Analysis and Interpretation of metagenomics data: an approach

Abstract

Advances in next-generation sequencing technologies have accelerated the momentum of metagenomic studies, which is increasing yearly. The metagenomics field is one of the versatile applications in microbiology, where any interaction in the environment involving microorganisms can be the topic of study. Due to this versatility, the number of applications of this omics technology reached its horizons. Agriculture is a crucial sector involving crop plants and microorganisms interacting together. Hence, studying these interactions through the lenses of metagenomics would completely disclose a new meaning to crop health and development. The rhizosphere is an essential reservoir of the microbial community for agricultural soil. Hence, we focus on the R&D of metagenomic studies on the rhizosphere of crops such as rice, wheat, legumes, chickpea, and sorghum. These recent developments are impossible without the continuous advancement seen in the next-generation sequencing platforms; thus, a brief introduction and analysis of the available sequencing platforms are presented here to have a clear picture of the workflow. Concluding the topic is the discussion about different pipelines applied to analyze data produced by sequencing techniques and have a significant role in interpreting the outcome of a particular experiment. A plethora of different software and tools are incorporated in the automated pipelines or individually available to perform manual metagenomic analysis. Here we describe 8–10 advanced, efficient pipelines used for analysis that explain their respective workflows to simplify the whole analysis process.

Comparative analysis of commercially available metagenomic kits for optimal DNA extraction from bovine fecal samples

“…Researchers must weigh the trade-offs between DNA quantity and potential biases introduced by different kits. Differences in bacterial community composition and e ciency in lysis may signi cantly impact downstream applications, particularly in metagenomic studies, where accurate representation of microbial diversity is paramount (Navgire et al 2022). Hence, researchers should choose a kit that aligns with the goals and nuances of their speci c study design.…”

Comparative evaluation of 16S rRNA metagenomic sequencing in the diagnosis and understanding of bacterial endophthalmitis

“…Metagenomic analysis enables the analysis of DNA segments from multiple microorganisms without the need for culture and is carried out using either an amplicon or shotgun-based approach. 17 Previously, shortread sequencing of the bacterial 16S rRNA gene has been the standard method for microbiome profiling; however, recently long-read sequencing method has been employed to achieve a more comprehensive microbiome profiling. 18 Long-read methods offer higher detection confidence than short-read methods do.…”

Exploring Cereal Metagenomics: Unravelling Microbial Communities for Improved Food Security

“…Metagenomics has enabled the identification of specific microbial species or groups that potentially benefit cereals (refer to Table 2 ). These studies provide valuable information on functional gene annotation within the cereal microbiome [ 91 ]. By comparing metagenomic sequences to reference databases, researchers can identify genes involved in various functions, such as nutrient cycling, plant growth promotion, disease suppression, and stress tolerance [ 92 ].…”