Overview

This course will introduce attendees to how the tools of population genomics can be used to inform conservation. The instructors will guide students through study design, genomic data collection methods, handling of raw genomic data, and SNP filtering to produce a dataset. Then, we will work through a suite of analyses looking at population structure, local adaptation, effective population size, inbreeding and relatedness. We will provide background on the theory and application of these analyses, and then run hands-on exercises running analyses and interpreting results. Through hands-on exercises, the course will teach basic bioinformatics skills and how to manipulate, visualize and interpret genomic data and patterns in a conservation related context.
For participants interested in more advanced applications of genomics to conservation decision-making, the Advanced Conservation course covers interpretation of genomic metrics, methodological limitations, and translating results into management strategies

Target audience and assumed background

The course is aimed at graduate students and researchers who are interested in using genomic tools to address issues in conservation. Participants should have some basic background in evolution and population genetics. Previous experience in UNIX-based command line and R is required. Hands-on exercises will be run in a Linux environment on remote servers and data analysis and visualization will be run in R using RStudio.

Teaching format

The course will be delivered fully online over 4 half-day (5 hour) sessions, with a combination of lectures and practical exercises that will be live (synchronous). Discussions among participants and with the instructors on concepts and data analyses will be possible through video conferencing and a dedicated Slack workspace.

Learning outcomes

1.    Study design and genomic data collection methods
2.    Handling genomic data from raw reads to a filtered dataset of SNP genotypes
3.    Assessing population structure using multiple methods
4.    Searching for signals of adaptation
5.    Estimating effective population size
6.    Calculating inbreeding
7.    Estimating relatedness

Day1 – Classes from 2-8 pm Berlin time

Part 1 – Introduction to genomic data (E. Jensen)
In this first session we will have an opportunity to get to know each other and the variety of research interests in the group. We will also explore different aspects of a population genetic study, including best practices around sampling, quality of DNA samples, and the various methods to generate genetic data for your species of interest. Finally you will be introduced to the various file types you will encounter when conducting studies that use NGS to generate genotype data.

Lecture breakdown
•    Introduce yourself and your research interests
•    Discuss study design: DNA sample sources, quality of DNA, sample sizes
•    Discuss genetic data collection methods: whole genome sequencing, capture (exon or mtDNA), RADseq, SNP panel
•    Introduce various file types (fastq, fasta, SAM/BAM, vcf, BED, program specific inputs)

Practical
•    Explore fastq sequence files typically generated by sequencing software
•    Check quality of fastq files using FastQC
•    Trim data to remove adapters, poor quality data

Part 2 – Alphabet soup (E. Jensen)
In this second half of day one you will learn how to assemble your raw sequence data to a reference genome, and learn how to assess quality of your assembly. You will be introduced to de novo approaches for studies where your species does not have a reference genome available. Finally, you will learn the basics of SNP genotype calling, and haplotype calling.

Lecture breakdown
•    Accessing reference genomes, understanding their quality, “in-group” reference bais
•    General introduction to de novo approaches
•    General introduction to the idea of SNP calling

 Practical
•    Examine the files associated with a reference genome, and index it
•    Assemble reads to the genome using BWA
•    Check the quality of assembly, filter the data using BAM
•    Call SNPs using BCFtools mpileup/call, generate a VCF output file of genotypes

1 - Population Genomics - ONLINE, 16-20 March

2- Deep Learning in Population Genomics & Phylogeography - ONLINE, 23-26 March

3 - Introduction to GWAS - ONLINE, 18-22 May

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.