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Google Releases AlphaGenome Atlas to Map Human Genome Mutations

Google announced AlphaGenome Atlas on Tuesday, a resource that predicts the functional consequences of all possible single-base variants across the roughly 3-billion-base human genome.

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Google Releases AlphaGenome Atlas to Map Human Genome Mutations

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Google announced AlphaGenome Atlas on Tuesday, a computational resource designed to predict the consequences of every possible single-base variant in the human genome. Because the human genome is approximately 3 billion bases long, substituting each position with the three alternative DNA bases produces a total of 9 billion variants to evaluate.

// in brief
  • AlphaGenome Atlas evaluates 9 billion base substitutions - three alternatives at each of the genome's ~3 billion positions
  • The system targets non-coding DNA, which makes up more than 97 percent of the human genome and controls gene activity
  • Current coverage is limited to human and mouse sequences, trained on a restricted set of heavily studied cell types

The system focuses on non-coding DNA, the portion of the genome that does not encode proteins but accounts for more than 97 percent of its total length. That non-coding region includes regulatory sequences that control where and when genes are active, signals that govern how messenger RNAs are processed, and chromatin-packaging instructions - alongside large stretches of what researchers consider molecular junk left by ancient viral infections. AlphaGenome attempts to characterise sequences across multiple functional dimensions, including gene expression, transcription initiation, chromatin accessibility, histone modifications, transcription factor binding, chromatin contact maps, splice site usage, and splice junction strength.

The tool is currently limited to human and mouse genomes and has been trained on a restricted number of cell types that biologists have studied extensively. Whether AlphaGenome delivers insights beyond what was already embedded in its training data will only become clear once researchers begin applying it at scale.

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Piotr Olszewski

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I edit and publish Quantslant. AI tools help with research, drafts and translation; choosing topics, running the tests, checking facts and the decision to publish are mine, and so is the responsibility for what appears here.

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