EMERGE Biology Integration Institute
Published March 18, 2025 | Version 0.0.0
Dataset Open

Stordalen Mire mire-wide survey: Relative abundances of microbial PiCRUST-inferred functional pathways

Authors/Creators

  • 1. ROR icon The Ohio State University

Description

Relative abundances of all microbial PiCRUST-inferred functional pathways for all samples, based on 16S rRNA amplicon sequencing data from a mire-wide survey (2015) and co-analyzed autochamber site samples (2014-2015).

The 16S rRNA amplicon sequencing data is available under NCBI BioProject PRJNA1236848. The sample metadata and SRA accessions are available at https://doi.org/10.5281/zenodo.15047156.

FUNDING:

  • National Aeronautics and Space Administration, Interdisciplinary Science program: From Archaea to the Atmosphere (award # NNX17AK10G).
  • National Science Foundation, Biology Integration Institutes Program: EMERGE Biology Integration Institute (award # 2022070).
  • United States Department of Energy Office of Biological and Environmental Research, Genomic Science Program: The IsoGenie Project (grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440).
  • Sequencing was performed using startup funding from the University of Arizona to Virginia Rich.
  • We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164.

Files

Files (711.7 kB)

Name Size Download all
md5:e2afd1dc09aabe674d2f134c267964a1
711.7 kB Download

Additional details

Related works

Has metadata
Dataset: 10.5281/zenodo.15047156 (DOI)
Is derived from
Dataset: https://www.ncbi.nlm.nih.gov/bioproject/1236848 (URL)

Funding

U.S. National Science Foundation
BII-Implementation: The EMERGE Institute: Identifying EMergent Ecosystem Responses through Genes-to-Ecosystems Integration 2022070
National Aeronautics and Space Administration
From Archaea to the Atmosphere: Integrating Microbial, Isotopic and Landscape-Scale Observations to Quantify Methane Emissions from Global High-Latitude Ecosystems NNX17AK10G