RedRibbon: A new rank-rank hypergeometric overlap for gene and transcript expression signatures.

High-throughput omics technologies have generated a wealth of large protein, gene, and transcript datasets that have exacerbated the need for new methods to analyse and compare big datasets. Rank-rank hypergeometric overlap is an important threshold-free method to combine and visualize two ranked lists of P-values or fold-changes, usually from differential gene expression analyses. Here, we introduce a new rank-rank hypergeometric overlap-based method aimed at gene level and alternative splicing analyses at transcript or exon level, hitherto unreachable as transcript numbers are an order of magnitude larger than gene numbers. We tested the tool on synthetic and real datasets at gene and transcript levels to detect correlation and anticorrelation patterns and found it to be fast and accurate, even on very large datasets thanks to an evolutionary algorithm-based minimal P-value search. The tool comes with a ready-to-use permutation scheme allowing the computation of adjusted P-values at low time cost. The package compatibility mode is a drop-in replacement to previous packages. RedRibbon holds the promise to accurately extricate detailed information from large comparative analyses.

Adipose tissue plasticity in pheochromocytoma patients suggests a role of the splicing machinery in human adipose browning.

Adipose tissue from pheochromocytoma patients acquires brown fat features, making it a valuable model for studying the mechanisms that control thermogenic adipose plasticity in humans. Transcriptomic analyses revealed a massive downregulation of splicing machinery components and splicing regulatory factors in browned adipose tissue from patients, with upregulation of a few genes encoding RNA-binding proteins potentially involved in splicing regulation. These changes were also observed in cell culture models of human brown adipocyte differentiation, confirming a potential involvement of splicing in the cell-autonomous control of adipose browning. The coordinated changes in splicing are associated with a profound modification in the expression levels of splicing-driven transcript isoforms for genes involved in the specialized metabolism of brown adipocytes and those encoding master transcriptional regulators of adipose browning. Splicing control appears to be a relevant component of the coordinated gene expression changes that allow human adipose tissue to acquire a brown phenotype.

TIGER: The gene expression regulatory variation landscape of human pancreatic islets.

Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.

Persistent or Transient Human ß Cell Dysfunction Induced by Metabolic Stress: Specific Signatures and Shared Gene Expression with Type 2 Diabetes.

Pancreatic ß cell failure is key to type 2 diabetes (T2D) onset and progression. Here, we assess whether human ß cell dysfunction induced by metabolic stress is reversible, evaluate the molecular pathways underlying persistent or transient damage, and explore the relationships with T2D islet traits. Twenty-six islet preparations are exposed to several lipotoxic/glucotoxic conditions, some of which impair insulin release, depending on stressor type, concentration, and combination. The reversal of dysfunction occurs after washout for some, although not all, of the lipoglucotoxic insults. Islet transcriptomes assessed by RNA sequencing and expression quantitative trait loci (eQTL) analysis identify specific pathways underlying ß cell failure and recovery. Comparison of a large number of human T2D islet transcriptomes with those of persistent or reversible ß cell lipoglucotoxicity show shared gene expression signatures. The identification of mechanisms associated with human ß cell dysfunction and recovery and their overlap with T2D islet traits provide insights into T2D pathogenesis, fostering the development of improved ß cell-targeted therapeutic strategies.

Calcium Oscillations in Pancreatic α-cells Rely on Noise and ATP-Driven Changes in Membrane Electrical Activity.

In pancreatic α-cells, intracellular Ca2+ ([Ca2+]i) acts as a trigger for secretion of glucagon, a hormone that plays a key role in blood glucose homeostasis. Intracellular Ca2+ dynamics in these cells are governed by the electrical activity of voltage-gated ion channels, among which ATP-sensitive K+ (KATP) channels play a crucial role. In the majority of α-cells, the global Ca2+ response to lowering external glucose occurs in the form of oscillations that are much slower than electrical activity. These Ca2+ oscillations are highly variable as far as inter-spike intervals, shapes and amplitudes are concerned. Such observations suggest that Ca2+ dynamics in α-cells are much influenced by noise. Actually, each Ca2+ increase corresponds to multiple cycles of opening/closing of voltage gated Ca2+ channels that abruptly become silent, before the occurrence of another burst of activity a few tens of seconds later. The mechanism responsible for this intermittent activity is currently unknown. In this work, we used computational modeling to investigate the mechanism of cytosolic Ca2+ oscillations in α-cells. Given the limited population of KATP channels in this cell type, we hypothesized that the stochastic activity of these channels could play a key role in the sporadic character of the action potentials. To test this assumption, we extended a previously proposed model of the α-cells electrical activity (Diderichsen and Göpel, 2006) to take Ca2+ dynamics into account. Including molecular noise on the basis of a Langevin type description as well as realistic dynamics of opening and closing of KATP channels, we found that stochasticity at the level of the activity of this channel is on its own not able to produce Ca2+ oscillations with a time scale of a few tens of seconds. However, when taking into account the intimate relation between Ca2+ and ATP changes together with the intrinsic noise at the level of the KATP channels, simulations displayed Ca2+ oscillations that are compatible with experimental observations. We analyzed the detailed mechanism and used computational simulations to identify the factors that can affect Ca2+ oscillations in α-cells.

