Department of Genomics and Systems Biology, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Diabetes. 2010 Mar;59(3):726-32. doi: 10.2337/db09-1277. Epub 2009 Dec 15.
Genome-wide association studies that compare the statistical association between thousands of DNA variations and a human trait have detected 958 loci across 127 different diseases and traits. However, these statistical associations only provide evidence for genomic regions likely to harbor a causal gene(s) and do not directly identify such genes. We combined gene variation and expression data in a human cohort to identify causal genes.
Global gene transcription activity was obtained for each individual in a large human cohort (n = 1,240). These quantitative transcript data were tested for correlation with genotype data generated from the same individuals to identify gene expression patterns influenced by the variants.
Variant rs8050136 lies within intron 1 of the FTO gene on chromosome 16 and marks a locus strongly associated with type 2 diabetes and obesity and widely replicated across many populations. We report that genetic variation at this locus does not influence FTO gene expression levels (P = 0.38), but is strongly correlated with expression of RBL2 (P = 2.7 x 10(-5)), approximately 270,000 base pairs distant to FTO.
These data suggest that variants at FTO influence RBL2 gene expression at large genetic distances. This observation underscores the complexity of human transcriptional regulation and highlights the utility of large human cohorts in which both genetic variation and global gene expression data are available to identify disease genes. Expedient identification of genes mediating the effects of genome-wide association study-identified loci will enable mechanism-of-action studies and accelerate understanding of human disease processes under genetic influence.
全基因组关联研究比较了数千个 DNA 变异与人类特征之间的统计关联,在 127 种不同的疾病和特征中检测到了 958 个位点。然而,这些统计关联仅提供了可能包含因果基因(s)的基因组区域的证据,而不能直接识别这些基因。我们结合了人类队列中的基因变异和表达数据,以确定因果基因。
对一个大型人类队列中的每个个体(n=1240)的整体基因转录活性进行了研究。对这些定量转录数据进行了与来自同一个体的基因型数据的相关性测试,以识别受变体影响的基因表达模式。
变体 rs8050136 位于 16 号染色体 FTO 基因的内含子 1 内,该基因与 2 型糖尿病和肥胖密切相关,在许多人群中广泛复制。我们报告称,该位点的遗传变异不会影响 FTO 基因的表达水平(P=0.38),但与 RBL2 的表达呈强烈相关(P=2.7×10(-5)),距离 FTO 约 270000 个碱基对。
这些数据表明,FTO 上的变体影响 RBL2 基因在较大遗传距离上的表达。这一观察结果突出了人类转录调控的复杂性,并强调了在具有遗传变异和全基因组表达数据的大型人类队列中识别疾病基因的效用。快速识别介导全基因组关联研究确定的位点效应的基因将使机制作用研究成为可能,并加速对遗传影响下人类疾病过程的理解。