To accurately identify the fungal communities in the rhizosphere of rice plants, Oryza sativa L. as well as understand their relationships, an Illumina-based sequencing approach was employed in this study. Rice rhizosphere samples were collected from four large-scale rice-producing villages in Niger State: Lagun, Batavovogi, Dokogi and Jikannagi. Genomic DNA was extracted from each sample, and their fungal Internal Transcribed Spacer (ITS) regions were amplified using standard Illumina sequencing protocols. After quality-filtering the sequences, the operational taxonomic units (OTUs) in each sample were identified using QIIME software, and were assigned taxonomies through the Unite databases. The sequencing produced 340,492 ITS rDNA reads. The sample from Lagun had the highest richness according to the Chao 1 diversity index (776.4), while the Dokogi sample had the lowest richness (482). Most OTUs belonged to Phylum Ascomycota, followed by Basidiomycota, while representatives of the following classes were observed, i.e. Sordariomycetes, Eurotiomycetes, Dothideomycetes, Agaricomycetes, and Rhizophyctidomycetes. The Jikannagi sample showed predominance of Sordariomycetes, Agaricomycetes, and Dothideomycetes, while Eurotiomycetes and Rhizophyctidomycetes were dominant in the Dokogi sample. The Jikannagi sample also exhibited the highest fungal diversity (Shannon index). However, a significant portion of the fungal reads were not classifiable because the data base used in this study was not sufficient enough. Therefore, there is need for future studies to be based on an improved data base in order to reduce the number of unclassified fungi.

DNA reads, fungal communities, illumina sequencing, operational taxonomic units, QIIME

Published by University of Zagreb, Faculty of Agriculture, Zagreb, CROATIA
Sponsored by Ministry Science and Education of the Republic of Croatia