GSE113648
Quantitative whole transcriptomics sequencing of progeria-derived cells point to a key role of nucleotide metabolism in premature aging
Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived PG and their healthy progenitor lines transcriptome profiling (RNA-seq) to proteomic methods (iTRAQ) and to evaluate these protocols for optimal high-throughput data analysis Methods: The raw RNA-Seq reads for each sample were aligned to the reference human genome browser (GRCh38.p12 assembly) using Bowtie2 and Tophat2. Results: An average of 23 million paired-end 100-bp reads was obtained per sample. After alignment, raw sequence read depths were converted to estimate transcript abundance measured as fragments per kilobase of exons per million (FPKM), and the cuffinks of differentially expressed genes and transcripts were calculate with Cuffdidd. Conclusions: Our study represents a detailed analysis of human PG lines 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 pathological line. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Overall design: The sequencing data was generated on Hiseq 1500 on a rapid mode flow cell from Illumina.