Sarah Cooper, Sofia Obolenski, Andrew J Waters, Andrew R Bassett, Matthew A Coelho
{"title":"Analyzing the functional effects of DNA variants with gene editing.","authors":"Sarah Cooper, Sofia Obolenski, Andrew J Waters, Andrew R Bassett, Matthew A Coelho","doi":"10.1016/j.crmeth.2024.100776","DOIUrl":null,"url":null,"abstract":"<p><p>Continual advancements in genomics have led to an ever-widening disparity between the rate of discovery of genetic variants and our current understanding of their functions and potential roles in disease. Systematic methods for phenotyping DNA variants are required to effectively translate genomics data into improved outcomes for patients with genetic diseases. To make the biggest impact, these approaches must be scalable and accurate, faithfully reflect disease biology, and define complex disease mechanisms. We compare current methods to analyze the function of variants in their endogenous DNA context using genome editing strategies, such as saturation genome editing, base editing and prime editing. We discuss how these technologies can be linked to high-content readouts to gain deep mechanistic insights into variant effects. Finally, we highlight key challenges that need to be addressed to bridge the genotype to phenotype gap, and ultimately improve the diagnosis and treatment of genetic diseases.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100776"},"PeriodicalIF":4.3000,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11133854/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Reports Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.crmeth.2024.100776","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/13 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Continual advancements in genomics have led to an ever-widening disparity between the rate of discovery of genetic variants and our current understanding of their functions and potential roles in disease. Systematic methods for phenotyping DNA variants are required to effectively translate genomics data into improved outcomes for patients with genetic diseases. To make the biggest impact, these approaches must be scalable and accurate, faithfully reflect disease biology, and define complex disease mechanisms. We compare current methods to analyze the function of variants in their endogenous DNA context using genome editing strategies, such as saturation genome editing, base editing and prime editing. We discuss how these technologies can be linked to high-content readouts to gain deep mechanistic insights into variant effects. Finally, we highlight key challenges that need to be addressed to bridge the genotype to phenotype gap, and ultimately improve the diagnosis and treatment of genetic diseases.
基因组学的不断进步导致基因变异的发现速度与我们目前对其功能和潜在疾病作用的了解之间的差距越来越大。要想有效地将基因组学数据转化为改善遗传病患者治疗效果的方法,就必须采用系统的 DNA 变异表型分析方法。为了产生最大的影响,这些方法必须具有可扩展性和准确性,能忠实反映疾病生物学特性,并能确定复杂的疾病机制。我们比较了目前使用基因组编辑策略(如饱和基因组编辑、碱基编辑和质粒编辑)分析变体在其内源 DNA 背景下的功能的方法。我们讨论了如何将这些技术与高含量读数联系起来,以深入了解变异效应的机理。最后,我们强调了需要应对的关键挑战,以弥合基因型与表型之间的差距,最终改善遗传病的诊断和治疗。