Nikolic Miloš, Papantonis Argyris, Rada-Iglesias Alvaro
Center for Molecular Medicine Cologne (CMMC), Robert-Koch-Str. 21, 50931 Cologne, Germany.
The Cologne Cluster of Excellence in Cellular Stress Responses in Aging-associated Diseases (CECAD), Joseph-Stelzmann-Straße 26, 50931 Cologne, Germany.
Hum Mol Genet. 2017 Feb 15;26(4):742-752. doi: 10.1093/hmg/ddw423.
Genome-wide association studies (GWAS) have emerged as a powerful tool to uncover the genetic basis of human common diseases, which often show a complex, polygenic and multi-factorial aetiology. These studies have revealed that 70-90% of all single nucleotide polymorphisms (SNPs) associated with common complex diseases do not occur within genes (i.e. they are non-coding), making the discovery of disease-causative genetic variants and the elucidation of the underlying pathological mechanisms far from straightforward. Based on emerging evidences suggesting that disease-associated SNPs are frequently found within cell type-specific regulatory sequences, here we present GARLIC (GWAS-based Prediction Toolkit for Connecting Diseases and Cell Types), a user-friendly, multi-purpose software with an associated database and online viewer that, using global maps of cis-regulatory elements, can aetiologically connect human diseases with relevant cell types. Additionally, GARLIC can be used to retrieve potential disease-causative genetic variants overlapping regulatory sequences of interest. Overall, GARLIC can satisfy several important needs within the field of medical genetics, thus potentially assisting in the ultimate goal of uncovering the elusive and complex genetic basis of common human disorders.
全基因组关联研究(GWAS)已成为揭示人类常见疾病遗传基础的有力工具,这些疾病通常呈现出复杂、多基因和多因素的病因。这些研究表明,与常见复杂疾病相关的所有单核苷酸多态性(SNP)中,70 - 90%并不出现在基因内(即它们是非编码的),这使得发现致病基因变异以及阐明潜在的病理机制并非易事。基于新出现的证据表明疾病相关的SNP经常出现在细胞类型特异性调控序列中,我们在此介绍GARLIC(基于GWAS的疾病与细胞类型关联预测工具包),这是一款用户友好的多功能软件,配有相关数据库和在线查看器,它利用顺式调控元件的全局图谱,能够从病因学角度将人类疾病与相关细胞类型联系起来。此外,GARLIC可用于检索与感兴趣的调控序列重叠的潜在致病基因变异。总体而言,GARLIC能够满足医学遗传学领域的几个重要需求,从而有可能助力实现揭示人类常见疾病难以捉摸且复杂的遗传基础这一最终目标。