Home
Deutsch
Advanced Search
Browse by ...
Publication overview
Contact persons
Help
Publ. Version/Full Text
Research data
DOI
PMC
 |
Open Access Hybrid |
|
as soon as is submitted to ZB.
Nucleotide dependency analysis of genomic language models detects functional elements.
Nat. Genet. 57, 2589-2602 (2025)
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.
Altmetric
Additional Metrics?
Edit extra informations
Login
Publication type
Article: Journal article
Document type
Scientific Article
ISSN (print) / ISBN
1061-4036
e-ISSN
1546-1718
Journal
Nature Genetics
Quellenangaben
Volume: 57,
Issue: 10,
Pages: 2589-2602
Publisher
Nature Publishing Group
Publishing Place
New York, NY
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)