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. 2020 Dec 18;10:22315. doi: 10.1038/s41598-020-79313-y

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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(A) Principal component analysis showing sample variation in two-dimensional principal component space for the sorted islet and exocrine endothelial cell samples. PC1 accounts for 23.09% of the total variation and PC2 16.07% of the total variation exocrine endothelial cell samples. PC1 accounts for 23.09% of the total variation and PC2 16.07% of the total variation. Circles indicate samples from IGM (Impaired Glucose Metabolism) donors, triangles indicate samples from normoglycemic donors. Red indicates islet MVEC samples, blue indicates exocrine MVEC samples. n = 12 (islets) and n = 13 (exocrine). (B) Heatmap with hierarchical clustering of genes and samples using the 1000 genes with the most variance. Color intensity indicates expression level, given as z-score of CPM- TMM- normalized counts. The colored bars on top indicates donor ID, condition (glycemic status) and tissue of origin respectively. A trend towards clustering by tissue of origin is evident. When samples from exocrine and islet cluster together, they originate from the same donor. n = 12 (islets) and 13 (exocrine).