Assessing Cell-to-Cell DNA Methylation Variability on Individual Long Reads

Scientific Reports
Wei QuShinichi Morishita

Abstract

Understanding cell-to-cell variability in cytosine methylation is essential for understanding cellular perturbation and its molecular machinery. However, conventional methylation studies have focused on the differences in the average levels between cell types while overlooking methylation heterogeneity within cell types. Little information has been uncovered using recent single-cell methods because of either technical limitations or the great labor required to process many single cells. Here, we report the highly efficient detection of cell-to-cell DNA methylation variability in liver tissue, based on comparing the methylation status of adjacent CpG sites on long sequencing reads. This method provides abundant methylation linkage information and enables genome-wide estimation of cell-to-cell variability. We observed repressed methylation variability in hypomethylated regions compared with the variability in hypomethylated regions across the genome, which we confirmed using public human sperm data. A gradual change in methylation status at the boundaries of hypomethylated regions was observed for the first time. This approach allows the concise, comprehensive assessment of cell-to-cell DNA methylation variability.

References

May 3, 2003·Genome Research·Toshikazu UshijimaKazuaki Miyamoto
Dec 16, 2003·Proceedings of the National Academy of Sciences of the United States of America·Charles D LairdReinhard Stöger
Feb 28, 2006·Nucleic Acids Research·Rachna GoyalAlbert Jeltsch
May 23, 2007·The Anatomical Record : Advances in Integrative Anatomy and Evolutionary Biology·Ron C HardmanDavid E Hinton
Jul 29, 2009·BMC Bioinformatics·Yuanxin Xi, Wei Li
Jan 19, 2010·Bioinformatics·Heng Li, Richard Durbin
Jul 6, 2013·Science·Ryan ListerJoseph R Ecker
Jul 22, 2014·Nature Methods·Sébastien A SmallwoodGavin Kelsey

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Datasets Mentioned

BETA
PRJNA279817

Methods Mentioned

BETA
single-cell sequencing
WGBS
PCR
chip

Software Mentioned

MEM
BWA
bsmap

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