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A Statistical Method for Observing Personal Diploid Methylomes and Transcriptomes with Single-Molecule Real-Time Sequencing

1
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 277-8561, Japan
2
Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA
3
Department of Biomedical Informatics, Ohio State University, Columbus, OH 43210, USA
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Genes 2018, 9(9), 460; https://doi.org/10.3390/genes9090460
Received: 15 August 2018 / Revised: 12 September 2018 / Accepted: 12 September 2018 / Published: 19 September 2018
(This article belongs to the Special Issue Advances in Single Molecule, Real-Time (SMRT) Sequencing)
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Abstract

We address the problem of observing personal diploid methylomes, CpG methylome pairs of homologous chromosomes that are distinguishable with respect to phased heterozygous variants (PHVs), which is challenging due to scarcity of PHVs in personal genomes. Single molecule real-time (SMRT) sequencing is promising as it outputs long reads with CpG methylation information, but a serious concern is whether reliable PHVs are available in erroneous SMRT reads with an error rate of ∼15%. To overcome the issue, we propose a statistical model that reduces the error rate of phasing CpG site to 1%, thereby calling CpG hypomethylation in each haplotype with >90% precision and sensitivity. Using our statistical model, we examined GNAS complex locus known for a combination of maternally, paternally, or biallelically expressed isoforms, and observed allele-specific methylation pattern almost perfectly reflecting their respective allele-specific expression status, demonstrating the merit of elucidating comprehensive personal diploid methylomes and transcriptomes. View Full-Text
Keywords: statistical methods; DNA methylation; gene expression; single molecule real-time sequencing; allele-specific analysis statistical methods; DNA methylation; gene expression; single molecule real-time sequencing; allele-specific analysis
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Suzuki, Y.; Wang, Y.; Au, K.F.; Morishita, S. A Statistical Method for Observing Personal Diploid Methylomes and Transcriptomes with Single-Molecule Real-Time Sequencing. Genes 2018, 9, 460.

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