VERSE: a novel approach to detect virus integration in host genomes through reference genome customization

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• 作者：Qingguo Wang (1)
  Peilin Jia (1) (2)
  Zhongming Zhao (1) (2) (3) (4)
  
  1. Department of Biomedical Informatics ; Vanderbilt University School of Medicine ; Nashville ; TN ; 37203 ; USA
  2. Center for Quantitative Sciences ; Vanderbilt University Medical Center ; Nashville ; TN ; 37232 ; USA
  3. Department of Psychiatry ; Vanderbilt University School of Medicine ; Nashville ; TN ; 37232 ; USA
  4. Department of Cancer Biology ; Vanderbilt University School of Medicine ; Nashville ; TN ; 37232 ; USA
  
• 刊名：Genome Medicine
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：7
• 期：1
• 全文大小：1,509 KB
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• 刊物主题：Human Genetics; Proteomics; Bioinformatics; Internal Medicine;
• 出版者：BioMed Central
• ISSN：1756-994X

文摘

Fueled by widespread applications of high-throughput next generation sequencing (NGS) technologies and urgent need to counter threats of pathogenic viruses, large-scale studies were conducted recently to investigate virus integration in host genomes (for example, human tumor genomes) that may cause carcinogenesis or other diseases. A limiting factor in these studies, however, is rapid virus evolution and resulting polymorphisms, which prevent reads from aligning readily to commonly used virus reference genomes, and, accordingly, make virus integration sites difficult to detect. Another confounding factor is host genomic instability as a result of virus insertions. To tackle these challenges and improve our capability to identify cryptic virus-host fusions, we present a new approach that detects Virus intEgration sites through iterative Reference SEquence customization (VERSE). To the best of our knowledge, VERSE is the first approach to improve detection through customizing reference genomes. Using 19 human tumors and cancer cell lines as test data, we demonstrated that VERSE substantially enhanced the sensitivity of virus integration site detection. VERSE is implemented in the open source package VirusFinder 2 that is available at http://bioinfo.mc.vanderbilt.edu/VirusFinder/.