[{"publication_status":"published","language":[{"iso":"eng"}],"issue":"2","volume":202,"ec_funded":1,"abstract":[{"text":"How likely is it that a population escapes extinction through adaptive evolution? The answer to this question is of great relevance in conservation biology, where we aim at species’ rescue and the maintenance of biodiversity, and in agriculture and medicine, where we seek to hamper the emergence of pesticide or drug resistance. By reshuffling the genome, recombination has two antagonistic effects on the probability of evolutionary rescue: It generates and it breaks up favorable gene combinations. Which of the two effects prevails depends on the fitness effects of mutations and on the impact of stochasticity on the allele frequencies. In this article, we analyze a mathematical model for rescue after a sudden environmental change when adaptation is contingent on mutations at two loci. The analysis reveals a complex nonlinear dependence of population survival on recombination. We moreover find that, counterintuitively, a fast eradication of the wild type can promote rescue in the presence of recombination. The model also shows that two-step rescue is not unlikely to happen and can even be more likely than single-step rescue (where adaptation relies on a single mutation), depending on the circumstances.","lang":"eng"}],"oa_version":"Preprint","scopus_import":1,"main_file_link":[{"url":"http://biorxiv.org/content/early/2015/07/06/022020.abstract","open_access":"1"}],"month":"02","intvolume":" 202","date_updated":"2023-02-21T10:24:19Z","department":[{"_id":"NiBa"}],"_id":"1241","type":"journal_article","status":"public","year":"2016","day":"01","publication":"Genetics","page":"721 - 732","doi":"10.1534/genetics.115.180299","date_published":"2016-02-01T00:00:00Z","date_created":"2018-12-11T11:50:54Z","acknowledgement":"This work was made possible by a “For Women in Science” fellowship (L’Oréal Österreich in cooperation with the Austrian Commission for the United Nations Educational, Scientific, and Cultural Organization and the Austrian Academy of Sciences with financial support from the Federal Ministry for Science and Research Austria) and European Research Council grant 250152 (to Nick Barton).","publisher":"Genetics Society of America","quality_controlled":"1","oa":1,"citation":{"ista":"Uecker H, Hermisson J. 2016. The role of recombination in evolutionary rescue. Genetics. 202(2), 721–732.","chicago":"Uecker, Hildegard, and Joachim Hermisson. “The Role of Recombination in Evolutionary Rescue.” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.115.180299.","ama":"Uecker H, Hermisson J. The role of recombination in evolutionary rescue. Genetics. 2016;202(2):721-732. doi:10.1534/genetics.115.180299","apa":"Uecker, H., & Hermisson, J. (2016). The role of recombination in evolutionary rescue. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.180299","short":"H. Uecker, J. Hermisson, Genetics 202 (2016) 721–732.","ieee":"H. Uecker and J. Hermisson, “The role of recombination in evolutionary rescue,” Genetics, vol. 202, no. 2. Genetics Society of America, pp. 721–732, 2016.","mla":"Uecker, Hildegard, and Joachim Hermisson. “The Role of Recombination in Evolutionary Rescue.” Genetics, vol. 202, no. 2, Genetics Society of America, 2016, pp. 721–32, doi:10.1534/genetics.115.180299."},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publist_id":"6091","author":[{"last_name":"Uecker","orcid":"0000-0001-9435-2813","full_name":"Uecker, Hildegard","first_name":"Hildegard","id":"2DB8F68A-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Hermisson","full_name":"Hermisson, Joachim","first_name":"Joachim"}],"title":"The role of recombination in evolutionary rescue","project":[{"name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"_id":"25B67606-B435-11E9-9278-68D0E5697425","name":"L'OREAL Fellowship"}]},{"project":[{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","grant_number":"618091","call_identifier":"FP7","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","citation":{"mla":"Oliveto, Pietro, et al. “When Non-Elitism Outperforms Elitism for Crossing Fitness Valleys.” Proceedings of the Genetic and Evolutionary Computation Conference 2016 , ACM, 2016, pp. 1163–70, doi:10.1145/2908812.2908909.","ama":"Oliveto P, Paixao T, Heredia J, Sudholt D, Trubenova B. When non-elitism outperforms elitism for crossing fitness valleys. In: Proceedings of the Genetic and Evolutionary Computation Conference 2016 . ACM; 2016:1163-1170. doi:10.1145/2908812.2908909","apa":"Oliveto, P., Paixao, T., Heredia, J., Sudholt, D., & Trubenova, B. (2016). When non-elitism outperforms elitism for crossing fitness valleys. In Proceedings of the Genetic and Evolutionary