Unraveling novel genetic mechanisms of Type 2 diabetes disease using single-cell RNA-seq data of human pancreatic islets

Identification: Martínez-López, J.A.


Description

Unraveling novel genetic mechanisms of Type 2 diabetes disease using single-cell RNA-seq data of human pancreatic islets

Martínez-López JA1, Fred R2, Muñoz-Manchado A1, Hjerling-Leffler J1, Wierup N2

1Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm (Sweden); 2Diabetes Centre, Lund University, Malmö (Sweden)

T2D is a devastating disease caused by a combination of insulin resistance and insufficient insulin release. The era of genome-wide association studies (GWAS) has shown that T2D is a polygenic disease and most T2D risk genes identified relate to islet function. Here we have used the Smart-seq2 single-cell transcriptomics method to sequence human pancreatic islets cells from 6 human control donors and 4 Type 2 diabetic donors, obtaining the transcriptome of 3075 cells. Cell identity has been determined using the two way unsupervised clustering algorithm BackSPIN and t-SNE technique uncovering 12 groups of cells. Furthermore, we have identified hundreds of genes that are differentially regulated in main cell types from T2D donors, but most of these genes have not been described in islets function previously.

Single cell RNA-seq data is ideally suited for gene-network analysis using tools such as weighted gene co-expression network analysis (WGCNA) due to the very large number of replicates where each cell is a n. Such analyses are based on co-variation of genes using the natural variability of gene expression. WGCNA allows us to create a network map of differentially regulated genes by T2D for each cell type, showing connections between them and with important islet genes based on co-expression levels. In this network, highly interconnected clusters of upregulated and/or downregulated genes by T2D for every specific cell type could give us a global perspective of genetic mechanisms, as well as specific novel genes involved in T2D.

Acknowledgments:

The single-cell transcriptome data was generated at the Eukaryotic Single-cell Genomics facility at Science for Life Laboratory in Stockholm, Sweden.

Funded by Novo Nordisk Foundation and EFSD-AZN.

Credits

Credits: None available.

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