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Abstract Background and AimsNitrogenous fertilizers provide a short-lived benefit to crops in agroecosystems, but stimulate nitrification and denitrification, processes that result in nitrate pollution, N2O production, and reduced soil fertility. Recent advances in plant microbiome science suggest that genetic variation in plants can modulate the composition and activity of rhizosphere N-cycling microorganisms. Here we attempted to determine whether genetic variation exists inZea maysfor the ability to influence the rhizosphere nitrifier and denitrifier microbiome under “real-world” conventional agricultural conditions. MethodsTo capture an extensive amount of genetic diversity within maize we grew and sampled the rhizosphere microbiome of a diversity panel of germplasm that included ex-PVP inbreds (Z. maysssp.mays), ex-PVP hybrids (Z. maysssp.mays), and teosinte (Z. maysssp. mexicanaandZ. maysssp.parviglumis). From these samples, we characterized the microbiome, a suite of microbial genes involved in nitrification and denitrification and carried out N-cycling potential assays. ResultsHere we are showing that populations/genotypes of a single species can vary in their ecological interaction with denitrifers and nitrifers. Some hybrid and teosinte genotypes supported microbial communities with lower potential nitrification and potential denitrification activity in the rhizosphere, while inbred genotypes stimulated/did not inhibit these N-cycling activities. These potential differences translated to functional differences in N2O fluxes, with teosinte plots producing less GHG than maize plots. ConclusionTaken together, these results suggest thatZeagenetic variation can lead to changes in N-cycling processes that result in N leaching and N2O production, and thereby are selectable targets for crop improvement. Understanding the underlying genetic variation contributing to belowground microbiome N-cycling into our conventional agricultural system could be useful for sustainability.
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This content will become publicly available on January 1, 2027
Modeled Rates Explain a Significant Amount of Variation in Abundance for Several Key Genes in an Important Estuarine Ecosystem
Abstract Metagenomics provides insights into the potential of microorganisms to mediate key biogeochemical processes encoded in ecosystem models. Efforts have been made to model gene abundance changes, but it is unclear how much gene abundance variation can be explained by modeled biogeochemical rates alone. We compare the relative abundance of 32 genes having the potential for photosynthesis, nitrification, denitrification, and sulfur cycling with rates predicted by a model in the Chesapeake Bay. Modeled rates explained a significant amount of gene abundance variation for half of the genes examined and at least one gene involved in four of five processes examined. An average of 21.3% of gene abundance variability is explained by the modeled rates, which increases to 31.8% when considering the 16 genes with significant relationships. For photosynthesis and denitrification, rates represent the behavior of some taxonomic groups (cyanobacteria and gammaproteobacteria) better than others (eukaryotic algae and Bacteroidetes). Significant correlations between sulfur cycling rates and genes appear for oxidative but not reductive forms of the relevant genes. The marker genesamoABwere not significantly correlated with nitrification rates. However, another gene involved in nitrification but not considered a marker gene (hao) was significantly correlated. This work demonstrates modeled rates often but not always and capture a significant amount variation of genes encoding enzymes involved in the modeled processes. Other factors, like temperature‐dependent rates or cell transport, may need to be incorporated into models to explain more variation in gene abundance. Doing so could be a useful quality control for microbial processes encoded in ecosystem‐level biogeochemical models.
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- Award ID(s):
- 2319123
- PAR ID:
- 10657558
- Publisher / Repository:
- American Geophysical Union
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Biogeosciences
- Volume:
- 131
- Issue:
- 1
- ISSN:
- 2169-8953
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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