Eurasian Soil Science · 2018 · 13 citations · 48 references
Life SciencesMicrobiologyPlant SciencesMicrobial EcologySoil EcologySoil MicrobiologyFungal DiversityFungal GeneticsFungal GenomicsPlant MicrobiomePlant-associated Microbial CommunitiesMycorrhizal Fungal DiversityPlant-associated Fungal CommunitiesPlant-associated Fungal DiversityRhizosphere Fungal CommunitiesRoot-associated Fungal CommunitiesSoil Fungal DiversitySoil Microbial Community Genomics
Soil fungal pathogens are the most common cause of diseases in commercial strawberry crops worldwide. Since simultaneous infections by different pathogens can severely damage the crop, understanding the associated fungal communities can be helpful to mitigate crop loss. Herein, we used Illumina metabarcoding to assess the structure of fungal communities in five strawberry production areas in Estonia. Our analysis revealed 990 to 1430 operational taxonomic units (OTUs) per soil sample (pools of eight soil samples per production area). Based on our analyses, Ascomycota (55.5%) and Basidiomycota (25.0%) were the most OTUs-rich. Amongst the 24 most abundant OTUs, Geomyces, Rhodotorula, Verticillium and Microdochium were the most abundant genera, which were found across nearly all the soil samples. The OTUs were also clustered into three distinct groups, corresponding to different functional guilds of fungi. In addition, Fusarium solani, V. dahliae, Rhizoctonia solani and Colletotrichum truncatum were enormously abundant in the fields with disease symptoms, whereas arbuscular mycorrhizal fungi especially Rhizophagus irregularis were considerably more abundant in the fields with healthy plants. These findings provide support that mycorrhizal fungi may play an important role in suppressing pathogens. Our study for the first time shows the usefulness of Illumina technology in surveying the communities of soil fungi in strawberry fields effectively, which may improve available disease management strategies against strawberry diseases.
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Search and clustering orders of magnitude faster than BLAST
R. C. Edgar · Bioinformatics · 2010 · 21.7K citations · Full text
UCHIME improves sensitivity and speed of chimera detection
R. C. Edgar, Brian J. Haas, José C. Clemente et al. · Bioinformatics · 2011 · 15.5K citations · Full text
Life Sciences, Biology, Microbiology +17