Pluto Bioinformatics

GSE129295: Next Generation Sequencing Facilitates Quantitative Analysis of bladder cancer cells (T24) with constitutively active RhoC mutant (Q63E) overexpression and vector control (VEC) Transcriptomes

Bulk RNA sequencing

Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived constitutively active RhoC mutant (Q63E) overexpressed bladder cancer cells (T24) transcriptome profiling (RNA-seq) to quantitative reverse transcription polymerase chain reaction (qRTPCR) methods and to evaluate protocols for optimal high-throughput data analysis; Methods: Bladder cancer cells mRNA profiles of vector(VEC) and RhoC constitutively active mutant (Q63E) stably expressing T24 cells were generated by deep sequencing, in triplicate, using Illumina HiSeqX Ten. The sequence reads that passed quality filters were analyzed at the transcript isoform level with the method: Hisat2 2.1.0 followed by StringTie. qRTPCR validation was performed using TaqMan and SYBR Green assays; Results: Using an optimized data analysis workflow, we mapped about 50 million sequence reads per sample to the hunam reference genome and identified 209,506 transcripts in the vector(VEC) and constitutively active RhoC mutant (Q63E) transduced bladder cancer cells (T24 cells) with Hisat2 2.1.0 workflow. RNA-seq data confirmed stable expression of known housekeeping genes. Approximately 3% of the transcripts showed differential expression between the vector(VEC) and constitutively active RhoC mutant (Q63E) transduced bladder cancer cells (T24 cells), with a fold change 1.5 and p value <0.05. Altered expression of 13 genes was confirmed with qRTPCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to RhoC function in bladder cancer. Data analysis with Hisat2 2.1.0 workflow revealed a significant overlap yet provided complementary insights in transcriptome profiling.; Conclusions: Our study represents the first detailed analysis of constitutively active RhoC mutant (Q63E) overexpressed bladder cancer cells 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 line. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. SOURCE: Yaxiu Guo (1797798719@qq.com) - Tianjin Medical University