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. 2023 Dec 6;52:109920. doi: 10.1016/j.dib.2023.109920

Dataset of amplicon metagenomic assessment of barley rhizosphere bacteria under different fertilization regimes

Olubukola Oluranti Babalola 1,⁎, Ben Jesuorsemwen Enagbonma 1
PMCID: PMC10770713  PMID: 38186742

Abstract

The metagenomic dataset profiled in this research is built on bacterial 16S rRNA gene amplicon of DNA mined from barley rhizosphere under chemical (CB) and organic (OB) fertilization. Amplicon-based sequencing was prepared by the Illumina platform, and the raw sequence dataset was examined using Metagenomic Rast Server (MG-RAST). The metagenome comprised sixteen samples that include CB1 (494,583 bp), CB2 (586,532 bp), CB3 (706,685 bp), CB4 (574,606 bp), CB5 (395,460 bp), CB6 (520,822 bp), CB7 (511,729 bp), CB8 (548,074 bp), OB1 (642,794 bp), OB2 (513,767 bp), OB3 (461,293 bp), OB4 (498,241 bp), OB5 (689,497 bp), OB6 (423,436 bp), OB7 (478,657 bp) and OB8 (279,186 bp). Information from the metagenome sequences is accessible under the bioproject numbers PRJNA827679 (CB1), PRJNA827686 (CB2), PRJNA827693 (CB3), PRJNA827699 (CB4), PRJNA827706 (CB5), PRJNA827761 (CB6), PRJNA827780 (CB7), PRJNA827786 (CB8), PRJNA826806 (OB1), PRJNA826824 (OB2), PRJNA826834 (OB3), PRJNA826841 (OB4), PRJNA826853 (OB5), PRJNA827254 (OB6), PRJNA827256 (OB7), and PRJNA827257 (OB8) at NCBI. Actinobacteria dominated the soil samples at the phylum level.

Keyword: Anthropogenic interference, Food safety, Metagenome, MG-RAST, Unclassified microbiome

Specifications Table

Subject Microbiology: rhizosphere bacteria
Specific subject area 16S rRNA gene amplicon metagenomic of barley rhizosphere bacteria under different fertilization scheme
Data format Raw data (FastQ file)
Type of data Table, figure and data gotten from high throughput amplicon generation sequencing
Data collection Metagenomic DNA extraction from soil samples from barley rhizosphere under chemical fertilization (CB) and under organic fertilization (OB), Next generation sequencing on Illumina (MiSeq) instrument and metagenomics classification using Ribosomal Database Project (RDP) Technology
Data source location Institution: North-West University
City/Town/Region: Madibeng,
Country: North West Province
Latitude and longitude (and GPS coordinates) for collected samples/data: CB = 25°39′32.2″S 27°39′49.8″E, OB = 25°39′04.9″S, 27°40′46.6″E
Data accessibility Repository name NCBI SRA
Data identification number: PRJNA827679 (CB1), PRJNA827686
(CB2), PRJNA827693 (CB3), PRJNA827699 (CB4), PRJNA827706
(CB5), PRJNA827761 (CB6), PRJNA827780 (CB7), PRJNA827786
(CB8), PRJNA826806 (OB1), PRJNA826824 (OB2), PRJNA826834
(OB3), PRJNA826841 (OB4), PRJNA826853 (OB5), PRJNA827254
(OB6), PRJNA827256 (OB7), and PRJNA827257 (OB8)
Direct URL to data:
https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827679 (CB1), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827686 (CB2), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827693 (CB3), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827699 (CB4),
https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827706 (CB5), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827761 (CB6), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827780 (CB7), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827786 (CB8), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=826806 (OB1), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=826824 (OB2), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=826834 (OB3), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=826841 (OB4), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=826853 (OB5), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827254 (OB6), https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827256 (OB7), and https://www.ncbi.nlm.nih.gov/sra?LinkName=bioproject_sra_all&from_uid=827257 (OB8)
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1. Value of the Data

  • •

    The dataset gives understanding on the influence of different fertilizer regimes on the structure, composition and diversity of microbiome from soils obtained from barley rhizosphere.

  • •

    Microbial communities residing in soils obtained from barley rhizosphere may possibly function as a pool of biological-active molecules and unique genes necessary for biotechnological, ecological and industrial purposes.

  • •

    Barley rhizosphere emerges as one of the factors of yield potential in crops, as well as plays a significant function in improving plant fitness.

  • •

    The knowledge of the influence of conventional and organic fertilizers on the structure, composition, and diversity of the rhizosphere bacteria will assist in engineering soil to increase microbial diversity in the agroecosystem.

2. Data Description

The metagenomic files (which is accessible under the bioproject numbers PRJNA827679 (CB1), PRJNA827686 (CB2), PRJNA827693 (CB3), PRJNA827699 (CB4), PRJNA827706 (CB5), PRJNA827761 (CB6), PRJNA827780 (CB7), PRJNA827786 (CB8), PRJNA826806 (OB1), PRJNA826824 (OB2), PRJNA826834 (OB3), PRJNA826841 (OB4), PRJNA826853 (OB5), PRJNA827254 (OB6), PRJNA827256 (OB7), and PRJNA827257 (OB8) at NCBI) comprises of raw sequences acquired via the 16S rRNA amplicon sequencing of soils from barley rhizosphere under chemical fertilization (CB1–8) and soils from barley rhizosphere under organic fertilization (OB1–8) from Madibeng, South Africa. The sequence information (Table 1), taxonomic abundance and diversity of bacterial communities of barley rhizosphere under chemical fertilization (CB) and organic fertilization (OB) are presented in Fig. 1, Fig 2 correspondingly.

