Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-siRNA and c-Myc-siRNA cells' Transcriptomes in lymphoma
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA523180 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8591250_1.fastq.gz | Fastqsanger.gz | |||
| SRR8591250_2.fastq.gz | Fastqsanger.gz | |||
| SRR8591251_1.fastq.gz | Fastqsanger.gz | |||
| SRR8591251_2.fastq.gz | Fastqsanger.gz | |||
| SRR8591252_1.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in Ctrl-siRNA and c-Myc-siRNA lymphoma cells by using NGS-derived lymphoma transcriptome profiling (RNA-seq). Methods: Ctrl-siRNA and c-Myc-siRNA cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 v2.1, IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, DEGseq v1.18.0 was used for differential gene expression analysis between two samples with non biological replicates and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents the first detailed analysis of Ctrl-siRNA and c-Myc-siRNA cells' 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.
2020-10-02 | GSE126739 | GEO
Project description:To identify c-myc target genes by siRNA transfection in a lymphoma cell line. Keywords: time series design OCI-Ly10 cells were transfected with c-myc siRNA pool versus control siRNA or buffer for a total of 4 microarrays.
2010-05-26 | E-GEOD-7245 | biostudies-arrayexpress
Project description:To identify c-myc target genes by siRNA transfection in a lymphoma cell line. Keywords: time series design
2008-03-01 | GSE7245 | GEO
Project description:Background: MYC is a transcription factor encoded by the c-MYC gene (thereafter termed MYC). MYC is key transcription factor involved in many central cellular processes including ribosomal biogenesis. MYC is overexpressed in the majority of human tumours including aggressive B-cell lymphoma especially Burkitt's lymphoma. Although Burkitt's lymphoma is a highlight example for MYC overexpression due to a chromosomal translocation, no global analysis of MYC binding sites by chromatin immunoprecipitation (ChIP) followed by global next generation sequencing (ChIP-Seq) has been conducted so far in Burkitt's lymphoma. Methodology/Principal Findings: ChIP-Seq was performed with a MYC-specific antibody giving rise to 7,054 predicted MYC binding sites after bioinformatics analysis of a total of 19 million sequence reads. In line with previous findings, binding sites accumulate in gene sets known to be involved in the ribosomal biogenesis, histone acetyltransferase and methyltransferase complexes and the cell cycle demonstrating a regulatory role of MYC in these processes. Unexpectedly, MYC binding sites also accumulate in genes typically expressed in mature B-cells. To assess the functional consequences of altered MYC binding, the ChIP-Seq data were supplemented with siRNA mediated knock-downs of MYC in BL cell lines followed by gene expression profiling. Interestingly, amongst others, genes involved in B-cell function were up-regulated in response to MYC silencing. Conclusion/Significance: The 7,054 MYC-binding sites identified by our ChIP-Seq approach greatly extend the knowledge regarding MYC binding in Burkitt's lymphoma and sheds further light on the enormous complexity of the MYC regulatory network. Especially our observation that (i) many B-cell relevant genes are targeted by MYC and (ii) that MYC down-regulation leads to an up-regulation of B-cell genes highlights an interesting aspect of BurkittM-BM-4s lymphoma biology. [ChIP-Seq] Analysis of MYC DNA binding sites by ChiP-Seq in 5 BurkittM-BM-4s lymphoma cell lines (Raji, Ramos, Blue1, BL41, CA46) [mRNA expression profiling] siRNA-mediated knock-down of MYC was done employing the BL cell lines Raji, BL41 and Blue1 in order to detect MYC-driven gene expression changes. For this purpose, the cells were Amaxa-transfected using MYC smart pool siRNA and control siRNA (Thermo Scientific/Dharmacon, Erembodegem, Belgium), respectively.
2011-11-28 | E-GEOD-30726 | biostudies-arrayexpress
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in Ctrl-Cas9 and TRIB3-Cas9 lymphoma cells by using NGS-derived lymphoma transcriptome profiling (RNA-seq). Methods: Ctrl-Cas9 and TRIB3-Cas9 cells' mRNA profiles 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 following methods: Alignment by using HISAT2 v2.1, IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, DEGseq v1.18.0 was used for differential gene expression analysis between two samples with non biological replicates and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents the first detailed analysis of Ctrl-Cas9 and TRIB3-Cas9 cells' 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.
2020-10-01 | GSE117128 | GEO
Project description:RNA-seq analysis in fibroblast IMR90 CTRL/MYC/MYC+SF3A3 KD
| PRJNA615007 | ENA
Project description:RNA-seq analysis in fibroblast IMR90 CTRL/MYC/MYC+SF3B1 KD
| PRJNA783790 | ENA
Project description:Background: MYC is a transcription factor encoded by the c-MYC gene (thereafter termed MYC). MYC is key transcription factor involved in many central cellular processes including ribosomal biogenesis. MYC is overexpressed in the majority of human tumours including aggressive B-cell lymphoma especially Burkitt's lymphoma. Although Burkitt's lymphoma is a highlight example for MYC overexpression due to a chromosomal translocation, no global analysis of MYC binding sites by chromatin immunoprecipitation (ChIP) followed by global next generation sequencing (ChIP-Seq) has been conducted so far in Burkitt's lymphoma. Methodology/Principal Findings: ChIP-Seq was performed with a MYC-specific antibody giving rise to 7,054 predicted MYC binding sites after bioinformatics analysis of a total of 19 million sequence reads. In line with previous findings, binding sites accumulate in gene sets known to be involved in the ribosomal biogenesis, histone acetyltransferase and methyltransferase complexes and the cell cycle demonstrating a regulatory role of MYC in these processes. Unexpectedly, MYC binding sites also accumulate in genes typically expressed in mature B-cells. To assess the functional consequences of altered MYC binding, the ChIP-Seq data were supplemented with siRNA mediated knock-downs of MYC in BL cell lines followed by gene expression profiling. Interestingly, amongst others, genes involved in B-cell function were up-regulated in response to MYC silencing. Conclusion/Significance: The 7,054 MYC-binding sites identified by our ChIP-Seq approach greatly extend the knowledge regarding MYC binding in Burkitt's lymphoma and sheds further light on the enormous complexity of the MYC regulatory network. Especially our observation that (i) many B-cell relevant genes are targeted by MYC and (ii) that MYC down-regulation leads to an up-regulation of B-cell genes highlights an interesting aspect of Burkitt´s lymphoma biology.
2011-11-28 | GSE30726 | GEO
Project description:N-Myc oncoprotein induces neuroblastoma by modulating gene transcription, and long noncoding RNAs exert biological effects by regulating gene expression. We analysed whether N-Myc and the long noncoding RNA lncMycN mediate the expression of common subsets of genes. Neuroblastoma Kelly cells were transfected with control siRNA, N-Myc siRNA-1, N-Myc siRNA-2, lncMycN siRNA-1 or lncMycN siRNA-2. RNA was extracted from the cells 48 hours after siRNA transfections, and subjected to differential gene expression studies with Affymetrix microarrays.
2015-03-31 | E-GEOD-50959 | biostudies-arrayexpress
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-Cas9 and TRIB3-Cas9 cells' Transcriptomes in lymphoma
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