[{"date_published":"2018-06-06T00:00:00Z","article_type":"original","publication":"eLife","citation":{"ama":"Alanko JH, Sixt MK. The cell sets the tone. eLife. 2018;7. doi:10.7554/eLife.37888","apa":"Alanko, J. H., & Sixt, M. K. (2018). The cell sets the tone. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.37888","ieee":"J. H. Alanko and M. K. Sixt, “The cell sets the tone,” eLife, vol. 7. eLife Sciences Publications, 2018.","ista":"Alanko JH, Sixt MK. 2018. The cell sets the tone. eLife. 7, e37888.","short":"J.H. Alanko, M.K. Sixt, ELife 7 (2018).","mla":"Alanko, Jonna H., and Michael K. Sixt. “The Cell Sets the Tone.” ELife, vol. 7, e37888, eLife Sciences Publications, 2018, doi:10.7554/eLife.37888.","chicago":"Alanko, Jonna H, and Michael K Sixt. “The Cell Sets the Tone.” ELife. eLife Sciences Publications, 2018. https://doi.org/10.7554/eLife.37888."},"day":"06","has_accepted_license":"1","article_processing_charge":"No","scopus_import":"1","file":[{"file_id":"5973","relation":"main_file","date_updated":"2020-07-14T12:47:13Z","date_created":"2019-02-13T10:52:11Z","checksum":"f1c7ec2a809408d763c4b529a98f9a3b","file_name":"2018_eLife_Alanko.pdf","access_level":"open_access","creator":"dernst","file_size":358141,"content_type":"application/pdf"}],"oa_version":"Published Version","status":"public","ddc":["570"],"title":"The cell sets the tone","intvolume":" 7","_id":"5861","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"text":"In zebrafish larvae, it is the cell type that determines how the cell responds to a chemokine signal.","lang":"eng"}],"type":"journal_article","language":[{"iso":"eng"}],"doi":"10.7554/eLife.37888","quality_controlled":"1","isi":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"external_id":{"isi":["000434375000001"]},"month":"06","publication_identifier":{"issn":["2050084X"]},"date_created":"2019-01-20T22:59:19Z","date_updated":"2023-09-19T10:01:39Z","volume":7,"author":[{"full_name":"Alanko, Jonna H","id":"2CC12E8C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7698-3061","first_name":"Jonna H","last_name":"Alanko"},{"full_name":"Sixt, Michael K","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6620-9179","first_name":"Michael K","last_name":"Sixt"}],"publication_status":"published","publisher":"eLife Sciences Publications","department":[{"_id":"MiSi"}],"year":"2018","license":"https://creativecommons.org/licenses/by/4.0/","file_date_updated":"2020-07-14T12:47:13Z","article_number":"e37888"},{"file_date_updated":"2020-07-14T12:47:10Z","publist_id":"7244","ec_funded":1,"article_number":"e28921","date_created":"2018-12-11T11:47:14Z","date_updated":"2021-01-12T08:03:15Z","volume":6,"author":[{"full_name":"Lagator, Mato","id":"345D25EC-F248-11E8-B48F-1D18A9856A87","last_name":"Lagator","first_name":"Mato"},{"full_name":"Sarikas, Srdjan","id":"35F0286E-F248-11E8-B48F-1D18A9856A87","last_name":"Sarikas","first_name":"Srdjan"},{"full_name":"Acar, Hande","orcid":"0000-0003-1986-9753","id":"2DDF136A-F248-11E8-B48F-1D18A9856A87","last_name":"Acar","first_name":"Hande"},{"full_name":"Bollback, Jonathan P","last_name":"Bollback","first_name":"Jonathan P","orcid":"0000-0002-4624-4612","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","first_name":"Calin C","last_name":"Guet"}],"publication_status":"published","department":[{"_id":"CaGu"},{"_id":"JoBo"},{"_id":"NiBa"}],"publisher":"eLife Sciences Publications","year":"2017","month":"11","publication_identifier":{"issn":["2050084X"]},"language":[{"iso":"eng"}],"doi":"10.7554/eLife.28921","quality_controlled":"1","project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"},{"name":"Selective Barriers to Horizontal Gene Transfer","call_identifier":"H2020","_id":"2578D616-B435-11E9-9278-68D0E5697425","grant_number":"648440"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"abstract":[{"text":"Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution. ","lang":"eng"}],"type":"journal_article","oa_version":"Published