Identification of a RAI1-associated disease network through integration of exome sequencing, transcriptomics, and 3D genomics. Issue 1 (December 2016) - Loviglio, Maria
Abstract Background Smith-Magenis syndrome (SMS) is a developmental disability/multiple congenital anomaly disorder resulting from haploinsufficiency ofRAI1. It is characterized by distinctive facial features, brachydactyly, sleep disturbances, and stereotypic behaviors. Methods We investigated a cohort of 15 individuals with a clinical suspicion of SMS who showed neither deletion in the SMS critical region nor damaging variants inRAI1 using whole exome sequencing. A combination of network analysis (co-expression and biomedical text mining), transcriptomics, and circularized chromatin conformation capture (4C-seq) was applied to verify whether modified genes are part of the same disease network as known SMS-causing genes. Results Potentially deleterious variants were identified in nine of these individuals using whole-exome sequencing. Eight of these changes affectKMT2D, ZEB2, MAP2K2, GLDC, CASK, MECP2, KDM5C, andPOGZ, known to be associated with Kabuki syndrome 1, Mowat-Wilson syndrome, cardiofaciocutaneous syndrome, glycine encephalopathy, mental retardation and microcephaly with pontine and cerebellar hypoplasia, X-linked mental retardation 13, X-linked mental retardation Claes-Jensen type, and White-Sutton syndrome, respectively. The ninth individual carries a de novo variant inJAKMIP1, a regulator of neuronal translation that was recently found deleted in a patient with autism spectrum disorder. Analyses of co-expression and biomedical text mining suggest that these pathologies and SMS are part of the same disease network. Further support for this hypothesis was obtained from transcriptome profiling that showed that the expression levels of bothZeb2 andMap2k2 are perturbed inRai1 –/– mice. As an orthogonal approach to potentially contributory disease gene variants, we used chromatin conformation capture to reveal chromatin contacts betweenRAI1 and the loci flankingZEB2 andGLDC, as well as betweenRAI1 and human orthologs of the genes that show perturbed expression in ourRai1 –/– mouse model. Conclusions These holistic studies ofRAI1 and its interactions allow insights into SMS and other disorders associated with intellectual disability and behavioral abnormalities. Our findings support a pan-genomic approach to the molecular diagnosis of a distinctive disorder.