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
Week 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.
Week 2. Genome annotation 2: visualisation, manual refinement, functional noncoding DNA (Artemis software; RFAM database). Lecture on principles, sources of data and interpretation of evidence; computer-based practical class.
Week 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.
Week 4. Genome and gene-family phylogenies (multiple alignment and phylogeny reconstruction; MAFFT and IQ-TREE software). Lecture on algorithms; computer-based practical class. Formative assessment hand-in.
Week 5. Reconciling gene and species trees (Notung software). Lecture on concepts and algorithms; computer-based practical class. Coursework assignment set.
Week 6. Homology - orthologs, paralogs and xenologs 1 (including sub-types of paralog and xenolog; Notung software). Lecture on concepts and case-studies of biomedical relevance; computer-based practical class.
Week 7. Homology - orthologs, paralogs and xenologs 2 (Notung software). Lecture on algorithms, batch analyses and highways of horizontal gene transfer; computer-based practical class. Formative assessment returned with feedback.
Week 8. rDNA variation and evolution. Guest lecturer (from Quadram Institute Bioscience). Lecture and computer-based practical class.
Week 9. Q&A tutorial. Students can raise questions about coursework, course content and exams. No practical class.
Week 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 Introduction to Bioinformatics for Life Scientists (PGBI11117) taken concurrently in Semester 2; or by previous experience. |
Course Delivery Information
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Academic year 2019/20, Not available to visiting students (SS1)
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Quota: 42 |
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 |
Written feedback will be provided for both ICA and exam. |
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: Daniel.Barker@ed.ac.uk |
Course secretary | Ms Louise Robertson
Tel: (0131 6)50 5988
Email: Louise.K.M.Robertson@ed.ac.uk |
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