GSE167573
Next generation sequencing  of TFE3-translocation renal cell carcinoma and adjacent normal tissue transcriptomes
Purpose: The goals of this study are using whole-exome and RNA sequencing technologies on 63 cases with TFE3-tRCC to explore the molecular characteristics of TFE3-tRCC and provide potential effective therapeutic strategies Methods: Total RNA was isolated from each sample (63 tumor samples and 14 paired adjacent normal samples) using Qiagen RNeasy formalin-fixed paraffin-embedded (FFPE) Kit (Qiagen, Hilden, Germany). Strand-specific RNA sequencing libraries were generated using the Whole RNA-seq Lib Prep kit for Illumina (ABclonal, China). Final libraries were sequenced at the Novogene Bioinformatics Institute (Beijing, China) on an Illumina Hiseq X10 platform by a 150bp paired-end reads. The raw RNA-sequencing reads were filtered by FastQC, Reads were aligned using STAR v2.7.0f with default parameters to the Ensembl human genome assembly GRCh37. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl-/- mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl-/- retina, with a fold change =1.5 and p value <0.05. Altered expression of 25 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 retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions: Our study represents the first detailed analysis of retinal 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. Overall design: Renal carcinoma mRNA profiles of 63 tumor tissue with TFE3 fusion and 14 adjacent normal tissue