CpG Island Definition and Methylation Mapping of the T2T-YAO Genome.

DNA methylation Density-defined CpG island Genome analysis Position-defined CpG island T2T-YAO

Journal

Genomics, proteomics & bioinformatics
ISSN: 2210-3244
Titre abrégé: Genomics Proteomics Bioinformatics
Pays: England
ID NLM: 101197608

Informations de publication

Date de publication:
03 Jul 2024
Historique:
received: 06 11 2023
revised: 05 12 2023
accepted: 08 12 2023
medline: 15 8 2024
pubmed: 15 8 2024
entrez: 14 8 2024
Statut: ppublish

Résumé

Precisely defining and mapping all cytosine (C) positions and their clusters, known as CpG islands (CGIs), as well as their methylation status, are pivotal for genome-wide epigenetic studies, especially when population-centric reference genomes are ready for timely application. Here, we first align the two high-quality reference genomes, T2T-YAO and T2T-CHM13, from different ethnic backgrounds in a base-by-base fashion and compute their genome-wide density-defined and position-defined CGIs. Second, by mapping some representative genome-wide methylation data from selected organs onto the two genomes, we find that there are about 4.7%-5.8% sequence divergency of variable categories depending on quality cutoffs. Genes among the divergent sequences are mostly associated with neurological functions. Moreover, CGIs associated with the divergent sequences are significantly different with respect to CpG density and observed CpG/expected CpG (O/E) ratio between the two genomes. Finally, we find that the T2T-YAO genome not only has a greater CpG coverage than that of the T2T-CHM13 genome when whole-genome bisulfite sequencing (WGBS) data from the European and American populations are mapped to each reference, but also shows more hyper-methylated CpG sites as compared to the T2T-CHM13 genome. Our study suggests that future genome-wide epigenetic studies of the Chinese populations rely on both acquisition of high-quality methylation data and subsequent precision CGI mapping based on the Chinese T2T reference.

Identifiants

pubmed: 39142816
pii: 7596638
doi: 10.1093/gpbjnl/qzae009
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press and Science Press on behalf of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China.

Auteurs

Ming Xiao (M)

College of Computer Science, Sichuan University, Chengdu 610065, China.

Rui Wei (R)

College of Computer Science, Sichuan University, Chengdu 610065, China.
Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.

Jun Yu (J)

CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.
University of Chinese Academy of Sciences, Beijing 100049, China.

Chujie Gao (C)

College of Computer Science, Sichuan University, Chengdu 610065, China.

Fengyi Yang (F)

College of Computer Science, Sichuan University, Chengdu 610065, China.

Le Zhang (L)

College of Computer Science, Sichuan University, Chengdu 610065, China.
Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.

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Classifications MeSH