ChIPBase v3.0: the encyclopedia of transcriptional regulations of non-coding RNAs and protein-coding genes

Abstract

Non-coding RNAs (ncRNAs) are emerging as key regulators of various biological processes. Although thousands of ncRNAs have been discovered, the transcriptional mechanisms and networks of the majority of ncRNAs have not been fully investigated. In this study, we updated ChIPBase to version 3.0 (https://rnasysu.com/chipbase3/) to provide the most comprehensive transcriptional regulation atlas of ncRNAs and protein-coding genes (PCGs). ChIPBase has identified ∼151 187 000 regulatory relationships between ∼171 600 genes and ∼3000 regulators by analyzing ∼55 000 ChIP-seq datasets, which represent a 30-fold expansion. Moreover, we de novo identified ∼29 000 motif matrices of transcription factors. In addition, we constructed a novel ‘Enhancer’ module to predict ∼1 837 200 regulation regions functioning as poised, active or super enhancers under ∼1300 conditions. Importantly, we constructed exhaustive coexpression maps between regulators and their target genes by integrating expression profiles of ∼65 000 normal and ∼15 000 tumor samples. We built a ‘Disease’ module to obtain an atlas of the disease-associated variations in the regulation regions of genes. We also constructed an ‘EpiInter’ module to explore potential interactions between epitranscriptome and epigenome. Finally, we designed ‘Network’ module to provide extensive and gene-centred regulatory networks. ChIPBase will serve as a useful resource to facilitate integrative explorations and expand our understanding of transcriptional regulation.

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“…DNA was released from the chromatin‐protein complex and purified using FastPure Cell/Tissue DNA Isolation Mini Kit (DC102‐01, Vazyme). Diluted DNA was futher subjected to PCR using primers (listed in Table S2 , Supporting Information) designed according to ChIP Base 3.0 database prediction, [ 49 ] and quantified using agarose gel electrophoresis, followed by staining with GelRed (TSJ002, Tsingke Biological Technology). A Venn diagram for demonstrating the common transcription factor was generated using an online program (cloud.genepioneer.com).…”

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“…Transcription factors (TFs) binding to Hub MRGs were identified using the CHIPBase database (version 3.0, https://rna.sysu.edu.cn/chipbase/ ) [ 32 ] with a criterion of interactions having a Number of samples found (upstream)≥5. The resulting mRNA-TF network was visualized using Cytoscape software.…”