[{"abstract":[{"lang":"eng","text":"The classical infinitesimal model is a simple and robust model for the inheritance of quantitative traits. In this model, a quantitative trait is expressed as the sum of a genetic and an environmental component, and the genetic component of offspring traits within a family follows a normal distribution around the average of the parents’ trait values, and has a variance that is independent of the parental traits. In previous work, we showed that when trait values are determined by the sum of a large number of additive Mendelian factors, each of small effect, one can justify the infinitesimal model as a limit of Mendelian inheritance. In this paper, we show that this result extends to include dominance. We define the model in terms of classical quantities of quantitative genetics, before justifying it as a limit of Mendelian inheritance as the number, M, of underlying loci tends to infinity. As in the additive case, the multivariate normal distribution of trait values across the pedigree can be expressed in terms of variance components in an ancestral population and probabilities of identity by descent determined by the pedigree. Now, with just first-order dominance effects, we require two-, three-, and four-way identities. We also show that, even if we condition on parental trait values, the “shared” and “residual” components of trait values within each family will be asymptotically normally distributed as the number of loci tends to infinity, with an error of order 1/M−−√. We illustrate our results with some numerical examples."}],"author":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","last_name":"Barton"},{"first_name":"Alison M.","full_name":"Etheridge, Alison M.","last_name":"Etheridge"},{"first_name":"Amandine","full_name":"Véber, Amandine","last_name":"Véber"}],"citation":{"short":"N.H. Barton, A.M. Etheridge, A. Véber, Genetics 225 (2023).","ista":"Barton NH, Etheridge AM, Véber A. 2023. The infinitesimal model with dominance. Genetics. 225(2), iyad133.","ama":"Barton NH, Etheridge AM, Véber A. The infinitesimal model with dominance. Genetics. 2023;225(2). doi:10.1093/genetics/iyad133","mla":"Barton, Nicholas H., et al. “The Infinitesimal Model with Dominance.” Genetics, vol. 225, no. 2, iyad133, Oxford Academic, 2023, doi:10.1093/genetics/iyad133.","chicago":"Barton, Nicholas H, Alison M. Etheridge, and Amandine Véber. “The Infinitesimal Model with Dominance.” Genetics. Oxford Academic, 2023. https://doi.org/10.1093/genetics/iyad133.","ieee":"N. H. Barton, A. M. Etheridge, and A. Véber, “The infinitesimal model with dominance,” Genetics, vol. 225, no. 2. Oxford Academic, 2023.","apa":"Barton, N. H., Etheridge, A. M., & Véber, A. (2023). The infinitesimal model with dominance. Genetics. Oxford Academic. https://doi.org/10.1093/genetics/iyad133"},"publication_status":"published","publication_identifier":{"eissn":["1943-2631"],"issn":["0016-6731"]},"_id":"14452","quality_controlled":"1","project":[{"grant_number":"250152","call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425"},{"_id":"bd6958e0-d553-11ed-ba76-86eba6a76c00","name":"Understanding the evolution of continuous genomes","grant_number":"101055327"}],"oa_version":"Published Version","acknowledgement":"NHB was supported in part by ERC Grants 250152 and 101055327. AV was partly supported by the chaire Modélisation Mathématique et Biodiversité of Veolia Environment—Ecole Polytechnique—Museum National d’Histoire Naturelle—Fondation X.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","arxiv":1,"article_processing_charge":"Yes (in subscription journal)","volume":225,"date_updated":"2025-05-28T11:42:48Z","oa":1,"external_id":{"arxiv":["2211.03515"]},"title":"The infinitesimal model with dominance","doi":"10.1093/genetics/iyad133","year":"2023","ec_funded":1,"related_material":{"record":[{"id":"12949","relation":"research_data","status":"public"}]},"ddc":["570"],"tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_number":"iyad133","intvolume":" 225","status":"public","day":"01","type":"journal_article","publication":"Genetics","issue":"2","file_date_updated":"2023-10-30T12:57:53Z","scopus_import":"1","publisher":"Oxford Academic","language":[{"iso":"eng"}],"month":"10","article_type":"original","date_published":"2023-10-01T00:00:00Z","date_created":"2023-10-29T23:01:15Z","file":[{"access_level":"open_access","date_updated":"2023-10-30T12:57:53Z","file_size":1439032,"file_name":"2023_Genetics_Barton.pdf","checksum":"3f65b1fbe813e2f4dbb5d2b5e891844a","date_created":"2023-10-30T12:57:53Z","relation":"main_file","content_type":"application/pdf","file_id":"14469","creator":"dernst","success":1}],"has_accepted_license":"1","department":[{"_id":"NiBa"}]},{"file_date_updated":"2022-09-12T08:08:12Z","publication":"Proceedings of the National Academy of Sciences","issue":"36","status":"public","intvolume":" 119","type":"journal_article","day":"29","date_created":"2022-09-11T22:01:55Z","file":[{"date_updated":"2022-09-12T08:08:12Z","access_level":"open_access","date_created":"2022-09-12T08:08:12Z","checksum":"6dec51f6567da9039982a571508a8e4d","file_name":"2022_PNAS_Hledik.pdf","file_size":2165752,"creator":"dernst","file_id":"12091","content_type":"application/pdf","relation":"main_file","success":1}],"department":[{"_id":"NiBa"},{"_id":"GaTk"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"scopus_import":"1","publisher":"Proceedings of the National Academy of Sciences","date_published":"2022-08-29T00:00:00Z","article_type":"original","month":"08","oa_version":"Published Version","quality_controlled":"1","project":[{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"},{"name":"Can evolution minimize spurious signaling crosstalk to reach optimal performance?","_id":"2665AAFE-B435-11E9-9278-68D0E5697425","grant_number":"RGP0034/2018"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","acknowledgement":"We thank Ksenia Khudiakova, Wiktor Młynarski, Sean Stankowski, and two anonymous reviewers for discussions and comments on the manuscript. G.T. and M.H. acknowledge funding from the Human Frontier Science Program Grant RGP0032/2018. N.B. acknowledges funding from ERC Grant 250152 “Information and Evolution.”","publication_identifier":{"eissn":["1091-6490"],"issn":["0027-8424"]},"_id":"12081","pmid":1,"article_processing_charge":"No","oa":1,"date_updated":"2025-06-30T13:21:05Z","volume":119,"author":[{"id":"4171253A-F248-11E8-B48F-1D18A9856A87","first_name":"Michal","last_name":"Hledik","full_name":"Hledik, Michal"},{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H","last_name":"Barton","full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240"},{"first_name":"Gašper","orcid":"1","last_name":"Tkačik","full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"}],"abstract":[{"lang":"eng","text":"Selection accumulates information in the genome—it guides stochastically evolving populations toward states (genotype frequencies) that would be unlikely under neutrality. This can be quantified as the Kullback–Leibler (KL) divergence between the actual distribution of genotype frequencies and the corresponding neutral distribution. First, we show that this population-level information sets an upper bound on the information at the level of genotype and phenotype, limiting how precisely they can be specified by selection. Next, we study how the accumulation and maintenance of information is limited by the cost of selection, measured as the genetic load or the relative fitness variance, both of which we connect to the control-theoretic KL cost of control. The information accumulation rate is upper bounded by the population size times the cost of selection. This bound is very general, and applies across models (Wright–Fisher, Moran, diffusion) and to arbitrary forms of selection, mutation, and recombination. Finally, the cost of maintaining information depends on how it is encoded: Specifying a single allele out of two is expensive, but one bit encoded among many weakly specified loci (as in a polygenic trait) is cheap."}],"citation":{"apa":"Hledik, M., Barton, N. H., & Tkačik, G. (2022). Accumulation and maintenance of information in evolution. Proceedings of the National Academy of Sciences. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2123152119","ieee":"M. Hledik, N. H. Barton, and G. Tkačik, “Accumulation and maintenance of information in evolution,” Proceedings of the National Academy of Sciences, vol. 119, no. 36. Proceedings of the National Academy of Sciences, 2022.","chicago":"Hledik, Michal, Nicholas H Barton, and Gašper Tkačik. “Accumulation and Maintenance of Information in Evolution.” Proceedings of the National Academy of Sciences. Proceedings of the National Academy of Sciences, 2022. https://doi.org/10.1073/pnas.2123152119.","ama":"Hledik M, Barton NH, Tkačik G. Accumulation and maintenance of information in evolution. Proceedings of the National Academy of Sciences. 2022;119(36). doi:10.1073/pnas.2123152119","mla":"Hledik, Michal, et al. “Accumulation and Maintenance of Information in Evolution.” Proceedings of the National Academy of Sciences, vol. 119, no. 36, e2123152119, Proceedings of the National Academy of Sciences, 2022, doi:10.1073/pnas.2123152119.","short":"M. Hledik, N.H. Barton, G. Tkačik, Proceedings of the National Academy of Sciences 119 (2022).","ista":"Hledik M, Barton NH, Tkačik G. 2022. Accumulation and maintenance of information in evolution. Proceedings of the National Academy of Sciences. 119(36), e2123152119."