Computation Conference 2016 (pp. 1163–1170). Denver, CO, USA: ACM. https://doi.org/10.1145/2908812.2908909","ieee":"P. Oliveto, T. Paixao, J. Heredia, D. Sudholt, and B. Trubenova, “When non-elitism outperforms elitism for crossing fitness valleys,” in Proceedings of the Genetic and Evolutionary Computation Conference 2016 , Denver, CO, USA, 2016, pp. 1163–1170.","short":"P. Oliveto, T. Paixao, J. Heredia, D. Sudholt, B. Trubenova, in:, Proceedings of the Genetic and Evolutionary Computation Conference 2016 , ACM, 2016, pp. 1163–1170.","chicago":"Oliveto, Pietro, Tiago Paixao, Jorge Heredia, Dirk Sudholt, and Barbora Trubenova. “When Non-Elitism Outperforms Elitism for Crossing Fitness Valleys.” In Proceedings of the Genetic and Evolutionary Computation Conference 2016 , 1163–70. ACM, 2016. https://doi.org/10.1145/2908812.2908909.","ista":"Oliveto P, Paixao T, Heredia J, Sudholt D, Trubenova B. 2016. When non-elitism outperforms elitism for crossing fitness valleys. Proceedings of the Genetic and Evolutionary Computation Conference 2016 . GECCO: Genetic and evolutionary computation conference, 1163–1170."},"title":"When non-elitism outperforms elitism for crossing fitness valleys","author":[{"last_name":"Oliveto","full_name":"Oliveto, Pietro","first_name":"Pietro"},{"last_name":"Paixao","orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","first_name":"Tiago"},{"first_name":"Jorge","last_name":"Heredia","full_name":"Heredia, Jorge"},{"first_name":"Dirk","full_name":"Sudholt, Dirk","last_name":"Sudholt"},{"full_name":"Trubenova, Barbora","orcid":"0000-0002-6873-2967","last_name":"Trubenova","id":"42302D54-F248-11E8-B48F-1D18A9856A87","first_name":"Barbora"}],"publist_id":"5900","quality_controlled":"1","publisher":"ACM","oa":1,"day":"20","publication":"Proceedings of the Genetic and Evolutionary Computation Conference 2016 ","has_accepted_license":"1","year":"2016","doi":"10.1145/2908812.2908909","date_published":"2016-07-20T00:00:00Z","date_created":"2018-12-11T11:51:31Z","page":"1163 - 1170","_id":"1349","status":"public","pubrep_id":"650","type":"conference","conference":{"end_date":"2016-07-24","location":"Denver, CO, USA","start_date":"2016-07-20","name":"GECCO: Genetic and evolutionary computation conference"},"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)"},"ddc":["576"],"date_updated":"2021-01-12T06:50:03Z","file_date_updated":"2020-07-14T12:44:45Z","department":[{"_id":"NiBa"},{"_id":"CaGu"}],"oa_version":"Published Version","abstract":[{"lang":"eng","text":"Crossing fitness valleys is one of the major obstacles to function optimization. In this paper we investigate how the structure of the fitness valley, namely its depth d and length ℓ, influence the runtime of different strategies for crossing these valleys. We present a runtime comparison between the (1+1) EA and two non-elitist nature-inspired algorithms, Strong Selection Weak Mutation (SSWM) and the Metropolis algorithm. While the (1+1) EA has to jump across the valley to a point of higher fitness because it does not accept decreasing moves, the non-elitist algorithms may cross the valley by accepting worsening moves. We show that while the runtime of the (1+1) EA algorithm depends critically on the length of the valley, the runtimes of the non-elitist algorithms depend crucially only on the depth of the valley. In particular, the expected runtime of both SSWM and Metropolis is polynomial in ℓ and exponential in d while the (1+1) EA is efficient only for valleys of small length. Moreover, we show that both SSWM and Metropolis can also efficiently optimize a rugged function consisting of consecutive valleys."}],"month":"07","scopus_import":1,"file":[{"date_updated":"2020-07-14T12:44:45Z","file_size":979026,"creator":"system","date_created":"2018-12-12T10:16:27Z","file_name":"IST-2016-650-v1+1_p1163-oliveto.pdf","content_type":"application/pdf","access_level":"open_access","relation":"main_file","checksum":"a1896e39e4113f2711e46b435d5f3e69","file_id":"5214"}],"language":[{"iso":"eng"}],"publication_status":"published","ec_funded":1},{"date_updated":"2021-01-12T06:50:08Z","department":[{"_id":"NiBa"},{"_id":"CaGu"}],"_id":"1359","type":"journal_article","article_type":"original","status":"public","publication_status":"published","language":[{"iso":"eng"}],"volume":113,"issue":"16","ec_funded":1,"abstract":[{"text":"The role of gene interactions in the evolutionary process has long\r\nbeen controversial. Although some argue that they are not of\r\nimportance, because most variation is additive, others claim that\r\ntheir effect in the long term can be substantial. Here, we focus on\r\nthe long-term effects of genetic interactions under directional\r\nselection assuming no mutation or dominance, and