MYC is a major determinant of mitotic cell fate
Transcriptomics Dataset
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General Information
AccessionGSE68219
TitleMYC is a major determinant of mitotic cell fate
DescriptionPurpose: To determine global gene expression changes following siRNA knockdown of Myc, Kcnk1, and Snta1 compared to non-targeting siRNAs or mock-transfected cells Methods: Total RNA was processed using the Illumina TruSeq Stranded mRNA Sample Preparation Kit according to manufacturers protocol. Generated cDNA libraries were sequenced using an Illumina HiSeq 2000 sequencer with four biological replicates sequenced per condition using single read, 50 cycle runs. Quality of sequencing reads were assessed using FastQC (Babraham Bioinformatics) and then aligned to a reference genome (hg19, UCSC Genome Browser) using TopHat. Sequencing yielded, on average, 23.7 million unique reads per sample with a 60.7 - 65.7%% mapping rate. Cufflinks was used to generate transcript abundance for each annotated protein-coding gene as Fragments Per Kilobase of transcript per Million mapped reads (FPKM), and statistical analysis and comparison of FPKM values was calculated using R (Bioconductor). Results: Fold changes comparing mock and a non-targeting siRNA were highly congruent. Myc RNAi induced numerous changes, with 955 downregulated genes and 1214 upregulated genes. The effect on Myc itself was relatively modest, possibly reflecting its ability to negatively auto-regulate its own expression. Gene ontology analysis highlighted ribosome biogenesis, metabolism, gene expression, cell cycle, and apoptosis pathways, consistent with known Myc functions. The Kcnk1 siRNA affected 424 genes, with KCNK1 itself one of the most repressed. While gene ontology analysis also highlighted metabolism and biosynthesis pathways, the p-values and fold enrichment scores were substantially lower, indicating that DiM can be suppressed without major effects on metabolism and biosynthesis pathways. The Snta1 siRNA deregulated 575 genes, with SNTA1 itself the most repressed gene. Cell cycle and mitosis-related gene ontology terms feature heavily, consistent with this siRNA accelerating mitotic exit. Interestingly, FoxM1, which drives G2/M gene expression was reduced 1.75-fold, indicating that this siRNA may disrupt mitotic controls by deregulating FoxM1. Conclusions: Global gene expression profiling identifies Egr1 as regulator of mitotic cell fate.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE68219
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE68219
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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