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Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome
Lettuce (Lactuca sativa L.) is an important vegetable grown and consumed across the world, including South Africa and its rhizosphere constitutes a dynamic community of root associated microbes. Dataset of the microbial community profile of the lettuce rhizospheric soils obtained from Talton, Gauten...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205420/ https://www.ncbi.nlm.nih.gov/pubmed/37228418 http://dx.doi.org/10.1016/j.dib.2023.109214 |
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author | Babalola, Olubukola Oluranti Akanmu, Akinlolu Olalekan Fadiji, Ayomide Emmanuel |
author_facet | Babalola, Olubukola Oluranti Akanmu, Akinlolu Olalekan Fadiji, Ayomide Emmanuel |
author_sort | Babalola, Olubukola Oluranti |
collection | PubMed |
description | Lettuce (Lactuca sativa L.) is an important vegetable grown and consumed across the world, including South Africa and its rhizosphere constitutes a dynamic community of root associated microbes. Dataset of the microbial community profile of the lettuce rhizospheric soils obtained from Talton, Gauteng Province of South Africa was subjected to metagenomic evaluation using the shotgun approach. The whole DNA isolated from the community was sequenced using NovaSeq 6000 system (Illumina). The raw data obtained consists of 129,063,513.33 sequences with an average length of 200 base pairs and 60.6% Guanine + Cytosine content. The metagenome data has been deposited to the National Centre for Biotechnology Information SRA under the bioproject number PRJNA763048. The downstream analysis alongside taxonomical annotation carried out using an online server MG-RAST, showed the community analysis as being made up of archaea (0.95%), eukaryotes (1.36%), viruses (0.04%), while 97.65% of the sequences were classified as bacteria. A sum of 25 bacteria, 20 eukaryotic and 4 archaea phyla were identified. The predominant genera were Acinetobacter (4.85%), Pseudomonas (3.41%), Streptomyces (2.79%), Candidatus solibacter (1.93%), Burkholderia (1.65%), Bradyrhizobium (1.51%) and Mycobacterium (1.31%). Annotation using Cluster of Orthologous Group (COG) showed 23.91% of the sequenced data were for metabolic function, 33.08% for chemical process and signaling while 6.42% were poorly characterized. Furthermore, the subsystem annotation method showed that sequences were majorly associated with carbohydrates (12.86%), clustering-based subsystems (12.68%), and genes coding for amino acids and derivatives (10.04%), all of which could serve in growth promotion and plant management. |
format | Online Article Text |
id | pubmed-10205420 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102054202023-05-24 Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome Babalola, Olubukola Oluranti Akanmu, Akinlolu Olalekan Fadiji, Ayomide Emmanuel Data Brief Data Article Lettuce (Lactuca sativa L.) is an important vegetable grown and consumed across the world, including South Africa and its rhizosphere constitutes a dynamic community of root associated microbes. Dataset of the microbial community profile of the lettuce rhizospheric soils obtained from Talton, Gauteng Province of South Africa was subjected to metagenomic evaluation using the shotgun approach. The whole DNA isolated from the community was sequenced using NovaSeq 6000 system (Illumina). The raw data obtained consists of 129,063,513.33 sequences with an average length of 200 base pairs and 60.6% Guanine + Cytosine content. The metagenome data has been deposited to the National Centre for Biotechnology Information SRA under the bioproject number PRJNA763048. The downstream analysis alongside taxonomical annotation carried out using an online server MG-RAST, showed the community analysis as being made up of archaea (0.95%), eukaryotes (1.36%), viruses (0.04%), while 97.65% of the sequences were classified as bacteria. A sum of 25 bacteria, 20 eukaryotic and 4 archaea phyla were identified. The predominant genera were Acinetobacter (4.85%), Pseudomonas (3.41%), Streptomyces (2.79%), Candidatus solibacter (1.93%), Burkholderia (1.65%), Bradyrhizobium (1.51%) and Mycobacterium (1.31%). Annotation using Cluster of Orthologous Group (COG) showed 23.91% of the sequenced data were for metabolic function, 33.08% for chemical process and signaling while 6.42% were poorly characterized. Furthermore, the subsystem annotation method showed that sequences were majorly associated with carbohydrates (12.86%), clustering-based subsystems (12.68%), and genes coding for amino acids and derivatives (10.04%), all of which could serve in growth promotion and plant management. Elsevier 2023-05-09 /pmc/articles/PMC10205420/ /pubmed/37228418 http://dx.doi.org/10.1016/j.dib.2023.109214 Text en © 2023 The Author(s) https://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 | Data Article Babalola, Olubukola Oluranti Akanmu, Akinlolu Olalekan Fadiji, Ayomide Emmanuel Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome |
title | Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome |
title_full | Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome |
title_fullStr | Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome |
title_full_unstemmed | Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome |
title_short | Dataset of shotgun metagenomic evaluation of lettuce (Lactuta sativa L.) rhizosphere microbiome |
title_sort | dataset of shotgun metagenomic evaluation of lettuce (lactuta sativa l.) rhizosphere microbiome |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205420/ https://www.ncbi.nlm.nih.gov/pubmed/37228418 http://dx.doi.org/10.1016/j.dib.2023.109214 |
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