that epistasis is\r\nsymmetrical overall. We ask by how much the mean of a complex\r\ntrait can be increased by selection and analyze two extreme\r\nregimes, in which either drift or selection dominate the dynamics\r\nof allele frequencies. In both scenarios, epistatic interactions affect\r\nthe long-term response to selection by modulating the additive\r\ngenetic variance. When drift dominates, we extend Robertson\r\n’\r\ns\r\n[Robertson A (1960)\r\nProc R Soc Lond B Biol Sci\r\n153(951):234\r\n−\r\n249]\r\nargument to show that, for any form of epistasis, the total response\r\nof a haploid population is proportional to the initial total genotypic\r\nvariance. In contrast, the total response of a diploid population is\r\nincreased by epistasis, for a given initial genotypic variance. When\r\nselection dominates, we show that the total selection response can\r\nonly be increased by epistasis when s\r\nome initially deleterious alleles\r\nbecome favored as the genetic background changes. We find a sim-\r\nple approximation for this effect and show that, in this regime, it is\r\nthe structure of the genotype - phenotype map that matters and not\r\nthe variance components of the population.","lang":"eng"}],"pmid":1,"oa_version":"Published Version","scopus_import":1,"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4843425/"}],"month":"04","intvolume":" 113","citation":{"mla":"Paixao, Tiago, and Nicholas H. Barton. “The Effect of Gene Interactions on the Long-Term Response to Selection.” PNAS, vol. 113, no. 16, National Academy of Sciences, 2016, pp. 4422–27, doi:10.1073/pnas.1518830113.","apa":"Paixao, T., & Barton, N. H. (2016). The effect of gene interactions on the long-term response to selection. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1518830113","ama":"Paixao T, Barton NH. The effect of gene interactions on the long-term response to selection. PNAS. 2016;113(16):4422-4427. doi:10.1073/pnas.1518830113","ieee":"T. Paixao and N. H. Barton, “The effect of gene interactions on the long-term response to selection,” PNAS, vol. 113, no. 16. National Academy of Sciences, pp. 4422–4427, 2016.","short":"T. Paixao, N.H. Barton, PNAS 113 (2016) 4422–4427.","chicago":"Paixao, Tiago, and Nicholas H Barton. “The Effect of Gene Interactions on the Long-Term Response to Selection.” PNAS. National Academy of Sciences, 2016. https://doi.org/10.1073/pnas.1518830113.","ista":"Paixao T, Barton NH. 2016. The effect of gene interactions on the long-term response to selection. PNAS. 113(16), 4422–4427."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","first_name":"Tiago","last_name":"Paixao","orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago"},{"full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H"}],"publist_id":"5886","article_processing_charge":"No","external_id":{"pmid":["27044080"]},"title":"The effect of gene interactions on the long-term response to selection","project":[{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation"},{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","grant_number":"618091","call_identifier":"FP7","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425"}],"year":"2016","day":"19","publication":"PNAS","page":"4422 - 4427","doi":"10.1073/pnas.1518830113","date_published":"2016-04-19T00:00:00Z","date_created":"2018-12-11T11:51:34Z","publisher":"National Academy of Sciences","quality_controlled":"1","oa":1},{"scopus_import":1,"intvolume":" 202","month":"01","oa_version":"Submitted Version","volume":202,"issue":"1","publication_status":"published","language":[{"iso":"eng"}],"file":[{"file_id":"4687","checksum":"3562b89c821a4be84edf2b6ebd870cf5","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_name":"IST-2017-769-v1+1_SewallWright1931.pdf","date_created":"2018-12-12T10:08:26Z","creator":"system","file_size":112674,"date_updated":"2020-07-14T12:44:46Z"}],"type":"journal_article","pubrep_id":"769","status":"public","_id":"1356","department":[{"_id":"NiBa"}],"file_date_updated":"2020-07-14T12:44:46Z","date_updated":"2021-01-12T06:50:07Z","ddc":["570"],"oa":1,"publisher":"Genetics Society of America","quality_controlled":"1","page":"3 - 4","date_created":"2018-12-11T11:51:33Z","doi":"10.1534/genetics.115.184796","date_published":"2016-01-05T00:00:00Z","year":"2016","has_accepted_license":"1","publication":"Genetics","day":"05","author":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H","last_name":"Barton","full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240"}],"publist_id":"5889","title":"Sewall Wright on evolution in Mendelian populations and the “Shifting Balance”","citation":{"ama":"Barton NH. Sewall Wright on evolution in Mendelian populations and the “Shifting Balance.” Genetics. 