Version","file":[{"relation":"main_file","file_id":"5096","date_created":"2018-12-12T10:14:42Z","date_updated":"2020-07-14T12:47:10Z","checksum":"273ab17f33305e4eaafd911ff88e7c5b","file_name":"IST-2017-918-v1+1_elife-28921-figures-v3.pdf","access_level":"open_access","file_size":8453470,"content_type":"application/pdf","creator":"system"},{"date_updated":"2020-07-14T12:47:10Z","date_created":"2018-12-12T10:14:43Z","checksum":"b433f90576c7be597cd43367946f8e7f","relation":"main_file","file_id":"5097","file_size":1953221,"content_type":"application/pdf","creator":"system","file_name":"IST-2017-918-v1+2_elife-28921-v3.pdf","access_level":"open_access"}],"pubrep_id":"918","title":"Regulatory network structure determines patterns of intermolecular epistasis","status":"public","ddc":["576"],"intvolume":" 6","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"570","day":"13","has_accepted_license":"1","scopus_import":1,"date_published":"2017-11-13T00:00:00Z","publication":"eLife","citation":{"short":"M. Lagator, S. Sarikas, H. Acar, J.P. Bollback, C.C. Guet, ELife 6 (2017).","mla":"Lagator, Mato, et al. “Regulatory Network Structure Determines Patterns of Intermolecular Epistasis.” ELife, vol. 6, e28921, eLife Sciences Publications, 2017, doi:10.7554/eLife.28921.","chicago":"Lagator, Mato, Srdjan Sarikas, Hande Acar, Jonathan P Bollback, and Calin C Guet. “Regulatory Network Structure Determines Patterns of Intermolecular Epistasis.” ELife. eLife Sciences Publications, 2017. https://doi.org/10.7554/eLife.28921.","ama":"Lagator M, Sarikas S, Acar H, Bollback JP, Guet CC. Regulatory network structure determines patterns of intermolecular epistasis. eLife. 2017;6. doi:10.7554/eLife.28921","apa":"Lagator, M., Sarikas, S., Acar, H., Bollback, J. P., & Guet, C. C. (2017). Regulatory network structure determines patterns of intermolecular epistasis. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.28921","ieee":"M. Lagator, S. Sarikas, H. Acar, J. P. Bollback, and C. C. Guet, “Regulatory network structure determines patterns of intermolecular epistasis,” eLife, vol. 6. eLife Sciences Publications, 2017.","ista":"Lagator M, Sarikas S, Acar H, Bollback JP, Guet CC. 2017. Regulatory network structure determines patterns of intermolecular epistasis. eLife. 6, e28921."}},{"citation":{"chicago":"Spira, Felix, Sara Cuylen Haering, Shalin Mehta, Matthias Samwer, Anne Reversat, Amitabh Verma, Rudolf Oldenbourg, Michael K Sixt, and Daniel Gerlich. “Cytokinesis in Vertebrate Cells Initiates by Contraction of an Equatorial Actomyosin Network Composed of Randomly Oriented Filaments.” ELife. eLife Sciences Publications, 2017. https://doi.org/10.7554/eLife.30867.","mla":"Spira, Felix, et al. “Cytokinesis in Vertebrate Cells Initiates by Contraction of an Equatorial Actomyosin Network Composed of Randomly Oriented Filaments.” ELife, vol. 6, e30867, eLife Sciences Publications, 2017, doi:10.7554/eLife.30867.","short":"F. Spira, S. Cuylen Haering, S. Mehta, M. Samwer, A. Reversat, A. Verma, R. Oldenbourg, M.K. Sixt, D. Gerlich, ELife 6 (2017).","ista":"Spira F, Cuylen Haering S, Mehta S, Samwer M, Reversat A, Verma A, Oldenbourg R, Sixt MK, Gerlich D. 2017. Cytokinesis in vertebrate cells initiates by contraction of an equatorial actomyosin network composed of randomly oriented filaments. eLife. 6, e30867.","ieee":"F. Spira et al., “Cytokinesis in vertebrate cells initiates by contraction of an equatorial actomyosin network composed of randomly oriented filaments,” eLife, vol. 6. eLife Sciences Publications, 2017.","apa":"Spira, F., Cuylen Haering, S., Mehta, S., Samwer, M., Reversat, A., Verma, A., … Gerlich, D. (2017). Cytokinesis in vertebrate cells initiates by contraction of an equatorial actomyosin network composed of randomly oriented filaments. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.30867","ama":"Spira F, Cuylen Haering S, Mehta S, et al. Cytokinesis in vertebrate cells initiates by contraction of an equatorial actomyosin network composed of randomly oriented filaments. eLife. 2017;6. doi:10.7554/eLife.30867"},"publication":"eLife","date_published":"2017-11-06T00:00:00Z","scopus_import":1,"has_accepted_license":"1","day":"06","intvolume":" 6","status":"public","title":"Cytokinesis in vertebrate cells initiates by contraction of an equatorial actomyosin network composed of randomly oriented filaments","ddc":["570"],"_id":"569","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"access_level":"open_access","file_name":"IST-2017-919-v1+1_elife-30867-figures-v1.pdf","content_type":"application/pdf","file_size":9666973,"creator":"system","relation":"main_file","file_id":"4829","checksum":"ba09c1451153d39e4f4b7cee013e314c","date_created":"2018-12-12T10:10:40Z","date_updated":"2020-07-14T12:47:10Z"},{"file_name":"IST-2017-919-v1+2_elife-30867-v1.pdf","access_level":"open_access","creator":"system","file_size":5951246,"content_type":"application/pdf","file_id":"4830","relation":"main_file","date_updated":"2020-07-14T12:47:10Z","date_created":"2018-12-12T10:10:41Z","checksum":"01eb51f1d6ad679947415a51c988e137"}],"oa_version":"Published Version","pubrep_id":"919","type":"journal_article","abstract":[{"lang":"eng","text":"The actomyosin ring generates force to ingress the cytokinetic cleavage furrow in animal cells, yet its filament organization and the mechanism of contractility is not well understood. We quantified actin filament order in human cells using fluorescence polarization microscopy and found that cleavage furrow ingression initiates by contraction of an equatorial actin network with randomly oriented filaments. The network subsequently gradually reoriented actin filaments along the cell equator. This strictly depended on myosin II activity, suggesting local network reorganization by mechanical forces. Cortical laser microsurgery revealed that during cytokinesis progression, mechanical tension increased substantially along the direction of the cell equator, while the network contracted laterally along the pole-to-pole axis without a detectable increase in tension. Our data suggest that an asymmetric increase in cortical tension promotes filament reorientation along the cytokinetic cleavage furrow, which might have implications for diverse other biological processes involving actomyosin rings."}],"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"language":[{"iso":"eng"}],"doi":"10.7554/eLife.30867","publication_identifier":{"issn":["2050084X"]},"month":"11","department":[{"_id":"MiSi"}],"publisher":"eLife Sciences Publications","publication_status":"published","year":"2017","volume":6,"date_created":"2018-12-11T11:47:14Z","date_updated":"2023-02-23T12:30:29Z","author":[{"full_name":"Spira, Felix","first_name":"Felix","last_name":"Spira"},{"full_name":"Cuylen Haering, Sara","last_name":"Cuylen Haering","first_name":"Sara"},{"last_name":"Mehta","first_name":"Shalin","full_name":"Mehta, Shalin"},{"first_name":"Matthias","last_name":"Samwer","full_name":"Samwer, Matthias"},{"first_name":"Anne","last_name":"Reversat","id":"35B76592-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-0666-8928","full_name":"Reversat, Anne"},{"full_name":"Verma, Amitabh","last_name":"Verma","first_name":"Amitabh"},{"full_name":"Oldenbourg, Rudolf","first_name":"Rudolf","last_name":"Oldenbourg"},{"full_name":"Sixt, Michael K","first_name":"Michael K","last_name":"Sixt","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6620-9179"},{"full_name":"Gerlich, Daniel","first_name":"Daniel","last_name":"Gerlich"}],"article_number":"e30867","publist_id":"7245","file_date_updated":"2020-07-14T12:47:10Z"},{"scopus_import":1,"has_accepted_license":"1","day":"06","citation":{"ista":"Renault T, Abraham A, Bergmiller T, Paradis G, Rainville S, Charpentier E, Guet CC, Tu Y, Namba K, Keener J, Minamino T, Erhardt M. 2017. Bacterial flagella grow through an injection diffusion mechanism. eLife. 