Researchers from the Barcelona Supercomputing Center (BSC) have led, together with the Broad Institute (Boston, USA) and the Université Libre de Bruxelles (Belgium), a project promoted by the international consortium T2Dsystems, which has allowed to create a repository with the results of the genomic, transcriptomic and epigenetic analysis of more than 500 human pacreatic samples.
This resource, called TIGER (Translational human Pancreatic Islet Genotype tissue-Expression Resource), allows an integrative exploration of the genetic expression data of pancreatic islets and that may have an effect on the development of type 2 diabetes. The results of this research have been published in Cell Reports, where Lorena Alonso (BSC), Anthony Piron (Université Libre de Bruxelles) and Ignasi Morán (BSC) are the lead authors.
TIGER is the largest pancreatic islet resource to date, in which 32 novel target genes have been identified that may contribute to type 2 diabetes risk. This is the first step towards understanding how each of these genetic variants increases type 2 diabetes risk, to potentially lead to the development of drug targets.
The study did not proceed without challenges: an enormous amount of data had to be harmonized and analyzed, something only possible by using the supercomputing resources at the Barcelona Supercomputing Center. “The amount of data generated is impossible to manage and analyze with a standard computer. Here, we used the most up to date supercomputing technology, without which we would have not been able to perform these analyses”, says David Torrents, one of the senior authors of this study and BSC group leader.
The study applied several innovative analytic strategies. Ignasi Morán, one of the lead authors, and methods developers, and BSC researcher, says: “A large part of this study consisted in developing new statistical methods to analyze differences in gene expression between individuals. This has allowed us to go one step further in the understanding of how genetic variants increase risk for developing type 2 diabetes”.
The researchers have made these data publicly available, and easily accessible to the diabetes research community through the TIGER web portal (tiger.bsc.es) thereby facilitating the access to and interpretation of these research findings. “We are proud that we are now able to share this wealth of data to the scientific community in an easily accessible way for all researchers in the type 2 diabetes field, without the need of computational or bioinformatic expertise”, stresses Lorena Alonso, one of the lead authors and BSC researcher.
DOI: https://doi.org/10.1016/j.celrep.2021.109807