Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma

Diboun, Ilhem; Wernisch, Lorenz; Orengo, Christine A.; Koltzenburg, M

doi:10.1186/1471-2164-7-252

Cited by 526 publications

(414 citation statements)

References 16 publications

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“…Next, limma package [15] in R (V.3.0.1) [16] was used to identify the DEGs between I/R group and control group in the two rat strains. Bayes testing [17] was applied to perform the multiple correction, and p values < 0.05 and |log fold change (FC)| > 1.0 were set as the threshold.…”

Section: Methodsmentioning

confidence: 99%

Revealing the Underlying Mechanism of Ischemia Reperfusion Injury Using Bioinformatics Approach

Shen

Zhou

et al. 2013

Kidney Blood Press Res

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Background/Aims: To reveal the potential pathogenesis of ischemia/reperfusion (I/R) injury. Methods: GSE9943 were downloaded from Genome Expression Omnibus database, including I/R and control samples for both Brown Norway (BN) and Sprague Dawley (SD) rats (3 rats/each group). Then differentially expressed genes (DEGs) were identified by limma package. miRNA-target gene network pairs were predicted using WebGestalt, and protein-protein interactions (PPI) were identified based on STRING database, followed by the networks construction using Cytoscape. Next, ClusterONE was used for modules screening. Furthermore, functional analyses were performed to common DEGs and genes. Results: Totally, 23 common DEGs of BR and SD rats were screened, enriched in functions, such as regulation of cellular protein metabolic process, response to wounding, proteinaceous extracellular matrix, and Enzyme inhibitor activity. MIR-29A, MIR-29B and MIR-29C were discovered both in up- and down-regulated miRNA-target gene networks. Genes in the PPI network were significantly disturbed in p53 signaling, complement and coagulation cascades pathway. Four modules were found significantly disturbed cytochrome P450, Serine/threonine protein kinase, calcium binding and Transient receptor potential channel protein domains. Conclusion: During I/R injury, many genes mutated, interrupting several biological functions, pathways and protein domains. MIR-29C and TRPC6 were suggested to be potential novel targets for this disease.

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Section: Methodsmentioning

confidence: 99%

Revealing the Underlying Mechanism of Ischemia Reperfusion Injury Using Bioinformatics Approach

Shen

Zhou

et al. 2013

Kidney Blood Press Res

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“…Genes that are differentially expressed between populations were detected with the limma package (Diboun et al 2006). Detailed information on data retrieval and analysis are fully described in the Supplemental Material.…”

Section: Population Differentiation Analysismentioning

confidence: 99%

Impact of microRNA regulation on variation in human gene expression

2012

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MicroRNAs (miRNAs) are endogenously expressed small RNAs that regulate expression of mRNAs at the post-transcriptional level. The consequence of miRNA regulation is hypothesized to reduce the expression variation of target genes. However, it is possible that mutations in miRNAs and target sites cause rewiring of the miRNA regulatory networks resulting in increased variation in gene expression. By examining variation in gene expression patterns in human populations and between human and other primate species, we find that miRNAs have stabilized expression of a small number of target genes during primate evolution. Compared with genes not regulated by miRNAs, however, genes regulated by miRNAs overall have higher expression variation at the population level, and they display greater variation in expression among human ethnic groups or between human and other primate species. By integrating expression data with genotypes determined in the HapMap 3 and the 1000 Genomes Projects, we found that expression variation in miRNAs, genetic variants in miRNA loci, and mutations in miRNA target sites are important sources of elevated expression variation of miRNA target genes. A reasonable case can be made that natural selection is driving this pattern of variation.

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“…[15,16] In the significance analysis, P value was adjusted as false discovery rate (FDR) by Benjamini and Hochberg method. [17] Only the miRNAs met with the criteria of |log 2 fold change (FC)| > 1 and FDR < 0.05 were defined as DEmiRNAs.…”

Section: Methodsmentioning

confidence: 99%

Screening the key microRNAs and transcription factors in prostate cancer based on microRNA functional synergistic relationships

Fěng

Gao

et al. 2017

Medicine

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Prostate cancer (PC) is a common neoplasm, and metastatic PC remains incurable. The study aims to screen key microRNAs (miRNAs) and transcription factors (TFs) involved in PC.The miRNA expression profile dataset (GSE45604) was downloaded from Gene Expression Omnibus database, including 50 PC and 10 normal specimens. Differentially expressed miRNAs (DEmiRNAs) were identified through limma package in R, and DEmiRNA–DEmiRNA co-regulation network was constructed based on the number of co-regulated target genes. Functional enrichment analysis of co-regulated target genes was performed using clusterProfiler package in R, and miRNA interactions sharing at least 1 functional term were used to construct a DEmiRNA–DEmiRNA functional synergistic network (MFSN). Based on Transcriptional Regulatory Element Database, cancer-related TFs which were co-regulated by DEmiRNAs were utilized to construct a DEmiRNA–TF regulation network.A total of 66 DEmiRNAs were identified, including 7 up-regulated miRNAs with 18,642 target genes and 59 down-regulated miRNAs with 130,694 target genes. Then, the DEmiRNA–DEmiRNA co-regulation network was constructed, including 66 DEmiRNAs and 2024 co-regulation relationships. In MFSN, hsa-miR-1184, hsa-miR-1207-5p, and hsa-miR-24 had significant functional synergistic relationships. The DEmiRNA–TF network contained 6 up-regulated DEmiRNAs and 4 of them were highlighted, as hsa-miR-1184, hsa-miR-1207-5p, hsa-miR-182, and hsa-miR-183. In subnetwork of the 4 miRNAs, peroxisome proliferative activated receptor, alpha (PPARA) and cyclic AMP-responsive element modulator (CREM) were the critical regulated TFs.Four up-regulated miRNAs (hsa-miR-1207-5p, hsa-miR-1184, hsa-miR-182, and hsa-miR-183) and 2 TFs (PPARA and CREM) were identified as key regulators in PC progression. The above 4 miRNAs might participate in PC progression by targeting PPARA and CREM.

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Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma

Cited by 526 publications

References 16 publications

Revealing the Underlying Mechanism of Ischemia Reperfusion Injury Using Bioinformatics Approach

Revealing the Underlying Mechanism of Ischemia Reperfusion Injury Using Bioinformatics Approach

Impact of microRNA regulation on variation in human gene expression

Screening the key microRNAs and transcription factors in prostate cancer based on microRNA functional synergistic relationships

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