Environmental Microbiology · 2015 · 213 citations · 78 references
AgricultureAgronomyCrop SciencesCrop EcologyMicrobial EcologySoil MicrobiologyPlant MicrobiomeRhizosphere EcologyRhizosphere MicrobiologyRoot MicrobiomeRoot-microbe InteractionsSoil Microbial BiomassCore MicrobiomeCore Microbiome AnalysisCrop YieldsDenitrificationDiazotroph DiversityDiazotrophic AssociationsNitrogen Fertilization EffectsNitrogen Fertilizer Management
Diazotrophic bacteria potentially supply substantial amounts of biologically fixed nitrogen to crops, but their occurrence may be suppressed by high nitrogen fertilizer application. Here, we explored the impact of high nitrogen fertilizer rates on the presence of diazotrophs in field-grown sugarcane with industry-standard or reduced nitrogen fertilizer application. Despite large differences in soil microbial communities between test sites, a core sugarcane root microbiome was identified. The sugarcane root-enriched core taxa overlap with those of Arabidopsis thaliana raising the possibility that certain bacterial families have had long association with plants. Reduced nitrogen fertilizer application had remarkably little effect on the core root microbiome and did not increase the relative abundance of root-associated diazotrophs or nif gene counts. Correspondingly, low nitrogen fertilizer crops had lower biomass and nitrogen content, reflecting a lack of major input of biologically fixed nitrogen, indicating that manipulating nitrogen fertilizer rates does not improve sugarcane yields by enriching diazotrophic populations under the test conditions. Standard nitrogen fertilizer crops had improved biomass and nitrogen content, and corresponding soils had higher abundances of nitrification and denitrification genes. These findings highlight that achieving a balance in maximizing crop yields and minimizing nutrient pollution associated with nitrogen fertilizer application requires understanding of how microbial communities respond to fertilizer use.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
CD-HIT: accelerated for clustering the next-generation sequencing data
LiMin Fu, Beifang Niu, Zhengwei Zhu et al. · Bioinformatics · 2012 · 11.8K citations · Full text
Life Sciences, Bioinformatics, High-performance Computing +12
Accelerated Profile HMM Searches
Sean R. Eddy · PLoS Computational Biology · 2011 · 7.5K citations · Full text