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用 GLUE 解读病毒深度测序数据。

Interpreting Viral Deep Sequencing Data with GLUE.

机构信息

MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, UK.

Virus Reference Department, National Infection Service, Public Health England, Colindale, London NW9 5EQ, UK.

出版信息

Viruses. 2019 Apr 3;11(4):323. doi: 10.3390/v11040323.

DOI:10.3390/v11040323
PMID:30987147
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6520954/
Abstract

Using deep sequencing technologies such as Illumina's platform, it is possible to obtain reads from the viral RNA population revealing the viral genome diversity within a single host. A range of software tools and pipelines can transform raw deep sequencing reads into Sequence Alignment Mapping (SAM) files. We propose that interpretation tools should process these SAM files, directly translating individual reads to amino acids in order to extract statistics of interest such as the proportion of different amino acid residues at specific sites. This preserves per-read linkage between nucleotide variants at different positions within a codon location. The samReporter is a subsystem of the GLUE software toolkit which follows this direct read translation approach in its processing of SAM files. We test samReporter on a deep sequencing dataset obtained from a cohort of 241 UK HCV patients for whom prior treatment with direct-acting antivirals has failed; deep sequencing and resistance testing have been suggested to be of clinical use in this context. We compared the polymorphism interpretation results of the samReporter against an approach that does not preserve per-read linkage. We found that the samReporter was able to properly interpret the sequence data at resistance-associated locations in nine patients where the alternative approach was equivocal. In three cases, the samReporter confirmed that resistance or an atypical substitution was present at NS5A position 30. In three further cases, it confirmed that the sofosbuvir-resistant NS5B substitution S282T was absent. This suggests the direct read translation approach implemented is of value for interpreting viral deep sequencing data.

摘要

使用深度测序技术,如 Illumina 的平台,可以从病毒 RNA 群体中获得读数,揭示单个宿主内的病毒基因组多样性。一系列软件工具和管道可以将原始深度测序读数转换为序列比对映射 (SAM) 文件。我们建议解释工具应处理这些 SAM 文件,直接将单个读数翻译为氨基酸,以提取感兴趣的统计信息,例如特定位置上不同氨基酸残基的比例。这保留了密码子位置内不同位置核苷酸变体之间的每个读数的链接。samReporter 是 GLUE 软件工具包的一个子系统,在处理 SAM 文件时采用这种直接读取翻译方法。我们在一个由 241 名英国 HCV 患者组成的队列的深度测序数据集上测试了 samReporter,这些患者先前因直接作用抗病毒药物治疗失败;在这种情况下,深度测序和耐药性检测被认为具有临床用途。我们比较了 samReporter 与不保留每个读数链接的方法的多态性解释结果。我们发现,在九名患者中,samReporter 能够正确解释耐药相关位置的序列数据,而替代方法则存在疑问。在三种情况下,samReporter 证实 NS5A 位置 30 存在耐药或非典型取代。在另外三种情况下,它证实了索非布韦耐药的 NS5B 取代 S282T 不存在。这表明实施的直接读取翻译方法对于解释病毒深度测序数据是有价值的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/207c/6520954/43fa8d3fbd00/viruses-11-00323-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/207c/6520954/43fa8d3fbd00/viruses-11-00323-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/207c/6520954/43fa8d3fbd00/viruses-11-00323-g001.jpg

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