Similar Datasets
Project description:Identifying differentially expressed genes in Zmat3 knockout cells
| PRJNA607207 | ENA
Project description:The goal of the study was to identify RNAs bound by Zmat3 using eCLIP.
2020-11-06 | GSE145555 | GEO
Project description:Transcriptional activation of target genes is essential for TP53-mediated tumour suppression, though the roles of the diverse TP53-activated target genes in tumour suppression remains poorly understood. Knockdown of Zmat3, an RNA-binding zinc-finger protein involved in regulating alternative splicing, in haematopoietic cells by shRNA caused leukaemia only with the concomitant absence of the Puma and p21, the critical effectors of Trp53-mediated apoptosis and cell cycle arrest respectively. We were interested to further investigate the role of ZMAT3 in tumour suppression beyond the haematopoietic system. Therefore, we generated Zmat3 knockout and compound gene knockout mice, lacking Zmat3 and p21, Zmat3 and Puma or all three genes. Puma-/-p21-/-Zmat3-/- triple knockout mice developed tumours at a significantly higher frequency compared to wild-type, Puma-/-Zmat3-/- or p21-/-Zmat3-/-deficient mice. Interestingly, we observed that the triple knockout and Puma-/-Zmat3-/- double deficient animals succumbed to lymphoma, while p21-/-Zmat3-/- animals developed mainly solid cancers. This analysis suggests that in addition to ZMAT3 loss, additional TRP53-regulated processes must be disabled simultaneously for TRP53-mediated tumour suppression to fail. Our findings reveal that the absence of different TRP53 regulated tumour suppressive processes changes the tumour spectrum, indicating that different TRP53 tumour suppressive pathways are more critical in different tissues.
2023-11-28 | GSE248747 | GEO
Project description:Purpose: p53 is a well-studied protein in which the activation of its main targets is not enough to explain its tumor suppressor effect. Aiming to search for direct p53 targets that mediate less studied processes within p53 pathway, like post-transcriptional regulation, we selected ZMAT3 as the RNA-binding protein most upregulated by p53 activation. Methods: We investigated ZMAT3 targets by using PAR-CLIP and RNA-seq in colorectal cancer cell line HCT116. Results.txt: We found that ZMAT3 binds to ~5000 genes mainly in their introns. It also causes alternative splicing and CD44 was its mostly altered target. ZMAT3 knock-down increased CD44v2-v10 and CD44v3-v10, but decreased CD44s expression. Increased survival and clonogenicity was observed upon knock-down of ZMAT3, which was rescued upon concurrent knock-down of CD44v Conclusions: We propose that ZMAT3 regulates splicing of CD44 following activation by p53, which upregulates CD44s at the expense of CD44v isoforms and leads to a decrease tumorigenicity.
2020-12-18 | GSE150717 | GEO
Project description:Purpose: p53 is a well-studied protein in which the activation of its main targets is not enough to explain its tumor suppressor effect. Aiming to search for direct p53 targets that mediate less studied processes within p53 pathway, like post-transcriptional regulation, we selected ZMAT3 as the RNA-binding protein most upregulated by p53 activation. Methods: We investigated ZMAT3 targets by using PAR-CLIP and RNA-seq in colorectal cancer cell line HCT116. Results.txt: We found that ZMAT3 binds to ~5000 genes mainly in their introns. It also causes alternative splicing and CD44 was its mostly altered target. ZMAT3 knock-down increased CD44v2-v10 and CD44v3-v10, but decreased CD44s expression. Increased survival and clonogenicity was observed upon knock-down of ZMAT3, which was rescued upon concurrent knock-down of CD44v Conclusions: We propose that ZMAT3 regulates splicing of CD44 following activation by p53, which upregulates CD44s at the expense of CD44v isoforms and leads to a decrease tumorigenicity.
2020-12-18 | GSE150716 | GEO
Project description:Purpose: p53 is a well-studied protein in which the activation of its main targets is not enough to explain its tumor suppressor effect. Aiming to search for direct p53 targets that mediate less studied processes within p53 pathway, like post-transcriptional regulation, we selected ZMAT3 as the RNA-binding protein most upregulated by p53 activation. Methods: We investigated ZMAT3 targets by using PAR-CLIP and RNA-seq in colorectal cancer cell line HCT116. Results: We found that ZMAT3 binds to ~5000 genes mainly in their introns. It also causes alternative splicing and CD44 was its mostly altered target. ZMAT3 knock-down increased CD44v2-v10 and CD44v3-v10, but decreased CD44s expression. Increased survival and clonogenicity was observed upon knock-down of ZMAT3, which was rescued upon concurrent knock-down of CD44v Conclusions: We propose that ZMAT3 regulates splicing of CD44 following activation by p53, which upregulates CD44s at the expense of CD44v isoforms and leads to a decrease tumorigenicity.
