MSc Precision Medicine

This 15 credit Unit is broadly structured into two parts. The first part of this Unit introduces students to the theoretical and practical skills and knowledge required to evaluate the contribution of genetic variation to human health and disease. The human genome comprises millions of nucleotides of genetic variation. Understanding genetic variation and its potential impact on human health and susceptibility to disease is essential for developing effective preventative or therapeutic treatment strategies to improve quality of life, for use in precision and stratified medicine, and may provide useful diagnostic biomarkers. The second part of this Unit aims to provide an understanding of the relationship between transcriptomics and functional genomics with life processes, the importance of measurements in these research fields, and the influence of data gathering process on data analysis. An appreciation of innovation and commercialization in the biotech industry will also be developed. This Unit is delivered using a combination of lectures, seminars and computer workshops.

The aims of this Unit are to provide students with theoretical knowledge and understanding of the scientific fields of genetics, transcriptomics and functional genomics, the use of computational and data analysis strategies to interrogate genetic and genomic datasets, and how these fields relate to human health and disease.

This Unit comprises lectures/tutorials and computer workshops totalling ~30 hours of teaching. The teaching and learning content cover the basis of genomic structure and variation, experimental methods available to measure this variation, methods to assess the potential contribution of genetic variation to human health and disease susceptibility and how this variation may give rise to differing responses to therapeutic treatment. This unit also covers how transcription works in the control of cell activity, how measurements can be made in the laboratory using different types of established and emerging techniques and methods to identify dysregulated transcripts associated with pathogenesis. Speakers have been invited from the private sector to discuss how innovation can lead to a commercial enterprise and the inter-relationship between industry and academia.

This Unit is delivered using a combination of lectures, seminars and computer workshops. Lectures are delivered by individuals from the academic, clinical and commercial sectors, including discussion of how innovation can lead to a commercial enterprise and the inter-relationship between industry and academia. The genetics component comprises approximately 16 hours of in-person or online lectures/ seminars and two computational workshops (a total of 21 hours) using online resources for interrogation of genetic data, genetic study design and statistical analysis. The transcriptomics and functional genomics component comprises approximately ten hours of teaching. A two-hour workshop may be included to allow students to manipulate genomics data.  

All lectures are supported with examples of online electronic resources and/or key references.  

Students are also provided with a formative MCQ and short-answer series of questions for self-directed learning. Students work both independently and in groups of 3-4 towards a formative group oral presentation. These group presentations provide further contact time and opportunities for learning and formative feedback.  

Students should be able to:  

i) Explain the basis of genomic structure and variation  

ii) Summarise the different experimental and analytical methods to measure genetic variation and assess its potential contribution to the molecular basis of human disease 

iii) Determine how genetic variation may provide useful diagnostic markers and give rise to differing responses to drug treatment  

iv) Summarise the role of transcription in the control of cell activity  

v) Explain the importance of measurements in transcriptomics and functional genomics 

vi) Critically evaluate the influence of experimental design and the data gathering process on analysis of gene regulation data  

vii) Summarise the role of new and emerging technologies in measurement of gene activity 

viii) Recall the role of innovation and commercialisation in transcriptomics and functional genomics in the biotechnology industry

Students will be able to:  

i) objectively analyse and critically interpret data relating to genetics, transcriptomics and functional genomics  

ii) critically evaluate experimental and in silico methodologies relating to genetics, transcriptomics and functional genomics 

iii) recognise, define and formulate questions in relation to the use of genetic and genomic techniques to investigate human health and disease

Students will be able to:  

i) carry out focussed searches to identify, retrieve and manage key literature relevant to a particular topic  

ii) critically appraise the literature  

iii) apply in silico resources or tools to retrieve, manipulate and analyse genetics and genomics data  

iv) communicate ideas and results of analyses in a clear, concise and effective manner.

Students will be able to:

i) demonstrate effective oral and written communication skills

ii) set priorities and manage time effectively

iii) demonstrate capacity for self-directed learning and independent thinking and to utilise problem solving skills.

Marks and written feedback are provided to students on all summative and formative assessments, including feedback on what was done well and what could be improved in order to achieve the next grade.  

A unit evaluation questionnaire is used to gather feedback from the students on the course  

A global reference for human genetic variation. Nature. 2015 (526):68-74.

National Human Genome Research Institute (NHGRI), Education pages: http://www.genome.gov/10001772

The Human Genome Project Fact sheets: https://www.genome.gov/about-genomics/fact-sheets

Pharmacogenomics in the UK National Health Service: opportunities and challenges. Richard M Turner, William G Newman, Elvira Bramon, Christine J McNamee, Wai Lup Wong, Siraj Misbah, Sue Hill, Mark Caulfield & Munir Pirmohamed. Pharmacogenomics 2020. Nov;21(17):1237-1246.

Whole-genome sequencing of patients with rare diseases in a national health system. Turro E, et al. Nature. 2020 Jul;583(7814):96-102.

EBI GWAS catalogue: www.ebi.ac.uk/training-beta/online/courses/gwas-catalogue-exploring-snp-trait-associations/

UCSC genome browser training: https://genome.ucsc.edu/training/index.html

Integrative single-cell analysis. Stuart T, Satija R. Nat Rev Genet 20, 257–272 (2019).  

Can Bottom-Up Synthetic Biology Generate Advanced Drug-Delivery Systems? Lussier F, Staufer O, Platzman I, Spatz JP. Trends in Biotechnology. 2021:39(5):445-459.