},"publication_status":"published","ddc":["570"],"related_material":{"record":[{"status":"public","id":"15020","relation":"dissertation_contains"}]},"article_number":"e2123152119","isi":1,"tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"external_id":{"pmid":["36037343"],"isi":["000889278400014"]},"title":"Accumulation and maintenance of information in evolution","ec_funded":1,"year":"2022","doi":"10.1073/pnas.2123152119"},{"department":[{"_id":"NiBa"}],"has_accepted_license":"1","date_created":"2021-05-23T22:01:43Z","file":[{"relation":"main_file","content_type":"application/pdf","creator":"kschuh","file_id":"9425","success":1,"access_level":"open_access","date_updated":"2021-05-25T14:09:03Z","file_size":726759,"file_name":"2021_BiologyLetters_Lagator.pdf","checksum":"9c13c1f5af7609c97c741f11d293188a","date_created":"2021-05-25T14:09:03Z"}],"date_published":"2021-05-12T00:00:00Z","month":"05","language":[{"iso":"eng"}],"scopus_import":"1","publisher":"Royal Society of London","file_date_updated":"2021-05-25T14:09:03Z","publication":"Biology letters","issue":"5","type":"journal_article","day":"12","status":"public","intvolume":" 17","article_number":"20200913","isi":1,"tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"ddc":["570"],"ec_funded":1,"year":"2021","doi":"10.1098/rsbl.2020.0913","external_id":{"pmid":[" 33975485"],"isi":["000651501400001"]},"title":"Adaptation at different points along antibiotic concentration gradients","article_processing_charge":"No","date_updated":"2025-05-28T11:42:50Z","oa":1,"volume":17,"oa_version":"Published Version","quality_controlled":"1","project":[{"name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"250152"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","acknowledgement":"We would like to thank Martin Ackermann, Camilo Barbosa, Nick Barton, Jonathan Bollback, Sebastian Bonhoeffer, Nick Colegrave, Calin Guet, Alex Hall, Sally Otto, Tiago Paixao, Srdjan Sarikas, Hinrich Schulenburg, Marjon de Vos and Michael Whitlock for insightful support.","publication_identifier":{"eissn":["1744957X"]},"pmid":1,"_id":"9410","citation":{"short":"M. Lagator, H. Uecker, P. Neve, Biology Letters 17 (2021).","ista":"Lagator M, Uecker H, Neve P. 2021. Adaptation at different points along antibiotic concentration gradients. Biology letters. 17(5), 20200913.","ama":"Lagator M, Uecker H, Neve P. Adaptation at different points along antibiotic concentration gradients. Biology letters. 2021;17(5). doi:10.1098/rsbl.2020.0913","mla":"Lagator, Mato, et al. “Adaptation at Different Points along Antibiotic Concentration Gradients.” Biology Letters, vol. 17, no. 5, 20200913, Royal Society of London, 2021, doi:10.1098/rsbl.2020.0913.","chicago":"Lagator, Mato, Hildegard Uecker, and Paul Neve. “Adaptation at Different Points along Antibiotic Concentration Gradients.” Biology Letters. Royal Society of London, 2021. https://doi.org/10.1098/rsbl.2020.0913.","ieee":"M. Lagator, H. Uecker, and P. Neve, “Adaptation at different points along antibiotic concentration gradients,” Biology letters, vol. 17, no. 5. Royal Society of London, 2021.","apa":"Lagator, M., Uecker, H., & Neve, P. (2021). Adaptation at different points along antibiotic concentration gradients. Biology Letters. Royal Society of London. https://doi.org/10.1098/rsbl.2020.0913"},"publication_status":"published","author":[{"id":"345D25EC-F248-11E8-B48F-1D18A9856A87","first_name":"Mato","full_name":"Lagator, Mato","last_name":"Lagator"},{"first_name":"Hildegard","orcid":"0000-0001-9435-2813","full_name":"Uecker, Hildegard","last_name":"Uecker","id":"2DB8F68A-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Neve","full_name":"Neve, Paul","first_name":"Paul"}],"abstract":[{"lang":"eng","text":"Antibiotic concentrations vary dramatically in the body and the environment. Hence, understanding the dynamics of resistance evolution along antibiotic concentration gradients is critical for predicting and slowing the emergence and spread of resistance. While it has been shown that increasing the concentration of an antibiotic slows resistance evolution, how adaptation to one antibiotic concentration correlates with fitness at other points along the gradient has not received much attention. Here, we selected populations of Escherichia coli at several points along a concentration gradient for three different antibiotics, asking how rapidly resistance evolved and whether populations became specialized to the antibiotic concentration they were selected on. Populations selected at higher concentrations evolved resistance more slowly but exhibited equal or higher fitness across the whole gradient. Populations selected at lower concentrations evolved resistance rapidly, but overall fitness in the presence of antibiotics was lower. However, these populations readily adapted to higher concentrations upon subsequent selection. Our results indicate that resistance management strategies must account not only for the rates of resistance evolution but also for the fitness of evolved strains."}]},{"isi":1,"related_material":{"record":[{"relation":"popular_science","id":"5583","status":"public"}]},"ec_funded":1,"year":"2018","doi":"10.1111/1755-0998.12782","title":"Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering","external_id":{"isi":["000441753000007"]},"article_processing_charge":"No","date_updated":"2025-05-28T11:42:43Z","volume":18,"oa_version":"None","project":[{"_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","grant_number":"250152"}],"quality_controlled":"1","acknowledgement":"ERC, Grant/Award Number: 250152","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"286","citation":{"ama":"Ellis T, Field D, Barton NH. Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering. Molecular Ecology Resources. 2018;18(5):988-999. doi:10.1111/1755-0998.12782","mla":"Ellis, Thomas, et al. “Efficient Inference of Paternity and Sibship Inference given Known Maternity via Hierarchical Clustering.” Molecular Ecology Resources, vol. 18, no. 5, Wiley, 2018, pp. 988–99, doi:10.1111/1755-0998.12782.","ista":"Ellis T, Field D, Barton NH. 2018. Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering. Molecular Ecology Resources. 18(5), 988–999.","short":"T. Ellis, D. Field, N.H. Barton, Molecular Ecology Resources 18 (2018) 988–999.","apa":"Ellis, T., Field, D., & Barton, N. H. (2018). Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering. Molecular Ecology Resources. Wiley. https://doi.org/10.1111/1755-0998.12782","ieee":"T. Ellis, D. Field, and N. H. Barton, “Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering,” Molecular Ecology Resources, vol. 18, no. 5. Wiley, pp. 988–999, 2018.","chicago":"Ellis, Thomas, David Field, and Nicholas H Barton. “Efficient Inference of Paternity and Sibship Inference given Known Maternity via Hierarchical Clustering.” Molecular Ecology Resources. Wiley, 2018. https://doi.org/10.1111/1755-0998.12782."},"publication_status":"published","author":[{"first_name":"Thomas","full_name":"Ellis, Thomas","last_name":"Ellis","orcid":"0000-0002-8511-0254","id":"3153D6D4-F248-11E8-B48F-1D18A9856A87"},{"id":"419049E2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4014-8478","last_name":"Field","full_name":"Field, David","first_name":"David"},{"orcid":"0000-0002-8548-5240","last_name":"Barton","full_name":"Barton, Nicholas H","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"}],"abstract":[{"lang":"eng","text":"Pedigree and sibship reconstruction are important methods in quantifying relationships and fitness of individuals in natural populations. Current methods employ a Markov chain-based algorithm to explore plausible possible pedigrees iteratively. This provides accurate results, but is time-consuming. Here, we develop a method to infer sibship and paternity relationships from half-sibling arrays of known maternity using hierarchical clustering. Given 50 or more unlinked SNP markers and empirically derived error rates, the method performs as well as the widely used package Colony, but is faster by two orders of magnitude. Using simulations, we show that the method performs well across contrasting mating scenarios, even when samples are large. We then apply the method to open-pollinated arrays of the snapdragon Antirrhinum majus and find evidence for a high degree of multiple mating. Although we focus on diploid SNP data, the method does not depend on marker type and as such has broad applications in nonmodel systems. "}],"department":[{"_id":"NiBa"}],"date_created":"2018-12-11T11:45:37Z","date_published":"2018-09-01T00:00:00Z","month":"09","language":[{"iso":"eng"}],"scopus_import":"1","publisher":"Wiley","page":"988 - 999","publication":"Molecular Ecology Resources","issue":"5","type":"journal_article","day":"01","status":"public","intvolume":" 18"},{"title":"Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system","external_id":{"isi":["000437171700017"]},"year":"2018","doi":"10.1534/genetics.118.300748","ec_funded":1,"related_material":{"record":[{"status":"public","id":"9813","relation":"research_data"}],"link":[{"description":"News on IST Homepage","relation":"press_release","url":"https://ist.ac.at/en/news/recognizing-others-but-not-yourself-new-insights-into-the-evolution-of-plant-mating/"}]},"main_file_link":[{"open_access":"1","url":"https://www.biorxiv.org/node/80098.abstract"}],"isi":1,"abstract":[{"lang":"eng","text":"Self-incompatibility (SI) is a genetically based recognition system that functions to prevent self-fertilization and mating among related plants. An enduring puzzle in SI is how the high diversity observed in nature arises and is maintained. Based on the underlying recognition mechanism, SI can be classified into two main groups: self- and non-self recognition. Most work has focused on diversification within self-recognition systems despite expected differences between the two groups in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic population genetic model and stochastic simulations to investigate how novel S-haplotypes evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI system. For this model the pathways for diversification involve either the maintenance or breakdown of SI and can vary in the order of mutations of the female (SRNase) and male (SLF) components. We show analytically that diversification can occur with high inbreeding depression and self-pollination, but this varies with evolutionary pathway and level of completeness (which determines the number of potential mating partners in the population), and in general is more likely for lower haplotype number. The conditions for diversification are broader in stochastic simulations of finite population size. However, the number of haplotypes observed under high inbreeding and moderate to high self-pollination is less than that commonly observed in nature. Diversification was observed through pathways that maintain SI as well as through self-compatible intermediates. Yet the lifespan of diversified haplotypes was sensitive to their level of completeness. By examining diversification in a non-self recognition SI system, this model extends our understanding of the evolution and maintenance of haplotype diversity observed in a self recognition system common in flowering plants."