Spatiotemporally controlled genetic perturbation for efficient large-scale studies of cell non-autonomous effects
Abstract
Studies in genetic model organisms have revealed much about the development and pathology of complex tissues. Most have focused on cell-intrinsic gene functions and mechanisms. Much less is known about how transformed, or otherwise functionally disrupted, cells interact with healthy ones towards a favorable or pathological outcome. This is largely due to technical limitations. We developed new genetic tools in Drosophila melanogaster that permit efficient multiplexed gain- and loss-of-function genetic perturbations with separable spatial and temporal control. Importantly, our novel tool-set is independent of the commonly used GAL4/UAS system, freeing the latter for additional, non-autonomous, genetic manipulations; and is built into a single strain, allowing one-generation interrogation of non-autonomous effects. Altogether, our design opens up efficient genome-wide screens on any deleterious phenotype, once plasmid or genome engineering is used to place the desired miRNA(s) or ORF(s) into our genotype. Specifically, we developed tools to study extrinsic effects on neural tumor growth but the strategy presented has endless applications within and beyond neurobiology, and in other model organisms.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files. A source data file has been provided for Figure 2-supplement figure 1 and for Figure 6; FOFO2.0 plasmid sequence has been uploaded; plasmids and transgenic flies will be deposited in stock centres before publication.
Article and author information
Author details
Funding
Cancer Research UK (Career Development Fellowship)
- Andrea Chai
- Ana M Mateus
- Rita Sousa-Nunes
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Chai et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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