Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and ZNFX1-overexpresed A549 Cells Transcriptomes
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE132890 | GEO | 2019/08/30
REPOSITORIES: GEO
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Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and ZNFX1-overexpresed A549 Cells Transcriptomes
| PRJNA549405 | ENA
Project description:Genes expression profiles in ZNFX1 overexpression in Rig-I-/- cells with or without poly I:C stimulation in A549 cells.
2019-08-30 | GSE132892 | GEO
Project description: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.
2020-03-06 | GSE146423 | GEO
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of A549 Control and A549 infected with Zika virus Transcriptomes
| PRJNA610552 | ENA
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.
| S-EPMC3233386 | biostudies-literature
Project description:We aimed to clarify the influence of IRX5 overexpression on the transcripts of human bone marrow-derived mesenchymal stem cells (hMSCs). We overexpressed IRX5 in hMSCs by Lentivirus. RNA of CTRL and IRX5-overexpressing hMSCs were generated by deep sequencing, in triplicate, using Illumina NovaSeq 6000. The Sample read counts were summarized by StringTie2 with the GENCODE V32 annotation file. Differential expression analysis was determined based on read counts by using DESeq2. As a results, we found that adipogenesis-associated genes were up-regulated in the Plvx/IRX5 group; whereas glycolysis-associated genes were down-regulated compared to control hMSCs.
2022-01-31 | GSE195679 | GEO
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.
2016-07-04 | E-GEOD-67344 | biostudies-arrayexpress
Project description:Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived normal human kidney 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 The kidney tissue was immediately placed and stored in RNAlater® (Ambion), according to the manufacturer’s instruction. The tissue was manually microdissected under microscope in RNAlater® pool for glomerular and tubular compartment. Dissected tissue was homogenized and RNA was prepared using RNAeasy mini columns (Qiagen, Valencia, CA, US), according to the manufacturer’s instructions. RNA quality and quantity were determined using the Laboratory-on-Chip Total RNA PicoKit Agilent BioAnalyzer. Only samples without evidence of degradation were further used (RNA Integrity Number >6).
2014-08-06 | E-GEOD-60119 | biostudies-arrayexpress
Project description:The goal of this study is to analyze the transcripts regulated by ZEB1.
2017-08-10 | GSE102337 | GEO
Project description:Purpose: To identify differentially expressed genes regulated by cystine. Methods: HCT116 or RKO cells were cultured for 48 hours in cystine-free or 25μM cystine-containing conditional media, and three independent samples were collected by Trizol reagent and subjected to mRNA-sequencing by the LC Bio (Zhejiang, China) and data analysis Results: we identified cystine upregulated 145 genes and downregulated 169 genes in both HCT116 and RKO cells. GO enrichment analysis revealed that cystine regulated biological functions of G1/S transition of mitotic cell cycle and regulation of DNA replication biosynthetic process.In addition, KEGG enrichment analysis showed that mammalian target of rapamycin (mTOR) signaling pathway, a well-known nutrient sensor, was regulated by cystine. Furthermore,we noticed that SESN2 was one of the most significantly downregulated genes by cystine in both cell lines, and confirmed that cystine activates mTORC1 via the GCN2-ATF4-SESN2 axis in colon cancer cells. Conclusions: Our study established that cystine activates mTORC1 through GCN2-ATF4-SESN2 axis.
2021-04-16 | GSE157894 | GEO