Jun Cheng, Kyle R Taylor, Lauren Nicolaisen, Joshua Pan, Clare Bycroft, Matteo Perino, Tom Ward, Gareth Hawkes, Laura E Covill, Melanie Weilert, Raina W Thomas, Natasha Latysheva, Maile J Hirschmann, Xi Dawn Chen, Robin N Beaumont, V Kartik Chundru, Michael N Weedon, Simon Bourdareau, Hoyin Chu, Dhavanthi Hariharan, Thais Kagohara, Lucas Tenorio, Yosuke Ushigome, Courtney A Shearer, Barbara Ikica, Ada Fang, Mouad Naciri, Victoria Johnston, Richard Green, Lai Hong Wong, Vincent Dutordoir, Anne Mottram, Adam Gayoso, Eirini Arvaniti, Guido Novati, Heidi L Rehm, Fei Chen, Caleb A Lareau, Caroline F Wright, Anne O'Donnell-Luria, Julia Zeitlinger, Pushmeet Kohli, Ziga Avsec
A major challenge in genomics is deciphering the functional consequences of non-coding genetic variation. Here we present AlphaGenome Atlas, a comprehensive resource that enables the joint interpretation and prioritization of variant effects across the entire human genome. Using AlphaGenome, we predicted the regulatory effects across thousands of molecular phenotypes for every possible human single nucleotide variant and many observed indels. These predictions were then used to derive a unified and interpretable AlphaGenome Variant Impact (AVI) score and to map cis-regulatory motifs across the genome. AVI achieved state-of-the-art performance across diverse benchmarks with improved prioritization of deleterious non-coding variants. Application of the combined Atlas resource helped solve an epileptic encephalopathy rare disease case, increased the statistical power to detect rare non-coding variants driving population-level phenotypes, and enhanced the mechanistic interpretation of these variants. Thus, AlphaGenome Atlas improves the prioritization and molecular interpretation of non-coding variants with genetic and clinical significance.