PLX273790

GSE126569: Genome-wide fetalization of enhancer architecture in heart disease [RNA-Seq]

  • Organsim human
  • Type RNASEQ
  • Target gene
  • Project ARCHS4

Heart disease is associated with re-expression of key transcription factors normally active only during prenatal development of the heart. However, the impact of this reactivation on the genome-wide regulatory landscape in heart disease has remained obscure. Here we show that pervasive epigenomic changes occur in heart disease, with thousands of regulatory sequences reacquiring fetal-like chromatin signatures. We used RNA-seq and ChIP-seq targeting a histone modification associated with active transcriptional enhancers to generate genome-wide enhancer maps from left ventricle tissue from 18 healthy controls and 18 individuals with idiopathic dilated cardiomyopathy (DCM). Healthy individuals had a highly reproducible epigenomic landscape, consisting of more than 31,000 predicted heart enhancers. In contrast, we observed reproducible disease-associated gains or losses of activity at more than 7,500 predicted heart enhancers. Next, we profiled human fetal heart tissue by ChIP-seq and RNA-seq. Comparison with adult tissues revealed that the heart disease epigenome and transcriptome both shift toward a fetal-like state, with more than 3,400 individual enhancers sharing fetal regulatory properties. Our results demonstrate widespread epigenomic changes in DCM, and we provide a comprehensive data resource (http://heart.lbl.gov) for the mechanistic exploration of heart disease etiology. SOURCE: Axel ViselMammalian functional genomics laboratory Lawrence Berkeley National Laboratory

View on GEOView in Pluto

Key Features

Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.

Learn More

14K+ Published Experiments

Access an extensive range of curated bioinformatics data sets, including genomic, transcriptomic, and proteomic data.

Easy Data Import

Request imports from GEO or TCGA directly within Pluto Bio. Seamlessly integrate external data sets into your workflow.

Advanced Search Capabilities

Utilize powerful search tools to quickly find the data sets relevant to your research. Filter by type, disease, gene, and more.

Analyze and visualize data for this experiment

Use Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.

Read about post-pipeline analysis

View QC data and experiment metadata

View quality control data and experiment metadata for this experiment.

Request import of other GEO data

Request imports from GEO or TCGA directly within Pluto Bio.

Chat with our Scientific Insights team