The 11th International Symposium on 3D Genomics

28 / 2024-09-23 11:11:08

Distinct RNA-RNA spatial interaction sub-networks of transcription factors in human hepatoma cells

RIC-seq、TFs、HepG2 cells

We applied the latest RIC-seq technology to study the RNA-RNA interactions in human liver HepG2 cells. Integrating ChIP-seq data with the RIC-seq data, we classified various transcription factors (TFs) into three distinct clusters based on the spatial interaction levels of the uaRNA (RNA transcribed in promoter regions) and eRNA (RNA transcribed in enhancer regions) potentially transcribed by the TF binding sites. We went on to compare the genomic features and clinical significance across different clusters, by further integrating Hi-C, ATAC-seq, and clinical data from liver cancer patients. Our results showed that Cluster I exhibited low spatial interaction and high tissue specificity, tended to reside in the B compartments and nucleoli, contained less densely clustered TF binding sites, and is more correlated with clinical outcomes. In contrast, Cluster III has the highest spatial interaction, is more likely to be found in the A compartments and nuclear speckles, contained more densely clustered TF binding sites, and is more prone to form loops. In Cluster II, the transcription factors MAFK and MAFF showed the lowest spatial interaction and tendency for TF binding sites clustering, located mainly in the B compartments and nucleoli, and are most strongly associated with clinical outcomes. These findings suggested that these transcription factors might play critical roles in regulating gene expression and serve as potential biomarkers and therapeutic targets with significant implications for cancer prognosis and treatment.

In summary, groups of TFs could occur as distinct sub-networks based on spatial proximity of non-coding RNAs transcribed by the TF binding sites. These sub-networks appear to be related to regulatory differences for the TF groups and may partially explain the chromosome compartments/domains.