{ "labelLang" : "hun", "responseDate" : "2024-03-28 11:45", "content" : { "otype" : "JournalArticle", "mtid" : 31730287, "status" : "VALIDATED", "published" : true, "comment" : "Funding Agency and Grant Number: Deutsche ForschungsgemeinschaftGerman Research Foundation (DFG) [INST 37/935-1 FUGG]; Novartis Stiftung fur Medizinisch-Biologische Forschung [17B083]; Schweizerischer Nationalfonds zur Forderung der Wissenschaftlichen ForschungAustrian Science Fund (FWF) [31003A_166448, P300PA_161014]\n Funding text: Deutsche Forschungsgemeinschaft, Grant/Award Number: INST 37/935-1 FUGG; Novartis Stiftung fur Medizinisch-Biologische Forschung, Grant/Award Number: 17B083; Schweizerischer Nationalfonds zur Forderung der Wissenschaftlichen Forschung, Grant/Award Number: 31003A_166448 and P300PA_161014\nPlant Evolutionary Ecology, Institute of Evolution & Ecology, University of Tübingen, Tübingen, Germany \n Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain \n CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, China \n Department of Biology/Ecology & Evolution, University of Fribourg, Fribourg, Switzerland \n Cited By :1 \n Export Date: 21 July 2021 \n Correspondence Address: Sun, Y.; Plant Evolutionary Ecology, Germany; email: yan.sun@unifr.ch \n Funding details: Novartis Foundation, 17B083 \n Funding details: Deutsche Forschungsgemeinschaft, DFG, 31003A_166448, INST 37/935‐1 FUGG \n Funding details: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF, P300PA_161014 \n Funding text 1: Y.S. was supported by an Advanced Postdoc.Mobility fellowship from the Swiss National Science Foundation (SNSF; Project No. P300PA_161014), with additional support from the Novartis Foundation (#17B083 to H.M.‐S. and Y.S.). Y.S. and O.B. acknowledge support by Maximilian Hanussek from the High Performance and Cloud Computing Group at the Zentrum für Datenverarbeitung of the University of Tübingen, the state of Baden‐Württemberg through bwHPC and the German Research Foundation (DFG) through grant no. INST 37/935‐1 FUGG. H.M.‐S. acknowledges funding through the Swiss National Science Foundation (project number 31003A_166448). We gratefully acknowledge the support and help of Detlef Weigel, Gautam Shirsekar, Julia Hildebrandt and Ilja Bezrukov with the DNA sequencing, Martin Kapun for their help with the pool‐seq analyses and Daniel Wegmann and Jérôme Goudet for their suggestions on how to assess selection through ratios of phenotypic and genetic divergences in our study. We also thank Kay Hodgins and Michael Martin for the draft genome of Ambrosia artemisiifolia, and two reviewers for their constructive comments on an earlier version of this manuscript. \n Funding text 2: Y.S. was supported by an Advanced Postdoc.Mobility fellowship from the Swiss National Science Foundation (SNSF; Project No. P300PA_161014), with additional support from the Novartis Foundation (#17B083 to H.M.-S. and Y.S.). Y.S. and O.B. acknowledge support by Maximilian Hanussek from the High Performance and Cloud Computing Group at the Zentrum f?r Datenverarbeitung of the University of T?bingen, the state of Baden-W?rttemberg through bwHPC and the German Research Foundation (DFG) through grant no. INST 37/935-1 FUGG. H.M.-S. acknowledges funding through the Swiss National Science Foundation (project number 31003A_166448). We gratefully acknowledge the support and help of Detlef Weigel, Gautam Shirsekar, Julia Hildebrandt and Ilja Bezrukov with the DNA sequencing, Martin Kapun for their help with the pool-seq analyses and Daniel Wegmann and J?r?me Goudet for their suggestions on how to assess selection through ratios of phenotypic and genetic divergences in our study. We also thank Kay Hodgins and Michael Martin for the draft genome of Ambrosia artemisiifolia, and two reviewers for their constructive comments on an earlier version of this manuscript. 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In an experimental evolution study with the invasive common ragweed (Ambrosia artemisiifoliaL.) we subjected replicated populations of the same initial genetic composition to simulated climate warming. Pooled DNA sequencing of parental and offspring populations showed that warming populations experienced greater genetic divergence from their parents, than control populations. In a common environment, offspring from warming populations showed more convergent phenotypes in seven out of nine plant traits, with later flowering and larger biomass, than plants from control populations. For both traits, we also found a significantly higher ratio of phenotypic to genetic differentiation across generations for warming than for control populations, indicating stronger response to selection under warming conditions. As a measure for evolutionary rate, the phenotypic and sequence divergence between generations were assessed using the Haldane metric. Our approach combining comparisons between generations (allochronic) and between treatments (synchronic) in an experimental evolutionary field study, and linking population genomic data with phenotyping analyses provided a powerful test to detect rapid responses to selection. Our findings demonstrate that ragweed populations can rapidly evolve in response to climate change within a single generation. 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