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

Author:

Chen Xun1ORCID,Li Dawei123ORCID

Affiliation:

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

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

3. Department of Computer Science, University of Vermont, Burlington, VT, USA

Abstract

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.

Funder

Solve ME/CFS Initiative Ramsay Award

University of Vermont Start-up Fund

American Cancer Society Institutional Research Grant

Scoliosis Research Society Small Exploratory Grant

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference63 articles.

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4. Transposable elements in cancer;Burns;Nat. Rev. Cancer,2017

5. Multi-platform discovery of haplotype-resolved structural variation in human genomes;Chaisson;bioRxiv,2018

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