Fungal ITS1 metabarcoding sequences from air samples
收藏NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP447952
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Many economically important plant pathogens are spread on air currents and monitoring the air for these pathogens can help manage diseases they cause in agricultural crops. The goal of this research project was to consolidate existing aerosol monitoring programs that are currently targeting individual pathogens in several crops (canola, dry bean, potato, wheat) across Alberta, Canada. With metabarcoding methods, DNA extracted from these air samples can reveal a much richer fungal community - including pathogenic and beneficial fungi - that crops interact with compared to single fungal species of interest that most research to-date examines.In 2019 and 2021, we collected air samples from across Alberta (Lethbridge, Brooks, Lacombe, and Beaverlodge) and from a range of crops in southern Alberta (canola, dry bean, potato, and wheat). Samples were sequenced using Illumina platforms (NovaSeq or MiSeq) to generate 250 bp paired-end reads. Analyses were performed to compare the airborne fungal communities among different regions in the province, and among different crop types within the same region. This research provides a proof of concept for the simultaneous monitoring of dozens of airborne plant pathogens across the province and integrates with similar efforts happening across the country. The methods employed here can also detect beneficial fungi, which may be important in the management of diseases, since the presence of beneficial fungi can reduce disease levels.
创建时间:
2023-07-07



