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Evaluation of a Custom Design Gene Panel as a Diagnostic Tool for Human Non-Syndromic Infertility

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Infertility is a global healthcare problem, which affects men and women equally. With the advance of genome-wide analysis, an increasing list of human genes involved in infertility is now available. In order to evaluate the diagnostic interest to analyze these genes, we have designed a gene panel allowing the analysis of 51 genes involved in non-syndromic human infertility. In this initial evaluation study, a cohort of 94 non-syndromic infertility cases with a well-defined infertility phenotype was examined. Five patients with previously known mutations were used as positive controls. With a mean coverage of 457×, and 99.8% of target bases successfully sequenced with a depth coverage over 30×, we prove the robustness and the quality of our panel. In total, we identified pathogenic or likely pathogenic variations in eight patients (five male and three female). With a diagnostic yield of 8.5% and the identification of a variety of variants including substitution, insertion, deletion, and copy number variations, our results demonstrate the usefulness of such a strategy, as well as the efficiency and the quality of this diagnostic gene panel.
Title: Evaluation of a Custom Design Gene Panel as a Diagnostic Tool for Human Non-Syndromic Infertility
Description:
Infertility is a global healthcare problem, which affects men and women equally.
With the advance of genome-wide analysis, an increasing list of human genes involved in infertility is now available.
In order to evaluate the diagnostic interest to analyze these genes, we have designed a gene panel allowing the analysis of 51 genes involved in non-syndromic human infertility.
In this initial evaluation study, a cohort of 94 non-syndromic infertility cases with a well-defined infertility phenotype was examined.
Five patients with previously known mutations were used as positive controls.
With a mean coverage of 457×, and 99.
8% of target bases successfully sequenced with a depth coverage over 30×, we prove the robustness and the quality of our panel.
In total, we identified pathogenic or likely pathogenic variations in eight patients (five male and three female).
With a diagnostic yield of 8.
5% and the identification of a variety of variants including substitution, insertion, deletion, and copy number variations, our results demonstrate the usefulness of such a strategy, as well as the efficiency and the quality of this diagnostic gene panel.

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