Revolutionizing Genetic Research: Google's 'DNA Search Engine' for Rapid Data Access

Researchers at ETH Zurich have developed an innovative digital tool that functions like a search engine for genetic data, enabling rapid full-text searches across vast DNA and RNA databases. Named 'MetaGraph', this technology allows scientists to query raw genomic data stored in central repositories such as the American SRA and European ENA, which collectively hold around 100 petabytes of information, comparable to all internet text combined. Traditionally, exploring these enormous datasets required significant computing resources and time-consuming downloads, limiting efficiency in genetic research.

MetaGraph transforms this process by indexing and compressing the data using complex mathematical graphs, making it possible to locate specific sequences within seconds or minutes—akin to a 'Google for DNA'. This approach significantly reduces costs, with larger queries costing no more than 0.74 dollars per megabase, and offers high precision and efficiency. It supports accelerating research on lesser-known pathogens, emerging pandemics, and antibiotic resistance genes by making previously inaccessible data readily searchable.

Since its initial presentation in 2020, MetaGraph has been continuously refined and now indexes nearly half of the globally available sequence datasets. The tool's scalability and open-source availability promise to widen access, potentially enabling private individuals to identify plant species through DNA or assist pharmaceutical companies in internal research. Ultimately, MetaGraph's approach not only expedites genomic research but also enhances our ability to respond to global health challenges more swiftly.

For further details, see the full study in Nature: Mikhail Karasikov et al, "Efficient and accurate search in petabase-scale sequence repositories" (2025). source: https://medicalxpress.com/news/2025-10-google-dna-enables-rapid-full.html