Reproducible Research Platform for Genetic Engineering Player Bundle

RRP Genetic Engineering Reproducible Research Platform (RRP) project for genetic engineering. Overview This RRP project repository demonstrates alternative, reproducible approaches to genetic engineering including molecular cloning and DNA editing. It provides reproducible workflows in contrast to desktop or cloud-based graphical user interfaces such as ApE, SnapGene, Genious or Benchling. The main outcome of this example is: In silico simulation of a CRISPR protocol. A CRISPR plasmid charged with a target sequence for the yeast gene Myo1. A PCR product with homologous recombination primers that amplify the fluorescent reporter (3x)mKate2. PCR Result This repository utilizes QUEEN [1] and Pydna [2] for DNA design and assembly. Detailed explanations of these tools can be found in their respective publications. Features Integration with RRP and openBIS ELN-LIMS: Mounts data (plasmids, oligos) from the research data management system openBIS in RRP for direct use. Reproducible workflow: Automate genetic engineering tasks using Python-based tools. Visualization: Generate detailed diagrams and results for plasmid construction and PCR products. Installation Prerequisites Local Docker installation. Steps Download and extract the .zip file Run the play script for your operating system Linux / macOS: play Windows: play.bat or play.ps1 Usage In RRP open and run the Jupyter notebook MYO1_mKate2_CRISPR.ipynb Workflow Overview Plasmid Design: Use QUEEN to design CRISPR plasmids targeting Myo1. PCR Primer Design: Generate primers for homologous recombination. Visualization: View PCR fragment results using built-in plotting tools. Directory Structure ├── .binder/ # Environment specifications, Python version, packages (QUEEN) etc. ├── .rrp/ # Specification of openBIS server and required data from RDMS openBIS ELN-LIMS (e.g. Plasmids) ├── docs/ # Documentation files │ └── resources │ └── images │ └── linearized_mKate2_fragment_w_Myo1_HR.png # Resources for the README ├── LICENSE # License ├── MYO1_mKate2_CRISPR.ipynb # Notebook demonstrating reproducible genetic engineering workflow. └── README.md # This file Authors and acknowledgment Andreas P. Cuny, ETH Zurich initial implementation Additionally, we acknowledge the use of QUEEN and Pydna tools in our workflows, as detailed in their respective publications. License This project is licensed under the Apache 2.0 License. See LICENSE file for details. Copyright © 2020-2025 ETH Zurich, Andreas P. Cuny, D-BSSE, CSB Group References 1: Mori, H., Yachie, N. A framework to efficiently describe and share reproducible DNA materials and construction protocols. Nat Commun 13, 2894 (2022). https://doi.org/10.1038/s41467-022-30588-x 2: Pereira, F., Azevedo, F., Carvalho, Â., Ribeiro, G. F., Budde, M. W., & Johansson, B. (2015). Pydna: a simulation and documentation tool for DNA assembly strategies using python. BMC Bioinformatics, 16(142), 142. https://doi.org/10.1186/s12859-015-0544-x