Mutation load characterization in major genesresponsible for congenital myopathy and identificationof hotspot regions useful for clinical approaches

Congenital myopathies are rare genetic-based muscle diseases that occur due to anomalies in the proteins involved in the structure and function of muscle fibers. The disease shows itself in the form of muscle weakness and hypotonia at birth or in the postnatal period. Positive results might be observed with musculoskeletal system movements and physiotherapeutic approaches to attenuate the progression of the muscle disorders. However, early diagnosis is important place in controlling the progression of the disease and choosing the appropriate treatment process for the patient. Although molecular mechanisms that lie behind the disease, approximately 2/3 of patients with congenital myopathy can be diagnosed with genetic testing. It is known that there are 13 major genes (ACTA1, NEB, MTM1, MYH7, DNM2, RYR1, TPM2, TPM3, TNNT1, CFL2, SEPN1, BIN1, TTN) responsible for the disease. Although many mutations have been identified in these genes that cause congenital myopathies in previous studies, there are not enough studies on which regions of the genes these mutations are concentrated in and which regions of the protein these regions affect. In this study, all DNA mutations belonging to the 13 genes which are considered causes of congenital myopathies obtained from literature and databases were evaluated on the bases of potential clinical usage in the diagnosis and typing of congenital myopathy patients. For this purpose, missense nonsense, synonym, frameshift, and intron mutations were studied to determine possible hotspot mutation positions, target exons, and intron regions that are causing congenital myopathies. A total of 68695 mutations that are correlated with congenital myopaties from 4 mutation types in 13 genes were obtained from the literature and databases. After mutation filtering and nesting of exon-intron location in genes, mutation-dense hotspot locations and regions were determined using outlier, clustering and multivariate statistical analyses. The distribution of mutations throughout each gene showed heterogeneous and region-specific patterns. The mutations that are responsible for the disease were detected mostly in the regions of proteins' catalytic and allosteric control regions. The results revealed that each gene has potential target exons, intron regions and positions for microchip screening panels that can be used for clinical diagnosis.