GSE106306
TBX3 promotes proliferation of papillary thyroid carcinoma cells through facilitating PRC2-mediated p57KIP2 repression
Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived thyroid cancer cell line k1 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  shCtrl and shTBX3 cells were generated by deep sequencing, in duplicate, using BGISEQ-500. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods:Bowtie2 to map clean reads to reference gene and use HISAT to reference genome.Bowtie2 parameters forSE reads:-q--phred64--sensitive--dpad0--gbar and HISTAparameters forSE reads:-p8--phred64--sensitive-I1-X 1000. qRT–PCR validation was performed using SYBR Green assays Results: Using an optimized data analysis workflow, we mapped about 24 million sequence reads per sample to the human genome (build hg19) and identified 20511 transcripts in K1-shCtrl and K1-shTBX3 cells with RSEM workflow.  Approximately 5% of the transcripts showed differential expression between  K1-shCtrl and K1-shTBX3 cells, with a fold change =1.5 and p value <0.01. Altered expression of 16 candidate 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  thyroid cancer function. Conclusions: Our study represents the first detailed analysis of  thyroid cancer cell line k1 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: Total mRNA profiles of   K1-shCtrl and K1-shTBX3 cells were generated by deep sequencing, in duplicate, using BGISEQ-500