Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation

Merico, Daniele; Isserlin, Ruth; Stueker, Oliver; Emili, Andrew; Bader, Gary D.

doi:10.1371/journal.pone.0013984

Cited by 1,863 publications

(1,648 citation statements)

References 54 publications

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“…Gene sets were derived from Gene Ontology, KEGG, National Cancer Institute, PFAM, and Biocarta pathway databases. Enrichment Map was used for interpretation of the GSEA results (43). Only gene sets consisting of more than 10 and fewer than 500 genes were taken into account.…”

Section: Methodsmentioning

confidence: 99%

Inflammasome is a central player in the induction of obesity and insulin resistance

Stienstra

Diepen

Tack

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

607

499

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Inflammation plays a key role in the pathogenesis of obesity. Chronic overfeeding leads to macrophage infiltration in the adipose tissue, resulting in proinflammatory cytokine production. Both microbial and endogenous danger signals trigger assembly of the intracellular innate immune sensor Nlrp3, resulting in caspase-1 activation and production of proinflammatory cytokines IL-1β and IL-18. Here, we showed that mice deficient in Nlrp3, apoptosis-associated speck-like protein, and caspase-1 were resistant to the development of high-fat diet-induced obesity, which correlated with protection from obesityinduced insulin resistance. Furthermore, hepatic triglyceride content, adipocyte size, and macrophage infiltration in adipose tissue were all reduced in mice deficient in inflammasome components. Monocyte chemoattractant protein (MCP)-1 is a key molecule that mediates macrophage infiltration. Indeed, defective inflammasome activation was associated with reduced MCP-1 production in adipose tissue. Furthermore, plasma leptin and resistin that affect energy use and insulin sensitivity were also changed by inflammasome-deficiency. Detailed metabolic and molecular phenotyping demonstrated that the inflammasome controls energy expenditure and adipogenic gene expression during chronic overfeeding. These findings reveal a critical function of the inflammasome in obesity and insulin resistance, and suggest inhibition of the inflammasome as a potential therapeutic strategy.

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Section: Methodsmentioning

confidence: 99%

Inflammasome is a central player in the induction of obesity and insulin resistance

Stienstra

Diepen

Tack

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

607

499

View full text Add to dashboard Cite

show abstract

“…For the enrichment analysis of genes affected by promoter hypermethylation, first, we used DAVID functional annotation tool 25 to carry out analysis against gene sets defined by SP_PIR_KEYWORDS annotation. Second, we used hypergeometric test to assess the enrichment of additional gene sets in the set of genes affected by promoter hypermethylation 26 . In both the analyses, the set of 15,643 RefSeq genes with promoters overlapping SssI regions was used as a background.…”

Section: Methodsmentioning

confidence: 99%

Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value

et al. 2015

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Epigenetic alterations in the cancer methylome are common in breast cancer and provide novel options for tumour stratification. Here, we perform whole-genome methylation capture sequencing on small amounts of DNA isolated from formalin-fixed, paraffin-embedded tissue from triple-negative breast cancer (TNBC) and matched normal samples. We identify differentially methylated regions (DMRs) enriched with promoters associated with transcription factor binding sites and DNA hypersensitive sites. Importantly, we stratify TNBCs into three distinct methylation clusters associated with better or worse prognosis and identify 17 DMRs that show a strong association with overall survival, including DMRs located in the Wilms tumour 1 (WT1) gene, bi-directional-promoter and antisense WT1-AS. Our data reveal that coordinated hypermethylation can occur in oestrogen receptor-negative disease, and that characterizing the epigenetic framework provides a potential signature to stratify TNBCs. Together, our findings demonstrate the feasibility of profiling the cancer methylome with limited archival tissue to identify regulatory regions associated with cancer.

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“…S8). We used a new gene function visualization method called Enrichment Map (Merico et al, 2010) to characterize the functional distribution of genes in the shared subnetwork (Fig. 3B).…”

Section: The Shared Subnetwork Between Pti and Eti Is Enriched With Ementioning

confidence: 99%

Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis

et al. 2015

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Pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) are two main plant immune responses to counter pathogen invasion. Genome-wide gene network organizing principles leading to quantitative differences between PTI and ETI have remained elusive. We combined an advanced machine learning method and modular network analysis to systematically characterize the organizing principles of Arabidopsis (Arabidopsis thaliana) PTI and ETI at three network resolutions. At the single network node/ edge level, we ranked genes and gene interactions based on their ability to distinguish immune response from normal growth and successfully identified many immune-related genes associated with PTI and ETI. Topological analysis revealed that the top-ranked gene interactions tend to link network modules. At the subnetwork level, we identified a subnetwork shared by PTI and ETI encompassing 1,159 genes and 1,289 interactions. This subnetwork is enriched in interactions linking network modules and is also a hotspot of attack by pathogen effectors. The subnetwork likely represents a core component in the coordination of multiple biological processes to favor defense over development. Finally, we constructed modular network models for PTI and ETI to explain the quantitative differences in the global network architecture. Our results indicate that the defense modules in ETI are organized into relatively independent structures, explaining the robustness of ETI to genetic mutations and effector attacks. Taken together, the multiscale comparisons of PTI and ETI provide a systems biology perspective on plant immunity and emphasize coordination among network modules to establish a robust immune response.

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Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation

Cited by 1,863 publications

References 54 publications

Inflammasome is a central player in the induction of obesity and insulin resistance

Inflammasome is a central player in the induction of obesity and insulin resistance

Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value

Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis

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