AlphaGenome predicts how DNA variants affect thousands of gene-regulation signals from 1 Mb of sequence
Result confirmed
The takeaway
DeepMind’s AlphaGenome reads up to 1 million DNA bases and predicts 5,930 human (1,128 mouse) genomic signals, including expression, chromatin accessibility and splicing, at base-pair resolution.
Status
- Claim
Result confirmed
- Our reporting
- High confidence
- Verification
- Peer-reviewed
- Importance
- 3 of 5
- Last verified
- 29 September 2026
Your AI and this story
- GPT-6 AstraIn its training data
- Claude Opus 5.5In its training data
- Gemini 4 HydrogenIn its training data
- Grok 4.7In its training data
It happened before the cutoffs of all four assistants, so it can be in their training data.
Key facts
- Input: up to 1 Mb of DNA; outputs 5,930 human tracks
- State of the art on most variant-effect benchmarks at announcement
- Nature paper 28 Jan 2026 (vol 649); API for non-commercial research
What happened
DeepMind extended from protein structure to how DNA sequence controls gene activity, releasing a model and API.
Why it matters
Most disease-linked variants are non-coding. AlphaGenome gives researchers a way to predict what they do.
Sources
3 sources from 3 sites. Numbers match the chips in the text.
3 sources: 2 primary, 1 reaction
Primary
- DeepMind: AlphaGenome — AI for better understanding the genomedeepmind.google, official
- Nature vol 649 issue 8099 (AlphaGenome paper)nature.com, paper
Reactions
- Science Media Centre: expert reaction to AlphaGenomesciencemediacentre.org, discussion
Changes
- Filed