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the phenotype. Moreover, this validation demonstrated that this approach can detect
different mutation types in a wide range of heterogeneous diseases.
All the known and novel mutations were identifi ed in previously characterized
patients and in patients lacking molecular diagnosis (Vasli et al. 2012 ). Specifi cally,
all mutation types, in the eight positive controls, were identifi ed. The large deletion
encompassing exons 18-44 of the DMD gene was detected in a patient with
Duchenne muscular dystrophy by comparing the number of reads in these regions
with other sequenced DNA samples. The mean coverage for exons 18-44 is 0X for
this patient and 177X for other patients. Two mutations in SETX were found in two
patients with ataxia. Similarly, samples from patients with heterogeneous NMD
without molecular characterization were sequenced. Potential disease-causing
mutations, supported by Sanger confi rmation and segregation, were identifi ed in
several patients, namely, RYR1 , TTN , and COL6A3 (Vasli et al. 2012 ). These genes
were also consistent with the clinical information. For example, compound hetero-
zygous mutations were in the ryanodine receptor ( RYR1 ) of a patient with muscular
dystrophy and arthrogryposis. Additionally, the mutations were present in his
affected twin brother and each parent was a carrier of each mutation.
NGS is suitable for analysis of diseases with high degree genetic heterogeneity
with many potential candidate causative genes and allelic diseases caused by muta-
tions of the same gene (Vasli et al. 2012 ). The latter application allows the sequenc-
ing of large genes such as DMD and TTN which are not routinely sequenced by the
Sanger method. This type of analysis allowed the clinical spectrum of TTN -related
diseases to be widened by noting a patient with myopathy with cytoplasmic aggre-
gates and respiratory insuffi ciency widens the clinical spectrum compared to previ-
ous studies (Hackman et al. 2002 ).
A disadvantage of panel-based NGS approaches is that not all genes or gene
regions associated with NMD are included either because of a target size limitation
or a specifi c gene has yet to be associated with NMD. Vasli et al. failed to fi nd the
genetic cause for four patients with an unknown molecular diagnosis (Vasli et al.
2012 ). Patient I was fi rst clinically diagnosed with demyelinating polyneuropathy,
but clinical and biochemical reanalyses in parallel to NGS suggested he had a mito-
chondrial disease which implicated genes are not covered by this present design.
Patient N showed two in cis missense changes in LMNA including the p.R644C
change, previously linked to various laminopathies, and cannot explain the pheno-
type. Mutations were not identifi ed in two patients by this NGS panel. Authors
speculated that mutations may be deep intronic changes, repeat expansions, or
translocation for which detection has not been tested in this study. Alternatively,
patients may also be mutated in a gene not linked to NMD at the time of the target-
ing library design.
Whole exome sequencing or whole genome sequencing could potentially fi nd
the causative mutations and/or gene in patients without a molecular diagnosis and
these must be added to the NMD capture library design. However, this WGS or
WES has several disadvantages for routine molecular diagnosis compared to tar-
geted panels. NMD-seq has a higher coverage and leads to a smaller list of variants
as it focuses on a subset of genes, whereas the sensitivity and heterozygosity
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