6, e23136.","ieee":"T. Renault et al., “Bacterial flagella grow through an injection diffusion mechanism,” eLife, vol. 6. eLife Sciences Publications, 2017.","apa":"Renault, T., Abraham, A., Bergmiller, T., Paradis, G., Rainville, S., Charpentier, E., … Erhardt, M. (2017). Bacterial flagella grow through an injection diffusion mechanism. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.23136","ama":"Renault T, Abraham A, Bergmiller T, et al. Bacterial flagella grow through an injection diffusion mechanism. eLife. 2017;6. doi:10.7554/eLife.23136","chicago":"Renault, Thibaud, Anthony Abraham, Tobias Bergmiller, Guillaume Paradis, Simon Rainville, Emmanuelle Charpentier, Calin C Guet, et al. “Bacterial Flagella Grow through an Injection Diffusion Mechanism.” ELife. eLife Sciences Publications, 2017. https://doi.org/10.7554/eLife.23136.","mla":"Renault, Thibaud, et al. “Bacterial Flagella Grow through an Injection Diffusion Mechanism.” ELife, vol. 6, e23136, eLife Sciences Publications, 2017, doi:10.7554/eLife.23136.","short":"T. Renault, A. Abraham, T. Bergmiller, G. Paradis, S. Rainville, E. Charpentier, C.C. Guet, Y. Tu, K. Namba, J. Keener, T. Minamino, M. Erhardt, ELife 6 (2017)."},"publication":"eLife","date_published":"2017-03-06T00:00:00Z","type":"journal_article","abstract":[{"lang":"eng","text":"The bacterial flagellum is a self-assembling nanomachine. The external flagellar filament, several times longer than a bacterial cell body, is made of a few tens of thousands subunits of a single protein: flagellin. A fundamental problem concerns the molecular mechanism of how the flagellum grows outside the cell, where no discernible energy source is available. Here, we monitored the dynamic assembly of individual flagella using in situ labelling and real-time immunostaining of elongating flagellar filaments. We report that the rate of flagellum growth, initially ~1,700 amino acids per second, decreases with length and that the previously proposed chain mechanism does not contribute to the filament elongation dynamics. Inhibition of the proton motive force-dependent export apparatus revealed a major contribution of substrate injection in driving filament elongation. The combination of experimental and mathematical evidence demonstrates that a simple, injection-diffusion mechanism controls bacterial flagella growth outside the cell."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"655","intvolume":" 6","ddc":["579"],"title":"Bacterial flagella grow through an injection diffusion mechanism","status":"public","pubrep_id":"904","file":[{"relation":"main_file","file_id":"4716","date_updated":"2020-07-14T12:47:33Z","date_created":"2018-12-12T10:08:53Z","checksum":"39e1c3e82ddac83a30422fa72fa1a383","file_name":"IST-2017-904-v1+1_elife-23136-v2.pdf","access_level":"open_access","content_type":"application/pdf","file_size":5520359,"creator":"system"},{"date_created":"2018-12-12T10:08:54Z","date_updated":"2020-07-14T12:47:33Z","checksum":"a6d542253028f52e00aa29739ddffe8f","file_id":"4717","relation":"main_file","creator":"system","file_size":11242920,"content_type":"application/pdf","file_name":"IST-2017-904-v1+2_elife-23136-figures-v2.pdf","access_level":"open_access"}],"oa_version":"Published Version","publication_identifier":{"issn":["2050084X"]},"month":"03","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"quality_controlled":"1","doi":"10.7554/eLife.23136","language":[{"iso":"eng"}],"article_number":"e23136","publist_id":"7082","file_date_updated":"2020-07-14T12:47:33Z","year":"2017","department":[{"_id":"CaGu"}],"publisher":"eLife Sciences