This module explores the state of the art genomics techniques used for DNA sequencing (targeted approaches, whole exome and whole genome sequencing) and RNA sequencing, using highly parallel techniques, together with current technologies routinely used to investigate genomic variation in the clinical setting. This module will introduce the bioinformatics approaches required for the analysis of genomic data, which together with data governance covered in GM1 will provide a solid foundation for the Bioinformatics and Statistics modules. The module will also cover the use of array based methodologies and RNA sequencing in estimating levels of protein expression, micro RNAs and long non–coding RNAs. A comprehensive introduction to metabolomics and proteomics, which are important for the functional interpretation of genomic data and discovery of disease biomarkers will also be included. Students will also learn about the strategies employed to evaluate pathogenicity of variants for clinical reporting.

In GM2 you will learn about:

• Basis of genotyping and detection of genetic variation

• Whole exome and whole genome sequencing, including library preparation methods, sequencing chemistries and platforms

• Hands-on practical experience of an ‘omics’ workflow from sample to analysed data (virtual for ACY 2020-21)

• Brief overview of methodologies for detecting base substitutions (SNV), small insertions and deletions (indels), copy number variants (CNV) or rearrangements, to include Sanger sequencing, pyrosequencing, ARMS, MLPA, qFPCR, microarray

• Genomic testing strategies as: gene focused, multiple genes, or whole genome or exome, and for detection of sequence, copy number or rearrangements

•  RNA expression profiling (expression array) and RNA sequencing

• Metabolomics and proteomics techniques

• Overview of bioinformatics approaches to the analysis of genomic data using Galaxy

By the end of this module students will be able to:

• Describe and critically evaluate a range of up-to-date genomic technologies and platforms used to sequence targeted parts of the genome or whole genomes

• Discuss the application of other techniques (for example array comparative genome hybridisation, qPCR) commonly used to interrogate genomic variation in the clinical setting using examples in cancer and rare inherited diseases and infectious diseases

• Acquire the knowledge of selecting appropriate technology platforms for applications in medical genomics either for research or medical diagnostic purposes

• Critique how these techniques and their applications in RNA expression can be applied to metabolomics and proteomic analysis

• Discuss and critically appraise approaches to the bioinformatics analysis and interpretation of ‘omics’ data

• Critically evaluate the different ‘omics’ technologies and platforms and their application to genomic medicine and the impact of personalised medicine