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Detection of copy-number variations from NGS data using read depth information: a diagnostic performance evaluation.

ABSTRACT: The detection of copy-number variations (CNVs) from NGS data is underexploited as chip-based or targeted techniques are still commonly used. We assessed the performances of a workflow centered on CANOES, a bioinformatics tool based on read depth information. We applied our workflow to gene panel (GP) and whole-exome sequencing (WES) data, and compared CNV calls to quantitative multiplex PCR of short fluorescent fragments (QMSPF) or array comparative genomic hybridization (aCGH) results. From GP data of 3776 samples, we reached an overall positive predictive value (PPV) of 87.8%. This dataset included a complete comprehensive QMPSF comparison of four genes (60 exons) on which we obtained 100% sensitivity and specificity. From WES data, we first compared 137 samples with aCGH and filtered comparable events (exonic CNVs encompassing enough aCGH probes) and obtained an 87.25% sensitivity. The overall PPV was 86.4% following the targeted confirmation of candidate CNVs from 1056 additional WES. In addition, our CANOES-centered workflow on WES data allowed the detection of CNVs with a resolution of single exons, allowing the detection of CNVs that were missed by aCGH. Overall, switching to an NGS-only approach should be cost-effective as it allows a reduction in overall costs together with likely stable diagnostic yields. Our bioinformatics pipeline is available at: https://gitlab.bioinfo-diag.fr/nc4gpm/canoes-centered-workflow .

SUBMITTER: Quenez O

PROVIDER: S-EPMC7852510 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundFetal echogenic bowel (FEB) is associated with an increased risk of poor pregnant outcomes; however, karyotyping fails to detect copy number variations (CNVs) in FEB. This study aimed to evaluate the performance of chromosomal microarray analysis (CMA) for detection of FEB.MethodsThe medical records of 147 pregnant women with FEB recruited during December 2015 to December 2018 were retrospectively reviewed, and prenatal samples were collected for karyotyping and CMA. The detection of chromosomal abnormality was compared between karyotyping and CMA.ResultsKaryotyping identified eight cases with abnormal karyotypes (5.44% prevalence), including four fetuses with pathogenic aneuploidy, three with chromosome polymorphism and one with balanced chromosome translocation. CMA identified 13 abnormal CNVs (8.84% prevalence), including 4 fetuses with pathogenic aneuploidy as detected by karyotyping and 9 additional CNVs with normal karyotypes; however, CMA failed to detect chromosome polymorphism and balanced chromosome translocation. In fetuses with isolated FEB, no cases presented pathogenic findings and CMA detected two cases with variants of uncertain significance (VOUS). In cases presenting FEB along with other ultrasound abnormalities, CMA detected three cases with pathogenic CNVs and four cases with VOUS in addition to four cases with aneuploidy. There was no significant difference in the detection of abnormal CNVs between the fetuses with echogenic bowel alone and along with other ultrasound abnormalities (10% vs 8.67%, P > 0.05). Except 9 fetuses lost to the follow-up, the other 138 fetuses with echogenic bowel were successfully followed up. Pregnancy was terminated in 5 fetuses with chromosomal abnormality, 2 with pathogenic CNVs and 1 with VOUS, and other 16 with normal karyotypes and CMA findings but showing ultrasound abnormalities or multiple malformations.ConclusionIsolated FEB is associated with a good prognosis, and a satisfactory pregnant outcome is expected for fetuses with echogenic bowel that are negative for chromosomal anomalies and other severe structure abnormalities. CMA shows an important value in the genetic diagnosis of FEB. As a supplement to karyotyping, CMA may improve the accuracy of prenatal diagnosis of fetal intestinal malformations in pregnant women with FEB.

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Detection of copy-number variations from NGS data using read depth information: a diagnostic performance evaluation.

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