[{"file_date_updated":"2020-07-14T12:44:53Z","publist_id":"5798","author":[{"last_name":"Abbott","first_name":"Richard","full_name":"Abbott, Richard"},{"full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","last_name":"Barton"},{"last_name":"Good","first_name":"Jeffrey","full_name":"Good, Jeffrey"}],"date_created":"2018-12-11T11:51:51Z","date_updated":"2021-01-12T06:50:33Z","volume":25,"year":"2016","publication_status":"published","department":[{"_id":"NiBa"}],"publisher":"Wiley-Blackwell","month":"06","doi":"10.1111/mec.13685","language":[{"iso":"eng"}],"oa":1,"quality_controlled":"1","issue":"11","type":"journal_article","pubrep_id":"772","oa_version":"Submitted Version","file":[{"relation":"main_file","file_id":"4797","date_created":"2018-12-12T10:10:12Z","date_updated":"2020-07-14T12:44:53Z","checksum":"ede7d0b8a471754f71f17e2b20f3135b","file_name":"IST-2017-772-v1+1_AbbotEtAl2016-3.pdf","access_level":"open_access","file_size":226137,"content_type":"application/pdf","creator":"system"}],"_id":"1409","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","title":"Genomics of hybridization and its evolutionary consequences","ddc":["576"],"status":"public","intvolume":" 25","day":"08","has_accepted_license":"1","scopus_import":1,"date_published":"2016-06-08T00:00:00Z","publication":"Molecular Ecology","citation":{"ama":"Abbott R, Barton NH, Good J. Genomics of hybridization and its evolutionary consequences. Molecular Ecology. 2016;25(11):2325-2332. doi:10.1111/mec.13685","ista":"Abbott R, Barton NH, Good J. 2016. Genomics of hybridization and its evolutionary consequences. Molecular Ecology. 25(11), 2325–2332.","ieee":"R. Abbott, N. H. Barton, and J. Good, “Genomics of hybridization and its evolutionary consequences,” Molecular Ecology, vol. 25, no. 11. Wiley-Blackwell, pp. 2325–2332, 2016.","apa":"Abbott, R., Barton, N. H., & Good, J. (2016). Genomics of hybridization and its evolutionary consequences. Molecular Ecology. Wiley-Blackwell. https://doi.org/10.1111/mec.13685","mla":"Abbott, Richard, et al. “Genomics of Hybridization and Its Evolutionary Consequences.” Molecular Ecology, vol. 25, no. 11, Wiley-Blackwell, 2016, pp. 2325–32, doi:10.1111/mec.13685.","short":"R. Abbott, N.H. Barton, J. Good, Molecular Ecology 25 (2016) 2325–2332.","chicago":"Abbott, Richard, Nicholas H Barton, and Jeffrey Good. “Genomics of Hybridization and Its Evolutionary Consequences.” Molecular Ecology. Wiley-Blackwell, 2016. https://doi.org/10.1111/mec.13685."},"page":"2325 - 2332"},{"month":"04","project":[{"call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425"},{"grant_number":"RGP0065/2012","_id":"255008E4-B435-11E9-9278-68D0E5697425","name":"Information processing and computation in fish groups"}],"quality_controlled":"1","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1510.08344"}],"external_id":{"arxiv":["1510.08344"]},"oa":1,"language":[{"iso":"eng"}],"doi":"10.1534/genetics.115.184127","publist_id":"5787","ec_funded":1,"publisher":"Genetics Society of America","department":[{"_id":"GaTk"},{"_id":"NiBa"}],"publication_status":"published","year":"2016","volume":202,"date_created":"2018-12-11T11:51:55Z","date_updated":"2022-08-01T10:49:55Z","author":[{"last_name":"Bod'ová","first_name":"Katarína","orcid":"0000-0002-7214-0171","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","full_name":"Bod'ová, Katarína"},{"first_name":"Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper"},{"full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","last_name":"Barton"}],"scopus_import":"1","article_processing_charge":"No","day":"06","page":"1523 - 1548","citation":{"ama":"Bodova K, Tkačik G, Barton NH. A general approximation for the dynamics of quantitative traits. Genetics. 2016;202(4):1523-1548. doi:10.1534/genetics.115.184127","ista":"Bodova K, Tkačik G, Barton NH. 2016. A general approximation for the dynamics of quantitative traits. Genetics. 202(4), 1523–1548.","apa":"Bodova, K., Tkačik, G., & Barton, N. H. (2016). A general approximation for the dynamics of quantitative traits. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.115.184127","ieee":"K. Bodova, G. Tkačik, and N. H. Barton, “A general approximation for the dynamics of quantitative traits,” Genetics, vol. 202, no. 4. Genetics Society of America, pp. 1523–1548, 2016.","mla":"Bodova, Katarina, et al. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics, vol. 202, no. 4, Genetics Society of America, 2016, pp. 1523–48, doi:10.1534/genetics.115.184127.","short":"K. Bodova, G. Tkačik, N.H. Barton, Genetics 202 (2016) 1523–1548.","chicago":"Bodova, Katarina, Gašper Tkačik, and Nicholas H Barton. “A General Approximation for the Dynamics of Quantitative Traits.” Genetics. Genetics Society of America, 2016. https://doi.org/10.1534/genetics.115.184127."},"publication":"Genetics","date_published":"2016-04-06T00:00:00Z","type":"journal_article","issue":"4","abstract":[{"lang":"eng","text":"Selection, mutation, and random drift affect the dynamics of allele frequencies and consequently of quantitative traits. While the macroscopic dynamics of quantitative traits can be measured, the underlying allele frequencies are typically unobserved. Can we understand how the macroscopic observables evolve without following these microscopic processes? This problem has been studied previously by analogy with statistical mechanics: the allele frequency distribution at each time point is approximated by the stationary form, which maximizes entropy. We explore the limitations of this method when mutation is small (4Nμ < 1) so that populations are typically close to fixation, and we extend the theory in this regime to account for changes in mutation strength. We consider a single diallelic locus either under directional selection or with overdominance and then generalize to multiple unlinked biallelic loci with unequal effects. We find that the maximum-entropy approximation is remarkably accurate, even when mutation and selection change rapidly. "}],"intvolume":" 202","title":"A general approximation for the dynamics of quantitative traits","status":"public","_id":"1420","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Preprint"},{"file_date_updated":"2020-07-14T12:45:00Z","ec_funded":1,"publist_id":"5658","date_created":"2018-12-11T11:52:29Z","date_updated":"2022-05-24T09:16:22Z","volume":202,"author":[{"first_name":"Konrad","last_name":"Lohse","full_name":"Lohse, Konrad"},{"last_name":"Chmelik","first_name":"Martin","id":"3624234E-F248-11E8-B48F-1D18A9856A87","full_name":"Chmelik, Martin"},{"full_name":"Martin, Simon","last_name":"Martin","first_name":"Simon"},{"full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","last_name":"Barton"}],"publication_status":"published","department":[{"_id":"KrCh"},{"_id":"NiBa"}],"publisher":"Genetics Society of America","year":"2016","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.).","pmid":1,"month":"02","language":[{"iso":"eng"}],"doi":"10.1534/genetics.115.183814","quality_controlled":"1","project":[{"call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425"}],"oa":1,"external_id":{"pmid":["26715666"]},"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"}],"issue":"2","type":"journal_article","oa_version":"Preprint","file":[{"relation":"main_file","file_id":"5241","checksum":"41c9b5d72e7fe4624dd22dfe622337d5","date_created":"2018-12-12T10:16:51Z","date_updated":"2020-07-14T12:45:00Z","access_level":"open_access","file_name":"IST-2016-561-v1+1_Lohse_et_al_Genetics_2015.pdf","content_type":"application/pdf","file_size":957466,"creator":"system"}],"pubrep_id":"561","title":"Efficient strategies for calculating blockwise likelihoods under the coalescent","ddc":["570"],"status":"public","intvolume":" 202","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1518","day":"01","has_accepted_license":"1","article_processing_charge":"No","scopus_import":"1","date_published":"2016-02-01T00:00:00Z","article_type":"original","page":"775 - 786","publication":"Genetics","citation":{"short":"K. Lohse, M. Chmelik, S. Martin, N.H. Barton, Genetics 202 (2016) 775–786.","mla":"Lohse, Konrad, et al. “Efficient Strategies for Calculating Blockwise Likelihoods under the Coalescent.” Genetics, vol. 202, no. 2, Genetics Society of America, 2016, pp. 775–86, doi:10.1534/genetics.115.183814.","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.","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","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","ista":"Lohse K, Chmelik M, Martin S, Barton NH. 2016. Efficient strategies for calculating blockwise likelihoods under the coalescent. Genetics. 