This course provides an introduction to the study of the genomic basis of adaptation through population genomics and comparative genomics approaches.

Participants will learn to analyze both sequence and structural genetic variation using cutting-edge methods. The course guides participants from the basics of pre-processing genomic data, variant calling, and summary statistics, through population structure analysis, up to advanced topics such as genotype-phenotype and genotype-environment association analyses, structural variant detection, and the analysis of gene family evolution and transposable elements.

Through a combination of theoretical lectures and hands-on practicals, participants will gain experience with widely used bioinformatics tools and workflows for the study of adaptation.

By the end of the course, participants will understand the opportunities and challenges of studying the genomic basis of adaptation and will be able to apply similar methods to their own datasets. 

This course is designed for graduate students, postdocs, and researchers interested in applying genomic tools to study adaptation in natural populations.

Previous experience in UNIX-based command line and R is required. We would like to ask participants without previous experience in R to go through this tutorial and participants without previous knowledge in the unix command line to go through this tutorial before the course. 

All hands-on exercises will be performed on remote Linux servers, with data analysis and visualization performed in R (using RStudio) and other bioinformatics software. 

The course will focus on the analysis of high-coverage whole-genome and long-read sequencing data. It will be delivered online over five days, combining live lectures with hands-on practical exercises that participants can complete on a flexible schedule within the course day.

The course will run from 14:00 to 19:00 CET to accommodate participants from different time zones.

Interaction among participants and with instructors will be encouraged through live video conferencing and a dedicated Slack workspace.

By the end of the course, participants will be able to:

1. Pre-process and analyze whole-genome sequencing data, including variant calling and filtering

2. Compute key population genomics statistics and investigate population structure

3. Detect genomic regions and variants involved in local adaptation and selection

4. Annotate genomic features and visualize genome data

5. Analyze gene family evolution and detect selective pressures

6. Identify structural variants and study their role in adaptation, including the impact of transposable elements

7. Understand the strengths, limitations, and appropriate applications of various genomic methods for studying adaptation

Live sessions from 2 to 7 pm Berlin time

Monday
• Lecture: General introduction to adaptation genomics
• Practical: Introduction to basic pre-processing of NGS data – general QC, trimming, data types, genome annotation

Part 1 - Population Genomics
• Lecture: Population genomics analysis using whole genome data
• Practical: Basic handling of population genomics data – variant calling; variant filtering

Tuesday
• Lectures: Factors affecting genomic differentiation – population structure, recombination, etc.
• Practical: Summary statistics (nucleotide diversity, FST) and methods to investigate population structure (PCA, Admixture). R package SambaR, for automated analyses containing other tools (e.g. ADMIXTURE, OutFLANK).

Wednesday
• Lectures: Strength and weaknesses of outlier detection, phenotype-genotype and environment-genotype association methods
• Practical: FST-outliers detection, phenotype-genotype and environment-genotype association methods (BayPass)

Part 2 - Comparative Genomics
• Lectures: Comparative genomic analysis for the study of adaptation
• Practical: Genome features annotation – transposon annotation, tandem repeats annotation, and rDNA annotation. IGVvisualisation of genomic data

Thursday
• Lectures: Characterizing selective pressures and gene family evolutionary histories
• Practical: Genome-scale identification of orthologous genes (OrthoFinder), gene family evolutionary analyses – counts-based methods (CAFE) vs gene tree–species tree reconciliation methods (GeneRax), detection of selective pressures with dN/dS (HyPhy)

• Lectures: Structural variants in genomic adaptation
• Practical: Identification of syntenic, rearranged genomic regions and structural variants based on whole genome alignments (Minimap2/MuMMer and Syri/SVIM-asm) and gene order conservation (GENESPACE)

Friday
• Lectures: Structural variants in genomic adaptation – the role of transposons
• Practical: TE curation (automatic vs manual, i.e. MCHelper) and identification of transposon-related rearrangements and the involved genes (Bedtools)

• Discussion: QA for whole course
• Closing lecture/s

Cancellation Policy:

> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.

Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.