2016;202(1):3-4. doi:10.1534/genetics.115.184796","apa":"Barton, N. H. (2016). Sewall Wright on evolution in Mendelian populations and the “Shifting Balance.” Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.184796","ieee":"N. H. Barton, “Sewall Wright on evolution in Mendelian populations and the ‘Shifting Balance,’” Genetics, vol. 202, no. 1. Genetics Society of America, pp. 3–4, 2016.","short":"N.H. Barton, Genetics 202 (2016) 3–4.","mla":"Barton, Nicholas H. “Sewall Wright on Evolution in Mendelian Populations and the ‘Shifting Balance.’” Genetics, vol. 202, no. 1, Genetics Society of America, 2016, pp. 3–4, doi:10.1534/genetics.115.184796.","ista":"Barton NH. 2016. Sewall Wright on evolution in Mendelian populations and the “Shifting Balance”. Genetics. 202(1), 3–4.","chicago":"Barton, Nicholas H. “Sewall Wright on Evolution in Mendelian Populations and the ‘Shifting Balance.’” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.115.184796."},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87"},{"pubrep_id":"768","status":"public","type":"journal_article","_id":"1357","file_date_updated":"2020-07-14T12:44:46Z","department":[{"_id":"NiBa"}],"ddc":["576"],"date_updated":"2021-01-12T06:50:07Z","intvolume":" 202","month":"03","scopus_import":1,"oa_version":"Submitted Version","volume":202,"issue":"3","language":[{"iso":"eng"}],"file":[{"date_created":"2018-12-12T10:15:09Z","file_name":"IST-2017-768-v1+1_Hudson-Kaplan-1988.pdf","date_updated":"2020-07-14T12:44:46Z","file_size":130779,"creator":"system","checksum":"b2174bab2de1d1142900062a150f35c9","file_id":"5127","content_type":"application/pdf","access_level":"open_access","relation":"main_file"}],"publication_status":"published","title":"Richard Hudson and Norman Kaplan on the coalescent process","publist_id":"5888","author":[{"first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Barton NH. 2016. Richard Hudson and Norman Kaplan on the coalescent process. Genetics. 202(3), 865–866.","chicago":"Barton, Nicholas H. “Richard Hudson and Norman Kaplan on the Coalescent Process.” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.116.187542.","short":"N.H. Barton, Genetics 202 (2016) 865–866.","ieee":"N. H. Barton, “Richard Hudson and Norman Kaplan on the coalescent process,” Genetics, vol. 202, no. 3. Genetics Society of America, pp. 865–866, 2016.","apa":"Barton, N. H. (2016). Richard Hudson and Norman Kaplan on the coalescent process. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.116.187542","ama":"Barton NH. Richard Hudson and Norman Kaplan on the coalescent process. Genetics. 2016;202(3):865-866. doi:10.1534/genetics.116.187542","mla":"Barton, Nicholas H. “Richard Hudson and Norman Kaplan on the Coalescent Process.” Genetics, vol. 202, no. 3, Genetics Society of America, 2016, pp. 865–66, doi:10.1534/genetics.116.187542."},"oa":1,"publisher":"Genetics Society of America","quality_controlled":"1","date_created":"2018-12-11T11:51:33Z","date_published":"2016-03-01T00:00:00Z","doi":"10.1534/genetics.116.187542","page":"865 - 866","publication":"Genetics","day":"01","year":"2016","has_accepted_license":"1"},{"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","citation":{"apa":"Abbott, R., Barton, N. H., & Good, J. (2016). Genomics of hybridization and its evolutionary consequences. Molecular Ecology. Wiley-Blackwell. https://doi.org/10.1111/mec.13685","ama":"Abbott R, Barton NH, Good J. Genomics of hybridization and its evolutionary consequences. Molecular Ecology. 2016;25(11):2325-2332. doi:10.1111/mec.13685","ieee":"R. Abbott, N. H. Barton, and J. Good, “Genomics of hybridization and its evolutionary consequences,” Molecular Ecology, vol. 25, no. 11. Wiley-Blackwell, pp. 2325–2332, 2016.","short":"R. Abbott, N.H. Barton, J. Good, Molecular Ecology 25 (2016) 2325–2332.","mla":"Abbott, Richard, et al. “Genomics of Hybridization and Its Evolutionary Consequences.” Molecular Ecology, vol. 25, no. 11, Wiley-Blackwell, 2016, pp. 2325–32, doi:10.1111/mec.13685.","ista":"Abbott R, Barton NH, Good J. 2016. Genomics of hybridization and its evolutionary consequences. Molecular Ecology. 25(11), 2325–2332.","chicago":"Abbott, Richard, Nicholas H Barton, and Jeffrey Good. “Genomics of Hybridization and Its Evolutionary Consequences.” Molecular Ecology. Wiley-Blackwell, 2016. https://doi.org/10.1111/mec.13685."