Comparison of NGS panel and Sanger sequencing for genotyping CAG repeats in the AR gene.


Journal

Molecular genetics & genomic medicine
ISSN: 2324-9269
Titre abrégé: Mol Genet Genomic Med
Pays: United States
ID NLM: 101603758

Informations de publication

Date de publication:
06 2020
Historique:
received: 23 08 2019
revised: 19 02 2020
accepted: 22 02 2020
pubmed: 28 3 2020
medline: 14 4 2021
entrez: 28 3 2020
Statut: ppublish

Résumé

The androgen receptor (AR) is a nuclear receptor, encoded by the AR gene on the X chromosome. Within the first exon of the AR gene, two short tandem repeats (STR), CAG and GGC, are a source of polymorphism in the population. Therefore, high-throughput methods for screening AR, such as next-generation sequencing (NGS), are sought after; however, data generated by NGS are limited by the availability of bioinformatics tools. Here, we evaluated the accuracy of the bioinformatics tool HipSTR in detecting and quantify CAG repeats within the AR gene. The AR gene of 228 infertile men was sequenced using NGSgene panel. Data generated were analyzed with HipSTR to detect CAG repeats. The accuracy was compared with the results obtained with Sanger. We found that HipSTR was more accurate than Sanger in genotyping normal karyotype men (46,XY), however, it was more likely to misidentify homozygote genotypes in men with Klinefelter syndrome (47,XXY). Our findings show that the bioinformatics tool HipSTR is 100% accurate in detecting and assessing AR CAG repeats in infertile men (46,XY) as well as in men with low-level mosaicism.

Sections du résumé

BACKGROUND
The androgen receptor (AR) is a nuclear receptor, encoded by the AR gene on the X chromosome. Within the first exon of the AR gene, two short tandem repeats (STR), CAG and GGC, are a source of polymorphism in the population. Therefore, high-throughput methods for screening AR, such as next-generation sequencing (NGS), are sought after; however, data generated by NGS are limited by the availability of bioinformatics tools. Here, we evaluated the accuracy of the bioinformatics tool HipSTR in detecting and quantify CAG repeats within the AR gene.
METHOD
The AR gene of 228 infertile men was sequenced using NGSgene panel. Data generated were analyzed with HipSTR to detect CAG repeats. The accuracy was compared with the results obtained with Sanger.
RESULTS
We found that HipSTR was more accurate than Sanger in genotyping normal karyotype men (46,XY), however, it was more likely to misidentify homozygote genotypes in men with Klinefelter syndrome (47,XXY).
CONCLUSION
Our findings show that the bioinformatics tool HipSTR is 100% accurate in detecting and assessing AR CAG repeats in infertile men (46,XY) as well as in men with low-level mosaicism.

Identifiants

pubmed: 32216057
doi: 10.1002/mgg3.1207
pmc: PMC7284049
doi:

Substances chimiques

Receptors, Androgen 0

Types de publication

Comparative Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1207

Informations de copyright

© 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.

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Auteurs

Maria Santa Rocca (MS)

Unit of Andrology and Reproductive Medicine, Department of Medicine, University of Padua, Padua, Italy.

Margherita Ferrarini (M)

Unit of Andrology and Reproductive Medicine, Department of Medicine, University of Padua, Padua, Italy.

Aichi Msaki (A)

Unit of Andrology and Reproductive Medicine, Department of Medicine, University of Padua, Padua, Italy.

Cinzia Vinanzi (C)

Unit of Andrology and Reproductive Medicine, Department of Medicine, University of Padua, Padua, Italy.

Marco Ghezzi (M)

Unit of Andrology and Reproductive Medicine, Department of Medicine, University of Padua, Padua, Italy.

Maurizio De Rocco Ponce (M)

Unit of Andrology and Reproductive Medicine, Department of Medicine, University of Padua, Padua, Italy.

Carlo Foresta (C)

Unit of Andrology and Reproductive Medicine, Department of Medicine, University of Padua, Padua, Italy.

Alberto Ferlin (A)

Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.

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Classifications MeSH