Reanalysing genomic data by normalized coverage values uncovers CNVs in bone marrow failure gene panels

通过标准化覆盖率值重新分析基因组数据,揭示了骨髓衰竭基因组中的拷贝数变异(CNV)。

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Abstract

Inherited bone marrow failure syndromes (IBMFSs) are genetically heterogeneous disorders with cytopenia. Many IBMFSs also feature physical malformations and an increased risk of cancer. Point mutations can be identified in about half of patients. Copy number variation (CNVs) have been reported; however, the frequency and spectrum of CNVs are unknown. Unfortunately, current genome-wide methods have major limitations since they may miss small CNVs or may have low sensitivity due to low read depths. Herein, we aimed to determine whether reanalysis of NGS panel data by normalized coverage value could identify CNVs and characterize them. To address this aim, DNA from IBMFS patients was analyzed by a NGS panel assay of known IBMFS genes. After analysis for point mutations, heterozygous and homozygous CNVs were searched by normalized read coverage ratios and specific thresholds. Of the 258 tested patients, 91 were found to have pathogenic point variants. NGS sample data from 165 patients without pathogenic point mutations were re-analyzed for CNVs; 10 patients were found to have deletions. Diamond Blackfan anemia genes most commonly exhibited heterozygous deletions, and included RPS19, RPL11, and RPL5. A diagnosis of GATA2-related disorder was made in a patient with myelodysplastic syndrome who was found to have a heterozygous GATA2 deletion. Importantly, homozygous FANCA deletion were detected in a patient who could not be previously assigned a specific syndromic diagnosis. Lastly, we identified compound heterozygousity for deletions and pathogenic point variants in RBM8A and PARN genes. All deletions were validated by orthogonal methods. We conclude that careful analysis of normalized coverage values can detect CNVs in NGS panels and should be considered as a standard practice prior to do further investigations.

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