Plant microbiota have different effects on the plant which can be beneficial or pathogenic. In this study, we concentrated on beneficial microbes associated with plants using endophytic microbes as a case study. Detailed knowledge of the microbial diversity, abundance, composition, functional genes patterns, and metabolic pathways at genome level could assist in understanding the contributions of microbial community towards plant growth and health. Recently, the study of microbial community has improved greatly with the discovery of next-generation sequencing and bioinformatics technologies. Analysis of next generation sequencing data and a proper computational method plays a key role in examining microbial metagenome. This review presents the general metagenomics and computational methods used in processing plant associated metagenomes with concentration on endophytes. This includes 1) introduction of plant-associated microbiota and the factors driving their diversity. 2) plant metagenome focusing on DNA extraction, verification and quality control. 3) metagenomics methods used in community analysis of endophytes focusing on maize plant and, 4) computational methods used in the study of endophytic microbiomes. Limitations and future prospects of metagenomics and computational methods for the analysis of plant-associated metagenome (endophytic metagenome) were also discussed with the aim of fostering its development. We conclude that there is need to adopt advanced genomic features such as k-mers of random size, which do not depend on annotation and can represent other sequence alternatives.
Keywords: Bioinformatics; Endophytes; Illumina Hiseq; Microbiomes; Shotgun metagenomics; Zea mays.
Copyright © 2020. Published by Elsevier B.V.