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一种综合方法来确定 SARS-CoV-2 基因组的丰度、突变率和系统发育。

An integrated approach to determine the abundance, mutation rate and phylogeny of the SARS-CoV-2 genome.

机构信息

Integrated Cancer Genomics Laboratory, Advanced Centre for Treatment, Research, and Education in Cancer, Kharghar, Navi Mumbai, Maharashtra, 410210, India.

Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai, Maharashtra, 400094, India.

出版信息

Brief Bioinform. 2021 Mar 22;22(2):1065-1075. doi: 10.1093/bib/bbaa437.

Abstract

The analysis of the SARS-CoV-2 genome datasets has significantly advanced our understanding of the biology and genomic adaptability of the virus. However, the plurality of advanced sequencing datasets-such as short and long reads-presents a formidable computational challenge to uniformly perform quantitative, variant or phylogenetic analysis, thus limiting its application in public health laboratories engaged in studying epidemic outbreaks. We present a computational tool, Infectious Pathogen Detector (IPD), to perform integrated analysis of diverse genomic datasets, with a customized analytical module for the SARS-CoV-2 virus. The IPD pipeline quantitates individual occurrences of 1060 pathogens and performs mutation and phylogenetic analysis from heterogeneous sequencing datasets. Using IPD, we demonstrate a varying burden (5.055-999655.7 fragments per million) of SARS-CoV-2 transcripts across 1500 short- and long-read sequencing SARS-CoV-2 datasets and identify 4634 SARS-CoV-2 variants (~3.05 variants per sample), including 449 novel variants, across the genome with distinct hotspot mutations in the ORF1ab and S genes along with their phylogenetic relationships establishing the utility of IPD in tracing the genome isolates from the genomic data (as accessed on 11 June 2020). The IPD predicts the occurrence and dynamics of variability among infectious pathogens-with a potential for direct utility in the COVID-19 pandemic and beyond to help automate the sequencing-based pathogen analysis and in responding to public health threats, efficaciously. A graphical user interface (GUI)-enabled desktop application is freely available for download for the academic users at http://www.actrec.gov.in/pi-webpages/AmitDutt/IPD/IPD.html and for web-based processing at http://ipd.actrec.gov.in/ipdweb/ to generate an automated report without any prior computational know-how.

摘要

对 SARS-CoV-2 基因组数据集的分析极大地促进了我们对病毒生物学和基因组适应性的理解。然而,多种先进的测序数据集(如短读长和长读长)对统一进行定量、变异或系统发育分析提出了巨大的计算挑战,从而限制了其在从事疫情爆发研究的公共卫生实验室中的应用。我们提出了一种计算工具 Infectious Pathogen Detector(IPD),用于对多样化的基因组数据集进行综合分析,并为 SARS-CoV-2 病毒定制了一个分析模块。IPD 管道定量了 1060 种病原体的个体出现情况,并从异质测序数据集中进行突变和系统发育分析。使用 IPD,我们在 1500 个短读长和长读长 SARS-CoV-2 测序数据集上展示了 SARS-CoV-2 转录物的不同负担(5.055-999655.7 个片段/百万),并在全基因组范围内鉴定了 4634 种 SARS-CoV-2 变体(每个样本约 3.05 种变体),包括 449 种新变体,在 ORF1ab 和 S 基因中存在明显的热点突变及其系统发育关系,证明了 IPD 在从基因组数据中追踪基因组分离株方面的效用(截至 2020 年 6 月 11 日访问)。IPD 预测了传染性病原体之间的发生和变异动态-具有直接应用于 COVID-19 大流行及以后的潜力,有助于自动化基于测序的病原体分析,并有效应对公共卫生威胁。一个带有图形用户界面(GUI)的桌面应用程序可免费供学术用户在 http://www.actrec.gov.in/pi-webpages/AmitDutt/IPD/IPD.html 下载,并可在 http://ipd.actrec.gov.in/ipdweb/ 进行基于网络的处理,以生成无需任何先前计算知识的自动报告。

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