Clustering analysis of soil microbial community at global scale

Abstract

There is a huge number of bacteria in the soil and their existence and function affect the soil properties. Bacteria form a complex community called microbiome. Compared to the ecosystem of plants and animals, we still know little about soil microbial ecosystem. How the soil microbiomes are different throughout the world and how they relate to the region and the environment is a major interest. Recently, the development of next-generation sequencer has been enabled to accumulate metagenome profile data, and a large scale and comprehensive microbiome analysis are required by an information scientific approach. In this study, we compared and analyzed the data from various environments on a global scale using the microbiome database, the Earth Microbiome Project (EMP). We calculated the distance based on genetic distance, named UniFrac distance and did clustering analysis. Clustering results were ecologically interpreted from the view of the function and the characteristics of bacteria. We revealed the characteristic of groups of bacteria related to paddy, vineyard, grasslands in Mongolian, forests, and biofilter. Furthermore, we investigated the relationship between clusters and climate zones. This research is expected to lead to knowledge of soil management based on soil microbiome.