Evidence map›Paper›PMID 37422489›Full record

ArticleNature communications2023

DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing.

Peng Ni, Fan Nie, Zeyu Zhong, Jinrui Xu, Neng Huang, Jun Zhang, Haochen Zhao, You Zou, Yuanfeng Huang, Jinchen Li and 3 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed
14.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

69 citing papers in PubMed, 90 citations in OpenAlex.

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  16. Epigenomic methylome landscape of promoters in vertebrate genomes.bioRxiv : the preprint server for biology · 2026
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9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 2 countries.

Peng Ni *School of Computer Science and Engineering, Central South University, Changsha, 410083, China.ORCID 0000-0002-0801-7574
Fan Nie *School of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Zeyu ZhongSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.ORCID 0009-0005-9967-4244
Jinrui XuSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Neng HuangSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Jun ZhangSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Haochen ZhaoSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.
You ZouSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Yuanfeng HuangBioinformatics Center, National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, 410000, China.
Jinchen LiBioinformatics Center, National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, 410000, China.ORCID 0000-0003-3335-9303
Chuan-Le XiaoState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, #7 Jinsui Road, Tianhe District, Guangzhou, China. xiaochuanle@126.com.ORCID 0000-0002-4680-0682
Feng LuoSchool of Computing, Clemson University, Clemson, SC, 29634-0974, USA. luofeng@clemson.edu.ORCID 0000-0002-4813-2403
Jianxin WangSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China. jxwang@mail.csu.edu.cn.ORCID 0000-0003-1516-0480
Central South University · CNClemson University · USSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.

Indexed as

5-MethylcytosineDNAConsensusDNA MethylationHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNA5-MethylcytosineDNA

Identifiers

PMID37422489
PMCPMC10329642
OpenAlexW4383619104

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.