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糖尿病中的非编码基因组功能

Non-coding genome functions in diabetes.

作者信息

Cebola Inês, Pasquali Lorenzo

机构信息

Department of MedicineImperial College London, London W12 0NN, UKDivision of EndocrinologyGermans Trias i Pujol University Hospital and Research Institute, 08916 Badalona, SpainJosep Carreras Leukaemia Research Institute08916 Badalona, SpainCIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM)08036 Barcelona, Spain.

Department of MedicineImperial College London, London W12 0NN, UKDivision of EndocrinologyGermans Trias i Pujol University Hospital and Research Institute, 08916 Badalona, SpainJosep Carreras Leukaemia Research Institute08916 Badalona, SpainCIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM)08036 Barcelona, Spain Department of MedicineImperial College London, London W12 0NN, UKDivision of EndocrinologyGermans Trias i Pujol University Hospital and Research Institute, 08916 Badalona, SpainJosep Carreras Leukaemia Research Institute08916 Badalona, SpainCIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM)08036 Barcelona, Spain Department of MedicineImperial College London, London W12 0NN, UKDivision of EndocrinologyGermans Trias i Pujol University Hospital and Research Institute, 08916 Badalona, SpainJosep Carreras Leukaemia Research Institute08916 Badalona, SpainCIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM)08036 Barcelona, Spain

出版信息

J Mol Endocrinol. 2016 Jan;56(1):R1-R20. doi: 10.1530/JME-15-0197. Epub 2015 Oct 5.

Abstract

Most of the genetic variation associated with diabetes, through genome-wide association studies, does not reside in protein-coding regions, making the identification of functional variants and their eventual translation to the clinic challenging. In recent years, high-throughput sequencing-based methods have enabled genome-scale high-resolution epigenomic profiling in a variety of human tissues, allowing the exploration of the human genome outside of the well-studied coding regions. These experiments unmasked tens of thousands of regulatory elements across several cell types, including diabetes-relevant tissues, providing new insights into their mechanisms of gene regulation. Regulatory landscapes are highly dynamic and cell-type specific and, being sensitive to DNA sequence variation, can vary with individual genomes. The scientific community is now in place to exploit the regulatory maps of tissues central to diabetes etiology, such as pancreatic progenitors and adult islets. This giant leap forward in the understanding of pancreatic gene regulation is revolutionizing our capacity to discriminate between functional and non-functional non-coding variants, opening opportunities to uncover regulatory links between sequence variation and diabetes susceptibility. In this review, we focus on the non-coding regulatory landscape of the pancreatic endocrine cells and provide an overview of the recent developments in this field.

摘要

通过全基因组关联研究发现,与糖尿病相关的大多数基因变异并不存在于蛋白质编码区域,这使得识别功能性变异并最终将其应用于临床具有挑战性。近年来,基于高通量测序的方法能够在多种人体组织中进行全基因组规模的高分辨率表观基因组分析,从而得以探索研究充分的编码区域之外的人类基因组。这些实验揭示了包括糖尿病相关组织在内的多种细胞类型中的数万个调控元件,为基因调控机制提供了新的见解。调控图谱具有高度动态性和细胞类型特异性,并且对DNA序列变异敏感,会因个体基因组而异。科学界现在正准备利用糖尿病病因学核心组织(如胰腺祖细胞和成年胰岛)的调控图谱。在胰腺基因调控理解方面的这一巨大飞跃正在彻底改变我们区分功能性和非功能性非编码变异的能力,为揭示序列变异与糖尿病易感性之间的调控联系带来了机遇。在本综述中,我们聚焦于胰腺内分泌细胞的非编码调控图谱,并概述该领域的最新进展。

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