202(2), 775–786."}},{"year":"2016","publication_status":"published","department":[{"_id":"NiBa"}],"publisher":"Academic Press","author":[{"full_name":"Kelleher, Jerome","first_name":"Jerome","last_name":"Kelleher"},{"first_name":"Alison","last_name":"Etheridge","full_name":"Etheridge, Alison"},{"last_name":"Véber","first_name":"Amandine","full_name":"Véber, Amandine"},{"full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","last_name":"Barton"}],"date_created":"2018-12-11T11:53:08Z","date_updated":"2021-01-12T06:52:07Z","volume":108,"file_date_updated":"2020-07-14T12:45:07Z","publist_id":"5524","ec_funded":1,"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","project":[{"name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425"}],"doi":"10.1016/j.tpb.2015.10.008","language":[{"iso":"eng"}],"month":"04","_id":"1631","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","ddc":["576"],"status":"public","title":"Spread of pedigree versus genetic ancestry in spatially distributed populations","intvolume":" 108","pubrep_id":"465","file":[{"checksum":"6a65ba187994d4ad86c1c509e0ff482a","date_created":"2018-12-12T10:11:12Z","date_updated":"2020-07-14T12:45:07Z","relation":"main_file","file_id":"4865","content_type":"application/pdf","file_size":1684043,"creator":"system","access_level":"open_access","file_name":"IST-2016-465-v1+1_1-s2.0-S0040580915001094-main.pdf"}],"oa_version":"Published Version","type":"journal_article","abstract":[{"lang":"eng","text":"Ancestral processes are fundamental to modern population genetics and spatial structure has been the subject of intense interest for many years. Despite this interest, almost nothing is known about the distribution of the locations of pedigree or genetic ancestors. Using both spatially continuous and stepping-stone models, we show that the distribution of pedigree ancestors approaches a travelling wave, for which we develop two alternative approximations. The speed and width of the wave are sensitive to the local details of the model. After a short time, genetic ancestors spread far more slowly than pedigree ancestors, ultimately diffusing out with radius ## rather than spreading at constant speed. In contrast to the wave of pedigree ancestors, the spread of genetic ancestry is insensitive to the local details of the models."}],"publication":"Theoretical Population Biology","citation":{"short":"J. Kelleher, A. Etheridge, A. Véber, N.H. Barton, Theoretical Population Biology 108 (2016) 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.","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.","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","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.","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."},"page":"1 - 12","date_published":"2016-04-01T00:00:00Z","scopus_import":1,"day":"01","has_accepted_license":"1"},{"article_number":"e2000234","publist_id":"6200","file_date_updated":"2020-07-14T12:44:36Z","acknowledgement":"European Research Council (ERC) https://erc.europa.eu/ (grant number ERC grant 232971). PopPhyl project. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. French National Research Agency (ANR) http://www.agence-nationale-recherche.fr/en/project-based-funding-to-advance-french-research/ (grant number ANR-12-BSV7- 0011). HYSEA project.\r\nWe thank Aude Darracq, Vincent Castric, Pierre-Alexandre Gagnaire, Xavier Vekemans, and John Welch for insightful discussions. The computations were performed at the Vital-IT (http://www.vital-it.ch) Center for high-performance computing of the SIB Swiss Institute of Bioinformatics and the ISEM computing cluster at the platform Montpellier Bioinformatique et Biodiversité.","year":"2016","department":[{"_id":"BeVi"},{"_id":"NiBa"}],"publisher":"Public Library of