Next generation sequencing (NGS) and the recent development of efficient algorithms for genomic analysis are contributing to the understanding of human genetic variation and thus to personalized medicine. Among those genomic analysis, disease-causal gene analysis that finds genes relevant to specific diseases has received much attention. In this paper, we present our work on extending the PostgreSQL open source relational database management system (RDBMS) to efficiently handle genomic analysis. We introduced a new genome data type and a genome type aggregation function that drastically improved the performance of a typical query for disease-causal gene analysis by a factor of 50 to 360.