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Massively parallel sequencing of micro-manipulated cells targeting a comprehensive panel of disease-causing genes: A comparative evaluation of upstream whole-genome amplification methods
Single Gene Disorders (SGD) are still routinely diagnosed using PCR-based assays that need to be developed and validated for each individual disease-specific gene fragment. The TruSight One sequencing panel currently covers 12 Mb of genomic content, including 4813 genes associated with a clinical ph...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5919401/ https://www.ncbi.nlm.nih.gov/pubmed/29698522 http://dx.doi.org/10.1371/journal.pone.0196334 |
Sumario: | Single Gene Disorders (SGD) are still routinely diagnosed using PCR-based assays that need to be developed and validated for each individual disease-specific gene fragment. The TruSight One sequencing panel currently covers 12 Mb of genomic content, including 4813 genes associated with a clinical phenotype. When only a limited number of cells are available, whole genome amplification (WGA) is required prior to DNA target capture techniques such as the TruSight One panel. In this study, we compared 4 different WGA methods in combination with the TruSight One sequencing panel to perform single nucleotide polymorphism (SNP) genotyping starting from 3 micro-manipulated cells. This setting simulates clinical settings such as day-5 blastocyst biopsy for Preimplantation Genetic Testing (PGT), liquid biopsy of circulating tumor cells (CTCs) and cancer-cell profiling. Bulk cell samples were processed alongside these WGA samples to serve as a performance reference. Target coverage, coverage uniformity and SNP calling accuracy obtained using any of the WGA, is inferior to the results obtained on bulk cell samples. However, results after REPLI-g come close. Compared to the other WGA methods, the method using REPLI-g WGA results in a better coverage of the targeted genomic regions with a more uniform read depth. Consequently, this method also results in a more accurate SNP calling and could be considered for clinical genotyping of a limited number of cells. |
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