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Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed b...

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Autores principales: Thurner, Matthias, van de Bunt, Martijn, Torres, Jason M, Mahajan, Anubha, Nylander, Vibe, Bennett, Amanda J, Gaulton, Kyle J, Barrett, Amy, Burrows, Carla, Bell, Christopher G, Lowe, Robert, Beck, Stephan, Rakyan, Vardhman K, Gloyn, Anna L, McCarthy, Mark I
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5828664/
https://www.ncbi.nlm.nih.gov/pubmed/29412141
http://dx.doi.org/10.7554/eLife.31977
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author Thurner, Matthias
van de Bunt, Martijn
Torres, Jason M
Mahajan, Anubha
Nylander, Vibe
Bennett, Amanda J
Gaulton, Kyle J
Barrett, Amy
Burrows, Carla
Bell, Christopher G
Lowe, Robert
Beck, Stephan
Rakyan, Vardhman K
Gloyn, Anna L
McCarthy, Mark I
author_facet Thurner, Matthias
van de Bunt, Martijn
Torres, Jason M
Mahajan, Anubha
Nylander, Vibe
Bennett, Amanda J
Gaulton, Kyle J
Barrett, Amy
Burrows, Carla
Bell, Christopher G
Lowe, Robert
Beck, Stephan
Rakyan, Vardhman K
Gloyn, Anna L
McCarthy, Mark I
author_sort Thurner, Matthias
collection PubMed
description Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.
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spelling pubmed-58286642018-02-28 Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci Thurner, Matthias van de Bunt, Martijn Torres, Jason M Mahajan, Anubha Nylander, Vibe Bennett, Amanda J Gaulton, Kyle J Barrett, Amy Burrows, Carla Bell, Christopher G Lowe, Robert Beck, Stephan Rakyan, Vardhman K Gloyn, Anna L McCarthy, Mark I eLife Genetics and Genomics Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis. eLife Sciences Publications, Ltd 2018-02-07 /pmc/articles/PMC5828664/ /pubmed/29412141 http://dx.doi.org/10.7554/eLife.31977 Text en © 2018, Thurner et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Genetics and Genomics
Thurner, Matthias
van de Bunt, Martijn
Torres, Jason M
Mahajan, Anubha
Nylander, Vibe
Bennett, Amanda J
Gaulton, Kyle J
Barrett, Amy
Burrows, Carla
Bell, Christopher G
Lowe, Robert
Beck, Stephan
Rakyan, Vardhman K
Gloyn, Anna L
McCarthy, Mark I
Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci
title Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci
title_full Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci
title_fullStr Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci
title_full_unstemmed Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci
title_short Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci
title_sort integration of human pancreatic islet genomic data refines regulatory mechanisms at type 2 diabetes susceptibility loci
topic Genetics and Genomics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5828664/
https://www.ncbi.nlm.nih.gov/pubmed/29412141
http://dx.doi.org/10.7554/eLife.31977
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