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In Proceedings of the National Academy of Sciences of the United States of America

Understanding the genetics and taxonomy of ancient viruses will give us great insights into not only the origin and evolution of viruses but also how viral infections played roles in our evolution. Endogenous viruses are remnants of ancient viral infections and are thought to retain the genetic characteristics of viruses from ancient times. In this study, we used machine learning of endogenous RNA virus sequence signatures to identify viruses in the human genome that have not been detected or are already extinct. Here, we show that the k-mer occurrence of ancient RNA viral sequences remains similar to that of extant RNA viral sequences and can be differentiated from that of other human genome sequences. Furthermore, using this characteristic, we screened RNA viral insertions in the human reference genome and found virus-like insertions with phylogenetic and evolutionary features indicative of an exogenous origin but lacking homology to previously identified sequences. Our analysis indicates that animal genomes still contain unknown virus-derived sequences and provides a glimpse into the diversity of the ancient virosphere.

Kojima Shohei, Yoshikawa Kohei, Ito Jumpei, Nakagawa So, Parrish Nicholas F, Horie Masayuki, Kawano Shuichi, Tomonaga Keizo


endogenous RNA virus, human genome, machine learning, paleovirology