Dataset Information

Tracing regulatory element networks using epigenetic traits to identify key transcription factors: TENET R/Bioconductor package.

ABSTRACT:

Summary

There is a lack of publicly available bioinformatic tools that can be widely used by researchers to identify transcription factors (TFs) that regulate cell type-specific regulatory elements (REs). To address this, we developed the Tracing regulatory Element Networks using Epigenetic Traits (TENET) R/Bioconductor package. By collecting hundreds of histone mark and open chromatin datasets from a variety of cell lines, primary cells, and tissues, and comparing these features along with matched DNA methylation and gene expression data, TENET identifies TFs and REs linked to a specific cell type. Moreover, we developed methods to interrogate findings using motifs, clinical information, and other genomic and chromatin conformation capture datasets, and applied them to pan-cancer data, highlighting TFs and REs associated with ten different cancer types. TENET enables researchers to better characterize the 3D epigenomes of cell types of interest for future clinical applications.

Availability and implementation

TENET is available at http://bioconductor.org/packages/TENET. Curated functional genomic datasets utilized by TENET are available at http://bioconductor.org/packages/TENET.AnnotationHub. Example datasets are available at http://bioconductor.org/packages/TENET.ExperimentHub.

SUBMITTER: Mullen DJ

PROVIDER: S-EPMC12349384 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature

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Publications

Tracing regulatory element networks using epigenetic traits to identify key transcription factors: TENET R/Bioconductor package.

Mullen Daniel J DJ Wu Zexun Z Nelson-Moore Ethan E Cao Huan H Han Lauren L Offringa Ite A IA Rhie Suhn K SK

Bioinformatics (Oxford, England) 20250801 8

<h4>Summary</h4>There is a lack of publicly available bioinformatic tools that can be widely used by researchers to identify transcription factors (TFs) that regulate cell type-specific regulatory elements (REs). To address this, we developed the Tracing regulatory Element Networks using Epigenetic Traits (TENET) R/Bioconductor package. By collecting hundreds of histone mark and open chromatin datasets from a variety of cell lines, primary cells, and tissues, and comparing these features along w ...[more]

PMID: 40748712

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Project description:Although technological advances now allow increased tumor profiling, a detailed understanding of the mechanisms leading to the development of different cancers remains elusive. Our approach towards understanding the molecular events that lead to cancer is to characterize changes in transcriptional regulatory networks between normal and tumor tissue. Because enhancer activity is thought to be critical in regulating cell fate decisions, we have focused our studies on distal regulatory elements and transcription factors that bind to these elements. Using DNA methylation data, we identified more than 25,000 enhancers that are differentially activated in breast, prostate, and kidney tumor tissues, as compared to normal tissues. We then developed an analytical approach called TENET (Tracing Enhancer Networks using Epigenetic Traits) that correlates DNA methylation levels at enhancers with gene expression to identify more than 800,000 genome-wide links from enhancers to genes and from genes to enhancers. We found more than 1,200 transcription factors to be involved in these tumor-specific enhancer networks. We further characterized several transcription factors linked to a large number of enhancers in each tumor type, including GATA3 in non-basal breast tumors, HOXC6 and DLX1 in prostate tumors, and ZNF395 in kidney tumors. We showed that HOXC6 and DLX1 are associated with different clusters of prostate tumor-specific enhancers and confer distinct transcriptomic changes upon knockdown in C42B prostate cancer cells. We also discovered de novo motifs enriched in enhancers linked to ZNF395 in kidney tumors. Our studies characterized tumor-specific enhancers and revealed key transcription factors involved in enhancer networks for specific tumor types and subgroups. Our findings, which include a large set of identified enhancers and transcription factors linked to those enhancers in breast, prostate, and kidney cancers, will facilitate understanding of enhancer networks and mechanisms leading to the development of these cancers. Examination of FAIRE and ChIP assays in prostate and breast epithelial cells. RNA-seq assays in C42B, prostate cancer cell line after knocking down of TFs (HOXC6, DLX1).

Dataset Information

Tracing regulatory element networks using epigenetic traits to identify key transcription factors: TENET R/Bioconductor package.

Summary

Availability and implementation

Publications

Tracing regulatory element networks using epigenetic traits to identify key transcription factors: TENET R/Bioconductor package.

Similar Datasets

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