Systematic prediction of genes functionally associated with bacterial retrons and classification of the encoded tripartite systems Rodríguez Mestre, Mario González-Delgado, Alejandro Gutiérrez Rus, Luis Ignacio Martínez-Abarca Pastor, Francisco Toro, Nicolás We thank all members of the NTG laboratory for helpful discussions during the development of this project. We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI). Supplementary Data are available at NAR Online: https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkaa1149#supplementary-data Bacterial retrons consist of a reverse transcriptase (RT) and a contiguous non-coding RNA (ncRNA) gene. One third of annotated retrons carry additional open reading frames (ORFs), the contribution and significance of which in retron biology remains to be determined. In this study we developed a computational pipeline for the systematic prediction of genes specifically associated with retron RTs based on a previously reported large dataset representative of the diversity of prokaryotic RTs. We found that retrons generally comprise a tripartite system composed of the ncRNA, the RT and an additional protein or RT-fused domain with diverse enzymatic functions. These retron systems are highly modular, and their components have coevolved to different extents. Based on the additional module, we classified retrons into 13 types, some of which include additional variants. Our findings provide a basis for future studies on the biological function of retrons and for expanding their biotechnological applications. 2021-02-24T11:56:55Z 2021-02-24T11:56:55Z 2020-12-04 info:eu-repo/semantics/article Mario Rodríguez Mestre, Alejandro González-Delgado, Luis I Gutiérrez-Rus, Francisco Martínez-Abarca, Nicolás Toro, Systematic prediction of genes functionally associated with bacterial retrons and classification of the encoded tripartite systems, Nucleic Acids Research, Volume 48, Issue 22, 16 December 2020, Pages 12632–12647, [https://doi.org/10.1093/nar/gkaa1149] http://hdl.handle.net/10481/66706 10.1093/nar/gkaa1149 eng http://creativecommons.org/licenses/by-nc/3.0/es/ info:eu-repo/semantics/openAccess Atribución-NoComercial 3.0 España Oxford University Press