Course code BIO326

BIO326 Genome sequencing; tools and analysis

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Norsk emneinformasjon

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Showing course contents for the educational year starting in 2020 .

Course responsible: Matthew Peter Kent, Phillip Byron Pope
Teachers: Mariann Arnyasi, Torfinn Nome, Tan Thi Nguyen, Kristina Severine Rudskjær Stenløkk, Marie Odile Charlotte Andree Baudement, Marie Saitou, Arturo VeraPonceDeLeon, Ianina Altshuler, Live Heldal Hagen, Dag Inge Våge
ECTS credits: 10
Faculty: Faculty of Biosciences
Teaching language: EN, NO
(NO=norsk, EN=Engelsk)
Limits of class size:
20
Teaching exam periods:
This course starts in Spring parallel. This course has teaching/evaluation in Spring parallel.
Course frequency: Annually
First time: 2020H
Preferential right:
Priority is given to students admitted to the Master program Genome Science (M-GS) because this is an obligatory course for them.
Course contents:
Our ability to translate an organisms genetic blueprint (it’s genome) from chemical nucleotides to electronic sequence information that can be computationally analyzed has become a critical tool in many life science fields. Improving animal and plant health, ensuring  sustainable primary production, preserving genetic diversity, and better understanding the links between genome and biology are all research areas that rely heavily on decoding and analyzing genetic code. The same applies for microbes and microbiomes, which play essential roles regulating the many biogeochemical cycles that are essential to life on earth. Using the latest technologies and computational strategies, this course will explore the different approaches used to recover and reconstruct genome sequences from various biological sources including prokaryotic and eukaryotic cells, as well as complex microbial communities (i.e. microbiomes). You will learn about how the dominant sequence technologies work, different ways that DNA and RNA can be prepared to answer specific questions. Computational analysis will include a variety of algorithms used for DNA analysis AND genome curation and annotation and how they best suit a particular biological sample. From this, students should be able to design and execute both wetlab (e.g. DNA preparation) and drylab (computational biology) experiments and select the appropriate methods and software. 
Learning outcome:
  • Ability to design experiments and select appropriate wet lab methods and bioinformatic software and analysis pipelines.
  • Ability to sequence DNA and assess raw data quality
  • Ability to assemble and annotate genomes, execute taxonomic binning methods and interpret output quality
  • Ability to combine the output from different sequencing methods
  • Ability to generate genomes from both eukaryotic and prokaryotic organisms as well as complex microbial communities (i.e. metagenome)
  • Explain the shortcomings about these types of analyses
Learning activities:

The course will involve lectures and group teaching as well as (wet and dry) lab work. Lectures, group discussions and practical bioinformatic exercises will be integrated to enable students to work on assigned tasks, which will include generating raw data, analyzing datasets and reporting their findings. 

The wet-lab work is intended to give students practical experience with extracting DNA, assessing its quality, preparing it for sequencing (library production) and sequencing; the sequencing technology of choice will be long-read technology from Oxford Nanopore. Dry-lab work will entail running different bioinformatic software that are designed for genome assembly, binning, annotation and quality assessment. Students will work with both genome datasets from eukaryotes and prokaryotes as well as metagenomes from microbiome samples.

Teaching support:
Canvas
Syllabus:
Can be found at the BIO326-Canvas pages.
Prerequisites:
Familiarity with a programming language (preferably Python and/or R), as well as a basic knowledge in molecular biology, microbiology and/or cell biology is required.
Recommended prerequisites:
Mandatory activity:
Your presence and active participation in the entire course and in the group work are prerequisites for participating in the exam. 
Assessment:
The examination is a combination of oral presentations and a project notebook that will follow the course’s experimental exercises and must be submitted 3 weeks after the course. The assessments will be marked as passed/not passed.
Nominal workload:
300 hours.
Entrance requirements:
Special requirements in Science. Studnets need to sign up at StudentWeb
Reduction of credits:
-
Note:
-
Examiner:
The reports will be approved by an external examiner.
Examination details: Langsgående vurdering: Passed / Failed