Next Generation Sequencing Facilitates Quantitative Analysis of Luc976, shVHL61, shKIM1-A1 and shVHL61-KIM1-A1 kidney tubular cell line transcriptomes

Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal 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: mRNA profiles of Luc976, shVHL61, shKIM-1, shVHL61-KIM1A1 human proximal kidney cell line (HK-2) 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-seq data analyzed the differentially expressed genes (DEGs) comparing control, VHL knockdown, KIM-1 knockdown, and VHL-KIM1 double knockdown. Many genes were found and 20 of these were validated with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. There are four distint groups of genes that show different express patterns in different gene knockdown background, with a fold change ≥1.5 and p value <0.05. The functional relationship between VHL and KIM-1 is not likely a simple linear pathway. Some functions are VHL dominant and others are KIM-1 dominants. A majority appears to be independent of each other. Conclusions: Our study represents the detailed analysis transcriptomes in proximal tubule epithelial cell line with different gene knockdown background, 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. mRNA profiles of Luc976, shVHL61, shKIM-1, shVHL61-KIM1A1 human proximal kidney cell line (HK-2)