Comprehensive dataset of shotgun metagenomes from oxygen stratified freshwater lakes and ponds
Buck, M., Garcia, S. L., Fernandez, L., Martin, G., Martinez-Rodriguez, G. A., Saarenheimo, J., Zopfi, J., Bertilsson, S., & Peura, S. (2021). Comprehensive dataset of shotgun metagenomes from oxygen stratified freshwater lakes and ponds. Scientific Data, 8, Article 131. https://doi.org/10.1038/s41597-021-00910-1
Published inScientific Data
© The Author(s) 2021
Stratified lakes and ponds featuring steep oxygen gradients are significant net sources of greenhouse gases and hotspots in the carbon cycle. Despite their significant biogeochemical roles, the microbial communities, especially in the oxygen depleted compartments, are poorly known. Here, we present a comprehensive dataset including 267 shotgun metagenomes from 41 stratified lakes and ponds mainly located in the boreal and subarctic regions, but also including one tropical reservoir and one temperate lake. For most lakes and ponds, the data includes a vertical sample set spanning from the oxic surface to the anoxic bottom layer. The majority of the samples were collected during the open water period, but also a total of 29 samples were collected from under the ice. In addition to the metagenomic sequences, the dataset includes environmental variables for the samples, such as oxygen, nutrient and organic carbon concentrations. The dataset is ideal for further exploring the microbial taxonomic and functional diversity in freshwater environments and potential climate change impacts on the functioning of these ecosystems. ...
PublisherNature Publishing Group
Publication in research information system
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Additional information about fundingThe sequencing was funded by a grant from the Science for Life Laboratory biodiversity program and SciLifeLab fellows program. Sequencing was performed by the SNP&SEQ Technology Platform in Uppsala. The facility is part of the National Genomics Infrastructure (NGI) Sweden and Science for Life Laboratory. The SNP&SEQ Platform is also supported by the Swedish Research Council and the Knut and Alice Wallenberg Foundation. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under Project SNIC snic2020-5-19. We also want to thank the SciLifeLab Data Center for helping us to make the data available more freely. Samplings were funded by miscellaneous grants from the Academy of Finland, INTERACT, K&A Wallenberg Foundation, Olsson-Borgh Foundation, Swedish Research Council, and Swedish Research Council Formas. Open access funding provided by Swedish University of Agricultural Sciences. ...
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