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阿里·马尔科:一种使用专家指导方法进行病毒识别的流程。

AliMarko: A Pipeline for Virus Identification Using an Expert-Guided Approach.

作者信息

Popov Nikolay, Sonets Ignat, Evdokimova Anastasia, Molchanova Maria, Panova Vera, Korneenko Elena, Manolov Alexander, Ilina Elena

机构信息

Research Institute for Systems Biology and Medicine (RISBM) of Rospotrebnadzor, 117246 Moscow, Russia.

Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, 119435 Moscow, Russia.

出版信息

Viruses. 2025 Feb 28;17(3):355. doi: 10.3390/v17030355.

Abstract

Viruses are ubiquitous across all kingdoms of cellular life, posing a significant threat to human health, and analyzing viral communities is challenging due to their genetic diversity and lack of a single, universally conserved marker gene. To address this challenge, we developed the AliMarko pipeline, a tool designed to streamline virus identification in metagenomic data. Our pipeline uses a dual approach, combining mapping reads with reference genomes and a de novo assembly-based approach involving an HMM-based homology search and phylogenetic analysis, to enable comprehensive detection of viral sequences, including low-coverage and divergent sequences. We applied our pipeline to total RNA sequencing of bat feces and identified a range of viruses, quickly validating viral sequences and assessing their phylogenetic relationships. We hope that the AliMarko pipeline will be a useful resource for the scientific community, facilitating the interpretation of viral communities and advancing our understanding of viral diversity and its impact on human health.

摘要

病毒在所有细胞生命王国中无处不在,对人类健康构成重大威胁,并且由于其基因多样性以及缺乏单一的、普遍保守的标记基因,分析病毒群落具有挑战性。为应对这一挑战,我们开发了AliMarko流程,这是一种旨在简化宏基因组数据中病毒识别的工具。我们的流程采用双重方法,将读段与参考基因组进行比对,并采用基于从头组装的方法,包括基于隐马尔可夫模型(HMM)的同源性搜索和系统发育分析,以全面检测病毒序列,包括低覆盖度和分歧序列。我们将我们的流程应用于蝙蝠粪便的总RNA测序,并鉴定出一系列病毒,快速验证了病毒序列并评估了它们的系统发育关系。我们希望AliMarko流程将成为科学界的有用资源,促进对病毒群落的解读,并推动我们对病毒多样性及其对人类健康影响的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ab2/11946232/0b746bb7d7bf/viruses-17-00355-g001.jpg

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