Co-occurrence network analysis of biogas reactor microbiomes based on metagenomics sequencing data
Abstract: Metagenome sequencing makes it possible to capture microbial communities in their diversity, to investigate population structures and evolutionary relationships, and to predict metabolic functions and interactions within the microbial community and with the environment. Metagenomics thus, significantly expands the research scope of microbiology. Compared with 16S sequencing, metagenome sequencing can get more information of species identification, and in-depth research on gene and function. Metagenome-assembled genomes (MAGs) retrieved from metagenomics data of 20 AD biogas reactors and the respective Illumina sequencing reads were used to create an abundance table and conduct co-occurrence network analysis. A feasible method was designed for making OTU table and network analysis of metagenomics data and some potential clusters were found may connected to the food chain in microbial community.
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