Postgraduate Course: Population and Quantitative Genetics for Breeding (VESC11280)
Course Outline
| School | Royal (Dick) School of Veterinary Studies |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This online postgraduate course covers fundamental principles of population and quantitative genetics, and guides the students through an in-depth understanding of estimating basic parameters for selective breeding. This course will cover topics including inheritance, quantitative traits, phenotypic and genetic variation, heritability, and resemblance between relatives, and predicting the response to selection and managing inbreeding for sustainable use of genetic resources.
The course will have a focus on practical implementation of the theoretical concepts, covering a wide range of case studies and examples for key terrestrial livestock, aquaculture, and plant species, and with practical and live Q&A sessions aiming for the students to develop strong statistical, programming and data analysis skills. |
| Course description |
This course aims to develop the students' understanding of key principles in population and quantitative genetics theory, and their role in data-driven breeding. The students will develop an understanding of the theorical background of quantitative genetics and, by the end of this course, they will be confident and able to calculate key genetic parameters essential to modern breeding programmes in terrestrial livestock and aquaculture species, and plants.
The course will advance the students' statistical and programming skills by emphasizing on the practical implementation of those principles, teaching how to perform essential calculations of key genetic parameters, and using statistical software and computational techniques commonly used in this field. Further, the course will discuss relevant sustainability challenges (e.g., managing genetic diversity and sustainable management of genetic resources).
Key concepts will be introduced and explored in pre-recorded lectures and invited seminars, and in discussion boards and weekly online activities. Their practical applications will be worked through in asynchronous practical sessions mainly using the R statistical package (and specialized R packages such as AlphaSimR), and live Q&A troubleshooting sessions, alongside recommended readings and self-directed learning.
Real-world training will be supported and encouraged using case studies and real-world examples in all teaching material, and by using state-of-the-art computational pipelines throughout the practical sessions.
Themes covered during this 5-week course will include:
*Introduction to genomes & inheritance*
Key concepts in population and quantitative genetics will be introduced, including: genotypes and phenotypes, inheritance, meiosis, recombination, and linkage disequilibrium, as well as an introduction to specialised software (AlphaSimR) that will be used throughout the practical sessions.
*Quantitative trait variation*
Will cover phenotypic and genetic variation, genotypes, genetic architecture and quantitative traits, as well as estimation of genetic parameters such as means, genotypic and allelic frequencies, variance components, and heritability.
*Selection and response to selection*
Will focus on genetic selection and key parameters affecting response to selection (the Breeder's equation). More advanced concepts such as correlated traits, selection indices, and genotype-by-environment interactions will be introduced.
*Resemblance between relatives*
Will explore resemblance between relatives, pedigrees, kinships and relationship matrices.
*Managing genetic diversity*
Will discuss sustainability issues, exploring management of inbreeding, heterosis, effective population size, sustainable management of genetic resources, and introduction to optimum contributions theory.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2025/26, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
MVM Online Learning Block 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Online Activities 33,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
65 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Formative: There will be a number of Multiple-Choice Questions (MCQs) to assess knowledge and understanding of quantitative and population genetics and R markdown. Discussion boards will also provide opportunities for feedback.
Summative assessments:
1. R Markdown analysis report in relation with population and quantitative genetics (70%)
2. Soundbite of report (30%) |
| Feedback |
The formative assessments will allow students to learn from feedback on these before embarking on the final summative assessments. Feedback will be in accordance with policy and regulations to ensure it is timely, consist of tangible suggestions such that it is actionable and relevant to the question being asked as well as the course and the programme going forward. Students are encouraged to reflect on their feedback and discuss with course leads if they need clarification of feedback received. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Demonstrate a critical understanding of the theory, and the key principles and concepts in quantitative and population genetics.
- Apply knowledge, critical analysis, evaluation, and synthesis to develop specialised practical skills and techniques, and demonstrate an understanding of the application in practice of quantitative genetics theory.
- Communicate, using appropriate methods, to specific audiences/stakeholder groups with different levels of knowledge or expertise.
- Taking responsibility for managing complex/range of data and making informed judgements on issue/challenge(s) relating to quantitative genetics.
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Reading List
The reading list will be provided electronically via Resource Lists. Essential/recommended and further reading and resources that align with the weekly content and course topics will be made available through the University Resource List platform. Here is an example of potential resources to be included:
1. D. S. Falconer and T. F. Mackay. 1996. Introduction to quantitative genetics. Longman.
2. B. Walsh and M. Lynch. 2018. Evolution and Selection of Quantitative Traits. Oxford.
3. G. Acquaah. 2012. Principles of Plant Genetics and Breeding. John Wiley & Sons, Ltd.
4. G. Simm, G. Pollott, R. Mrode, R. Houston, K. Marshall. 2021. Genetic improvement of farmed animals. CABI.
5. R.C. Gaynor, G. Gorjanc, J.M. Hickey. 2021. AlphaSimR: an R package for breeding program simulations. G3 Genes|Genomes|Genetics |
Additional Information
| Graduate Attributes and Skills |
Enquiry and lifelong learning: The University of Edinburgh graduate seeks personal and academic learning in order to inform, guide, or make a positive difference to knowledge-creation, others, or themselves. Inspired by their exposure to world-leading research and innovative practices, they continue their own journey of life-long learning.
Research and enquiry: The University of Edinburgh graduate develops their skills in research and enquiry, including problem-solving, analytical, and critical thinking, and digital literacies.
Personal and intellectual autonomy: graduates use their personal and intellectual autonomy to think independently, exercise personal judgement, and analyse facts and data in order to develop appropriate solutions. |
| Keywords | Quantitative genetics,genetic variation,heritability,selective breeding |
Contacts
| Course organiser | Dr Smaragda Tsairidou
Tel: (0131 6)517112
Email: Smaragda.Tsairidou@ed.ac.uk |
Course secretary | Miss Stavriana Manti
Tel: (0131 6)50 5310
Email: stavriana.manti@ed.ac.uk |
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