Identification of ZNF395 as a novel modulator of adipogenesis

Hasegawa, Ryota; Tomaru, Yuji; Hoon, Michiel de; Suzuki, Harukazu; Hayashizaki, Yoshihide; Shin, Jay W.

doi:10.1016/j.yexcr.2012.11.003

Cited by 33 publications

(28 citation statements)

References 30 publications

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“…That the computational model at the core of ISMARA, i.e., motif activity response analysis, is a powerful method for reconstructing regulatory interactions from high-throughput data has already been demonstrated, not only in its original application (The FANTOM Consortium et al 2009), but in a substantial number of recent studies across a wide range of mammalian systems (Summers et al 2010;Aceto et al 2012;Arner et al 2012;Arnold et al 2012b;The FANTOM Consortium et al 2012;Hasegawa et al 2012;Pérez-Schindler et al 2012;Eisele et al 2013;Meier-Abt et al 2013;Tiwari et al 2013a,b;Vervoort et al 2013). In each of these studies, MARA successfully inferred key regulators and their regulatory interactions ab initio.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, whereas many laboratories are now routinely producing high-throughput data sets, and methodologies for analyzing such data have been described in the literature, the vast majority of groups that produce data have to develop collaborations with expert computational groups to apply these methods. Indeed, in recent years MARA has been applied to a large range of mammalian systems studied by various experimental collaborators and experimentally validated predicted regulatory circuitry in these systems (Summers et al 2010;Aceto et al 2012;Arner et al 2012;Hasegawa et al 2012;Pérez-Schindler et al 2012;Suzuki et al 2012;Eisele et al 2013;Meier-Abt et al 2013;Tiwari et al 2013a,b;Vervoort et al 2013). Although these studies further validated the power of the method, they required a considerable investment of time and effort for the analysis of each new data set.…”

Section: [Supplemental Materials Is Available For This Article]mentioning

confidence: 99%

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ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs

et al. 2014

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Accurate reconstruction of the regulatory networks that control gene expression is one of the key current challenges in molecular biology. Although gene expression and chromatin state dynamics are ultimately encoded by constellations of binding sites recognized by regulators such as transcriptions factors (TFs) and microRNAs (miRNAs), our understanding of this regulatory code and its context-dependent read-out remains very limited. Given that there are thousands of potential regulators in mammals, it is not practical to use direct experimentation to identify which of these play a key role for a particular system of interest. We developed a methodology that models gene expression or chromatin modifications in terms of genome-wide predictions of regulatory sites and completely automated it into a web-based tool called ISMARA (Integrated System for Motif Activity Response Analysis). Given only gene expression or chromatin state data across a set of samples as input, ISMARA identifies the key TFs and miRNAs driving expression/chromatin changes and makes detailed predictions regarding their regulatory roles. These include predicted activities of the regulators across the samples, their genome-wide targets, enriched gene categories among the targets, and direct interactions between the regulators. Applying ISMARA to data sets from well-studied systems, we show that it consistently identifies known key regulators ab initio. We also present a number of novel predictions including regulatory interactions in innate immunity, a master regulator of mucociliary differentiation, TFs consistently disregulated in cancer, and TFs that mediate specific chromatin modifications.

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Section: Discussionmentioning

confidence: 99%

Section: [Supplemental Materials Is Available For This Article]mentioning

confidence: 99%

ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs

et al. 2014

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“…ZNF395 is also known as HDBP2 (101) PPARγ2 to promote adipogenesis (103). ZNF395 has been shown to bind to the promoters of Huntington gene (101) and interferon-induced genes, and to cause upregulation of cancer-related genes (MACC1, PEG10, CALCOCO1, and MEF2C; ref.…”

Section: Discussionmentioning

confidence: 99%

VHL Deficiency Drives Enhancer Activation of Oncogenes in Clear Cell Renal Cell Carcinoma

et al. 2017

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Protein-coding mutations in clear cell renal cell carcinoma (ccRCC) have been extensively characterized, frequently involving inactivation of the von Hippel-Lindau ( VHL ) tumor suppressor. Roles for noncoding cis -regulatory aberrations in ccRCC tumorigenesis, however, remain unclear. Analyzing 10 primary tumor/normal pairs and 9 cell lines across 79 chromatin profi les, we observed pervasive enhancer malfunction in ccRCC, with cognate enhancer-target genes associated with tissue-specifi c aspects of malignancy. Superenhancer profi ling identifi ed ZNF395 as a ccRCCspecifi c and VHL-regulated master regulator whose depletion causes near-complete tumor elimination in vitro and in vivo . VHL loss predominantly drives enhancer/superenhancer deregulation more so than promoters, with acquisition of active enhancer marks (H3K27ac, H3K4me1) near ccRCC hallmark genes. Mechanistically, VHL loss stabilizes HIF2α-HIF1β heterodimer binding at enhancers, subsequently recruiting histone acetyltransferase p300 without overtly affecting preexisting promoter-enhancer interactions. Subtype-specifi c driver mutations such as VHL may thus propagate unique pathogenic dependencies in ccRCC by modulating epigenomic landscapes and cancer gene expression. SIGnIFICAnCE:Comprehensive epigenomic profi ling of ccRCC establishes a compendium of somatically altered cis -regulatory elements, uncovering new potential targets including ZNF395, a ccRCC master regulator. Loss of VHL , a ccRCC signature event, causes pervasive enhancer malfunction, with binding of enhancer-centric HIF2α and recruitment of histone acetyltransferase p300 at preexisting lineage-specifi c promoter-enhancer complexes. Cancer Discov; 7(11); 1284-305.

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“…After the initial presentation of MARA and its application to inferring the core regulatory network of a differentiating human cell line [11], MARA has since been applied to a large number of different mammalian systems [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] and extended to model genome-wide chromatin marks in terms of epigenetic motif activities [28]. Remarkably, in all these systems, MARA's predictions of key regulators and their interactions were subsequently confirmed by experimental validation.…”

Section: Motif Activity Response Analysismentioning

confidence: 99%

ARMADA: Using motif activity dynamics to infer gene regulatory networks from gene expression data

Pemberton-Ross

Nimwegen

2015

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Identification of ZNF395 as a novel modulator of adipogenesis

Cited by 33 publications

References 30 publications

ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs

ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs

VHL Deficiency Drives Enhancer Activation of Oncogenes in Clear Cell Renal Cell Carcinoma

ARMADA: Using motif activity dynamics to infer gene regulatory networks from gene expression data

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