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单核苷酸多态性(SNP)基因型对原代人白细胞基因表达影响的复杂本质。

Complex nature of SNP genotype effects on gene expression in primary human leucocytes.

作者信息

Heap Graham A, Trynka Gosia, Jansen Ritsert C, Bruinenberg Marcel, Swertz Morris A, Dinesen Lotte C, Hunt Karen A, Wijmenga Cisca, Vanheel David A, Franke Lude

机构信息

Institute of Cell and Molecular Science, Barts and The London School of Medicine and Dentistry, London, E1 2AT, UK.

出版信息

BMC Med Genomics. 2009 Jan 7;2:1. doi: 10.1186/1755-8794-2-1.

Abstract

BACKGROUND

Genome wide association studies have been hugely successful in identifying disease risk variants, yet most variants do not lead to coding changes and how variants influence biological function is usually unknown.

METHODS

We correlated gene expression and genetic variation in untouched primary leucocytes (n = 110) from individuals with celiac disease - a common condition with multiple risk variants identified. We compared our observations with an EBV-transformed HapMap B cell line dataset (n = 90), and performed a meta-analysis to increase power to detect non-tissue specific effects.

RESULTS

In celiac peripheral blood, 2,315 SNP variants influenced gene expression at 765 different transcripts (< 250 kb from SNP, at FDR = 0.05, cis expression quantitative trait loci, eQTLs). 135 of the detected SNP-probe effects (reflecting 51 unique probes) were also detected in a HapMap B cell line published dataset, all with effects in the same allelic direction. Overall gene expression differences within the two datasets predominantly explain the limited overlap in observed cis-eQTLs. Celiac associated risk variants from two regions, containing genes IL18RAP and CCR3, showed significant cis genotype-expression correlations in the peripheral blood but not in the B cell line datasets. We identified 14 genes where a SNP affected the expression of different probes within the same gene, but in opposite allelic directions. By incorporating genetic variation in co-expression analyses, functional relationships between genes can be more significantly detected.

CONCLUSION

In conclusion, the complex nature of genotypic effects in human populations makes the use of a relevant tissue, large datasets, and analysis of different exons essential to enable the identification of the function for many genetic risk variants in common diseases.

摘要

背景

全基因组关联研究在识别疾病风险变异方面取得了巨大成功,但大多数变异不会导致编码变化,而且变异如何影响生物学功能通常尚不清楚。

方法

我们将乳糜泻患者未受影响的原代白细胞(n = 110)中的基因表达与遗传变异进行了关联分析——乳糜泻是一种常见疾病,已鉴定出多个风险变异。我们将我们的观察结果与一个EBV转化的HapMap B细胞系数据集(n = 90)进行了比较,并进行了荟萃分析以提高检测非组织特异性效应的能力。

结果

在乳糜泻外周血中,2315个单核苷酸多态性(SNP)变异影响了765个不同转录本的基因表达(SNP距离小于250 kb,错误发现率FDR = 0.05,顺式表达数量性状位点,即eQTL)。在已发表的HapMap B细胞系数据集中也检测到了135个检测到的SNP-探针效应(反映51个独特探针),所有效应的等位基因方向相同。两个数据集内的总体基因表达差异主要解释了观察到的顺式eQTL中有限的重叠。来自两个区域的与乳糜泻相关的风险变异,包含IL18RAP和CCR3基因,在外周血中显示出显著的顺式基因型-表达相关性,但在B细胞系数据集中未显示。我们鉴定出14个基因,其中一个SNP在同一基因内影响不同探针的表达,但等位基因方向相反。通过在共表达分析中纳入遗传变异,可以更显著地检测基因之间的功能关系。

结论

总之,人群中基因型效应的复杂性使得使用相关组织、大型数据集以及对不同外显子进行分析对于识别常见疾病中许多遗传风险变异的功能至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe0/2628677/825e3b65646c/1755-8794-2-1-1.jpg

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