{"title":"Predicting bacterial promoter function and evolution from random sequences","isi":1,"scopus_import":"1","oa_version":"Published Version","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.","pmid":1,"has_accepted_license":"1","citation":{"short":"M. Lagator, S. Sarikas, M. Steinrück, D. Toledo-Aparicio, J.P. Bollback, C.C. Guet, G. Tkačik, ELife 11 (2022).","ama":"Lagator M, Sarikas S, Steinrück M, et al. Predicting bacterial promoter function and evolution from random sequences. <i>eLife</i>. 2022;11. doi:<a href=\"https://doi.org/10.7554/eLife.64543\">10.7554/eLife.64543</a>","ieee":"M. Lagator <i>et al.</i>, “Predicting bacterial promoter function and evolution from random sequences,” <i>eLife</i>, vol. 11. eLife Sciences Publications, 2022.","ista":"Lagator M, Sarikas S, Steinrück M, Toledo-Aparicio D, Bollback JP, Guet CC, Tkačik G. 2022. Predicting bacterial promoter function and evolution from random sequences. eLife. 11, e64543.","apa":"Lagator, M., Sarikas, S., Steinrück, M., Toledo-Aparicio, D., Bollback, J. P., Guet, C. C., &#38; Tkačik, G. (2022). Predicting bacterial promoter function and evolution from random sequences. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/eLife.64543\">https://doi.org/10.7554/eLife.64543</a>","mla":"Lagator, Mato, et al. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” <i>ELife</i>, vol. 11, e64543, eLife Sciences Publications, 2022, doi:<a href=\"https://doi.org/10.7554/eLife.64543\">10.7554/eLife.64543</a>.","chicago":"Lagator, Mato, Srdjan Sarikas, Magdalena Steinrück, David Toledo-Aparicio, Jonathan P Bollback, Calin C Guet, and Gašper Tkačik. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” <i>ELife</i>. eLife Sciences Publications, 2022. <a href=\"https://doi.org/10.7554/eLife.64543\">https://doi.org/10.7554/eLife.64543</a>."},"status":"public","day":"26","type":"journal_article","publication_identifier":{"eissn":["2050-084X"]},"article_number":"e64543","publisher":"eLife Sciences Publications","month":"01","quality_controlled":"1","corr_author":"1","_id":"10736","article_processing_charge":"No","article_type":"original","license":"https://creativecommons.org/licenses/by/4.0/","author":[{"full_name":"Lagator, Mato","last_name":"Lagator","id":"345D25EC-F248-11E8-B48F-1D18A9856A87","first_name":"Mato"},{"first_name":"Srdjan","id":"35F0286E-F248-11E8-B48F-1D18A9856A87","last_name":"Sarikas","full_name":"Sarikas, Srdjan"},{"id":"2C023F40-F248-11E8-B48F-1D18A9856A87","full_name":"Steinrück, Magdalena","orcid":"0000-0003-1229-9719","last_name":"Steinrück","first_name":"Magdalena"},{"last_name":"Toledo-Aparicio","full_name":"Toledo-Aparicio, David","first_name":"David"},{"first_name":"Jonathan P","last_name":"Bollback","full_name":"Bollback, Jonathan P","orcid":"0000-0002-4624-4612","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","full_name":"Guet, Calin C","orcid":"0000-0001-6220-2052","first_name":"Calin C"},{"full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper"}],"oa":1,"language":[{"iso":"eng"}],"department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"NiBa"}],"external_id":{"isi":["000751104400001"],"pmid":["35080492"]},"publication_status":"published","doi":"10.7554/eLife.64543","ec_funded":1,"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"}],"file_date_updated":"2022-02-07T07:14:09Z","publication":"eLife","file":[{"checksum":"decdcdf600ff51e9a9703b49ca114170","file_id":"10739","relation":"main_file","date_created":"2022-02-07T07:14:09Z","success":1,"content_type":"application/pdf","creator":"cchlebak","access_level":"open_access","date_updated":"2022-02-07T07:14:09Z","file_name":"2022_ELife_Lagator.pdf","file_size":5604343}],"intvolume":"        11","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2022-02-06T23:01:32Z","year":"2022","date_published":"2022-01-26T00:00:00Z","ddc":["576"],"project":[{"name":"Selective Barriers to Horizontal Gene Transfer","call_identifier":"H2020","_id":"2578D616-B435-11E9-9278-68D0E5697425","grant_number":"648440"}],"date_updated":"2025-03-31T16:00:23Z","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"},"volume":11}