[{"oa":1,"publisher":"The Company of Biologists","quality_controlled":"1","date_created":"2019-12-10T14:39:50Z","date_published":"2019-12-04T00:00:00Z","doi":"10.1242/dev.176297","year":"2019","isi":1,"has_accepted_license":"1","publication":"Development","day":"04","project":[{"grant_number":"680037","name":"Coordination of Patterning And Growth In the Spinal Cord","call_identifier":"H2020","_id":"B6FC0238-B512-11E9-945C-1524E6697425"}],"article_number":"dev176297","article_processing_charge":"No","external_id":{"isi":["000507575700004"],"pmid":["31784457"]},"author":[{"first_name":"Pilar","full_name":"Guerrero, Pilar","last_name":"Guerrero"},{"last_name":"Perez-Carrasco","full_name":"Perez-Carrasco, Ruben","first_name":"Ruben"},{"orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P","last_name":"Zagórski","first_name":"Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Page","full_name":"Page, David","first_name":"David"},{"last_name":"Kicheva","full_name":"Kicheva, Anna","orcid":"0000-0003-4509-4998","first_name":"Anna","id":"3959A2A0-F248-11E8-B48F-1D18A9856A87"},{"first_name":"James","last_name":"Briscoe","full_name":"Briscoe, James"},{"last_name":"Page","full_name":"Page, Karen M.","first_name":"Karen M."}],"title":"Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium","citation":{"ista":"Guerrero P, Perez-Carrasco R, Zagórski MP, Page D, Kicheva A, Briscoe J, Page KM. 2019. Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium. Development. 146(23), dev176297.","chicago":"Guerrero, Pilar, Ruben Perez-Carrasco, Marcin P Zagórski, David Page, Anna Kicheva, James Briscoe, and Karen M. Page. “Neuronal Differentiation Influences Progenitor Arrangement in the Vertebrate Neuroepithelium.” Development. The Company of Biologists, 2019. https://doi.org/10.1242/dev.176297.","short":"P. Guerrero, R. Perez-Carrasco, M.P. Zagórski, D. Page, A. Kicheva, J. Briscoe, K.M. Page, Development 146 (2019).","ieee":"P. Guerrero et al., “Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium,” Development, vol. 146, no. 23. The Company of Biologists, 2019.","ama":"Guerrero P, Perez-Carrasco R, Zagórski MP, et al. Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium. Development. 2019;146(23). doi:10.1242/dev.176297","apa":"Guerrero, P., Perez-Carrasco, R., Zagórski, M. P., Page, D., Kicheva, A., Briscoe, J., & Page, K. M. (2019). Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium. Development. The Company of Biologists. https://doi.org/10.1242/dev.176297","mla":"Guerrero, Pilar, et al. “Neuronal Differentiation Influences Progenitor Arrangement in the Vertebrate Neuroepithelium.” Development, vol. 146, no. 23, dev176297, The Company of Biologists, 2019, doi:10.1242/dev.176297."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","scopus_import":"1","intvolume":" 146","month":"12","abstract":[{"lang":"eng","text":"Cell division, movement and differentiation contribute to pattern formation in developing tissues. This is the case in the vertebrate neural tube, in which neurons differentiate in a characteristic pattern from a highly dynamic proliferating pseudostratified epithelium. To investigate how progenitor proliferation and differentiation affect cell arrangement and growth of the neural tube, we used experimental measurements to develop a mechanical model of the apical surface of the neuroepithelium that incorporates the effect of interkinetic nuclear movement and spatially varying rates of neuronal differentiation. Simulations predict that tissue growth and the shape of lineage-related clones of cells differ with the rate of differentiation. Growth is isotropic in regions of high differentiation, but dorsoventrally biased in regions of low differentiation. This is consistent with experimental observations. The absence of directional signalling in the simulations indicates that global mechanical constraints are sufficient to explain the observed differences in anisotropy. This provides insight into how the tissue growth rate affects cell dynamics and growth anisotropy and opens up possibilities to study the coupling between mechanics, pattern formation and growth in the neural tube."}],"oa_version":"Published Version","pmid":1,"ec_funded":1,"volume":146,"issue":"23","publication_status":"published","publication_identifier":{"eissn":["1477-9129"],"issn":["0950-1991"]},"language":[{"iso":"eng"}],"file":[{"access_level":"open_access","relation":"main_file","content_type":"application/pdf","checksum":"b6533c37dc8fbd803ffeca216e0a8b8a","file_id":"7177","creator":"dernst","date_updated":"2020-07-14T12:47:50Z","file_size":7797881,"date_created":"2019-12-13T07:34:06Z","file_name":"2019_Development_Guerrero.pdf"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"journal_article","article_type":"original","status":"public","_id":"7165","file_date_updated":"2020-07-14T12:47:50Z","department":[{"_id":"AnKi"}],"date_updated":"2023-09-06T11:26:36Z","ddc":["570"]},{"publisher":"Springer Nature","quality_controlled":"1","date_published":"2019-10-01T00:00:00Z","doi":"10.1007/978-3-030-32079-9_17","date_created":"2019-12-09T08:47:55Z","page":"292-309","day":"01","publication":"19th International Conference on Runtime Verification","isi":1,"year":"2019","project":[{"name":"The Wittgenstein Prize","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"call_identifier":"FWF","_id":"25F2ACDE-B435-11E9-9278-68D0E5697425","name":"Rigorous Systems Engineering","grant_number":"S11402-N23"}],"title":"Shape expressions for specifying and extracting signal features","author":[{"last_name":"Ničković","full_name":"Ničković, Dejan","first_name":"Dejan"},{"first_name":"Xin","last_name":"Qin","full_name":"Qin, Xin"},{"id":"40960E6E-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas","last_name":"Ferrere","orcid":"0000-0001-5199-3143","full_name":"Ferrere, Thomas"},{"last_name":"Mateis","full_name":"Mateis, Cristinel","first_name":"Cristinel"},{"first_name":"Jyotirmoy","last_name":"Deshmukh","full_name":"Deshmukh, Jyotirmoy"}],"external_id":{"isi":["000570006300017"]},"article_processing_charge":"No","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"mla":"Ničković, Dejan, et al. “Shape Expressions for Specifying and Extracting Signal Features.” 19th International Conference on Runtime Verification, vol. 11757, Springer Nature, 2019, pp. 292–309, doi:10.1007/978-3-030-32079-9_17.","short":"D. Ničković, X. Qin, T. Ferrere, C. Mateis, J. Deshmukh, in:, 19th International Conference on Runtime Verification, Springer Nature, 2019, pp. 292–309.","ieee":"D. Ničković, X. Qin, T. Ferrere, C. Mateis, and J. Deshmukh, “Shape expressions for specifying and extracting signal features,” in 19th International Conference on Runtime Verification, Porto, Portugal, 2019, vol. 11757, pp. 292–309.","apa":"Ničković, D., Qin, X., Ferrere, T., Mateis, C., & Deshmukh, J. (2019). Shape expressions for specifying and extracting signal features. In 19th International Conference on Runtime Verification (Vol. 11757, pp. 292–309). Porto, Portugal: Springer Nature. https://doi.org/10.1007/978-3-030-32079-9_17","ama":"Ničković D, Qin X, Ferrere T, Mateis C, Deshmukh J. Shape expressions for specifying and extracting signal features. In: 19th International Conference on Runtime Verification. Vol 11757. Springer Nature; 2019:292-309. doi:10.1007/978-3-030-32079-9_17","chicago":"Ničković, Dejan, Xin Qin, Thomas Ferrere, Cristinel Mateis, and Jyotirmoy Deshmukh. “Shape Expressions for Specifying and Extracting Signal Features.” In 19th International Conference on Runtime Verification, 11757:292–309. Springer Nature, 2019. https://doi.org/10.1007/978-3-030-32079-9_17.","ista":"Ničković D, Qin X, Ferrere T, Mateis C, Deshmukh J. 2019. Shape expressions for specifying and extracting signal features. 19th International Conference on Runtime Verification. RV: Runtime Verification, LNCS, vol. 11757, 292–309."},"month":"10","intvolume":" 11757","alternative_title":["LNCS"],"scopus_import":"1","oa_version":"None","abstract":[{"lang":"eng","text":"Cyber-physical systems (CPS) and the Internet-of-Things (IoT) result in a tremendous amount of generated, measured and recorded time-series data. Extracting temporal segments that encode patterns with useful information out of these huge amounts of data is an extremely difficult problem. We propose shape expressions as a declarative formalism for specifying, querying and extracting sophisticated temporal patterns from possibly noisy data. Shape expressions are regular expressions with arbitrary (linear, exponential, sinusoidal, etc.) shapes with parameters as atomic predicates and additional constraints on these parameters. We equip shape expressions with a novel noisy semantics that combines regular expression matching semantics with statistical regression. We characterize essential properties of the formalism and propose an efficient approximate shape expression matching procedure. We demonstrate the wide applicability of this technique on two case studies. "}],"volume":11757,"language":[{"iso":"eng"}],"publication_identifier":{"issn":["0302-9743"],"isbn":["9783030320782","9783030320799"]},"publication_status":"published","status":"public","type":"conference","conference":{"name":"RV: Runtime Verification","start_date":"2019-10-08","location":"Porto, Portugal","end_date":"2019-10-11"},"_id":"7159","department":[{"_id":"ToHe"}],"date_updated":"2023-09-06T11:24:10Z"},{"_id":"7183","status":"public","type":"conference","conference":{"location":"Taipei, Taiwan","end_date":"2019-10-31","start_date":"2019-10-28","name":"ATVA: Automated TEchnology for Verification and Analysis"},"date_updated":"2023-09-06T12:40:58Z","department":[{"_id":"KrCh"}],"oa_version":"Preprint","abstract":[{"lang":"eng","text":"A probabilistic vector addition system with states (pVASS) is a finite state Markov process augmented with non-negative integer counters that can be incremented or decremented during each state transition, blocking any behaviour that would cause a counter to decrease below zero. The pVASS can be used as abstractions of probabilistic programs with many decidable properties. The use of pVASS as abstractions requires the presence of nondeterminism in the model. In this paper, we develop techniques for checking fast termination of pVASS with nondeterminism. That is, for every initial configuration of size n, we consider the worst expected number of transitions needed to reach a configuration with some counter negative (the expected termination time). We show that the problem whether the asymptotic expected termination time is linear is decidable in polynomial time for a certain natural class of pVASS with nondeterminism. Furthermore, we show the following dichotomy: if the asymptotic expected termination time is not linear, then it is at least quadratic, i.e., in Ω(n2)."}],"month":"10","intvolume":" 11781","scopus_import":"1","alternative_title":["LNCS"],"main_file_link":[{"url":"https://arxiv.org/abs/1907.11010","open_access":"1"}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["03029743"],"isbn":["9783030317836"],"eissn":["16113349"]},"publication_status":"published","volume":11781,"project":[{"name":"Rigorous Systems Engineering","grant_number":"S 11407_N23","_id":"25832EC2-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"chicago":"Brázdil, Tomás, Krishnendu Chatterjee, Antonín Kucera, Petr Novotný, and Dominik Velan. “Deciding Fast Termination for Probabilistic VASS with Nondeterminism.” In International Symposium on Automated Technology for Verification and Analysis, 11781:462–78. Springer Nature, 2019. https://doi.org/10.1007/978-3-030-31784-3_27.","ista":"Brázdil T, Chatterjee K, Kucera A, Novotný P, Velan D. 2019. Deciding fast termination for probabilistic VASS with nondeterminism. International Symposium on Automated Technology for Verification and Analysis. ATVA: Automated TEchnology for Verification and Analysis, LNCS, vol. 11781, 462–478.","mla":"Brázdil, Tomás, et al. “Deciding Fast Termination for Probabilistic VASS with Nondeterminism.” International Symposium on Automated Technology for Verification and Analysis, vol. 11781, Springer Nature, 2019, pp. 462–78, doi:10.1007/978-3-030-31784-3_27.","ama":"Brázdil T, Chatterjee K, Kucera A, Novotný P, Velan D. Deciding fast termination for probabilistic VASS with nondeterminism. In: International Symposium on Automated Technology for Verification and Analysis. Vol 11781. Springer Nature; 2019:462-478. doi:10.1007/978-3-030-31784-3_27","apa":"Brázdil, T., Chatterjee, K., Kucera, A., Novotný, P., & Velan, D. (2019). Deciding fast termination for probabilistic VASS with nondeterminism. In International Symposium on Automated Technology for Verification and Analysis (Vol. 11781, pp. 462–478). Taipei, Taiwan: Springer Nature. https://doi.org/10.1007/978-3-030-31784-3_27","ieee":"T. Brázdil, K. Chatterjee, A. Kucera, P. Novotný, and D. Velan, “Deciding fast termination for probabilistic VASS with nondeterminism,” in International Symposium on Automated Technology for Verification and Analysis, Taipei, Taiwan, 2019, vol. 11781, pp. 462–478.","short":"T. Brázdil, K. Chatterjee, A. Kucera, P. Novotný, D. Velan, in:, International Symposium on Automated Technology for Verification and Analysis, Springer Nature, 2019, pp. 462–478."},"title":"Deciding fast termination for probabilistic VASS with nondeterminism","author":[{"first_name":"Tomás","full_name":"Brázdil, Tomás","last_name":"Brázdil"},{"first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","last_name":"Chatterjee","full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X"},{"first_name":"Antonín","last_name":"Kucera","full_name":"Kucera, Antonín"},{"last_name":"Novotný","full_name":"Novotný, Petr","id":"3CC3B868-F248-11E8-B48F-1D18A9856A87","first_name":"Petr"},{"full_name":"Velan, Dominik","last_name":"Velan","first_name":"Dominik"}],"external_id":{"isi":["000723515700027"],"arxiv":["1907.11010"]},"article_processing_charge":"No","quality_controlled":"1","publisher":"Springer Nature","oa":1,"day":"21","publication":"International Symposium on Automated Technology for Verification and Analysis","isi":1,"year":"2019","doi":"10.1007/978-3-030-31784-3_27","date_published":"2019-10-21T00:00:00Z","date_created":"2019-12-15T23:00:44Z","page":"462-478"},{"article_number":"1437","citation":{"apa":"Alcântara, A., Bosch, J., Nazari, F., Hoffmann, G., Gallei, M. C., Uhse, S., … Djamei, A. (2019). Systematic Y2H screening reveals extensive effector-complex formation. Frontiers in Plant Science. Frontiers. https://doi.org/10.3389/fpls.2019.01437","ama":"Alcântara A, Bosch J, Nazari F, et al. Systematic Y2H screening reveals extensive effector-complex formation. Frontiers in Plant Science. 2019;10(11). doi:10.3389/fpls.2019.01437","short":"A. Alcântara, J. Bosch, F. Nazari, G. Hoffmann, M.C. Gallei, S. Uhse, M.A. Darino, T. Olukayode, D. Reumann, L. Baggaley, A. Djamei, Frontiers in Plant Science 10 (2019).","ieee":"A. Alcântara et al., “Systematic Y2H screening reveals extensive effector-complex formation,” Frontiers in Plant Science, vol. 10, no. 11. Frontiers, 2019.","mla":"Alcântara, André, et al. “Systematic Y2H Screening Reveals Extensive Effector-Complex Formation.” Frontiers in Plant Science, vol. 10, no. 11, 1437, Frontiers, 2019, doi:10.3389/fpls.2019.01437.","ista":"Alcântara A, Bosch J, Nazari F, Hoffmann G, Gallei MC, Uhse S, Darino MA, Olukayode T, Reumann D, Baggaley L, Djamei A. 2019. Systematic Y2H screening reveals extensive effector-complex formation. Frontiers in Plant Science. 10(11), 1437.","chicago":"Alcântara, André, Jason Bosch, Fahimeh Nazari, Gesa Hoffmann, Michelle C Gallei, Simon Uhse, Martin A. Darino, et al. “Systematic Y2H Screening Reveals Extensive Effector-Complex Formation.” Frontiers in Plant Science. Frontiers, 2019. https://doi.org/10.3389/fpls.2019.01437."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","author":[{"first_name":"André","last_name":"Alcântara","full_name":"Alcântara, André"},{"first_name":"Jason","last_name":"Bosch","full_name":"Bosch, Jason"},{"last_name":"Nazari","full_name":"Nazari, Fahimeh","first_name":"Fahimeh"},{"first_name":"Gesa","full_name":"Hoffmann, Gesa","last_name":"Hoffmann"},{"id":"35A03822-F248-11E8-B48F-1D18A9856A87","first_name":"Michelle C","full_name":"Gallei, Michelle C","orcid":"0000-0003-1286-7368","last_name":"Gallei"},{"first_name":"Simon","full_name":"Uhse, Simon","last_name":"Uhse"},{"last_name":"Darino","full_name":"Darino, Martin A.","first_name":"Martin A."},{"first_name":"Toluwase","full_name":"Olukayode, Toluwase","last_name":"Olukayode"},{"first_name":"Daniel","last_name":"Reumann","full_name":"Reumann, Daniel"},{"first_name":"Laura","full_name":"Baggaley, Laura","last_name":"Baggaley"},{"full_name":"Djamei, Armin","last_name":"Djamei","first_name":"Armin"}],"article_processing_charge":"No","external_id":{"isi":["000499821700001"],"pmid":["31803201"]},"title":"Systematic Y2H screening reveals extensive effector-complex formation","quality_controlled":"1","publisher":"Frontiers","oa":1,"isi":1,"has_accepted_license":"1","year":"2019","day":"14","publication":"Frontiers in Plant Science","doi":"10.3389/fpls.2019.01437","date_published":"2019-11-14T00:00:00Z","date_created":"2019-12-15T23:00:43Z","_id":"7182","type":"journal_article","article_type":"original","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"status":"public","date_updated":"2023-09-06T14:33:46Z","ddc":["580"],"department":[{"_id":"JiFr"}],"file_date_updated":"2020-07-14T12:47:52Z","abstract":[{"lang":"eng","text":"During infection pathogens secrete small molecules, termed effectors, to manipulate and control the interaction with their specific hosts. Both the pathogen and the plant are under high selective pressure to rapidly adapt and co-evolve in what is usually referred to as molecular arms race. Components of the host’s immune system form a network that processes information about molecules with a foreign origin and damage-associated signals, integrating them with developmental and abiotic cues to adapt the plant’s responses. Both in the case of nucleotide-binding leucine-rich repeat receptors and leucine-rich repeat receptor kinases interaction networks have been extensively characterized. However, little is known on whether pathogenic effectors form complexes to overcome plant immunity and promote disease. Ustilago maydis, a biotrophic fungal pathogen that infects maize plants, produces effectors that target hubs in the immune network of the host cell. Here we assess the capability of U. maydis effector candidates to interact with each other, which may play a crucial role during the infection process. Using a systematic yeast-two-hybrid approach and based on a preliminary pooled screen, we selected 63 putative effectors for one-on-one matings with a library of nearly 300 effector candidates. We found that 126 of these effector candidates interacted either with themselves or other predicted effectors. Although the functional relevance of the observed interactions remains elusive, we propose that the observed abundance in complex formation between effectors adds an additional level of complexity to effector research and should be taken into consideration when studying effector evolution and function. Based on this fundamental finding, we suggest various scenarios which could evolutionarily drive the formation and stabilization of an effector interactome."}],"oa_version":"Published Version","pmid":1,"scopus_import":"1","month":"11","intvolume":" 10","publication_identifier":{"eissn":["1664462X"]},"publication_status":"published","file":[{"relation":"main_file","access_level":"open_access","content_type":"application/pdf","checksum":"995aa838aec2064d93550de82b40bbd1","file_id":"7185","creator":"dernst","file_size":1532505,"date_updated":"2020-07-14T12:47:52Z","file_name":"2019_FrontiersPlant_Alcantara.pdf","date_created":"2019-12-16T07:58:43Z"}],"language":[{"iso":"eng"}],"issue":"11","volume":10},{"scopus_import":"1","month":"12","intvolume":" 10","abstract":[{"text":"Arabidopsis PIN2 protein directs transport of the phytohormone auxin from the root tip into the root elongation zone. Variation in hormone transport, which depends on a delicate interplay between PIN2 sorting to and from polar plasma membrane domains, determines root growth. By employing a constitutively degraded version of PIN2, we identify brassinolides as antagonists of PIN2 endocytosis. This response does not require de novo protein synthesis, but involves early events in canonical brassinolide signaling. Brassinolide-controlled adjustments in PIN2 sorting and intracellular distribution governs formation of a lateral PIN2 gradient in gravistimulated roots, coinciding with adjustments in auxin signaling and directional root growth. Strikingly, simulations indicate that PIN2 gradient formation is no prerequisite for root bending but rather dampens asymmetric auxin flow and signaling. Crosstalk between brassinolide signaling and endocytic PIN2 sorting, thus, appears essential for determining the rate of gravity-induced root curvature via attenuation of differential cell elongation.","lang":"eng"}],"pmid":1,"oa_version":"Published Version","volume":10,"publication_identifier":{"eissn":["20411723"]},"publication_status":"published","file":[{"checksum":"77e8720a8e0f3091b98159f85be40893","file_id":"7184","content_type":"application/pdf","access_level":"open_access","relation":"main_file","date_created":"2019-12-16T07:37:50Z","file_name":"2019_NatureComm_Retzer.pdf","date_updated":"2020-07-14T12:47:52Z","file_size":5156533,"creator":"dernst"}],"language":[{"iso":"eng"}],"article_type":"original","type":"journal_article","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"status":"public","_id":"7180","file_date_updated":"2020-07-14T12:47:52Z","department":[{"_id":"DaSi"}],"date_updated":"2023-09-06T14:08:21Z","ddc":["570"],"quality_controlled":"1","publisher":"Springer Nature","oa":1,"doi":"10.1038/s41467-019-13543-1","date_published":"2019-12-01T00:00:00Z","date_created":"2019-12-15T23:00:43Z","has_accepted_license":"1","isi":1,"year":"2019","day":"01","publication":"Nature Communications","project":[{"name":"Modeling epithelial tissue mechanics during cell invasion","grant_number":"M02379","_id":"264CBBAC-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"}],"article_number":"5516","author":[{"last_name":"Retzer","full_name":"Retzer, Katarzyna","first_name":"Katarzyna"},{"last_name":"Akhmanova","orcid":"0000-0003-1522-3162","full_name":"Akhmanova, Maria","id":"3425EC26-F248-11E8-B48F-1D18A9856A87","first_name":"Maria"},{"first_name":"Nataliia","last_name":"Konstantinova","full_name":"Konstantinova, Nataliia"},{"first_name":"Kateřina","full_name":"Malínská, Kateřina","last_name":"Malínská"},{"last_name":"Leitner","full_name":"Leitner, Johannes","first_name":"Johannes"},{"last_name":"Petrášek","full_name":"Petrášek, Jan","first_name":"Jan"},{"first_name":"Christian","last_name":"Luschnig","full_name":"Luschnig, Christian"}],"article_processing_charge":"No","external_id":{"isi":["000500508100001"],"pmid":["31797871"]},"title":"Brassinosteroid signaling delimits root gravitropism via sorting of the Arabidopsis PIN2 auxin transporter","citation":{"mla":"Retzer, Katarzyna, et al. “Brassinosteroid Signaling Delimits Root Gravitropism via Sorting of the Arabidopsis PIN2 Auxin Transporter.” Nature Communications, vol. 10, 5516, Springer Nature, 2019, doi:10.1038/s41467-019-13543-1.","ama":"Retzer K, Akhmanova M, Konstantinova N, et al. Brassinosteroid signaling delimits root gravitropism via sorting of the Arabidopsis PIN2 auxin transporter. Nature Communications. 2019;10. doi:10.1038/s41467-019-13543-1","apa":"Retzer, K., Akhmanova, M., Konstantinova, N., Malínská, K., Leitner, J., Petrášek, J., & Luschnig, C. (2019). Brassinosteroid signaling delimits root gravitropism via sorting of the Arabidopsis PIN2 auxin transporter. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-019-13543-1","ieee":"K. Retzer et al., “Brassinosteroid signaling delimits root gravitropism via sorting of the Arabidopsis PIN2 auxin transporter,” Nature Communications, vol. 10. Springer Nature, 2019.","short":"K. Retzer, M. Akhmanova, N. Konstantinova, K. Malínská, J. Leitner, J. Petrášek, C. Luschnig, Nature Communications 10 (2019).","chicago":"Retzer, Katarzyna, Maria Akhmanova, Nataliia Konstantinova, Kateřina Malínská, Johannes Leitner, Jan Petrášek, and Christian Luschnig. “Brassinosteroid Signaling Delimits Root Gravitropism via Sorting of the Arabidopsis PIN2 Auxin Transporter.” Nature Communications. Springer Nature, 2019. https://doi.org/10.1038/s41467-019-13543-1.","ista":"Retzer K, Akhmanova M, Konstantinova N, Malínská K, Leitner J, Petrášek J, Luschnig C. 2019. Brassinosteroid signaling delimits root gravitropism via sorting of the Arabidopsis PIN2 auxin transporter. Nature Communications. 10, 5516."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1"},{"quality_controlled":"1","publisher":"Springer Nature","oa":1,"page":"1466-1470","date_published":"2019-12-01T00:00:00Z","doi":"10.1038/s41587-019-0333-6","date_created":"2019-12-15T23:00:43Z","isi":1,"year":"2019","day":"01","publication":"Nature Biotechnology","project":[{"grant_number":"771209","name":"Characterizing the fitness landscape on population and global scales","_id":"26580278-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}],"author":[{"first_name":"Edgar","full_name":"Garriga, Edgar","last_name":"Garriga"},{"last_name":"Di Tommaso","full_name":"Di Tommaso, Paolo","first_name":"Paolo"},{"first_name":"Cedrik","full_name":"Magis, Cedrik","last_name":"Magis"},{"first_name":"Ionas","full_name":"Erb, Ionas","last_name":"Erb"},{"full_name":"Mansouri, Leila","last_name":"Mansouri","first_name":"Leila"},{"full_name":"Baltzis, Athanasios","last_name":"Baltzis","first_name":"Athanasios"},{"first_name":"Hafid","full_name":"Laayouni, Hafid","last_name":"Laayouni"},{"id":"44FDEF62-F248-11E8-B48F-1D18A9856A87","first_name":"Fyodor","full_name":"Kondrashov, Fyodor","orcid":"0000-0001-8243-4694","last_name":"Kondrashov"},{"first_name":"Evan","full_name":"Floden, Evan","last_name":"Floden"},{"first_name":"Cedric","full_name":"Notredame, Cedric","last_name":"Notredame"}],"external_id":{"pmid":["31792410"],"isi":["000500748900021"]},"article_processing_charge":"No","title":"Large multiple sequence alignments with a root-to-leaf regressive method","citation":{"short":"E. Garriga, P. Di Tommaso, C. Magis, I. Erb, L. Mansouri, A. Baltzis, H. Laayouni, F. Kondrashov, E. Floden, C. Notredame, Nature Biotechnology 37 (2019) 1466–1470.","ieee":"E. Garriga et al., “Large multiple sequence alignments with a root-to-leaf regressive method,” Nature Biotechnology, vol. 37, no. 12. Springer Nature, pp. 1466–1470, 2019.","apa":"Garriga, E., Di Tommaso, P., Magis, C., Erb, I., Mansouri, L., Baltzis, A., … Notredame, C. (2019). Large multiple sequence alignments with a root-to-leaf regressive method. Nature Biotechnology. Springer Nature. https://doi.org/10.1038/s41587-019-0333-6","ama":"Garriga E, Di Tommaso P, Magis C, et al. Large multiple sequence alignments with a root-to-leaf regressive method. Nature Biotechnology. 2019;37(12):1466-1470. doi:10.1038/s41587-019-0333-6","mla":"Garriga, Edgar, et al. “Large Multiple Sequence Alignments with a Root-to-Leaf Regressive Method.” Nature Biotechnology, vol. 37, no. 12, Springer Nature, 2019, pp. 1466–70, doi:10.1038/s41587-019-0333-6.","ista":"Garriga E, Di Tommaso P, Magis C, Erb I, Mansouri L, Baltzis A, Laayouni H, Kondrashov F, Floden E, Notredame C. 2019. Large multiple sequence alignments with a root-to-leaf regressive method. Nature Biotechnology. 37(12), 1466–1470.","chicago":"Garriga, Edgar, Paolo Di Tommaso, Cedrik Magis, Ionas Erb, Leila Mansouri, Athanasios Baltzis, Hafid Laayouni, Fyodor Kondrashov, Evan Floden, and Cedric Notredame. “Large Multiple Sequence Alignments with a Root-to-Leaf Regressive Method.” Nature Biotechnology. Springer Nature, 2019. https://doi.org/10.1038/s41587-019-0333-6."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","scopus_import":"1","main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894943/"}],"month":"12","intvolume":" 37","abstract":[{"lang":"eng","text":"Multiple sequence alignments (MSAs) are used for structural1,2 and evolutionary predictions1,2, but the complexity of aligning large datasets requires the use of approximate solutions3, including the progressive algorithm4. Progressive MSA methods start by aligning the most similar sequences and subsequently incorporate the remaining sequences, from leaf-to-root, based on a guide-tree. Their accuracy declines substantially as the number of sequences is scaled up5. We introduce a regressive algorithm that enables MSA of up to 1.4 million sequences on a standard workstation and substantially improves accuracy on datasets larger than 10,000 sequences. Our regressive algorithm works the other way around to the progressive algorithm and begins by aligning the most dissimilar sequences. It uses an efficient divide-and-conquer strategy to run third-party alignment methods in linear time, regardless of their original complexity. Our approach will enable analyses of extremely large genomic datasets such as the recently announced Earth BioGenome Project, which comprises 1.5 million eukaryotic genomes6."}],"pmid":1,"oa_version":"Submitted Version","issue":"12","volume":37,"related_material":{"record":[{"relation":"research_data","id":"13059","status":"public"}]},"ec_funded":1,"publication_identifier":{"eissn":["15461696"],"issn":["10870156"]},"publication_status":"published","language":[{"iso":"eng"}],"article_type":"original","type":"journal_article","status":"public","_id":"7181","department":[{"_id":"FyKo"}],"date_updated":"2023-09-06T14:32:52Z"},{"file":[{"date_updated":"2020-07-14T12:47:53Z","file_size":2960543,"creator":"dernst","date_created":"2020-02-18T15:19:26Z","file_name":"2019_eLife_Llorca.pdf","content_type":"application/pdf","access_level":"open_access","relation":"main_file","checksum":"b460ecc33e1a68265e7adea775021f3a","file_id":"7503"}],"language":[{"iso":"eng"}],"publication_identifier":{"eissn":["2050084X"]},"publication_status":"published","volume":8,"ec_funded":1,"pmid":1,"oa_version":"Published Version","abstract":[{"text":"The cerebral cortex contains multiple areas with distinctive cytoarchitectonical patterns, but the cellular mechanisms underlying the emergence of this diversity remain unclear. Here, we have investigated the neuronal output of individual progenitor cells in the developing mouse neocortex using a combination of methods that together circumvent the biases and limitations of individual approaches. Our experimental results indicate that progenitor cells generate pyramidal cell lineages with a wide range of sizes and laminar configurations. Mathematical modelling indicates that these outcomes are compatible with a stochastic model of cortical neurogenesis in which progenitor cells undergo a series of probabilistic decisions that lead to the specification of very heterogeneous progenies. Our findings support a mechanism for cortical neurogenesis whose flexibility would make it capable to generate the diverse cytoarchitectures that characterize distinct neocortical areas.","lang":"eng"}],"month":"11","intvolume":" 8","scopus_import":"1","ddc":["570"],"date_updated":"2023-09-06T14:38:39Z","department":[{"_id":"SiHi"}],"file_date_updated":"2020-07-14T12:47:53Z","_id":"7202","status":"public","article_type":"original","type":"journal_article","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"day":"18","publication":"eLife","isi":1,"has_accepted_license":"1","year":"2019","doi":"10.7554/eLife.51381","date_published":"2019-11-18T00:00:00Z","date_created":"2019-12-22T23:00:42Z","publisher":"eLife Sciences Publications","quality_controlled":"1","oa":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"ista":"Llorca A, Ciceri G, Beattie RJ, Wong FK, Diana G, Serafeimidou-Pouliou E, Fernández-Otero M, Streicher C, Arnold SJ, Meyer M, Hippenmeyer S, Maravall M, Marín O. 2019. A stochastic framework of neurogenesis underlies the assembly of neocortical cytoarchitecture. eLife. 8, e51381.","chicago":"Llorca, Alfredo, Gabriele Ciceri, Robert J Beattie, Fong Kuan Wong, Giovanni Diana, Eleni Serafeimidou-Pouliou, Marian Fernández-Otero, et al. “A Stochastic Framework of Neurogenesis Underlies the Assembly of Neocortical Cytoarchitecture.” ELife. eLife Sciences Publications, 2019. https://doi.org/10.7554/eLife.51381.","ieee":"A. Llorca et al., “A stochastic framework of neurogenesis underlies the assembly of neocortical cytoarchitecture,” eLife, vol. 8. eLife Sciences Publications, 2019.","short":"A. Llorca, G. Ciceri, R.J. Beattie, F.K. Wong, G. Diana, E. Serafeimidou-Pouliou, M. Fernández-Otero, C. Streicher, S.J. Arnold, M. Meyer, S. Hippenmeyer, M. Maravall, O. Marín, ELife 8 (2019).","ama":"Llorca A, Ciceri G, Beattie RJ, et al. A stochastic framework of neurogenesis underlies the assembly of neocortical cytoarchitecture. eLife. 2019;8. doi:10.7554/eLife.51381","apa":"Llorca, A., Ciceri, G., Beattie, R. J., Wong, F. K., Diana, G., Serafeimidou-Pouliou, E., … Marín, O. (2019). A stochastic framework of neurogenesis underlies the assembly of neocortical cytoarchitecture. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.51381","mla":"Llorca, Alfredo, et al. “A Stochastic Framework of Neurogenesis Underlies the Assembly of Neocortical Cytoarchitecture.” ELife, vol. 8, e51381, eLife Sciences Publications, 2019, doi:10.7554/eLife.51381."},"title":"A stochastic framework of neurogenesis underlies the assembly of neocortical cytoarchitecture","author":[{"first_name":"Alfredo","last_name":"Llorca","full_name":"Llorca, Alfredo"},{"full_name":"Ciceri, Gabriele","last_name":"Ciceri","first_name":"Gabriele"},{"first_name":"Robert J","id":"2E26DF60-F248-11E8-B48F-1D18A9856A87","full_name":"Beattie, Robert J","orcid":"0000-0002-8483-8753","last_name":"Beattie"},{"first_name":"Fong Kuan","full_name":"Wong, Fong Kuan","last_name":"Wong"},{"last_name":"Diana","full_name":"Diana, Giovanni","first_name":"Giovanni"},{"first_name":"Eleni","full_name":"Serafeimidou-Pouliou, Eleni","last_name":"Serafeimidou-Pouliou"},{"last_name":"Fernández-Otero","full_name":"Fernández-Otero, Marian","first_name":"Marian"},{"first_name":"Carmen","id":"36BCB99C-F248-11E8-B48F-1D18A9856A87","full_name":"Streicher, Carmen","last_name":"Streicher"},{"first_name":"Sebastian J.","full_name":"Arnold, Sebastian J.","last_name":"Arnold"},{"full_name":"Meyer, Martin","last_name":"Meyer","first_name":"Martin"},{"last_name":"Hippenmeyer","full_name":"Hippenmeyer, Simon","orcid":"0000-0003-2279-1061","id":"37B36620-F248-11E8-B48F-1D18A9856A87","first_name":"Simon"},{"full_name":"Maravall, Miguel","last_name":"Maravall","first_name":"Miguel"},{"full_name":"Marín, Oscar","last_name":"Marín","first_name":"Oscar"}],"external_id":{"isi":["000508156800001"],"pmid":["31736464"]},"article_processing_charge":"No","article_number":"e51381","project":[{"grant_number":"725780","name":"Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development","call_identifier":"H2020","_id":"260018B0-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","_id":"264E56E2-B435-11E9-9278-68D0E5697425","name":"Molecular Mechanisms Regulating Gliogenesis in the Cerebral Cortex","grant_number":"M02416"}]},{"file_date_updated":"2020-12-06T17:30:09Z","department":[{"_id":"RySh"}],"date_updated":"2023-09-06T14:34:36Z","ddc":["571","599"],"article_type":"original","type":"journal_article","status":"public","_id":"7179","volume":33,"issue":"12","publication_identifier":{"eissn":["15306860"]},"publication_status":"published","file":[{"access_level":"open_access","relation":"main_file","content_type":"application/pdf","checksum":"79e3b72481dc32489911121cf3b7d8d0","file_id":"8922","success":1,"creator":"shigemot","date_updated":"2020-12-06T17:30:09Z","file_size":4766789,"date_created":"2020-12-06T17:30:09Z","file_name":"Klotz et al 2019 EMBO Reports.pdf"}],"language":[{"iso":"eng"}],"scopus_import":"1","month":"12","intvolume":" 33","abstract":[{"text":"Glutamate is the major excitatory neurotransmitter in the CNS binding to a variety of glutamate receptors. Metabotropic glutamate receptors (mGluR1 to mGluR8) can act excitatory or inhibitory, depending on associated signal cascades. Expression and localization of inhibitory acting mGluRs at inner hair cells (IHCs) in the cochlea are largely unknown. Here, we analyzed expression of mGluR2, mGluR3, mGluR4, mGluR6, mGluR7, and mGluR8 and investigated their localization with respect to the presynaptic ribbon of IHC synapses. We detected transcripts for mGluR2, mGluR3, and mGluR4 as well as for mGluR7a, mGluR7b, mGluR8a, and mGluR8b splice variants. Using receptor-specific antibodies in cochlear wholemounts, we found expression of mGluR2, mGluR4, and mGluR8b close to presynaptic ribbons. Super resolution and confocal microscopy in combination with 3-dimensional reconstructions indicated a postsynaptic localization of mGluR2 that overlaps with postsynaptic density protein 95 on dendrites of afferent type I spiral ganglion neurons. In contrast, mGluR4 and mGluR8b were expressed at the presynapse close to IHC ribbons. In summary, we localized in detail 3 mGluR types at IHC ribbon synapses, providing a fundament for new therapeutical strategies that could protect the cochlea against noxious stimuli and excitotoxicity.","lang":"eng"}],"oa_version":"Submitted Version","pmid":1,"author":[{"first_name":"Lisa","full_name":"Klotz, Lisa","last_name":"Klotz"},{"first_name":"Olaf","last_name":"Wendler","full_name":"Wendler, Olaf"},{"first_name":"Renato","full_name":"Frischknecht, Renato","last_name":"Frischknecht"},{"last_name":"Shigemoto","orcid":"0000-0001-8761-9444","full_name":"Shigemoto, Ryuichi","first_name":"Ryuichi","id":"499F3ABC-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Schulze, Holger","last_name":"Schulze","first_name":"Holger"},{"full_name":"Enz, Ralf","last_name":"Enz","first_name":"Ralf"}],"article_processing_charge":"No","external_id":{"isi":["000507466100054"],"pmid":["31585509"]},"title":"Localization of group II and III metabotropic glutamate receptors at pre- and postsynaptic sites of inner hair cell ribbon synapses","citation":{"mla":"Klotz, Lisa, et al. “Localization of Group II and III Metabotropic Glutamate Receptors at Pre- and Postsynaptic Sites of Inner Hair Cell Ribbon Synapses.” FASEB Journal, vol. 33, no. 12, FASEB, 2019, pp. 13734–46, doi:10.1096/fj.201901543R.","ieee":"L. Klotz, O. Wendler, R. Frischknecht, R. Shigemoto, H. Schulze, and R. Enz, “Localization of group II and III metabotropic glutamate receptors at pre- and postsynaptic sites of inner hair cell ribbon synapses,” FASEB Journal, vol. 33, no. 12. FASEB, pp. 13734–13746, 2019.","short":"L. Klotz, O. Wendler, R. Frischknecht, R. Shigemoto, H. Schulze, R. Enz, FASEB Journal 33 (2019) 13734–13746.","apa":"Klotz, L., Wendler, O., Frischknecht, R., Shigemoto, R., Schulze, H., & Enz, R. (2019). Localization of group II and III metabotropic glutamate receptors at pre- and postsynaptic sites of inner hair cell ribbon synapses. FASEB Journal. FASEB. https://doi.org/10.1096/fj.201901543R","ama":"Klotz L, Wendler O, Frischknecht R, Shigemoto R, Schulze H, Enz R. Localization of group II and III metabotropic glutamate receptors at pre- and postsynaptic sites of inner hair cell ribbon synapses. FASEB Journal. 2019;33(12):13734-13746. doi:10.1096/fj.201901543R","chicago":"Klotz, Lisa, Olaf Wendler, Renato Frischknecht, Ryuichi Shigemoto, Holger Schulze, and Ralf Enz. “Localization of Group II and III Metabotropic Glutamate Receptors at Pre- and Postsynaptic Sites of Inner Hair Cell Ribbon Synapses.” FASEB Journal. FASEB, 2019. https://doi.org/10.1096/fj.201901543R.","ista":"Klotz L, Wendler O, Frischknecht R, Shigemoto R, Schulze H, Enz R. 2019. Localization of group II and III metabotropic glutamate receptors at pre- and postsynaptic sites of inner hair cell ribbon synapses. FASEB Journal. 33(12), 13734–13746."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","page":"13734-13746","date_published":"2019-12-01T00:00:00Z","doi":"10.1096/fj.201901543R","date_created":"2019-12-15T23:00:42Z","isi":1,"has_accepted_license":"1","year":"2019","day":"01","publication":"FASEB Journal","publisher":"FASEB","quality_controlled":"1","oa":1},{"date_updated":"2023-09-06T14:37:55Z","department":[{"_id":"DaAl"}],"_id":"7201","status":"public","conference":{"name":"SC: Conference for High Performance Computing, Networking, Storage and Analysis","location":"Denver, CO, Unites States","end_date":"2019-11-19","start_date":"2019-11-17"},"type":"conference","language":[{"iso":"eng"}],"publication_status":"published","publication_identifier":{"issn":["21674329"],"isbn":["9781450362290"],"eissn":["21674337"]},"ec_funded":1,"oa_version":"Preprint","abstract":[{"lang":"eng","text":"Applying machine learning techniques to the quickly growing data in science and industry requires highly-scalable algorithms. Large datasets are most commonly processed \"data parallel\" distributed across many nodes. Each node's contribution to the overall gradient is summed using a global allreduce. This allreduce is the single communication and thus scalability bottleneck for most machine learning workloads. We observe that frequently, many gradient values are (close to) zero, leading to sparse of sparsifyable communications. To exploit this insight, we analyze, design, and implement a set of communication-efficient protocols for sparse input data, in conjunction with efficient machine learning algorithms which can leverage these primitives. Our communication protocols generalize standard collective operations, by allowing processes to contribute arbitrary sparse input data vectors. Our generic communication library, SparCML1, extends MPI to support additional features, such as non-blocking (asynchronous) operations and low-precision data representations. As such, SparCML and its techniques will form the basis of future highly-scalable machine learning frameworks."}],"month":"11","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1802.08021"}],"scopus_import":"1","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"apa":"Renggli, C., Ashkboos, S., Aghagolzadeh, M., Alistarh, D.-A., & Hoefler, T. (2019). SparCML: High-performance sparse communication for machine learning. In International Conference for High Performance Computing, Networking, Storage and Analysis, SC. Denver, CO, Unites States: ACM. https://doi.org/10.1145/3295500.3356222","ama":"Renggli C, Ashkboos S, Aghagolzadeh M, Alistarh D-A, Hoefler T. SparCML: High-performance sparse communication for machine learning. In: International Conference for High Performance Computing, Networking, Storage and Analysis, SC. ACM; 2019. doi:10.1145/3295500.3356222","ieee":"C. Renggli, S. Ashkboos, M. Aghagolzadeh, D.-A. Alistarh, and T. Hoefler, “SparCML: High-performance sparse communication for machine learning,” in International Conference for High Performance Computing, Networking, Storage and Analysis, SC, Denver, CO, Unites States, 2019.","short":"C. Renggli, S. Ashkboos, M. Aghagolzadeh, D.-A. Alistarh, T. Hoefler, in:, International Conference for High Performance Computing, Networking, Storage and Analysis, SC, ACM, 2019.","mla":"Renggli, Cedric, et al. “SparCML: High-Performance Sparse Communication for Machine Learning.” International Conference for High Performance Computing, Networking, Storage and Analysis, SC, a11, ACM, 2019, doi:10.1145/3295500.3356222.","ista":"Renggli C, Ashkboos S, Aghagolzadeh M, Alistarh D-A, Hoefler T. 2019. SparCML: High-performance sparse communication for machine learning. International Conference for High Performance Computing, Networking, Storage and Analysis, SC. SC: Conference for High Performance Computing, Networking, Storage and Analysis, a11.","chicago":"Renggli, Cedric, Saleh Ashkboos, Mehdi Aghagolzadeh, Dan-Adrian Alistarh, and Torsten Hoefler. “SparCML: High-Performance Sparse Communication for Machine Learning.” In International Conference for High Performance Computing, Networking, Storage and Analysis, SC. ACM, 2019. https://doi.org/10.1145/3295500.3356222."},"title":"SparCML: High-performance sparse communication for machine learning","external_id":{"isi":["000545976800011"],"arxiv":["1802.08021"]},"article_processing_charge":"No","author":[{"first_name":"Cedric","full_name":"Renggli, Cedric","last_name":"Renggli"},{"last_name":"Ashkboos","full_name":"Ashkboos, Saleh","id":"0D0A9058-257B-11EA-A937-9341C3D8BC8A","first_name":"Saleh"},{"first_name":"Mehdi","full_name":"Aghagolzadeh, Mehdi","last_name":"Aghagolzadeh"},{"first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh","full_name":"Alistarh, Dan-Adrian","orcid":"0000-0003-3650-940X"},{"first_name":"Torsten","full_name":"Hoefler, Torsten","last_name":"Hoefler"}],"article_number":"a11","project":[{"grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020","_id":"268A44D6-B435-11E9-9278-68D0E5697425"}],"publication":"International Conference for High Performance Computing, Networking, Storage and Analysis, SC","day":"17","year":"2019","isi":1,"date_created":"2019-12-22T23:00:42Z","date_published":"2019-11-17T00:00:00Z","doi":"10.1145/3295500.3356222","oa":1,"publisher":"ACM","quality_controlled":"1"},{"department":[{"_id":"NiBa"}],"title":"Data from: Is embryo abortion a postzygotic barrier to gene flow between Littorina ecotypes?","author":[{"first_name":"Kerstin","full_name":"Johannesson, Kerstin","last_name":"Johannesson"},{"first_name":"Zuzanna","full_name":"Zagrodzka, Zuzanna","last_name":"Zagrodzka"},{"full_name":"Faria, Rui","last_name":"Faria","first_name":"Rui"},{"orcid":"0000-0003-1050-4969","full_name":"Westram, Anja M","last_name":"Westram","id":"3C147470-F248-11E8-B48F-1D18A9856A87","first_name":"Anja M"},{"first_name":"Roger","last_name":"Butlin","full_name":"Butlin, Roger"}],"article_processing_charge":"No","ddc":["570"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2023-09-06T14:48:57Z","citation":{"chicago":"Johannesson, Kerstin, Zuzanna Zagrodzka, Rui Faria, Anja M Westram, and Roger Butlin. “Data from: Is Embryo Abortion a Postzygotic Barrier to Gene Flow between Littorina Ecotypes?” Dryad, 2019. https://doi.org/10.5061/DRYAD.TB2RBNZWK.","ista":"Johannesson K, Zagrodzka Z, Faria R, Westram AM, Butlin R. 2019. Data from: Is embryo abortion a postzygotic barrier to gene flow between Littorina ecotypes?, Dryad, 10.5061/DRYAD.TB2RBNZWK.","mla":"Johannesson, Kerstin, et al. Data from: Is Embryo Abortion a Postzygotic Barrier to Gene Flow between Littorina Ecotypes? Dryad, 2019, doi:10.5061/DRYAD.TB2RBNZWK.","apa":"Johannesson, K., Zagrodzka, Z., Faria, R., Westram, A. M., & Butlin, R. (2019). Data from: Is embryo abortion a postzygotic barrier to gene flow between Littorina ecotypes? Dryad. https://doi.org/10.5061/DRYAD.TB2RBNZWK","ama":"Johannesson K, Zagrodzka Z, Faria R, Westram AM, Butlin R. Data from: Is embryo abortion a postzygotic barrier to gene flow between Littorina ecotypes? 2019. doi:10.5061/DRYAD.TB2RBNZWK","ieee":"K. Johannesson, Z. Zagrodzka, R. Faria, A. M. Westram, and R. Butlin, “Data from: Is embryo abortion a postzygotic barrier to gene flow between Littorina ecotypes?” Dryad, 2019.","short":"K. Johannesson, Z. Zagrodzka, R. Faria, A.M. Westram, R. Butlin, (2019)."},"status":"public","type":"research_data_reference","tmp":{"image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)","short":"CC0 (1.0)"},"_id":"13067","doi":"10.5061/DRYAD.TB2RBNZWK","related_material":{"record":[{"id":"7205","status":"public","relation":"used_in_publication"}]},"date_published":"2019-12-02T00:00:00Z","date_created":"2023-05-23T16:36:27Z","license":"https://creativecommons.org/publicdomain/zero/1.0/","day":"02","year":"2019","month":"12","publisher":"Dryad","oa":1,"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5061/dryad.tb2rbnzwk"}],"oa_version":"Published Version","abstract":[{"lang":"eng","text":"Genetic incompatibilities contribute to reproductive isolation between many diverging populations, but it is still unclear to what extent they play a role if divergence happens with gene flow. In contact zones between the \"Crab\" and \"Wave\" ecotypes of the snail Littorina saxatilis divergent selection forms strong barriers to gene flow, while the role of postzygotic barriers due to selection against hybrids remains unclear. High embryo abortion rates in this species could indicate the presence of such barriers. Postzygotic barriers might include genetic incompatibilities (e.g. Dobzhansky-Muller incompatibilities) but also maladaptation, both expected to be most pronounced in contact zones. In addition, embryo abortion might reflect physiological stress on females and embryos independent of any genetic stress. We examined all embryos of >500 females sampled outside and inside contact zones of three populations in Sweden. Females' clutch size ranged from 0 to 1011 embryos (mean 130±123) and abortion rates varied between 0 and100% (mean 12%). We described female genotypes by using a hybrid index based on hundreds of SNPs differentiated between ecotypes with which we characterised female genotypes. We also calculated female SNP heterozygosity and inversion karyotype. Clutch size did not vary with female hybrid index and abortion rates were only weakly related to hybrid index in two sites but not at all in a third site. No additional variation in abortion rate was explained by female SNP heterozygosity, but increased female inversion heterozygosity added slightly to increased abortion. Our results show only weak and probably biologically insignificant postzygotic barriers contributing to ecotype divergence and the high and variable abortion rates were marginally, if at all, explained by hybrid index of females."}]}]