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拓扑分析用于序列变异:以 54 个国家 2000 多个 COVID-19 感染 SARS-CoV-2 序列为例,与 SARS-CoV-1 和 MERS-CoV 进行比较。

Topological Analysis for Sequence Variability: Case Study on more than 2K SARS-CoV-2 sequences of COVID-19 infected 54 countries in comparison with SARS-CoV-1 and MERS-CoV.

机构信息

Larsen & Toubro Infotech Ltd., Pune, Maharashtra, India; Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India.

Department of Computer Science and Engineering, National Institute of Technical Teachers' Training & Research, Kolkata, West Bengal, India.

出版信息

Infect Genet Evol. 2021 Mar;88:104708. doi: 10.1016/j.meegid.2021.104708. Epub 2021 Jan 6.

Abstract

The pandemic due to novel coronavirus, SARS-CoV-2 is a serious global concern now. More than thousand new COVID-19 infections are getting reported daily for this virus across the globe. Thus, the medical research communities are trying to find the remedy to restrict the spreading of this virus, while the vaccine development work is still under research in parallel. In such critical situation, not only the medical research community, but also the scientists in different fields like microbiology, pharmacy, bioinformatics and data science are also sharing effort to accelerate the process of vaccine development, virus prediction, forecasting the transmissible probability and reproduction cases of virus for social awareness. With the similar context, in this article, we have studied sequence variability of the virus primarily focusing on three aspects: (a) sequence variability among SARS-CoV-1, MERS-CoV and SARS-CoV-2 in human host, which are in the same coronavirus family, (b) sequence variability of SARS-CoV-2 in human host for 54 different countries and (c) sequence variability between coronavirus family and country specific SARS-CoV-2 sequences in human host. For this purpose, as a case study, we have performed topological analysis of 2391 global genomic sequences of SARS-CoV-2 in association with SARS-CoV-1 and MERS-CoV using an integrated semi-alignment based computational technique. The results of the semi-alignment based technique are experimentally and statistically found similar to alignment based technique and computationally faster. Moreover, the outcome of this analysis can help to identify the nations with homogeneous SARS-CoV-2 sequences, so that same vaccine can be applied to their heterogeneous human population.

摘要

目前,由新型冠状病毒引起的大流行是一个严重的全球关注问题。每天都有超过一千例新的 COVID-19 感染病例在全球范围内被报告。因此,医学研究界正在努力寻找限制这种病毒传播的方法,同时疫苗开发工作也在并行研究中。在这种危急情况下,不仅医学研究界,而且微生物学、药学、生物信息学和数据科学等不同领域的科学家也在共同努力,加速疫苗开发、病毒预测、预测病毒的传播概率和繁殖病例,以提高公众的认识。在类似的背景下,本文主要从三个方面研究了病毒的序列变异性:(a)在同一冠状病毒家族中,SARS-CoV-1、MERS-CoV 和 SARS-CoV-2 在人类宿主中的序列变异性;(b)在人类宿主中 54 个不同国家的 SARS-CoV-2 序列变异性;(c)冠状病毒家族和特定国家的 SARS-CoV-2 序列在人类宿主中的序列变异性。为此,作为一个案例研究,我们使用基于集成半对齐的计算技术对 2391 条 SARS-CoV-2 的全球基因组序列与 SARS-CoV-1 和 MERS-CoV 进行了拓扑分析。基于半对齐的技术结果在实验和统计上都与基于对齐的技术结果相似,并且计算速度更快。此外,该分析的结果可以帮助识别具有同质 SARS-CoV-2 序列的国家,以便可以将相同的疫苗应用于其异质人群。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c59d/7787073/77a5a50d4d5f/gr1_lrg.jpg

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