Deepmind’s AlphaGenome Atlas maps every possible DNA change in the human genome

Google Deepmind has predicted what each of the roughly nine billion possible single-letter changes in the human genome would likely do inside the body. The AlphaGenome Atlas aims to help researchers spot the few relevant variants among a flood of genetic ones.

The human genome runs to about three billion DNA letters. Every person carries millions of tiny deviations from the reference sequence, usually a single swapped letter. Most of these variants are harmless. A few cause disease. Which ones can’t be read directly from the DNA, and testing every one in the lab is basically impossible when there are roughly nine billion possible swaps. The newly released AlphaGenome Atlas tries to fill that gap with predictions. For each of those nine billion changes, it offers an estimate of how the change would likely affect molecular processes across hundreds of cell types and tissues. The dataset spans one petabyte, making it more than 30 times the size of the AlphaFold database for protein structures. It builds on the AI model AlphaGenome, introduced in 2025. The model reads DNA stretches one million letters long and predicts how strongly a gene gets read, whether regulatory proteins can bind to the DNA, and how a gene’s transcript gets spliced. Until now, the model had to be queried for each variant one at a time. Now the answers are precomputed. According to the paper, each variant comes with about 27,000 individual prediction values on average. That matters most for the roughly 98 percent of the genome that holds no blueprints for proteins. These noncoding regions act like switches and dials that decide when and in which tissue a gene is active.