Unraveling Rare Diseases: Bioinformatic Evaluation of Novel Sequencing Technologies

This dissertation evaluates how newer sequencing technologies can improve genetic diagnosis in rare disease, especially intellectual disability and other genetically heterogeneous disorders. It first compares modern exome capture strategies with short-read and long-read whole-genome sequencing, showing that Twist exome capture provides more uniform coding-region coverage and maintains reliable SNV and CNV detection even at lower depth. It then assesses PacBio HiFi long-read sequencing in unsolved trios, demonstrating improved access to repetitive and GC-rich regions, better structural-variant discovery, and recovery of clinically relevant variants missed by short reads. Finally, the thesis examines whether HiFi long reads are accurate enough for de novo SNV discovery and shows high concordance with short-read sequencing. Together, these studies support improved exome capture and long-read sequencing as valuable advances for more comprehensive and clinically useful rare-disease genomics.