Google DeepMind releases AlphaGenome Atlas, scoring all 9 billion single-letter DNA changes

What Google DeepMind released

Google DeepMind released AlphaGenome Atlas on 8 September 2026, a set of precomputed predictions for every possible single-letter change in the human genome, 9 billion single-nucleotide variants in all. For each variant the Atlas holds thousands of predicted molecular effects on gene regulation across hundreds of human and mouse cell types and tissues. The dataset is 1 petabyte, which the team says is more than 30 times the size of the AlphaFold Database.

The Atlas adds a single number per variant, the AVI score, which combines predictions from AlphaGenome and AlphaMissense. Feature attributions break the score into categories such as chromatin accessibility, splicing and conservation. A separate collection lists more than 2,500 recurring DNA sequence motifs and where they occur. The focus matters because coding regions are only about 2% of the genome and the remaining 98% is non-coding, where variant effects are harder to read.

Early results from partners

The post describes several case studies. With the GREGoR Consortium at the Broad Institute, the AVI score helped identify a variant in the DNM1 gene, linked to epileptic encephalopathy, that creates a faulty splice site; lab screens confirmed the prediction. Gareth Hawkes at the University of Exeter used whole-genome data from more than 54,000 UK Biobank participants and found 22% more non-coding genetic associations with protein levels by grouping rare variants by predicted effect. Focusing on the top 1% of non-coding variants, he identified 19 genetic regions linked to body mass index for further study.

The team reports best-in-class performance on several pathogenicity and rare disease benchmarks, but the blog post gives no figures. A paper is linked from the post; the journal is not stated.

Why it matters for genetics research

Researchers working on rare disease or genome-wide association studies usually have to run a model on each variant they care about. A precomputed map for every possible variant turns that into a lookup, much as the AlphaFold Database did for protein structures. Google DeepMind stresses that the Atlas is a baseline that will improve with better models and that AlphaGenome is not validated for any clinical use. For a different use of AI in biology, see Anthropic's drug development work with Claude.

What to watch next

The open points are the date for commercial Atlas access on Google Cloud, published benchmark numbers for the AVI score, and peer review of the paper. The Atlas is also offered as a skill in Google Antigravity, and the base AlphaGenome model remains available for academic use on GitHub and through an API. More AI for science stories are under AI Research.

Questions people ask

What is AlphaGenome Atlas?

A 1-petabyte dataset of AlphaGenome predictions for all 9 billion possible single-letter DNA changes in the human genome, released by Google DeepMind on 8 September 2026.

Is AlphaGenome Atlas free?

It is free for academic and non-commercial use. Commercial use on Google Cloud is planned, with no date given.

Can doctors use AlphaGenome Atlas for diagnosis?

No. Google DeepMind says AlphaGenome has not been validated for, and is not approved for, any clinical use.

Sources

1. AlphaGenome Atlas: A predictive map of every possible DNA letter change in the human genome (Google DeepMind, 8 Sep 2026)
2. AlphaGenome Atlas paper (PDF) (Google DeepMind, 8 Sep 2026)