COXPRESdb: a database of coexpressed gene networks in mammals

Obayashi, Takeshi; Hayashi, Shinji; Shibaoka, Masayuki; Saeki, Motoshi; Ohta, Hiroyuki; Kinoshita, Kengo

doi:10.1093/nar/gkm840

Cited by 128 publications

(136 citation statements)

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“…[10], see Methods for details) and mutual ranks of gene co-expression rates (provided by COXPRESdb[11]). We controlled the effect of transcription factors on co-expression using transcription control similarity (TCS, see Methods for details) [12], and used 6,084 genes with both TF annotation (from ITFP[13]) and co-expression information for analyses.…”

Section: Resultsmentioning

confidence: 99%

Human transcriptional interactome of chromatin contribute to gene co-expression

Dong

Chen

et al. 2010

BMC Genomics

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BackgroundTranscriptional interactome of chromatin is one of the important mechanisms in gene transcription regulation. By chromatin conformation capture and 3D FISH experiments, several chromatin interactions cases among sequence-distant genes or even inter-chromatin genes were reported. However, on genomics level, there is still little evidence to support these mechanisms. Recently based on Hi-C experiment, a genome-wide picture of chromatin interactions in human cells was presented. It provides a useful material for analysing whether the mechanism of transcriptional interactome is common.ResultsThe main work here is to demonstrate whether the effects of transcriptional interactome on gene co-expression exist on genomic level. While controlling the effects of transcription factors control similarities (TCS), we tested the correlation between Hi-C interaction and the mutual ranks of gene co-expression rates (provided by COXPRESdb) of intra-chromatin gene pairs. We used 6,084 genes with both TF annotation and co-expression information, and matched them into 273,458 pairs with similar Hi-C interaction ranks in different cell types. The results illustrate that co-expression is strongly associated with chromatin interaction. Further analysis using GO annotation reveals potential correlation between gene function similarity, Hi-C interaction and their co-expression.ConclusionsAccording to the results in this research, the intra-chromatin interactome may have relation to gene function and associate with co-expression. This study provides evidence for illustrating the effect of transcriptional interactome on transcription regulation.

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Section: Resultsmentioning

confidence: 99%

Human transcriptional interactome of chromatin contribute to gene co-expression

Dong

Chen

et al. 2010

BMC Genomics

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“…33 The core region was identified with MCODE, a plugin planted in Cytoscape. 1,44 Protein-protein interaction information was queried from Michigan Molecular Interactions (MiMI).…”

Section: Oncogenic Module Analysismentioning

confidence: 99%

“…33 We created a subnetwork by mapping the genes of the oncogenic module onto the COXPRESdb database (Fig. 8).…”

Section: Validation Of the Oncogenic Module With Other Biological Netmentioning

confidence: 99%

Genomic and transcriptome analysis revealing an oncogenic functional module in meningiomas

Chang

Shi

Russin

et al. 2013

FOC

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Object Meningiomas are among the most common primary adult brain tumors. Although typically benign, roughly 2%–5% display malignant pathological features. The key molecular pathways involved in malignant transformation remain to be determined. Methods Illumina expression microarrays were used to assess gene expression levels, and Illumina single-nucleotide polymorphism arrays were used to identify copy number variants in benign, atypical, and malignant meningiomas (19 tumors, including 4 malignant ones). The authors also reanalyzed 2 expression data sets generated on Affymetrix microarrays (n = 68, including 6 malignant ones; n = 56, including 3 malignant ones). A weighted gene coexpression network approach was used to identify coexpression modules associated with malignancy. Results At the genomic level, malignant meningiomas had more chromosomal losses than atypical and benign meningiomas, with average length of 528, 203, and 34 megabases, respectively. Monosomic loss of chromosome 22 was confirmed to be one of the primary chromosomal level abnormalities in all subtypes of meningiomas. At the transcriptome level, the authors identified 23 coexpression modules from the weighted gene coexpression network. Gene functional enrichment analysis highlighted a module with 356 genes that was highly related to tumorigenesis. Four intramodular hubs within the module (GAB2, KLF2, ID1, and CTF1) were oncogenic in other cancers such as leukemia. A putative meningioma tumor suppressor MN1 was also identified in this module with differential expression between malignant and benign meningiomas. Conclusions The authors' genomic and transcriptome analysis of meningiomas provides novel insights into the molecular pathways involved in malignant transformation of meningiomas, with implications for molecular heterogeneity of the disease.

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“…The co-expression correlation coefficients of seven model animals, including human, mouse, chicken, zebra fish, fruit fly, and Coenorhabditis elegans, and nematode, are recorded in COXPRESdb (Obayashi et al, 2008;. The coexpression correlation coefficients of A. thaliana and many other flowering plants are recorded in ATTED-II .…”

Section: Co-expressionmentioning

confidence: 99%