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Mol Syst Biol. 2016 Aug 1;12(8):879. doi: 10.15252/msb.20166890.

Parallel reverse genetic screening in mutant human cells using transcriptomics.

Author information

1
Nuffield Department of Clinical Medicine, Ludwig Cancer Research Ltd. University of Oxford, Oxford, UK.
2
CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
3
Horizon Genomics, Vienna, Austria.
4
CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria Max Planck Institute for Informatics, Saarbrücken, Germany.
5
Nuffield Department of Clinical Medicine, Ludwig Cancer Research Ltd. University of Oxford, Oxford, UK CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria Nuffield Department of Clinical Medicine, Target Discovery Institute University of Oxford, Oxford, UK Sebastian.nijman@ludwig.ox.ac.uk.

Abstract

Reverse genetic screens have driven gene annotation and target discovery in model organisms. However, many disease-relevant genotypes and phenotypes cannot be studied in lower organisms. It is therefore essential to overcome technical hurdles associated with large-scale reverse genetics in human cells. Here, we establish a reverse genetic approach based on highly robust and sensitive multiplexed RNA sequencing of mutant human cells. We conduct 10 parallel screens using a collection of engineered haploid isogenic cell lines with knockouts covering tyrosine kinases and identify known and unexpected effects on signaling pathways. Our study provides proof of concept for a scalable approach to link genotype to phenotype in human cells, which has broad applications. In particular, it clears the way for systematic phenotyping of still poorly characterized human genes and for systematic study of uncharacterized genomic features associated with human disease.

KEYWORDS:

kinases; multiplexed RNA sequencing; parallel screening; reverse genetics; systematic phenotyping

PMID:
27482057
PMCID:
PMC5119491
DOI:
10.15252/msb.20166890
[Indexed for MEDLINE]
Free PMC Article

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