}],"author":[{"id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","first_name":"Katarina","orcid":"0000-0002-7214-0171","full_name":"Bodova, Katarina","last_name":"Bodova"},{"full_name":"Priklopil, Tadeas","last_name":"Priklopil","first_name":"Tadeas","id":"3C869AA0-F248-11E8-B48F-1D18A9856A87"},{"id":"419049E2-F248-11E8-B48F-1D18A9856A87","first_name":"David","orcid":"0000-0002-4014-8478","last_name":"Field","full_name":"Field, David"},{"first_name":"Nicholas H","last_name":"Barton","full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Melinda","orcid":"0000-0001-6118-0541","full_name":"Pickup, Melinda","last_name":"Pickup","id":"2C78037E-F248-11E8-B48F-1D18A9856A87"}],"citation":{"ama":"Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. 2018;209(3):861-883. doi:10.1534/genetics.118.300748","mla":"Bodova, Katarina, et al. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” Genetics, vol. 209, no. 3, Genetics Society of America, 2018, pp. 861–83, doi:10.1534/genetics.118.300748.","ista":"Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. 209(3), 861–883.","short":"K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, Genetics 209 (2018) 861–883.","apa":"Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018). Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.118.300748","ieee":"K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system,” Genetics, vol. 209, no. 3. Genetics Society of America, pp. 861–883, 2018.","chicago":"Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and Melinda Pickup. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” Genetics. Genetics Society of America, 2018. https://doi.org/10.1534/genetics.118.300748."},"publication_status":"published","_id":"316","project":[{"call_identifier":"FP7","name":"Mating system and the evolutionary dynamics of hybrid zones","_id":"25B36484-B435-11E9-9278-68D0E5697425","grant_number":"329960"},{"name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"250152"},{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"}],"oa_version":"Preprint","quality_controlled":"1","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","article_processing_charge":"No","volume":209,"oa":1,"date_updated":"2025-05-28T11:42:44Z","scopus_import":"1","publisher":"Genetics Society of America","language":[{"iso":"eng"}],"month":"07","date_published":"2018-07-01T00:00:00Z","article_type":"original","date_created":"2018-12-11T11:45:47Z","department":[{"_id":"NiBa"},{"_id":"GaTk"}],"intvolume":" 209","status":"public","day":"01","type":"journal_article","publication":"Genetics","issue":"3","page":"861-883"},{"file":[{"relation":"main_file","content_type":"application/pdf","creator":"nbarton","file_id":"7199","access_level":"open_access","date_updated":"2020-07-14T12:47:09Z","file_size":2287682,"file_name":"bartonetheridge.pdf","checksum":"0b96f6db47e3e91b5e7d103b847c239d","date_created":"2019-12-21T09:36:39Z"}],"date_created":"2018-12-11T11:47:12Z","department":[{"_id":"NiBa"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"publisher":"Academic Press","scopus_import":"1","date_published":"2018-07-01T00:00:00Z","article_type":"original","month":"07","page":"110-127","file_date_updated":"2020-07-14T12:47:09Z","issue":"7","publication":"Theoretical Population Biology","status":"public","intvolume":" 122","type":"journal_article","day":"01","ddc":["519","576"],"related_material":{"record":[{"status":"public","relation":"research_data","id":"9842"}]},"isi":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","image":"/images/cc_by_nc.png","name":"Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)","short":"CC BY-NC (4.0)"},"external_id":{"isi":["000440392900014"]},"title":"Establishment in a new habitat by polygenic adaptation","ec_funded":1,"doi":"10.1016/j.tpb.2017.11.007","year":"2018","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","quality_controlled":"1","oa_version":"Submitted Version","project":[{"call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152"}],"_id":"564","oa":1,"date_updated":"2025-05-28T11:42:45Z","volume":122,"publist_id":"7250","article_processing_charge":"No","author":[{"full_name":"Barton, Nicholas H","last_name":"Barton","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Alison","full_name":"Etheridge, Alison","last_name":"Etheridge"}],"abstract":[{"lang":"eng","text":"Maladapted individuals can only colonise a new habitat if they can evolve a\r\npositive growth rate fast enough to avoid extinction, a process known as evolutionary\r\nrescue. We treat log fitness at low density in the new habitat as a\r\nsingle polygenic trait and thus use the infinitesimal model to follow the evolution\r\nof the growth rate; this assumes that the trait values of offspring of a\r\nsexual union are normally distributed around the mean of the parents’ trait\r\nvalues, with variance that depends only on the parents’ relatedness. The\r\nprobability that a single migrant can establish depends on just two parameters:\r\nthe mean and genetic variance of the trait in the source population.\r\nThe chance of success becomes small if migrants come from a population\r\nwith mean growth rate in the new habitat more than a few standard deviations\r\nbelow zero; this chance depends roughly equally on the probability\r\nthat the initial founder is unusually fit, and on the subsequent increase in\r\ngrowth rate of its offspring as a result of selection. The loss of genetic variation\r\nduring the founding event is substantial, but highly variable. With\r\ncontinued migration at rate M, establishment is inevitable; when migration\r\nis rare, the expected time to establishment decreases inversely with M.\r\nHowever, above a threshold migration rate, the population may be trapped\r\nin a ‘sink’ state, in which adaptation is held back by gene flow; above this\r\nthreshold, the expected time to establishment increases exponentially with M. This threshold behaviour is captured by a deterministic approximation,\r\nwhich assumes a Gaussian distribution of the trait in the founder population\r\nwith mean and variance evolving deterministically. By assuming a constant\r\ngenetic variance, we also develop a diffusion approximation for the joint distribution\r\nof population size and trait mean, which extends to include stabilising\r\nselection and density regulation. Divergence of the population from its\r\nancestors causes partial reproductive isolation, which we measure through\r\nthe reproductive value of migrants into the newly established population."}],"publication_status":"published","citation":{"ista":"Barton NH, Etheridge A. 2018. Establishment in a new habitat by polygenic adaptation. Theoretical Population Biology. 122(7), 110–127.","short":"N.H. Barton, A. Etheridge, Theoretical Population Biology 122 (2018) 110–127.","ama":"Barton NH, Etheridge A. Establishment in a new habitat by polygenic adaptation. Theoretical Population Biology. 2018;122(7):110-127. doi:10.1016/j.tpb.2017.11.007","mla":"Barton, Nicholas H., and Alison Etheridge. “Establishment in a New Habitat by Polygenic Adaptation.” Theoretical Population Biology, vol. 122, no. 7, Academic Press, 2018, pp. 110–27, doi:10.1016/j.tpb.2017.11.007.","chicago":"Barton, Nicholas H, and Alison Etheridge. “Establishment in a New Habitat by Polygenic Adaptation.” Theoretical Population Biology. Academic Press, 2018. https://doi.org/10.1016/j.tpb.2017.11.007.","apa":"Barton, N. H., & Etheridge, A. (2018). Establishment in a new habitat by polygenic adaptation. Theoretical Population Biology. Academic Press. https://doi.org/10.1016/j.tpb.2017.11.007","ieee":"N. H. Barton and A. Etheridge, “Establishment in a new habitat by polygenic adaptation,” Theoretical Population Biology, vol. 122, no. 7. Academic Press, pp. 110–127, 2018."}},{"intvolume":" 205","status":"public","day":"01","type":"journal_article","issue":"3","publication":"Genetics","page":"1335 - 1351","publisher":"Genetics Society of America","scopus_import":"1","language":[{"iso":"eng"}],"month":"03","date_published":"2017-03-01T00:00:00Z","date_created":"2018-12-11T11:50:00Z","department":[{"_id":"NiBa"}],"abstract":[{"lang":"eng","text":"Recently it has become feasible to detect long blocks of nearly identical sequence shared between pairs of genomes. These IBD blocks are direct traces of recent coalescence events and, as such, contain ample signal to infer recent demography. Here, we examine sharing of such blocks in two-dimensional populations with local migration. Using a diffusion approximation to trace genetic ancestry, we derive analytical formulae for patterns of isolation by distance of IBD blocks, which can also incorporate recent population density changes. We introduce an inference scheme that uses a composite likelihood approach to fit these formulae. We then extensively evaluate our theory and inference method on a range of scenarios using simulated data. We first validate the diffusion approximation by showing that the theoretical results closely match the simulated block sharing patterns. We then demonstrate that our inference scheme can accurately and robustly infer dispersal rate and effective density, as well as bounds on recent dynamics of population density. To demonstrate an application, we use our estimation scheme to explore the fit of a diffusion model to Eastern European samples in the POPRES data set. We show that ancestry diffusing with a rate of σ ≈ 50–100 km/√gen during the last centuries, combined with accelerating population growth, can explain the observed exponential decay of block sharing with increasing pairwise sample distance."