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Purpose: To develop criteria to interpret mitochondrial transfer RNA (mt-tRNA) variants based on unique characteristics of mitochondrial genetics and conserved structural/functional properties of tRNA., Methods: We developed rules on a set of established pathogenic/benign variants by examining heteroplasmy correlations with phenotype, tissue distribution, family members, and among unrelated families from published literature. We validated these deduced rules using our new cases and applied them to classify novel variants., Results: Evaluation of previously reported pathogenic variants found that 80.6% had sufficient evidence to support phenotypic correlation with heteroplasmy levels among and within families. The remaining variants were downgraded due to the lack of similar evidence. Application of the verified criteria resulted in rescoring 80.8% of reported variants of uncertain significance (VUS) to benign and likely benign. Among 97 novel variants, none met pathogenic criteria. A large proportion of novel variants (84.5%) remained as VUS, while only 10.3% were likely pathogenic. Detection of these novel variants in additional individuals would facilitate their classification., Conclusion: Proper interpretation of mt-tRNA variants is crucial for accurate clinical diagnosis and genetic counseling. Correlations with tissue distribution, heteroplasmy levels, predicted perturbations to tRNA structure, and phenotypes provide important evidence for determining the clinical significance of mt-tRNA variants.

Purpose: Next-generation sequencing (NGS) has been widely applied to clinical diagnosis. Target-gene capture followed by deep sequencing provides unbiased enrichment of the target sequences, which not only accurately detects single-nucleotide variations (SNVs) and small insertion/deletions (indels) but also provides the opportunity for the identification of exonic copy-number variants (CNVs) and large genomic rearrangements., Method: Capture NGS has the ability to easily detect SNVs and small indels. However, genomic changes involving exonic deletions/duplications and chromosomal rearrangements require more careful analysis of captured NGS data. Misaligned raw sequence reads may be more than just bad data. Some mutations that are difficult to detect are filtered by the preset analytical parameters. "Loose" filtering and alignment conditions were used for thorough analysis of the misaligned NGS reads. Additionally, using an in-house algorithm, NGS coverage depth was thoroughly analyzed to detect CNVs., Results: Using real examples, this report underscores the importance of the accessibility to raw sequence data and manual review of suspicious sequence regions to avoid false-negative results in the clinical application of NGS. Assessment of the NGS raw data generated by the use of loose filtering parameters identified several sequence aberrations, including large indels and genomic rearrangements. Furthermore, NGS coverage depth analysis identified homozygous and heterozygous deletions involving single or multiple exons., Conclusion: Our results demonstrate the power of deep NGS in the simultaneous detection of point mutations and intragenic exonic deletion in one comprehensive step.Genet Med 18 5, 513-521.

Purpose: We aimed to demonstrate the detection of exonic deletions using target capture and deep sequencing data., Methods: Sequence data from target gene capture followed by massively parallel sequencing were analyzed for the detection of exonic deletions using the normalized mean coverage of individual exons. We compared the results with those obtained from high-density exon-targeted array comparative genomic hybridization and applied similar analysis to examine samples from patients with pathogenic exonic deletions., Results: Thirty-eight samples, each containing 2,134, 2,833, or 4,688 coding exons from different panels, with a total of 103,863 exons, were analyzed by capture-massively parallel sequencing and array comparative genomic hybridization. Ten deletions detected by array comparative genomic hybridization were all detected by massively parallel sequencing, whereas only two of three duplications were detected. We were able to detect all pathogenic exonic deletions in 11 positive cases. Thirty-one exonic copy number changes from nine perspective clinical samples were also identified., Conclusion: Our results demonstrated the feasibility of using the same set of sequence data to detect both point mutations and exonic deletions, thus improving the diagnostic power of massively parallel sequencing-based assays.

Purpose: Glycogen storage diseases are a group of inborn errors of glycogen synthesis or catabolism. The outcome for untreated patients can be devastating. Given the genetic heterogeneity and the limited availability of enzyme study data, the definitive diagnosis of glycogen storage diseases is made on the basis of sequence analysis of selected potentially causative genes., Methods: A massively parallel sequencing test was developed for simultaneous sequencing of 16 genes known to cause muscle and liver forms of glycogen storage diseases: GYS2, GYS1, G6PC, SLC37A4, GAA, AGL, GBE1, PYGM, PYGL, PFKM, PHKA2, PHKB, PHKG2, PHKA1, PGAM2, and PGM1. All the nucleotides in the coding regions of these 16 genes have been enriched with sufficient coverage in an unbiased manner., Results: Massively parallel sequencing demonstrated 100% sensitivity and specificity as compared with Sanger sequencing. Massively parallel sequencing correctly identified all types of mutations, including single-nucleotide substitutions, small deletions and duplications, and large deletions involving one or more exons. In addition, we have confirmed the molecular diagnosis in 11 of 17 patients in whom glycogen storage diseases were suspected., Conclusion: This report demonstrates the clinical utility of massively parallel sequencing technology in the diagnostic testing of a group of clinically and genetically heterogeneous disorders such as glycogen storage diseases, in a cost- and time-efficient manner.

Purpose: The mitochondrial genome is highly polymorphic. A unique feature of deleterious mitochondrial DNA (mtDNA) mutations is heteroplasmy. Genetic background and variable penetrance also play roles in the pathogenicity for a mtDNA variant. Clinicians are increasingly interested in requesting mtDNA testing. However, interpretation of uncharacterized mtDNA variants is a great challenge. We suggest a stepwise interpretation procedure for clinical service., Methods: We describe the algorithms used to interpret novel and rare mtDNA variants. mtDNA databases and in silico predictive algorithms are used to evaluate the pathogenic potential of novel and/or rare mtDNA variants., Results: mtDNA variants can be classified into three categories: benign variants, unclassified variants, and deleterious mutations based on database search and in silico prediction. Targeted DNA sequence analysis of matrilineal relatives, heteroplasmy quantification, and functional studies are useful to classify mtDNA variants., Conclusion: Clinical significance of a novel or rare variant is critical in the diagnosis of the disease and counseling of the family. Based on the results from clinical, biochemical, and molecular genetic studies of multiple family members, proper interpretation of mtDNA variants is important for clinical laboratories and for patient care.