},"title":"Genomics of hybridization and its evolutionary consequences","publist_id":"5798","author":[{"full_name":"Abbott, Richard","last_name":"Abbott","first_name":"Richard"},{"full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H"},{"last_name":"Good","full_name":"Good, Jeffrey","first_name":"Jeffrey"}],"oa":1,"quality_controlled":"1","publisher":"Wiley-Blackwell","publication":"Molecular Ecology","day":"08","year":"2016","has_accepted_license":"1","date_created":"2018-12-11T11:51:51Z","doi":"10.1111/mec.13685","date_published":"2016-06-08T00:00:00Z","page":"2325 - 2332","_id":"1409","pubrep_id":"772","status":"public","type":"journal_article","ddc":["576"],"date_updated":"2021-01-12T06:50:33Z","department":[{"_id":"NiBa"}],"file_date_updated":"2020-07-14T12:44:53Z","oa_version":"Submitted Version","intvolume":" 25","month":"06","scopus_import":1,"language":[{"iso":"eng"}],"file":[{"content_type":"application/pdf","relation":"main_file","access_level":"open_access","file_id":"4797","checksum":"ede7d0b8a471754f71f17e2b20f3135b","file_size":226137,"date_updated":"2020-07-14T12:44:53Z","creator":"system","file_name":"IST-2017-772-v1+1_AbbotEtAl2016-3.pdf","date_created":"2018-12-12T10:10:12Z"}],"publication_status":"published","volume":25,"issue":"11"},{"issue":"4","volume":202,"ec_funded":1,"language":[{"iso":"eng"}],"publication_status":"published","month":"04","intvolume":" 202","scopus_import":"1","main_file_link":[{"url":"http://arxiv.org/abs/1510.08344","open_access":"1"}],"oa_version":"Preprint","abstract":[{"text":"Selection, mutation, and random drift affect the dynamics of allele frequencies and consequently of quantitative traits. While the macroscopic dynamics of quantitative traits can be measured, the underlying allele frequencies are typically unobserved. Can we understand how the macroscopic observables evolve without following these microscopic processes? This problem has been studied previously by analogy with statistical mechanics: the allele frequency distribution at each time point is approximated by the stationary form, which maximizes entropy. We explore the limitations of this method when mutation is small (4Nμ < 1) so that populations are typically close to fixation, and we extend the theory in this regime to account for changes in mutation strength. We consider a single diallelic locus either under directional selection or with overdominance and then generalize to multiple unlinked biallelic loci with unequal effects. We find that the maximum-entropy approximation is remarkably accurate, even when mutation and selection change rapidly. ","lang":"eng"}],"department":[{"_id":"GaTk"},{"_id":"NiBa"}],"date_updated":"2022-08-01T10:49:55Z","status":"public","type":"journal_article","_id":"1420","doi":"10.1534/genetics.115.184127","date_published":"2016-04-06T00:00:00Z","date_created":"2018-12-11T11:51:55Z","page":"1523 - 1548","day":"06","publication":"Genetics","year":"2016","quality_controlled":"1","publisher":"Genetics Society of America","oa":1,"title":"A general approximation for the dynamics of quantitative traits","author":[{"orcid":"0000-0002-7214-0171","full_name":"Bod'ová, Katarína","last_name":"Bod'ová","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","first_name":"Katarína"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper","full_name":"Tkacik, Gasper","orcid":"0000-0002-6699-1455","last_name":"Tkacik"},{"last_name":"Barton","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H"}],"publist_id":"5787","external_id":{"arxiv":["1510.08344"]},"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Bodova K, Tkačik G, Barton NH. 2016. A general approximation for the dynamics of quantitative traits. Genetics. 202(4), 1523–1548.","chicago":"Bodova, Katarina, Gašper Tkačik, and Nicholas H Barton. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.115.184127.","short":"K. Bodova, G. Tkačik, N.H. Barton, Genetics 202 (2016) 1523–1548.","ieee":"K. Bodova, G. Tkačik, and N. H. Barton, “A general approximation for the dynamics of quantitative traits,” Genetics, vol. 202, no. 4. Genetics Society of America, pp. 1523–1548, 2016.","ama":"Bodova K, Tkačik G, Barton NH. A general approximation for the dynamics of quantitative traits. Genetics. 2016;202(4):1523-1548. doi:10.1534/genetics.115.184127","apa":"Bodova, K., Tkačik, G., & Barton, N. H. (2016). A general approximation for the dynamics of quantitative traits. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.184127","mla":"Bodova, Katarina, et al. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics, vol. 202, no. 4, Genetics Society of America, 2016, pp. 1523–48, doi:10.1534/genetics.115.184127."