Postgraduate Course: Comparative and Evolutionary Genomics (PGBI11115)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | The course covers primary genome annotation, including protein-coding and RNA genes in prokaryotes and eukaryotes; predicting gene/protein families across species; genome and gene-family phylogenies; reconciling gene and species trees; rDNA variation and evolution (partial SNPs or pSNPs); homology ¿ orthologs, paralogs and xenologs; whole-genome comparison of large genomes; and pan-genomes and applications. Lectures are supplemented by on-line exercises and tutorials and in-course assignments. |
| Course description |
Detailed Programme
1. Genome annotation 1: protein-coding genes (gene finding, ab-initio and homology-based; prokaryotes and eukaryotes; TBLASTN and BRAKER software). Lecture on principles, algorithms, sources of data and interpretation of evidence; computer-based practical class.
2. Genome annotation 2: visualisation, manual refinement, functional noncoding DNA (Apollo software; RFAM database). Lecture on principles, sources of data and interpretation of evidence; computer-based practical class.
3. Predicting gene/protein families across species (beginning with genome-wide protein sets; OrthoMCL and OrthoFinder software). Lecture on algorithms; computer-based practical class. Formative assessment set.
4. Genome and gene-family phylogenies (multiple alignment and phylogeny reconstruction; MAFFT and PhyML software). Lecture on algorithms; computer-based practical class. Formative assessment hand-in.
5. Reconciling gene and species trees (Notung software). Lecture on concepts and algorithms; computer-based practical class. Formative assessment returned with feedback. Coursework assignment set.
6. rDNA variation and evolution. Guest lecturer (from Quadram Institute Bioscience). Lecture and computer-based practical class.
7. Homology ¿ orthologs, paralogs and xenologs (including sub-types of paralog and xenolog; Notung software). Lecture on concepts, algorithms and case-studies of biomedical relevance; computer-based practical class.
8. Q&A tutorial. Students can raise questions about coursework, course content and exams. No practical class.
9. Whole-genome comparison of large genomes (MUMmer, NUCmer and PROmer). Lecture on algorithms and case-studies; computer-based practical class.
10. Pan-genomes and applications (¿core¿ and ¿dispensable¿ components; ¿guilt by association¿ functional predictions from phylogenetic profiles and correlated gain/loss of genes). Lecture on algorithms; computer-based practical class.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | There is no formal pre-requisite for this course. However, students must have experience of the Linux command-line. This may be obtained, for example, by taking Bioinformatics Programming and System Management (PGBI11095) in Semester 1; or by Bioinformatics (PGBI11006) taken concurrently in Semester 2; or by previous experience. |
Course Delivery Information
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| Academic year 2017/18, Not available to visiting students (SS1)
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Quota: 40 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 18,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
70 )
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| Assessment (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
In-course continuous assessment (50%). Exam (50%). |
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S2 (April/May) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- choose and apply algorithms and software to compare genome sequences, to make discoveries of evolutionary and/or functional importance.
- have enhanced competence and skills in bioinformatics.
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Additional Information
| Graduate Attributes and Skills |
Computational thinking. Computer literacy. Bioinformatics. Interdisciplinarity. |
| Additional Class Delivery Information |
Weekly lectures (~1 hour) and practical classes (~2 hours) will include time to comment on whole-class performance. |
| Keywords | MSc Bioinformatics |
Contacts
| Course organiser | Dr Daniel Barker
Tel: (0131 6)51 7812
Email: |
Course secretary | Miss Emma Currie
Tel: (0131 6)50 5988
Email: |
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