GENTANGLE: integrated computational design of gene entanglements

• Published in: Bioinformatics (Oxford, England) Vol. 40; no. 7
• Main Authors: Manuel Martí, Jose, Hsu, Chloe, Rochereau, Charlotte, Xu, Chenling, Blazejewski, Tomasz, Nisonoff, Hunter, Leonard, Sean P, Kang-Yun, Christina S, Chlebek, Jennifer, Ricci, Dante P, Park, Dan, Wang, Harris, Listgarten, Jennifer, Jiao, Yongqin, Allen, Jonathan E
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 21.06.2024
• Subjects: Applications Note; Biological and medical sciences, Energy - Biomass, Computer science
• ISSN: 1367-4811; 1367-4803; 1367-4811
• DOI: 10.1093/bioinformatics/btae380

The design of two overlapping genes in a microbial genome is an emerging technique for adding more reliable control mechanisms in engineered organisms for increased stability. The design of functional overlapping gene pairs is a challenging procedure and computational design tools are used to improve the efficiency to deploy successful designs in genetically engineered systems. GENTANGLE (Gene Tuples ArraNGed in overLapping Elements) is a high-performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome. This new software package can be used to design and test gene entanglements for microbial engineering projects using arbitrary sets of user specified gene pairs. The GENTANGLE source code and its submodules are freely available on GitHub at https://github.com/BiosecSFA/gentangle. The DATANGLE (DATA for genTANGLE) repository contains related data and results, and is freely available on GitHub at https://github.com/BiosecSFA/datangle. The GENTANGLE container is freely available on Singularity Cloud Library at https://cloud.sylabs.io/library/khyox/gentangle/gentangle.sif. The GENTANGLE repository wiki (https://github.com/BiosecSFA/gentangle/wiki), website (https://biosecsfa.github.io/gentangle/) and user manual contain detailed instructions on how to use the different components of software and data, including examples and reproducing the results. The code is licensed under the GNU Affero General Public License version 3 (https://www.gnu.org/licenses/agpl.html). Supplementary data are available at Bioinformatics online.