The course is designed to provide an understanding of microbiome analysis, from sample collection to advanced data interpretation, fostering the development of skills necessary for addressing ecological questions related to forest microbial communities.
This advanced PhD course offers a comprehensive exploration of microbiome data analysis with a specific focus on its application in the field of forest ecology. The course is structured around these key components:

Lectures on Metabarcoding in Forest Ecology: Principles, methodologies, and applications of metabarcoding techniques within the context of forest ecology. Lectures will cover the latest advancements in DNA sequencing technologies and bioinformatics tools essential for understanding microbial communities in forest ecosystems.

Hands-on eDNA Sampling: Practical session where participants gain firsthand experience in collecting environmental DNA (eDNA) samples from forest ecosystems, covering proper sampling techniques, preservation methods, and considerations for ensuring the accuracy and reliability of eDNA data.
Molecular Lab Analysis: This module guides students through the molecular laboratory analysis of collected eDNA samples. Techniques such as DNA extraction, PCR amplification, and sequencing will be covered.

Principles of Bioinformatics: This module offers a foundational understanding of bioinformatics principles essential for processing, managing, and interpreting large-scale microbiome datasets. Topics include sequence data quality control, and taxonomic assignment.

Practical Exercises on Microbiome Data Analysis using R: These sessions will cover data preprocessing, statistical analysis, and visualization techniques specific to microbiome datasets derived from forest environments. Emphasis will be placed on interpreting results in the context of ecological questions and drawing meaningful conclusions from complex microbial community data.

Written Report: The course culminates in a research project where participants conduct in-depth analyses of microbiome data. They are either provided with real-world data sets or work on their own, followed by the creation of a written report detailing their findings and interpretations.

Knowledge:

• Gain in-depth knowledge of the principles, methodologies, and applications of metabarcoding in the context of forest ecology.
• Demonstrate a thorough understanding of proper eDNA sampling techniques, including considerations for sample collection, preservation, and quality control.
• Understand the application of bioinformatics tools specific to microbiome datasets, with a focus on translating results into ecological insights.

Skills:

• Develop hands-on skills in implementing metabarcoding techniques, from experimental design to data interpretation.
• Demonstrate competence in troubleshooting common challenges encountered during metabarcoding experiments.
• Apply practical skills in eDNA sampling, ensuring accurate and reliable collection of environmental samples in diverse forest environments.
• Apply R programming skills to perform advanced analysis on microbiome datasets, including diversity metrics, differential abundance analysis, and community structure assessments.

Competences:

• Demonstrate the ability to design and execute research projects involving microbiome analysis in forest ecology, integrating metabarcoding techniques and eDNA sampling.
• Exhibit problem-solving skills in addressing challenges associated with metabarcoding experiments, eDNA sampling, and microbiome data analysis.

Prof. Leho Tedersoo , Mycology and Microbiology Center, University of Tartu (EE), is an expert on microbiome and molecular identification methods. He will introduce the usage of next generation sequences and metabarcoding techniques to investigate the microbial diversity in forest ecosystems.  

Dr. Sofia Fernandes Gomes, Institute of Biology, University of Leiden (NL), is an expert in above-belowground interactions with an in-depth knowledge of the workflow for microbiome sequence analysis using the statistical software R. She will assist during the hands-on exercises on datasets and provide the theoretical background on the different steps of the analyses. 

Dr. Giovanni Emiliani, NRC (IT), is an expert on molecular and functional characterization of fungal species and endophytic bacteria in forest ecosystems. During the course, he will introduce the complex relationships that fungi establish with plants, the processes of antagonism between symbiotic and pathogenic species and he will provide examples of how to link microbiome sequencing results to ecologically relevant functions.

Collaborating Partners:

• Sofia Gomes, University of Leiden 30%
• Leho Tedersoo, University of Tartu 30%