Elimination of Foreign Sequences in Eukaryotic Viral Reference Genomes Improves the Accuracy of Virome Analysis
Junjie Chen, Yue Sun, Xiaomin Yan, Zilin Ren, Guoshuai Wang, Yuhang Liu, Zihan Zhao, Yi Le, Changchun Tu, Biao He
Abstract
High-throughput sequencing-based viromics highly depends on reference databases, but foreign contamination is widespread in public databases and often leads to confusing and even wrong conclusions in genomic analysis and viromic profiling. To address this issue, we systematically detected and identified the contamination in the largest viral sequence collections of GenBank and UniProt based on a stringent scrutiny pipeline. We found hundreds of PVSs that are related to hosts, vectors, and laboratory components. By the removal of them, the resulting data set greatly improves the accuracy and efficiency of eukaryotic virome profiling. These results refresh our knowledge of the type and origin of PVSs and also have warning implications for viromic analysis. Viromic practitioners should be aware of these problems caused by PVSs and need to realize that a careful review of bioinformatic results is necessary for a reliable conclusion.