Biodiversity Data Journal :
OMIC Data Paper
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Corresponding author: Olubukola O. Babalola (olubukola.babalola@nwu.ac.za)
Academic editor: Anna Sandionigi
Received: 01 Nov 2020 | Accepted: 05 Feb 2021 | Published: 25 Feb 2021
© 2021 Olubukola Babalola, Rebaona Molefe, Adenike Amoo
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Babalola OO, Molefe RR, Amoo AE (2021) Revealing the active microbiome connected with the rhizosphere soil of maize plants in Ventersdorp, South Africa. Biodiversity Data Journal 9: e60245. https://doi.org/10.3897/BDJ.9.e60245
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We conducted shotgun metagenomics sequencing of the maize rhizosphere and bulk soils in Ventersdorp, South Africa. Information on the structural composition and functional capabilities of microbial communities in the maize rhizosphere are provided by the data. Characterising the functional potentials of rhizosphere microbiomes gives an opportunity to link the microbiome to plant growth and health and provides the possibility of discovering new plant-beneficial genes that could enhance agricultural sustainability.
Illumina sequencing, metagenomics, rhizosphere, maize plants
Maize is one of South Africa's most economically-valuable crops. Globally, it fills the diets of billions of people with basic carbohydrates. Poor management practices, such as over-fertilisation, have gone up significantly due to the quest to feed the ever-increasing human population. Therefore, it is imperative to identify eco-friendly fertilisers that do not have adverse effects on soil and maize development. Plants establish associations with soil microorganisms for various functions including nutrient cycling, stress tolerance and pathogen immunity (
The rhizosphere, which is the medium between plants and soil, has been labelled a 'hotspot' for new genes and biomolecules (
Rhizosphere microbes exist to protect against pathogens and improve growth by developing phytohormones. These organisms enable plants to handle environmental disruptions, such as irregular climate-related changes in temperature, drought and salinity (
The dataset contains raw sequences (FASTQ format files) obtained using shotgun metagenomic sequencing of the maize rhizosphere and bulk soils. Samples were collected from the maize rhizosphere (F3R1) and bulk (F3B1) soils to understand the microbial community structure, function and plant-beneficial genes in maize plantations. These data can be used alone or along with other datasets to achieve a larger scale view with more power for maize-associated microbiome research.
Soil samples were collected from the rhizosphere soil (F3R1) and the bulk soil (F3B1) of maize plants on 16 June 2019 from a farm situated at Ventersdorp, South Africa. The rhizosphere soil samples were collected at 8 cm diameter, 15 cm depth of maize plants. The bulk soils were also collected within the maize farms.
The maize field being investigated in this study is a private farm in Ventersdorp in the North West Province of South Africa. The farm was intentionally selected, based on the geographic location and the availability of maize plants. Ventersdorp has summer temperatures ranging from 17ºC to 31ºC and winter temperatures ranging from 3ºC to 21ºC. The annual rainfall ranges between 300 mm and 600 mm with more rain falling in summer than in winter.
Ventersdorp, North West Province (approximately
The soil samples were transported to the laboratory on ice and stored until further use. Genomic DNA extraction was conducted using the DNeasy PowerSoil® DNA isolation kit (MoBio Laboratories, Carlsbad, CA) in accordance with the manufacturer's directions. The extracted DNA was sent for shotgun metagenome sequencing to the Molecular Research Laboratory (www.mrdnalab.com) in Texas, USA. The initial concentration of DNA was evaluated using the Qubit® dsDNA HS Assay Kit (Life Technologies). The libraries were prepared using Nextera DNA Flex library preparation kit (Illumina), following the manufacturer's user guide. Using 50 ng of DNA from each sample, libraries were prepared according to the Illumina NovaSeq DNA library preparation protocol. The determination of library average insert size was determined using the Agilent 2100 Bioanalyzer (Agilent Technologies). The library insert size ranged from 617 bp to 873 bp. The libraries were pooled, diluted (to 0.6 nM) and sequenced paired-end for 300 cycles using the NovaSeq system (Illumina).
