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  5. Characterization of Parent-of-Origin Methylation Using the Illumina Infinium Methylationepic Array Platform

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Article
en
2018

Characterization of Parent-of-Origin Methylation Using the Illumina Infinium Methylationepic Array Platform

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0 Files

en
2018
Vol 10 (7)
Vol. 10
DOI: 10.2217/epi-2017-0172

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Manel Esteller
Manel Esteller

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José Ramón Hernández Mora
Chiharu Tayama
Marta Sánchez-Delgado
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Abstract

Aim: This study aimed to establish a catalog of probes corresponding to imprinted differentially methylated regions (DMRs) on the Infinium HumanMethylationEPIC BeadChip. Materials & methods: Reciprocal uniparental diploidies with low normal biparental mosaic contribution, together with normal diploid controls, were subjected to EPIC BeadChip hybridization. The methylation profiles were assessed for imprinted differential methylation. Top candidates were validated using locus-specific PCR-based assays. Results: Seven hundred and eighty-nine CpG probes coincided with 50 known imprinted DMRs and 467 CpG probes corresponding to 124 novel imprinted DMR candidates were identified. Validation led to identification of several subtle DMRs within known imprinted domains as well as novel maternally methylated regions associated with PTCHD3 and JAKMIP1. Conclusion: Our comprehensive list of bona fide-imprinted DMR probes will simplify and facilitate methylation profiling of individuals with imprinting disorders and is applicable to other diseases in which aberrant imprinting has been implicated, such as cancer and fetal growth.

How to cite this publication

José Ramón Hernández Mora, Chiharu Tayama, Marta Sánchez-Delgado, Ana Monteagudo, Kenichiro Hata, Tsutomu Ogata, José V. Medrano, Maria Eugenia Poo-Llanillo, Carlos Simón, Sebastián Morán, Manel Esteller, Jair Tenorio, Pablo Lapunzina, Masayo Kagami, David Monk, Kazuhiko Nakabayashi (2018). Characterization of Parent-of-Origin Methylation Using the Illumina Infinium Methylationepic Array Platform. , 10(7), DOI: https://doi.org/10.2217/epi-2017-0172.

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Publication Details

Type

Article

Year

2018

Authors

16

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.2217/epi-2017-0172

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