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bioRxiv · 10.1101/2025.05.31.657172

dnaudit + Pydnaweb: A lightweight text-based planning and documentation workflow for genetic cloning with automatic verification

Fernandes, P.·Ghasemi, F.·Silva, P. C.·Paiva, S.·Johansson, B.
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Abstract

Life science research often depends on the construction and analysis of recombinant DNA molecules, where sequence accuracy is critical. However, the field continues to face a reproducibility crisis, partly due to the lack of comprehensive, systematic, and verifiable documentation of genetic constructions. Although most cloning procedures are deterministic and theoretically describable in a complete and unambiguous way, published methods are typically described in a form free narrative, making them laborious to reproduce and assess for completeness. Tools like the Python package Pydna support programmable and reproducible cloning strategies but require coding expertise, which can be a barrier for some users. To address this, we developed Pydnaweb and dnaudit, two open-source and complementary web tools that build on Pydna. Pydnaweb offers simulation of unit operations such as PCR and restriction digestion providing results in text format. These results can be collected and combined to form complex cloning strategies in a bottom-up approach. Dnaudit can verify such collections for internal consistency and that the cloning strategy meet a specific goal such as the expression of a protein sequence. The tools are design for a low barrier of entry, and they can be used separately. This workflow enables fully automated validation, providing a no-code, reproducible solution for documenting and sharing molecular cloning workflows. These tools ease compliance with FAIR principles and align with emerging standards for the transparent and reproducible sharing of scientific methods and data.

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Fernandes, P., Ghasemi, F., Silva, P. C., Paiva, S., Johansson, B.. 2025-06-03. dnaudit + Pydnaweb: A lightweight text-based planning and documentation workflow for genetic cloning with automatic verification. https://doi.org/10.1101/2025.05.31.657172

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