Nucleotide dependency analysis of genomic language models detects functional elements

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Bibliographic Details
Title: Nucleotide dependency analysis of genomic language models detects functional elements
Authors: Tomaz da Silva, Pedro, Karollus, Alexander, Hingerl, Johannes, Galindez, Gihanna Sta Teresa, Wagner, Nils, Hernandez-Alias, Xavier, Incarnato, Danny, Gagneur, Julien
Source: Nature Genetics. 57(10):2589-2602
Publisher Information: Nature Publishing Group, 2025.
Publication Year: 2025
Subject Terms: Genetic, Models, Humans, Nucleic Acid Conformation, Genome/genetics, RNA/genetics, Nucleotides/genetics, Genomics/methods
Description: Deciphering how nucleotides in genomes encode regulatory instructions and molecular machines is a long-standing goal. Genomic language models (gLMs) implicitly capture functional elements and their organization from genomic sequences alone by modeling probabilities of each nucleotide given its sequence context. However, discovering functional genomic elements from gLMs has been challenging due to the lack of interpretable methods. Here we introduce nucleotide dependencies, which quantify how nucleotide substitutions at one genomic position affect the probabilities of nucleotides at other positions. We demonstrate that nucleotide dependencies are more effective at indicating the deleteriousness of genetic variants than alignment-based conservation and gLM reconstruction. Dependency analysis accurately detects regulatory motifs and highlights bases in contact within RNAs, including pseudoknots and tertiary structure contacts, revealing new, experimentally validated RNA structures. Finally, we leverage dependency maps to reveal critical limitations of several gLM architectures and training strategies. Altogether, nucleotide dependency analysis opens a new avenue for discovering and studying functional elements and their interactions in genomes.
Document Type: Article
Language: English
ISSN: 1061-4036
DOI: 10.1038/s41588-025-02347-3
Access URL: https://research.rug.nl/en/publications/3d5add9d-35f2-4c78-a3dc-7f9d53852abb
https://hdl.handle.net/11370/3d5add9d-35f2-4c78-a3dc-7f9d53852abb
Rights: CC BY
Accession Number: edsair.dris...01423..007b4be2ec1068d0860634f57a886354
Database: OpenAIRE
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