Literature DB >> 36167926

Microbial co-occurrence network in the rhizosphere microbiome: its association with physicochemical properties and soybean yield at a regional scale.

Sarbjeet Niraula1,2, Meaghan Rose1, Woo-Suk Chang3.   

Abstract

Microbial communities in the rhizosphere play a crucial role in determining plant growth and crop yield. A few studies have been performed to evaluate the diversity and co-occurrence patterns of rhizosphere microbiomes in soybean (Glycine max) at a regional scale. Here, we used a culture-independent method to compare the bacterial communities of the soybean rhizosphere between Nebraska (NE), a high-yield state, and Oklahoma (OK), a low-yield state. It is well known that the rhizosphere microbiome is a subset of microbes that ultimately get colonized by microbial communities from the surrounding bulk soil. Therefore, we hypothesized that differences in the soybean yield are attributed to the variations in the rhizosphere microbes at taxonomic, functional, and community levels. In addition, soil physicochemical properties were also evaluated from each sampling site for comparative study. Our result showed that distinct clusters were formed between NE and OK in terms of their soil physicochemical property. Among 3 primary nutrients (i.e., nitrogen, phosphorus, and potassium), potassium is more positively correlated with the high-yield state NE samples. We also attempted to identify keystone communities that significantly affected the soybean yield using co-occurrence network patterns. Network analysis revealed that communities formed distinct clusters in which members of modules having significantly positive correlations with the soybean yield were more abundant in NE than OK. In addition, we identified the most influential bacteria for the soybean yield in the identified modules. For instance, included are class Anaerolineae, family Micromonosporaceae, genus Plantomyces, and genus Nitrospira in the most complex module (ME9) and genus Rhizobium in ME23. This research would help to further identify a way to increase soybean yield in low-yield states in the U.S. as well as worldwide by reconstructing the microbial communities in the rhizosphere.
© 2022. Author(s).

Entities:  

Keywords:  microbial co-occurrence network; microbial communities; microbiome; soil physicochemical properties; soybean rhizosphere; soybean yield

Mesh:

Substances:

Year:  2022        PMID: 36167926     DOI: 10.1007/s12275-022-2363-x

Source DB:  PubMed          Journal:  J Microbiol        ISSN: 1225-8873            Impact factor:   2.902


  48 in total

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9.  Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

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Journal:  Front Physiol       Date:  2019-11-12       Impact factor: 4.566

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