Schierding William, Antony Jisha, Cutfield Wayne S, Horsfield Julia A, O'Sullivan Justin M
Liggins Institute, University of Auckland, Grafton, Auckland 1032, New Zealand.
Department of Pathology, Dunedin School of Medicine, The University of Otago, Dunedin 9016, New Zealand.
Hum Mol Genet. 2016 Aug 1;25(15):3372-3382. doi: 10.1093/hmg/ddw165. Epub 2016 Jun 10.
Meta-analysis of genome-wide association studies has resulted in the identification of hundreds of genetic variants associated with growth and stature. Determining how these genetic variants influence growth is important, but most are non-coding, and there is little understanding of how these variants contribute to adult height. To determine the mechanisms by which human variation contributes to growth, we combined spatial genomic connectivity (high-throughput conformation capture) with functional (gene expression, expression Quantitative Trait Loci) data to determine how non-genic loci associated with infant length, pubertal and adult height and contribute to gene regulatory networks. This approach identified intergenic single-nucleotide polymorphisms (SNPs) ∼85 kb upstream of FBXW11 that spatially connect with distant loci. These regulatory connections are reinforced by evidence of SNP-enhancer effects and altered expression in genes influencing the action of human growth hormone. Functional assays provided evidence for enhancer activity of the intergenic region near FBXW11 that harbors SNP rs12153391, which is associated with an expression Quantitative Trait Loci. Our results suggest that variants in this locus have genome-wide effects as key modifiers of growth (both overgrowth and short stature) acting through a regulatory network. We believe that the genes and pathways connected with this regulatory network are potential targets that could be investigated for diagnostic, prenatal and carrier testing for growth disorders. Finally, the regulatory networks we generated illustrate the power of using existing datasets to interrogate the contribution of intergenic SNPs to common syndromes/diseases.
全基因组关联研究的荟萃分析已鉴定出数百种与生长和身高相关的基因变异。确定这些基因变异如何影响生长很重要，但大多数变异是非编码的，人们对这些变异如何影响成人身高了解甚少。为了确定人类变异影响生长的机制，我们将空间基因组连通性（高通量构象捕获）与功能（基因表达、表达数量性状位点）数据相结合，以确定与婴儿身长、青春期和成人身高相关的非基因位点如何影响基因调控网络。这种方法鉴定出了位于FBXW11上游约85 kb处的基因间单核苷酸多态性（SNP），这些SNP在空间上与远处的位点相连。SNP增强子效应的证据以及影响人类生长激素作用的基因中表达的改变，进一步证实了这些调控联系。功能分析为含有与表达数量性状位点相关的SNP rs12153391的FBXW11附近基因间区域的增强子活性提供了证据。我们的结果表明，该位点的变异通过调控网络作为生长（包括生长过度和身材矮小）的关键调节因子具有全基因组效应。我们认为，与该调控网络相关的基因和途径是生长障碍诊断、产前和携带者检测的潜在研究靶点。最后，我们生成的调控网络说明了利用现有数据集探究基因间SNP对常见综合征/疾病贡献的作用。
