Postgraduate Course: Applications of Data-Driven Breeding and Genetics to Real-Life Challenges (VESC11275)
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 brings together all the theory and practice delivered on the programme to date and applies it to real-life datasets from the Global North and South across species. This highlights the practicalities and challenges of working with 'real' data and the nuances required in modelling different datasets in order to implement successful breeding programmes.
Importantly, this course takes a holistic view on the use of breeding and genetics in practice; from identifying who the stakeholders are in this process, the evaluation of the economic, social, and environmental impact of recommendations made as well as the communication skills required to appropriately engage with the end-users and the public for effective dissemination. |
| Course description |
This online postgraduate course aims to collate and apply the statistical, computational, and biological concepts delivered across the programme to date in practice. This application is to 'real-life' datasets which allows students to experience the practicalities and challenges of working with 'real' data and the nuances required in approaches to modelling when working with different datasets (e.g. across species and from the Global North and South) in order to suggest improvements to breeding programmes. Further, this course is important in relaying to students the need for professional and considered dissemination of any results, which takes into account the different perspectives of stakeholders and the economic, social, and environmental context into which these are being delivered.
Key concepts and principles will be introduced and explored in pre-recorded lectures and case studies, as well as through discussion boards and practical online activities. This will be accompanied by recommended reading.
Themes covered during this 5-week course will include:
*Real-life datasets: animals and plants*
We present a number of 'real-life' datasets from animal and plant systems and Global North and Global South. Ultimately, we are going to take these datasets through analyses each week and bring together all the tools discussed in the programme so far.
Using example animal and plant records (datasets) from the Global North and South, we explore the use of AlphaSimR to understand how to evaluate and improve the breeding programmes in hand, and explore real-life case studies.
*Processes and impacts, and sustainability*
We look at the practicalities and challenges of using 'real' data and review the stakeholders involved in this process.
We explore the potential economic, social, and environmental impact of the breeding programmes suggested as results of our previous analyses. We link back to the United Nations Sustainable Development Goals (https://sdgs.un.org/goals) and how breeding and genetics can be used to build towards sustainable progress.
*Communication, consideration, and dissemination*
Here we consider how to communicate and disseminate our findings in relation to breeding programme improvements. Through this process, we consider the perspectives of all the stakeholders involved, regulation and legislations, and professional skills required to achieve successful impact.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Demonstrate a critical understanding of the practicalities, challenges, and opportunities of use of real-life data in the application of data-driven breeding and genetics in different contexts.
- Apply knowledge, skills, and understanding, using professional skills and materials/data that addresses and is informed by approaches and developments in data-driven genetics and breeding.
- Apply critical analysis, evaluation, and synthesis of forefront issues, that are informed by data or developments in the application of data-driven genetics and breeding.
- Using ICT applications and critical evaluations of data, to communicate to specific audiences(s) about the application of data-driven genetics and breeding.
- Manage complex professional issues, considering ethical and professional guidelines, and best practice related to animal/plant/aquaculture breeding and 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. R Chris Gaynor, Gregor Gorjanc, John M Hickey, AlphaSimR: an R package for breeding program simulations, G3 Genes|Genomes|Genetics. [https://doi.org/10.1093/g3journal/jkaa017]
2. Vignette: R Chris Gaynor, Introduction to AlphaSimR, CRAN. [https://cran.r-project.org/web/packages/AlphaSimR/vignettes/intro.html]
3. AlphaSimR Package. [https://cran.r-project.org/web/packages/AlphaSimR/vignettes/traits.pdf]
4. G Acquaah. 2012. Principles of Plant Genetics and Breeding. John Wiley & Sons, Ltd.
5. D. S. Falconer and T. F. Mackay. 1996. Introduction to quantitative genetics. Longman.
6. Plant breeding simulations with AlphaSimR. [https://acsess.onlinelibrary.wiley.com/doi/10.1002/csc2.21312] |
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.
Outlook and engagement: The University of Edinburgh graduate draws on quality, experiences, and expertise of others to engage with the global community in a manner that is respectful, ethical, and positive.
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. |
| Keywords | Real-life data,sustainable development,Global North,Global South,impact,agriculture |
Contacts
| Course organiser | Dr Steph Smith
Tel: (0131 6)50 6096
Email: Steph.Smith1@ed.ac.uk |
Course secretary | Mr Gordon Littlejohn
Tel:
Email: Gordon.Littlejohn@ed.ac.uk |
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