Diversity and Spatiotemporal Dynamics of Fungal Communities in the Rhizosphere Soil of Cotton in the Arid Region of Northwest China

This study aimed to investigate the fungal diversity and its temporal and spatial dynamics in the rhizosphere soil of healthy cotton by high-throughput sequencing. We studied species richness, composition, and distribution of cotton rhizosphere fungal community with respect to location (Alaer, Kuerle, Tumushuke, Hami, Shihezi, Wusu, and Jinghe) and plant growth period (seedling stage, bud stage, flowering stage, and boll-opening stage) using the methods of PCR-based high-throughput sequencing and real-time quantitative PCR. A total of 1,838,454 fungal nuclear ribosomal internal transcribed spacer region sequences (rRNA ITS) were obtained from all cotton plants sampled at different growth stages in the seven locations in Xinjiang. The most abundant fungal group in the cotton rhizosphere was the Ascomycota (78.72%), followed by the Zygomycota (9.56%) and Basidiomycota (2.77%). These sequences revealed an enormous number of operational taxonomic units (OTUs) in cotton (1802 unique OTUs), with 67–464 OTUs in a single cotton sample, at a 3% threshold and a sequencing depth of 30,000 sequences. We identified 33 classes and 389 genera from the resulting 1,800,714 sequences. Sordariomycetes was the most frequent class in all samples, followed by Leotiomycetes and Eurotiomycetes. There were some differences in OTUs among different growth stages, but the differences were not significant, with 382 OTUs (14.66%) being common to each of the stages. A marked difference in the diversity of fungi in the rhizosphere soil of cotton was evident among the different locations, with the highest number of OTUs being detected in Jinghe (1084 OTUs) and clusters of OTUs representative of northern and eastern Xinjiang being detected. There were significantly more tags of Mortierella in Jinghe and Wusu than in the other sampling sites. The dynamics of the rhizosphere fungal communities were influenced by sampling sites. To the best of our knowledge, the current study is the first application of PCR-based Illumina to characterize and compare the fungal biodiversity in multiple rhizosphere soil samples from cotton.