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A user-friendly platform for yeast two-hybrid library screening using next generation sequencing.

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 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 identification of PPIs without prior knowledge of the organism's ORFs, thereby extending the method to organisms of which the genome has not entirely been annotated yet. The quantitative NGS readout allows to increase genome coverage, thereby overcoming some of the bottlenecks of current Y2H technologies, which will further strengthen the value of the Y2H technology as a discovery platform.

SUBMITTER: Erffelinck ML

PROVIDER: S-EPMC6303091 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Next generation sequencing (NGS) technologies are indispensable for molecular biology research, but data analysis represents the bottleneck in their application. Users need to be familiar with computer terminal commands, the Linux environment, and various software tools and scripts. Analysis workflows have to be optimized and experimentally validated to extract biologically meaningful data. Moreover, as larger datasets are being generated, their analysis requires use of high-performance servers.To address these needs, we developed CANEapp (application for Comprehensive automated Analysis of Next-generation sequencing Experiments), a unique suite that combines a Graphical User Interface (GUI) and an automated server-side analysis pipeline that is platform-independent, making it suitable for any server architecture. The GUI runs on a PC or Mac and seamlessly connects to the server to provide full GUI control of RNA-sequencing (RNA-seq) project analysis. The server-side analysis pipeline contains a framework that is implemented on a Linux server through completely automated installation of software components and reference files. Analysis with CANEapp is also fully automated and performs differential gene expression analysis and novel noncoding RNA discovery through alternative workflows (Cuffdiff and R packages edgeR and DESeq2). We compared CANEapp to other similar tools, and it significantly improves on previous developments. We experimentally validated CANEapp's performance by applying it to data derived from different experimental paradigms and confirming the results with quantitative real-time PCR (qRT-PCR). CANEapp adapts to any server architecture by effectively using available resources and thus handles large amounts of data efficiently. CANEapp performance has been experimentally validated on various biological datasets. CANEapp is available free of charge at http://psychiatry.med.miami.edu/research/laboratory-of-translational-rna-genomics/CANE-app .We believe that CANEapp will serve both biologists with no computational experience and bioinformaticians as a simple, timesaving but accurate and powerful tool to analyze large RNA-seq datasets and will provide foundations for future development of integrated and automated high-throughput genomics data analysis tools. Due to its inherently standardized pipeline and combination of automated analysis and platform-independence, CANEapp is an ideal for large-scale collaborative RNA-seq projects between different institutions and research groups.

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A user-friendly platform for yeast two-hybrid library screening using next generation sequencing.

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