The raw metagenome sequences were subjected to quality control using Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST) online server (
MG-RAST (https://mg-rast.org).
Source: The National Human Genome Research Institute (NHGRI)
The maize rhizosphere soil sample had more microorganisms than the bulk soil sample.
The rhizosphere microbiome and their functional potentials.
All soil microbiomes were identified to genus or species level. The study revealed that the most abundant phyla were Proteobacteria and Actinobacteria in the rhizosphere and bulk soils. Ascomycota and Basidiomycota were distributed fungal reads, while Thauarcheota and Euyarchaeota were distributed as archaeal reads, respectively, but with an abundance of < 1%.Table
Taxonomic classification of microorganisms in the maize rhizosphere and bulk soils
Domain |
Phyla |
F3R1 |
F3B1 |
Bacteria |
Acidobacteria |
368735 |
226709 |
Bacteria |
2511153 |
2794515 |
|
Bacteria |
15800 |
10882 |
|
Bacteria |
347509 |
261611 |
|
Bacteria |
3480 |
1944 |
|
Bacteria |
6644 |
4512 |
|
Bacteria |
35848 |
24915 |
|
Bacteria |
203916 |
170908 |
|
Bacteria |
2318 |
1452 |
|
Bacteria |
190459 |
138395 |
|
Bacteria |
6452 |
4206 |
|
Bacteria |
66466 |
56965 |
|
Bacteria |
4479 |
3216 |
|
Bacteria |
1759 |
1224 |
|
Bacteria |
1452 |
1021 |
|
Bacteria |
393062 |
304682 |
|
Bacteria |
5707 |
4073 |
|
Bacteria |
153957 |
140020 |
|
Bacteria |
4635 |
3029 |
|
Bacteria |
27120 |
15636 |
|
Bacteria |
185528 |
121559 |
|
Bacteria |
3443718 |
2362316 |
|
Bacteria |
17790 |
12214 |
|
Bacteria |
9010 |
6373 |
|
Bacteria |
1687 |
1121 |
|
Bacteria |
15919 |
11866 |
|
Bacteria |
179156 |
100394 |
|
Bacteria |
22169 |
18869 |
|
Fungi |
30221 |
31523 |
|
Fungi |
3615 |
2657 |
|
Fungi |
14 |
20 |
|
Fungi |
44 |
32 |
|
Fungi |
38 |
6 |
|
Fungi |
121 |
57 |
|
Fungi |
43 |
20 |
|
Archaea |
10423 |
7705 |
|
Archaea |
59001 |
45925 |
|
Archaea |
728 |
451 |
|
Archaea |
60 |
44 |
|
Archaea |
6596 |
5229 |
|
Viruses |
1244 |
1109 |
The functional annotation using SEED subsystems revealed that reads were more ascribed to carbohydrates metabolism (15.76 to 15.90%), amino acids and derivatives (11.53 to 11.61%) and clustering-based systems (13.63 to 13.78%) in the maize rhizosphere and bulk soils samples.
Maize associated microbiome studies (Suppl. material
Creative Commons Public Domain Waiver (CC-Zero)
OOB would like to thank the National Research Foundation of South Africa for a grant (Grant Ref: UID123634; OOB) that has supported work in our laboratory. RRM would like to thank the North-West University for the postgraduate bursary that was granted during her MSc programme. AEA is grateful to the North-West University for postdoctoral bursary and research support.
North-West University
All the mentioned authors contributed substantially and intellectually to the work. OOB designed the research, revised the work critically for important intellectual content, performed quality assurance, provided funding acquisition, project administration and resources. RRM was involved in data curation, formal analysis, investigation, visualisation of data and writing of the original draft of the manuscript. AEA was involved in data curation, visualisation of data, reviewing and thoroughly editing of the original draft, validation and formal analysis.
The authors declare that they have no conflict of interest, either financial or commercial wise.