Nucleotide dependency analysis of genomic language models detects functional elements.

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

SUBMITTER: Tomaz da Silva P 

PROVIDER: S-EPMC12513839 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature