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ERVcaller:使用全基因组测序数据鉴定多态性内源性逆转录病毒和其他转座元件插入。

ERVcaller: identifying polymorphic endogenous retrovirus and other transposable element insertions using whole-genome sequencing data.

机构信息

Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT, USA.

Neuroscience, Behavior, and Health Initiative, University of Vermont, Burlington, VT, USA.

出版信息

Bioinformatics. 2019 Oct 15;35(20):3913-3922. doi: 10.1093/bioinformatics/btz205.

Abstract

MOTIVATION

Approximately 8% of the human genome is derived from endogenous retroviruses (ERVs). In recent years, an increasing number of human diseases have been found to be associated with ERVs. However, it remains challenging to accurately detect the full spectrum of polymorphic (unfixed) ERVs using whole-genome sequencing (WGS) data.

RESULTS

We designed a new tool, ERVcaller, to detect and genotype transposable element (TE) insertions, including ERVs, in the human genome. We evaluated ERVcaller using both simulated and real benchmark WGS datasets. Compared to existing tools, ERVcaller consistently obtained both the highest sensitivity and precision for detecting simulated ERV and other TE insertions derived from real polymorphic TE sequences. For the WGS data from the 1000 Genomes Project, ERVcaller detected the largest number of TE insertions per sample based on consensus TE loci. By analyzing the experimentally verified TE insertions, ERVcaller had 94.0% TE detection sensitivity and 96.6% genotyping accuracy. Polymerase chain reaction and Sanger sequencing in a small sample set verified 86.7% of examined insertion statuses and 100% of examined genotypes. In conclusion, ERVcaller is capable of detecting and genotyping TE insertions using WGS data with both high sensitivity and precision. This tool can be applied broadly to other species.

AVAILABILITY AND IMPLEMENTATION

http://www.uvm.edu/genomics/software/ERVcaller.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

人类基因组约有 8%来自内源性逆转录病毒(ERVs)。近年来,越来越多的人类疾病被发现与 ERVs 有关。然而,使用全基因组测序(WGS)数据准确检测全谱多态(未固定)ERV 仍然具有挑战性。

结果

我们设计了一种新工具 ERVcaller,用于检测和分型人类基因组中转座元件(TE)的插入,包括 ERVs。我们使用模拟和真实基准 WGS 数据集评估了 ERVcaller。与现有工具相比,ERVcaller 始终能够以最高的灵敏度和精度检测模拟的 ERV 和来自真实多态 TE 序列的其他 TE 插入。对于 1000 基因组计划的 WGS 数据,ERVcaller 根据共识 TE 基因座在每个样本中检测到最多的 TE 插入。通过分析经过实验验证的 TE 插入,ERVcaller 的 TE 检测灵敏度为 94.0%,基因分型准确率为 96.6%。在一个小样本集中进行聚合酶链反应和 Sanger 测序验证了 86.7%的插入状态和 100%的基因型。总之,ERVcaller 能够使用 WGS 数据以高灵敏度和高精度检测和分型 TE 插入。该工具可广泛应用于其他物种。

可用性和实现

http://www.uvm.edu/genomics/software/ERVcaller.html。

补充信息

补充数据可在生物信息学在线获得。

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