Characterization of the soil fungal microbiome associated with mildew-resistant grapevine varieties in La Rioja

Abstract

The study was conducted using 9 fungal-resistant varieties planted at the “Finca Valdegón,” belonging to the Government of La Rioja. Specifically, the white varieties Fleurtai, Soreli, Sauvignon Rytos, Sauvignon Kretos, and Sauvignon Nepis were analyzed, along with the red varieties Cabernet Eidos, Cabernet Volos, Julius, and Merlot Khorus. Tempranillo and Viura varieties were used as controls.

Four samplings were carried out between June and July, two in 2023 and two in 2024: the first without disease incidence and the second when infection was already present in the plants. A total of 0.5 kg of soil was sampled from the root zone (between 5 and 20 cm depth, corresponding to the area of greatest microbial activity) at 50 cm from the base of the plant along the row. DNA extractions were performed with the PowerSoil Pro Kit (QIAGEN) on the 66 samples corresponding to the two samplings (11 varieties × 3 blocks) each year. Fungal DNA was amplified using primers ITS86F and ITS4 which amplify approximately 300 bp of the internal transcribed spacer region of the 18S rRNA–5.8S rRNA (ITS). Purification, library preparation, and sequencing were performed using the DADA2 method, which generated amplicon sequence variants (ASVs). Taxonomic identification from phylum to genus level for each sample was performed using the QIIME2 algorithm by Novogene.

To compare phylum and order data among samples, mean comparisons were performed using ANOVA with Duncan’s test at a significance level of 0.05. The same test was used to compare alpha diversity parameters based on genus-level data. The alpha diversity parameters analysed were richness (R), abundance (N), Shannon (H), Simpson 1/D (S1/D, values between 0 and 1), dominance (D, values between 0 and 1), evenness (E, values between 0 and 1), equitability (J), and Berger–Parker (d, values between 0 and 1). Beta diversity was analysed using the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), based on the Bray–Curtis (dis)similarity index. Anon-metric multidimensional scaling (NMDS) analysis using the Prefscal algorithm was used to position samples in a two-dimensional space based on their similarity in genus composition, highlighting the genera with the greatest weight in the analysis. Past 4.03 and SPSS v28 software were used for these analyses.

The analysis of the filamentous fungal microbiome, after applying a filtering process to remove singletons, allowed the identification of 238 genera belonging to 66 orders across 6 phyla. The phylum Ascomycota predominated in all samples, followed by Basidiomycota, as is typical in agricultural soil samples. Cryptomycota was detected only in samples from Fleurtai and Julius. Zoopagomycota was the least abundant phylum, although it was present in approximately half of the samples, with higher incidence in those originating from healthy plants. Hypocreales and Eurotiales were the two most abundant orders, representing more than 50% of total reads in most samples. Order level analysis revealed 11 orders with relative abundances above 1% of total reads: Sporidiobolales, Eremomycetales, Rhizophydiales, Auriculariales, Botryosphaeriales, Cantharellales, Chaetothyriales, Microascales, Cystofilobasidiales, Orbiliales, and Glomerales

In summary, the fungal microbiome exhibited populations characterized by the co dominance of the orders Hypocreales and Eurotiales (which together accounted for more than 50% of all reads), as well as by the marked presence of a core of saprotrophic and antagonistic genera. The greatest variability observed among fungal populations could be attributed primarily to the health status of the plant, outweighing factors such as variety or sampling year. The fungal communities of the two varieties most susceptible to pathogens, Tempranillo and Viura, showed the greatest divergence from the rest.

Implications for further research will be discussed.

Acknowledgements

This work has been funded by the Government of La Rioja, through grant Fortalece2021/08, RESVIN. We are very grateful to field staff at Plant resources Services and at the Governement of La Rioja for technical support.