AlphaGenome is a large-scale deep-learning system developed by DeepMind to predict how segments of DNA regulate gene expression and how single-nucleotide variants may disrupt that regulation.[1][2] It was launched on 25 June 2025.[3]
Ever since the first draft of the human genome appeared in 2001, most of its over 3 billion letters have remained functionally opaque.[4][1] AlphaGenome extends DeepMind's "Alpha" line of models beyond protein folding and chip design into the longstanding puzzle of the genome's non-coding dark matter.[1]
AlphaGenome accepts stretches of up to one million base pairs, orders of magnitude longer than typical sequence-to-function models, and produces thousands of quantitative predictions, including gene-expression levels, chromatin accessibility, three-dimensional genome contacts and RNA-splicing junctions.[1] The model was trained using genomic data from humans and mice, and its effectiveness on other organisms has not been tested.[1] Current limitations include difficulty in predicting the effects of mutations on genes located more than 100,000 base pairs away.[1]