}],"author":[{"full_name":"Ringbauer, Harald","last_name":"Ringbauer","orcid":"0000-0002-4884-9682","first_name":"Harald","id":"417FCFF4-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Coop, Graham","last_name":"Coop","first_name":"Graham"},{"orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","last_name":"Barton","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"}],"publication_status":"published","citation":{"ama":"Ringbauer H, Coop G, Barton NH. Inferring recent demography from isolation by distance of long shared sequence blocks. Genetics. 2017;205(3):1335-1351. doi:10.1534/genetics.116.196220","mla":"Ringbauer, Harald, et al. “Inferring Recent Demography from Isolation by Distance of Long Shared Sequence Blocks.” Genetics, vol. 205, no. 3, Genetics Society of America, 2017, pp. 1335–51, doi:10.1534/genetics.116.196220.","ista":"Ringbauer H, Coop G, Barton NH. 2017. Inferring recent demography from isolation by distance of long shared sequence blocks. Genetics. 205(3), 1335–1351.","short":"H. Ringbauer, G. Coop, N.H. Barton, Genetics 205 (2017) 1335–1351.","apa":"Ringbauer, H., Coop, G., & Barton, N. H. (2017). Inferring recent demography from isolation by distance of long shared sequence blocks. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.116.196220","ieee":"H. Ringbauer, G. Coop, and N. H. Barton, “Inferring recent demography from isolation by distance of long shared sequence blocks,” Genetics, vol. 205, no. 3. Genetics Society of America, pp. 1335–1351, 2017.","chicago":"Ringbauer, Harald, Graham Coop, and Nicholas H Barton. “Inferring Recent Demography from Isolation by Distance of Long Shared Sequence Blocks.” Genetics. Genetics Society of America, 2017. https://doi.org/10.1534/genetics.116.196220."},"_id":"1074","publication_identifier":{"issn":["00166731"]},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","quality_controlled":"1","project":[{"name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"250152"}],"oa_version":"Preprint","publist_id":"6307","date_updated":"2025-05-28T11:42:51Z","volume":205,"oa":1,"article_processing_charge":"No","title":"Inferring recent demography from isolation by distance of long shared sequence blocks","external_id":{"isi":["000395807200023"]},"year":"2017","doi":"10.1534/genetics.116.196220","ec_funded":1,"related_material":{"record":[{"id":"200","relation":"dissertation_contains","status":"public"}]},"main_file_link":[{"open_access":"1","url":"http://www.biorxiv.org/content/early/2016/09/23/076810"}],"isi":1},{"year":"2017","doi":"10.1098/rsif.2016.0139","ec_funded":1,"title":"Evolutionary interplay between structure, energy and epistasis in the coat protein of the ϕX174 phage family","external_id":{"isi":["000393380400001"]},"tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_number":"20160139","isi":1,"related_material":{"record":[{"id":"9864","relation":"research_data","status":"public"}]},"ddc":["570"],"citation":{"ama":"Fernandes Redondo RA, de Vladar H, Włodarski T, Bollback JP. Evolutionary interplay between structure, energy and epistasis in the coat protein of the ϕX174 phage family. Journal of the Royal Society Interface. 2017;14(126). doi:10.1098/rsif.2016.0139","mla":"Fernandes Redondo, Rodrigo A., et al. “Evolutionary Interplay between Structure, Energy and Epistasis in the Coat Protein of the ΦX174 Phage Family.” Journal of the Royal Society Interface, vol. 14, no. 126, 20160139, Royal Society of London, 2017, doi:10.1098/rsif.2016.0139.","short":"R.A. Fernandes Redondo, H. de Vladar, T. Włodarski, J.P. Bollback, Journal of the Royal Society Interface 14 (2017).","ista":"Fernandes Redondo RA, de Vladar H, Włodarski T, Bollback JP. 2017. Evolutionary interplay between structure, energy and epistasis in the coat protein of the ϕX174 phage family. Journal of the Royal Society Interface. 14(126), 20160139.","apa":"Fernandes Redondo, R. A., de Vladar, H., Włodarski, T., & Bollback, J. P. (2017). Evolutionary interplay between structure, energy and epistasis in the coat protein of the ϕX174 phage family. Journal of the Royal Society Interface. Royal Society of London. https://doi.org/10.1098/rsif.2016.0139","ieee":"R. A. Fernandes Redondo, H. de Vladar, T. Włodarski, and J. P. Bollback, “Evolutionary interplay between structure, energy and epistasis in the coat protein of the ϕX174 phage family,” Journal of the Royal Society Interface, vol. 14, no. 126. Royal Society of London, 2017.","chicago":"Fernandes Redondo, Rodrigo A, Harold de Vladar, Tomasz Włodarski, and Jonathan P Bollback. “Evolutionary Interplay between Structure, Energy and Epistasis in the Coat Protein of the ΦX174 Phage Family.” Journal of the Royal Society Interface. Royal Society of London, 2017. https://doi.org/10.1098/rsif.2016.0139."},"publication_status":"published","abstract":[{"text":"Viral capsids are structurally constrained by interactions among the amino acids (AAs) of their constituent proteins. Therefore, epistasis is expected to evolve among physically interacting sites and to influence the rates of substitution. To study the evolution of epistasis, we focused on the major structural protein of the fX174 phage family by first reconstructing the ancestral protein sequences of 18 species using a Bayesian statistical framework. The inferred ancestral reconstruction differed at eight AAs, for a total of 256 possible ancestral haplotypes. For each ancestral haplotype and the extant species, we estimated, in silico, the distribution of free energies and epistasis of the capsid structure. We found that free energy has not significantly increased but epistasis has. We decomposed epistasis up to fifth order and found that higher-order epistasis sometimes compensates pairwise interactions making the free energy seem additive. The dN/dS ratio is low, suggesting strong purifying selection, and that structure is under stabilizing selection. We synthesized phages carrying ancestral haplotypes of the coat protein gene and measured their fitness experimentally. Our findings indicate that stabilizing mutations can have higher fitness, and that fitness optima do not necessarily coincide with energy minima.","lang":"eng"}],"author":[{"id":"409D5C96-F248-11E8-B48F-1D18A9856A87","full_name":"Fernandes Redondo, Rodrigo A","last_name":"Fernandes Redondo","orcid":"0000-0002-5837-2793","first_name":"Rodrigo A"},{"id":"2A181218-F248-11E8-B48F-1D18A9856A87","first_name":"Harold","full_name":"Vladar, Harold","last_name":"Vladar","orcid":"0000-0002-5985-7653"},{"first_name":"Tomasz","full_name":"Włodarski, Tomasz","last_name":"Włodarski"},{"last_name":"Bollback","full_name":"Bollback, Jonathan P","orcid":"0000-0002-4624-4612","first_name":"Jonathan P","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87"}],"article_processing_charge":"Yes (in subscription journal)","oa":1,"date_updated":"2025-05-28T11:42:51Z","publist_id":"6303","volume":14,"publication_identifier":{"issn":["17425689"]},"_id":"1077","project":[{"grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"grant_number":"648440","call_identifier":"H2020","name":"Selective Barriers to Horizontal Gene Transfer","_id":"2578D616-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","oa_version":"Published Version","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","month":"01","date_published":"2017-01-04T00:00:00Z","scopus_import":"1","publisher":"Royal Society of London","language":[{"iso":"eng"}],"has_accepted_license":"1","department":[{"_id":"NiBa"},{"_id":"JoBo"}],"date_created":"2018-12-11T11:50:01Z","file":[{"access_level":"open_access","date_updated":"2019-01-18T09:14:02Z","date_created":"2019-01-18T09:14:02Z","file_size":1092015,"file_name":"2017_JRSI_Redondo.pdf","creator":"dernst","file_id":"5843","relation":"main_file","content_type":"application/pdf","success":1}],"day":"04","type":"journal_article","intvolume":" 14","status":"public","publication":"Journal of the Royal Society Interface","issue":"126","file_date_updated":"2019-01-18T09:14:02Z"},{"ddc":["576"],"isi":1,"title":"Spatial gene frequency waves under genotype dependent dispersal","external_id":{"isi":["000393677300025"]},"pubrep_id":"727","ec_funded":1,"year":"2017","doi":"10.1534/genetics.116.193946","project":[{"grant_number":"618091","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425"},{"grant_number":"250152","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation"}],"oa_version":"Submitted Version","quality_controlled":"1","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publication_identifier":{"issn":["00166731"]},"_id":"1169","article_processing_charge":"No","volume":205,"publist_id":"6188","date_updated":"2025-05-28T11:42:46Z","oa":1,"author":[{"id":"461468AE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-824X","last_name":"Novak","full_name":"Novak, Sebastian","first_name":"Sebastian"},{"first_name":"Richard","last_name":"Kollár","full_name":"Kollár, Richard"}],"abstract":[{"lang":"eng","text":"Dispersal is a crucial factor in natural evolution, since it determines the habitat experienced by any population and defines the spatial scale of interactions between individuals. There is compelling evidence for systematic differences in dispersal characteristics within the same population, i.e., genotype-dependent dispersal. The consequences of genotype-dependent dispersal on other evolutionary phenomena, however, are poorly understood. In this article we investigate the effect of genotype-dependent dispersal on spatial gene frequency patterns, using a generalization of the classical diffusion model of selection and dispersal. Dispersal is characterized by the variance of dispersal (diffusion coefficient) and the mean displacement (directional advection term). We demonstrate that genotype-dependent dispersal may change the qualitative behavior of Fisher waves, which change from being “pulled” to being “pushed” wave fronts as the discrepancy in dispersal between genotypes increases. The speed of any wave is partitioned into components due to selection, genotype-dependent variance of dispersal, and genotype-dependent mean displacement. We apply our findings to wave fronts maintained by selection against heterozygotes. Furthermore, we identify a benefit of increased variance of dispersal, quantify its effect on the speed of the wave, and discuss the implications for the evolution of dispersal strategies."