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Identification of potential target genes of USP22 via ChIP-seq and RNA-seq analysis in HeLa cells.

ABSTRACT: The ubiquitin-specific protease 22 (USP22) is an oncogene and its expression is upregulated in many types of cancer. In the nucleus, USP22 functions as one subunit of the SAGA to regulate gene transcription. However, the genome-wide USP22 binding sites and its direct target genes are yet clear. In this study, we characterized the potential genomic binding sites of UPS22 and GCN5 by ChIP-seq using specific antibodies in HeLa cells. There were 408 overlapping putative target genes bound by both USP22 and GCN5. Motif analysis showed that the sequences bound by USP22 and GCN5 shared two common motifs. Gene ontology (GO) and pathway analysis indicated that the genes targeted by USP22 and GCN5 were involved in different physiological processes and pathways. Further RNA-seq, GO and pathway analyses revealed that knockdown of UPS22 induced differential expression of many genes that participated in diverse physiological processes, such as metabolic process. Integration of ChIP-seq and RNA-seq data revealed that UPS22 bound to the promoters of 56 genes. These findings may provide new insights into the regulation of USP22 on gene expression during the development of cervical cancer.

SUBMITTER: Gong Z

PROVIDER: S-EPMC6082230 | biostudies-literature | 2018 Apr./Jun

REPOSITORIES: biostudies-literature

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Project description:Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) or microarray hybridization (ChIP-chip) has been widely used to determine the genomic occupation of transcription factors (TFs). We have previously developed a probabilistic method, called TIP (Target Identification from Profiles), to identify TF target genes using ChIP-seq/ChIP-chip data. To achieve high specificity, TIP applies a conservative method to estimate significance of target genes, with the trade-off being a relatively low sensitivity of target gene identification compared to other methods. Additionally, TIP's output does not render binding-peak locations or intensity, information highly useful for visualization and general experimental biological use, while the variability of ChIP-seq/ChIP-chip file formats has made input into TIP more difficult than desired.To improve upon these facets, here we present are fined TIP with key extensions. First, it implements a Gaussian mixture model for p-value estimation, increasing target gene identification sensitivity and more accurately capturing the shape of TF binding profile distributions. Second, it enables the incorporation of TF binding-peak data by identifying their locations in significant target gene promoter regions and quantifies their strengths. Finally, for full ease of implementation we have incorporated it into a web server ( http://syslab3.nchu.edu.tw/iTAR/ ) that enables flexibility of input file format, can be used across multiple species and genome assembly versions, and is freely available for public use. The web server additionally performs GO enrichment analysis for the identified target genes to reveal the potential function of the corresponding TF.The iTAR web server provides a user-friendly interface and supports target gene identification in seven species, ranging from yeast to human. To facilitate investigating the quality of ChIP-seq/ChIP-chip data, the web server generates the chart of the characteristic binding profiles and the density plot of normalized regulatory scores. The iTAR web server is a useful tool in identifying TF target genes from ChIP-seq/ChIP-chip data and discovering biological insights.

Dataset Information

Identification of potential target genes of USP22 via ChIP-seq and RNA-seq analysis in HeLa cells.

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