Publications","publication_status":"published","author":[{"first_name":"Thibaud","last_name":"Renault","full_name":"Renault, Thibaud"},{"full_name":"Abraham, Anthony","last_name":"Abraham","first_name":"Anthony"},{"full_name":"Bergmiller, Tobias","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5396-4346","first_name":"Tobias","last_name":"Bergmiller"},{"last_name":"Paradis","first_name":"Guillaume","full_name":"Paradis, Guillaume"},{"full_name":"Rainville, Simon","first_name":"Simon","last_name":"Rainville"},{"first_name":"Emmanuelle","last_name":"Charpentier","full_name":"Charpentier, Emmanuelle"},{"orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","first_name":"Calin C","full_name":"Guet, Calin C"},{"full_name":"Tu, Yuhai","first_name":"Yuhai","last_name":"Tu"},{"last_name":"Namba","first_name":"Keiichi","full_name":"Namba, Keiichi"},{"full_name":"Keener, James","last_name":"Keener","first_name":"James"},{"full_name":"Minamino, Tohru","last_name":"Minamino","first_name":"Tohru"},{"full_name":"Erhardt, Marc","last_name":"Erhardt","first_name":"Marc"}],"volume":6,"date_created":"2018-12-11T11:47:44Z","date_updated":"2021-01-12T08:07:55Z"},{"file_date_updated":"2020-07-14T12:47:50Z","publist_id":"6971","article_number":"e25125","date_created":"2018-12-11T11:48:05Z","date_updated":"2021-01-12T08:11:57Z","volume":6,"author":[{"full_name":"Andergassen, Daniel","first_name":"Daniel","last_name":"Andergassen"},{"id":"4C66542E-F248-11E8-B48F-1D18A9856A87","first_name":"Christoph","last_name":"Dotter","full_name":"Dotter, Christoph"},{"full_name":"Wenzel, Dyniel","first_name":"Dyniel","last_name":"Wenzel"},{"first_name":"Verena","last_name":"Sigl","full_name":"Sigl, Verena"},{"full_name":"Bammer, Philipp","first_name":"Philipp","last_name":"Bammer"},{"first_name":"Markus","last_name":"Muckenhuber","full_name":"Muckenhuber, Markus"},{"last_name":"Mayer","first_name":"Daniela","full_name":"Mayer, Daniela"},{"full_name":"Kulinski, Tomasz","first_name":"Tomasz","last_name":"Kulinski"},{"full_name":"Theussl, Hans","first_name":"Hans","last_name":"Theussl"},{"last_name":"Penninger","first_name":"Josef","full_name":"Penninger, Josef"},{"first_name":"Christoph","last_name":"Bock","full_name":"Bock, Christoph"},{"first_name":"Denise","last_name":"Barlow","full_name":"Barlow, Denise"},{"full_name":"Pauler, Florian","id":"48EA0138-F248-11E8-B48F-1D18A9856A87","first_name":"Florian","last_name":"Pauler"},{"full_name":"Hudson, Quanah","first_name":"Quanah","last_name":"Hudson"}],"publication_status":"published","department":[{"_id":"GaNo"},{"_id":"SiHi"}],"publisher":"eLife Sciences Publications","year":"2017","month":"08","publication_identifier":{"issn":["2050084X"]},"language":[{"iso":"eng"}],"doi":"10.7554/eLife.25125","quality_controlled":"1","project":[{"grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"abstract":[{"text":"To determine the dynamics of allelic-specific expression during mouse development, we analyzed RNA-seq data from 23 F1 tissues from different developmental stages, including 19 female tissues allowing X chromosome inactivation (XCI) escapers to also be detected. We demonstrate that allelic expression arising from genetic or epigenetic differences is highly tissue-specific. We find that tissue-specific strain-biased gene expression may be regulated by tissue-specific enhancers or by post-transcriptional differences in stability between the alleles. We also find that escape from X-inactivation is tissue-specific, with leg muscle showing an unexpectedly high rate of XCI escapers. By surveying a range of tissues during development, and performing extensive validation, we are able to provide a high confidence list of mouse imprinted genes including 18 novel genes. This shows that cluster size varies dynamically during development and can be substantially larger than previously thought, with the Igf2r cluster extending over 10 Mb in