Protein structural based analysis for interpretation of missense variants at the genomics era: Using MNGIE disease as an example

Abstract

The analysis of a group of genes or the whole exome by massively parallel sequencing provides an efficient way to molecular diagnosis of genetic disorders. Meanwhile, tremendous amount of variant data produced brings great challenges for interpretation, particularly for novel variants without functional evidences. There is an urgent need for a nonexperimentally based method to understand their genotype and phenotype correlation. Moreover, missense variants contribute to about 50 % disease-causing changes. This chapter will demonstrate the value of in silico stereochemical analysis in the interpretation of disease-causing missense mutations using thymidine phosphorylase as an example. The integrated approaches including disease clinical phenotype, biochemical genetic analysis, computational prediction, and structural based modeling can be helpful in understanding the pathogenic mechanism of these missense variants. The protein structural based analysis is a valuable tool to visualize small but signifi cant structural changes, thus, can be incorporated into routine variant interpretation pipeline.