Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.)

This dataset represents the root endophytic microbial community profile of maize (Zea mays L.), one of the largest food crops in South Africa, using a shotgun metagenomic approach. To the best of our understanding, this is the first account showcasing the endophytic microbial diversity in maize plants via the shotgun metagenomics approach. High throughput sequencing of the whole DNA from the community was carried out using NovaSeq 6000 system (Illumina). The data obtained consists of 10,915,268 sequences accounting for 261,906,948 bps with an average length of 153 base pairs and 43% Guanine+Cytosine content. The metagenome data can be accessed at the National Centre for Biotechnology Information SRA registered with the accession number PRJNA607664. Community analysis was done using an online server called MG-RAST, which showed that 0.12% of the sequences were archaeal associated, eukaryotes were 15.06%, while 84.77% were classified as bacteria. A sum of 28 bacterial, 22 eukaryotic and 4 archaeal phyla were identified. The predominant genera were Bacillus (16%), Chitinophaga (12%), Flavobacterium (4%), Chryseobacterium (4%), Paenibacillus (4%), Pedobacter (3%) and Alphaproteobacteria (3%). Annotation using Cluster of Orthologous Group (COG) revealed that 41.47% of the sequenced data were for metabolic function, 24.10% for chemical process and signaling, while 17.43% of the sequences were in the poorly characterized group. Annotation using the subsystem method showed that 18% of the sequences were associated with carbohydrates, 9% were for clustering-based subsystems, and 9% contain genes coding for amino acids and derivatives, which might be beneficial in plant growth and health improvement.


a b s t r a c t
This dataset represents the root endophytic microbial community profile of maize ( Zea mays L.), one of the largest food crops in South Africa, using a shotgun metagenomic approach. To the best of our understanding, this is the first account showcasing the endophytic microbial diversity in maize plants via the shotgun metagenomics approach. High throughput sequencing of the whole DNA from the community was carried out using NovaSeq 60 0 0 system (Illumina). The data obtained consists of 10,915,268 sequences accounting for 261,906,948 bps with an average length of 153 base pairs and 43% Guanine + Cytosine content. The metagenome data can be accessed at the National Centre for Biotechnology Information SRA registered with the accession number PRJNA607664. Community analysis was done using an online server called MG-RAST, which showed that 0.12% of the sequences were archaeal associated, eukaryotes were 15.06%, while 84.77% were classified as bacteria. A sum of 28 bacterial, 22 eukaryotic and 4 archaeal phyla were identified. The predominant genera were Bacillus (16%), Chitinophaga (12%), Flavobacterium (4%), Chryseobacterium (4%), Paenibacillus (4%), Pedobacter (3%) and Alphaproteobacteria (3%). Annotation using Cluster of Orthologous Group (COG) revealed that 41.47% of the sequenced data were for metabolic function, 24.10% for chemical process and signaling, while 17.43% of the sequences were in the poorly characterized group. Annotation using the subsystem method showed that 18% of the sequences were associated with carbohydrates, 9% were for clustering-based subsystems, and 9% contain genes coding for amino acids and derivatives, which might be beneficial in plant growth and health improvement.
© 2020 The Author(s Value of the data -Endophytic microbial communities' resident in maize plant could serve as a reservoir of plant growth-promoting compounds and novel genes which can help in the growth and health improvement of crops. -They could serve as an alternative to synthetic fertilizers via the discovery of eco-friendly biofertilizers and potential biocontrol agents in the management of crop diseases. -Future studies should explore the application and contribution of the novel microbial species and gene discovered in this study for improved agricultural practices.

Data description
This dataset contains raw NGS data obtained via shotgun sequencing of maize plant metagenome from South Africa. All datasets obtained in fastq.gz file were deposited at the National Centre for Biotechnology Information SRA database (PRJNA607664). Details of the microbial community and functional structure using SEED subsystem of endophytic microbial communities in maize plants are shown in Figs. 1 and 2 correspondingly.

Experimental design, materials and methods
Fresh roots of maize plants were collected from the North-West University school farm (S25o47 23", E25o37 15"), Molelwane, Northwest, South Africa. Surface sterilization of the maize roots was carried out using standard methods as described by Correa-Galeote et al. [1] , the whole community DNA was extracted from maize plant using Qiagen DNeasy Plant Mini Kit, following guidelines as described by the manufacturer. Shotgun metagenomic sequencing was done using NovaSeq 60 0 0 system (Illumina, USA) following standard methods as provided by the  manufacturer. Structural analysis and functional annotation of sequenced data were carried out using an online server called Metagenomics rapid annotation subsystem (MG-RAST) [2] using default specifications. After quality assessment, sequenced data were annotated using a BLAST-like alignment algorithm called BLAT [3] , against M5NR database [4] which offers a concise alliance with other numerous databases.

Declaration of Competing Interest
There is no conflict of interest whatsoever among the authors which could affect the data presented in this paper.

Funding
This work was funded by the National Research Foundation , South Africa ( UID123634 ).