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Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE196106 | GEO | 2022/07/13

REPOSITORIES: GEO

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Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [RNA-seq_mouse]

Project description:The roles of retinal cis-regulatory landscape in controlling the expression of gene regulatory networks important for retinogenesis remain poorly understood. Vsx2 is a transcription factor essential for retinal proliferation and bipolar cell differentiation but the molecular mechanisms underlying its developmental roles are unclear. Here, we profiled VSX2 genomic occupancy during mouse retinogenesis, revealing extensive retinal gene regulatory networks associated with Vsx2 during development. We defined an autoregulatory loop in which VSX2 binds and transactivates its own enhancer in association with the transcription factor PAX6 . The Vsx2 regulatory landscape contains elements that are required for Vsx2 expression, retinal proliferation and proper cell type differentiation. We further show that retinae in which the Vsx2 enhancer landscape has been largely deleted suffer a bias toward photoreceptor production. Genomic data indicate that VSX2 occupies cis-regulatory elements nearby genes associated with photoreceptor differentiation and homeostasis in mouse and human retinae, including a conserved region nearby the rod-specifying factor Prdm1. We provide evidence that VSX2 associates with OTX2 and can act to suppress OTX2-dependent enhancer transactivation of Prdm1 enhancer. Taken together, our analyses illuminate important mechanistic insights on how VSX2 is engaged with gene regulatory networks that are essential for retinal proliferation and cell fate acquisition.

2022-07-13 | GSE196104 | GEO

Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [ChIP-seq_mouse]

2022-07-13 | GSE196103 | GEO

Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [ChIP-seq_human]

2022-07-13 | GSE196097 | GEO

Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis

Project description:Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis

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Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [ChIP-seq_human]

Project description:Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [ChIP-seq_human]

| PRJNA803241 | ENA

Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [ChIP-seq_mouse]

Project description:Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [ChIP-seq_mouse]

| PRJNA803304 | ENA

Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [RNA-seq_mouse]

Project description:Functional analysis of Vsx2 super-enhancer reveals an autoregulatory network governing Vsx2 expression during retinogenesis [RNA-seq_mouse]

| PRJNA803305 | ENA

Vsx2 Super-Enhancer

Project description:Identification of a bifunctional super-enhancer in retinal development

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Epigenomic profiling of primary gastric adenocarcinoma reveals super-enhancer heterogeneity.

Project description:Regulatory enhancer elements in solid tumours remain poorly characterized. Here we apply micro-scale chromatin profiling to survey the distal enhancer landscape of primary gastric adenocarcinoma (GC), a leading cause of global cancer mortality. Integrating 110 epigenomic profiles from primary GCs, normal gastric tissues and cell lines, we highlight 36,973 predicted enhancers and 3,759 predicted super-enhancers respectively. Cell-line-defined super-enhancers can be subclassified by their somatic alteration status into somatic gain, loss and unaltered categories, each displaying distinct epigenetic, transcriptional and pathway enrichments. Somatic gain super-enhancers are associated with complex chromatin interaction profiles, expression patterns correlated with patient outcome and dense co-occupancy of the transcription factors CDX2 and HNF4?. Somatic super-enhancers are also enriched in genetic risk SNPs associated with cancer predisposition. Our results reveal a genome-wide reprogramming of the GC enhancer and super-enhancer landscape during tumorigenesis, contributing to dysregulated local and regional cancer gene expression.

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DEEPSEN: a convolutional neural network based method for super-enhancer prediction.

Project description:BACKGROUND:Super-enhancers (SEs) are clusters of transcriptional active enhancers, which dictate the expression of genes defining cell identity and play an important role in the development and progression of tumors and other diseases. Many key cancer oncogenes are driven by super-enhancers, and the mutations associated with common diseases such as Alzheimer's disease are significantly enriched with super-enhancers. Super-enhancers have shown great potential for the identification of key oncogenes and the discovery of disease-associated mutational sites. RESULTS:In this paper, we propose a new computational method called DEEPSEN for predicting super-enhancers based on convolutional neural network. The proposed method integrates 36 kinds of features. Compared with existing approaches, our method performs better and can be used for genome-wide prediction of super-enhancers. Besides, we screen important features for predicting super-enhancers. CONCLUSION:Convolutional neural network is effective in boosting the performance of super-enhancer prediction.

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