},"project":[{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"},{"name":"Information processing and computation in fish groups","grant_number":"RGP0065/2012","_id":"255008E4-B435-11E9-9278-68D0E5697425"}]},{"publication_status":"published","language":[{"iso":"eng"}],"file":[{"creator":"system","date_updated":"2020-07-14T12:45:00Z","file_size":957466,"date_created":"2018-12-12T10:16:51Z","file_name":"IST-2016-561-v1+1_Lohse_et_al_Genetics_2015.pdf","access_level":"open_access","relation":"main_file","content_type":"application/pdf","checksum":"41c9b5d72e7fe4624dd22dfe622337d5","file_id":"5241"}],"ec_funded":1,"volume":202,"issue":"2","abstract":[{"text":"The inference of demographic history from genome data is hindered by a lack of efficient computational approaches. In particular, it has proved difficult to exploit the information contained in the distribution of genealogies across the genome. We have previously shown that the generating function (GF) of genealogies can be used to analytically compute likelihoods of demographic models from configurations of mutations in short sequence blocks (Lohse et al. 2011). Although the GF has a simple, recursive form, the size of such likelihood calculations explodes quickly with the number of individuals and applications of this framework have so far been mainly limited to small samples (pairs and triplets) for which the GF can be written by hand. Here we investigate several strategies for exploiting the inherent symmetries of the coalescent. In particular, we show that the GF of genealogies can be decomposed into a set of equivalence classes that allows likelihood calculations from nontrivial samples. Using this strategy, we automated blockwise likelihood calculations for a general set of demographic scenarios in Mathematica. These histories may involve population size changes, continuous migration, discrete divergence, and admixture between multiple populations. To give a concrete example, we calculate the likelihood for a model of isolation with migration (IM), assuming two diploid samples without phase and outgroup information. We demonstrate the new inference scheme with an analysis of two individual butterfly genomes from the sister species Heliconius melpomene rosina and H. cydno.","lang":"eng"}],"pmid":1,"oa_version":"Preprint","scopus_import":"1","intvolume":" 202","month":"02","date_updated":"2022-05-24T09:16:22Z","ddc":["570"],"department":[{"_id":"KrCh"},{"_id":"NiBa"}],"file_date_updated":"2020-07-14T12:45:00Z","_id":"1518","article_type":"original","type":"journal_article","pubrep_id":"561","status":"public","year":"2016","has_accepted_license":"1","publication":"Genetics","day":"01","page":"775 - 786","date_created":"2018-12-11T11:52:29Z","doi":"10.1534/genetics.115.183814","date_published":"2016-02-01T00:00:00Z","acknowledgement":"We thank Lynsey Bunnefeld for discussions throughout the project and Joshua Schraiber and one anonymous reviewer\r\nfor constructive comments on an earlier version of this manuscript. This work was supported by funding from the\r\nUnited Kingdom Natural Environment Research Council (to K.L.) (NE/I020288/1) and a grant from the European\r\nResearch Council (250152) (to N.H.B.).","oa":1,"publisher":"Genetics Society of America","quality_controlled":"1","citation":{"chicago":"Lohse, Konrad, Martin Chmelik, Simon Martin, and Nicholas H Barton. “Efficient Strategies for Calculating Blockwise Likelihoods under the Coalescent.” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.115.183814.","ista":"Lohse K, Chmelik M, Martin S, Barton NH. 2016. Efficient strategies for calculating blockwise likelihoods under the coalescent. Genetics. 202(2), 775–786.","mla":"Lohse, Konrad, et al. “Efficient Strategies for Calculating Blockwise Likelihoods under the Coalescent.” Genetics, vol. 202, no. 2, Genetics Society of America, 2016, pp. 775–86, doi:10.1534/genetics.115.183814.","ieee":"K. Lohse, M. Chmelik, S. Martin, and N. H. Barton, “Efficient strategies for calculating blockwise likelihoods under the coalescent,” Genetics, vol. 202, no. 2. Genetics Society of America, pp. 775–786, 2016.","short":"K. Lohse, M. Chmelik, S. Martin, N.H. Barton, Genetics 202 (2016) 775–786.","apa":"Lohse, K., Chmelik, M., Martin, S., & Barton, N. H. (2016). Efficient strategies for calculating blockwise likelihoods under the coalescent. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.183814","ama":"Lohse K, Chmelik M, Martin S, Barton NH. Efficient strategies for calculating blockwise likelihoods under the coalescent. Genetics. 