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Effect of the twelve isoforms of Hepatocyte nuclear factor 4 alpha on HCT116 cell line transcriptome

ABSTRACT: The nuclear receptor HNF4alpha is regulating a wide set of genes associated with development, cell differentiation, inflammation and metabolism. In human, 12 variants of HNF4α can be expressed by the use of two promoters and by alternative splicing. Until now, the characterization of this transcription factor has ignored this diversity and has remained confined to the study of a fraction of the isoforms. We therefore wanted to clarify the situation by specifically characterizing the transcriptional functions of the 12 isoforms of HNF4α. We have generated for this purpose stable lines expressing each isoform of HNF4α in HCT 116 cells. The expression of each isoform was then induced for 48 hours and the whole transcriptome was analyzed by RNA sequencing. The transcriptome associated with each specific isoform was then compared to empty control cells to determine the specific transcriptional functions of HNF4alpha's isoforms.

ORGANISM(S): Homo sapiens

PROVIDER: GSE125852 | GEO | 2019/06/28

REPOSITORIES: GEO

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Project description:HNF4α is a nuclear receptor regulating the transcription of genes involved mainly in development, cell differentiation and metabolism. Opposite functions for the two classes of P1 and P2 isoforms of HNF4α have recently been highlighted. These classes include 12 variants of HNF4α that can be expressed by the use of two promoters and by alternative splicing. Until now, the characterization of this transcription factor has ignored this diversity and has remained confined to the study of a fraction of the isoforms. We therefore wanted to clarify the situation by specifically characterizing the transcriptional functions of the 12 isoforms of HNF4α. We have generated for this purpose stable lines expressing each isoform of HNF4α in HCT 116 cells. We analyzed the whole transcriptome associated with each isoform by sequencing RNA, as well as their proteome by a BioID approach coupled to quantitative mass spectrometry. We noted major differences in the transcriptional function of the 12 isoforms. The α4, α5 and α6 isoforms have been characterized for the first time, and show a greatly reduced transcriptional potential. We have shown that these isoforms are unable to recognize the consensus response element of HNF4α. The α1 and α2 isoforms are the most potent regulators of gene expression, while the α3 isoform exhibits significantly reduced activity. Several transcription factors and coregulators have been identified as potential specific partners for certain HFH4α isoforms. The IRF-2BP2 co-repressor interacts specifically with isoforms which include the long form of the F domain of HNF4α. This specific interaction could explain the large number of genes modulated negatively by α1 and α2 compared to α3. The analysis integrating the vast amount of transcriptomic and proteomic data allows the identification of transcriptional regulatory mechanisms specific to certain isoforms, demonstrating the importance of considering all isoforms which can have diverse functions.

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived HCT-116 cell transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. Methods: HCT-116 cell mRNA profiles of HCT-116-GOLPH3-Vector and HCT-116-GOLPH3-Overepression were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results: RNA sequencing (RNA-seq) was used to investigate gene expression in HCT-116-PMSCV-Vector and HCT-116-PMSCV GOLPH3 cells, while Gene Ontology (GO) was used to annotate the various functional genes. By comparing the differentially expressed genes, we noticed that GOLPH3 was associated with EMT. Gene set enrichment analysis (GSEA) analysis of the RNA-seq results based on the GSE77953 dataset was performed to investigate the biological functions of HCT-116-PMSCV-Vector and HCT-116-PMSCV-GOLPH3 cells. The findings suggested that GOLPH3 expression was positively associated with colon cancer cell autophagy. Signal pathway enrichment was next analyzed based on the differential expression of genes between HCT-116-PMSCV-Vector and HCT-116-PMSCV-GOLPH3 cells, as examined by RNA-seq. Notably, GOLPH3 has correlated with the PI3K/Akt signaling pathway. Conclusions: Our study represents the first detailed analysis of HCT-116 cell transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

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Effect of the twelve isoforms of Hepatocyte nuclear factor 4 alpha on HCT116 cell line transcriptome

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