Google DeepMind Ships 1PB AlphaGenome Atlas of 9B DNA Variants

Google DeepMind pre-computed the regulatory impact of every possible single-letter change to the human genome. All 9 billion of them. In a post on the Google blog, the team calls the result AlphaGenome Atlas: "a database that predicts the effects of every possible single nucleotide variant in the human genome." The finished file runs to 1 petabyte.

The reason it exists is that only about 2% of the genome codes for protein. The other 98% is regulatory and, until now, thinly annotated. AlphaGenome Atlas assigns each of those 9 billion positions a summary number the team calls the AVI score. "This single, easy-to-use score combines predictions for both coding and non-coding regions," the post says.

Two field trials are cited. At the Broad Institute, Laura Covill's team ran a rare-disease case through the atlas: "The tool highlighted a critical variant in the DNM1 gene, predicting that it created an incorrect splice site." Dr. Gareth Hawkes then applied it to 54,000+ UK Biobank participants and, by grouping variants by their predicted molecular effect, "uncovered 22% more non-coding genetic associations," landing on 19 genetic regions linked to body mass index.

Access is a browser tab. "AlphaGenome Atlas is available today through an intuitive website portal that requires zero coding skills," the announcement says.

The post gives no false-positive rate for AVI, no ancestry breakdown of the UK Biobank cohort, and no license terms for commercial reuse. It follows Google's male fruit fly connectome release from four days earlier, part of a busy run on our Healthcare AI beat.