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。

IF 7.7
Julien Dénéréaz, Elise Eray, Bimal Jana, Vincent de Bakker, Horia Todor, Tim van Opijnen, Xue Liu, Jan-Willem Veening
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引用次数: 0

摘要

基因冗余阻碍了基因型-表型关系的揭示。例如,肺炎链球菌中的大多数基因在实验室条件下都不是必需的。揭示基因冗余的一种有效方法是识别基因间的相互作用。我们开发了一种广泛适用的双crispr -seq方法和分析管道来探测全基因组的遗传相互作用(GIs)。建立了一个869个靶向高置信度操纵子的双单导rna (sgRNAs)文库,覆盖了肺炎球菌基因组中70%以上的遗传元件。对这378,015个独特组合进行测试,鉴定出4,026个显著的地理标志。除了已知的地理信息系统,我们还发现了以前未知的积极和消极的相互作用,涉及基因在基本细胞过程中,如分裂和染色体分离。所提出的方法和生物信息学方法可以作为其他生物全基因组基因相互作用研究的路线图。所有的相互作用都可以通过肺炎球菌遗传相互作用网络(肺炎gin)进行探索,这可以作为新的生物学发现的起点。本文的透明同行评议过程记录包含在补充信息中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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