Cell-type, allelic, and genetic signatures in the human pancreatic beta cell transcriptome - PubMed (original) (raw)

Cell-type, allelic, and genetic signatures in the human pancreatic beta cell transcriptome

Alexandra C Nica et al. Genome Res. 2013 Sep.

Abstract

Elucidating the pathophysiology and molecular attributes of common disorders as well as developing targeted and effective treatments hinges on the study of the relevant cell type and tissues. Pancreatic beta cells within the islets of Langerhans are centrally involved in the pathogenesis of both type 1 and type 2 diabetes. Describing the differentiated state of the human beta cell has been hampered so far by technical (low resolution microarrays) and biological limitations (whole islet preparations rather than isolated beta cells). We circumvent these by deep RNA sequencing of purified beta cells from 11 individuals, presenting here the first characterization of the human beta cell transcriptome. We perform the first comparison of gene expression profiles between beta cells, whole islets, and beta cell depleted islet preparations, revealing thus beta-cell-specific expression and splicing signatures. Further, we demonstrate that genes with consistent increased expression in beta cells have neuronal-like properties, a signal previously hypothesized. Finally, we find evidence for extensive allelic imbalance in expression and uncover genetic regulatory variants (eQTLs) active in beta cells. This first molecular blueprint of the human beta cell offers biological insight into its differentiated function, including expression of key genes associated with both major types of diabetes.

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Figures

Figure 1.

Figure 1.

High overall similarity between beta cell and islet gene expression. (A) PCA analysis of gene RPKMs for beta (N = 11), islet (N = 7), nonbeta (N = 5) preparations, and 18 other tissues from unrelated individuals. Beta cell and islet samples cluster together, separating from nonbetas. The other tissues cluster separately, with liver being the most similar to the islet-derived RNA-seq data. (B) Scatterplot of beta cell versus islet median RPKMs on log10 scale.

Figure 2.

Figure 2.

Expression differences between beta, islet, and nonbeta samples. (A) Dot chart of top 10 highest expressed genes and their contribution to the nuclear transcriptome by cell type. (B) Histogram of log2 Fold Change (islet/beta) for differentially expressed genes (10% FDR) in islets and beta cells. (C) Histogram of log2 Fold Change (nonbeta/beta) for differentially expressed genes (10% FDR) in nonbeta and beta cells.

Figure 3.

Figure 3.

Sharing of significant ASE effects between beta cells and islets (sample P775). Left panel histograms show the enrichment (pi1) of significant ASE _P_-values in the islets for ASE sites discovered in beta cells and vice versa (beta cell ASE _P_-values of ASE sites discovered in islets). Right panel scatterplots display the direction of ASE effects (ratio of reference allele count to the total number of reads covering that site) between the two cell types, almost always in concordance.

Figure 4.

Figure 4.

Candidate beta cell cis eQTLs discovered initially in other tissues (fat, LCL, skin). Top panel boxplots show the deviations of allelic ratios (reference/total) from the expected 0.5 in ASE individuals grouped by eQTL genotype, with heterozygotes having markedly higher effects on ASE ratios compared to homozygotes. Bottom scatterplots show the beta coefficients of the MuTHER eQTLs and the corresponding beta ASE ratios for the selected candidate beta cell regulatory variants.

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