Abstract:
Accurate interpretation of human genetic data is critical for optimizing outcomes in the era of genomic medicine. Powerful methods for testing genetic variants for functional effects are allowing researchers to characterize thousands of variants across disease genes. Here, we review experimental tools enabling highly scalable assays of variants, focusing specifically on Saturation Genome Editing (SGE). We discuss examples of how this technique is being implemented for variant testing at scale and describe how SGE data for BRCA1 have been clinically validated and used to aid variant interpretation. The initial success at predicting variant pathogenicity with SGE has spurred efforts to expand this and related techniques to many more genes.
摘要:
准确解释人类基因数据对于优化基因组医学时代的结果至关重要。用于测试遗传变异的功能效应的强大方法使研究人员能够表征跨疾病基因的数千个变异。这里,我们回顾了能够实现高度可扩展的变体测定的实验工具,专注于饱和基因组编辑(SGE)。我们讨论了如何在大规模的变体测试中实施此技术的示例,并描述了如何对BRCA1的SGE数据进行临床验证并用于辅助变体解释。用SGE预测变异致病性的初步成功促使人们努力将这种技术和相关技术扩展到更多的基因。