In Yi chuan = Hereditas
The root-associated bacterial microbiota is closely related to life activities of land plants, and its composition is affected by geographic locations and plant genotypes. However, the influence of plant genotypes on root microbiota in rice grown in northern China remains to be explained. In this study, we performed 16S rRNA gene amplicon sequencing to generate bacterial community profiles of two representative rice cultivars, Nipponbare and IR24. They are planted in Changping and Shangzhuang farms in Beijing and have reached the reproductive stage. We compared their root microbiota in details by Random Forest machine learning algorithm and network analysis. We found that the diversity of rice root microbiota was significantly affected by geographic locations and rice genotypes. Nipponbare and IR24 showed distinct taxonomic composition of the root microbiota and the interactions between different bacteria. Moreover, the root bacteria could be used as biomarkers to distinguish Nipponbare from IR24 across regions. Our study provides a theoretical basis for the in-depth understanding of rice root microbiota in Northern China and the improvement of rice breeding from the perspective of the interaction between root microorganisms and plants.
Hu Ya Li, Dai Rui, Liu Yong Xin, Zhang Jing Ying, Hu Bin, Chu Cheng Cai, Yuan Huai Bo, Bai Yang
diversity analysis, machine learning, network analysis, rice root microbiota, taxonomic composition