Researchers used machine learning to identify nucleic acid sequence patterns characteristic of endogenous RNA viruses, allowing detection of such viruses in the human genome even in the absence of sequence similarity with known viruses; the authors identified two previously undetected endogenous RNA viruses and one endogenous RNA virus-like element, which lacked homology to known viral sequences, in the human genome, suggesting that many such virus-like insertions may remain undiscovered in animal genomes.
Article #20-10758: "Virus-like insertions with sequence signatures similar to those of endogenous nonretroviral RNA viruses in the human genome," by Shohei Kojima et al.
MEDIA CONTACT: Keizo Tomonaga, Kyoto University, JAPAN; tel: +81-75-751-3997; email: tomonaga.keizo.5r@kyoto-u.ac.jp ; Shuichi Kawano, The University of Electro-Communications, Chofu, JAPAN; email: skawano@ai.lab.uec.ac.jp
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Proceedings of the National Academy of Sciences