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


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data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in 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.

SUBMITTER: Kapun M 

PROVIDER: S-EPMC8662648 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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

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

Molecular biology and evolution 20211201 12


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 p  ...[more]

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