Google DeepMind has launched AlphaGenome, a groundbreaking AI model designed to predict how mutations in DNA affect gene regulation and molecular processes. This model represents a significant advance in genomics by analyzing extremely long DNA sequences—up to 1 million base pairs—with single-base resolution, enabling it to predict thousands of molecular properties such as gene expression levels, splicing patterns, and protein production across many cell types and tissues.
AlphaGenome addresses the challenge of interpreting the vast “dark matter” of the genome—the 98% of DNA that does not code for proteins but regulates gene activity. It combines multiple genomic prediction tasks into one unified model, outperforming previous specialized models by jointly predicting splice sites, RNA coverage, and the effects of genetic variants on gene regulation.
Trained on extensive public datasets from consortia like ENCODE, GTEx, and 4D Nucleome, AlphaGenome helps researchers understand how small genetic variations influence health and disease, including cancer and rare genetic disorders caused by splicing errors. It offers the potential to conduct some laboratory experiments virtually, accelerating insights into the functional impact of DNA variants.
DeepMind has made AlphaGenome freely available for non-commercial research use and plans to release full technical details soon. The model builds on previous DeepMind successes such as AlphaFold and complements tools like AlphaMissense, extending AI’s reach into the non-coding genome.
AlphaGenome is a major leap forward in decoding the genome’s regulatory code, enabling scientists to better predict how genetic mutations affect gene function and disease risk at an unprecedented scale and resolution.