}],"citation":{"apa":"Novak, S., & Kollár, R. (2017). Spatial gene frequency waves under genotype dependent dispersal. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.116.193946","ieee":"S. Novak and R. Kollár, “Spatial gene frequency waves under genotype dependent dispersal,” Genetics, vol. 205, no. 1. Genetics Society of America, pp. 367–374, 2017.","chicago":"Novak, Sebastian, and Richard Kollár. “Spatial Gene Frequency Waves under Genotype Dependent Dispersal.” Genetics. Genetics Society of America, 2017. https://doi.org/10.1534/genetics.116.193946.","mla":"Novak, Sebastian, and Richard Kollár. “Spatial Gene Frequency Waves under Genotype Dependent Dispersal.” Genetics, vol. 205, no. 1, Genetics Society of America, 2017, pp. 367–74, doi:10.1534/genetics.116.193946.","ama":"Novak S, Kollár R. Spatial gene frequency waves under genotype dependent dispersal. Genetics. 2017;205(1):367-374. doi:10.1534/genetics.116.193946","ista":"Novak S, Kollár R. 2017. Spatial gene frequency waves under genotype dependent dispersal. Genetics. 205(1), 367–374.","short":"S. Novak, R. Kollár, Genetics 205 (2017) 367–374."},"publication_status":"published","date_created":"2018-12-11T11:50:31Z","file":[{"content_type":"application/pdf","relation":"main_file","file_id":"4833","creator":"system","file_name":"IST-2016-727-v1+1_SFC_Genetics_final.pdf","file_size":361500,"date_created":"2018-12-12T10:10:43Z","checksum":"7c8ab79cda1f92760bbbbe0f53175bfc","date_updated":"2020-07-14T12:44:37Z","access_level":"open_access"}],"department":[{"_id":"NiBa"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"scopus_import":"1","publisher":"Genetics Society of America","date_published":"2017-01-01T00:00:00Z","month":"01","file_date_updated":"2020-07-14T12:44:37Z","page":"367 - 374","publication":"Genetics","issue":"1","status":"public","intvolume":" 205","type":"journal_article","day":"01"},{"publication":"Theoretical Population Biology","file_date_updated":"2020-07-14T12:47:25Z","page":"50 - 73","day":"01","type":"journal_article","intvolume":" 118","status":"public","has_accepted_license":"1","department":[{"_id":"NiBa"}],"date_created":"2018-12-11T11:47:34Z","file":[{"creator":"system","file_id":"4964","relation":"main_file","content_type":"application/pdf","checksum":"7dd02bfcfe8f244f4a6c19091aedf2c8","date_created":"2018-12-12T10:12:45Z","file_size":1133924,"file_name":"IST-2017-908-v1+1_1-s2.0-S0040580917300886-main_1_.pdf","access_level":"open_access","date_updated":"2020-07-14T12:47:25Z"}],"month":"12","date_published":"2017-12-01T00:00:00Z","publisher":"Academic Press","scopus_import":1,"language":[{"iso":"eng"}],"publist_id":"7169","oa":1,"date_updated":"2021-01-12T08:06:50Z","volume":118,"_id":"626","publication_identifier":{"issn":["00405809"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","oa_version":"Published Version","project":[{"name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"250152"}],"publication_status":"published","citation":{"apa":"Barton, N. H., Etheridge, A., & Véber, A. (2017). The infinitesimal model: Definition derivation and implications. Theoretical Population Biology. Academic Press. https://doi.org/10.1016/j.tpb.2017.06.001","ieee":"N. H. Barton, A. Etheridge, and A. Véber, “The infinitesimal model: Definition derivation and implications,” Theoretical Population Biology, vol. 118. Academic Press, pp. 50–73, 2017.","chicago":"Barton, Nicholas H, Alison Etheridge, and Amandine Véber. “The Infinitesimal Model: Definition Derivation and Implications.” Theoretical Population Biology. Academic Press, 2017. https://doi.org/10.1016/j.tpb.2017.06.001.","mla":"Barton, Nicholas H., et al. “The Infinitesimal Model: Definition Derivation and Implications.” Theoretical Population Biology, vol. 118, Academic Press, 2017, pp. 50–73, doi:10.1016/j.tpb.2017.06.001.","ama":"Barton NH, Etheridge A, Véber A. The infinitesimal model: Definition derivation and implications. Theoretical Population Biology. 2017;118:50-73. doi:10.1016/j.tpb.2017.06.001","ista":"Barton NH, Etheridge A, Véber A. 2017. The infinitesimal model: Definition derivation and implications. Theoretical Population Biology. 118, 50–73.","short":"N.H. Barton, A. Etheridge, A. Véber, Theoretical Population Biology 118 (2017) 50–73."},"abstract":[{"lang":"eng","text":"Our focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation, population structure, …. We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1∕M. Simulations suggest that in some cases the convergence may be as fast as 1∕M."}],"author":[{"orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","last_name":"Barton","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Etheridge, Alison","last_name":"Etheridge","first_name":"Alison"},{"first_name":"Amandine","full_name":"Véber, Amandine","last_name":"Véber"}],"tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"ddc":["576"],"year":"2017","doi":"10.1016/j.tpb.2017.06.001","ec_funded":1,"pubrep_id":"908","title":"The infinitesimal model: Definition derivation and implications"},{"has_accepted_license":"1","department":[{"_id":"ToHe"},{"_id":"CaGu"},{"_id":"NiBa"}],"date_created":"2018-12-11T11:51:32Z","file":[{"file_size":755241,"file_name":"2017_ActaInformatica_Giacobbe.pdf","checksum":"4e661d9135d7f8c342e8e258dee76f3e","date_created":"2019-01-17T15:57:29Z","access_level":"open_access","date_updated":"2020-07-14T12:44:46Z","relation":"main_file","content_type":"application/pdf","file_id":"5841","creator":"dernst"}],"month":"12","date_published":"2017-12-01T00:00:00Z","publisher":"Springer","scopus_import":"1","language":[{"iso":"eng"}],"issue":"8","publication":"Acta Informatica","file_date_updated":"2020-07-14T12:44:46Z","page":"765 - 787","day":"01","type":"journal_article","intvolume":" 54","status":"public","tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"isi":1,"related_material":{"record":[{"status":"public","id":"1835","relation":"earlier_version"}]},"ddc":["006","576"],"year":"2017","doi":"10.1007/s00236-016-0278-x","ec_funded":1,"pubrep_id":"649","title":"Model checking the evolution of gene regulatory networks","external_id":{"isi":["000414343200003"]},"publist_id":"5898","date_updated":"2025-05-28T11:57:04Z","oa":1,"volume":54,"article_processing_charge":"No","_id":"1351","publication_identifier":{"issn":["00015903"]},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","oa_version":"Published Version","quality_controlled":"1","project":[{"name":"Quantitative Reactive Modeling","_id":"25EE3708-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"267989"},{"grant_number":"S 11407_N23","call_identifier":"FWF","name":"Rigorous Systems Engineering","_id":"25832EC2-B435-11E9-9278-68D0E5697425"},{"_id":"25F42A32-B435-11E9-9278-68D0E5697425","name":"The Wittgenstein Prize","call_identifier":"FWF","grant_number":"Z211"},{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"618091"},{"name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"291734"},{"grant_number":"250152","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation"}],"publication_status":"published","citation":{"apa":"Giacobbe, M., Guet, C. C., Gupta, A., Henzinger, T. A., Paixao, T., & Petrov, T. (2017). Model checking the evolution of gene regulatory networks. Acta Informatica. Springer. https://doi.org/10.1007/s00236-016-0278-x","ieee":"M. Giacobbe, C. C. Guet, A. Gupta, T. A. Henzinger, T. Paixao, and T. Petrov, “Model checking the evolution of gene regulatory networks,” Acta Informatica, vol. 54, no. 8. Springer, pp. 765–787, 2017.","chicago":"Giacobbe, Mirco, Calin C Guet, Ashutosh Gupta, Thomas A Henzinger, Tiago Paixao, and Tatjana Petrov. “Model Checking the Evolution of Gene Regulatory Networks.” Acta Informatica. Springer, 2017. https://doi.org/10.1007/s00236-016-0278-x.","ama":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. Model checking the evolution of gene regulatory networks. Acta Informatica. 2017;54(8):765-787. doi:10.1007/s00236-016-0278-x","mla":"Giacobbe, Mirco, et al. “Model Checking the Evolution of Gene Regulatory Networks.” Acta Informatica, vol. 54, no. 8, Springer, 2017, pp. 765–87, doi:10.1007/s00236-016-0278-x.","short":"M. Giacobbe, C.C. Guet, A. Gupta, T.A. Henzinger, T. Paixao, T. Petrov, Acta Informatica 54 (2017) 765–787.","ista":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. 2017. Model checking the evolution of gene regulatory networks. Acta Informatica. 54(8), 765–787."},"abstract":[{"text":"The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs—an important problem of interest in evolutionary biology—more efficiently than the classical simulation method. We specify the property in linear temporal logic. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights.","lang":"eng"}],"author":[{"orcid":"0000-0001-8180-0904","last_name":"Giacobbe","full_name":"Giacobbe, Mirco","first_name":"Mirco","id":"3444EA5E-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Guet","full_name":"Guet, Calin C","orcid":"0000-0001-6220-2052","first_name":"Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87"},{"id":"335E5684-F248-11E8-B48F-1D18A9856A87","full_name":"Gupta, Ashutosh","last_name":"Gupta","first_name":"Ashutosh"},{"orcid":"0000−0002−2985−7724","last_name":"Henzinger","full_name":"Henzinger, Thomas A","first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago","last_name":"Paixao","first_name":"Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87"},{"id":"3D5811FC-F248-11E8-B48F-1D18A9856A87","first_name":"Tatjana","last_name":"Petrov","full_name":"Petrov, Tatjana","orcid":"0000-0002-9041-0905"}]},{"date_published":"2017-08-09T00:00:00Z","month":"08","language":[{"iso":"eng"}],"scopus_import":"1","publisher":"Nature Publishing Group","department":[{"_id":"GaTk"},{"_id":"NiBa"}],"has_accepted_license":"1","file":[{"file_id":"5064","creator":"system","relation":"main_file","content_type":"application/pdf","access_level":"open_access","date_updated":"2020-07-14T12:48:16Z","checksum":"29a1b5db458048d3bd5c67e0e2a56818","date_created":"2018-12-12T10:14:14Z","file_size":998157,"file_name":"IST-2017-864-v1+1_s41467-017-00238-8.pdf"},{"file_size":9715993,"file_name":"IST-2017-864-v1+2_41467_2017_238_MOESM1_ESM.pdf","checksum":"7b78401e52a576cf3e6bbf8d0abadc17","date_created":"2018-12-12T10:14:15Z","access_level":"open_access","date_updated":"2020-07-14T12:48:16Z","relation":"main_file","content_type":"application/pdf","creator":"system","file_id":"5065"}],"date_created":"2018-12-11T11:49:23Z","type":"journal_article","day":"09","status":"public","intvolume":" 8","file_date_updated":"2020-07-14T12:48:16Z","publication":"Nature Communications","issue":"1","ec_funded":1,"doi":"10.1038/s41467-017-00238-8","year":"2017","external_id":{"isi":["000407198800005"]},"title":"Evolution of new regulatory functions on biophysically realistic fitness landscapes","pubrep_id":"864","isi":1,"article_number":"216","tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"ddc":["539","576"],"related_material":{"record":[{"status":"public","id":"6071","relation":"dissertation_contains"}]},"citation":{"chicago":"Friedlander, Tamar, Roshan Prizak, Nicholas H Barton, and Gašper Tkačik. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-00238-8.","ieee":"T. Friedlander, R. Prizak, N. H. Barton, and G. Tkačik, “Evolution of new regulatory functions on biophysically realistic fitness landscapes,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017.","apa":"Friedlander, T., Prizak, R., Barton, N. H., & Tkačik, G. (2017). Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-00238-8","short":"T. Friedlander, R. Prizak, N.H. Barton, G. Tkačik, Nature Communications 8 (2017).","ista":"Friedlander T, Prizak R, Barton NH, Tkačik G. 2017. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 8(1), 216.","ama":"Friedlander T, Prizak R, Barton NH, Tkačik G. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-00238-8","mla":"Friedlander, Tamar, et al. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” Nature Communications, vol. 8, no. 1, 216, Nature Publishing Group, 2017, doi:10.1038/s41467-017-00238-8."},"publication_status":"published","author":[{"first_name":"Tamar","last_name":"Friedlander","full_name":"Friedlander, Tamar","id":"36A5845C-F248-11E8-B48F-1D18A9856A87"},{"id":"4456104E-F248-11E8-B48F-1D18A9856A87","first_name":"Roshan","last_name":"Prizak","full_name":"Prizak, Roshan"},{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H","last_name":"Barton","orcid":"0000-0002-8548-5240","first_name":"Nicholas H"},{"last_name":"Tkacik","full_name":"Tkacik, Gasper","orcid":"0000-0002-6699-1455","first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"}],"abstract":[{"lang":"eng","text":"Gene expression is controlled by networks of regulatory proteins that interact specifically with external signals and DNA regulatory sequences. These interactions force the network components to co-evolve so as to continually maintain function. Yet, existing models of evolution mostly focus on isolated genetic elements. In contrast, we study the essential process by which regulatory networks grow: the duplication and subsequent specialization of network components. We synthesize a biophysical model of molecular interactions with the evolutionary framework to find the conditions and pathways by which new regulatory functions emerge. We show that specialization of new network components is usually slow, but can be drastically accelerated in the presence of regulatory crosstalk and mutations that promote promiscuous interactions between network components."}],"article_processing_charge":"Yes (in subscription journal)","oa":1,"date_updated":"2025-05-28T11:42:50Z","volume":8,"publist_id":"6459","oa_version":"Published Version","project":[{"grant_number":"291734","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme"},{"grant_number":"250152","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation"},{"grant_number":"P28844-B27","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","_id":"254E9036-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publication_identifier":{"issn":["20411723"]},"_id":"955"},{"volume":71,"publist_id":"6327","date_updated":"2025-05-28T11:42:51Z","oa":1,"article_processing_charge":"No","_id":"1063","publication_identifier":{"issn":["00143820"]},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","project":[{"grant_number":"250152","call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","oa_version":"Submitted Version","publication_status":"published","citation":{"chicago":"Uecker, Hildegard. “Evolutionary Rescue in Randomly Mating, Selfing, and Clonal Populations.” Evolution. Wiley-Blackwell, 2017. https://doi.org/10.1111/evo.13191.","ieee":"H. Uecker, “Evolutionary rescue in randomly mating, selfing, and clonal populations,” Evolution, vol. 71, no. 4. Wiley-Blackwell, pp. 845–858, 2017.","apa":"Uecker, H. (2017). Evolutionary rescue in randomly mating, selfing, and clonal populations. Evolution. Wiley-Blackwell. https://doi.org/10.1111/evo.13191","short":"H. Uecker, Evolution 71 (2017) 845–858.","ista":"Uecker H. 2017. Evolutionary rescue in randomly mating, selfing, and clonal populations. Evolution. 71(4), 845–858.","ama":"Uecker H. Evolutionary rescue in randomly mating, selfing, and clonal populations. Evolution. 2017;71(4):845-858. doi:10.1111/evo.13191","mla":"Uecker, Hildegard. “Evolutionary Rescue in Randomly Mating, Selfing, and Clonal Populations.” Evolution, vol. 71, no. 4, Wiley-Blackwell, 2017, pp. 845–58, doi:10.1111/evo.13191."},"abstract":[{"lang":"eng","text":"Severe environmental change can drive a population extinct unless the population adapts in time to the new conditions (“evolutionary rescue”). How does biparental sexual reproduction influence the chances of population persistence compared to clonal reproduction or selfing? In this article, we set up a one‐locus two‐allele model for adaptation in diploid species, where rescue is contingent on the establishment of the mutant homozygote. Reproduction can occur by random mating, selfing, or clonally. Random mating generates and destroys the rescue mutant; selfing is efficient at generating it but at the same time depletes the heterozygote, which can lead to a low mutant frequency in the standing genetic variation. Due to these (and other) antagonistic effects, we find a nontrivial dependence of population survival on the rate of sex/selfing, which is strongly influenced by the dominance coefficient of the mutation before and after the environmental change. Importantly, since mating with the wild‐type breaks the mutant homozygote up, a slow decay of the wild‐type population size can impede rescue in randomly mating populations."}],"author":[{"id":"2DB8F68A-F248-11E8-B48F-1D18A9856A87","first_name":"Hildegard","last_name":"Uecker","full_name":"Uecker, Hildegard","orcid":"0000-0001-9435-2813"}],"isi":1,"main_file_link":[{"url":"http://biorxiv.org/content/early/2016/10/14/081042","open_access":"1"}],"doi":"10.1111/evo.13191","year":"2017","ec_funded":1,"title":"Evolutionary rescue in randomly mating, selfing, and clonal populations","external_id":{"isi":["000398545200003"]},"issue":"4","publication":"Evolution","page":"845 - 858","day":"01","type":"journal_article","intvolume":" 71","status":"public","department":[{"_id":"NiBa"}],"date_created":"2018-12-11T11:49:57Z","month":"04","date_published":"2017-04-01T00:00:00Z","publisher":"Wiley-Blackwell","scopus_import":"1","language":[{"iso":"eng"}]},{"ec_funded":1,"doi":"10.1007/s11538-016-0244-3","year":"2017","title":"Existence of traveling waves for the generalized F–KPP equation","main_file_link":[{"url":"https://arxiv.org/abs/1607.00944","open_access":"1"}],"citation":{"chicago":"Kollár, Richard, and Sebastian Novak. “Existence of Traveling Waves for the Generalized F–KPP Equation.” Bulletin of Mathematical Biology. Springer, 2017. https://doi.org/10.1007/s11538-016-0244-3.","apa":"Kollár, R., & Novak, S. (2017). Existence of traveling waves for the generalized F–KPP equation. Bulletin of Mathematical Biology. Springer. https://doi.org/10.1007/s11538-016-0244-3","ieee":"R. Kollár and S. Novak, “Existence of traveling waves for the generalized F–KPP equation,” Bulletin of Mathematical Biology, vol. 79, no. 3. Springer, pp. 525–559, 2017.","short":"R. Kollár, S. Novak, Bulletin of Mathematical Biology 79 (2017) 525–559.","ista":"Kollár R, Novak S. 2017. Existence of traveling waves for the generalized F–KPP equation. Bulletin of Mathematical Biology. 79(3), 525–559.","mla":"Kollár, Richard, and Sebastian Novak. “Existence of Traveling Waves for the Generalized F–KPP Equation.” Bulletin of Mathematical Biology, vol. 79, no. 3, Springer, 2017, pp. 525–59, doi:10.1007/s11538-016-0244-3.","ama":"Kollár R, Novak S. Existence of traveling waves for the generalized F–KPP equation. Bulletin of Mathematical Biology. 2017;79(3):525-559. doi:10.1007/s11538-016-0244-3"},"publication_status":"published","author":[{"last_name":"Kollár","full_name":"Kollár, Richard","first_name":"Richard"},{"first_name":"Sebastian","full_name":"Novak, Sebastian","last_name":"Novak","orcid":"0000-0002-2519-824X","id":"461468AE-F248-11E8-B48F-1D18A9856A87"}],"abstract":[{"lang":"eng","text":"Variation in genotypes may be responsible for differences in dispersal rates, directional biases, and growth rates of individuals. These traits may favor certain genotypes and enhance their spatiotemporal spreading into areas occupied by the less advantageous genotypes. We study how these factors influence the speed of spreading in the case of two competing genotypes under the assumption that spatial variation of the total population is small compared to the spatial variation of the frequencies of the genotypes in the population. In that case, the dynamics of the frequency of one of the genotypes is approximately described by a generalized Fisher–Kolmogorov–Petrovskii–Piskunov (F–KPP) equation. This generalized F–KPP equation with (nonlinear) frequency-dependent diffusion and advection terms admits traveling wave solutions that characterize the invasion of the dominant genotype. Our existence results generalize the classical theory for traveling waves for the F–KPP with constant coefficients. Moreover, in the particular case of the quadratic (monostable) nonlinear growth–decay rate in the generalized F–KPP we study in detail the influence of the variance in diffusion and mean displacement rates of the two genotypes on the minimal wave propagation speed."