PICKLES: the database of pooled in-vitro CRISPR knockout library essentiality screens.
PICKLES: the database of pooled in-vitro CRISPR knockout library essentiality screens.
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DOI：
10.1093/nar/gkx993
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发表时间：
2018-01-04
影响因子：
14.9
通讯作者：
Hart T
中科院分区：
文献类型：
--
作者：
Lenoir WF;Lim TL;Hart T
CRISPR/Cas9系统在哺乳动物细胞中用于合并文库遗传敲除筛选的适应性已经实质性地推进了人类功能基因组学的现有技术。筛选基因敲除造成显著适应性缺陷的细胞系小组极大地扩展了我们的高置信度必需基因目录，并且已经证明在识别肿瘤特异性必需基因以开发靶向治疗方面是有用的。然而，非专家目前缺乏一种易于使用的方法来访问这些数据，并确定他们感兴趣的基因是否在不同的遗传背景中是必不可少的。预计筛查数据量将大幅增长，使问题更加棘手。在这里，我们描述了PICKLES，汇集体外CRISPR敲除文库必要性筛选的数据库，最终用户可以显示和下载50多个细胞系中超过18000个蛋白质编码基因的原始或标准化的必要性特征。还包括在超过100个细胞系中由汇集的文库shRNA靶向的15，000个基因的额外数据集。研究人员可以一目了然地看到他们感兴趣的基因的相对适应性缺陷和组织特异性，在本地生成和保存数据，并下载所有原始数据。该数据库可在http://pickles.hart-lab.org上查阅。
The adaptation of CRISPR/Cas9 systems for pooled library genetic knockout screens in mammalian cells has substantially advanced the state of the art in human functional genomics. Screening panels of cell lines for genes whose knockout imposes a significant fitness defect has dramatically expanded our catalog of high-confidence essential genes, and has already proven useful in identifying tumor-specific essential genes for the development of targeted therapies. However, nonexperts currently lack an easy to use way to access this data and to identify whether their genes of interest are essential across different genetic backgrounds. The volume of screening data is expected to grow massively, making the problem more intractable. Here we describe PICKLES, the database of Pooled In vitro CRISPR Knockout Library Essentiality Screens, where end users can display and download raw or normalized essentiality profiles for more that 18 000 protein-coding genes across more than 50 cell lines. An additional data set with 15,000 genes targeted by pooled library shRNA in over 100 cell lines is also included. Researchers can see at a glance the relative fitness defect and tissue specificity of their genes of interest, generate and save figures locally, and download all raw data. The database is available at http://pickles.hart-lab.org.
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DOI：
10.1126/science.aah7111
发表时间：
2017-01-06
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Liu SJ;Horlbeck MA;Cho SW;Birk HS;Malatesta M;He D;Attenello FJ;Villalta JE;Cho MY;Chen Y;Mandegar MA;Olvera MP;Gilbert LA;Conklin BR;Chang HY;Weissman JS;Lim DA
通讯作者：
Lim DA
影响因子：
64.8
作者：
Konermann S;Brigham MD;Trevino AE;Joung J;Abudayyeh OO;Barcena C;Hsu PD;Habib N;Gootenberg JS;Nishimasu H;Nureki O;Zhang F
通讯作者：
Zhang F
影响因子：
8.8
作者：
Tzelepis K;Koike-Yusa H;De Braekeleer E;Li Y;Metzakopian E;Dovey OM;Mupo A;Grinkevich V;Li M;Mazan M;Gozdecka M;Ohnishi S;Cooper J;Patel M;McKerrell T;Chen B;Domingues AF;Gallipoli P;Teichmann S;Ponstingl H;McDermott U;Saez-Rodriguez J;Huntly BJP;Iorio F;Pina C;Vassiliou GS;Yusa K
通讯作者：
Yusa K
影响因子：
64.5
作者：
McDonald, E. Robert, III;de Weck, Antoine;Sellers, William R.
通讯作者：
Sellers, William R.
影响因子：
8.8
作者：
Medrano, Mauricio;Communal, Laudine;Rottapel, Robert
通讯作者：
Rottapel, Robert