Title |
Pooled CRISPR interference screening enables genome-scale functional genomics study in bacteria with superior performance
|
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Published in |
Nature Communications, June 2018
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DOI | 10.1038/s41467-018-04899-x |
Pubmed ID | |
Authors |
Tianmin Wang, Changge Guan, Jiahui Guo, Bing Liu, Yinan Wu, Zhen Xie, Chong Zhang, Xin-Hui Xing |
Abstract |
To fully exploit the microbial genome resources, a high-throughput experimental platform is needed to associate genes with phenotypes at the genome level. We present here a novel method that enables investigation of the cellular consequences of repressing individual transcripts based on the CRISPR interference (CRISPRi) pooled screening in bacteria. We identify rules for guide RNA library design to handle the unique structure of prokaryotic genomes by tiling screening and construct an E. coli genome-scale guide RNA library (~60,000 members) accordingly. We show that CRISPRi outperforms transposon sequencing, the benchmark method in the microbial functional genomics field, when similar library sizes are used or gene length is short. This tool is also effective for mapping phenotypes to non-coding RNAs (ncRNAs), as elucidated by a comprehensive tRNA-fitness map constructed here. Our results establish CRISPRi pooled screening as a powerful tool for mapping complex prokaryotic genetic networks in a precise and high-throughput manner. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 14% |
United Kingdom | 1 | 7% |
Australia | 1 | 7% |
Unknown | 10 | 71% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 9 | 64% |
Scientists | 4 | 29% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 317 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 61 | 19% |
Researcher | 43 | 14% |
Student > Bachelor | 35 | 11% |
Student > Master | 32 | 10% |
Student > Doctoral Student | 17 | 5% |
Other | 43 | 14% |
Unknown | 86 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 101 | 32% |
Agricultural and Biological Sciences | 52 | 16% |
Immunology and Microbiology | 13 | 4% |
Chemical Engineering | 11 | 3% |
Engineering | 8 | 3% |
Other | 34 | 11% |
Unknown | 98 | 31% |