Postgraduate Course: Breeding Programmes and their Modelling (VESC11276)
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 fundamentals and current status of structure, design, evaluation, and optimisation of breeding programmes. It will introduce concepts, analytical and computational tools that are required to understand evaluate and optimise the performance of breeding programmes with varying structures, giving the students the skills to apply these across species. We will showcase computational tools that allow modelling simple and highly complex breeding programs, such as commercial breeding programmes or those in alternative production systems such smallholder farms in low- to middle-income countries, and illustrate the importance of simulation to optimise breeding programmes, with real-life impacts.
The course will have a focus on practical implementation, covering case studies and examples for animal and plant species, and with practical sessions aiming for the students to develop strong statistical, programming and data analysis skills. |
| Course description |
This course aims to develop the students' understanding breeding programmes, how they can be described, evaluated, modelled, and optimised, using computer simulation and analytical skills. The students will become familiar with different structures of breeding programmes across species and production systems and, by the end of this course, will be able to identify and assess key performance indicators, understand how these change with different breeding strategies, and communicate this to a range of stakeholders.
The course will strengthen the students' statistical and computational skills by focusing on hands-on practical sessions, and the use of appropriate and current general and specialised software solutions. Further, the course will discuss the contribution of these tools and their uses to tackle Global sustainability challenges affecting food security and sustainable agricultural production of feed, heat, power and raw materials.
Key concepts will be introduced and explored in a directed framework with pre-recorded lectures, invited seminars and case studies, and in discussion boards and weekly online activities. Their practical applications will be worked through in asynchronous practical sessions mainly within the R statistical package framework, using current general and specialised software such as R and the AlphaSimR R package. There will also be an independent learning component, including recommended resources for self-directed learning, leading to the assessments.
We strive to facilitate an authentic learning experience, centred on authentic, relevant, real-world challenges, through the use case studies and real-world examples in our teaching, and using state-of-the-art computational pipelines throughout the practical sessions. This will be accompanied by self-directed learning, reflective activities and discussion board interactions designed to support the development of a community of practice with the potential to support the students beyond the course. Throughout the course, there will be opportunities to enhance professional skills, such as communication and presentation, through hands on activities.
Themes covered during this 5-week course will include:
*Breeding programmes: overview*
We will introduce breeding programmes, the rationale behind them, context -including Global and production system contexts-, and structure, breeding goals, data used, evaluation methods and key performance indicators and sustainability.
*Breeding programme modelling using AlphaSimR*
We will use state-of-the art software to model breeding programmes using stochastic simulation.
*Breeding programme evaluation*
We will introduce key performance indicators to evaluate the performance of breeding programmes.
*Assessing the effect of changes in breeding programme parameters through simulation*
We will use simulation to understand and assess changes in key performance indicators when we modify breeding programmes. We will discuss and train on how to communicate these to relevant stakeholders.
*Applications to a range of species of agricultural importance*
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
|
| Academic year 2025/26, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
MVM Online Learning Block 3 |
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 to assess knowledge and understanding of breeding programmes, as well as practice reports. Coding activities will prepare students for summative assessment. Discussion boards will also provide opportunities for feedback through activities and more generally.
Summative assessments:
1. Simulate breeding programme and interpret output (50%)
2. Interpret complex breeding programme simulation output and communicate to stakeholders (50%) |
| 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 knowledge and understanding of the principal concepts and processes of the design of breeding programmes.
- Apply knowledge, skills and understanding in using a range of specialised skills, techniques, practices and/or software, that are at the forefront of breeding programme design and evaluation.
- Apply critical analysis, evaluation, and synthesis to forefront issues/examples/developments/approaches that apply to breeding programme design and implementation.
- Undertake critical evaluations of a range of numerical data, using software/ICT applications, which are appropriate for breeding programme design and implementation.
- Take responsibility for a range of complex data and make informed professional decisions in relation to current research problems in breeding programme design and implementation.
|
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. G Simm, G Pollott, R Mrode, R Houston, K Marshall. 2021. Genetic improvement of farmed animals. CABI.
2. G Acquaah. 2012. Principles of Plant Genetics and Breeding. John Wiley & Sons, Ltd.
3. DS Falconer and TF Mackay. 1996. Introduction to quantitative genetics. Longman.
4. Gorjanc (2023) The genome and phenotype. In: Linear models for the prediction of the genetic merit of animals. CABI. [https://www.cabidigitallibrary.org/doi/book/10.1079/9781800620506.0000]
5. Gaynor, R.C., Gorjanc, G., Hickey, J.M. (2021), AlphaSimR: an R package for breeding program simulations, G3 Genes|Genomes|Genetics. [https://doi.org/10.1093/g3journal/jkaa017]
6. Gaynor et al. (2017) A Two-Part Strategy for Using Genomic Selection to Develop Inbred Lines [https://doi.org/10.2135/cropsci2016.09.0742]
7. Bancic et al. (2024) Plant breeding simulations with AlphaSimR [https://acsess.onlinelibrary.wiley.com/doi/10.1002/csc2.21312]
8. Werner et al. (2024) FieldSimR: an R package for simulating plot data in multi-environment field trials [https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2024.1330574/full]
|
Additional Information
| Graduate Attributes and Skills |
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 effectiveness: The University of Edinburgh graduate will draw from their experiences and knowledge to ensure they can adapt to new, fluid, or complex situations/scenarios with sensitivity, integrity, and confidence.
Communication: The University of Edinburgh graduate uses communication skills to articulate and effectively explain information, including complex data, to engage with different audiences or situations. |
| Keywords | Breeding programme,genetic and genomic evaluation and selection,sustainable breeding |
Contacts
| Course organiser | Prof Gregor Gorjanc
Tel:
Email: Gregor.Gorjanc@roslin.ed.ac.uk |
Course secretary | Miss Stavriana Manti
Tel: (0131 6)50 5310
Email: stavriana.manti@ed.ac.uk |
|
|
University Homepage