Dataset Information

Identification of Major Rhizobacterial Taxa Affected by a Glyphosate-Tolerant Soybean Line via Shotgun Metagenomic Approach.

ABSTRACT: The worldwide commercial cultivation of transgenic crops, including glyphosate-tolerant (GT) soybeans, has increased widely during the past 20 years. However, it is accompanied with a growing concern about potential effects of transgenic crops on the soil microbial communities, especially on rhizosphere bacterial communities. Our previous study found that the GT soybean line NZL06-698 (N698) significantly affected rhizosphere bacteria, including some unidentified taxa, through 16S rRNA gene (16S rDNA) V4 region amplicon deep sequencing via Illumina MiSeq. In this study, we performed 16S rDNA V5-V7 region amplicon deep sequencing via Illumina MiSeq and shotgun metagenomic approaches to identify those major taxa. Results of these processes revealed that the species richness and evenness increased in the rhizosphere bacterial communities of N698, the beta diversity of the rhizosphere bacterial communities of N698 was affected, and that certain dominant bacterial phyla and genera were related to N698 compared with its control cultivar Mengdou12. Consistent with our previous findings, this study showed that N698 affects the rhizosphere bacterial communities. In specific, N698 negatively affects Rahnella, Janthinobacterium, Stenotrophomonas, Sphingomonas and Luteibacter while positively affecting Arthrobacter, Bradyrhizobium, Ramlibacter and Nitrospira.

SUBMITTER: Lu GH

PROVIDER: S-EPMC5924556 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Publications

Identification of Major Rhizobacterial Taxa Affected by a Glyphosate-Tolerant Soybean Line via Shotgun Metagenomic Approach.

Lu Gui-Hua GH Hua Xiao-Mei XM Liang Li L Wen Zhong-Ling ZL Du Mei-Hang MH Meng Fan-Fan FF Pang Yan-Jun YJ Qi Jin-Liang JL Tang Cheng-Yi CY Yang Yong-Hua YH

Genes 20180416 4

The worldwide commercial cultivation of transgenic crops, including glyphosate-tolerant (GT) soybeans, has increased widely during the past 20 years. However, it is accompanied with a growing concern about potential effects of transgenic crops on the soil microbial communities, especially on rhizosphere bacterial communities. Our previous study found that the GT soybean line NZL06-698 (N698) significantly affected rhizosphere bacteria, including some unidentified taxa, through 16S rRNA gene (16S ...[more]

PMID: 29659545

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Project description:Metagenomics has transformed our understanding of the microbial world, allowing researchers to bypass the need to isolate and culture individual taxa and to directly characterize both the taxonomic and gene compositions of environmental samples. However, associating the genes found in a metagenomic sample with the specific taxa of origin remains a critical challenge. Existing binning methods, based on nucleotide composition or alignment to reference genomes allow only a coarse-grained classification and rely heavily on the availability of sequenced genomes from closely related taxa. Here, we introduce a novel computational framework, integrating variation in gene abundances across multiple samples with taxonomic abundance data to deconvolve metagenomic samples into taxa-specific gene profiles and to reconstruct the genomic content of community members. This assembly-free method is not bounded by various factors limiting previously described methods of metagenomic binning or metagenomic assembly and represents a fundamentally different approach to metagenomic-based genome reconstruction. An implementation of this framework is available at http://elbo.gs.washington.edu/software.html. We first describe the mathematical foundations of our framework and discuss considerations for implementing its various components. We demonstrate the ability of this framework to accurately deconvolve a set of metagenomic samples and to recover the gene content of individual taxa using synthetic metagenomic samples. We specifically characterize determinants of prediction accuracy and examine the impact of annotation errors on the reconstructed genomes. We finally apply metagenomic deconvolution to samples from the Human Microbiome Project, successfully reconstructing genus-level genomic content of various microbial genera, based solely on variation in gene count. These reconstructed genera are shown to correctly capture genus-specific properties. With the accumulation of metagenomic data, this deconvolution framework provides an essential tool for characterizing microbial taxa never before seen, laying the foundation for addressing fundamental questions concerning the taxa comprising diverse microbial communities.

Dataset Information

Identification of Major Rhizobacterial Taxa Affected by a Glyphosate-Tolerant Soybean Line via Shotgun Metagenomic Approach.

Publications

Identification of Major Rhizobacterial Taxa Affected by a Glyphosate-Tolerant Soybean Line via Shotgun Metagenomic Approach.

Similar Datasets

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