論文

国際誌
2021年2月2日

Virus-like insertions with sequence signatures similar to those of endogenous nonretroviral RNA viruses in the human genome.

Proceedings of the National Academy of Sciences of the United States of America
  • Shohei Kojima
  • ,
  • Kohei Yoshikawa
  • ,
  • Jumpei Ito
  • ,
  • So Nakagawa
  • ,
  • Nicholas F Parrish
  • ,
  • Masayuki Horie
  • ,
  • Shuichi Kawano
  • ,
  • Keizo Tomonaga

118
5
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1073/pnas.2010758118

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.

リンク情報
DOI
https://doi.org/10.1073/pnas.2010758118
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/33495343
PubMed Central
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865133
ID情報
  • DOI : 10.1073/pnas.2010758118
  • PubMed ID : 33495343
  • PubMed Central 記事ID : PMC7865133

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