viGEN: An Open Source Pipeline for the Detection and Quantification of Viral RNA in Human Tumors

Abstract

An estimated 17% of cancers worldwide are associated with infectious causes. The extent and biological significance of viral presence/infection in actual tumor samples is generally unknown but could be measured using human transcriptome (RNA-seq) data from tumor samples. We present an open source bioinformatics pipeline viGEN, which allows for not only the detection and quantification of viral RNA, but also variants in the viral transcripts. The pipeline includes 4 major modules: The first module aligns and filter out human RNA sequences; the second module maps and count (remaining un-aligned) reads against reference genomes of all known and sequenced human viruses; the third module quantifies read counts at the individual viral-gene level thus allowing for downstream differential expression analysis of viral genes between case and controls groups. The fourth module calls variants in these viruses. To the best of our knowledge, there are no publicly available pipelines or packages that would provide this type of complete analysis in one open source package. In this paper, we applied the viGEN pipeline to two case studies. We first demonstrate the working of our pipeline on a large public dataset, the TCGA cervical cancer cohort. In the second case study, we performed an in-depth analysis on a small focused study of TCGA liver cancer patients. In the latter cohort, we performed viral-gene quantification, viral-variant extraction and survival analysis. This allowed us to find differentially expressed viral-transcripts and viral-variants between the groups of patients, and connect them to clinical outcome. From our analyses, we show that we were able to successfully detect the human papilloma virus among the TCGA cervical cancer patients. We compared the viGEN pipeline with two metagenomics tools and demonstrate similar sensitivity/specificity. We were also able to quantify viral-transcripts and extract viral-variants using the liver cancer dataset. The results presented corresponded with published literature in terms of rate of detection, and impact of several known variants of HBV genome. This pipeline is generalizable, and can be used to provide novel biological insights into microbial infections in complex diseases and tumorigeneses. Our viral pipeline could be used in conjunction with additional type of immuno-oncology analysis based on RNA-seq data of host RNA for cancer immunology applications. The source code, with example data and tutorial is available at: https://github.com/ICBI/viGEN/.

High-Throughput Sequencing Assists Studies in Genomic Variability and Epidemiology of Little Cherry Virus 1 and 2 infecting Prunus spp. in Belgium

“…Also, regarding the use of HTS analysis in epidemiological studies, it is important to quantify the read counts of specific viruses in each sample. Using recent open source pipelines [65], the normalized read counts may reflect the relative abundance of specific viral RNAs within samples and provide valuable information such as the relative stability of viral RNA fragments within the whole genome and the within-population variations of the same virus species. In addition, the read counts could reveal the prevalence of different Prunus -associated viruses (LChV-1, LChV-2, CVA, PDV, PrVF, etc.)…”

Correlation of HPV16 Gene Status and Gene Expression With Antibody Seropositivity and TIL Status in OPSCC

“…The primer pairs we used in the qPCR assay for HPV16 detection were rigorously tested to be specific for each HPV16 gene, without cross reactivities to other high-risk HPV types, or other human viruses. The assay specificity was also supported by using the viGen bioinformatic pipeline ( 31 ) to detect HPV16 genes, mapping the RNA-sequencing data onto HPV16 genome. This separate analysis using different starting material revealed the same findings and confirms the validity of our qPCR assay.…”

“…The “viral genome level analysis module” of the bioinformatics pipeline viGen ( 31 ) was used to align the FASTQ files against the human reference genome (hg19), filter out human RNA-sequences and map un-aligned reads against the viral reference. Access to the raw and processed data of this RNA sequencing set is possible via the gene expression omnibus (GEO accession number: GSE160008).…”

Novel NGS pipeline for virus discovery from a wide spectrum of hosts and sample types

“…2017 ), Viral Informatics Resource for Metagenome Exploration ( Wommack et al. 2012 ), viGEN ( Bhuvaneshwar et al. 2018 ), the Viral MetaGenome Annotation Pipeline ( Lorenzi et al.…”