Genetic regulation of RNA splicing in human pancreatic islets

Abstract

Background: Non-coding genetic variants that influence gene transcription in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D), and likely also contribute to type 1 diabetes (T1D) risk. For many loci, however, the mechanisms through which non-coding variants influence diabetes susceptibility are unknown. Results:We examine splicing QTLs (sQTLs) in pancreatic islets from 399 human donors and observe that common genetic variation has a widespread influence on the splicing of genes with established roles in islet biology and diabetes. In parallel, we profile expression QTLs (eQTLs) and use transcriptome-wide association as well as genetic colocalization studies to assign islet sQTLs or eQTLs to T2D and T1D susceptibility signals, many of which lack candidate effector genes. This analysis reveals biologically plausible mechanisms, including the association of T2D with an sQTL that creates a nonsense isoform in ERO1B, a regulator of ER-stress and proinsulin biosynthesis. The expanded list of T2D risk effector genes reveals overrepresented pathways, including regulators of G-protein-mediated cAMP production. The analysis of sQTLs also reveals candidate effector genes for T1D susceptibility such as DCLRE1B, a senescence regulator, and lncRNA MEG3.Conclusions: These data expose widespread effects of common genetic variants on RNA splicing in pancreatic islets. The results support a role for splicing variation in diabetes susceptibility, and offer a new set of genetic targets with potential therapeutic benefit.

Multiple genetic variants at theSLC30A8locus affect local super-enhancer activity and influence pancreatic β-cell survival and function

“…Previous reports [20, 23, 24, 50] have focused almost exclusively on the lead variant rs13266634 which alters the amino acid sequence of ZnT8 (R325W), or on rare loss-of function SLC30A8 variants [27, 51]. Whilst previous eQTL analyses [12, 52, 53] have failed to identify eQTLs for SLC30A8 , analyses based on cASE identified significant allelic expression imbalance in SLC30A8 [12]. Building on these earlier analyses [12], we confirm here that SLC30A8 expression in human islets exhibits imbalanced allelic expression, where the T2D risk allele is more strongly expressed than the protective allele (Figure 1B).…”

“…cells). Since the latter cell types comprise as much as 65 % of typical human islet preparations [53] our current study may be underpowered to detect cASE in the genes neighbouring SLC30A8 . Future collective efforts to increase the scale of single-cell RNA-seq datasets facilitate cASE analysis at single b-cell resolution and they might expand the number of GWAS loci with allelic imbalanced gene expression.…”

“…RNA gene expression was determined using Affymetrix (Human Genome U133 Plus 2.0 Array). RNA expression data was normalised using the Robust Multichip Analysis (RMA) method utilising the package affy [53] and transcriptomic batch effect was corrected for using the combat approach using the sva R package [58]. Genotyping and RNA data was integrated using the fastQTL software to identify eQTLs, adjusted for sex and age.…”

“…Thus, more than 200 genetic loci carrying >400 independent signals associated with T2D have been discovered [1–4], with the majority of these influencing insulin secretion [5–10]. Analyses of chromatin accessibility and expression quantitative trait (eQTL) loci in human islets have further increased our understanding of how variants are likely to exert their effects [7, 11–13]. These, alongside functional studies to determine the role of implicated gene products in pancreatic β cell function, have allowed us [14–17] to determine the likely mode(s) of action of variants at several T2D-associated loci .…”

Multiple genetic variants at the SLC30A8 locus affect local super‐enhancer activity and influence pancreatic β‐cell survival and function

“…2,[5][6][7][8][9] Analyses of chromatin accessibility and expression quantitative trait (eQTL) loci in human islets have further increased our understanding of how variants are likely to exert their effects. 7,[9][10][11] These, alongside functional studies to determine the role of implicated gene products in pancreatic βcell function, have allowed us [12][13][14][15] to determine the likely mode(s) of action of variants at several T2D-associated loci.…”