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. 2012 Oct;58(10):1467-75.
doi: 10.1373/clinchem.2012.189589. Epub 2012 Aug 15.

Noninvasive prenatal diagnosis of monogenic diseases by targeted massively parallel sequencing of maternal plasma: application to β-thalassemia

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Noninvasive prenatal diagnosis of monogenic diseases by targeted massively parallel sequencing of maternal plasma: application to β-thalassemia

Kwan-Wood G Lam et al. Clin Chem. 2012 Oct.

Abstract

Background: A genomewide genetic and mutational profile of a fetus was recently determined via deep sequencing of maternal plasma DNA. This technology could have important applications for noninvasive prenatal diagnosis (NIPD) of many monogenic diseases. Relative haplotype dosage (RHDO) analysis, a core step of this procedure, would allow one to elucidate the maternally inherited half of the fetal genome. For clinical applications, the cost and complexity of data analysis might be reduced via targeted application of this approach to selected genomic regions containing disease-causing genes. There is thus a need to explore the feasibility of performing RHDO analysis in a targeted manner.

Methods: We performed target enrichment by using solution-phase hybridization followed by massively parallel sequencing of the β-globin gene region in 2 families undergoing prenatal diagnosis for β-thalassemia. We used digital PCR strategies to physically deduce parental haplotypes. Finally, we performed RHDO analysis with target-enriched sequencing data and parental haplotypes to reveal the β-thalassemic status for the fetuses.

Results: A mean sequencing depth of 206-fold was achieved in the β-globin gene region by targeted sequencing of maternal plasma DNA. RHDO analysis was successful for the sequencing data obtained from the target-enriched samples, including a region in one of the families in which the parents had similar haplotype structures. Data analysis revealed that both fetuses were heterozygous carriers of β-thalassemia.

Conclusions: Targeted sequencing of maternal plasma DNA for NIPD of monogenic diseases is feasible.

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