Author:
Anthony Winston E.,Allison Steven D.,Broderick Caitlin M.,Chavez Rodriguez Luciana,Clum Alicia,Cross Hugh,Eloe-Fadrosh Emiley,Evans Sarah,Fairbanks Dawson,Gallery Rachel,Gontijo Júlia Brandão,Jones Jennifer,McDermott Jason,Pett-Ridge Jennifer,Record Sydne,Rodrigues Jorge Luiz Mazza,Rodriguez-Reillo William,Shek Katherine L.,Takacs-Vesbach Tina,Blanchard Jeffrey L.
Abstract
AbstractSoil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.
Funder
U.S. Department of Energy
Publisher
Springer Science and Business Media LLC