{"publication":"eLife","day":"26","publication_status":"published","date_published":"2022-01-26T00:00:00Z","volume":11,"_id":"10736","doi":"10.7554/eLife.64543","author":[{"first_name":"Mato","full_name":"Lagator, Mato","last_name":"Lagator","id":"345D25EC-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Srdjan","id":"35F0286E-F248-11E8-B48F-1D18A9856A87","full_name":"Sarikas, Srdjan","last_name":"Sarikas"},{"full_name":"Steinrueck, Magdalena","last_name":"Steinrueck","first_name":"Magdalena"},{"first_name":"David","last_name":"Toledo-Aparicio","full_name":"Toledo-Aparicio, David"},{"first_name":"Jonathan P","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4624-4612","full_name":"Bollback, Jonathan P","last_name":"Bollback"},{"last_name":"Guet","full_name":"Guet, Calin C","orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C"},{"first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","last_name":"Tkačik","full_name":"Tkačik, Gašper"}],"pmid":1,"project":[{"name":"Selective Barriers to Horizontal Gene Transfer","_id":"2578D616-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"648440"}],"external_id":{"pmid":["35080492"],"isi":["000751104400001"]},"quality_controlled":"1","language":[{"iso":"eng"}],"license":"https://creativecommons.org/licenses/by/4.0/","intvolume":" 11","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"oa":1,"file":[{"date_updated":"2022-02-07T07:14:09Z","file_size":5604343,"content_type":"application/pdf","creator":"cchlebak","checksum":"decdcdf600ff51e9a9703b49ca114170","file_id":"10739","date_created":"2022-02-07T07:14:09Z","success":1,"access_level":"open_access","relation":"main_file","file_name":"2022_ELife_Lagator.pdf"}],"file_date_updated":"2022-02-07T07:14:09Z","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","has_accepted_license":"1","date_created":"2022-02-06T23:01:32Z","article_number":"e64543","type":"journal_article","citation":{"ista":"Lagator M, Sarikas S, Steinrueck M, Toledo-Aparicio D, Bollback JP, Guet CC, Tkačik G. 2022. Predicting bacterial promoter function and evolution from random sequences. eLife. 11, e64543.","short":"M. Lagator, S. Sarikas, M. Steinrueck, D. Toledo-Aparicio, J.P. Bollback, C.C. Guet, G. Tkačik, ELife 11 (2022).","ieee":"M. Lagator et al., “Predicting bacterial promoter function and evolution from random sequences,” eLife, vol. 11. eLife Sciences Publications, 2022.","ama":"Lagator M, Sarikas S, Steinrueck M, et al. Predicting bacterial promoter function and evolution from random sequences. eLife. 2022;11. doi:10.7554/eLife.64543","mla":"Lagator, Mato, et al. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” ELife, vol. 11, e64543, eLife Sciences Publications, 2022, doi:10.7554/eLife.64543.","chicago":"Lagator, Mato, Srdjan Sarikas, Magdalena Steinrueck, David Toledo-Aparicio, Jonathan P Bollback, Calin C Guet, and Gašper Tkačik. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” ELife. eLife Sciences Publications, 2022. https://doi.org/10.7554/eLife.64543.","apa":"Lagator, M., Sarikas, S., Steinrueck, M., Toledo-Aparicio, D., Bollback, J. P., Guet, C. C., & Tkačik, G. (2022). Predicting bacterial promoter function and evolution from random sequences. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.64543"},"acknowledgement":"We thank Hande Acar, Nicholas H Barton, Rok Grah, Tiago Paixao, Maros Pleska, Anna Staron, and Murat Tugrul for insightful comments and input on the manuscript. This work was supported by: Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 216779/Z/19/Z) to ML; IPC Grant from IST Austria to ML and SS; European Research Council Funding Programme 7 (2007–2013, grant agreement number 648440) to JPB.","title":"Predicting bacterial promoter function and evolution from random sequences","month":"01","date_updated":"2023-08-02T14:09:02Z","scopus_import":"1","isi":1,"article_processing_charge":"No","publisher":"eLife Sciences Publications","publication_identifier":{"eissn":["2050-084X"]},"year":"2022","ddc":["576"],"abstract":[{"text":"Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ70 binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10–20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ70-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ70-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought.","lang":"eng"}],"department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"NiBa"}],"oa_version":"Published Version","status":"public","article_type":"original","ec_funded":1}