The Islet Regulome Browser

The Islet Regulome Browser is a visualization tool that provides access to interactive exploration of pancreatic islet genomic data.

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Chromatin Maps




RNA-seq Expression


Adult human islets

Pancretic Islet super-enhancers / enhancer hubs / structural transcription factors / virtual 4C

Human pancreatic islet 3D chromatin architecture provides insights into the genetics of type 2 diabetes. Miguel-Escalada I, et al. 2018. bioRxiv Preprint. doi: 10.1101/400291

Open chromatin classes / enhancer clusters / transcription factors

Pancreatic islet enhancer clusters enriched in type 2 diabetes risk-associated variants. Pasquali L, et al. Nat Genet. 2014 Feb;46(2):136-43. doi: 10.1038/ng.2870.

Pancreatic islet transcriptome

Human cell transcriptome analysis uncovers lncRNAs that are tissue-specific, dynamically regulated, and abnormally expressed in type 2 diabetes. Morn I, et al. Cell Metab. 2012 Oct 3;16(4):435-48. doi: 10.1016/j.cmet.2012.08.010.

Human Pancreatic Cell lncRNAs Control Cell-Specific Regulatory Networks. Akerman I, et al. Cell Metab. 2016 Dec 28. doi: 10.1016/j.cmet.2016.11.016.

Pancreatic islet open chromatin map / COREs

A map of open chromatin in human pancreatic islets. Gaulton KJ, et al. Nat Genet. 2010 Mar;42(3):255-9. doi: 10.1038/ng.530.

Chromatin states / stretch enhancers

Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants. Parker SC, et al. Proc Natl Acad Sci U S A. 2013 Oct 29;110(44):17921-6. doi: 10.1073/pnas.1317023110.

Pancreatic progenitors

Pancreatic progenitors regulatory regions / transcription factors

TEAD and YAP regulate the enhancer network of human embryonic pancreatic progenitors. Cebola I, et al. Nat Cell Biol. 2015 May;17(5):615-26. doi: 10.1038/ncb3160

GWAS variants

T2D - 70KforT2D

Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes. Bons-Guarch S, et al. Nat Commun. 9, 321 (2018). doi: 10.1038/s41467-017-02380-9


Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Morris AP, et al. Nat Genet. 2012 Sep;44(9):981-90. doi: 10.1038/ng.2383.

Fasting glycemia - MAGIC

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Scott RA, Nat Genet. 2012 Sep;44(9):991-1005. doi: 10.1038/ng.2385.

The Islet Regulome Browser

The Islet Regulome browser was originally designed by Dr. Lorenzo Pasquali (IGTP/IJC) and Dr. Loris Mularoni (IRB). Initial supervision for the project was provided by Prof. Jorge Ferrer (ICL).

The Islet Regulome Browser is now developed and maintained in the Pasquali Lab by Mireia Ramos with support from the Institute Germans Trias i Pujol (IGTP) Bioinformatics Core.

If you make use of results generated by the Islet Regulome Browser, please include the following reference in your scientific publication:

Mularoni L, Ramos M and Pasquali L (2017). The pancreatic islet regulome browser. Front. Genet. 8:13. doi: 10.3389/fgene.2017.00013

The Islet Regulome Browser

We encourage you to contact us to ask questions, leave suggestions, comments, feedback, and any other concerns. For bug reports, please include the type and version of the browser you are using along with the description of the bug.

Create a plot

A plot can be generated by selecting a valid gene name or an absolute chromosomal location by specifying the genomic coordinates (chromosome, start, and end) in the human build hg19. The plot can be extended on both sides by selecting a 0, 1Kb, 5Kb, 10Kb, 50Kb (default), 100Kb, 500Kb, 1Mb range.

From the <80><9c>Features<80><9d> panel 4 major track types can be loaded to obtain the desired plot.

  1. Tracks called Chromatin maps and Enhancer clustering annotations refer to genomic maps of regions that may be involved in gene transcription regulation. Such maps were inferred from experimental data sets such as open chromatin and histone modification profiles obtained from adult human pancreatic islets and pancreatic progenitors cell types.
  2. Transcription factors tracks are maps of transcription factors binding sites obtained from Chip-seq experiments performed in human adult pancreatic islets and pancreatic progenitors.
  3. SNPs tracks include GWAS variants datasets associated to type 2 diabetes and fasting glycemia.
  4. The Virtual 4C track enables to visualize promoter capture HiC data performed in human pancreatic islets in a virtual 4C format, in which the queried region (scrooll down menu) is used as the bait or viewpoint.

Description of the plot

IRB Example

The plot illustrates regulatory regions, transcription factors binding sites, chromatin interaction data and GWAS variants in which the sequence of the base genome is represented on the horizontal axis. In the upper part of the plot a green line on the chromosome ideogram reflects the portion of the chromosome displayed. Each dot represents a genomic variant, being the color intensity of the dot proportional to -Log10 p-value of association, as indicated on the side of the plot. The rs# ID depicts the top associated variants in the locus.

The virtual 4C data is visualized as an interaction frequency histogram plot, where the bait/viewpoint is depict as a black triangle region. A distal peak in the signal indicates that there is a chromatin interaction event with the bait/viewpoint. The interaction significance is depicted by a color code reflecting the CHiCAGO scores. Such chromatin interaction maps were extracted from promoter capture HiC data centered on the queried bait region, hence, virtual 4C.

The black box in the middle of the plot contains vertical colored bands depicting different chromatin states, open chromatin classes or regulatory elements as described in the legend above the plot. Black lines connecting the circles (each representing a different transcription factor) to the black box, point to the genomic location of each transcription factor binding site. The color intensity of such lines is proportional to the number of co-bound transcription factors. Annotated genes are depicted as horizontal gray lines at the bottom of the plot. Boxes along the line correspond to positions of coding exons. The color of the box indicates the type of annotation: black boxes indicate lncRNAs, grey boxes indicate genes and purple boxes represent islet-specific genes.

Moving around

It is possible to change the coordinates of the plot by moving left or right to the desired coordinates, the circles above the plot. Alternatively new coordinates can be entered in the Input Region section at the left of the plot. The submit button will allow to refresh the plot to the desired new coordinates.

Retrieve results

Graphical representations and text tables are available for download.

The plot can be downloaded as PDF (Adobe Portable Document) format by clicking on the download icon above the plot.

A button above the plot provides a link to a UCSC browser session containing all the data currently available in the Islet Regulome Browser for classic UCSC visualization. For this purpose bigwig files were generated by aligning unique reads from the raw data using Bowtie2 (default parameters). For transcription factor binding sites and chromatin maps refer to the parameters used in the original publications.

Two tables related to the selected locus can be downloaded from the “Table” panel, selectable from the top left corner of the plot page. One table contains the regulatory regions, open chromatin classes or chromatin states selected for display along with the transcription factors who's bind sites overlap them. The other table contains a list of the variants contained in the selected locus along with their p-value of association.

The Setting panel, selectable from top left corner of the plot page, allows to retrieve all the settings used to make the plot including genomic coordinates genome build, SNPs datasets and feature selected.

How to cite

If you make use of any result generated by the Islet Regulome Browser, please include the following reference in your scientific publication:

Mularoni L, Ramos M and Pasquali L (2017). The pancreatic islet regulome browser. Front. Genet. 8:13. doi: 10.3389/fgene.2017.00013