Low coverage Whole Genome Sequencing (LC-WGS) Validation for Pharmacogenetics and Risk Prediction Assessment
Recent technological advances have made it possible to sequence the entire genome of an individual and obtain a comprehensive description of mutations in genes associated with cancer, neurodegenerative disease, and drug response. Most of these technologies leverage what is known as high-coverage whole-genome sequencing, referring to the amount of information obtained from the experiments. However, such high-coverage tests are typically associated with elevated costs.
We have developed a method using whole-genome sequencing at a lower coverage and still retain the ability to characterize mutations in an entire genome. This is possible because of the volume of genetic data available to the community and provided by resources such as the UK Biobank. By combining genetic data from multiple participants, we can infer which sets of mutations are inherited together, and thus fill in any gaps that may arise from lower-depth sequencing experiments. This is a well-established method that is known as imputation.
Our 36-months study aims to verify and validate our low coverage sequencing pipeline using UK Biobank data to detect mutations linked to a higher or lower risk of developing cancer, neurodegenerative disorders, and coronary disease. Additionally, we aim to show that our pipeline can detect mutations in well-known pharmacogenomics targets.
As there are not many pipelines available to reliably detect mutation from low coverage sequencing data, we expect that this project will deliver results in a cost-efficient manner without compromising performance. In turn, this will enable access to tailored screening programs, whereby patients are stratified based on their genetic risk profile for various conditions. We expect the adoption of our pipeline will potentially facilitate access to lower-cost genetic testing in emerging markets such as Southeast Asia.