Recent whole exome and genome sequencing studies, including our own, have revealed that both healthy individuals and those affected by genetic diseases carry many rare DNA sequence variants. They classify them correctly as either bona fide causal mutations for genetic diseases, or merely benign polymorphisms. New approaches are clearly needed to filter through candidate sequence variants identified in whole exome/genome studies to identify causal mutations and evaluate their epistatic interactions in human genetic diseases, particularly complex traits. Building upon the experience of the PIs, we propose an innovative hybrid computational-experimental systems.The high-throughput 3DIP strategy can classify coding genetic variants as causative mutations or benign polymorphisms and evaluate epistatic interactions that can be broadly applied to human genetic diseases, including complex traits. Our overall goal is to develop a high-throughput approach that can accurately validate coding genetic variants as causal mutations or merely benign polymorphisms to improve exome study success rates. Our long-term goal is to apply this approach to improve the medical outcomes of patients and their family members who carry variants of uncertain significance in genetic disease risk genes.
Recent advances in DNA sequencing have globally transformed our understanding of human genetic diseases by revealing the ubiquity of rare DNA sequence variants: All our genomes are riddled with rare loss-of-function and gain-of-function gene variants. The almost overwhelming number of 'background' rare variants has become the rate limiting step to identify causative mutations underlying important genetic diseases. This project proposes a new approach to help distinguish causative mutations from merely benign polymorphisms. DESCRIPTION (provided by applicant): Recent whole exome and genome sequencing studies, including our own, have revealed that both healthy individuals and those affected by genetic diseases carry many rare DNA sequence variants. They classify them correctly as either bona fide causal mutations for genetic diseases, or merely benign polymorphisms. New approaches are clearly needed to filter through candidate sequence variants identified in whole exome/genome studies to identify causal mutations and evaluate their epistatic interactions in human genetic diseases, particularly complex traits. Building upon the experience of the PIs, we propose an innovative hybrid computational-experimental systems.The high-throughput 3DIP strategy can classify coding genetic variants as causative mutations or benign polymorphisms and evaluate epistatic interactions that can be broadly applied to human genetic diseases, including complex traits. Our overall goal is to develop a high-throughput approach that can accurately validate coding genetic variants as causal mutations or merely benign polymorphisms to improve exome study success rates. Our long-term goal is to apply this approach to improve the medical outcomes of patients and their family members who carry variants of uncertain significance in genetic disease risk genes.
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