利用饱和基因组编辑减少基因检测中的不确定性

IF 0.8 4区生物学 Q4 GENETICS & HEREDITY

Medizinische Genetik Pub Date : 2022-11-29 eCollection Date: 2022-12-01 DOI:10.1515/medgen-2022-2159

Phoebe Dace, Gregory M Findlay

{"title":"利用饱和基因组编辑减少基因检测中的不确定性","authors":"Phoebe Dace, Gregory M Findlay","doi":"10.1515/medgen-2022-2159","DOIUrl":null,"url":null,"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.","PeriodicalId":48632,"journal":{"name":"Medizinische Genetik","volume":"34 1","pages":"297-304"},"PeriodicalIF":0.8000,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11006300/pdf/","citationCount":"0","resultStr":"{\"title\":\"Reducing uncertainty in genetic testing with Saturation Genome Editing.\",\"authors\":\"Phoebe Dace, Gregory M Findlay\",\"doi\":\"10.1515/medgen-2022-2159\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":48632,\"journal\":{\"name\":\"Medizinische Genetik\",\"volume\":\"34 1\",\"pages\":\"297-304\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11006300/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medizinische Genetik\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1515/medgen-2022-2159\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/12/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q4\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medizinische Genetik","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1515/medgen-2022-2159","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/12/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}

引用次数: 0

摘要

在基因组医学时代，人类基因数据的准确解释对于优化结果至关重要。检测基因变异的功能影响的强大方法使研究人员能够描述疾病基因中数千种变异的特征。在这里，我们回顾了能够高度可扩展的变异分析的实验工具，特别关注饱和基因组编辑(SGE)。我们讨论了该技术如何被大规模应用于变异测试的例子，并描述了BRCA1的SGE数据是如何被临床验证并用于帮助解释变异的。用SGE预测变异致病性的初步成功促使人们努力将这一技术和相关技术扩展到更多的基因。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Reducing uncertainty in genetic testing with Saturation Genome Editing.

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Medizinische Genetik Medicine-Genetics (clinical)

CiteScore

1.40

自引率

9.10%

发文量

审稿时长

>12 weeks

期刊介绍： medizinischegenetik is a scientific journal that is owned and published by the German Society of Human Genetics e.V. since 1989. The journal was founded by Prof. Jan Murken, München. Self-published until 2006, from 2007-2019 published at Springer Verlag and since 2020 at De Gruyter. medizinischegenetik serves education and training among colleagues, the interdisciplinary exchange of knowledge in all areas of human genetics in clinics, practice, research and teaching. Each issue of the quarterly journal deals with a focus that provides a comprehensive overview of current developments in specific clinical pictures, technical developments and therapeutic approaches. All reviews are written in English language. The journal thus creates a platform for the international exchange of knowledge and increased awareness of German research activities in the scientific community. In addition, medizinischegenetik contains information on activities in its own subject in the German-language section. This includes conference reports, association announcements, personnel matters, statements and guidelines. With health policy questions, historical retrospectives and comments on current developments, the profession takes a stand on human genetic issues in Germany, Austria and Switzerland.