}],"date_updated":"2025-05-28T11:42:46Z","oa":1,"volume":79,"publist_id":"6160","project":[{"grant_number":"618091","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","call_identifier":"FP7"},{"name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"250152"}],"oa_version":"Preprint","quality_controlled":"1","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","acknowledgement":"We thank Nick Barton, Katarína Bod’ová, and Sr\r\n-\r\ndan Sarikas for constructive feed-\r\nback and support. Furthermore, we would like to express our deep gratitude to the anonymous referees (one\r\nof whom, Jimmy Garnier, agreed to reveal his identity) and the editor Max Souza, for very helpful and\r\ndetailed comments and suggestions that significantly helped us to improve the manuscript. This project has\r\nreceived funding from the European Union’s Seventh Framework Programme for research, technological\r\ndevelopment and demonstration under Grant Agreement 618091 Speed of Adaptation in Population Genet-\r\nics and Evolutionary Computation (SAGE) and the European Research Council (ERC) Grant No. 250152\r\n(SN), from the Scientific Grant Agency of the Slovak Republic under the Grant 1/0459/13 and by the Slovak\r\nResearch and Development Agency under the Contract No. APVV-14-0378 (RK). RK would also like to\r\nthank IST Austria for its hospitality during the work on this project.","_id":"1191","date_published":"2017-03-01T00:00:00Z","month":"03","language":[{"iso":"eng"}],"scopus_import":1,"publisher":"Springer","department":[{"_id":"NiBa"}],"date_created":"2018-12-11T11:50:38Z","type":"journal_article","day":"01","status":"public","intvolume":" 79","page":"525-559","publication":"Bulletin of Mathematical Biology","issue":"3"},{"publication":"Heredity","page":"96 - 109","intvolume":" 118","status":"public","day":"01","type":"journal_article","date_created":"2018-12-11T11:50:40Z","department":[{"_id":"NiBa"}],"scopus_import":"1","publisher":"Nature Publishing Group","language":[{"iso":"eng"}],"month":"01","date_published":"2017-01-01T00:00:00Z","_id":"1199","project":[{"call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152"}],"oa_version":"Submitted Version","quality_controlled":"1","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","article_processing_charge":"No","publist_id":"6151","volume":118,"date_updated":"2025-05-28T11:42:47Z","oa":1,"abstract":[{"lang":"eng","text":"Much of quantitative genetics is based on the ‘infinitesimal model’, under which selection has a negligible effect on the genetic variance. This is typically justified by assuming a very large number of loci with additive effects. However, it applies even when genes interact, provided that the number of loci is large enough that selection on each of them is weak relative to random drift. In the long term, directional selection will change allele frequencies, but even then, the effects of epistasis on the ultimate change in trait mean due to selection may be modest. Stabilising selection can maintain many traits close to their optima, even when the underlying alleles are weakly selected. However, the number of traits that can be optimised is apparently limited to ~4Ne by the ‘drift load’, and this is hard to reconcile with the apparent complexity of many organisms. Just as for the mutation load, this limit can be evaded by a particular form of negative epistasis. A more robust limit is set by the variance in reproductive success. This suggests that selection accumulates information most efficiently in the infinitesimal regime, when selection on individual alleles is weak, and comparable with random drift. A review of evidence on selection strength suggests that although most variance in fitness may be because of alleles with large Nes, substantial amounts of adaptation may be because of alleles in the infinitesimal regime, in which epistasis has modest effects."}],"author":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","last_name":"Barton","first_name":"Nicholas H"}],"citation":{"apa":"Barton, N. H. (2017). How does epistasis influence the response to selection? Heredity. Nature Publishing Group. https://doi.org/10.1038/hdy.2016.109","ieee":"N. H. Barton, “How does epistasis influence the response to selection?,” Heredity, vol. 118. Nature Publishing Group, pp. 96–109, 2017.","chicago":"Barton, Nicholas H. “How Does Epistasis Influence the Response to Selection?” Heredity. Nature Publishing Group, 2017. https://doi.org/10.1038/hdy.2016.109.","ama":"Barton NH. How does epistasis influence the response to selection? Heredity. 2017;118:96-109. doi:10.1038/hdy.2016.109","mla":"Barton, Nicholas H. “How Does Epistasis Influence the Response to Selection?” Heredity, vol. 118, Nature Publishing Group, 2017, pp. 96–109, doi:10.1038/hdy.2016.109.","ista":"Barton NH. 2017. How does epistasis influence the response to selection? Heredity. 118, 96–109.","short":"N.H. Barton, Heredity 118 (2017) 96–109."},"publication_status":"published","related_material":{"record":[{"id":"9710","relation":"research_data","status":"public"}]},"isi":1,"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176114/"}],"title":"How does epistasis influence the response to selection?","external_id":{"isi":["000392229100011"]},"doi":"10.1038/hdy.2016.109","year":"2017","ec_funded":1},{"date_created":"2018-12-11T11:49:34Z","file":[{"file_id":"6329","creator":"dernst","relation":"main_file","content_type":"application/pdf","access_level":"open_access","date_updated":"2020-07-14T12:48:18Z","checksum":"6d4c38cb1347fd43620d1736c6df5c79","date_created":"2019-04-17T07:37:04Z","file_size":625260,"file_name":"2017_Evolution_Sachdeva_supplement.pdf"},{"date_updated":"2020-07-14T12:48:18Z","access_level":"open_access","file_name":"2017_Evolution_Sachdeva_article.pdf","file_size":520110,"date_created":"2019-04-17T07:37:04Z","checksum":"f1d90dd8831b44baf49b4dd176f263af","content_type":"application/pdf","relation":"main_file","file_id":"6330","creator":"dernst"}],"has_accepted_license":"1","department":[{"_id":"NiBa"}],"publisher":"Wiley-Blackwell","scopus_import":"1","language":[{"iso":"eng"}],"month":"06","date_published":"2017-06-01T00:00:00Z","issue":"6","publication":"Evolution; International Journal of Organic Evolution","page":"1478 - 1493 ","file_date_updated":"2020-07-14T12:48:18Z","intvolume":" 71","status":"public","day":"01","type":"journal_article","ddc":["576"],"isi":1,"pubrep_id":"977","title":"Divergence and evolution of assortative mating in a polygenic trait model of speciation with gene flow","external_id":{"isi":["000403014800005"],"pmid":["28419447"]},"doi":"10.1111/evo.13252","year":"2017","ec_funded":1,"pmid":1,"_id":"990","publication_identifier":{"issn":["00143820"]},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","project":[{"grant_number":"291734","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme"},{"grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"quality_controlled":"1","oa_version":"Submitted Version","publist_id":"6409","volume":71,"date_updated":"2025-05-28T11:42:51Z","oa":1,"article_processing_charge":"No","abstract":[{"lang":"eng","text":"Assortative mating is an important driver of speciation in populations with gene flow and is predicted to evolve under certain conditions in few-locus models. However, the evolution of assortment is less understood for mating based on quantitative traits, which are often characterized by high genetic variability and extensive linkage disequilibrium between trait loci. We explore this scenario for a two-deme model with migration, by considering a single polygenic trait subject to divergent viability selection across demes, as well as assortative mating and sexual selection within demes, and investigate how trait divergence is shaped by various evolutionary forces. Our analysis reveals the existence of sharp thresholds of assortment strength, at which divergence increases dramatically. We also study the evolution of assortment via invasion of modifiers of mate discrimination and show that the ES assortment strength has an intermediate value under a range of migration-selection parameters, even in diverged populations, due to subtle effects which depend sensitively on the extent of phenotypic variation within these populations. The evolutionary dynamics of the polygenic trait is studied using the hypergeometric and infinitesimal models. We further investigate the sensitivity of our results to the assumptions of the hypergeometric model, using individual-based simulations."}],"author":[{"id":"42377A0A-F248-11E8-B48F-1D18A9856A87","full_name":"Sachdeva, Himani","last_name":"Sachdeva","first_name":"Himani"},{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H","last_name":"Barton","orcid":"0000-0002-8548-5240","first_name":"Nicholas H"}],"publication_status":"published","citation":{"short":"H. Sachdeva, N.H. Barton, Evolution; International Journal of Organic Evolution 71 (2017) 1478–1493.","ista":"Sachdeva H, Barton NH. 2017. Divergence and evolution of assortative mating in a polygenic trait model of speciation with gene flow. Evolution; International Journal of Organic Evolution. 71(6), 1478–1493.","ama":"Sachdeva H, Barton NH. Divergence and evolution of assortative mating in a polygenic trait model of speciation with gene flow. Evolution; International Journal of Organic Evolution. 2017;71(6):1478-1493. doi:10.1111/evo.13252","mla":"Sachdeva, Himani, and Nicholas H. Barton. “Divergence and Evolution of Assortative Mating in a Polygenic Trait Model of Speciation with Gene Flow.” Evolution; International Journal of Organic Evolution, vol. 71, no. 6, Wiley-Blackwell, 2017, pp. 1478–93, doi:10.1111/evo.13252.","chicago":"Sachdeva, Himani, and Nicholas H Barton. “Divergence and Evolution of Assortative Mating in a Polygenic Trait Model of Speciation with Gene Flow.” Evolution; International Journal of Organic Evolution. Wiley-Blackwell, 2017. https://doi.org/10.1111/evo.13252.","apa":"Sachdeva, H., & Barton, N. H. (2017). Divergence and evolution of assortative mating in a polygenic trait model of speciation with gene flow. Evolution; International Journal of Organic Evolution. Wiley-Blackwell. https://doi.org/10.1111/evo.13252","ieee":"H. Sachdeva and N. H. Barton, “Divergence and evolution of assortative mating in a polygenic trait model of speciation with gene flow,” Evolution; International Journal of Organic Evolution, vol. 71, no. 6. Wiley-Blackwell, pp. 1478–1493, 2017."