Study of genetic variations and their target genes in cancers and chronic diseases through the lens of 3D genome organization.
We aim to (1) develop new computation methods to investigate the connections between disease-specific DNA-DNA interactions and disease-specific genetic information; (2) investigate their critical biological functions in various cancers and chronic diseases; (3) develop new predictive models to predict novel target genes of genetic variations.
New biotechnologies, such as Hi-C, could map interactions between DNA fragments in the genome. Large-scale biobanks such as UK Biobank discover genetic variation associated with various cancer and chronic diseases. However, many of the associated variations do not reside in human genes, challenging the interpretation of their functions and causality with diseases. DNA-DNA interactions revealed by Hi-C biotechnology provides a new lens to resolve this problem. We will develop advanced statistical and machine learning algorithms for interpreting the biological functions and gene-gene interaction for variants relevant to diseases in the UK Biobank, using the DNA-DNA interaction data we collected and the genetic and health information provided by UK Biobank.
We intended to finish the project in a 36-month period.
Public health impact
Cancers and chronic diseases are major threats to human health. The difficulty to discover the underlying genetic variations that cause these diseases hinders the prevention and treatment improvement. The computational methods developed in this project and their discoveries would further improve our understanding of the causal relations between human DNA and complex diseases, which could improve the prevention, diagnosis, and treatment of cancers and chronic diseases.