Google DeepMind has announced AlphaGenome 2, a model that predicts how DNA variants affect specific human cell types, available for non-commercial research via the AlphaGenome API.
Google DeepMind has announced AlphaGenome 2, a next-generation DNA sequence model that predicts how DNA sequences and their variations impact specific human cell types. The company says the model gives scientists a tool to uncover the cellular drivers of disease.
Cells carry the same DNA blueprint, but different cell types switch different genes on or off. AlphaGenome 2 predicts how genetic variants affect hundreds of human cell types, moving from broad tissue averages to individual cell types and cell states. The model is trained on more than 100 million individual cell profiles across 68 tissues, and on both bulk and single-cell data from human and mouse samples, including over 107 million individual cell profiles.
AlphaGenome 2 is a conditional model. It takes a specific biological condition alongside an input DNA sequence, either chosen from a reference catalog of cell types or generated on the fly from a scientist’s own single-cell experiment via a cell encoder. It predicts gene expression, histone modifications, chromatin accessibility, and DNA methylation.
The model can adapt directly to new single-cell data without retraining. Scientists can upload a single-cell RNA-seq snapshot of gene activity from just a few dozen cells, and AlphaGenome 2 can predict variant effects and gene regulation for new cell states, such as those that occur from disease or vaccination.
Google DeepMind says AlphaGenome 2 identifies nearly twice as many variants that change gene expression in cells, compared to its previous state-of-the-art model. On the TenK10K dataset, a large single-cell map of 28 primary immune cell types, AlphaGenome 2 reliably identified nearly twice as many causal variants (30% vs. 16%) and directional gene effects (43% vs. 23%) as the original AlphaGenome fine-tuned on single-cell data and other specialized tools.
The company gave an example involving inflammatory bowel disease. A recent landmark study showed that a variant in a distant regulatory switch drives IBD by overactivating the ETS2 gene in gut immune cells (macrophages). Making predictions across various immune cell types in the gut, AlphaGenome 2 reproduced this finding computationally. It singled out the causal variant and showed that it selectively boosts the ETS2 gene in gut macrophages, leaving other cell types and genes largely unaffected.
The model also revealed that a variant linked to severe COVID-19 disrupts gene activity more strongly when cells are in an activated state, an effect that would be missed in unactivated cells.
AlphaGenome 2 is available today for non-commercial research via the AlphaGenome API, and in private preview for commercial research. Interactive Colab tutorials for expression conditioning are also available. Google DeepMind says it will soon release AlphaGenome 2 Skills in Google Antigravity, its agentic development platform.
The company notes that AlphaGenome and AlphaGenome 2 are intended for research use only and have not been validated or approved for clinical or diagnostic purposes.
The release connects human genetics to single-cell biology by precomputing AlphaGenome 2 predictions for trait-associated variants across hundreds of human cell and tissue conditions. This helps researchers map enhancer-gene links in real human cell types and pinpoint causal GWAS variants and the cells where they act, across traits ranging from height to type 2 diabetes.
Sources
This article was drafted with AI assistance and checked against the sources above. Company claims are reported as claims. Cover image is AI-generated.
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