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利用基因型可选择的人类生物资源对自身免疫基因座IL2RA进行细胞特异性蛋白质表型分析。

Cell-specific protein phenotypes for the autoimmune locus IL2RA using a genotype-selectable human bioresource.

作者信息

Dendrou Calliope A, Plagnol Vincent, Fung Erik, Yang Jennie H M, Downes Kate, Cooper Jason D, Nutland Sarah, Coleman Gillian, Himsworth Matthew, Hardy Matthew, Burren Oliver, Healy Barry, Walker Neil M, Koch Kerstin, Ouwehand Willem H, Bradley John R, Wareham Nicholas J, Todd John A, Wicker Linda S

机构信息

Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, UK.

出版信息

Nat Genet. 2009 Sep;41(9):1011-5. doi: 10.1038/ng.434. Epub 2009 Aug 23.

Abstract

Genome-wide association studies (GWAS) have identified over 300 regions associated with more than 70 common diseases. However, identifying causal genes within an associated region remains a major challenge. One approach to resolving causal genes is through the dissection of gene-phenotype correlations. Here we use polychromatic flow cytometry to show that differences in surface expression of the human interleukin-2 (IL-2) receptor alpha (IL2RA, or CD25) protein are restricted to particular immune cell types and correlate with several haplotypes in the IL2RA region that have previously been associated with two autoimmune diseases, type 1 diabetes (T1D) and multiple sclerosis. We confirm our strongest gene-phenotype correlation at the RNA level by allele-specific expression (ASE). We also define key parameters for the design and implementation of post-GWAS gene-phenotype investigations and demonstrate the usefulness of a large bioresource of genotype-selectable normal donors from whom fresh, primary cells can be analyzed.

摘要

全基因组关联研究(GWAS)已确定了300多个与70多种常见疾病相关的区域。然而,在相关区域内确定因果基因仍然是一项重大挑战。解决因果基因的一种方法是通过剖析基因-表型相关性。在这里,我们使用多色流式细胞术表明,人类白细胞介素-2(IL-2)受体α(IL2RA,或CD25)蛋白的表面表达差异仅限于特定的免疫细胞类型,并且与IL2RA区域中先前与两种自身免疫性疾病——1型糖尿病(T1D)和多发性硬化症相关的几种单倍型相关。我们通过等位基因特异性表达(ASE)在RNA水平上证实了最强的基因-表型相关性。我们还定义了GWAS后基因-表型研究设计和实施的关键参数,并证明了一个可选择基因型的正常供体的大型生物资源的有用性,从中可以分析新鲜的原代细胞。

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