Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Identifying the ecological forces that structure root-associated microbial communities is an essential step toward more sustainable agriculture. Legumes are widely utilized as model plants to study selective forces and their functioning in plant-microbial interactions owing to their ability to establish mutualism with rhizobia. Root nodules act as symbiotic organs to optimize the cost-benefit balance in this mutualistic relationship by modulating the number of nodules. However, it is not known whether the number of nodules is related to the structure of root-associated bacterial communities. Here, the root-associated bacterial communities of soybean grown in native soil by means of soybean cultivars with super- or normal nodulation were investigated across four developmental stages. We compared ecological processes between communities and found decreased relative importance of neutral processes for super-nodulating soybean, although the overall structures resembled those of normal-nodulating soybean. We identified the generalist core bacterial populations in each root-associated compartment, that are shared across root-associated niches, and persist through developmental stages. Within core bacterial species, the relative abundances of bacterial species in the rhizosphere microbiome were linked to host-plant functional traits and can be used to predict these traits from microbes using machine learning algorithms. These findings broaden the comprehensive understanding of the ecological forces and associations of microbiotas in various root-associated compartments and provide novel insights to integrate beneficial plant microbiomes into agricultural production to enhance plant performance.
Pubmed ID: 37640896
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
High quality ribosomal RNA databases providing comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukarya). Supplementary services include a rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. The extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. Alignment tool, SINA, is available for download as well as available for use online.
View all literature mentionsSoftware for handling and analysis of high-throughput microbiome census data.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsSoftware tool for producing high-quality circular representations of taxonomic and phylogenetic trees. Used for concise, integrative, informative, and publication-ready representations of phylogenetically- and taxonomically-driven investigation as a high-resolution microbial tree of life with taxonomic annotations.
View all literature mentionsOpen source software R package for modeling and correcting Illumina sequenced amplicon errors. Fast and accurate sample inference from amplicon data with single nucleotide resolution.
View all literature mentions