placenta.","lang":"eng"}],"type":"journal_article","file":[{"date_updated":"2020-07-14T12:47:50Z","date_created":"2018-12-12T10:13:36Z","checksum":"1ace3462e64a971b9ead896091829549","relation":"main_file","file_id":"5020","file_size":6399510,"content_type":"application/pdf","creator":"system","file_name":"IST-2017-885-v1+1_elife-25125-figures-v2.pdf","access_level":"open_access"},{"access_level":"open_access","file_name":"IST-2017-885-v1+2_elife-25125-v2.pdf","creator":"system","file_size":4264398,"content_type":"application/pdf","file_id":"5021","relation":"main_file","checksum":"6241dc31eeb87b03facadec3a53a6827","date_created":"2018-12-12T10:13:36Z","date_updated":"2020-07-14T12:47:50Z"}],"oa_version":"Published Version","pubrep_id":"885","title":"Mapping the mouse Allelome reveals tissue specific regulation of allelic expression","ddc":["576"],"status":"public","intvolume":" 6","_id":"713","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"14","has_accepted_license":"1","scopus_import":1,"date_published":"2017-08-14T00:00:00Z","publication":"eLife","citation":{"ista":"Andergassen D, Dotter C, Wenzel D, Sigl V, Bammer P, Muckenhuber M, Mayer D, Kulinski T, Theussl H, Penninger J, Bock C, Barlow D, Pauler F, Hudson Q. 2017. Mapping the mouse Allelome reveals tissue specific regulation of allelic expression. eLife. 6, e25125.","ieee":"D. Andergassen et al., “Mapping the mouse Allelome reveals tissue specific regulation of allelic expression,” eLife, vol. 6. eLife Sciences Publications, 2017.","apa":"Andergassen, D., Dotter, C., Wenzel, D., Sigl, V., Bammer, P., Muckenhuber, M., … Hudson, Q. (2017). Mapping the mouse Allelome reveals tissue specific regulation of allelic expression. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.25125","ama":"Andergassen D, Dotter C, Wenzel D, et al. Mapping the mouse Allelome reveals tissue specific regulation of allelic expression. eLife. 2017;6. doi:10.7554/eLife.25125","chicago":"Andergassen, Daniel, Christoph Dotter, Dyniel Wenzel, Verena Sigl, Philipp Bammer, Markus Muckenhuber, Daniela Mayer, et al. “Mapping the Mouse Allelome Reveals Tissue Specific Regulation of Allelic Expression.” ELife. eLife Sciences Publications, 2017. https://doi.org/10.7554/eLife.25125.","mla":"Andergassen, Daniel, et al. “Mapping the Mouse Allelome Reveals Tissue Specific Regulation of Allelic Expression.” ELife, vol. 6, e25125, eLife Sciences Publications, 2017, doi:10.7554/eLife.25125.","short":"D. Andergassen, C. Dotter, D. Wenzel, V. Sigl, P. Bammer, M. Muckenhuber, D. Mayer, T. Kulinski, H. Theussl, J. Penninger, C. Bock, D. Barlow, F. Pauler, Q. Hudson, ELife 6 (2017)."}},{"publist_id":"6460","ec_funded":1,"file_date_updated":"2020-07-14T12:48:16Z","article_number":"e25192","author":[{"full_name":"Lagator, Mato","id":"345D25EC-F248-11E8-B48F-1D18A9856A87","first_name":"Mato","last_name":"Lagator"},{"first_name":"Tiago","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago"},{"full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","last_name":"Barton"},{"full_name":"Bollback, Jonathan P","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4624-4612","first_name":"Jonathan P","last_name":"Bollback"},{"orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","first_name":"Calin C","full_name":"Guet, Calin C"}],"volume":6,"date_updated":"2023-09-22T10:01:17Z","date_created":"2018-12-11T11:49:23Z","year":"2017","department":[{"_id":"CaGu"},{"_id":"NiBa"},{"_id":"JoBo"}],"publisher":"eLife Sciences Publications","publication_status":"published","publication_identifier":{"issn":["2050084X"]},"month":"05","doi":"10.7554/eLife.25192","language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"external_id":{"isi":["000404024800001"]},"project":[{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","call_identifier":"FP7","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091"},{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"},{"grant_number":"648440","_id":"2578D616-B435-11E9-9278-68D0E5697425","name":"Selective