VIRUSBreakend: Viral Integration Recognition Using Single Breakends

Abstract

Integration of viruses into infected host cell DNA can causes DNA damage and can disrupt genes. Recent cost reductions and growth of whole genome sequencing has produced a wealth of data in which viral presence and integration detection is possible. While key research and clinically relevant insights can be uncovered, existing software has not achieved widespread adoption, limited in part due to high computational costs, the inability to detect a wide range of viruses, as well as precision and sensitivity. Here, we describe VIRUSBreakend, a high-speed tool that identifies viral DNA presence and genomic integration recognition tool using single breakend variant calling. Single breakends are breakpoints in which only one side has been unambiguously placed. We show that by using a novel virus-centric single breakend variant calling and assembly approach, viral integrations can be identified with high sensitivity and a near-zero false discovery rate, even when integrated in regions of the host genome with low mappability, such as centromeres and telomeres that cannot be reliably called by existing tools. Applying VIRUSBreakend to a large metastatic cancer cohort, we demonstrate that it can reliably detect clinically relevant viral presence and integration including HPV, HBV, MCPyV, EBV, and HHV-8.

FastViFi: Fast and accurate detection of (Hybrid) Viral DNA and RNA

“…We compared these methods against FastViFi (Filter only with no ViFi coupling), Kraken( 21 ) (a single level keyword filtering method optimized for HPV), DVF( 18 ), a recent deep learning based virus finder method, and ViFi( 15 ). VIRUSBreakend( 17 ) requires an assembly step which failed in these sparse data-sets that are unsuitable for checking sites of integration.…”

“…VIRUSBreakend does not report viral-only reads but has shown excellent performance for the detection of integration locations using local assembly on simulated data ( 17 ). On 22 of HCC samples with HBV, they reported exactly the same 16 integration sites as ViFi ( 17 ). As FastViFi has a different focus, we only did a partial comparison against VIRUSBreakend using 2 WGS HNSC samples.…”

“…New methods like VIRUSBreakend ( 17 ) focus specifically on improved detection of viral integration locations. VIRUSBreakend uses a keyword matching approach for the detection of viruses, followed by a local genome assembly that allows it to detect integration even in low-complexity regions of the host genome that are missed by other methods.…”

“…we tested the importance of having two Kraken filters instead of a single Kraken filter by comparing the performance of single-stage vs two-stage Kraken filtering. As VIRUSBreakend ( 17 ) is focused on integration sites and does not work for sparse, viral-only read data, we compared partially against it for host-viral integration and identification of hybrid viral-human transcripts in RNA-seq data. Finally, we tested the relevance of FastViFi results on three TCGA cancer datasets with Human Papilloma virus, Hepatitis B virus, Hepatitis C virus, and Epstein Barr virus infections, focusing specifically on hybrid human viral RNA detection.…”

GRIDSS2: comprehensive characterisation of somatic structural variation using single breakend variants and structural variant phasing

“…The identification of frequent somatic centromeric rearrangements demonstrates the utility single breakend variant calling has in regions of the genome traditionally considered inaccessible to short read sequencing. Single breakend variant calling provides a framework for the reliable detection of LINE integration without a specialised caller 28 , for the detection of centromeric and telomeric viral integrations 29 , and for an entire ecosystem of tools that explicitly model the ambiguity they represent. As single breakends comprise 7.0% of GRIDSS2 calls in the Hartwig cohort, any purely breakpoint-based caller must have a false negative rate of at least 7.0%.…”