Changepoint detection in base-resolution methylome data reveals a robust signature of methylated domain landscape.
BACKGROUND
Base-resolution methylome data generated by whole-genome bisulfite sequencing (WGBS) is often used to segment the genome into domains with distinct methylation levels. However, most segmentation methods include many parameters to be carefully tuned and/or fail to exploit the unsurpassed resolution of the data. Furthermore, there is no simple method that displays the composition of the domains to grasp global trends in each methylome.


RESULTS
We propose to use changepoint detection for domain demarcation based on base-resolution methylome data. While the proposed method segments the methylome in a largely comparable manner to conventional approaches, it has only a single parameter to be tuned. Furthermore, it fully exploits the base-resolution of the data to enable simultaneous detection of methylation changes in even contrasting size ranges, such as focal hypermethylation and global hypomethylation in cancer methylomes. We also propose a simple plot termed methylated domain landscape (MDL) that globally displays the size, the methylation level and the number of the domains thus defined, thereby enabling one to intuitively grasp trends in each methylome. Since the pattern of MDL often reflects cell lineages and is largely unaffected by data size, it can serve as a novel signature of methylome.


CONCLUSIONS
Changepoint detection in base-resolution methylome data followed by MDL plotting provides a novel method for methylome characterization and will facilitate global comparison among various WGBS data differing in size and even species origin.
Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa 277-8561, Japan. cb.yokoyama@gmail.com.
Takao
T
Yokoyama
Department of Biochemistry, Kyushu University Graduate School of Medical Sciences, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan. fumihito@med.kyushu-u.ac.jp.|Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan. fumihito@med.kyushu-u.ac.jp.
Fumihito
F
Miura
Department of Biochemistry, Kyushu University Graduate School of Medical Sciences, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan. h-araki@med.kyushu-u.ac.jp.
Hiromitsu
H
Araki
Department of Systems Biomedicine, National Research Institute for Child Health and Development, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo 157-8535, Japan. okamura-k@ncchd.go.jp.
Kohji
K
Okamura
Department of Biochemistry, Kyushu University Graduate School of Medical Sciences, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan. tito@med.kyushu-u.ac.jp.|Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan. tito@med.kyushu-u.ac.jp.
Takashi
T
Ito
D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D015894:Genome, Human; D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D009696:Nucleic Acids / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*
D009696:Nucleic Acids