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微生物全基因组关联研究的现状:方法、瓶颈与分析陷阱

Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls.

作者信息

San James Emmanuel, Baichoo Shakuntala, Kanzi Aquillah, Moosa Yumna, Lessells Richard, Fonseca Vagner, Mogaka John, Power Robert, de Oliveira Tulio

机构信息

Kwazulu-Natal Research and Innovation Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.

Department of Digital Technologies, FoICDT, University of Mauritius, Réduit, Mauritius.

出版信息

Front Microbiol. 2020 Jan 30;10:3119. doi: 10.3389/fmicb.2019.03119. eCollection 2019.

DOI:10.3389/fmicb.2019.03119
PMID:32082269
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7002396/
Abstract

Microbial genome-wide association studies (mGWAS) are a new and exciting research field that is adapting human GWAS methods to understand how variations in microbial genomes affect host or pathogen phenotypes, such as drug resistance, virulence, host specificity and prognosis. Several computational tools and methods have been developed or adapted from human GWAS to facilitate the discovery of novel mutations and structural variations that are associated with the phenotypes of interest. However, no comprehensive, end-to-end, user-friendly tool is currently available. The development of a broadly applicable pipeline presents a real opportunity among computational biologists. Here, (i) we review the prominent and promising tools, (ii) discuss analytical pitfalls and bottlenecks in mGWAS, (iii) provide insights into the selection of appropriate tools, (iv) highlight the gaps that still need to be filled and how users and developers can work together to overcome these bottlenecks. Use of mGWAS research can inform drug repositioning decisions as well as accelerate the discovery and development of more effective vaccines and antimicrobials for pressing infectious diseases of global health significance, such as HIV, TB, influenza, and malaria.

摘要

微生物全基因组关联研究(mGWAS)是一个崭新且令人兴奋的研究领域,它正在采用人类全基因组关联研究方法来理解微生物基因组变异如何影响宿主或病原体的表型,如耐药性、毒力、宿主特异性和预后。已经从人类全基因组关联研究中开发或改编了几种计算工具和方法,以促进发现与感兴趣的表型相关的新突变和结构变异。然而,目前还没有一个全面的、端到端的、用户友好的工具。开发一个广泛适用的流程在计算生物学家中提供了一个真正的机会。在此,(i)我们回顾突出且有前景的工具,(ii)讨论mGWAS中的分析陷阱和瓶颈,(iii)提供关于选择合适工具的见解,(iv)强调仍需填补的空白以及用户和开发者如何共同努力克服这些瓶颈。mGWAS研究的应用可为药物重新定位决策提供信息,并加速针对具有全球健康意义的紧迫传染病(如艾滋病毒、结核病、流感和疟疾)开发更有效的疫苗和抗菌药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22dd/7002396/ec1e382123f3/fmicb-10-03119-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22dd/7002396/f6d7865886a5/fmicb-10-03119-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22dd/7002396/0b8bc08bd18c/fmicb-10-03119-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22dd/7002396/ec1e382123f3/fmicb-10-03119-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22dd/7002396/f6d7865886a5/fmicb-10-03119-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22dd/7002396/0b8bc08bd18c/fmicb-10-03119-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22dd/7002396/ec1e382123f3/fmicb-10-03119-g003.jpg

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