Identification of previously unidentified genetic variations and evaluation of their functional effects
Approved Research ID: 84306
Approval date: June 22nd 2022
It is known that human genetic variations affect the risk of diseases and traits. Identifying them would provide us with valuable information on the cause of disease and contribute to predicting disease risk of people. However, the current human genome studies have not identified all genetic predispositions related to human diseases and traits. This would be, in part, caused by problems in methods for identifying genetic variations. Genetics variations are detected by analyzing sequencing data with computer programs, and therefore the analysis results depend on the programs. Although programs to identify simple genetic variations have been already established, these for complex variations are still too far from perfect.
Another essential problem is the interpretation of the functional effects of genetic variations. There are many genetic variations in the human population. Previous studies suggest that a diploid human genome has 3-4 million genetic variations. The majority of them would not have biological effects on human health, but some of them affect the risk of diseases and traits. Therefore, identifying functional variations from many genetic variations is a critical issue in genomic medicine.
This proposal aims to apply our methods to UK Biobank for identifying previously unidentified genetic variations and contributing to human genetics studies. We have developed several methods for detecting genetic variations and inferring the impact of genetic variations. We will use these methods in this study. We will also infer the importance of genetic variations considering protein structure. Additionally, we will develop methods to detect complex genetic variations. We will apply these methods to UK Biobank data and analyze variation in the population and association with traits. This study should make a complete catalog of human genetic variations and contribute to future genomic medicine.