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PLoS ONEMolecular BiologyPeer-reviewed journal article

High-throughput yeast two-hybrid library screening using next generation sequencing

Marie‐Laure ErffelinckiD, Bianca RibeiroiD, Marı́a PerassoloiD, Laurens PauwelsiD, Jacob PollieriD, Véronique StormeiD, Alain GoossensiD

PDFDOIPreprint

Abstract

Yeast two-hybrid (Y2H) is a well-established genetics-based system that uses yeast to selectively display binary protein-protein interactions (PPIs). To meet the current need to unravel complex PPI networks, several adaptations have been made to establish medium- to high-throughput Y2H screening platforms, with several having successfully incorporated the use of the next-generation sequencing (NGS) technology to increase the scale and sensitivity of the method. However, these have been to date mainly restricted to the use of fully annotated custom-made open reading frame (ORF) libraries and subject to complex downstream data processing. Here, a streamlined high-throughput Y2H library screening strategy, based on integration of Y2H with NGS, called Y2H-seq, was developed, which allows efficient and reliable screening of Y2H cDNA libraries. To generate proof of concept, the method was applied to screen for interaction partners of two key components of the jasmonate signaling machinery in the model plant Arabidopsis thaliana, resulting in the identification of several previously reported as well as hitherto unknown interactors. Our Y2H-seq method offers a user-friendly, specific and sensitive screening method that allows high-throughput identification of PPIs without prior knowledge of the organisms ORFs, thereby extending the method to organisms of which the genome has not entirely been annotated yet. The quantitative NGS readout and the incorporation of background controls allow to increase genome coverage and ultimately dispose of recurrent false positives, thereby overcoming some of the bottlenecks of current Y2H technologies, which will further strengthen the value of the Y2H technology as a discovery platform.

Citations
51
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top 13%

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