}},{"month":"04","date_published":"2016-04-01T00:00:00Z","scopus_import":1,"publisher":"Academic Press","language":[{"iso":"eng"}],"has_accepted_license":"1","department":[{"_id":"NiBa"}],"file":[{"file_id":"4865","creator":"system","content_type":"application/pdf","relation":"main_file","date_updated":"2020-07-14T12:45:07Z","access_level":"open_access","date_created":"2018-12-12T10:11:12Z","checksum":"6a65ba187994d4ad86c1c509e0ff482a","file_name":"IST-2016-465-v1+1_1-s2.0-S0040580915001094-main.pdf","file_size":1684043}],"date_created":"2018-12-11T11:53:08Z","day":"01","type":"journal_article","intvolume":" 108","status":"public","publication":"Theoretical Population Biology","page":"1 - 12","file_date_updated":"2020-07-14T12:45:07Z","year":"2016","doi":"10.1016/j.tpb.2015.10.008","ec_funded":1,"title":"Spread of pedigree versus genetic ancestry in spatially distributed populations","pubrep_id":"465","tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"ddc":["576"],"citation":{"short":"J. Kelleher, A. Etheridge, A. Véber, N.H. Barton, Theoretical Population Biology 108 (2016) 1–12.","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.","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.","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","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.","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","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."},"publication_status":"published","abstract":[{"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.","lang":"eng"}],"author":[{"last_name":"Kelleher","full_name":"Kelleher, Jerome","first_name":"Jerome"},{"first_name":"Alison","last_name":"Etheridge","full_name":"Etheridge, Alison"},{"last_name":"Véber","full_name":"Véber, Amandine","first_name":"Amandine"},{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H","full_name":"Barton, Nicholas H","last_name":"Barton","orcid":"0000-0002-8548-5240"}],"publist_id":"5524","oa":1,"volume":108,"date_updated":"2021-01-12T06:52:07Z","_id":"1631","project":[{"grant_number":"250152","call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425"}],"oa_version":"Published Version","quality_controlled":"1","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87"},{"page":"775 - 786","file_date_updated":"2020-07-14T12:45:00Z","issue":"2","publication":"Genetics","status":"public","intvolume":" 202","type":"journal_article","day":"01","date_created":"2018-12-11T11:52:29Z","file":[{"creator":"system","file_id":"5241","relation":"main_file","content_type":"application/pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:00Z","checksum":"41c9b5d72e7fe4624dd22dfe622337d5","date_created":"2018-12-12T10:16:51Z","file_size":957466,"file_name":"IST-2016-561-v1+1_Lohse_et_al_Genetics_2015.pdf"}],"department":[{"_id":"KrCh"},{"_id":"NiBa"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"publisher":"Genetics Society of America","scopus_import":"1","article_type":"original","date_published":"2016-02-01T00:00:00Z","month":"02","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","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.).","quality_controlled":"1","oa_version":"Preprint","project":[{"call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"}],"pmid":1,"_id":"1518","volume":202,"oa":1,"date_updated":"2025-05-28T11:42:48Z","publist_id":"5658","article_processing_charge":"No","author":[{"first_name":"Konrad","full_name":"Lohse, Konrad","last_name":"Lohse"},{"first_name":"Martin","last_name":"Chmelik","full_name":"Chmelik, Martin","id":"3624234E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Simon","last_name":"Martin","full_name":"Martin, Simon"},{"full_name":"Barton, Nicholas H","last_name":"Barton","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"}],"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"}],"publication_status":"published","citation":{"short":"K. Lohse, M. Chmelik, S. Martin, N.H. Barton, Genetics 202 (2016) 775–786.","ista":"Lohse K, Chmelik M, Martin S, Barton NH. 2016. Efficient strategies for calculating blockwise likelihoods under the coalescent. Genetics. 202(2), 775–786.","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","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.","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.","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.","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"},"ddc":["570"],"pubrep_id":"561","title":"Efficient strategies for calculating blockwise likelihoods under the coalescent","external_id":{"pmid":["26715666"]},"ec_funded":1,"doi":"10.1534/genetics.115.183814","year":"2016"},{"department":[{"_id":"GaTk"},{"_id":"NiBa"},{"_id":"CaGu"}],"has_accepted_license":"1","date_created":"2018-12-11T11:51:34Z","file":[{"content_type":"application/pdf","relation":"main_file","file_id":"4919","creator":"system","date_updated":"2020-07-14T12:44:46Z","access_level":"open_access","file_name":"IST-2016-627-v1+1_ncomms12307.pdf","file_size":861805,"date_created":"2018-12-12T10:12:01Z","checksum":"fe3f3a1526d180b29fe691ab11435b78"},{"relation":"main_file","content_type":"application/pdf","creator":"system","file_id":"4920","file_size":1084703,"file_name":"IST-2016-627-v1+2_ncomms12307-s1.pdf","checksum":"164864a1a675f3ad80e9917c27aba07f","date_created":"2018-12-12T10:12:02Z","access_level":"open_access","date_updated":"2020-07-14T12:44:46Z"}],"date_published":"2016-08-04T00:00:00Z","month":"08","language":[{"iso":"eng"}],"scopus_import":1,"publisher":"Nature Publishing Group","file_date_updated":"2020-07-14T12:44:46Z","publication":"Nature Communications","type":"journal_article","day":"04","status":"public","intvolume":" 7","article_number":"12307","tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"ddc":["576"],"related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"6071"}]},"ec_funded":1,"year":"2016","doi":"10.1038/ncomms12307","title":"Intrinsic limits to gene regulation by global crosstalk","pubrep_id":"627","publist_id":"5887","volume":7,"date_updated":"2023-09-07T12:53:49Z","oa":1,"oa_version":"Published Version","project":[{"name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"291734"},{"grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF","grant_number":"P28844-B27"}],"quality_controlled":"1","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1358","citation":{"ama":"Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 2016;7. doi:10.1038/ncomms12307","mla":"Friedlander, Tamar, et al. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications, vol. 7, 12307, Nature Publishing Group, 2016, doi:10.1038/ncomms12307.","short":"T. Friedlander, R. Prizak, C.C. Guet, N.H. Barton, G. Tkačik, Nature Communications 7 (2016).","ista":"Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. 2016. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 7, 12307.","apa":"Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., & Tkačik, G. (2016). Intrinsic limits to gene regulation by global crosstalk. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms12307","ieee":"T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkačik, “Intrinsic limits to gene regulation by global crosstalk,” Nature Communications, vol. 7. Nature Publishing Group, 2016.","chicago":"Friedlander, Tamar, Roshan Prizak, Calin C Guet, Nicholas H Barton, and Gašper Tkačik. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms12307."},"publication_status":"published","author":[{"last_name":"Friedlander","full_name":"Friedlander, Tamar","first_name":"Tamar","id":"36A5845C-F248-11E8-B48F-1D18A9856A87"},{"id":"4456104E-F248-11E8-B48F-1D18A9856A87","first_name":"Roshan","full_name":"Prizak, Roshan","last_name":"Prizak"},{"first_name":"Calin C","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-8548-5240","last_name":"Barton","full_name":"Barton, Nicholas H","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Tkacik","full_name":"Tkacik, Gasper","orcid":"0000-0002-6699-1455","first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"}],"abstract":[{"lang":"eng","text":"Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements."}]},{"author":[{"first_name":"Tiago","orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","last_name":"Barton","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"}],"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"}],"publication_status":"published","citation":{"short":"T. Paixao, N.H. Barton, PNAS 113 (2016) 4422–4427.","ista":"Paixao T, Barton NH. 2016. The effect of gene interactions on the long-term response to selection. PNAS. 113(16), 4422–4427.","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","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.","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.","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.","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"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","quality_controlled":"1","project":[{"name":"Limits to selection in biology and in evolutionary computation","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"250152"},{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"618091"}],"pmid":1,"_id":"1359","volume":113,"oa":1,"date_updated":"2021-01-12T06:50:08Z","publist_id":"5886","article_processing_charge":"No","external_id":{"pmid":["27044080"]},"title":"The effect of gene interactions on the long-term response to selection","ec_funded":1,"year":"2016","doi":"10.1073/pnas.1518830113","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4843425/","open_access":"1"}],"status":"public","intvolume":" 113","type":"journal_article","day":"19","page":"4422 - 4427","issue":"16","publication":"PNAS","language":[{"iso":"eng"}],"publisher":"National Academy of Sciences","scopus_import":1,"article_type":"original","date_published":"2016-04-19T00:00:00Z","month":"04","date_created":"2018-12-11T11:51:34Z","department":[{"_id":"NiBa"},{"_id":"CaGu"}]}]