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PLoS Biol. 2018 Apr 23;16(4):e2005129. doi: 10.1371/journal.pbio.2005129. eCollection 2018 Apr.

In vivo insertion pool sequencing identifies virulence factors in a complex fungal-host interaction.

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Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria.
Center for Integrative Bioinformatics Vienna (CIBIV), Max F Perutz Laboratories (MFPL), University of Vienna, Medical University Vienna, Vienna, Austria.
Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria.


Large-scale insertional mutagenesis screens can be powerful genome-wide tools if they are streamlined with efficient downstream analysis, which is a serious bottleneck in complex biological systems. A major impediment to the success of next-generation sequencing (NGS)-based screens for virulence factors is that the genetic material of pathogens is often underrepresented within the eukaryotic host, making detection extremely challenging. We therefore established insertion Pool-Sequencing (iPool-Seq) on maize infected with the biotrophic fungus U. maydis. iPool-Seq features tagmentation, unique molecular barcodes, and affinity purification of pathogen insertion mutant DNA from in vivo-infected tissues. In a proof of concept using iPool-Seq, we identified 28 virulence factors, including 23 that were previously uncharacterized, from an initial pool of 195 candidate effector mutants. Because of its sensitivity and quantitative nature, iPool-Seq can be applied to any insertional mutagenesis library and is especially suitable for genetically complex setups like pooled infections of eukaryotic hosts.

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