Dataset Information

Alpha TC1 and Beta-TC-6 genomic profiling uncovers both shared and distinct transcriptional regulatory features with their primary islet counterparts

ABSTRACT: Alpha TC1 (αTC1) and Beta-TC-6 (βTC6) mouse islet cell lines are cellular models of islet (dys)function and type 2 diabetes (T2D). However, genomic characteristics of these cells, and their similarities to primary islet alpha and beta cells, are undefined. Here, we report the epigenomic (ATAC-seq) and transcriptomic (RNA-seq) landscapes of αTC1 and βTC6 cells. Each cell type exhibits hallmarks of its primary islet cell counterpart including cell-specific expression of beta (e.g., Pdx1) and alpha (e.g., Arx) cell transcription factors (TFs), and enrichment of binding motifs for these TFs in αTC1/βTC6 cis-regulatory elements. αTC1/βTC6 transcriptomes overlap significantly with the transcriptomes of primary mouse/human alpha and beta cells. Our data further indicate that ATAC-seq detects cell-specific regulatory elements for cell types comprising ≥ 20% of a mixed cell population. We identified αTC1/βTC6 cis-regulatory elements orthologous to those containing type 2 diabetes (T2D)-associated SNPs in human islets for 33 loci, suggesting these cells’ utility to dissect T2D molecular genetics in these regions. Together, these maps provide important insights into the conserved regulatory architecture between αTC1/βTC6 and primary islet cells that can be leveraged in functional (epi)genomic approaches to dissect the genetic and molecular factors controlling islet cell identity and function.

ORGANISM(S): Mus musculus

PROVIDER: GSE99954 | GEO | 2017/09/20

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Recent advances in the understanding of the genetics of type 2 diabetes (T2D) susceptibility have focused attention on the regulation of transcriptional activity within the pancreatic beta-cell. MicroRNAs (miRNAs) represent an important component of regulatory control, and have proven roles in the development of human disease and control of glucose homeostasis. We set out to establish the miRNA profile of human pancreatic islets and of enriched beta-cell populations, and to explore their potential involvement in T2D susceptibility. We used Illumina small RNA sequencing to profile the miRNA fraction in three preparations each of primary human islets and of enriched beta-cells generated by fluorescence-activated cell sorting. In total, 366 miRNAs were found to be expressed (i.e. >100 cumulative reads) in islets and 346 in beta-cells; of the total of 384 unique miRNAs, 328 were shared. A comparison of the islet-cell miRNA profile with those of 15 other human tissues identified 40 miRNAs predominantly expressed (i.e. >50% of all reads seen across the tissues) in islets. Several highly-expressed islet miRNAs, such as miR-375, have established roles in the regulation of islet function, but others (e.g. miR-27b-3p, miR-192-5p) have not previously been described in the context of islet biology. As a first step towards exploring the role of islet-expressed miRNAs and their predicted mRNA targets in T2D pathogenesis, we looked at published T2D association signals across these sites. We found evidence that predicted mRNA targets of islet-expressed miRNAs were globally enriched for signals of T2D association (p-values <0.01, q-values <0.1). At six loci with genome-wide evidence for T2D association (AP3S2, KCNK16, NOTCH2, SCL30A8, VPS26A, and WFS1) predicted mRNA target sites for islet-expressed miRNAs overlapped potentially causal variants. In conclusion, we have described the miRNA profile of human islets and beta-cells and provide evidence linking islet miRNAs to T2D pathogenesis. Examination of the miRNA profiles in 3 preparations of isolated pancreatic islets and 3 preparations of FACS-enriched pancreatic beta-cells

Project description:Pancreatic islet (dys)function is central to glucose homeostasis and type 2 diabetes (patho)physiology. Human islets consist of multiple endocrine (alpha, beta, delta, gamma), endothelial, and resident/inflitrating immune cells whose coordinated functions modulate glucose mobilization or disposal. Single cell transcriptome profiling (scRNA-seq) studies have been applied to dissect human islet cellular heterogeneity, identify islet cell (sub)populations, and define their molecular repertoire. However, precise understanding of cell type-specific alterations in type 2 diabetic vs. non-diabetic individuals is lacking, due in part to the limited number of individuals or single cell transcriptomes per individual profiled for comparison. Here, we create a comprehensive single cell transcriptome atlas of 245,878 human islet cells from 48 individuals spanning non-diabetic (ND), pre-diabetic (PD), and type 2 diabetic (T2D) states and matched for sex, age, and ancestry and define marker gene sets that are robustly expressed across disease states for each of the 14 cell types identified. We observe significant decreases in the number of beta cells sampled from T2D vs. ND or PD donors. Two of eight putative beta cell subpopulations, with ‘high functioning’ and ‘senescent’ cell gene signatures, increase and decrease in T2D donor islets, respectively. Importantly, we identify 511 differentially expressed genes in beta cells from T2D vs. ND donors. This includes monogenic and type 2 diabetes effector genes, such as HNF1A, DGKB, ST6GAL1, and FXYD2, for which genetic and environmental effects on their expression is concordant. Human beta cell and islet knockdown of selected newly-identified down-regulated genes impairs beta cell viability or function. Together, this study provides new and robust, cell type-resolved insights on the cellular and molecular changes in healthy vs. diabetic human islets and represents a valuable resource to the islet biology and type 2 diabetes communities.

Dataset Information

Alpha TC1 and Beta-TC-6 genomic profiling uncovers both shared and distinct transcriptional regulatory features with their primary islet counterparts

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets