[{"department":[{"_id":"NiBa"},{"_id":"KrCh"}],"article_type":"original","title":"Evolutionarily stable mating decisions for sequentially searching females and the stability of reproductive isolation by assortative mating","oa":1,"publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"02","_id":"1851","citation":{"ista":"Priklopil T, Kisdi E, Gyllenberg M. 2015. Evolutionarily stable mating decisions for sequentially searching females and the stability of reproductive isolation by assortative mating. Evolution. 69(4), 1015–1026.","apa":"Priklopil, T., Kisdi, E., &#38; Gyllenberg, M. (2015). Evolutionarily stable mating decisions for sequentially searching females and the stability of reproductive isolation by assortative mating. <i>Evolution</i>. Wiley. <a href=\"https://doi.org/10.1111/evo.12618\">https://doi.org/10.1111/evo.12618</a>","chicago":"Priklopil, Tadeas, Eva Kisdi, and Mats Gyllenberg. “Evolutionarily Stable Mating Decisions for Sequentially Searching Females and the Stability of Reproductive Isolation by Assortative Mating.” <i>Evolution</i>. Wiley, 2015. <a href=\"https://doi.org/10.1111/evo.12618\">https://doi.org/10.1111/evo.12618</a>.","mla":"Priklopil, Tadeas, et al. “Evolutionarily Stable Mating Decisions for Sequentially Searching Females and the Stability of Reproductive Isolation by Assortative Mating.” <i>Evolution</i>, vol. 69, no. 4, Wiley, 2015, pp. 1015–26, doi:<a href=\"https://doi.org/10.1111/evo.12618\">10.1111/evo.12618</a>.","ieee":"T. Priklopil, E. Kisdi, and M. Gyllenberg, “Evolutionarily stable mating decisions for sequentially searching females and the stability of reproductive isolation by assortative mating,” <i>Evolution</i>, vol. 69, no. 4. Wiley, pp. 1015–1026, 2015.","short":"T. Priklopil, E. Kisdi, M. Gyllenberg, Evolution 69 (2015) 1015–1026.","ama":"Priklopil T, Kisdi E, Gyllenberg M. Evolutionarily stable mating decisions for sequentially searching females and the stability of reproductive isolation by assortative mating. <i>Evolution</i>. 2015;69(4):1015-1026. doi:<a href=\"https://doi.org/10.1111/evo.12618\">10.1111/evo.12618</a>"},"intvolume":"        69","has_accepted_license":"1","day":"09","abstract":[{"text":"We consider mating strategies for females who search for males sequentially during a season of limited length. We show that the best strategy rejects a given male type if encountered before a time-threshold but accepts him after. For frequency-independent benefits, we obtain the optimal time-thresholds explicitly for both discrete and continuous distributions of males, and allow for mistakes being made in assessing the correct male type. When the benefits are indirect (genes for the offspring) and the population is under frequency-dependent ecological selection, the benefits depend on the mating strategy of other females as well. This case is particularly relevant to speciation models that seek to explore the stability of reproductive isolation by assortative mating under frequency-dependent ecological selection. We show that the indirect benefits are to be quantified by the reproductive values of couples, and describe how the evolutionarily stable time-thresholds can be found. We conclude with an example based on the Levene model, in which we analyze the evolutionarily stable assortative mating strategies and the strength of reproductive isolation provided by them.","lang":"eng"}],"status":"public","ec_funded":1,"ddc":["570"],"author":[{"id":"3C869AA0-F248-11E8-B48F-1D18A9856A87","first_name":"Tadeas","full_name":"Priklopil, Tadeas","last_name":"Priklopil"},{"last_name":"Kisdi","full_name":"Kisdi, Eva","first_name":"Eva"},{"last_name":"Gyllenberg","full_name":"Gyllenberg, Mats","first_name":"Mats"}],"publication":"Evolution","issue":"4","publist_id":"5249","date_published":"2015-02-09T00:00:00Z","oa_version":"Submitted Version","external_id":{"pmid":["25662095"]},"file_date_updated":"2020-07-14T12:45:19Z","type":"journal_article","language":[{"iso":"eng"}],"publisher":"Wiley","doi":"10.1111/evo.12618","scopus_import":"1","pmid":1,"publication_identifier":{"eissn":["1558-5646"],"issn":["0014-3820"]},"article_processing_charge":"No","volume":69,"file":[{"checksum":"1e8be0b1d7598a78cd2623d8ee8e7798","relation":"main_file","creator":"dernst","file_size":967214,"file_name":"2015_Evolution_Priklopil.pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:19Z","file_id":"7855","date_created":"2020-05-15T09:05:34Z","content_type":"application/pdf"}],"date_updated":"2022-06-07T10:52:37Z","project":[{"grant_number":"291734","name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"quality_controlled":"1","page":"1015 - 1026","date_created":"2018-12-11T11:54:21Z","year":"2015"},{"date_published":"2015-02-02T00:00:00Z","external_id":{"arxiv":["1012.3298"]},"oa_version":"Preprint","author":[{"first_name":"Stephanie","full_name":"Keller-Schmidt, Stephanie","last_name":"Keller-Schmidt"},{"last_name":"Tugrul","first_name":"Murat","full_name":"Tugrul, Murat","id":"37C323C6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8523-0758"},{"first_name":"Víctor","full_name":"Eguíluz, Víctor","last_name":"Eguíluz"},{"last_name":"Hernandez Garcia","first_name":"Emilio","full_name":"Hernandez Garcia, Emilio"},{"first_name":"Konstantin","full_name":"Klemm, Konstantin","last_name":"Klemm"}],"issue":"2","publication":"Physical Review E Statistical Nonlinear and Soft Matter Physics","publist_id":"5213","publisher":"American Institute of Physics","doi":"10.1103/PhysRevE.91.022803","type":"journal_article","language":[{"iso":"eng"}],"arxiv":1,"article_processing_charge":"No","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1012.3298"}],"scopus_import":1,"date_updated":"2021-01-12T06:53:49Z","date_created":"2018-12-11T11:54:31Z","year":"2015","quality_controlled":"1","volume":91,"department":[{"_id":"NiBa"}],"month":"02","_id":"1883","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_type":"original","publication_status":"published","oa":1,"title":"Anomalous scaling in an age-dependent branching model","day":"02","intvolume":"        91","citation":{"ama":"Keller-Schmidt S, Tugrul M, Eguíluz V, Hernandez Garcia E, Klemm K. Anomalous scaling in an age-dependent branching model. <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. 2015;91(2). doi:<a href=\"https://doi.org/10.1103/PhysRevE.91.022803\">10.1103/PhysRevE.91.022803</a>","short":"S. Keller-Schmidt, M. Tugrul, V. Eguíluz, E. Hernandez Garcia, K. Klemm, Physical Review E Statistical Nonlinear and Soft Matter Physics 91 (2015).","mla":"Keller-Schmidt, Stephanie, et al. “Anomalous Scaling in an Age-Dependent Branching Model.” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>, vol. 91, no. 2, 022803, American Institute of Physics, 2015, doi:<a href=\"https://doi.org/10.1103/PhysRevE.91.022803\">10.1103/PhysRevE.91.022803</a>.","ieee":"S. Keller-Schmidt, M. Tugrul, V. Eguíluz, E. Hernandez Garcia, and K. Klemm, “Anomalous scaling in an age-dependent branching model,” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>, vol. 91, no. 2. American Institute of Physics, 2015.","ista":"Keller-Schmidt S, Tugrul M, Eguíluz V, Hernandez Garcia E, Klemm K. 2015. Anomalous scaling in an age-dependent branching model. Physical Review E Statistical Nonlinear and Soft Matter Physics. 91(2), 022803.","apa":"Keller-Schmidt, S., Tugrul, M., Eguíluz, V., Hernandez Garcia, E., &#38; Klemm, K. (2015). Anomalous scaling in an age-dependent branching model. <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. American Institute of Physics. <a href=\"https://doi.org/10.1103/PhysRevE.91.022803\">https://doi.org/10.1103/PhysRevE.91.022803</a>","chicago":"Keller-Schmidt, Stephanie, Murat Tugrul, Víctor Eguíluz, Emilio Hernandez Garcia, and Konstantin Klemm. “Anomalous Scaling in an Age-Dependent Branching Model.” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. American Institute of Physics, 2015. <a href=\"https://doi.org/10.1103/PhysRevE.91.022803\">https://doi.org/10.1103/PhysRevE.91.022803</a>."},"abstract":[{"text":"We introduce a one-parametric family of tree growth models, in which branching probabilities decrease with branch age τ as τ-α. Depending on the exponent α, the scaling of tree depth with tree size n displays a transition between the logarithmic scaling of random trees and an algebraic growth. At the transition (α=1) tree depth grows as (logn)2. This anomalous scaling is in good agreement with the trend observed in evolution of biological species, thus providing a theoretical support for age-dependent speciation and associating it to the occurrence of a critical point.\r\n","lang":"eng"}],"status":"public","article_number":"022803"},{"date_published":"2015-07-11T00:00:00Z","department":[{"_id":"NiBa"},{"_id":"CaGu"}],"oa_version":"Preprint","conference":{"end_date":"2015-07-15","location":"Madrid, Spain","start_date":"2015-07-11","name":"GECCO: Genetic and evolutionary computation conference"},"author":[{"id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago","first_name":"Tiago","last_name":"Paixao"},{"full_name":"Sudholt, Dirk","first_name":"Dirk","last_name":"Sudholt"},{"first_name":"Jorge","full_name":"Heredia, Jorge","last_name":"Heredia"},{"orcid":"0000-0002-6873-2967","id":"42302D54-F248-11E8-B48F-1D18A9856A87","last_name":"Trubenova","first_name":"Barbora","full_name":"Trubenova, Barbora"}],"publication":"Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation","publist_id":"5768","publisher":"ACM","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1430","doi":"10.1145/2739480.2754758","month":"07","type":"conference","title":"First steps towards a runtime comparison of natural and artificial evolution","oa":1,"language":[{"iso":"eng"}],"publication_status":"published","day":"11","scopus_import":1,"main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1504.06260"}],"citation":{"chicago":"Paixao, Tiago, Dirk Sudholt, Jorge Heredia, and Barbora Trubenova. “First Steps towards a Runtime Comparison of Natural and Artificial Evolution.” In <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i>, 1455–62. ACM, 2015. <a href=\"https://doi.org/10.1145/2739480.2754758\">https://doi.org/10.1145/2739480.2754758</a>.","ista":"Paixao T, Sudholt D, Heredia J, Trubenova B. 2015. First steps towards a runtime comparison of natural and artificial evolution. Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation. GECCO: Genetic and evolutionary computation conference, 1455–1462.","apa":"Paixao, T., Sudholt, D., Heredia, J., &#38; Trubenova, B. (2015). First steps towards a runtime comparison of natural and artificial evolution. In <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i> (pp. 1455–1462). Madrid, Spain: ACM. <a href=\"https://doi.org/10.1145/2739480.2754758\">https://doi.org/10.1145/2739480.2754758</a>","ieee":"T. Paixao, D. Sudholt, J. Heredia, and B. Trubenova, “First steps towards a runtime comparison of natural and artificial evolution,” in <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i>, Madrid, Spain, 2015, pp. 1455–1462.","mla":"Paixao, Tiago, et al. “First Steps towards a Runtime Comparison of Natural and Artificial Evolution.” <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i>, ACM, 2015, pp. 1455–62, doi:<a href=\"https://doi.org/10.1145/2739480.2754758\">10.1145/2739480.2754758</a>.","short":"T. Paixao, D. Sudholt, J. Heredia, B. Trubenova, in:, Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, ACM, 2015, pp. 1455–1462.","ama":"Paixao T, Sudholt D, Heredia J, Trubenova B. First steps towards a runtime comparison of natural and artificial evolution. In: <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i>. ACM; 2015:1455-1462. doi:<a href=\"https://doi.org/10.1145/2739480.2754758\">10.1145/2739480.2754758</a>"},"date_updated":"2021-01-12T06:50:41Z","ec_funded":1,"project":[{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","grant_number":"618091","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"page":"1455 - 1462","quality_controlled":"1","date_created":"2018-12-11T11:51:58Z","year":"2015","abstract":[{"lang":"eng","text":"Evolutionary algorithms (EAs) form a popular optimisation paradigm inspired by natural evolution. In recent years the field of evolutionary computation has developed a rigorous analytical theory to analyse their runtime on many illustrative problems. Here we apply this theory to a simple model of natural evolution. In the Strong Selection Weak Mutation (SSWM) evolutionary regime the time between occurrence of new mutations is much longer than the time it takes for a new beneficial mutation to take over the population. In this situation, the population only contains copies of one genotype and evolution can be modelled as a (1+1)-type process where the probability of accepting a new genotype (improvements or worsenings) depends on the change in fitness. We present an initial runtime analysis of SSWM, quantifying its performance for various parameters and investigating differences to the (1+1) EA. We show that SSWM can have a moderate advantage over the (1+1) EA at crossing fitness valleys and study an example where SSWM outperforms the (1+1) EA by taking advantage of information on the fitness gradient."}],"status":"public"},{"department":[{"_id":"NiBa"},{"_id":"CaGu"},{"_id":"GaTk"}],"date_published":"2015-11-06T00:00:00Z","oa_version":"Published Version","author":[{"orcid":"0000-0002-8523-0758","id":"37C323C6-F248-11E8-B48F-1D18A9856A87","first_name":"Murat","full_name":"Tugrul, Murat","last_name":"Tugrul"},{"orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","first_name":"Tiago","full_name":"Paixao, Tiago"},{"full_name":"Barton, Nicholas H","first_name":"Nicholas H","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","last_name":"Tkačik","full_name":"Tkačik, Gašper","first_name":"Gašper"}],"publisher":"Public Library of Science","month":"11","_id":"9712","doi":"10.1371/journal.pgen.1005639.s001","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","type":"research_data_reference","title":"Other fitness models for comparison & for interacting TFBSs","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"1666"}]},"article_processing_charge":"No","day":"06","citation":{"short":"M. Tugrul, T. Paixao, N.H. Barton, G. Tkačik, (2015).","ama":"Tugrul M, Paixao T, Barton NH, Tkačik G. Other fitness models for comparison &#38; for interacting TFBSs. 2015. doi:<a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">10.1371/journal.pgen.1005639.s001</a>","chicago":"Tugrul, Murat, Tiago Paixao, Nicholas H Barton, and Gašper Tkačik. “Other Fitness Models for Comparison &#38; for Interacting TFBSs.” Public Library of Science, 2015. <a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">https://doi.org/10.1371/journal.pgen.1005639.s001</a>.","ista":"Tugrul M, Paixao T, Barton NH, Tkačik G. 2015. Other fitness models for comparison &#38; for interacting TFBSs, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">10.1371/journal.pgen.1005639.s001</a>.","apa":"Tugrul, M., Paixao, T., Barton, N. H., &#38; Tkačik, G. (2015). Other fitness models for comparison &#38; for interacting TFBSs. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">https://doi.org/10.1371/journal.pgen.1005639.s001</a>","ieee":"M. Tugrul, T. Paixao, N. H. Barton, and G. Tkačik, “Other fitness models for comparison &#38; for interacting TFBSs.” Public Library of Science, 2015.","mla":"Tugrul, Murat, et al. <i>Other Fitness Models for Comparison &#38; for Interacting TFBSs</i>. Public Library of Science, 2015, doi:<a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">10.1371/journal.pgen.1005639.s001</a>."},"date_updated":"2025-05-28T11:57:04Z","year":"2015","date_created":"2021-07-23T12:00:37Z","status":"public"},{"article_processing_charge":"No","day":"18","citation":{"ama":"Trubenova B, Novak S, Hager R. Mathematical inference of the results. 2015. doi:<a href=\"https://doi.org/10.1371/journal.pone.0126907.s001\">10.1371/journal.pone.0126907.s001</a>","short":"B. Trubenova, S. Novak, R. Hager, (2015).","mla":"Trubenova, Barbora, et al. <i>Mathematical Inference of the Results</i>. Public Library of Science, 2015, doi:<a href=\"https://doi.org/10.1371/journal.pone.0126907.s001\">10.1371/journal.pone.0126907.s001</a>.","ieee":"B. Trubenova, S. Novak, and R. Hager, “Mathematical inference of the results.” Public Library of Science, 2015.","ista":"Trubenova B, Novak S, Hager R. 2015. Mathematical inference of the results, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pone.0126907.s001\">10.1371/journal.pone.0126907.s001</a>.","apa":"Trubenova, B., Novak, S., &#38; Hager, R. (2015). Mathematical inference of the results. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pone.0126907.s001\">https://doi.org/10.1371/journal.pone.0126907.s001</a>","chicago":"Trubenova, Barbora, Sebastian Novak, and Reinmar Hager. “Mathematical Inference of the Results.” Public Library of Science, 2015. <a href=\"https://doi.org/10.1371/journal.pone.0126907.s001\">https://doi.org/10.1371/journal.pone.0126907.s001</a>."},"date_updated":"2023-02-23T10:15:25Z","year":"2015","date_created":"2021-07-23T12:11:30Z","status":"public","department":[{"_id":"NiBa"}],"date_published":"2015-05-18T00:00:00Z","oa_version":"Published Version","author":[{"last_name":"Trubenova","first_name":"Barbora","full_name":"Trubenova, Barbora","orcid":"0000-0002-6873-2967","id":"42302D54-F248-11E8-B48F-1D18A9856A87"},{"id":"461468AE-F248-11E8-B48F-1D18A9856A87","first_name":"Sebastian","full_name":"Novak, Sebastian","last_name":"Novak"},{"last_name":"Hager","full_name":"Hager, Reinmar","first_name":"Reinmar"}],"publisher":"Public Library of Science","_id":"9715","month":"05","doi":"10.1371/journal.pone.0126907.s001","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","type":"research_data_reference","title":"Mathematical inference of the results","related_material":{"record":[{"id":"1809","relation":"used_in_publication","status":"public"}]}},{"status":"public","date_updated":"2023-02-23T10:15:25Z","date_created":"2021-08-05T12:55:20Z","year":"2015","citation":{"ama":"Trubenova B, Novak S, Hager R. Description of the agent based simulations. 2015. doi:<a href=\"https://doi.org/10.1371/journal.pone.0126907.s003\">10.1371/journal.pone.0126907.s003</a>","short":"B. Trubenova, S. Novak, R. Hager, (2015).","ieee":"B. Trubenova, S. Novak, and R. Hager, “Description of the agent based simulations.” Public Library of Science, 2015.","mla":"Trubenova, Barbora, et al. <i>Description of the Agent Based Simulations</i>. Public Library of Science, 2015, doi:<a href=\"https://doi.org/10.1371/journal.pone.0126907.s003\">10.1371/journal.pone.0126907.s003</a>.","apa":"Trubenova, B., Novak, S., &#38; Hager, R. (2015). Description of the agent based simulations. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pone.0126907.s003\">https://doi.org/10.1371/journal.pone.0126907.s003</a>","ista":"Trubenova B, Novak S, Hager R. 2015. Description of the agent based simulations, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pone.0126907.s003\">10.1371/journal.pone.0126907.s003</a>.","chicago":"Trubenova, Barbora, Sebastian Novak, and Reinmar Hager. “Description of the Agent Based Simulations.” Public Library of Science, 2015. <a href=\"https://doi.org/10.1371/journal.pone.0126907.s003\">https://doi.org/10.1371/journal.pone.0126907.s003</a>."},"article_processing_charge":"No","day":"18","type":"research_data_reference","related_material":{"record":[{"id":"1809","relation":"used_in_publication","status":"public"}]},"title":"Description of the agent based simulations","publisher":"Public Library of Science","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","_id":"9772","doi":"10.1371/journal.pone.0126907.s003","month":"05","author":[{"orcid":"0000-0002-6873-2967","id":"42302D54-F248-11E8-B48F-1D18A9856A87","full_name":"Trubenova, Barbora","first_name":"Barbora","last_name":"Trubenova"},{"last_name":"Novak","first_name":"Sebastian","full_name":"Novak, Sebastian","id":"461468AE-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Hager","full_name":"Hager, Reinmar","first_name":"Reinmar"}],"date_published":"2015-05-18T00:00:00Z","department":[{"_id":"NiBa"}],"oa_version":"Published Version"},{"publication":"Physical Review E Statistical Nonlinear and Soft Matter Physics","publist_id":"5198","issue":"3","author":[{"full_name":"Kollár, Richard","first_name":"Richard","last_name":"Kollár"},{"orcid":"0000-0002-7214-0171","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","last_name":"Bod'ová","first_name":"Katarína","full_name":"Bod'ová, Katarína"},{"full_name":"Nosek, Jozef","first_name":"Jozef","last_name":"Nosek"},{"full_name":"Tomáška, Ľubomír","first_name":"Ľubomír","last_name":"Tomáška"}],"oa_version":"Submitted Version","date_published":"2014-03-04T00:00:00Z","language":[{"iso":"eng"}],"type":"journal_article","doi":"10.1103/PhysRevE.89.032701","publisher":"American Institute of Physics","scopus_import":"1","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1402.0430"}],"article_processing_charge":"No","volume":89,"year":"2014","date_created":"2018-12-11T11:54:35Z","date_updated":"2022-08-01T10:50:10Z","acknowledgement":"The work was supported by the VEGA Grant No. 1/0459/13 (R.K. and K.B.).","department":[{"_id":"NiBa"},{"_id":"GaTk"}],"oa":1,"title":"Mathematical model of alternative mechanism of telomere length maintenance","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1896","month":"03","citation":{"ieee":"R. Kollár, K. Bodova, J. Nosek, and Ľ. Tomáška, “Mathematical model of alternative mechanism of telomere length maintenance,” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>, vol. 89, no. 3. American Institute of Physics, 2014.","mla":"Kollár, Richard, et al. “Mathematical Model of Alternative Mechanism of Telomere Length Maintenance.” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>, vol. 89, no. 3, 032701, American Institute of Physics, 2014, doi:<a href=\"https://doi.org/10.1103/PhysRevE.89.032701\">10.1103/PhysRevE.89.032701</a>.","apa":"Kollár, R., Bodova, K., Nosek, J., &#38; Tomáška, Ľ. (2014). Mathematical model of alternative mechanism of telomere length maintenance. <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. American Institute of Physics. <a href=\"https://doi.org/10.1103/PhysRevE.89.032701\">https://doi.org/10.1103/PhysRevE.89.032701</a>","chicago":"Kollár, Richard, Katarina Bodova, Jozef Nosek, and Ľubomír Tomáška. “Mathematical Model of Alternative Mechanism of Telomere Length Maintenance.” <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. American Institute of Physics, 2014. <a href=\"https://doi.org/10.1103/PhysRevE.89.032701\">https://doi.org/10.1103/PhysRevE.89.032701</a>.","ista":"Kollár R, Bodova K, Nosek J, Tomáška Ľ. 2014. Mathematical model of alternative mechanism of telomere length maintenance. Physical Review E Statistical Nonlinear and Soft Matter Physics. 89(3), 032701.","ama":"Kollár R, Bodova K, Nosek J, Tomáška Ľ. Mathematical model of alternative mechanism of telomere length maintenance. <i>Physical Review E Statistical Nonlinear and Soft Matter Physics</i>. 2014;89(3). doi:<a href=\"https://doi.org/10.1103/PhysRevE.89.032701\">10.1103/PhysRevE.89.032701</a>","short":"R. Kollár, K. Bodova, J. Nosek, Ľ. Tomáška, Physical Review E Statistical Nonlinear and Soft Matter Physics 89 (2014)."},"intvolume":"        89","day":"04","article_number":"032701","status":"public","abstract":[{"lang":"eng","text":"Biopolymer length regulation is a complex process that involves a large number of biological, chemical, and physical subprocesses acting simultaneously across multiple spatial and temporal scales. An illustrative example important for genomic stability is the length regulation of telomeres - nucleoprotein structures at the ends of linear chromosomes consisting of tandemly repeated DNA sequences and a specialized set of proteins. Maintenance of telomeres is often facilitated by the enzyme telomerase but, particularly in telomerase-free systems, the maintenance of chromosomal termini depends on alternative lengthening of telomeres (ALT) mechanisms mediated by recombination. Various linear and circular DNA structures were identified to participate in ALT, however, dynamics of the whole process is still poorly understood. We propose a chemical kinetics model of ALT with kinetic rates systematically derived from the biophysics of DNA diffusion and looping. The reaction system is reduced to a coagulation-fragmentation system by quasi-steady-state approximation. The detailed treatment of kinetic rates yields explicit formulas for expected size distributions of telomeres that demonstrate the key role played by the J factor, a quantitative measure of bending of polymers. The results are in agreement with experimental data and point out interesting phenomena: an appearance of very long telomeric circles if the total telomere density exceeds a critical value (excess mass) and a nonlinear response of the telomere size distributions to the amount of telomeric DNA in the system. The results can be of general importance for understanding dynamics of telomeres in telomerase-independent systems as this mode of telomere maintenance is similar to the situation in tumor cells lacking telomerase activity. Furthermore, due to its universality, the model may also serve as a prototype of an interaction between linear and circular DNA structures in various settings."}]},{"scopus_import":1,"main_file_link":[{"url":"http://arxiv.org/abs/1307.0737","open_access":"1"}],"volume":196,"date_updated":"2021-01-12T06:53:59Z","project":[{"call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","page":"1167 - 1183","date_created":"2018-12-11T11:54:39Z","year":"2014","author":[{"id":"2D0CE020-F248-11E8-B48F-1D18A9856A87","last_name":"Weissman","first_name":"Daniel","full_name":"Weissman, Daniel"},{"full_name":"Hallatschek, Oskar","first_name":"Oskar","last_name":"Hallatschek"}],"publist_id":"5187","issue":"4","publication":"Genetics","date_published":"2014-04-01T00:00:00Z","oa_version":"Submitted Version","type":"journal_article","language":[{"iso":"eng"}],"publisher":"Genetics Society of America","doi":"10.1534/genetics.113.160705","citation":{"short":"D. Weissman, O. Hallatschek, Genetics 196 (2014) 1167–1183.","ama":"Weissman D, Hallatschek O. The rate of adaptation in large sexual populations with linear chromosomes. <i>Genetics</i>. 2014;196(4):1167-1183. doi:<a href=\"https://doi.org/10.1534/genetics.113.160705\">10.1534/genetics.113.160705</a>","ista":"Weissman D, Hallatschek O. 2014. The rate of adaptation in large sexual populations with linear chromosomes. Genetics. 196(4), 1167–1183.","apa":"Weissman, D., &#38; Hallatschek, O. (2014). The rate of adaptation in large sexual populations with linear chromosomes. <i>Genetics</i>. Genetics Society of America. <a href=\"https://doi.org/10.1534/genetics.113.160705\">https://doi.org/10.1534/genetics.113.160705</a>","chicago":"Weissman, Daniel, and Oskar Hallatschek. “The Rate of Adaptation in Large Sexual Populations with Linear Chromosomes.” <i>Genetics</i>. Genetics Society of America, 2014. <a href=\"https://doi.org/10.1534/genetics.113.160705\">https://doi.org/10.1534/genetics.113.160705</a>.","ieee":"D. Weissman and O. Hallatschek, “The rate of adaptation in large sexual populations with linear chromosomes,” <i>Genetics</i>, vol. 196, no. 4. Genetics Society of America, pp. 1167–1183, 2014.","mla":"Weissman, Daniel, and Oskar Hallatschek. “The Rate of Adaptation in Large Sexual Populations with Linear Chromosomes.” <i>Genetics</i>, vol. 196, no. 4, Genetics Society of America, 2014, pp. 1167–83, doi:<a href=\"https://doi.org/10.1534/genetics.113.160705\">10.1534/genetics.113.160705</a>."},"intvolume":"       196","day":"01","abstract":[{"lang":"eng","text":"In large populations, multiple beneficial mutations may be simultaneously spreading. In asexual populations, these mutations must either arise on the same background or compete against each other. In sexual populations, recombination can bring together beneficial alleles from different backgrounds, but tightly linked alleles may still greatly interfere with each other. We show for well-mixed populations that when this interference is strong, the genome can be seen as consisting of many effectively asexual stretches linked together. The rate at which beneficial alleles fix is thus roughly proportional to the rate of recombination and depends only logarithmically on the mutation supply and the strength of selection. Our scaling arguments also allow us to predict, with reasonable accuracy, the fitness distribution of fixed mutations when the mutational effect sizes are broad. We focus on the regime in which crossovers occur more frequently than beneficial mutations, as is likely to be the case for many natural populations."}],"status":"public","ec_funded":1,"department":[{"_id":"NiBa"}],"title":"The rate of adaptation in large sexual populations with linear chromosomes","oa":1,"publication_status":"published","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","month":"04","_id":"1908"},{"citation":{"ama":"Ezard T, Prizak R, Hoyle R. The fitness costs of adaptation via phenotypic plasticity and maternal effects. <i>Functional Ecology</i>. 2014;28(3):693-701. doi:<a href=\"https://doi.org/10.1111/1365-2435.12207\">10.1111/1365-2435.12207</a>","short":"T. Ezard, R. Prizak, R. Hoyle, Functional Ecology 28 (2014) 693–701.","mla":"Ezard, Thomas, et al. “The Fitness Costs of Adaptation via Phenotypic Plasticity and Maternal Effects.” <i>Functional Ecology</i>, vol. 28, no. 3, Wiley-Blackwell, 2014, pp. 693–701, doi:<a href=\"https://doi.org/10.1111/1365-2435.12207\">10.1111/1365-2435.12207</a>.","ieee":"T. Ezard, R. Prizak, and R. Hoyle, “The fitness costs of adaptation via phenotypic plasticity and maternal effects,” <i>Functional Ecology</i>, vol. 28, no. 3. Wiley-Blackwell, pp. 693–701, 2014.","ista":"Ezard T, Prizak R, Hoyle R. 2014. The fitness costs of adaptation via phenotypic plasticity and maternal effects. Functional Ecology. 28(3), 693–701.","apa":"Ezard, T., Prizak, R., &#38; Hoyle, R. (2014). The fitness costs of adaptation via phenotypic plasticity and maternal effects. <i>Functional Ecology</i>. Wiley-Blackwell. <a href=\"https://doi.org/10.1111/1365-2435.12207\">https://doi.org/10.1111/1365-2435.12207</a>","chicago":"Ezard, Thomas, Roshan Prizak, and Rebecca Hoyle. “The Fitness Costs of Adaptation via Phenotypic Plasticity and Maternal Effects.” <i>Functional Ecology</i>. Wiley-Blackwell, 2014. <a href=\"https://doi.org/10.1111/1365-2435.12207\">https://doi.org/10.1111/1365-2435.12207</a>."},"intvolume":"        28","day":"01","has_accepted_license":"1","status":"public","abstract":[{"lang":"eng","text":"Summary: Phenotypes are often environmentally dependent, which requires organisms to track environmental change. The challenge for organisms is to construct phenotypes using the most accurate environmental cue. Here, we use a quantitative genetic model of adaptation by additive genetic variance, within- and transgenerational plasticity via linear reaction norms and indirect genetic effects respectively. We show how the relative influence on the eventual phenotype of these components depends on the predictability of environmental change (fast or slow, sinusoidal or stochastic) and the developmental lag τ between when the environment is perceived and when selection acts. We then decompose expected mean fitness into three components (variance load, adaptation and fluctuation load) to study the fitness costs of within- and transgenerational plasticity. A strongly negative maternal effect coefficient m minimizes the variance load, but a strongly positive m minimises the fluctuation load. The adaptation term is maximized closer to zero, with positive or negative m preferred under different environmental scenarios. Phenotypic plasticity is higher when τ is shorter and when the environment changes frequently between seasonal extremes. Expected mean population fitness is highest away from highest observed levels of phenotypic plasticity. Within- and transgenerational plasticity act in concert to deliver well-adapted phenotypes, which emphasizes the need to study both simultaneously when investigating phenotypic evolution."}],"pubrep_id":"419","department":[{"_id":"NiBa"},{"_id":"GaTk"}],"acknowledgement":"Engineering and Physical Sciences Research Council. Grant Number: EP/H031928/1","title":"The fitness costs of adaptation via phenotypic plasticity and maternal effects","oa":1,"publication_status":"published","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","_id":"1909","month":"06","scopus_import":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"volume":28,"file":[{"file_name":"IST-2016-419-v1+1_Ezard_et_al-2014-Functional_Ecology.pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:20Z","content_type":"application/pdf","date_created":"2018-12-12T10:15:45Z","file_id":"5167","checksum":"3cbe8623174709a8ceec2103246f8fe0","relation":"main_file","creator":"system","file_size":536154}],"page":"693 - 701","year":"2014","date_created":"2018-12-11T11:54:40Z","date_updated":"2021-01-12T06:54:00Z","publication":"Functional Ecology","publist_id":"5186","issue":"3","ddc":["570"],"author":[{"last_name":"Ezard","first_name":"Thomas","full_name":"Ezard, Thomas"},{"last_name":"Prizak","full_name":"Prizak, Roshan","first_name":"Roshan","id":"4456104E-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Hoyle, Rebecca","first_name":"Rebecca","last_name":"Hoyle"}],"oa_version":"Published Version","date_published":"2014-06-01T00:00:00Z","language":[{"iso":"eng"}],"file_date_updated":"2020-07-14T12:45:20Z","type":"journal_article","doi":"10.1111/1365-2435.12207","publisher":"Wiley-Blackwell"},{"intvolume":"        68","citation":{"short":"M. Trotter, D. Weissman, G. Peterson, K. Peck, J. Masel, Evolution 68 (2014) 3357–3367.","ama":"Trotter M, Weissman D, Peterson G, Peck K, Masel J. Cryptic genetic variation can make &#38;quot;irreducible complexity&#38;quot; a common mode of adaptation in sexual populations. <i>Evolution</i>. 2014;68(12):3357-3367. doi:<a href=\"https://doi.org/10.1111/evo.12517\">10.1111/evo.12517</a>","apa":"Trotter, M., Weissman, D., Peterson, G., Peck, K., &#38; Masel, J. (2014). Cryptic genetic variation can make &#38;quot;irreducible complexity&#38;quot; a common mode of adaptation in sexual populations. <i>Evolution</i>. Wiley-Blackwell. <a href=\"https://doi.org/10.1111/evo.12517\">https://doi.org/10.1111/evo.12517</a>","ista":"Trotter M, Weissman D, Peterson G, Peck K, Masel J. 2014. Cryptic genetic variation can make &#38;quot;irreducible complexity&#38;quot; a common mode of adaptation in sexual populations. Evolution. 68(12), 3357–3367.","chicago":"Trotter, Meredith, Daniel Weissman, Grant Peterson, Kayla Peck, and Joanna Masel. “Cryptic Genetic Variation Can Make &#38;quot;Irreducible Complexity&#38;quot; a Common Mode of Adaptation in Sexual Populations.” <i>Evolution</i>. Wiley-Blackwell, 2014. <a href=\"https://doi.org/10.1111/evo.12517\">https://doi.org/10.1111/evo.12517</a>.","mla":"Trotter, Meredith, et al. “Cryptic Genetic Variation Can Make &#38;quot;Irreducible Complexity&#38;quot; a Common Mode of Adaptation in Sexual Populations.” <i>Evolution</i>, vol. 68, no. 12, Wiley-Blackwell, 2014, pp. 3357–67, doi:<a href=\"https://doi.org/10.1111/evo.12517\">10.1111/evo.12517</a>.","ieee":"M. Trotter, D. Weissman, G. Peterson, K. Peck, and J. Masel, “Cryptic genetic variation can make &#38;quot;irreducible complexity&#38;quot; a common mode of adaptation in sexual populations,” <i>Evolution</i>, vol. 68, no. 12. Wiley-Blackwell, pp. 3357–3367, 2014."},"day":"01","abstract":[{"lang":"eng","text":"The existence of complex (multiple-step) genetic adaptations that are &quot;irreducible&quot; (i.e., all partial combinations are less fit than the original genotype) is one of the longest standing problems in evolutionary biology. In standard genetics parlance, these adaptations require the crossing of a wide adaptive valley of deleterious intermediate stages. Here, we demonstrate, using a simple model, that evolution can cross wide valleys to produce &quot;irreducibly complex&quot; adaptations by making use of previously cryptic mutations. When revealed by an evolutionary capacitor, previously cryptic mutants have higher initial frequencies than do new mutations, bringing them closer to a valley-crossing saddle in allele frequency space. Moreover, simple combinatorics implies an enormous number of candidate combinations exist within available cryptic genetic variation. We model the dynamics of crossing of a wide adaptive valley after a capacitance event using both numerical simulations and analytical approximations. Although individual valley crossing events become less likely as valleys widen, by taking the combinatorics of genotype space into account, we see that revealing cryptic variation can cause the frequent evolution of complex adaptations."}],"status":"public","ec_funded":1,"acknowledgement":"Funded by National Institutes of Health. Grant Numbers: R01GM076041, R01GM104040         \r\n\r\nSimons Foundation\r\n\r\n","department":[{"_id":"NiBa"}],"publication_status":"published","oa":1,"title":"Cryptic genetic variation can make &quot;irreducible complexity&quot; a common mode of adaptation in sexual populations","month":"12","_id":"1932","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","main_file_link":[{"url":"http://arxiv.org/abs/1310.6077","open_access":"1"}],"scopus_import":1,"volume":68,"project":[{"name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"date_updated":"2021-01-12T06:54:10Z","date_created":"2018-12-11T11:54:47Z","year":"2014","page":"3357 - 3367","quality_controlled":"1","author":[{"last_name":"Trotter","full_name":"Trotter, Meredith","first_name":"Meredith"},{"first_name":"Daniel","full_name":"Weissman, Daniel","last_name":"Weissman","id":"2D0CE020-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Peterson, Grant","first_name":"Grant","last_name":"Peterson"},{"first_name":"Kayla","full_name":"Peck, Kayla","last_name":"Peck"},{"first_name":"Joanna","full_name":"Masel, Joanna","last_name":"Masel"}],"publication":"Evolution","publist_id":"5162","issue":"12","date_published":"2014-12-01T00:00:00Z","oa_version":"Submitted Version","type":"journal_article","language":[{"iso":"eng"}],"publisher":"Wiley-Blackwell","doi":"10.1111/evo.12517"},{"oa_version":"Submitted Version","date_published":"2014-02-13T00:00:00Z","publication":"Behavioral Ecology","publist_id":"5157","issue":"3","author":[{"full_name":"Arbilly, Michal","first_name":"Michal","last_name":"Arbilly"},{"full_name":"Weissman, Daniel","first_name":"Daniel","last_name":"Weissman","id":"2D0CE020-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Feldman","first_name":"Marcus","full_name":"Feldman, Marcus"},{"full_name":"Grodzinski, Uri","first_name":"Uri","last_name":"Grodzinski"}],"doi":"10.1093/beheco/aru002","publisher":"Oxford University Press","language":[{"iso":"eng"}],"type":"journal_article","scopus_import":1,"main_file_link":[{"open_access":"1","url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4014306/"}],"quality_controlled":"1","page":"487 - 495","year":"2014","date_created":"2018-12-11T11:54:48Z","date_updated":"2021-01-12T06:54:11Z","project":[{"grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"volume":25,"department":[{"_id":"NiBa"}],"user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","month":"02","_id":"1936","title":"An arms race between producers and scroungers can drive the evolution of social cognition","oa":1,"publication_status":"published","day":"13","citation":{"ista":"Arbilly M, Weissman D, Feldman M, Grodzinski U. 2014. An arms race between producers and scroungers can drive the evolution of social cognition. Behavioral Ecology. 25(3), 487–495.","apa":"Arbilly, M., Weissman, D., Feldman, M., &#38; Grodzinski, U. (2014). An arms race between producers and scroungers can drive the evolution of social cognition. <i>Behavioral Ecology</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/beheco/aru002\">https://doi.org/10.1093/beheco/aru002</a>","chicago":"Arbilly, Michal, Daniel Weissman, Marcus Feldman, and Uri Grodzinski. “An Arms Race between Producers and Scroungers Can Drive the Evolution of Social Cognition.” <i>Behavioral Ecology</i>. Oxford University Press, 2014. <a href=\"https://doi.org/10.1093/beheco/aru002\">https://doi.org/10.1093/beheco/aru002</a>.","mla":"Arbilly, Michal, et al. “An Arms Race between Producers and Scroungers Can Drive the Evolution of Social Cognition.” <i>Behavioral Ecology</i>, vol. 25, no. 3, Oxford University Press, 2014, pp. 487–95, doi:<a href=\"https://doi.org/10.1093/beheco/aru002\">10.1093/beheco/aru002</a>.","ieee":"M. Arbilly, D. Weissman, M. Feldman, and U. Grodzinski, “An arms race between producers and scroungers can drive the evolution of social cognition,” <i>Behavioral Ecology</i>, vol. 25, no. 3. Oxford University Press, pp. 487–495, 2014.","short":"M. Arbilly, D. Weissman, M. Feldman, U. Grodzinski, Behavioral Ecology 25 (2014) 487–495.","ama":"Arbilly M, Weissman D, Feldman M, Grodzinski U. An arms race between producers and scroungers can drive the evolution of social cognition. <i>Behavioral Ecology</i>. 2014;25(3):487-495. doi:<a href=\"https://doi.org/10.1093/beheco/aru002\">10.1093/beheco/aru002</a>"},"intvolume":"        25","ec_funded":1,"status":"public","abstract":[{"lang":"eng","text":"The social intelligence hypothesis states that the need to cope with complexities of social life has driven the evolution of advanced cognitive abilities. It is usually invoked in the context of challenges arising from complex intragroup structures, hierarchies, and alliances. However, a fundamental aspect of group living remains largely unexplored as a driving force in cognitive evolution: the competition between individuals searching for resources (producers) and conspecifics that parasitize their findings (scroungers). In populations of social foragers, abilities that enable scroungers to steal by outsmarting producers, and those allowing producers to prevent theft by outsmarting scroungers, are likely to be beneficial and may fuel a cognitive arms race. Using analytical theory and agent-based simulations, we present a general model for such a race that is driven by the producer-scrounger game and show that the race's plausibility is dramatically affected by the nature of the evolving abilities. If scrounging and scrounging avoidance rely on separate, strategy-specific cognitive abilities, arms races are short-lived and have a limited effect on cognition. However, general cognitive abilities that facilitate both scrounging and scrounging avoidance undergo stable, long-lasting arms races. Thus, ubiquitous foraging interactions may lead to the evolution of general cognitive abilities in social animals, without the requirement of complex intragroup structures."}]},{"citation":{"short":"S. Novak, Ecology and Evolution 4 (2014) 4589–4597.","ama":"Novak S. Habitat heterogeneities versus spatial type frequency variances as driving forces of dispersal evolution. <i>Ecology and Evolution</i>. 2014;4(24):4589-4597. doi:<a href=\"https://doi.org/10.1002/ece3.1289\">10.1002/ece3.1289</a>","chicago":"Novak, Sebastian. “Habitat Heterogeneities versus Spatial Type Frequency Variances as Driving Forces of Dispersal Evolution.” <i>Ecology and Evolution</i>. Wiley-Blackwell, 2014. <a href=\"https://doi.org/10.1002/ece3.1289\">https://doi.org/10.1002/ece3.1289</a>.","ista":"Novak S. 2014. Habitat heterogeneities versus spatial type frequency variances as driving forces of dispersal evolution. Ecology and Evolution. 4(24), 4589–4597.","apa":"Novak, S. (2014). Habitat heterogeneities versus spatial type frequency variances as driving forces of dispersal evolution. <i>Ecology and Evolution</i>. Wiley-Blackwell. <a href=\"https://doi.org/10.1002/ece3.1289\">https://doi.org/10.1002/ece3.1289</a>","ieee":"S. Novak, “Habitat heterogeneities versus spatial type frequency variances as driving forces of dispersal evolution,” <i>Ecology and Evolution</i>, vol. 4, no. 24. Wiley-Blackwell, pp. 4589–4597, 2014.","mla":"Novak, Sebastian. “Habitat Heterogeneities versus Spatial Type Frequency Variances as Driving Forces of Dispersal Evolution.” <i>Ecology and Evolution</i>, vol. 4, no. 24, Wiley-Blackwell, 2014, pp. 4589–97, doi:<a href=\"https://doi.org/10.1002/ece3.1289\">10.1002/ece3.1289</a>."},"intvolume":"         4","day":"27","has_accepted_license":"1","status":"public","abstract":[{"text":"Understanding the evolution of dispersal is essential for understanding and predicting the dynamics of natural populations. Two main factors are known to influence dispersal evolution: spatio-temporal variation in the environment and relatedness between individuals. However, the relation between these factors is still poorly understood, and they are usually treated separately. In this article, I present a theoretical framework that contains and connects effects of both environmental variation and relatedness, and reproduces and extends their known features. Spatial habitat variation selects for balanced dispersal strategies, whereby the population is kept at an ideal free distribution. Within this class of dispersal strategies, I explain how increased dispersal is promoted by perturbations to the dispersal type frequencies. An explicit formula shows the magnitude of the selective advantage of increased dispersal in terms of the spatial variability in the frequencies of the different dispersal strategies present. These variances are capable of capturing various sources of stochasticity and hence establish a common scale for their effects on the evolution of dispersal. The results furthermore indicate an alternative approach to identifying effects of relatedness on dispersal evolution.","lang":"eng"}],"ec_funded":1,"pubrep_id":"462","department":[{"_id":"NiBa"}],"title":"Habitat heterogeneities versus spatial type frequency variances as driving forces of dispersal evolution","oa":1,"related_material":{"record":[{"id":"1125","relation":"dissertation_contains","status":"public"}]},"publication_status":"published","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","_id":"2023","month":"11","scopus_import":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"volume":4,"file":[{"file_id":"4946","date_created":"2018-12-12T10:12:28Z","content_type":"application/pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:25Z","file_name":"IST-2016-462-v1+1_Novak-2014-Ecology_and_Evolution.pdf","file_size":118813,"creator":"system","relation":"main_file","checksum":"9ab43db1b0fede7bfe560ed77e177b76"}],"quality_controlled":"1","page":"4589 - 4597","year":"2014","date_created":"2018-12-11T11:55:16Z","date_updated":"2023-09-07T11:55:53Z","project":[{"grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"publication":"Ecology and Evolution","issue":"24","publist_id":"5049","ddc":["570"],"author":[{"id":"461468AE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-824X","last_name":"Novak","full_name":"Novak, Sebastian","first_name":"Sebastian"}],"oa_version":"Published Version","date_published":"2014-11-27T00:00:00Z","language":[{"iso":"eng"}],"file_date_updated":"2020-07-14T12:45:25Z","type":"journal_article","doi":"10.1002/ece3.1289","publisher":"Wiley-Blackwell"},{"scopus_import":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"file":[{"file_size":569005,"creator":"system","relation":"main_file","checksum":"979d7a8034e9df198f068f0d251f31bd","date_created":"2018-12-12T10:10:49Z","file_id":"4839","content_type":"application/pdf","date_updated":"2020-07-14T12:45:31Z","access_level":"open_access","file_name":"IST-2015-391-v1+1_1-s2.0-S0040580914000355-main.pdf"}],"volume":95,"year":"2014","date_created":"2018-12-11T11:56:06Z","page":"13 - 23","quality_controlled":"1","project":[{"grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"date_updated":"2021-01-12T06:55:44Z","publist_id":"4816","publication":"Theoretical Population Biology","author":[{"first_name":"Jerome","full_name":"Kelleher, Jerome","last_name":"Kelleher"},{"last_name":"Etheridge","first_name":"Alison","full_name":"Etheridge, Alison"},{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","last_name":"Barton","full_name":"Barton, Nicholas H","first_name":"Nicholas H"}],"ddc":["570"],"oa_version":"Published Version","date_published":"2014-08-01T00:00:00Z","language":[{"iso":"eng"}],"type":"journal_article","file_date_updated":"2020-07-14T12:45:31Z","doi":"10.1016/j.tpb.2014.05.001","publisher":"Academic Press","citation":{"chicago":"Kelleher, Jerome, Alison Etheridge, and Nicholas H Barton. “Coalescent Simulation in Continuous Space: Algorithms for Large Neighbourhood Size.” <i>Theoretical Population Biology</i>. Academic Press, 2014. <a href=\"https://doi.org/10.1016/j.tpb.2014.05.001\">https://doi.org/10.1016/j.tpb.2014.05.001</a>.","apa":"Kelleher, J., Etheridge, A., &#38; Barton, N. H. (2014). Coalescent simulation in continuous space: Algorithms for large neighbourhood size. <i>Theoretical Population Biology</i>. Academic Press. <a href=\"https://doi.org/10.1016/j.tpb.2014.05.001\">https://doi.org/10.1016/j.tpb.2014.05.001</a>","ista":"Kelleher J, Etheridge A, Barton NH. 2014. Coalescent simulation in continuous space: Algorithms for large neighbourhood size. Theoretical Population Biology. 95, 13–23.","ieee":"J. Kelleher, A. Etheridge, and N. H. Barton, “Coalescent simulation in continuous space: Algorithms for large neighbourhood size,” <i>Theoretical Population Biology</i>, vol. 95. Academic Press, pp. 13–23, 2014.","mla":"Kelleher, Jerome, et al. “Coalescent Simulation in Continuous Space: Algorithms for Large Neighbourhood Size.” <i>Theoretical Population Biology</i>, vol. 95, Academic Press, 2014, pp. 13–23, doi:<a href=\"https://doi.org/10.1016/j.tpb.2014.05.001\">10.1016/j.tpb.2014.05.001</a>.","short":"J. Kelleher, A. Etheridge, N.H. Barton, Theoretical Population Biology 95 (2014) 13–23.","ama":"Kelleher J, Etheridge A, Barton NH. Coalescent simulation in continuous space: Algorithms for large neighbourhood size. <i>Theoretical Population Biology</i>. 2014;95:13-23. doi:<a href=\"https://doi.org/10.1016/j.tpb.2014.05.001\">10.1016/j.tpb.2014.05.001</a>"},"intvolume":"        95","day":"01","has_accepted_license":"1","status":"public","abstract":[{"lang":"eng","text":"Many species have an essentially continuous distribution in space, in which there are no natural divisions between randomly mating subpopulations. Yet, the standard approach to modelling these populations is to impose an arbitrary grid of demes, adjusting deme sizes and migration rates in an attempt to capture the important features of the population. Such indirect methods are required because of the failure of the classical models of isolation by distance, which have been shown to have major technical flaws. A recently introduced model of extinction and recolonisation in two dimensions solves these technical problems, and provides a rigorous technical foundation for the study of populations evolving in a spatial continuum. The coalescent process for this model is simply stated, but direct simulation is very inefficient for large neighbourhood sizes. We present efficient and exact algorithms to simulate this coalescent process for arbitrary sample sizes and numbers of loci, and analyse these algorithms in detail."}],"ec_funded":1,"pubrep_id":"391","department":[{"_id":"NiBa"}],"publication_status":"published","oa":1,"title":"Coalescent simulation in continuous space: Algorithms for large neighbourhood size","month":"08","_id":"2168","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87"},{"publisher":"National Academy of Sciences","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","month":"07","_id":"2169","doi":"10.1073/pnas.1410107111","type":"journal_article","oa":1,"title":"Diverse forms of selection in evolution and computer science","publication_status":"published","language":[{"iso":"eng"}],"date_published":"2014-07-22T00:00:00Z","department":[{"_id":"NiBa"}],"oa_version":"Submitted Version","author":[{"orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","first_name":"Nicholas H","full_name":"Barton, Nicholas H"},{"last_name":"Novak","full_name":"Novak, Sebastian","first_name":"Sebastian","id":"461468AE-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Paixao","first_name":"Tiago","full_name":"Paixao, Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953"}],"publist_id":"4815","issue":"29","publication":"PNAS","date_updated":"2021-01-12T06:55:45Z","page":"10398 - 10399","quality_controlled":"1","date_created":"2018-12-11T11:56:07Z","year":"2014","volume":111,"status":"public","day":"22","scopus_import":1,"main_file_link":[{"open_access":"1","url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4115508/"}],"intvolume":"       111","citation":{"ista":"Barton NH, Novak S, Paixao T. 2014. Diverse forms of selection in evolution and computer science. PNAS. 111(29), 10398–10399.","apa":"Barton, N. H., Novak, S., &#38; Paixao, T. (2014). Diverse forms of selection in evolution and computer science. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1410107111\">https://doi.org/10.1073/pnas.1410107111</a>","chicago":"Barton, Nicholas H, Sebastian Novak, and Tiago Paixao. “Diverse Forms of Selection in Evolution and Computer Science.” <i>PNAS</i>. National Academy of Sciences, 2014. <a href=\"https://doi.org/10.1073/pnas.1410107111\">https://doi.org/10.1073/pnas.1410107111</a>.","mla":"Barton, Nicholas H., et al. “Diverse Forms of Selection in Evolution and Computer Science.” <i>PNAS</i>, vol. 111, no. 29, National Academy of Sciences, 2014, pp. 10398–99, doi:<a href=\"https://doi.org/10.1073/pnas.1410107111\">10.1073/pnas.1410107111</a>.","ieee":"N. H. Barton, S. Novak, and T. Paixao, “Diverse forms of selection in evolution and computer science,” <i>PNAS</i>, vol. 111, no. 29. National Academy of Sciences, pp. 10398–10399, 2014.","short":"N.H. Barton, S. Novak, T. Paixao, PNAS 111 (2014) 10398–10399.","ama":"Barton NH, Novak S, Paixao T. Diverse forms of selection in evolution and computer science. <i>PNAS</i>. 2014;111(29):10398-10399. doi:<a href=\"https://doi.org/10.1073/pnas.1410107111\">10.1073/pnas.1410107111</a>"}},{"oa_version":"Submitted Version","date_published":"2014-01-01T00:00:00Z","publist_id":"4814","publication":"Molecular Ecology","issue":"1","author":[{"full_name":"Hearn, Jack","first_name":"Jack","last_name":"Hearn"},{"first_name":"Graham","full_name":"Stone, Graham","last_name":"Stone"},{"full_name":"Bunnefeld, Lynsey","first_name":"Lynsey","last_name":"Bunnefeld"},{"last_name":"Nicholls","first_name":"James","full_name":"Nicholls, James"},{"orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","first_name":"Nicholas H","full_name":"Barton, Nicholas H"},{"first_name":"Konrad","full_name":"Lohse, Konrad","last_name":"Lohse"}],"ddc":["570"],"doi":"10.1111/mec.12578","publisher":"Wiley-Blackwell","language":[{"iso":"eng"}],"type":"journal_article","file_date_updated":"2020-07-14T12:45:31Z","scopus_import":1,"year":"2014","date_created":"2018-12-11T11:56:07Z","quality_controlled":"1","page":"198 - 211","date_updated":"2023-02-23T14:07:09Z","file":[{"file_name":"IST-2016-559-v1+1_Hearn_et_al.pdf","file_id":"4651","date_created":"2018-12-12T10:07:52Z","content_type":"application/pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:31Z","relation":"main_file","checksum":"4de1ab255976a8ae77eb0e55ad62ecc9","file_size":807444,"creator":"system"},{"checksum":"01a8073e071c088500425f910b0f1f71","relation":"main_file","creator":"system","file_size":1518088,"file_name":"IST-2016-559-v1+2_Hearn_et_al_Suppl.pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:31Z","file_id":"4652","date_created":"2018-12-12T10:07:53Z","content_type":"application/pdf"}],"volume":23,"acknowledgement":"This work was funded by NERC grants to G Stone, J Nicholls, K Lohse and N Barton (NE/J010499, NBAF375, NE/E014453/1 and NER/B/S2003/00856).","department":[{"_id":"NiBa"}],"pubrep_id":"559","month":"01","_id":"2170","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","publication_status":"published","oa":1,"title":"Likelihood-based inference of population history from low-coverage de novo genome assemblies","related_material":{"record":[{"status":"public","relation":"research_data","id":"9754"}]},"day":"01","has_accepted_license":"1","citation":{"short":"J. Hearn, G. Stone, L. Bunnefeld, J. Nicholls, N.H. Barton, K. Lohse, Molecular Ecology 23 (2014) 198–211.","ama":"Hearn J, Stone G, Bunnefeld L, Nicholls J, Barton NH, Lohse K. Likelihood-based inference of population history from low-coverage de novo genome assemblies. <i>Molecular Ecology</i>. 2014;23(1):198-211. doi:<a href=\"https://doi.org/10.1111/mec.12578\">10.1111/mec.12578</a>","apa":"Hearn, J., Stone, G., Bunnefeld, L., Nicholls, J., Barton, N. H., &#38; Lohse, K. (2014). Likelihood-based inference of population history from low-coverage de novo genome assemblies. <i>Molecular Ecology</i>. Wiley-Blackwell. <a href=\"https://doi.org/10.1111/mec.12578\">https://doi.org/10.1111/mec.12578</a>","chicago":"Hearn, Jack, Graham Stone, Lynsey Bunnefeld, James Nicholls, Nicholas H Barton, and Konrad Lohse. “Likelihood-Based Inference of Population History from Low-Coverage de Novo Genome Assemblies.” <i>Molecular Ecology</i>. Wiley-Blackwell, 2014. <a href=\"https://doi.org/10.1111/mec.12578\">https://doi.org/10.1111/mec.12578</a>.","ista":"Hearn J, Stone G, Bunnefeld L, Nicholls J, Barton NH, Lohse K. 2014. Likelihood-based inference of population history from low-coverage de novo genome assemblies. Molecular Ecology. 23(1), 198–211.","mla":"Hearn, Jack, et al. “Likelihood-Based Inference of Population History from Low-Coverage de Novo Genome Assemblies.” <i>Molecular Ecology</i>, vol. 23, no. 1, Wiley-Blackwell, 2014, pp. 198–211, doi:<a href=\"https://doi.org/10.1111/mec.12578\">10.1111/mec.12578</a>.","ieee":"J. Hearn, G. Stone, L. Bunnefeld, J. Nicholls, N. H. Barton, and K. Lohse, “Likelihood-based inference of population history from low-coverage de novo genome assemblies,” <i>Molecular Ecology</i>, vol. 23, no. 1. Wiley-Blackwell, pp. 198–211, 2014."},"intvolume":"        23","status":"public","abstract":[{"text":" Short-read sequencing technologies have in principle made it feasible to draw detailed inferences about the recent history of any organism. In practice, however, this remains challenging due to the difficulty of genome assembly in most organisms and the lack of statistical methods powerful enough to discriminate between recent, nonequilibrium histories. We address both the assembly and inference challenges. We develop a bioinformatic pipeline for generating outgroup-rooted alignments of orthologous sequence blocks from de novo low-coverage short-read data for a small number of genomes, and show how such sequence blocks can be used to fit explicit models of population divergence and admixture in a likelihood framework. To illustrate our approach, we reconstruct the Pleistocene history of an oak-feeding insect (the oak gallwasp Biorhiza pallida), which, in common with many other taxa, was restricted during Pleistocene ice ages to a longitudinal series of southern refugia spanning the Western Palaearctic. Our analysis of sequence blocks sampled from a single genome from each of three major glacial refugia reveals support for an unexpected history dominated by recent admixture. Despite the fact that 80% of the genome is affected by admixture during the last glacial cycle, we are able to infer the deeper divergence history of these populations. These inferences are robust to variation in block length, mutation model and the sampling location of individual genomes within refugia. This combination of de novo assembly and numerical likelihood calculation provides a powerful framework for estimating recent population history that can be applied to any organism without the need for prior genetic resources.","lang":"eng"}]},{"scopus_import":1,"main_file_link":[{"url":"http://arxiv.org/abs/1404.1017","open_access":"1"}],"date_updated":"2021-01-12T06:55:47Z","project":[{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation"}],"page":"749 - 767","quality_controlled":"1","date_created":"2018-12-11T11:56:08Z","year":"2014","volume":197,"date_published":"2014-06-01T00:00:00Z","oa_version":"Submitted Version","author":[{"first_name":"Harold","full_name":"De Vladar, Harold","last_name":"De Vladar"},{"full_name":"Barton, Nicholas H","first_name":"Nicholas H","last_name":"Barton","orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"}],"issue":"2","publist_id":"4809","publication":"Genetics","publisher":"Genetics Society of America","doi":"10.1534/genetics.113.159111","type":"journal_article","language":[{"iso":"eng"}],"day":"01","intvolume":"       197","citation":{"ama":"De Vladar H, Barton NH. Stability and response of polygenic traits to stabilizing selection and mutation. <i>Genetics</i>. 2014;197(2):749-767. doi:<a href=\"https://doi.org/10.1534/genetics.113.159111\">10.1534/genetics.113.159111</a>","short":"H. De Vladar, N.H. Barton, Genetics 197 (2014) 749–767.","ieee":"H. De Vladar and N. H. Barton, “Stability and response of polygenic traits to stabilizing selection and mutation,” <i>Genetics</i>, vol. 197, no. 2. Genetics Society of America, pp. 749–767, 2014.","mla":"De Vladar, Harold, and Nicholas H. Barton. “Stability and Response of Polygenic Traits to Stabilizing Selection and Mutation.” <i>Genetics</i>, vol. 197, no. 2, Genetics Society of America, 2014, pp. 749–67, doi:<a href=\"https://doi.org/10.1534/genetics.113.159111\">10.1534/genetics.113.159111</a>.","chicago":"De Vladar, Harold, and Nicholas H Barton. “Stability and Response of Polygenic Traits to Stabilizing Selection and Mutation.” <i>Genetics</i>. Genetics Society of America, 2014. <a href=\"https://doi.org/10.1534/genetics.113.159111\">https://doi.org/10.1534/genetics.113.159111</a>.","apa":"De Vladar, H., &#38; Barton, N. H. (2014). Stability and response of polygenic traits to stabilizing selection and mutation. <i>Genetics</i>. Genetics Society of America. <a href=\"https://doi.org/10.1534/genetics.113.159111\">https://doi.org/10.1534/genetics.113.159111</a>","ista":"De Vladar H, Barton NH. 2014. Stability and response of polygenic traits to stabilizing selection and mutation. Genetics. 197(2), 749–767."},"ec_funded":1,"abstract":[{"text":"When polygenic traits are under stabilizing selection, many different combinations of alleles allow close adaptation to the optimum. If alleles have equal effects, all combinations that result in the same deviation from the optimum are equivalent. Furthermore, the genetic variance that is maintained by mutation-selection balance is 2μ/S per locus, where μ is the mutation rate and S the strength of stabilizing selection. In reality, alleles vary in their effects, making the fitness landscape asymmetric and complicating analysis of the equilibria. We show that that the resulting genetic variance depends on the fraction of alleles near fixation, which contribute by 2μ/S, and on the total mutational effects of alleles that are at intermediate frequency. The inpplayfi between stabilizing selection and mutation leads to a sharp transition: alleles with effects smaller than a threshold value of 2 remain polymorphic, whereas those with larger effects are fixed. The genetic load in equilibrium is less than for traits of equal effects, and the fitness equilibria are more similar. We find p the optimum is displaced, alleles with effects close to the threshold value sweep first, and their rate of increase is bounded by Long-term response leads in general to well-adapted traits, unlike the case of equal effects that often end up at a suboptimal fitness peak. However, the particular peaks to which the populations converge are extremely sensitive to the initial states and to the speed of the shift of the optimum trait value.","lang":"eng"}],"status":"public","department":[{"_id":"NiBa"}],"user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","_id":"2174","month":"06","title":"Stability and response of polygenic traits to stabilizing selection and mutation","oa":1,"publication_status":"published"},{"department":[{"_id":"NiBa"}],"date_published":"2014-01-01T00:00:00Z","oa_version":"None","author":[{"full_name":"Phadke, Sujal","first_name":"Sujal","last_name":"Phadke"},{"id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago","first_name":"Tiago","last_name":"Paixao"},{"last_name":"Pham","full_name":"Pham, Tuan","first_name":"Tuan"},{"last_name":"Pham","full_name":"Pham, Stephanie","first_name":"Stephanie"},{"last_name":"Zufall","first_name":"Rebecca","full_name":"Zufall, Rebecca"}],"publication":"Journal of Heredity","publist_id":"4695","issue":"1","publisher":"Oxford University Press","doi":"10.1093/jhered/est063","_id":"2252","month":"01","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","type":"journal_article","publication_status":"published","language":[{"iso":"eng"}],"title":"Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila","article_processing_charge":"No","day":"01","citation":{"ieee":"S. Phadke, T. Paixao, T. Pham, S. Pham, and R. Zufall, “Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila,” <i>Journal of Heredity</i>, vol. 105, no. 1. Oxford University Press, pp. 130–135, 2014.","mla":"Phadke, Sujal, et al. “Genetic Background Alters Dominance Relationships between Mat Alleles in the Ciliate Tetrahymena Thermophila.” <i>Journal of Heredity</i>, vol. 105, no. 1, Oxford University Press, 2014, pp. 130–35, doi:<a href=\"https://doi.org/10.1093/jhered/est063\">10.1093/jhered/est063</a>.","apa":"Phadke, S., Paixao, T., Pham, T., Pham, S., &#38; Zufall, R. (2014). Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila. <i>Journal of Heredity</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/jhered/est063\">https://doi.org/10.1093/jhered/est063</a>","ista":"Phadke S, Paixao T, Pham T, Pham S, Zufall R. 2014. Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila. Journal of Heredity. 105(1), 130–135.","chicago":"Phadke, Sujal, Tiago Paixao, Tuan Pham, Stephanie Pham, and Rebecca Zufall. “Genetic Background Alters Dominance Relationships between Mat Alleles in the Ciliate Tetrahymena Thermophila.” <i>Journal of Heredity</i>. Oxford University Press, 2014. <a href=\"https://doi.org/10.1093/jhered/est063\">https://doi.org/10.1093/jhered/est063</a>.","ama":"Phadke S, Paixao T, Pham T, Pham S, Zufall R. Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila. <i>Journal of Heredity</i>. 2014;105(1):130-135. doi:<a href=\"https://doi.org/10.1093/jhered/est063\">10.1093/jhered/est063</a>","short":"S. Phadke, T. Paixao, T. Pham, S. Pham, R. Zufall, Journal of Heredity 105 (2014) 130–135."},"intvolume":"       105","scopus_import":"1","publication_identifier":{"issn":["00221503"]},"date_updated":"2022-08-25T14:45:42Z","year":"2014","date_created":"2018-12-11T11:56:35Z","quality_controlled":"1","page":"130 - 135","volume":105,"abstract":[{"lang":"eng","text":"The pattern of inheritance and mechanism of sex determination can have important evolutionary consequences. We studied probabilistic sex determination in the ciliate Tetrahymena thermophila, which was previously shown to cause evolution of skewed sex ratios. We find that the genetic background alters the sex determination patterns of mat alleles in heterozygotes and that allelic interaction can differentially influence the expression probability of the 7 sexes. We quantify the dominance relationships between several mat alleles and find that A-type alleles, which specify sex I, are indeed recessive to B-type alleles, which are unable to specify that sex. Our results provide additional support for the presence of modifier loci and raise implications for the dynamics of sex ratios in populations of T. thermophila."}],"status":"public"},{"pubrep_id":"934","department":[{"_id":"NiBa"},{"_id":"GaTk"}],"publication_status":"published","title":"Fitness consequences of maternal and grandmaternal effects","oa":1,"month":"07","_id":"537","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":"         4","citation":{"chicago":"Prizak, Roshan, Thomas Ezard, and Rebecca Hoyle. “Fitness Consequences of Maternal and Grandmaternal Effects.” <i>Ecology and Evolution</i>. Wiley-Blackwell, 2014. <a href=\"https://doi.org/10.1002/ece3.1150\">https://doi.org/10.1002/ece3.1150</a>.","apa":"Prizak, R., Ezard, T., &#38; Hoyle, R. (2014). Fitness consequences of maternal and grandmaternal effects. <i>Ecology and Evolution</i>. Wiley-Blackwell. <a href=\"https://doi.org/10.1002/ece3.1150\">https://doi.org/10.1002/ece3.1150</a>","ista":"Prizak R, Ezard T, Hoyle R. 2014. Fitness consequences of maternal and grandmaternal effects. Ecology and Evolution. 4(15), 3139–3145.","ieee":"R. Prizak, T. Ezard, and R. Hoyle, “Fitness consequences of maternal and grandmaternal effects,” <i>Ecology and Evolution</i>, vol. 4, no. 15. Wiley-Blackwell, pp. 3139–3145, 2014.","mla":"Prizak, Roshan, et al. “Fitness Consequences of Maternal and Grandmaternal Effects.” <i>Ecology and Evolution</i>, vol. 4, no. 15, Wiley-Blackwell, 2014, pp. 3139–45, doi:<a href=\"https://doi.org/10.1002/ece3.1150\">10.1002/ece3.1150</a>.","short":"R. Prizak, T. Ezard, R. Hoyle, Ecology and Evolution 4 (2014) 3139–3145.","ama":"Prizak R, Ezard T, Hoyle R. Fitness consequences of maternal and grandmaternal effects. <i>Ecology and Evolution</i>. 2014;4(15):3139-3145. doi:<a href=\"https://doi.org/10.1002/ece3.1150\">10.1002/ece3.1150</a>"},"has_accepted_license":"1","day":"19","abstract":[{"text":"Transgenerational effects are broader than only parental relationships. Despite mounting evidence that multigenerational effects alter phenotypic and life-history traits, our understanding of how they combine to determine fitness is not well developed because of the added complexity necessary to study them. Here, we derive a quantitative genetic model of adaptation to an extraordinary new environment by an additive genetic component, phenotypic plasticity, maternal and grandmaternal effects. We show how, at equilibrium, negative maternal and negative grandmaternal effects maximize expected population mean fitness. We define negative transgenerational effects as those that have a negative effect on trait expression in the subsequent generation, that is, they slow, or potentially reverse, the expected evolutionary dynamic. When maternal effects are positive, negative grandmaternal effects are preferred. As expected under Mendelian inheritance, the grandmaternal effects have a lower impact on fitness than the maternal effects, but this dual inheritance model predicts a more complex relationship between maternal and grandmaternal effects to constrain phenotypic variance and so maximize expected population mean fitness in the offspring.","lang":"eng"}],"status":"public","author":[{"id":"4456104E-F248-11E8-B48F-1D18A9856A87","last_name":"Prizak","full_name":"Prizak, Roshan","first_name":"Roshan"},{"full_name":"Ezard, Thomas","first_name":"Thomas","last_name":"Ezard"},{"full_name":"Hoyle, Rebecca","first_name":"Rebecca","last_name":"Hoyle"}],"ddc":["530","571"],"publist_id":"7280","issue":"15","publication":"Ecology and Evolution","date_published":"2014-07-19T00:00:00Z","oa_version":"Published Version","type":"journal_article","file_date_updated":"2020-07-14T12:46:38Z","language":[{"iso":"eng"}],"publisher":"Wiley-Blackwell","doi":"10.1002/ece3.1150","scopus_import":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)"},"file":[{"creator":"system","file_size":621582,"checksum":"e32abf75a248e7a11811fd7f60858769","relation":"main_file","date_updated":"2020-07-14T12:46:38Z","access_level":"open_access","file_id":"4886","content_type":"application/pdf","date_created":"2018-12-12T10:11:31Z","file_name":"IST-2018-934-v1+1_Prizak_et_al-2014-Ecology_and_Evolution.pdf"}],"volume":4,"date_updated":"2021-01-12T08:01:30Z","date_created":"2018-12-11T11:47:02Z","year":"2014","page":"3139 - 3145"},{"doi":"10.5061/dryad.r3r60","_id":"9754","month":"10","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","publisher":"Dryad","oa":1,"related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"2170"}]},"title":"Data from: Likelihood-based inference of population history from low coverage de novo genome assemblies","type":"research_data_reference","oa_version":"Published Version","department":[{"_id":"NiBa"}],"date_published":"2013-10-01T00:00:00Z","author":[{"first_name":"Jack","full_name":"Hearn, Jack","last_name":"Hearn"},{"first_name":"Graham","full_name":"Stone, Graham","last_name":"Stone"},{"first_name":"Nicholas H","full_name":"Barton, Nicholas H","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240"},{"last_name":"Lohse","full_name":"Lohse, Konrad","first_name":"Konrad"},{"first_name":"Lynsey","full_name":"Bunnefeld, Lynsey","last_name":"Bunnefeld"}],"year":"2013","date_created":"2021-07-30T08:31:22Z","date_updated":"2023-02-23T10:31:17Z","status":"public","abstract":[{"text":"Short-read sequencing technologies have in principle made it feasible to draw detailed inferences about the recent history of any organism. In practice, however, this remains challenging due to the difficulty of genome assembly in most organisms and the lack of statistical methods powerful enough to discriminate among recent, non-equilibrium histories. We address both the assembly and inference challenges. We develop a bioinformatic pipeline for generating outgroup-rooted alignments of orthologous sequence blocks from de novo low-coverage short-read data for a small number of genomes, and show how such sequence blocks can be used to fit explicit models of population divergence and admixture in a likelihood framework. To illustrate our approach, we reconstruct the Pleistocene history of an oak-feeding insect (the oak gallwasp Biorhiza pallida) which, in common with many other taxa, was restricted during Pleistocene ice ages to a longitudinal series of southern refugia spanning theWestern Palaearctic. Our analysis of sequence blocks sampled from a single genome from each of three major glacial refugia reveals support for an unexpected history dominated by recent admixture. Despite the fact that 80% of the genome is affected by admixture during the last glacial cycle, we are able to infer the deeper divergence history of these populations. These inferences are robust to variation in block length, mutation model, and the sampling location of individual genomes within refugia. This combination of de novo assembly and numerical likelihood calculation provides a powerful framework for estimating recent population history that can be applied to any organism without the need for prior genetic resources.","lang":"eng"}],"day":"01","article_processing_charge":"No","citation":{"ama":"Hearn J, Stone G, Barton NH, Lohse K, Bunnefeld L. Data from: Likelihood-based inference of population history from low coverage de novo genome assemblies. 2013. doi:<a href=\"https://doi.org/10.5061/dryad.r3r60\">10.5061/dryad.r3r60</a>","short":"J. Hearn, G. Stone, N.H. Barton, K. Lohse, L. Bunnefeld, (2013).","mla":"Hearn, Jack, et al. <i>Data from: Likelihood-Based Inference of Population History from Low Coverage de Novo Genome Assemblies</i>. Dryad, 2013, doi:<a href=\"https://doi.org/10.5061/dryad.r3r60\">10.5061/dryad.r3r60</a>.","ieee":"J. Hearn, G. Stone, N. H. Barton, K. Lohse, and L. Bunnefeld, “Data from: Likelihood-based inference of population history from low coverage de novo genome assemblies.” Dryad, 2013.","ista":"Hearn J, Stone G, Barton NH, Lohse K, Bunnefeld L. 2013. Data from: Likelihood-based inference of population history from low coverage de novo genome assemblies, Dryad, <a href=\"https://doi.org/10.5061/dryad.r3r60\">10.5061/dryad.r3r60</a>.","chicago":"Hearn, Jack, Graham Stone, Nicholas H Barton, Konrad Lohse, and Lynsey Bunnefeld. “Data from: Likelihood-Based Inference of Population History from Low Coverage de Novo Genome Assemblies.” Dryad, 2013. <a href=\"https://doi.org/10.5061/dryad.r3r60\">https://doi.org/10.5061/dryad.r3r60</a>.","apa":"Hearn, J., Stone, G., Barton, N. H., Lohse, K., &#38; Bunnefeld, L. (2013). Data from: Likelihood-based inference of population history from low coverage de novo genome assemblies. Dryad. <a href=\"https://doi.org/10.5061/dryad.r3r60\">https://doi.org/10.5061/dryad.r3r60</a>"},"main_file_link":[{"url":"https://doi.org/10.5061/dryad.r3r60","open_access":"1"}]},{"date_updated":"2022-06-20T09:18:06Z","page":"508-515","quality_controlled":"1","date_created":"2022-03-21T07:46:22Z","year":"2013","status":"public","article_processing_charge":"No","day":"01","scopus_import":"1","citation":{"ama":"Barton NH. Differentiation. In: <i>Encyclopedia of Biodiversity</i>. 2nd ed. Elsevier; 2013:508-515. doi:<a href=\"https://doi.org/10.1016/b978-0-12-384719-5.00031-9\">10.1016/b978-0-12-384719-5.00031-9</a>","short":"N.H. Barton, in:, Encyclopedia of Biodiversity, 2nd ed., Elsevier, 2013, pp. 508–515.","ieee":"N. H. Barton, “Differentiation,” in <i>Encyclopedia of Biodiversity</i>, 2nd ed., Elsevier, 2013, pp. 508–515.","mla":"Barton, Nicholas H. “Differentiation.” <i>Encyclopedia of Biodiversity</i>, 2nd ed., Elsevier, 2013, pp. 508–15, doi:<a href=\"https://doi.org/10.1016/b978-0-12-384719-5.00031-9\">10.1016/b978-0-12-384719-5.00031-9</a>.","ista":"Barton NH. 2013.Differentiation. In: Encyclopedia of Biodiversity. , 508–515.","apa":"Barton, N. H. (2013). Differentiation. In <i>Encyclopedia of Biodiversity</i> (2nd ed., pp. 508–515). Elsevier. <a href=\"https://doi.org/10.1016/b978-0-12-384719-5.00031-9\">https://doi.org/10.1016/b978-0-12-384719-5.00031-9</a>","chicago":"Barton, Nicholas H. “Differentiation.” In <i>Encyclopedia of Biodiversity</i>, 2nd ed., 508–15. Elsevier, 2013. <a href=\"https://doi.org/10.1016/b978-0-12-384719-5.00031-9\">https://doi.org/10.1016/b978-0-12-384719-5.00031-9</a>."},"edition":"2","keyword":["Adaptive landscape","Cline","Coalescent process","Gene flow","Hybrid zone","Local adaptation","Natural selection","Neutral theory","Population structure","Speciation"],"publication_identifier":{"isbn":["978-0-12-384720-1"]},"publisher":"Elsevier","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"01","_id":"10899","doi":"10.1016/b978-0-12-384719-5.00031-9","type":"book_chapter","title":"Differentiation","language":[{"iso":"eng"}],"publication_status":"published","date_published":"2013-01-01T00:00:00Z","department":[{"_id":"NiBa"}],"oa_version":"None","author":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","first_name":"Nicholas H","last_name":"Barton"}],"publication":"Encyclopedia of Biodiversity"}]