5th-9th December 2022

Due to the COVID-19 outbreak, this course will be held online

This course will provide a thorough introduction to the growing field of speciation genomics. The course aims to take students from the initial steps required for handling raw sequencing data to demographic modelling and inference of genome-wide signatures of selection and introgression. Through a combination of lectures covering key theoretical and conceptual topics, alongside hands-on exercises, participants will learn the most important computational approaches used in speciation genomics. This will include a heavy emphasis on data visualization and intepretation. After completing of the course, the participants should be able to begin using NGS data to shed light on the genomic aspects of speciation in their study system of choice.

This course is designed for researchers and graduate students with strong interests in applying novel high-throughput DNA sequencing technologies to study the population genomic basis of speciation. The course will mainly focus on the analysis of NGS data for study systems for which a reference genome is available. We will provide theoretical lectures and hands-on exercises drawing on examples of whole-genome resequenced and RAD-sequencing data. Participants will make use of the UNIX command line and R.

The participants should have some basic background in evolution and genomics. No programming or scripting expertise is required. Previous experience in UNIX-based command line and R is an advantage. Because we will only provide a very brief introduction, 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 run in a Linux environment on remote servers. Statistical analyses will be run in R using RStudio.

1)      Handling NGS data from raw reads to genetic variants

2)      Applying basic population genetic statistics

3)      Visualizing the genetic structure

4)      Inferring demographic history

5)      Identifying regions under divergent selection or barriers to gene flow

6)      Understanding the potential and limitations of different methods to detect regions under selection

Day 1 - 2 -9 pm Berlin time

• Introduction to Unix

• Introduction to NGS data

• Mapping NGS reads to a reference genome