New categories introduced to capture the diversity of the newly discovered species
© Getty Images / AltoClassic
At least 5,500 new virus species have reportedly been found across the world’s oceans in a major new discovery published by an international team of researchers in the Science journal on Thursday.
The team stated that they had achieved this advance by using machine-learning analyses in tandem with traditional evolutionary trees to assess some 35,000 water samples from around the globe.
The group was specifically searching for new viruses that contained RNA genetic material, stating that the scientific community understands relatively little about these kinds of viruses when it comes to the wider world.
“Whereas DNA viruses are known to be abundant, diverse, and commonly key ecosystem players, RNA viruses are insufficiently studied outside disease settings,” reads the report’s abstract. “Using new approaches to optimize discovery and classification, we identified RNA viruses that necessitate substantive revisions of taxonomy (doubling phyla and adding >50% new classes) and evolutionary understanding.”
Read more
The report points out that the most abundant collection of newly identified species belongs to a completely new classification, or phylum, which the scientists have proposed dubbing “Taraviricota,” as a nod to the source of the 35,000 water samples, The Tara Oceans Consortium.
“There’s so much new diversity here – and an entire phylum, the Taraviricota, were found all over the oceans, which suggests they’re ecologically important,” the study’s lead author, Matthew Sullivan, from Ohio State University said in a statement.
The scientists say that the newly discovered “Taraviricota” phyla, which could be the missing link in early RNA virus evolution dating back billions of years, and another new phyla, the “Arctiviricot,” are extremely widespread and dominant in the oceans, and that the research of these new species will “provide foundational knowledge critical to integrating RNA viruses into ecological and epidemiological models.”
