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Series GSE129295 Query DataSets for GSE129295
Status Public on Apr 04, 2020
Title Next Generation Sequencing Facilitates Quantitative Analysis of bladder cancer cells (T24) with constitutively active RhoC mutant (Q63E) overexpression and vector control (VEC) Transcriptomes
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary 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 (qRT–PCR) 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. qRT–PCR 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 qRT–PCR, 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.
 
Overall design Bladder cancer mRNA profiles of vector (VEC) and constitutively active RhoC mutant (Q63E) transduced T24 cells were generated by deep sequencing, in triplicate, using Illumina HiSeqX Ten.
 
Contributor(s) Wang Q, Guo Y
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Submission date Apr 03, 2019
Last update date Apr 06, 2020
Contact name Yaxiu Guo
E-mail(s) 1797798719@qq.com
Phone +86 13820890279
Organization name Tianjin Medical University
Department Immunology
Street address 22 Qi Xiangtai Road
City Tianjin
ZIP/Postal code 300070
Country China
 
Platforms (1)
GPL20795 HiSeq X Ten (Homo sapiens)
Samples (6)
GSM3704165 T24 cells_VEC1
GSM3704166 T24 cells_VEC2
GSM3704167 T24 cells_VEC3
Relations
BioProject PRJNA530762
SRA SRP190501

Download family Format
SOFT formatted family file(s) SOFTHelp
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Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE129295_RAW.tar 1.2 Mb (http)(custom) TAR (of TXT)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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