Next Generation Sequencing Facilitates Quantitative Analysis of A549 Control and A549 infected with Zika virus Transcriptomes

ABSTRACT: Purpose:The goals of this study to compare NGS-derived transcriptome profiling (RNA-seq) to examine differentially expressed genes berween A549 infected with Zika virus and A549 Control . Methods: A549 cells mRNA profiles of A549 cells-infected with Zika virus and aun-infected A549 cells were generated by deep sequencing, in triplicate, using Illumina Hiseq4000. The mapped reads of each sample were assembled by StringTie (v1.3.1) (Mihaela Pertea.et al. 2016) in a reference-based approach. StringTie uses a novel network flow algorithm as well as an optional de novo assembly step to assemble and quantitate full-length transcripts representing multiple splice variants for each gene locus. Results: Using an optimized data analysis workflow, we mapped about identified 11124 transcripts in the A549 cells of control and Zika virus with Cuffcompare workflow. RNA-seq data confirmed stable expression of 20 known housekeeping genes, and 10 of these were validated with qRT–PCR. Approximately 10% of the transcripts showed differential expression between the control and DV, with a fold change >1 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. Conclusions: Our study represents the first detailed analysis of A549 cells transcriptomes, 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. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

ORGANISM(S): Homo sapiens

PROVIDER: GSE146423 | GEO | 2020/03/06

REPOSITORIES: GEO