The tool, which has been accessible online since 2021, now records more than 15 million viral sequences, and scientists add to it daily. It helps them and public health officials discover new strains, assign them names, and track their evolution. It also allows them to surveil the virus in real time on a global scale with a high degree of precision.
More recently, the team built another software tool, called RIPPLES, which examines UShER’s extensive family tree structure and investigates whether specific “branches” of variants may be recombinants—genetically distinct hybrid variants. A recombinant could, for example, take one part of its genome from the delta variant and another part from omicron. Because they essentially have two “parents,” recombinants are both rarer and tougher to identify.
Before the development of RIPPLES, scientists’ only method of identifying potential recombinants was by remembering mutations they’d spotted in other variants. RIPPLES automates that process, allowing health experts to reconstruct the virus’s evolutionary history. It also helps them work out whether a previously unseen sequence is a truly independent mutation or a combination of existing variants.
“Our global understanding of how covid spreads would have been severely compromised without Yatish’s work,” says David Haussler, scientific director of the UCSC Genomics Institute, who worked with Turakhia on the project. “The product of his algorithm, which nobody else could make, is a global picture of how the virus spread in full genetic detail around the entire globe.”
Since the tool’s release in 2022, RIPPLES has helped reveal hundreds of new SARS-CoV-2 recombinants. “I just started working on it during the pandemic solely because I wanted to be useful,” says Turakhia, 31. “Now, when we get a new sequence, people have already used UShER to train models that can predict whether that new variant will be more transmissible and more immune-invasive than omicron or not, just based on this big data that is available.”