Monitoring and Surveillance of Aerial Mycobiota of Rice Paddy through DNA Metabarcoding and qPCR.

The airborne mycobiota has been understudied in comparison with the mycobiota present in other agricultural environments. Traditional, culture-based methods allow the study of a small fraction of the organisms present in the atmosphere, thus missing important information. In this study, the aerial mycobiota in a rice paddy has been examined during the cropping season (from June to September 2016) using qPCRs for two important rice pathogens ( and ) and by using DNA metabarcoding of the fungal ITS region. The metabarcoding results demonstrated a higher alpha diversity (Shannon-Wiener diversity index H' and total number of observed species) at the beginning of the trial (June), suggesting a higher level of community complexity, compared with the end of the season. The main taxa identified by HTS analysis showed a shift in their relative abundance that drove the cluster separation as a function of time and temperature. The most abundant OTUs corresponded to genera such as , , or . Changes in the mycobiota composition were clearly dependent on the average air temperature with a potential impact on disease development in rice. In parallel, oligotyping analysis was performed to obtain a sub-OTU identification which revealed the presence of several oligotypes of and with relative abundance changing during monitoring.