Minimized combinatorial CRISPR screens identify genetic interactions in autophagy.
Minimized combinatorial CRISPR screens identify genetic interactions in autophagy.
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DOI:
10.1093/nar/gkab309
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发表时间:
2021-06-04
影响因子:
14.9
通讯作者:
Kaulich M
中科院分区:
文献类型:
--
作者:
Diehl V;Wegner M;Grumati P;Husnjak K;Schaubeck S;Gubas A;Shah VJ;Polat IH;Langschied F;Prieto-Garcia C;Müller K;Kalousi A;Ebersberger I;Brandts CH;Dikic I;Kaulich M
Combinatorial CRISPR-Cas screens have advanced the mapping of genetic interactions, but their experimental scale limits the number of targetable gene combinations. Here, we describe 3Cs multiplexing, a rapid and scalable method to generate highly diverse and uniformly distributed combinatorial CRISPR libraries. We demonstrate that the library distribution skew is the critical determinant of its required screening coverage. By circumventing iterative cloning of PCR-amplified oligonucleotides, 3Cs multiplexing facilitates the generation of combinatorial CRISPR libraries with low distribution skews. We show that combinatorial 3Cs libraries can be screened with minimal coverages, reducing associated efforts and costs at least 10-fold. We apply a 3Cs multiplexing library targeting 12,736 autophagy gene combinations with 247,032 paired gRNAs in viability and reporter-based enrichment screens. In the viability screen, we identify, among others, the synthetic lethal WDR45B-PIK3R4 and the proliferation-enhancing ATG7-KEAP1 genetic interactions. In the reporter-based screen, we identify over 1,570 essential genetic interactions for autophagy flux, including interactions among paralogous genes, namely ATG2A-ATG2B, GABARAP-MAP1LC3B and GABARAP-GABARAPL2. However, we only observe few genetic interactions within paralogous gene families of more than two members, indicating functional compensation between them. This work establishes 3Cs multiplexing as a platform for genetic interaction screens at scale.
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DOI:
10.1093/bioinformatics/btu638
发表时间:
2015-01-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Anders S;Pyl PT;Huber W
通讯作者:
Huber W
影响因子:
5.6
作者:
Ford K;McDonald D;Mali P
通讯作者:
Mali P
影响因子:
12.3
作者:
Dang Y;Jia G;Choi J;Ma H;Anaya E;Ye C;Shankar P;Wu H
通讯作者:
Wu H
影响因子:
46.9
作者:
Doench JG;Fusi N;Sullender M;Hegde M;Vaimberg EW;Donovan KF;Smith I;Tothova Z;Wilen C;Orchard R;Virgin HW;Listgarten J;Root DE
通讯作者:
Root DE
影响因子:
12.3
作者:
Dede M;McLaughlin M;Kim E;Hart T
通讯作者:
Hart T