Shotgun metagenomics dataset of Striga hermonthica-infested maize (Zea mays L.) rhizospheric soil microbiome

Olubukola Oluranti Babalola; Olumayowa Mary Olowe; Ayansina Segun Ayangbenro

doi:10.1016/j.dib.2023.109132

Shotgun metagenomics dataset of Striga hermonthica-infested maize (Zea mays L.) rhizospheric soil microbiome

Data Brief. 2023 Apr 7:48:109132. doi: 10.1016/j.dib.2023.109132. eCollection 2023 Jun.

Authors

Olubukola Oluranti Babalola¹, Olumayowa Mary Olowe¹, Ayansina Segun Ayangbenro¹

Affiliation

¹ Food Security and Safety Focus Area, Faculty of Natural and Agricultural Sciences, North-West University, Private Mail Bag, Mmabatho, South Africa.

Abstract

This dataset includes shotgun metagenomics sequencing of the rhizosphere microbiome of maize infested with Striga hermonthica from Mbuzini, South Africa, and Eruwa, Nigeria. The sequences were used for microbial taxonomic classification and functional categories in the infested maize rhizosphere. High throughput sequencing of the complete microbial community's DNA was performed using the Illumina NovaSeq 6000 technology. The average base pair count of the sequences were 5,353,206 bp with G+C content of 67%. The raw sequence data used for analysis is available in NCBI under the BioProject accession numbers PRJNA888840 and PRJNA889583. The taxonomic analysis was performed using Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST). Bacteria had the highest taxonomic representation (98.8%), followed by eukaryotes (0.56%), and archaea (0.45%). This metagenome dataset provide valuable information on microbial communities associated with Striga-infested maize rhizosphere and their functionality. It can also be used for further studies on application of microbial resources for sustainable crop production in this region.

Keywords: Biotic stress; Cereal; Food security; MG-RAST; Microbial community; Parasitic weed.