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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 plan...

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Autores principales: Babalola, Olubukola Oluranti, Fadiji, Ayomide Emmanuel, Ayangbenro, Ayansina Segun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327808/
https://www.ncbi.nlm.nih.gov/pubmed/32637499
http://dx.doi.org/10.1016/j.dib.2020.105893
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author Babalola, Olubukola Oluranti
Fadiji, Ayomide Emmanuel
Ayangbenro, Ayansina Segun
author_facet Babalola, Olubukola Oluranti
Fadiji, Ayomide Emmanuel
Ayangbenro, Ayansina Segun
author_sort Babalola, Olubukola Oluranti
collection PubMed
description 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.
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spelling pubmed-73278082020-07-06 Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.) Babalola, Olubukola Oluranti Fadiji, Ayomide Emmanuel Ayangbenro, Ayansina Segun Data Brief Agricultural and Biological Science 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. Elsevier 2020-06-20 /pmc/articles/PMC7327808/ /pubmed/32637499 http://dx.doi.org/10.1016/j.dib.2020.105893 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Agricultural and Biological Science
Babalola, Olubukola Oluranti
Fadiji, Ayomide Emmanuel
Ayangbenro, Ayansina Segun
Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.)
title Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.)
title_full Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.)
title_fullStr Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.)
title_full_unstemmed Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.)
title_short Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.)
title_sort shotgun metagenomic data of root endophytic microbiome of maize (zea mays l.)
topic Agricultural and Biological Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327808/
https://www.ncbi.nlm.nih.gov/pubmed/32637499
http://dx.doi.org/10.1016/j.dib.2020.105893
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