ArticleNature genetics2025
Nucleotide dependency analysis of genomic language models detects functional elements.
Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Article
- Intron location and sequence modulate gene expression in Yarrowia lipolytica.Nucleic acids research · 2026Article
- An RNA Language Model trained on sequence alone reveals the structural logic of Internal Ribosome Entry Sites.bioRxiv : the preprint server for biology · 2026Article
- What does it take to learn the rules of RNA base pairing? A lot less than you may think.Communications biology · 2026Article
- The DNA dialect: a comprehensive guide to pretrained genomic language models.Molecular systems biology · 2026Review
- In silico genome transplants and the cis-regulatory basis of biodiversity.Trends in genetics : TIG · 2026Review
- Short-Context Regulatory DNA Language Models with Motif-Discovery Regularization.bioRxiv : the preprint server for biology · 2026Article
- Predicting dynamic expression patterns in budding yeast with a fungal DNA language model.Research square · 2025Article
- Uncovering the Mechanistic Landscape of Regulatory DNA with Deep Learning.bioRxiv : the preprint server for biology · 2025Article
- Nucleotide dependency analysis of genomic language models detects functional elements.Nature genetics · 2025Article
- Predicting dynamic expression patterns in budding yeast with a fungal DNA language model.bioRxiv : the preprint server for biology · 2025Article
- Investigating the performance of foundation models on human 3'UTR sequences.Nucleic acids research · 2025Article
- In silico prediction of variant effects: promises and limitations for precision plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Orthrus: Towards Evolutionary and Functional RNA Foundation Models.bioRxiv : the preprint server for biology · 2025Article
- Recipes and ingredients for deep learning models of 3D genome folding.Current opinion in genetics & development · 2025Review
- Benchmarking DNA Sequence Models for Causal Regulatory Variant Prediction in Human Genetics.bioRxiv : the preprint server for biology · 2025Article
- Interpreting deep neural networks for the prediction of translation rates.BMC genomics · 2024Article
- Article
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8 authors.
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Abstract
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.
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