DeepMind's AlphaGenome 2 predicts how DNA variants affect hundreds of human cell types

Google DeepMind has announced AlphaGenome 2, a model that predicts how DNA sequences and their variants affect gene activity in specific human cell types. The post introducing it is by Adam Gayoso, Natasha Latysheva, Pushmeet Kohli and Žiga Avsec. Every cell in the body carries the same DNA, but each cell type, such as a heart muscle cell or an immune cell, switches different genes on or off. Projects such as the Human Cell Atlas are mapping gene expression across millions of cells. Predicting how small DNA changes alter that expression in particular cells is still an unsolved problem, and those changes are a key driver of human traits and disease. The original AlphaGenome, released last year, predicted variant effects across broad tissues. DeepMind later added AlphaGenome Atlas, which holds predictions for all 9 billion possible single-letter changes in the human genome. AlphaGenome 2 extends predictions to hundreds of cell types. DeepMind says this gives researchers a finer tool for prioritizing and interpreting variants in work on rare diseases, complex traits and drug development. On the same day, SiliconANGLE reports, DeepMind released Gemini Robotics 2.5, a vision-language-action model for controlling robots. DeepMind tested it on more than 200 distinct tasks.