ABSTRACT
BACKGROUND: Testing strategies is crucial for genetics clinics and testing laboratories. In this study, we tried to compare the hit rate between solo and trio and trio plus testing and between trio and sibship testing. Finally, we studied the impact of extended family analysis, mainly in complex and unsolved cases. METHODS: Three cohorts were used for this analysis: one cohort to assess the hit rate between solo, trio and trio plus testing, another cohort to examine the impact of the testing strategy of sibship genome vs trio-based analysis, and a third cohort to test the impact of an extended family analysis of up to eight family members to lower the number of candidate variants. RESULTS: The hit rates in solo, trio and trio plus testing were 39, 40, and 41%, respectively. The total number of candidate variants in the sibship testing strategy was 117 variants compared to 59 variants in the trio-based analysis. We noticed that the average number of coding candidate variants in trio-based analysis was 1192 variants and 26,454 noncoding variants, and this number was lowered by 50-75% after adding additional family members, with up to two coding and 66 noncoding homozygous variants only, in families with eight family members. CONCLUSION: There was no difference in the hit rate between solo and extended family members. Trio-based analysis was a better approach than sibship testing, even in a consanguineous population. Finally, each additional family member helped to narrow down the number of variants by 50-75%. Our findings could help clinicians, researchers and testing laboratories select the most cost-effective and appropriate sequencing approach for their patients. Furthermore, using extended family analysis is a very useful tool for complex cases with novel genes.
Subject(s)
Consanguinity , Exome , Family , Genetic Markers , Genetic Predisposition to Disease , Genetic Testing , Genetic Variation , Adult , Child , Female , Humans , Male , Retrospective Studies , Exome SequencingABSTRACT
A set of glutamylases and deglutamylases controls levels of tubulin polyglutamylation, a prominent post-translational modification of neuronal microtubules. Defective tubulin polyglutamylation was first linked to neurodegeneration in the Purkinje cell degeneration (pcd) mouse, which lacks deglutamylase CCP1, displays massive cerebellar atrophy, and accumulates abnormally glutamylated tubulin in degenerating neurons. We found biallelic rare and damaging variants in the gene encoding CCP1 in 13 individuals with infantile-onset neurodegeneration and confirmed the absence of functional CCP1 along with dysregulated tubulin polyglutamylation. The human disease mainly affected the cerebellum, spinal motor neurons, and peripheral nerves. We also demonstrate previously unrecognized peripheral nerve and spinal motor neuron degeneration in pcd mice, which thus recapitulated key features of the human disease. Our findings link human neurodegeneration to tubulin polyglutamylation, entailing this post-translational modification as a potential target for drug development for neurodegenerative disorders.
Subject(s)
Carboxypeptidases/deficiency , Cerebellum/enzymology , Motor Neurons/enzymology , Peripheral Nerves/enzymology , Purkinje Cells/enzymology , Spine/enzymology , Spinocerebellar Degenerations/enzymology , Cerebellum/pathology , Female , GTP-Binding Proteins , Humans , Male , Motor Neurons/pathology , Peptides/genetics , Peptides/metabolism , Peripheral Nerves/pathology , Protein Processing, Post-Translational , Purkinje Cells/pathology , Serine-Type D-Ala-D-Ala Carboxypeptidase , Spine/pathology , Spinocerebellar Degenerations/genetics , Spinocerebellar Degenerations/pathologyABSTRACT
PURPOSE: Whole-exome sequencing (WES) and whole-genome sequencing (WGS) are used to diagnose genetic and inherited disorders. However, few studies comparing the detection rates of WES and WGS in clinical settings have been performed. METHODS: Variant call format files were generated and raw data analysis was performed in cases in which the final molecular results showed discrepancies. We classified the possible explanations for the discrepancies into three categories: the time interval between the two tests, the technical limitations of WES, and the impact of the sequencing system type. RESULTS: This cohort comprised 108 patients with negative array comparative genomic hybridization and negative or inconclusive WES results before WGS was performed. Ten (9%) patients had positive WGS results. However, after reanalysis the WGS hit rate decreased to 7% (7 cases). In four cases the variants were identified by WES but missed for different reasons. Only 3 cases (3%) were positive by WGS but completely unidentified by WES. CONCLUSION: In this study, we showed that 30% of the positive cases identified by WGS could be identified by reanalyzing the WES raw data, and WGS achieved an only 7% higher detection rate. Therefore, until the cost of WGS approximates that of WES, reanalyzing WES raw data is recommended before performing WGS.
