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

被引:12
作者
Babalola, Olubukola Oluranti [1 ]
Fadiji, Ayomide Emmanuel [1 ]
Ayangbenro, Ayansina Segun [1 ]
机构
[1] North West Univ, Fac Nat & Agr Sci, Food Secur & Safety Niche, Private Mail Bag X2046, Mmabatho, South Africa
基金
新加坡国家研究基金会;
关键词
BLAT; Illumina NovaSeq; Maize metagenome; MG-RAST; Plant microbial community; Novel genes;
D O I
10.1016/j.dib.2020.105893
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. (c) 2020 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/ )
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页数:4
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