DeepCis: A Transformer-based Multi-Omics Framework for Cross-Scale Explainability in Gene Regulatory Element Identification

Dysregulation of gene expression is a hallmark of cancer, wherein cis-regulatory elements(CREs) in non-coding genomic regions play pivotal roles in precise transcriptional control. Although numerous candidate CREs(cCREs) have been identified, the complex regulatory relationships between cCREs and their target genes remain poorly characterized, and current computational approaches are inadequate for large-scale prediction of functional cCREs. Here, we introduce DeepCis, a Transformer-based multi-omics framework that integrates base-level genomic sequence and epigenomics features, as well as region-level 3D chromatin organization to capture regulatory information across multiple scales. DeepCis quantitatively assesses the contribution of individual cCREs to gene regulation and reveals the cooperative interactions among cCREs. Our framework demonstrates robust performance in gene expression prediction, effectively identifying key cCREs and their specific contributions to transcriptional output. The model captures both proximal dominance and distal activity of cCREs and elucidates how 3D chromatin organization constrains gene regulation. Furthtermore, DeepCis successfully identifies transcription factor binding sites associated with active regulation. Through comprehensive multi-level interpretability analyses, we validate the reliability and effectiveness of the DeepCis in deciphering gene regulation mechanisms, providing a powerful foundation for advancing our understanding of transcripgional regulation and enabling applications in precision medicine.