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Year of entry: 2023
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Course unit details:
Post-Genome Biology (L)
|Unit level||Level 3|
|Teaching period(s)||Semester 1|
|Available as a free choice unit?||No|
We live in a post genome world, where we can understand biological phenomena by studying all the molecules encoded in the genome at various levels. In this unit we review the state-of-the-art in post-genome biology, from a brief overview of genome sequencing itself through to models of entire systems. We will cover the challenges of genome annotation, comparative genomics, and informatic approaches to understanding evolution and function. This leads onto post-genomics, where we introduce methods to monitor the transcriptome (both coding and non-coding), illustrated with applications which show how new discoveries can be made. Proteomics follows this, explaining how the proteins encoded in the genome can be studied, and how they may be quantified and networks of interactions characterised. This leads on to systems biology, from basic principles to full kinetic models, which can predict and model biological function. Finally, structural biological context is added, considering how structure is integrated into biological function on the genome scale.
|Unit title||Unit code||Requirement type||Description|
|`Omic Technologies & Resources||BIOL21152||Pre-Requisite||Recommended|
This unit aims to explain how the increase in genome sequencing has underpinned many modern methodological advances in biological research that attempt to understand function, ultimately at a "systems" level. The material tackles the detail of the techniques, with a critical appraisal of their advantages and disadvantages, illustrated by examples from ground-breaking studies on a range of organisms from microbes to humans. The flow of the unit is from genome to systems, beginning with the complete genome itself, covering transcriptome, proteome, and integrated systems approaches including consideration of biological networks and protein structure.
Upon completion of this unit, students will be able to:
- describe modern approaches to genome sequencing and annotation, and how genome sequences can be compared to gain biological understanding.
- describe methods to study the dynamic transcriptome and proteome, and how they can be applied to gain insight into biological function, including prediction of gene function and genome annotation.
- appreciate the range of non-coding RNAs in the genome, and describe how they can be annotated and how they function in gene expression regulation.
- describe systems-based approaches to modelling and understanding biological function, including network biology and protein-protein interactions.
- explain how protein structure and protein interactions can be predicted on a genome scale.
- Use bioinformatics webtools and software to investigate example genomic datasets in the context of genomes.
Lectures begin with an introduction to the post genome world, then briefly covering recent advances in genome sequencing technology, followed by genome annotation and comparative genomics. This leads into post-genomics, where we introduce transcriptomics via arrays and next generation sequencing, illustrated with applications which show how new discoveries can be made. Proteomics follows this, explaining how the proteins encoded in the genome can be studied, and how they may be quantified and networks of interactions characterised. This leads on to systems biology, from basic principles to full kinetic models, which can predict and model biological function. Finally, structural biological context is added, considering how structure is integrated into biological function on the genome scale.
This is all backed-up via four discussion classes which explore key topics in more detail, centred around recent publications. Self-directed computer labs (on genome browsers and proteomics) allow student to explore two topics in further detail. The discussion classes help develop critical analysis in these areas - reviewing the latest developments in the field - and the two computer sessions develop practical computational skills, to help appreciate how data is presented and analysed in the context of the genome.
- Analytical skills
- Data analysis in the two computer self-directed tutorials .
- Group/team working
- As part of the discussion class exercise students are split into groups and have to work together to read assigned papers, understand key points, write a talk and then present it as a team.
- Opportunity for someone to lead group presentation activity.
- Oral communication
- All students (in groups) are asked to read and review a paper from the latest research (usually Nature or similar) in 4 discussion group sessions. They then present PowerPoint talks to the whole class and answer questions.
- Problem solving
- In computer tutorials students need to 'solve' a problem, using the information provided in the handout and the associated webtools. For example, in the proteomics lab they need to identify which protein isoforms are present given the mass spec search results.
- Students read and present research papers. They are also exposed to research methods in the two computer hands-on tutorials.
- Written communication
- Apart from the exam, there is also an essay mid-way through the unit. This is marked and feedback is provided on essays.
Examination; 2hr 45min online exam, Answering two questions from five (80%)
MCQ: 1 hour online exam (10%)
Class presentation mark: (10%)
This is provided in follow up lectures which explain concepts from the self-directed computer tasks, and the four Discussion classes, as well as via a mid-semester essay. In the discussion classes, you will present key research articles and receive feedback from staff and colleagues. We also set a mid-semester essay, where written feedback is provided. Finally, MCQs on the first three themes (genomics, transcriptomics, and proteomics) will test your understanding, with feedback provided on set of test questions. The MCQs are assessed (see above).
All our material is supported by journal articles and recent reviews, recommended by lecturers.
|Scheduled activity hours|
|Assessment written exam||2|
|Independent study hours|
|Simon Hubbard||Unit coordinator|