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In a recent study published in the journal Cell, researchers developed a deep learning model, “LucaProt,” a transformer-based AI model to detect highly divergent ribonucleic acid (RNA)-dependent RNA polymerase (RdRP) sequences in meta-transcriptomes from diverse ecosystems. They identified 180 RNA virus supergroups and 161,979 putative RNA virus species, showing that RNA viruses are widespread and present even in extreme environments.
Background
RNA viruses are widespread and infect a variety of species, yet their role in global ecosystems has only recently been recognized due to large-scale virus discovery efforts. These studies, primarily using RdRP sequences, have expanded the known virosphere by identifying thousands of new virus species. However, current tools often miss highly divergent RNA viruses, prompting the need for improved identification strategies.
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