Description:

"One of the primary research efforts of the genomic era has been mapping the genes that contribute to common, complex diseases. While thousands of genetic variants have been discovered over the last decade that are significantly associated with many different diseases, collectively they account for only a small fraction of the population burden of any disease, and thus most of the heritable risk for common, complex diseases remains unexplained. Much of this “missing heritability” may be due to rarer variants that occur too infrequently to be measured using traditional genome-wide association study methods. Recent improvements and cost-reductions in DNA sequencing technologies and services have now made it feasible to pursue genome-wide studies of rare variants, but the corresponding statistical analysis tools remain fragmented and underdeveloped, and most have been validated using simulated datasets. Our objective is to produce an integrated, genome-wide bioinformatics pipeline using real data that is able to identify rare variants that contribute to the heritability of complex diseases. Using whole-genome sequencing (WGS) data that we’ve generated from 76-two generation families affected by polycystic ovary syndrome (PCOS), a common, complex genetic disease affecting approximately 6-10% of premenopausal women worldwide, we are developing methods to test the hypothesis that rare genetic variants contribute to the pathogenesis of PCOS. By applying a multidimensional approach to analyzing real WGS data from a family-based cohort, we can determine if and how rare variants influence PCOS pathogenesis and produce novel methods for studying the genetics of complex diseases in general."