A Molecular Chipper technology for CRISPR sgRNA library generation and functional mapping of noncoding regions
Jijun Cheng (),
Christine A. Roden,
Wen Pan,
Shu Zhu,
Anna Baccei,
Xinghua Pan,
Tingting Jiang,
Yuval Kluger,
Sherman M. Weissman,
Shangqin Guo,
Richard A. Flavell,
Ye Ding and
Jun Lu ()
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Jijun Cheng: Yale University School of Medicine
Christine A. Roden: Yale University School of Medicine
Wen Pan: Yale University School of Medicine
Shu Zhu: Yale University School of Medicine
Anna Baccei: Yale Stem Cell Center, Yale Cancer Center
Xinghua Pan: Yale University School of Medicine
Tingting Jiang: Yale University School of Medicine
Yuval Kluger: Yale University School of Medicine
Sherman M. Weissman: Yale University School of Medicine
Shangqin Guo: Yale Stem Cell Center, Yale Cancer Center
Richard A. Flavell: Yale University School of Medicine
Ye Ding: Wadsworth Center
Jun Lu: Yale University School of Medicine
Nature Communications, 2016, vol. 7, issue 1, 1-10
Abstract:
Abstract Clustered regularly-interspaced palindromic repeats (CRISPR)-based genetic screens using single-guide-RNA (sgRNA) libraries have proven powerful to identify genetic regulators. Applying CRISPR screens to interrogate functional elements in noncoding regions requires generating sgRNA libraries that are densely covering, and ideally inexpensive, easy to implement and flexible for customization. Here we present a Molecular Chipper technology for generating dense sgRNA libraries for genomic regions of interest, and a proof-of-principle screen that identifies novel cis-regulatory domains for miR-142 biogenesis. The Molecular Chipper approach utilizes a combination of random fragmentation and a type III restriction enzyme to derive a densely covering sgRNA library from input DNA. Applying this approach to 17 microRNAs and their flanking regions and with a reporter for miR-142 activity, we identify both the pre-miR-142 region and two previously unrecognized cis-domains important for miR-142 biogenesis, with the latter regulating miR-142 processing. This strategy will be useful for identifying functional noncoding elements in mammalian genomes.
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms11178
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DOI: 10.1038/ncomms11178
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