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Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and ZNFX1-overexpresed A549 Cells Transcriptomes

ABSTRACT: Analysis of the pathways among genes significantly up-regulated or down-regulated between ZNFX1 overexpressed cells and wild-type A549 cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE132890 | GEO | 2019/08/30

REPOSITORIES: GEO

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Project description:PurposeNext-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.MethodsRetinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl(-/-)) mice 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.ResultsUsing 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 a goodness of fit (R(2)) 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.ConclusionsOur 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.

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of gene regulon. The goal of this study is to investigate the genes regulated by Rsp in MRSA BD02-25 Methods: mRNA profiles of wild-type (WT) and Rsp knockout (â³Rsp) MRSA at mid-logarithmic growth phase (4h) were generated by deep sequencing, respectively in duplicate samples, using the Hiseq2000 (Illumina, CA) sequencer. The sequence reads that passed quality filters were aligned to S. aureus COL (RefSeq accession number NC_002951.2) using the Burrows-Wheeler Alignment tool (BWA) followed by ANOVA (ANOVA). Only the consistent data between the two WT or mutant samples were reserved for further analysis. qRTâPCR validation was performed using SYBR Green assays. Results: Using an optimized data analysis workflow, RNA-seq analyses revealed that 328 genes were up-regulated and 176 genes were down-regulated in â³rsp compared with wild type. In order to explain the major relevant changes in â³rsp compare to wild-type, the differential expressed genes obtained in RNA-seq with three biological replicates were used to construct a regulation network. 108 up-regulated genes and 33 down-regulated genes in RNA-seq data had gathered in the protein-protein interaction network. 15 modules of biological processes were responsible, including ribosome, metabolism, biofilm formation, cell wall degradation, cytolysis, two-component system and so on. Biological processes related to biofilm formation, such as cell wall degradation and metabolism were up regulated, indicating that the defense systems were activated. However, the genes that responsible for the two-component system and cytolysis were down regulated, suggesting a possible pathway how Rsp controls the virulence. Conclusions: Our data provide new information to the virulence regulatory network in S. aureus. mRNA profiles of wild-type (WT) and Rsp knockout (â³Rsp) MRSA were generated by deep sequencing, in duplicate, using the Hiseq2000 (Illumina, CA) sequencer.

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Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and ZNFX1-overexpresed A549 Cells Transcriptomes

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