Integration of ATAC-seq and RNA-seq Identifies Human Alpha Cell and Beta Cell Signature Genes
Transcriptomics Dataset
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General Information
AccessionGSE76268
TitleIntegration of ATAC-seq and RNA-seq Identifies Human Alpha Cell and Beta Cell Signature Genes
DescriptionObjective: Although glucagon-secreting -cells and insulin-secreting -cells have opposing functions in regulating plasma glucose levels, the two cell types share a common developmental origin and have overlaps in their transcriptome and epigenome profiles. Notably, destruction of one of these cell populations can stimulate repopulation via transdifferentiation of the other cell type, at least in mice, suggesting plasticity between these cell fates. Furthermore, dysfunction of both - and -cells contributes to the pathophysiology of type 1 and type 2 diabetes, and -cell de-differentiation has been proposed to contribute to type 2 diabetes. Our objective was to delineate the molecular properties that maintain islet cell type specification yet allow for cellular plasticity. We hypothesized that correlating cell type-specific transcriptomes with an atlas of open chromatin will identify novel genes and transcriptional regulatory elements such as enhancers involved in - and -cell specification and plasticity. Methods: We sorted human a- and b-cells and performed the Assay for Transposase-Accessible Chromatin with high throughput sequencing (ATAC-seq) and mRNA-seq, followed by integrative analysis to identify cell type-selective gene regulatory regions. Results: We identified numerous transcripts with either -cell- or -cell-selective expression and discovered the cell type-selective open chromatin regions that correlate with these gene activation patterns. We confirmed cell type-selective expression on the protein level for two of the top hits from our screen. The group specific protein (GC; or vitamin D binding protein) was restricted to a-cells, while CHODL (chondrolectin) immunoreactivity was only present in b-cells. Furthermore, -cell- and -cell-selective ATAC-seq peaks were identified to overlap with known binding sites for islet transcription factors, as well as with common single nucleotide polymorphisms (SNPs) previously identified as risk loci for type 2 diabetes. Conclusions: We have determined the genetic landscape of human - and -cells based on chromatin accessibility and transcript levels, which allowed for detection of novel - and -cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76268
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

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Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE76268
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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