2020-12-18 | GSE150715 | GEO
Project description:RNA sequencing (RNA-Seq) enables the measurement and comparison of gene expression with isoform-level quantification. Differences in the effect of each isoform may make traditional methods, which aggregate isoforms, ineffective. Here, we introduce a variance component-based test that can jointly test multiple isoforms of one gene to identify differentially expressed (DE) genes, especially those with isoforms that have differential effects. We model isoform-level expression data from RNA-Seq using a negative binomial distribution and consider the baseline abundance of isoforms and their effects as two random terms. Our approach tests the global null hypothesis of no difference in any of the isoforms. The null distribution of the derived score statistic is investigated using empirical and theoretical methods. The results of simulations suggest that the performance of the proposed set test is superior to that of traditional algorithms and almost reaches optimal power when the variance of covariates is large. This method is also applied to analyze real data. Our algorithm, as a supplement to traditional algorithms, is superior at selecting DE genes with sparse or opposite effects for isoforms.
| S-EPMC5592911 | biostudies-literature
Project description:Differential expressed (DE) genes analysis is valuable for understanding comparative transcriptomics between cells, conditions or time evolution. However, the predominant way of identifying DE genes is to use arbitrary threshold fold or expression changes as cutoff. Here, we developed a more objective method, Scatter Overlay or ScatLay, to extract and graphically visualize DE genes across any two samples by utilizing their pair-wise scatter or transcriptome-wide noise, while factoring replicate variabilities. We tested ScatLay for 3 cell types: between time points for Escherichia coli aerobiosis and Saccharomyces cerevisiae hypoxia, and between untreated and Etomoxir treated Mus Musculus embryonic stem cell. As a result, we obtain 1194, 2061 and 2932 DE genes, respectively. Next, we compared these data with two widely used current approaches (DESeq2 and NOISeq) with typical twofold expression changes threshold, and show that ScatLay reveals significantly larger number of DE genes. Hence, our method provides a wider coverage of DE genes, and will likely pave way for finding more novel regulatory genes in future works.
| S-EPMC7566603 | biostudies-literature
Project description:Kawasaki disease (KD) is an acute systemic immune vasculitis caused by infection, and its etiology and underlying mechanisms are not completely clear. This study aimed to identify differentially expressed genes (DEGs) with diagnostic and treatment potential for KD using bioinformatics analysis. In this study, three KD datasets (GSE68004, GSE73461, GSE18606) were downloaded from the Gene Expression Omnibus (GEO) database. Identification of DEGs between normal and KD whole blood was performed using the GEO2R online tool. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of DEGs was undertaken with Metascape. Analysis and visualization of protein-protein interaction networks (PPI) were carried out with STRING and Cytoscape. Lastly, miRNA-genes regulatory networks were built by Cytoscape to predict the underlying microRNAs (miRNAs) associated with DEGs. Overall, 269 DEGs were identified, including 230 up-regulated and 39 down-regulated genes. The enrichment functions and pathways of DEGs involve regulation of defense response, inflammatory response, response to bacterium, and T cell differentiation. KEGG analysis indicates that the genes were significantly enriched in Neutrophil extracellular trap formation, TNF signaling pathway, Cytokine-cytokine receptor interaction, and Primary immunodeficiency. After combining the results of the protein-protein interaction (PPI) network and CytoHubba, 9 hub genes were selected, including TLR8, ITGAX, HCK, LILRB2, IL1B, FCGR2A, S100A12, SPI1, and CD8A. Based on the DEGs-miRNAs network construction, 3 miRNAs including mir-126-3p, mir-375 and mir-146a-5p were determined to be potential key miRNAs. To summarize, a total of 269 DEGs, 9 hub genes and 3 miRNAs were identified, which could be considered as KD biomarkers. However, further studies are needed to clarify the biological roles of these genes in KD.
| S-EPMC9763244 | biostudies-literature