Rebeca Olvera-León, Fang Zhang, Victoria Offord, Yajie Zhao, Hong Kee Tan, Prashant Gupta, Tuya Pal, Carla Daniela Robles-Espinoza, Fernanda G. Arriaga-González, Larissa Satiko Alcantara Sekimoto Matsuyama, Erwan Delage, Ed Dicks, Suzana Ezquina, Charlie F. Rowlands, Clare Turnbull, Paul Pharoah, John R.B. Perry, Maria Jasin, Andrew J. Waters, David J. Adams
{"title":"通过饱和基因组编辑绘制 RAD51C 的高分辨率功能图谱","authors":"Rebeca Olvera-León, Fang Zhang, Victoria Offord, Yajie Zhao, Hong Kee Tan, Prashant Gupta, Tuya Pal, Carla Daniela Robles-Espinoza, Fernanda G. Arriaga-González, Larissa Satiko Alcantara Sekimoto Matsuyama, Erwan Delage, Ed Dicks, Suzana Ezquina, Charlie F. Rowlands, Clare Turnbull, Paul Pharoah, John R.B. Perry, Maria Jasin, Andrew J. Waters, David J. Adams","doi":"10.1016/j.cell.2024.08.039","DOIUrl":null,"url":null,"abstract":"<p>Pathogenic variants in <em>RAD51C</em> confer an elevated risk of breast and ovarian cancer, while individuals homozygous for specific <em>RAD51C</em> alleles may develop Fanconi anemia. Using saturation genome editing (SGE), we functionally assess 9,188 unique variants, including >99.5% of all possible coding sequence single-nucleotide alterations. By computing changes in variant abundance and Gaussian mixture modeling (GMM), we functionally classify 3,094 variants to be disruptive and use clinical truth sets to reveal an accuracy/concordance of variant classification >99.9%. Cell fitness was the primary assay readout allowing us to observe a phenomenon where specific missense variants exhibit distinct depletion kinetics potentially suggesting that they represent hypomorphic alleles. We further explored our exhaustive functional map, revealing critical residues on the RAD51C structure and resolving variants found in cancer-segregating kindred. Furthermore, through interrogation of UK Biobank and a large multi-center ovarian cancer cohort, we find significant associations between SGE-depleted variants and cancer diagnoses.</p>","PeriodicalId":9656,"journal":{"name":"Cell","volume":null,"pages":null},"PeriodicalIF":45.5000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-resolution functional mapping of RAD51C by saturation genome editing\",\"authors\":\"Rebeca Olvera-León, Fang Zhang, Victoria Offord, Yajie Zhao, Hong Kee Tan, Prashant Gupta, Tuya Pal, Carla Daniela Robles-Espinoza, Fernanda G. Arriaga-González, Larissa Satiko Alcantara Sekimoto Matsuyama, Erwan Delage, Ed Dicks, Suzana Ezquina, Charlie F. Rowlands, Clare Turnbull, Paul Pharoah, John R.B. Perry, Maria Jasin, Andrew J. Waters, David J. Adams\",\"doi\":\"10.1016/j.cell.2024.08.039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Pathogenic variants in <em>RAD51C</em> confer an elevated risk of breast and ovarian cancer, while individuals homozygous for specific <em>RAD51C</em> alleles may develop Fanconi anemia. Using saturation genome editing (SGE), we functionally assess 9,188 unique variants, including >99.5% of all possible coding sequence single-nucleotide alterations. By computing changes in variant abundance and Gaussian mixture modeling (GMM), we functionally classify 3,094 variants to be disruptive and use clinical truth sets to reveal an accuracy/concordance of variant classification >99.9%. Cell fitness was the primary assay readout allowing us to observe a phenomenon where specific missense variants exhibit distinct depletion kinetics potentially suggesting that they represent hypomorphic alleles. We further explored our exhaustive functional map, revealing critical residues on the RAD51C structure and resolving variants found in cancer-segregating kindred. Furthermore, through interrogation of UK Biobank and a large multi-center ovarian cancer cohort, we find significant associations between SGE-depleted variants and cancer diagnoses.</p>\",\"PeriodicalId\":9656,\"journal\":{\"name\":\"Cell\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":45.5000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1016/j.cell.2024.08.039\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.cell.2024.08.039","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
High-resolution functional mapping of RAD51C by saturation genome editing
Pathogenic variants in RAD51C confer an elevated risk of breast and ovarian cancer, while individuals homozygous for specific RAD51C alleles may develop Fanconi anemia. Using saturation genome editing (SGE), we functionally assess 9,188 unique variants, including >99.5% of all possible coding sequence single-nucleotide alterations. By computing changes in variant abundance and Gaussian mixture modeling (GMM), we functionally classify 3,094 variants to be disruptive and use clinical truth sets to reveal an accuracy/concordance of variant classification >99.9%. Cell fitness was the primary assay readout allowing us to observe a phenomenon where specific missense variants exhibit distinct depletion kinetics potentially suggesting that they represent hypomorphic alleles. We further explored our exhaustive functional map, revealing critical residues on the RAD51C structure and resolving variants found in cancer-segregating kindred. Furthermore, through interrogation of UK Biobank and a large multi-center ovarian cancer cohort, we find significant associations between SGE-depleted variants and cancer diagnoses.
期刊介绍:
Cells is an international, peer-reviewed, open access journal that focuses on cell biology, molecular biology, and biophysics. It is affiliated with several societies, including the Spanish Society for Biochemistry and Molecular Biology (SEBBM), Nordic Autophagy Society (NAS), Spanish Society of Hematology and Hemotherapy (SEHH), and Society for Regenerative Medicine (Russian Federation) (RPO).
The journal publishes research findings of significant importance in various areas of experimental biology, such as cell biology, molecular biology, neuroscience, immunology, virology, microbiology, cancer, human genetics, systems biology, signaling, and disease mechanisms and therapeutics. The primary criterion for considering papers is whether the results contribute to significant conceptual advances or raise thought-provoking questions and hypotheses related to interesting and important biological inquiries.
In addition to primary research articles presented in four formats, Cells also features review and opinion articles in its "leading edge" section, discussing recent research advancements and topics of interest to its wide readership.