Only about 2% of the human genome
contains direct blueprints that code for proteins. Scientists understand that 2% fairly well.
AlphaGenome
Using AI to understand the human genome
AlphaGenome Atlas is the most comprehensive catalogue of how single-letter variant changes in the human genome affect molecular biology.
Atlas simplifies variant prioritisation with the AlphaGenome Variant Impact (AVI) score, allowing researchers to quickly prioritize between different variants across the whole genome, both those that produce proteins and control gene activity, while also interpreting their molecular effects. It’s available to researchers around the world.
What is AlphaGenome?
Deciphering the human genome.
The remaining 98%
acts as the body’s control panel, orchestrating gene activity, and contains most variants associated with physical traits. Think of it as an array of millions of switches and dials that tell the body when, where, and how much of a certain protein to make.
Interpreting how genetic variations impact
this complex system of gene expression and its effects at a molecular level, has been a difficult experimental process. AlphaGenome can help accelerate progress towards that challenge. It is an advanced AI model that can predict how genetic variants disrupt these biological processes, revealing how both the blueprints and the control panel are wired together.
AlphaGenome Atlas
Predicting the effects of every possible single-letter change in the human genome.
We’ve used AlphaGenome to predict the molecular impact of every possible single-letter change in the human genome. All nine billion of them.
AlphaGenome Atlas is a 1PB dataset containing every single possible nucleotide variant alongside an AlphaGenome Variant Impact (AVI) score. This score helps researchers instantly understand the potential impact of any given variation.
AlphaGenome Atlas is available to researchers around the world, with coding and non-coding variations available.
AlphaGenome Skills
Accelerating genomic research with Google Antigravity.
The AlphaGenome and AlphaGenome Atlas Skills empowers researchers to run complex workflows directly within Google Antigravity—an AI-powered scientific workbench.
By connecting an AI assistant directly to the 1PB AlphaGenome Atlas dataset, researchers can transition from manual data searching to automated hypothesis generation in minutes.
Automate Prioritization
Rank massive lists of uncharacterized genetic errors using the AlphaGenome Variant Impact (AVI) score.
Explain Biological Context
Receive AI-generated breakdowns explaining why a variant is highly ranked, pinpointing specific biological disruptions like splicing defects.
Render In-Chat Visualizations
Generate visualizations, such as ref/alt plots, directly inside your chat window without writing a single line of code.
Seamless navigation to Atlas website
The Atlas skill automatically generates parameterized URLs, allowing you to jump straight from your query directly to the relevant tracks on the Atlas website.
Empowering researchers to solve biological mysteries
AlphaGenome is already helping scientists advance their research.
Uncovering rare genomic mysteries
Broad Institute scientist Laura Covill searches for the underlying causes of unexplained rare diseases, but the list of possible genetic changes is vast. Using AlphaGenome’s Variant Impact Score, she found a critical editing error in the DNM1 gene. Backed by the scientific literature, we collaborated with the Broad team to design lab experiments that validated the prediction, successfully reclassifying the variant with the new data. By replacing months of searching and analysis with AI-guided precision, this approach accelerates how quickly scientists can understand certain causes of rare diseases.
“The synergistic approach of using pre-computed AVI scores to prioritise variants from a starting point of millions, followed by visualising the predicted impact of specific variants in Atlas, is a powerful leveraging of both breadth and precision to identify novel interesting candidates for rare disease. As a non-coding specialist, there has never been the same array of tools available to us for in silico non-coding predictions as for protein-coding variants, so I see this as a really important step towards a time when we can recognise the contribution of these regions to rare disease.”
Laura Covill
Broad Institute / GREGoR Consortium
Uncovering the regulatory grammar of the human genome
While every cell contains the complete human genome, cellular identity depends on which genes get turned on and how much. Julia Zeitlinger at the Stowers Institute for Medical Research used AlphaGenome to define the short DNA sequences acting as switches and volume dials. By decoding how these signals turn gene activity up and down in specific cell types, the study helps us better understand the fundamental rules governing cellular identity and gene regulation.
“This is a very difficult problem as every cell type 'speaks a slightly different language' and thus it is hard to know what rules are general. With AlphaGenome, we can quickly query lots of cell types and look for general patterns by which genes are activated and repressed.”
Julia Zeitlinger
Stowers Institute for Medical Research
Unveiling shared genetic drivers across complex conditions
“What excited me about AlphaGenome is that we're no longer limited to understanding how disease risk variants affect gene expression alone. You can take a variant, mutate it in computationally, and understand its effects across the whole regulatory landscape - splicing, chromatin, even how the genome folds. For Alzheimer's, where most risk variants sit in the “dark matter” of the genome, outside of genes, that was huge. It's what allowed us to trace the genetic risk signals of Alzheimer’s out of the brain and into immune and metabolic tissues.”
César Cunha
University of Copenhagen
Alzheimer's disease unfolds in the brain, yet its origins may lie elsewhere in the body. Conditions like obesity and type 2-diabetes are known to raise the risk of Alzheimer's, but untangling the shared biology connecting them has proved difficult. Under the supervision of Tuomas Kilpeläinen at the University of Copenhagen, César Cunha and Marc Pielies Avelli used AlphaGenome to trace how Alzheimer's genetic risk factors operate across the entire body. By scoring variants not only for their effects on gene activity but across the full spectrum of gene regulation, the model helped reveal that many of these genetic signals operate through immune and metabolic tissues, not just the brain. There, AlphaGenome also uncovered a rewiring of the regulatory switches that control genes in immune and metabolic cells, a way for genetic risk to act beyond the brain, and a finding that is reshaping how we think about Alzheimer's disease.
Try AlphaGenome
Accelerate your genomics research
AlphaGenome Atlas UI
A free, interactive portal for visual analysis with zero coding expertise required.
AlphaGenome Skills
Accelerate your genomics research using AlphaGenome Skills on Antigravity.
AlphaGenome API
High-throughput access for computational biologists running large-scale workflows.
AlphaGenome on Google Cloud
Access AlphaGenome for commercial and enterprise workflows on Google Cloud via Model Garden on Gemini Enterprise Agent Platform.