Barriers to Horizontal Gene Transfer","call_identifier":"H2020"}],"isi":1,"quality_controlled":"1","abstract":[{"text":"Understanding the relation between genotype and phenotype remains a major challenge. The difficulty of predicting individual mutation effects, and particularly the interactions between them, has prevented the development of a comprehensive theory that links genotypic changes to their phenotypic effects. We show that a general thermodynamic framework for gene regulation, based on a biophysical understanding of protein-DNA binding, accurately predicts the sign of epistasis in a canonical cis-regulatory element consisting of overlapping RNA polymerase and repressor binding sites. Sign and magnitude of individual mutation effects are sufficient to predict the sign of epistasis and its environmental dependence. Thus, the thermodynamic model offers the correct null prediction for epistasis between mutations across DNA-binding sites. Our results indicate that a predictive theory for the effects of cis-regulatory mutations is possible from first principles, as long as the essential molecular mechanisms and the constraints these impose on a biological system are accounted for.","lang":"eng"}],"type":"journal_article","pubrep_id":"841","file":[{"access_level":"open_access","file_name":"IST-2017-841-v1+1_elife-25192-v2.pdf","creator":"system","content_type":"application/pdf","file_size":2441529,"file_id":"5306","relation":"main_file","checksum":"59cdd4400fb41280122d414fea971546","date_created":"2018-12-12T10:17:49Z","date_updated":"2020-07-14T12:48:16Z"},{"date_created":"2018-12-12T10:17:50Z","date_updated":"2020-07-14T12:48:16Z","checksum":"b69024880558b858eb8c5d47a92b6377","file_id":"5307","relation":"main_file","creator":"system","file_size":3752660,"content_type":"application/pdf","file_name":"IST-2017-841-v1+2_elife-25192-figures-v2.pdf","access_level":"open_access"}],"oa_version":"Published Version","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"954","intvolume":" 6","ddc":["576"],"status":"public","title":"On the mechanistic nature of epistasis in a canonical cis-regulatory element","article_processing_charge":"Yes","has_accepted_license":"1","day":"18","scopus_import":"1","date_published":"2017-05-18T00:00:00Z","citation":{"apa":"Lagator, M., Paixao, T., Barton, N. H., Bollback, J. P., & Guet, C. C. (2017). On the mechanistic nature of epistasis in a canonical cis-regulatory element. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.25192","ieee":"M. Lagator, T. Paixao, N. H. Barton, J. P. Bollback, and C. C. Guet, “On the mechanistic nature of epistasis in a canonical cis-regulatory element,” eLife, vol. 6. eLife Sciences Publications, 2017.","ista":"Lagator M, Paixao T, Barton NH, Bollback JP, Guet CC. 2017. On the mechanistic nature of epistasis in a canonical cis-regulatory element. eLife. 6, e25192.","ama":"Lagator M, Paixao T, Barton NH, Bollback JP, Guet CC. On the mechanistic nature of epistasis in a canonical cis-regulatory element. eLife. 2017;6. doi:10.7554/eLife.25192","chicago":"Lagator, Mato, Tiago Paixao, Nicholas H Barton, Jonathan P Bollback, and Calin C Guet. “On the Mechanistic Nature of Epistasis in a Canonical Cis-Regulatory Element.” ELife. eLife Sciences Publications, 2017. https://doi.org/10.7554/eLife.25192.","short":"M. Lagator, T. Paixao, N.H. Barton, J.P. Bollback, C.C. Guet, ELife 6 (2017).","mla":"Lagator, Mato, et al. “On the Mechanistic Nature of Epistasis in a Canonical Cis-Regulatory Element.” ELife, vol. 6, e25192, eLife Sciences Publications, 2017, doi:10.7554/eLife.25192."