Background Metagenomics is a widely used and powerful tool to characterize the microbial community inhabiting various environments. We are interested in metagenomics analysis applied to species of agricultural interest [1], ecologically relevant settings [2] food products [3, 4], and animal setting. Additional applications include the detection and characterization of viral pathogens of plants and animals [5, 6] Characterization of the metagenome can be undertaken using a targeted approach or a shotgun approach, each one with its advantages, which we have briefly discussed before [7]. In addition, several sequencing platforms are available. For each platform, different classifiers and different databases can be used. Finally, several methods exist to infer functional composition based on taxonomic composition.

Aim of the present PhD work will be to benchmark the different approaches using publicly available data and data produced by our research group to assess strengths and weaknesses of the different approaches, and to facilitate the harmonization of methodology in metagenomics analysis.
The successful applicant will be enrolled in the 40th Cycle of the PhD course in Agricultural Sciences and Biotechnology.

Interested candidates are strongly encouraged to contact Prof. Fabio Marroni (fabio.marroni@uniud.it) for informal discussion.


Bibliography
1. Savian F, Marroni F, Ermacora P, Firrao G, Martini M. A Metabarcoding Approach to Investigate Fungal and Oomycete Communities Associated with Kiwifruit Vine Decline Syndrome in Italy. Phytobiomes J. 2022;6:290–304.
2. Misson G, Mainardis M, Marroni F, Peressotti A, Goi D. Environmental methane emissions from seagrass wrack and evaluation of salinity effect on microbial community composition. J Clean Prod. 2021;285:125426.
3. Rossi A, Marroni F, Renoldi N, Di Filippo G, Gover E, Marino M, et al. An integrated approach to explore the microbial biodiversity of natural milk cultures for cheesemaking. J Dairy Sci. 2024. https://doi.org/10.3168/jds.2024-24463.
4. Marino M, Dubsky de Wittenau G, Saccà E, Cattonaro F, Spadotto A, Innocente N, et al. Metagenomic profiles of different types of Italian high-moisture Mozzarella cheese. Food Microbiol. 2019;79:123–31.
5. Di Gaspero G, Radovic S, De Luca E, Spadotto A, Magris G, Falginella L, et al. Evaluation of sensitivity and specificity in RNA-Seq-based detection of grapevine viral pathogens. J Virol Methods. 2022;300:114383.
6. Zanni V, Frizzera D, Marroni F, Seffin E, Annoscia D, Nazzi F. Age-related response to mite parasitization and viral infection in the honey bee suggests a trade-off between growth and immunity. PLOS ONE. 2023;18:e0288821.
7. Cattonaro F, Spadotto A, Radovic S, Marroni F. Do you cov me? Effect of coverage reduction on metagenome shotgun sequencing studies. F1000Research. 2020;7:1767.