a model system for studying evolutionary processes, viral molecular epidemiology and environmental virology. The aim of the journal is to provide a forum for original research papers, reviews, commentaries and a venue for in-depth discussion on the topics relevant to virus evolution.
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