Table 1.

The sequence information of barley rhizosphere under chemical and organic fertilization.

Samples Base count (bp) Sequences count (bp) Mean sequence length (bp)
CB1 144,422,171 494,583 292 ± 4
CB2 171,279,689 586,532 292 ± 3
CB3 206,379,594 706,685 292 ± 3
CB4 167,790,610 574,606 292 ± 4
CB5 115,489,933 395,460 292 ± 3
CB6 152,095,576 520,822 292 ± 4
CB7 149,445,112 511,729 292 ± 4
CB8 160,057,506 548,074 292 ± 3
OB1 187,730,488 642,794 292 ± 3
OB2 150,036,417 513,767 292 ± 2
OB3 134,731,154 461,293 292 ± 3
OB4 145,525,929 498,241 292 ± 2
OB5 201,338,767 689,497 292 ± 3
OB6 119,267,313 423,436 282 ± 49
OB7 139,777,709 478,657 292 ± 3
OB8 81,530,862 279,186 292 ± 3
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CB = barley rhizosphere under chemical fertilization and OB = barley rhizosphere under organic fertilization.

Fig. 1.

Fig 1:

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Taxonomic abundance of microbial communities among barley rhizosphere under chemical (CB) and organic (OB) fertilization.

Fig 2.

Fig 2:

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The rarefaction curves showing the species richness computation among barley rhizosphere under chemical (CB) and organic (OB) fertilization.

3. Experimental Design, Materials and Methods

In this experiment, we collected sixteen soil samples of 20 g each from barley rhizosphere (the barley plants are 6 weeks old) under chemical fertilization (CB1–8) (25°39′32.2″S 27°39′49.8″E) and barley rhizosphere under organic fertilization (OB1–8) (25°39′04.9″S, 27°40′46.6″E) at a depth of 0–15 cm [1]. For the inorganic field, 75 kg ha−1 K2O, 75 kg ha−1 P2O5, and150 kg ha−1 N were the quantities of inorganic fertilizer which had been in use. Urea, potassium sulphate and calcium superphosphate were the sources of N fertilizer, K fertilizer, and P fertilizer respectively. The organic fertilizer field has been undergoing the use of cow dung of 10,625 kg ha−1 amount for more than a decade. The fertilization regimes employed in this study was in line with the United State Department of Agriculture (USDA, 2014). 10 × 4 m was the measurement for the respective planting field for this research and the cultivar planted on both field is barley seeds (Puma). Each of the research fields (that is CB and OB) were 10 m away. Sterile plastic bags were used to temporarily store the soil samples and then moved to cooler boxes filled with ice. On getting to the laboratory, the soil samples (after removal of debris) were stored in the refrigerator at –20 °C for further analysis. We used the Nucleospin Soil kit (Macherey-Negel, Germany) to extract the DNA of the entire barley rhizosphere microbiome by using the kit's manual as a guide.

The mined DNA was later sent to Molecular Research Laboratory, Clovis road, Texas, United States. Libraries of the 16S rRNA were arranged from the QC-passed DNA samples via the universal primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) with standard Illumina barcodes and adapters. The Ampure XP beads were further used to purify the amplicons. Agilent DNA 1000 Bioanalyser was used to validate the barcoded libraries, while the quantification was done with the Qubit DNA BR reagent assay. After that, the MiSeq was used to sequence the quantified libraries that were later processed and analysed via the MG-RAST server v4.0.3 (http://metagenomics.anl.gov/) [2,3]. Raw data were uploaded as FASTQ files after demultiplexing of pairedend reads. Reads generated after quality processing and deduplication (by eliminating sequences that are: (a) greater than 5 ambiguous base pairs with 15 phred score cutoff (b) artificial sequences made by sequencing artifacts (c) have a length of greater than 2 standard deviations from the average value) by MG-RAST pipeline analysis, were subjected to annotation by using a BLAST-like alignment device called BLAT against a database that offers a nonredundant integration of numerous databases called M5NR database. Taxonomic analysis was done using RDP database under the following conditions: a maximum alignment length of 15 base pairs, an e-value of 1e–5 and a minimum identity of 60%. MG-RAST pipeline made available estimation of microbial abundances present in barley rhizosphere under chemical fertilization (CB) and barley rhizosphere under organic fertilization (OB).

After the MG-RAST analysis on the sequences, we visualized them by plugging them with a stacked bar chart in Excel (version 2010) to appraise the taxonomic abundance. An evaluation of the species richness was done with rarefaction curves from the MG-RAST tool.

Limitations

Not applicable.

Ethics Statement

The current work follows the ethical requirements for publication in Data in Brief. It does not involve human subjects, animal experiments, or any data collected from social media platforms.

CRediT authorship contribution statement

Olubukola Oluranti Babalola: Conceptualization, Supervision, Project administration, Resources. Ben Jesuorsemwen Enagbonma: Writing – original draft, Writing – review & editing, Formal analysis, Data curation, Investigation.

Acknowledgements

Ben Jesuorsemwen Enagbonma thanks South Africa's National Research Foundation/The World Academy of Science African Renaissance. Work in Olubukola Oluranti Babalola lab is based on support by the National Research Foundation of South Africa [grant numbers UID95111, UID110909, UID105248, UID81192; Olubukola Oluranti Babalola].

Declaration of Competing Interest

Both authors affirm that they have no identified conflicting financial benefits or individual connexions that could have seemed to influence the work described in this article.

Data Availability

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Articles from Data in Brief are provided here courtesy of Elsevier

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