Dataset Information

Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data.

ABSTRACT: Predicting responsible transcription regulators on the basis of transcriptome data is one of the most promising computational approaches to understanding cellular processes and characteristics. Here, we present a novel method employing vast amounts of chromatin immunoprecipitation (ChIP) experimental data to address this issue. Global high-throughput ChIP data was collected to construct a comprehensive database, containing 8 578 738 binding interactions of 454 transcription regulators. To incorporate information about heterogeneous frequencies of transcription factor (TF)-binding events, we developed a flexible framework for gene set analysis employing the weighted t-test procedure, namely weighted parametric gene set analysis (wPGSA). Using transcriptome data as an input, wPGSA predicts the activities of transcription regulators responsible for observed gene expression. Validation of wPGSA with published transcriptome data, including that from over-expressed TFs, showed that the method can predict activities of various TFs, regardless of cell type and conditions, with results totally consistent with biological observations. We also applied wPGSA to other published transcriptome data and identified potential key regulators of cell reprogramming and influenza virus pathogenesis, generating compelling hypotheses regarding underlying regulatory mechanisms. This flexible framework will contribute to uncovering the dynamic and robust architectures of biological regulation, by incorporating high-throughput experimental data in the form of weights.

SUBMITTER: Kawakami E

PROVIDER: S-EPMC4914117 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data.

Kawakami Eiryo E Nakaoka Shinji S Ohta Tazro T Kitano Hiroaki H

Nucleic acids research 20160430 11

Predicting responsible transcription regulators on the basis of transcriptome data is one of the most promising computational approaches to understanding cellular processes and characteristics. Here, we present a novel method employing vast amounts of chromatin immunoprecipitation (ChIP) experimental data to address this issue. Global high-throughput ChIP data was collected to construct a comprehensive database, containing 8 578 738 binding interactions of 454 transcription regulators. To incorp ...[more]

PMID: 27131787

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Project description:BACKGROUND: Transcription factors (TFs) and their binding sites (TFBSs) play a central role in the regulation of gene expression. It is therefore vital to know how the allocation pattern of TFBSs affects the functioning of any particular gene in vivo. A widely used method to analyze TFBSs in vivo is the chromatin immunoprecipitation (ChIP). However, this method in its present state does not enable the individual investigation of densely arranged TFBSs due to the underlying unspecific DNA fragmentation technique. This study describes a site-specific ChIP which aggregates the benefits of both EMSA and in vivo footprinting in only one assay, thereby allowing the individual detection and analysis of single binding motifs. FINDINGS: The standard ChIP protocol was modified by replacing the conventional DNA fragmentation, i. e. via sonication or undirected enzymatic digestion (by MNase), through a sequence specific enzymatic digestion step. This alteration enables the specific immunoprecipitation and individual examination of occupied sites, even in a complex system of adjacent binding motifs in vivo. Immunoprecipitated chromatin was analyzed by PCR using two primer sets - one for the specific detection of precipitated TFBSs and one for the validation of completeness of the enzyme digestion step. The method was established exemplary for Sp1 TFBSs within the egfr promoter region. Using this site-specific ChIP, we were able to confirm four previously described Sp1 binding sites within egfr promoter region to be occupied by Sp1 in vivo. Despite the dense arrangement of the Sp1 TFBSs the improved ChIP method was able to individually examine the allocation of all adjacent Sp1 TFBS at once. The broad applicability of this site-specific ChIP could be demonstrated by analyzing these SP1 motifs in both osteosarcoma cells and kidney carcinoma tissue. CONCLUSIONS: The ChIP technology is a powerful tool for investigating transcription factors in vivo, especially in cancer biology. The established site-specific enzyme digestion enables a reliable and individual detection option for densely arranged binding motifs in vivo not provided by e.g. EMSA or in vivo footprinting. Given the important function of transcription factors in neoplastic mechanism, our method enables a broad diversity of application options for clinical studies.

Dataset Information

Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data.

Publications

Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data.

Similar Datasets

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