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Functional interpretation of non-coding sequence variation: Concepts and challenges

机译：非编码序列变异的功能解释：概念和挑战

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Understanding the functional mechanisms underlying genetic signals associated with complex traits and common diseases, such as cancer, diabetes and Alzheimer's disease, is a formidable challenge. Many genetic signals discovered through genome-wide association studies map to non-protein coding sequences, where their molecular consequences are difficult to evaluate. This article summarizes concepts for the systematic interpretation of non-coding genetic signals using genome annotation data sets in different cellular systems. We outline strategies for the global analysis of multiple association intervals and the in-depth molecular investigation of individual intervals. We highlight experimental techniques to validate candidate (potential causal) regulatory variants, with a focus on novel genome-editing techniques including CRISPR/Cas9. These approaches are also applicable to low-frequency and rare variants, which have become increasingly important in genomic studies of complex traits and diseases. There is a pressing need to translate genetic signals into biological mechanisms, leading to prognostic, diagnostic and therapeutic advances.
机译：理解与复杂性状和常见疾病（例如癌症，糖尿病和阿尔茨海默氏病）相关的遗传信号的潜在功能机制是一项艰巨的挑战。通过全基因组关联研究发现的许多遗传信号都映射到非蛋白质编码序列，其分子后果难以评估。本文概述了使用不同细胞系统中的基因组注释数据集对非编码遗传信号进行系统解释的概念。我们概述了多个关联区间的全局分析和单个区间的深入分子研究的策略。我们重点介绍了验证候选（潜在因果）调控变异的实验技术，重点是包括CRISPR / Cas9在内的新型基因组编辑技术。这些方法也适用于低频和稀有变异体，这些变异体在复杂性状和疾病的基因组研究中变得越来越重要。迫切需要将遗传信号转化为生物学机制，从而带来预后，诊断和治疗方面的进步。

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