Mullen Daniel J, Wu Zexun, Nelson-Moore Ethan, Cao Huan, Han Lauren, Offringa Ite A, Rhie Suhn K
Department of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Bioinformatics. 2025 Aug 2;41(8). doi: 10.1093/bioinformatics/btaf435.
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.
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.
目前缺乏可供研究人员广泛使用的生物信息学工具来识别调控细胞类型特异性调控元件(RE)的转录因子(TF)。为了解决这一问题,我们开发了利用表观遗传特征追踪调控元件网络(TENET)的R/Bioconductor软件包。通过收集来自多种细胞系、原代细胞和组织的数百个组蛋白标记和开放染色质数据集,并将这些特征与匹配的DNA甲基化和基因表达数据进行比较,TENET可识别与特定细胞类型相关的TF和RE。此外,我们还开发了利用基序、临床信息以及其他基因组和染色质构象捕获数据集来探究研究结果的方法,并将其应用于泛癌数据,突出了与十种不同癌症类型相关的TF和RE。TENET使研究人员能够更好地表征感兴趣细胞类型的三维表观基因组,以用于未来的临床应用。