2016;202(2):775-786. doi:10.1534/genetics.115.183814"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","external_id":{"pmid":["26715666"]},"author":[{"full_name":"Lohse, Konrad","last_name":"Lohse","first_name":"Konrad"},{"first_name":"Martin","id":"3624234E-F248-11E8-B48F-1D18A9856A87","last_name":"Chmelik","full_name":"Chmelik, Martin"},{"full_name":"Martin, Simon","last_name":"Martin","first_name":"Simon"},{"last_name":"Barton","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H"}],"publist_id":"5658","title":"Efficient strategies for calculating blockwise likelihoods under the coalescent","project":[{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"}]},{"oa_version":"Published Version","abstract":[{"lang":"eng","text":"Ancestral processes are fundamental to modern population genetics and spatial structure has been the subject of intense interest for many years. Despite this interest, almost nothing is known about the distribution of the locations of pedigree or genetic ancestors. Using both spatially continuous and stepping-stone models, we show that the distribution of pedigree ancestors approaches a travelling wave, for which we develop two alternative approximations. The speed and width of the wave are sensitive to the local details of the model. After a short time, genetic ancestors spread far more slowly than pedigree ancestors, ultimately diffusing out with radius ## rather than spreading at constant speed. In contrast to the wave of pedigree ancestors, the spread of genetic ancestry is insensitive to the local details of the models."}],"month":"04","intvolume":" 108","scopus_import":1,"file":[{"checksum":"6a65ba187994d4ad86c1c509e0ff482a","file_id":"4865","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_name":"IST-2016-465-v1+1_1-s2.0-S0040580915001094-main.pdf","date_created":"2018-12-12T10:11:12Z","creator":"system","file_size":1684043,"date_updated":"2020-07-14T12:45:07Z"}],"language":[{"iso":"eng"}],"publication_status":"published","volume":108,"ec_funded":1,"_id":"1631","status":"public","pubrep_id":"465","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)"},"ddc":["576"],"date_updated":"2021-01-12T06:52:07Z","department":[{"_id":"NiBa"}],"file_date_updated":"2020-07-14T12:45:07Z","publisher":"Academic Press","quality_controlled":"1","oa":1,"day":"01","publication":"Theoretical Population Biology","has_accepted_license":"1","year":"2016","doi":"10.1016/j.tpb.2015.10.008","date_published":"2016-04-01T00:00:00Z","date_created":"2018-12-11T11:53:08Z","page":"1 - 12","project":[{"grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","citation":{"short":"J. Kelleher, A. Etheridge, A. Véber, N.H. Barton, Theoretical Population Biology 108 (2016) 1–12.","ieee":"J. Kelleher, A. Etheridge, A. Véber, and N. H. Barton, “Spread of pedigree versus genetic ancestry in spatially distributed populations,” Theoretical Population Biology, vol. 108. Academic Press, pp. 1–12, 2016.","apa":"Kelleher, J., Etheridge, A., Véber, A., & Barton, N. H. (2016). Spread of pedigree versus genetic ancestry in spatially distributed populations. Theoretical Population Biology. Academic Press. https://doi.org/10.1016/j.tpb.2015.10.008","ama":"Kelleher J, Etheridge A, Véber A, Barton NH. Spread of pedigree versus genetic ancestry in spatially distributed populations. Theoretical Population Biology. 2016;108:1-12. doi:10.1016/j.tpb.2015.10.008","mla":"Kelleher, Jerome, et al. “Spread of Pedigree versus Genetic Ancestry in Spatially Distributed Populations.” Theoretical Population Biology, vol. 108, Academic Press, 2016, pp. 1–12, doi:10.1016/j.tpb.2015.10.008.","ista":"Kelleher J, Etheridge A, Véber A, Barton NH. 2016. Spread of pedigree versus genetic ancestry in spatially distributed populations. Theoretical Population Biology. 108, 1–12.","chicago":"Kelleher, Jerome, Alison Etheridge, Amandine Véber, and Nicholas H Barton. “Spread of Pedigree versus Genetic Ancestry in Spatially Distributed Populations.” Theoretical Population Biology. Academic Press, 2016. https://doi.org/10.1016/j.tpb.2015.10.008."},"title":"Spread of pedigree versus genetic ancestry in spatially distributed populations","author":[{"first_name":"Jerome","last_name":"Kelleher","full_name":"Kelleher, Jerome"},{"full_name":"Etheridge, Alison","last_name":"Etheridge","first_name":"Alison"},{"first_name":"Amandine","full_name":"Véber, Amandine","last_name":"Véber"},{"last_name":"Barton","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H"}],"publist_id":"5524"},{"article_number":"e2000234","citation":{"mla":"Roux, Camille, et al. “Shedding Light on the Grey Zone of Speciation along a Continuum of Genomic Divergence.” PLoS Biology, vol. 14, no. 12, e2000234, Public Library of Science, 2016, doi:10.1371/journal.pbio.2000234.","ama":"Roux C, Fraisse C, Romiguier J, Anciaux Y, Galtier N, Bierne N. Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biology. 2016;14(12). doi:10.1371/journal.pbio.2000234","apa":"Roux, C., Fraisse, C., Romiguier, J., Anciaux, Y., Galtier, N., & Bierne, N. (2016). Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biology. Public Library of Science. https://doi.org/10.1371/journal.pbio.2000234","ieee":"C. Roux, C. Fraisse, J. Romiguier, Y. Anciaux, N. Galtier, and N. Bierne, “Shedding light on the grey zone of speciation along a continuum of genomic divergence,” PLoS Biology, vol. 14, no. 12. Public Library of Science, 2016.","short":"C. Roux, C. Fraisse, J. Romiguier, Y. Anciaux, N. Galtier, N. Bierne, PLoS Biology 14 (2016).","chicago":"Roux, Camille, Christelle Fraisse, Jonathan Romiguier, Youann Anciaux, Nicolas Galtier, and Nicolas Bierne. “Shedding Light on the Grey Zone of Speciation along a Continuum of Genomic Divergence.” PLoS Biology. Public Library of Science, 2016. https://doi.org/10.1371/journal.pbio.2000234.","ista":"Roux C, Fraisse C, Romiguier J, Anciaux Y, Galtier N, Bierne N. 2016. Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biology. 14(12), e2000234."},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Roux, Camille","last_name":"Roux","first_name":"Camille"},{"last_name":"Fraisse","orcid":"0000-0001-8441-5075","full_name":"Fraisse, Christelle","id":"32DF5794-F248-11E8-B48F-1D18A9856A87","first_name":"Christelle"},{"full_name":"Romiguier, Jonathan","last_name":"Romiguier","first_name":"Jonathan"},{"full_name":"Anciaux, Youann","last_name":"Anciaux","first_name":"Youann"},{"first_name":"Nicolas","last_name":"Galtier","full_name":"Galtier, Nicolas"},{"last_name":"Bierne","full_name":"Bierne, Nicolas","first_name":"Nicolas"}],"publist_id":"6200","title":"Shedding light on the grey zone of speciation along a continuum of genomic divergence","acknowledgement":"European Research Council (ERC) https://erc.europa.eu/ (grant number ERC grant 232971). PopPhyl project. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. French National Research Agency (ANR) http://www.agence-nationale-recherche.fr/en/project-based-funding-to-advance-french-research/ (grant number ANR-12-BSV7- 0011). HYSEA project.\r\nWe thank Aude Darracq, Vincent Castric, Pierre-Alexandre Gagnaire, Xavier Vekemans, and John Welch for insightful discussions. The computations were performed at the Vital-IT (http://www.vital-it.ch) Center for high-performance computing of the SIB Swiss Institute of Bioinformatics and the ISEM computing cluster at the platform Montpellier Bioinformatique et Biodiversité.","publisher":"Public Library of Science","quality_controlled":"1","oa":1,"has_accepted_license":"1","year":"2016","day":"27","publication":"PLoS Biology","doi":"10.1371/journal.pbio.2000234","date_published":"2016-12-27T00:00:00Z","date_created":"2018-12-11T11:50:28Z","_id":"1158","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","pubrep_id":"742","date_updated":"2023-02-23T14:11:16Z","ddc":["576"],"department":[{"_id":"BeVi"},{"_id":"NiBa"}],"file_date_updated":"2020-07-14T12:44:36Z","abstract":[{"lang":"eng","text":"Speciation results from the progressive accumulation of mutations that decrease the probability of mating between parental populations or reduce the fitness of hybrids—the so-called species barriers. The speciation genomic literature, however, is mainly a collection of case studies, each with its own approach and specificities, such that a global view of the gradual process of evolution from one to two species is currently lacking. Of primary importance is the prevalence of gene flow between diverging entities, which is central in most species concepts and has been widely discussed in recent years. Here, we explore the continuum of speciation thanks to a comparative analysis of genomic data from 61 pairs of populations/species of animals with variable levels of divergence. Gene flow between diverging gene pools is assessed under an approximate Bayesian computation (ABC) framework. We show that the intermediate "grey zone" of speciation, in which taxonomy is often controversial, spans from 0.5% to 2% of net synonymous divergence, irrespective of species life history traits or ecology. Thanks to appropriate modeling of among-locus variation in genetic drift and introgression rate, we clarify the status of the majority of ambiguous cases and uncover a number of cryptic species. Our analysis also reveals the high incidence in animals of semi-isolated species (when some but not all loci are affected by barriers to gene flow) and highlights the intrinsic difficulty, both statistical and conceptual, of delineating species in the grey zone of speciation."}],"oa_version":"Published Version","scopus_import":1,"month":"12","intvolume":" 14","publication_status":"published","file":[{"file_name":"IST-2017-742-v1+1_journal.pbio.2000234.pdf","date_created":"2018-12-12T10:15:42Z","creator":"system","file_size":2494348,"date_updated":"2020-07-14T12:44:36Z","checksum":"2bab63b068a9840efd532b9ae583f9bb","file_id":"5164","relation":"main_file","access_level":"open_access","content_type":"application/pdf"}],"language":[{"iso":"eng"}],"issue":"12","related_material":{"record":[{"id":"9862","status":"public","relation":"research_data"},{"status":"public","id":"9863","relation":"research_data"}]},"volume":14}]