Developmental disorders and malformations encompass over 7,000 rare congenital diseases, affecting around 30 million people in the European Union. Approximately 80% of these conditions are genetic, most of them diagnosed in childhood and often leading to lifelong disabilities. Massive parallel sequencing (MPS) has revolutionized genetic diagnostics. Exome sequencing (ES), targeting protein-coding genes (2% of the genome), achieves a diagnostic yield of ~30%, while whole-genome sequencing (WGS) increases this to 30–50% by detecting structural and intronic variants. Despite these advances, 50–70% of genetic diagnoses remain unsolved. Our recent studies, including the discovery of the first neomorphic mutation in microRNA140 causing human skeletal dysplasia, indicate that mutations in non-coding regions can lead to human disease. However, bioinformatic interpretation of variants in non-coding regions remains a major challenge, requiring precise correlation between phenotype and molecular mechanisms. Recently, we identified two novel candidate variants in rare pediatric skeletal syndromes. The first variant, found in two unrelated families with X-linked calvarial hyperostosis, is a single-nucleotide substitution in a highly conserved promoter region. The second is an approximately 2 kb intergenic deletion at 11p15.5 that segregates with extreme tall stature in seven affected individuals from a three-generation pedigree. This deletion overlaps an enhancer of H19, which may play a critical role in skeletal growth regulation. In this project, we will investigate the functional consequences of these two variants through bulk RNA sequencing, spatial transcriptomics, and complementary molecular assays. These computational analyses will be used to characterize transcriptional dysregulation and tissue-specific expression patterns associated with the variants. The overall aim of this project is to elucidate the genetic causes and molecular mechanisms underlying unsolved pediatric skeletal disorders by integrating whole-genome variant discovery with transcriptomic and spatial profiling. By leveraging high-performance computing resources, we aim to uncover new disease mechanisms and improve diagnostic yield for rare congenital skeletal diseases.