AgIn: measuring the landscape of CpG methylation of individual repetitive elements.
Determining the methylation state of regions with high copy numbers is challenging for second-generation sequencing, because the read length is insufficient to map reads uniquely, especially when repetitive regions are long and nearly identical to each other. Single-molecule real-time (SMRT) sequencing is a promising method for observing such regions, because it is not vulnerable to GC bias, it produces long read lengths, and its kinetic information is sensitive to DNA modifications.



We propose a novel linear-time algorithm that combines the kinetic information for neighboring CpG sites and increases the confidence in identifying the methylation states of those sites. Using a practical read coverage of ∼30-fold from an inbred strain medaka (Oryzias latipes), we observed that both the sensitivity and precision of our method on individual CpG sites were ∼93.7%. We also observed a high correlation coefficient (R = 0.884) between our method and bisulfite sequencing, and for 92.0% of CpG sites, methylation levels ranging over [0,1] were in concordance within an acceptable difference 0.25. Using this method, we characterized the landscape of the methylation status of repetitive elements, such as LINEs, in the human genome, thereby revealing the strong correlation between CpG density and hypomethylation and detecting hypomethylation hot spots of LTRs and LINEs. We uncovered the methylation states for nearly identical active transposons, two novel LINE insertions of identity ∼99% and length 6050 base pairs (bp) in the human genome, and 16 Tol2 elements of identity >99.8% and length 4682 bp in the medaka genome.



AgIn (Aggregate on Intervals) is available at: https://github.com/hacone/AgIn



ysuzuki@cb.k.u-tokyo.ac.jp or moris@cb.k.u-tokyo.ac.jp



Supplementary data are available at Bioinformatics online.
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8583, Japan.
Yuta
Y
Suzuki
Pacific Biosciences, Menlo Park, CA 94025, USA.
Jonas
J
Korlach
Pacific Biosciences, Menlo Park, CA 94025, USA.
Stephen W
SW
Turner
Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan.
Tatsuya
T
Tsukahara
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8583, Japan.
Junko
J
Taniguchi
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8583, Japan.
Wei
W
Qu
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8583, Japan.
Kazuki
K
Ichikawa
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8583, Japan.
Jun
J
Yoshimura
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8583, Japan.
Hideaki
H
Yurino
Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan.
Yuji
Y
Takahashi
Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan.
Jun
J
Mitsui
Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan.
Hiroyuki
H
Ishiura
Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan.
Shoji
S
Tsuji
Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan.
Hiroyuki
H
Takeda
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8583, Japan.
Shinichi
S
Morishita
D000465:Algorithms; D018899:CpG Islands; D019175:DNA Methylation; D015894:Genome, Human; D006801:Humans; D017422:Sequence Analysis, DNA