Identification of Viral Variants from Functional Genomics Data

The analysis of virus knockout mutants is a common approach for studying the role of individual viral genes in viral infections and is increasingly performed using functional genomics sequencing experiments, e.g. RNA-seq or ATAC-seq, of infected cells. Identifying viral variants directly in these experiments avoids additional genome sequencing and allows confirming the presence of particular mutations directly in the experiment of interest. Here, we present a pipeline to directly identify viral variants from these functional genomics data. This combines existing SNP callers with novel methods for identifying deletions, insertions, and corresponding inserted sequences. The latter address the problem that existing structural variant callers performed poorly on functional genomics data with large variations in coverage. We evaluated the pipeline on RNA-seq data for infection with wild-type Herpes simplex virus 1 (HSV-1) and null mutants of important HSV-1 proteins. Comparison of variants identified by our pipeline with the descriptions of the original publications showed that we could correctly recover the introduced mutations. Thus, our pipeline offers researchers a fast and easy way to verify the existence of variants in the viral genome without additional genome sequencing experiments.