MAE-50806 Advanced Molecular Ecology

Course

Credits 6.00

Teaching methodContact hours
Individual Paper2
Lecture18
Tutorial30
Practical24
Course coordinator(s)dr. R Nijland
Lecturer(s)dr. ir. BA Pannebakker
dr. ir. JWM Bastiaansen
dr. R Nijland
prof. dr. AJ Murk
dr. ir. HJ Megens
J van den Heuvel
DL Maas
Examiner(s)prof. dr. AJ Murk

Language of instruction:

EN

Mandatory knowledge:

ZSS06100 Laboratory Safety

Assumed knowledge on:

This course is aimed at MSc students that are interested to combine genomics and transcriptomics approaches including hands on bioinformatics to assess biodiversity, non-indigenous species, genetic heterogeneity, population genomics, adaptations to changing environments, with organisms ranging from microbes to fish and insects. Especially MSc students Biology (MBI) and Aquaculture and Marine Resource Management (MAS) are expected to profit from this course.
Basic knowledge molecular biology and genetics, builds upon BSc courses like;
GEN-20306 Molecular and Evolutionary Ecology
GEN-11806 Fundamentals of Genetics and Molecular Biology
BIF-20306 Introduction to Bioinformatics 
MIB-10306 Microbiology & Biochemistry
Builds upon MSc course: GEN-30806 Population and quantitative genetics


Continuation courses:

MAE-Thesis ABG/GEN/MAE, and Internship ABG/GEN/MAE, MAE-50306 Short Research Projects in Marine Animal Ecology




Contents:

The course discusses how to obtain data on the biodiversity, genomic diversity and adaptation of organisms to changing environments using DNA sequencing technology on a diversity of samples including eDNA from water samples. Through lectures and tutorials, this course will introduce the main principles underlying biodiversity and genetic diversity assessment using DNA sequencing. Characterisation of diversity, from within species to species community, will be used to infer ecosystem functioning and infer response to a changing environment. These techniques are for example applied to understand how species can invade new environments, how animals adapt to climate change, and how isolated populations change genetically. In this advanced course the focus lies on approaches to obtain and analyse complex datasets, and interpret their biological meaning. During the tutorials  and practical, students will work on several case studies to analyse a specific biodiversity or genome dataset. Since advanced tools for analysing genomic datasets usually require Linux and command-line skills, an introduction to acquiring basic competences in this area will be included. 
The topics that are treated cover: 
- Population genomics – variation within and between population;
- microbiome diversity;
- DNA metabarcoding;
- environmental DNA;
- next generation/third generation DNA sequencing technologies
- data-analysis: Linux, programming concepts, and scripted data analysis
- landscape genomics
- from genome function to ecology

Learning outcomes:

After successful completion of this course students are expected to be able to:
- reconstruct evolutionary processes using genomic data;
- assess biodiversity using metagenomic or metabarcoding sequencing data;
- describe the different DNA sequencing methods available survey biodiversity;
- design appropriate sampling and sequencing approaches in order to collect meaningful data;
- analyse the ecological status of the sampled ecosystem based on a metagenomics sequencing experiment.
- interpret and convert the raw sequencing data into clear information on the ecosystem studied using appropriate bioinformatics tools;

Activities:

- lectures;
- tutorials;
- practical (DNA isolation+ metabarcode amplification+ sequencing).
- individual project

Examination:

The students have to pass two self-tests with >80% score. Examination is based on participation in tutorials, reporting and defense of own work (poster) on a selected topic, and an electronic exam.
Results from the participation in tutorials, poster and defence, and the exam all count for the final mark (10:40:50). The minimum mark for the exam is 5.5

Literature:

All study materials will be made available on Brightspace. This will consists of links to relevant recent literature, to the presentations of the lectures, and further background information in review papers. Also the contents of the computer exercises for the tutorials and self tests are available via BrightSpace.