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High-throughput, image-based screening of genetic variant libraries

George Emanuel, Jeffrey R. Moffitt, Xiaowei Zhuang
doi: https://doi.org/10.1101/143966
George Emanuel
1Howard Hughes Medical Institute, Cambridge, MA 02138, USA
2Graduate Program in Biophysics, Cambridge, MA 02138, USA
3Department of Chemistry and Chemical Biology, Cambridge, MA 02138, USA
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Jeffrey R. Moffitt
1Howard Hughes Medical Institute, Cambridge, MA 02138, USA
3Department of Chemistry and Chemical Biology, Cambridge, MA 02138, USA
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Xiaowei Zhuang
1Howard Hughes Medical Institute, Cambridge, MA 02138, USA
3Department of Chemistry and Chemical Biology, Cambridge, MA 02138, USA
4Department of Physics, Harvard University, Cambridge, MA 02138, USA
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Abstract

Image-based, high-throughput, high-content screening of pooled libraries of genetic perturbations will greatly advance our understanding biological systems and facilitate many biotechnology applications. Here we introduce a high-throughput screening method that allows highly diverse genotypes and the corresponding phenotypes to be imaged in numerous individual cells. To facilitate genotyping by imaging, barcoded genetic variants are introduced into the cells, each cell carrying a single genetic variant connected to a unique, nucleic-acid barcode. To identify the genotype-phenotype correspondence, we perform live-cell imaging to determine the phenotype of each cell, and massively multiplexed FISH imaging to measure the barcode expressed in the same cell. We demonstrated the utility of this approach by screening for brighter and more photostable variants of the fluorescent protein YFAST. We imaged 20 million cells expressing ~60,000 YFAST mutants and identified novel YFAST variants that are substantially brighter and/or more photostable than the wild-type protein.

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Posted May 30, 2017.
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High-throughput, image-based screening of genetic variant libraries
George Emanuel, Jeffrey R. Moffitt, Xiaowei Zhuang
bioRxiv 143966; doi: https://doi.org/10.1101/143966
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High-throughput, image-based screening of genetic variant libraries
George Emanuel, Jeffrey R. Moffitt, Xiaowei Zhuang
bioRxiv 143966; doi: https://doi.org/10.1101/143966

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