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Article|03 Jun 2015|OPEN
Amplicon-based metagenomics identified candidate organisms in soils that caused yield decline in strawberry
Xiangming Xu1 , , Thomas Passey1 , Feng Wei1 , Robert Saville1 and Richard J. Harrison,1 ,
1East Malling Research, East Malling, West Malling, Kent, ME19 6BJ, UK
*Corresponding author. E-mail: Xiangming.xu@emr.ac.uk,richard.harrison@emr.ac.uk

Horticulture Research 2,
Article number: 22 (2015)
doi: https://doi.org/10.1038/hortres.2015.22
Views: 985

Received: 18 Mar 2015
Revised: 20 Apr 2015
Accepted: 22 Apr 2015
Published online: 03 Jun 2015

Abstract

A phenomenon of yield decline due to weak plant growth in strawberry was recently observed in non-chemo-fumigated soils, which was not associated with the soil fungal pathogen Verticillium dahliae, the main target of fumigation. Amplicon-based metagenomics was used to profile soil microbiota in order to identify microbial organisms that may have caused the yield decline. A total of 36 soil samples were obtained in 2013 and 2014 from four sites for metagenomic studies; two of the four sites had a yield-decline problem, the other two did not. More than 2000 fungal or bacterial operational taxonomy units (OTUs) were found in these samples. Relative abundance of individual OTUs was statistically compared for differences between samples from sites with or without yield decline. A total of 721 individual comparisons were statistically significant – involving 366 unique bacterial and 44 unique fungal OTUs. Based on further selection criteria, we focused on 34 bacterial and 17 fungal OTUs and found that yield decline resulted probably from one or more of the following four factors: (1) low abundance of Bacillus and Pseudomonas populations, which are well known for their ability of supressing pathogen development and/or promoting plant growth; (2) lack of the nematophagous fungus (Paecilomyces species); (3) a high level of two non-specific fungal root rot pathogens; and (4) wet soil conditions. This study demonstrated the usefulness of an amplicon-based metagenomics approach to profile soil microbiota and to detect differential abundance in microbes.