Mutations in ~100 genes cause muscle diseases with complex and often unexplained genotype/phenotype correlations. Next-generation sequencing studies identify a greater-than-expected number of genetic variations in the human genome. This suggests that existing clinical monogenic testing systematically miss very relevant information.We have created a core panel of genes that cause all known forms of nonsyndromic muscle disorders (MotorPlex). It comprises 93 loci, among which are the largest and most complex human genes, such as TTN, RYR1, NEB and DMD. MotorPlex captures at least 99.2% of 2,544 exons with a very accurate and uniform coverage. This quality is highlighted by the discovery of 20-30% more variations in comparison with whole exome sequencing. The coverage homogeneity has also made feasible to apply a cost-effective pooled sequencing strategy while maintaining optimal sensitivity and specificity.We studied 177 unresolved cases of myopathies for which the best candidate genes were previously excluded. We have identified known pathogenic variants in 52 patients and potential causative ones in further 56 patients. We have also discovered 23 patients showing multiple true disease-associated variants suggesting complex inheritance. Moreover, we frequently detected other nonsynonymous variants of unknown significance in the largest muscle genes. Cost-effective combinatorial pools of DNA samples were similarly accurate (97-99%). MotorPlex is a very robust platform that overcomes for power, costs, speed, sensitivity and specificity the gene-by-gene strategy. The applicability of pooling makes this tool affordable for the screening of genetic variability of muscle genes also in a larger population. We consider that our strategy can have much broader applications.

MotorPlex provides accurate variant detection across large muscle genes both in single myopathic patients and in pools of DNA samples / M. Savarese, G. Di Fruscio, M. Mutarelli, A. Torella, F. Magri, F.M. Santorelli, G.P. Comi, C. Bruno, V. Nigro. - In: ACTA NEUROPATHOLOGICA COMMUNICATIONS. - ISSN 2051-5960. - 2(2014), pp. 100.1-100.13. [10.1186/s40478-014-0100-3]

MotorPlex provides accurate variant detection across large muscle genes both in single myopathic patients and in pools of DNA samples

F. Magri;G.P. Comi;
2014

Abstract

Mutations in ~100 genes cause muscle diseases with complex and often unexplained genotype/phenotype correlations. Next-generation sequencing studies identify a greater-than-expected number of genetic variations in the human genome. This suggests that existing clinical monogenic testing systematically miss very relevant information.We have created a core panel of genes that cause all known forms of nonsyndromic muscle disorders (MotorPlex). It comprises 93 loci, among which are the largest and most complex human genes, such as TTN, RYR1, NEB and DMD. MotorPlex captures at least 99.2% of 2,544 exons with a very accurate and uniform coverage. This quality is highlighted by the discovery of 20-30% more variations in comparison with whole exome sequencing. The coverage homogeneity has also made feasible to apply a cost-effective pooled sequencing strategy while maintaining optimal sensitivity and specificity.We studied 177 unresolved cases of myopathies for which the best candidate genes were previously excluded. We have identified known pathogenic variants in 52 patients and potential causative ones in further 56 patients. We have also discovered 23 patients showing multiple true disease-associated variants suggesting complex inheritance. Moreover, we frequently detected other nonsynonymous variants of unknown significance in the largest muscle genes. Cost-effective combinatorial pools of DNA samples were similarly accurate (97-99%). MotorPlex is a very robust platform that overcomes for power, costs, speed, sensitivity and specificity the gene-by-gene strategy. The applicability of pooling makes this tool affordable for the screening of genetic variability of muscle genes also in a larger population. We consider that our strategy can have much broader applications.
Settore MED/26 - Neurologia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/254057
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