Julien Dénéréaz, Elise Eray, Bimal Jana, Vincent de Bakker, Horia Todor, Tim van Opijnen, Xue Liu, Jan-Willem Veening
{"title":"用于全基因组遗传相互作用研究的双crispr -seq鉴定了参与肺炎球菌细胞周期的关键基因。","authors":"Julien Dénéréaz, Elise Eray, Bimal Jana, Vincent de Bakker, Horia Todor, Tim van Opijnen, Xue Liu, Jan-Willem Veening","doi":"10.1016/j.cels.2025.101408","DOIUrl":null,"url":null,"abstract":"<p><p>Uncovering genotype-phenotype relationships is hampered by genetic redundancy. For example, most genes in Streptococcus pneumoniae are non-essential under laboratory conditions. A powerful approach to unravel genetic redundancy is by identifying gene-gene interactions. We developed a broadly applicable dual CRISPRi-seq method and analysis pipeline to probe genetic interactions (GIs) genome-wide. A library of 869 dual single-guide RNAs (sgRNAs) targeting high-confidence operons was created, covering over 70% of the genetic elements in the pneumococcal genome. Testing these 378,015 unique combinations, 4,026 significant GIs were identified. Besides known GIs, we found previously unknown positive and negative interactions involving genes in fundamental cellular processes such as division and chromosome segregation. The presented methods and bioinformatic approaches can serve as a roadmap for genome-wide gene interaction studies in other organisms. All interactions are available for exploration via the Pneumococcal Genetic Interaction Network (PneumoGIN), which can serve as a starting point for new biological discoveries. A record of this paper's transparent peer review process is included in the supplemental information.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101408"},"PeriodicalIF":7.7000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dual CRISPRi-seq for genome-wide genetic interaction studies identifies key genes involved in the pneumococcal cell cycle.\",\"authors\":\"Julien Dénéréaz, Elise Eray, Bimal Jana, Vincent de Bakker, Horia Todor, Tim van Opijnen, Xue Liu, Jan-Willem Veening\",\"doi\":\"10.1016/j.cels.2025.101408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Uncovering genotype-phenotype relationships is hampered by genetic redundancy. For example, most genes in Streptococcus pneumoniae are non-essential under laboratory conditions. A powerful approach to unravel genetic redundancy is by identifying gene-gene interactions. We developed a broadly applicable dual CRISPRi-seq method and analysis pipeline to probe genetic interactions (GIs) genome-wide. A library of 869 dual single-guide RNAs (sgRNAs) targeting high-confidence operons was created, covering over 70% of the genetic elements in the pneumococcal genome. Testing these 378,015 unique combinations, 4,026 significant GIs were identified. Besides known GIs, we found previously unknown positive and negative interactions involving genes in fundamental cellular processes such as division and chromosome segregation. The presented methods and bioinformatic approaches can serve as a roadmap for genome-wide gene interaction studies in other organisms. All interactions are available for exploration via the Pneumococcal Genetic Interaction Network (PneumoGIN), which can serve as a starting point for new biological discoveries. A record of this paper's transparent peer review process is included in the supplemental information.</p>\",\"PeriodicalId\":93929,\"journal\":{\"name\":\"Cell systems\",\"volume\":\" \",\"pages\":\"101408\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2025-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.cels.2025.101408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.cels.2025.101408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dual CRISPRi-seq for genome-wide genetic interaction studies identifies key genes involved in the pneumococcal cell cycle.
Uncovering genotype-phenotype relationships is hampered by genetic redundancy. For example, most genes in Streptococcus pneumoniae are non-essential under laboratory conditions. A powerful approach to unravel genetic redundancy is by identifying gene-gene interactions. We developed a broadly applicable dual CRISPRi-seq method and analysis pipeline to probe genetic interactions (GIs) genome-wide. A library of 869 dual single-guide RNAs (sgRNAs) targeting high-confidence operons was created, covering over 70% of the genetic elements in the pneumococcal genome. Testing these 378,015 unique combinations, 4,026 significant GIs were identified. Besides known GIs, we found previously unknown positive and negative interactions involving genes in fundamental cellular processes such as division and chromosome segregation. The presented methods and bioinformatic approaches can serve as a roadmap for genome-wide gene interaction studies in other organisms. All interactions are available for exploration via the Pneumococcal Genetic Interaction Network (PneumoGIN), which can serve as a starting point for new biological discoveries. A record of this paper's transparent peer review process is included in the supplemental information.