Science","publication_status":"published","related_material":{"record":[{"status":"public","relation":"research_data","id":"9862"},{"id":"9863","relation":"research_data","status":"public"}]},"author":[{"last_name":"Roux","first_name":"Camille","full_name":"Roux, Camille"},{"first_name":"Christelle","last_name":"Fraisse","id":"32DF5794-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8441-5075","full_name":"Fraisse, Christelle"},{"full_name":"Romiguier, Jonathan","last_name":"Romiguier","first_name":"Jonathan"},{"full_name":"Anciaux, Youann","last_name":"Anciaux","first_name":"Youann"},{"full_name":"Galtier, Nicolas","first_name":"Nicolas","last_name":"Galtier"},{"first_name":"Nicolas","last_name":"Bierne","full_name":"Bierne, Nicolas"}],"volume":14,"date_updated":"2023-02-23T14:11:16Z","date_created":"2018-12-11T11:50:28Z","month":"12","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","doi":"10.1371/journal.pbio.2000234","language":[{"iso":"eng"}],"type":"journal_article","issue":"12","abstract":[{"text":"Speciation results from the progressive accumulation of mutations that decrease the probability of mating between parental populations or reduce the fitness of hybrids—the so-called species barriers. The speciation genomic literature, however, is mainly a collection of case studies, each with its own approach and specificities, such that a global view of the gradual process of evolution from one to two species is currently lacking. Of primary importance is the prevalence of gene flow between diverging entities, which is central in most species concepts and has been widely discussed in recent years. Here, we explore the continuum of speciation thanks to a comparative analysis of genomic data from 61 pairs of populations/species of animals with variable levels of divergence. Gene flow between diverging gene pools is assessed under an approximate Bayesian computation (ABC) framework. We show that the intermediate "grey zone" of speciation, in which taxonomy is often controversial, spans from 0.5% to 2% of net synonymous divergence, irrespective of species life history traits or ecology. Thanks to appropriate modeling of among-locus variation in genetic drift and introgression rate, we clarify the status of the majority of ambiguous cases and uncover a number of cryptic species. Our analysis also reveals the high incidence in animals of semi-isolated species (when some but not all loci are affected by barriers to gene flow) and highlights the intrinsic difficulty, both statistical and conceptual, of delineating species in the grey zone of speciation.","lang":"eng"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1158","intvolume":" 14","title":"Shedding light on the grey zone of speciation along a continuum of genomic divergence","status":"public","ddc":["576"],"pubrep_id":"742","oa_version":"Published Version","file":[{"relation":"main_file","file_id":"5164","date_created":"2018-12-12T10:15:42Z","date_updated":"2020-07-14T12:44:36Z","checksum":"2bab63b068a9840efd532b9ae583f9bb","file_name":"IST-2017-742-v1+1_journal.pbio.2000234.pdf","access_level":"open_access","file_size":2494348,"content_type":"application/pdf","creator":"system"}],"scopus_import":1,"has_accepted_license":"1","day":"27","citation":{"short":"C. Roux, C. Fraisse, J. Romiguier, Y. Anciaux, N. Galtier, N. Bierne, PLoS Biology 14 (2016).","mla":"Roux, Camille, et al. “Shedding Light on the Grey Zone of Speciation along a Continuum of Genomic Divergence.” PLoS Biology, vol. 14, no. 12, e2000234, Public Library of Science, 2016, doi:10.1371/journal.pbio.2000234.","chicago":"Roux, Camille, Christelle Fraisse, Jonathan Romiguier, Youann Anciaux, Nicolas Galtier, and Nicolas Bierne. “Shedding Light on the Grey Zone of Speciation along a Continuum of Genomic Divergence.” PLoS Biology. Public Library of Science, 2016. https://doi.org/10.1371/journal.pbio.2000234.","ama":"Roux C, Fraisse C, Romiguier J, Anciaux Y, Galtier N, Bierne N. Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biology. 2016;14(12). doi:10.1371/journal.pbio.2000234","ieee":"C. Roux, C. Fraisse, J. Romiguier, Y. Anciaux, N. Galtier, and N. Bierne, “Shedding light on the grey zone of speciation along a continuum of genomic divergence,” PLoS Biology, vol. 14, no. 12. Public Library of Science, 2016.","apa":"Roux, C., Fraisse, C., Romiguier, J., Anciaux, Y., Galtier, N., & Bierne, N. (2016). Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biology. Public Library of Science. https://doi.org/10.1371/journal.pbio.2000234","ista":"Roux C, Fraisse C, Romiguier J, Anciaux Y, Galtier N, Bierne N. 2016. Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biology. 14(12), e2000234."},"publication":"PLoS Biology","date_published":"2016-12-27T00:00:00Z"}]