AgIn: measuring the landscape of CpG methylation of individual repetitive elements. (17th June 2016)
- Record Type:
- Journal Article
- Title:
- AgIn: measuring the landscape of CpG methylation of individual repetitive elements. (17th June 2016)
- Main Title:
- AgIn: measuring the landscape of CpG methylation of individual repetitive elements
- Authors:
- Suzuki, Yuta
Korlach, Jonas
Turner, Stephen W.
Tsukahara, Tatsuya
Taniguchi, Junko
Qu, Wei
Ichikawa, Kazuki
Yoshimura, Jun
Yurino, Hideaki
Takahashi, Yuji
Mitsui, Jun
Ishiura, Hiroyuki
Tsuji, Shoji
Takeda, Hiroyuki
Morishita, Shinichi - Abstract:
- Abstract : Motivation: 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. Results: 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, twoAbstract : Motivation: 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. Results: 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. Availability and Implementation: AgIn ( Ag gregate on In tervals) is available at: https://github.com/hacone/AgIn Contact: ysuzuki@cb.k.u-tokyo.ac.jp or moris@cb.k.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. … (more)
- Is Part Of:
- Bioinformatics. Volume 32:Number 19(2016)
- Journal:
- Bioinformatics
- Issue:
- Volume 32:Number 19(2016)
- Issue Display:
- Volume 32, Issue 19 (2016)
- Year:
- 2016
- Volume:
- 32
- Issue:
- 19
- Issue Sort Value:
- 2016-0032-0019-0000
- Page Start:
- 2911
- Page End:
- 2919
- Publication Date:
- 2016-06-17
- Subjects:
- Bioinformatics -- Periodicals
Genomics -- Data processing -- Periodicals
Computational biology -- Periodicals
572.80285 - Journal URLs:
- http://bioinformatics.oxfordjournals.org ↗
http://firstsearch.oclc.org ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/bioinformatics/btw360 ↗
- Languages:
- English
- ISSNs:
- 1367-4803
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2072.348000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12388.xml