Institute of Animal Sciences, Humboldt-Universtät zu Berlin, Germany.
OMICS. 2011 Jul-Aug;15(7-8):507-12. doi: 10.1089/omi.2010.0154. Epub 2011 Jun 23.
Recent technological progress has permitted the efficient performance of genome-wide association studies (GWAS) to map genetic variants associated with common diseases. Here, we analyzed 2,893 single nucleotide polymorphisms (SNPs) that have been identified in 593 published GWAS as associated with a disease phenotype with respect to their genomic location. In absolute numbers, most significant SNPs are located in intergenic regions and introns. When compared to their representation on the chips, there is essentially overrepresentation of nonsynonymous coding SNPs (nsSNPs), synonymous coding SNPs, and SNPs in untranscribed regions upstream of genes among the disease associated SNPs. A Gene Ontology term analysis showed that genes putatively causing a phenotype often code for membrane associated proteins or signal transduction genes.
最近的技术进步使得全基因组关联研究(GWAS)能够有效地进行,以绘制与常见疾病相关的遗传变异。在这里,我们分析了 2893 个单核苷酸多态性(SNP),这些 SNP 是在 593 项已发表的 GWAS 中确定的,与疾病表型相关,这些 SNP 与基因组位置有关。从绝对数量上看,大多数显著的 SNP 位于基因间区和内含子中。与芯片上的 SNP 相比,疾病相关 SNP 中存在非同义编码 SNP(nsSNP)、同义编码 SNP 和基因上游未转录区 SNP 的显著过表达。基因本体论术语分析表明,可能导致表型的基因通常编码膜相关蛋白或信号转导基因。