},"publication":"eLife"},{"publication_identifier":{"issn":["2050084X"]},"month":"07","doi":"10.7554/eLife.25100","language":[{"iso":"eng"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","publist_id":"6990","file_date_updated":"2020-07-14T12:47:48Z","article_number":"e25100","related_material":{"record":[{"relation":"popular_science","status":"public","id":"5564"},{"id":"26","relation":"dissertation_contains","status":"public"}]},"author":[{"id":"2C023F40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-1229-9719","first_name":"Magdalena","last_name":"Steinrück","full_name":"Steinrück, Magdalena"},{"full_name":"Guet, Calin C","last_name":"Guet","first_name":"Calin C","orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87"}],"volume":6,"date_created":"2018-12-11T11:48:01Z","date_updated":"2024-03-28T23:30:28Z","year":"2017","department":[{"_id":"CaGu"}],"publisher":"eLife Sciences Publications","publication_status":"published","has_accepted_license":"1","day":"25","scopus_import":1,"date_published":"2017-07-25T00:00:00Z","citation":{"ama":"Steinrück M, Guet CC. Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection. eLife. 2017;6. doi:10.7554/eLife.25100","apa":"Steinrück, M., & Guet, C. C. (2017). Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.25100","ieee":"M. Steinrück and C. C. Guet, “Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection,” eLife, vol. 6. eLife Sciences Publications, 2017.","ista":"Steinrück M, Guet CC. 2017. Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection. eLife. 6, e25100.","short":"M. Steinrück, C.C. Guet, ELife 6 (2017).","mla":"Steinrück, Magdalena, and Calin C. Guet. “Complex Chromosomal Neighborhood Effects Determine the Adaptive Potential of a Gene under Selection.” ELife, vol. 6, e25100, eLife Sciences Publications, 2017, doi:10.7554/eLife.25100.","chicago":"Steinrück, Magdalena, and Calin C Guet. “Complex Chromosomal Neighborhood Effects Determine the Adaptive Potential of a Gene under Selection.” ELife. eLife Sciences Publications, 2017. https://doi.org/10.7554/eLife.25100."},"publication":"eLife","abstract":[{"text":"How the organization of genes on a chromosome shapes adaptation is essential for understanding evolutionary paths. Here, we investigate how adaptation to rapidly increasing levels of antibiotic depends on the chromosomal neighborhood of a drug-resistance gene inserted at different positions of the Escherichia coli chromosome. Using a dual-fluorescence reporter that allows us to distinguish gene amplifications from other up-mutations, we track in real-time adaptive changes in expression of the drug-resistance gene. We find that the relative contribution of several mutation types differs systematically between loci due to properties of neighboring genes: essentiality, expression, orientation, termination, and presence of duplicates. These properties determine rate and fitness effects of gene amplification, deletions, and mutations compromising transcriptional termination. Thus, the adaptive potential of a gene under selection is a system-property with a complex genetic basis that is specific for each chromosomal locus, and it can be inferred from detailed functional and genomic data.","lang":"eng"}],"type":"journal_article","pubrep_id":"890","file":[{"date_updated":"2020-07-14T12:47:48Z","date_created":"2018-12-12T10:12:54Z","checksum":"6b908b5db9f61f6820ebd7f8fa815571","file_id":"4975","relation":"main_file","creator":"system","content_type":"application/pdf","file_size":2092088,"file_name":"IST-2017-890-v1+1_elife-25100-v1.pdf","access_level":"open_access"},{"file_size":3428681,"content_type":"application/pdf","creator":"system","access_level":"open_access","file_name":"IST-2017-890-v1+2_elife-25100-figures-v1.pdf","checksum":"ca21530389b720243552678125fdba35","date_updated":"2020-07-14T12:47:48Z","date_created":"2018-12-12T10:12:55Z","relation":"main_file","file_id":"4976"}],"oa_version":"Published Version","_id":"704","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 6","title":"Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection","status":"public","ddc":["576"]}]