Drosophila Evolution over Space and Time (DEST): A New Population Genomics Resource

Martin Kapun, Joaquin C.B. Nunez, María Bogaerts-Márquez, Jesús Murga-Moreno, Margot Paris, Joseph Outten, Marta Coronado-Zamora, Courtney Tern, Omar Rota-Stabelli, Maria P. García Guerreiro, Sònia Casillas, Dorcas J. Orengo, Eva Puerma, Maaria Kankare, Lino Ometto, Volker Loeschcke, Banu S. Onder, Jessica K. Abbott, Stephen W. Schaeffer, Subhash RajpurohitEmily L. Behrman, Mads F. Schou, Thomas J.S. Merritt, Brian P. Lazzaro, Amanda Glaser-Schmitt, Eliza Argyridou, Fabian Staubach, Yun Wang, Eran Tauber, Svitlana V. Serga, Daniel K. Fabian, Kelly A. Dyer, Christopher W. Wheat, John Parsch, Sonja Grath, Marija Savic Veselinovic, Marina Stamenkovic-Radak, Mihailo Jelic, Antonio J. Buendía-Ruíz, Maria Josefa Gómez-Julián, Maria Luisa Espinosa-Jimenez, Francisco D. Gallardo-Jiménez, Aleksandra Patenkovic, Katarina Eric, Marija Tanaskovic, Anna Ullastres, Lain Guio, Miriam Merenciano, Sara Guirao-Rico, Vivien Horváth, Darren J. Obbard, Elena Pasyukova, Vladimir E. Alatortsev, Cristina P. Vieira, Jorge Vieira, Jorge Roberto Torres, Iryna Kozeretska, Oleksandr M. Maistrenko, Catherine Montchamp-Moreau, Dmitry V. Mukha, Heather E. Machado, Keric Lamb, Tânia Paulo, Leeban Yusuf, Antonio Barbadilla, Dmitri Petrov, Paul Schmidt, Josefa Gonzalez, Thomas Flatt, Alan O. Bergland

Research output: Contribution to journalArticlepeer-review

Abstract

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.

Original languageEnglish
Pages (from-to)5782-5805
Number of pages24
JournalMolecular Biology and Evolution
Volume38
Issue number12
DOIs
StatePublished - 2021

Bibliographical note

Funding Information:
We thank four reviewers and the handling editor for helpful comments on previous versions of our manuscript. We are grateful to the members of the DrosEU and DrosRTEC consortia for their long-standing support, collaboration, and for discussion. DrosEU was funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). M.K. was supported by the Austrian Science Foundation (grant no. FWF P32275); J.G. by the European Research Council (ERC) under the European Union?s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); T.F. by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of M?nster; AOB by the National Institutes of Health (R35 GM119686); M.K. by Academy of Finland grant 322980; V.L. by Danish Natural Science Research Council (FNU) (grant no. 4002-00113B); FS Deutsche Forschungsgemeinschaft (DFG) (grant no. STA1154/4-1), Project 408908608; J.P. by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; A.U. by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) (grant no. 1737/17); M.S.V., M.S.R. and M.J. by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); A.P., K.E. and M.T. by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551. The authors acknowledge Research Computing at The University of Virginia for providing computational resources and technical support that have contributed to the results reported within this publication (https://rc.virginia.edu, last accessed September 6, 2021).

Funding Information:
We thank four reviewers and the handling editor for helpful comments on previous versions of our manuscript. We are grateful to the members of the DrosEU and DrosRTEC consortia for their long-standing support, collaboration, and for discussion. DrosEU was funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). M.K. was supported by the Austrian Science Foundation (grant no. FWF P32275); J.G. by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); T.F. by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of Münster; AOB by the National Institutes of Health (R35 GM119686); M.K. by Academy of Finland grant 322980; V.L. by Danish Natural Science Research Council (FNU) (grant no. 4002-00113B); FS Deutsche Forschungsgemeinschaft (DFG) (grant no. STA1154/4-1), Project 408908608; J.P. by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; A.U. by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) (grant no. 1737/17); M.S.V., M.S.R. and M.J. by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); A.P., K.E. and M.T. by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551. The authors acknowledge Research Computing at The University of Virginia for providing computational resources and technical support that have contributed to the results reported within this publication (https://rc.virginia.edu, last accessed September 6, 2021).

Publisher Copyright:
© The Author(s) 2021.

Keywords

  • Adaptation
  • Demography
  • Drosophila melanogaster
  • Evolution
  • Population genomics
  • SNPs

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics

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