In this project, a crop rotation study was conducted at two field sites (Morden, Manitoba and Saskatoon, Saskatchewan) in the 2021 and 2022 cropping seasons.  A total of 9 crop combinations/treatments, including cereals (Maize, Wheat, Barley, Durum), pulses (Lentil, Pea and Soybeans) and oilseeds (Canola), were evaluated.  Samples from rhizosphere and bulk soils were subjected to metagenomics and physicochemical analysis.  Soil microbiome analysis uses 16S rRNA (bacteria), ITS (fungi) genes and whole metagenome shotgun sequencing with the top 6-inch bulk and crop rhizosphere soil samples.

The amplicon-based 16S and ITS sequencing were used to identify and quantify soil microbes (milestone 1).  The whole metagenome shotgun sequencing method was used for functional analysis of all the genes associated with plant pathogens-suppression within various cropping systems (milestones 2 and 3).  A crop rotation study was established at two field sites (SK and MB) to meet the above milestones in 2020 and 2021.  The analysis of samples collected in 2020 has been completed.  The results indicate that crop rotation alters the abundance and diversity of the major pathogenic and non-pathogenic/beneficial microbial (fungi and bacteria) taxa and affects gene sequence abundance related to disease suppression.  The fungal pathogenic and non-pathogenic microbiome changes were more responsive to the crop types and soil properties than bacterial communities.  Crop rotation affects all fungal diversity indices, including OTUs richness, Shannon and phylogenetic diversity).  Bacterial OTUs richness is the only bacterial diversity index affected by rotational treatments.  The crop rotation also affects soil chemical properties, the concentration of NO3-N, Ca, Cl, and soil pH, which positively or negatively correlate with the diversity of the soil microbial community.

Data analysis from shotgun sequencing of soil samples collected in the 2020 crop season generated a metagenome assembly containing 1.5M contigs belonging to 5 fungal phyla and 11 bacterial phyla.  The metagenome assembly was screened against a panel of disease-suppressive genes (2100 genes) encoding anti-fungal metabolites.  A total of 1153 contigs were identified in the initial dataset.  These contigs are found to encode chitinases, siderophore and antibiotics known to suppress common soil-borne fungi pathogens.  The abundance of these contigs differs in different rotational treatment.  A key set of candidates encoding chitinases, pyrrolnitrin, and 2,4-diacetylphloroglucinol was identified.  The variation of these candidates in soil samples are being verified using digital PCR.  Additionally,  the abundance of these is being analyzed in samples collected in the 2021-2022 growing seasons