Combined transcriptome and proteome profiling of the pancreatic ß-cell response to palmitate unveils key pathways of ß-cell lipotoxicity.

BACKGROUND: Prolonged exposure to elevated free fatty acids induces ß-cell failure (lipotoxicity) and contributes to the pathogenesis of type 2 diabetes. In vitro exposure of ß-cells to the saturated free fatty acid palmitate is a valuable model of lipotoxicity, reproducing features of ß-cell failure observed in type 2 diabetes. In order to map the ß-cell response to lipotoxicity, we combined RNA-sequencing of palmitate-treated human islets with iTRAQ proteomics of insulin-secreting INS-1E cells following a time course exposure to palmitate. RESULTS: Crossing transcriptome and proteome of palmitate-treated ß-cells revealed 85 upregulated and 122 downregulated genes at both transcript and protein level. Pathway analysis identified lipid metabolism, oxidative stress, amino-acid metabolism and cell cycle pathways among the most enriched palmitate-modified pathways. Palmitate induced gene expression changes compatible with increased free fatty acid mitochondrial import and ß-oxidation, decreased lipogenesis and modified cholesterol transport. Palmitate modified genes regulating endoplasmic reticulum (ER) function, ER-to-Golgi transport and ER stress pathways. Furthermore, palmitate modulated cAMP/protein kinase A (PKA) signaling, inhibiting expression of PKA anchoring proteins and downregulating the GLP-1 receptor. SLC7 family amino-acid transporters were upregulated in response to palmitate but this induction did not contribute to ß-cell demise. To unravel critical mediators of lipotoxicity upstream of the palmitate-modified genes, we identified overrepresented transcription factor binding sites and performed network inference analysis. These identified LXR, PPARα, FOXO1 and BACH1 as key transcription factors orchestrating the metabolic and oxidative stress responses to palmitate. CONCLUSIONS: This is the first study to combine transcriptomic and sensitive time course proteomic profiling of palmitate-exposed ß-cells. Our results provide comprehensive insight into gene and protein expression changes, corroborating and expanding beyond previous findings. The identification of critical drivers and pathways of the ß-cell lipotoxic response points to novel therapeutic targets for type 2 diabetes.

Interindividual Heterogeneity of SGLT2 Expression and Function in Human Pancreatic Islets.

Studies implicating sodium-glucose cotransporter 2 (SGLT2) inhibitors in glucagon secretion by pancreatic α-cells reported controversial results. We hypothesized that interindividual heterogeneity in SGLT2 expression and regulation may affect glucagon secretion by human α-cells in response to SGLT2 inhibitors. An unbiased RNA-sequencing analysis of 207 donors revealed an unprecedented level of heterogeneity of SLC5A2 expression. To determine heterogeneity of SGLT2 expression at the protein level, the anti-SGLT2 antibody was first rigorously evaluated for specificity, followed by Western blot and immunofluorescence analysis on islets from 10 and 12 donors, respectively. The results revealed a high interdonor variability of SGLT2 protein expression. Quantitative analysis of 665 human islets showed a significant SGLT2 protein colocalization with glucagon but not with insulin or somatostatin. Moreover, glucagon secretion by islets from 31 donors at low glucose (1 mmol/L) was also heterogeneous and correlated with dapagliflozin-induced glucagon secretion at 6 mmol/L glucose. Intriguingly, islets from three donors did not secrete glucagon in response to either 1 mmol/L glucose or dapagliflozin, indicating a functional impairment of the islets of these donors to glucose sensing and SGLT2 inhibition. Collectively, these data suggest that heterogeneous expression of SGLT2 protein and variability in glucagon secretory responses contribute to interindividual differences in response to SGLT2 inhibitors.