Unraveling the whole genome DNA methylation profile of zebrafish kidney marrow by Oxford Nanopore sequencing

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Xudong Liu
  • Dandan Wang
  • Silin Ye
  • Xuan Sun
  • Anskar Yu Hung Leung

Detail(s)

Original languageEnglish
Pages (from-to)532
Journal / PublicationScientific data
Volume10
Online published10 Aug 2023
Publication statusPublished - 2023

Link(s)

Abstract

Zebrafish is a widely used model organism for investigating human diseases, including hematopoietic disorders. However, a comprehensive methylation baseline for zebrafish primary hematopoietic organ, the kidney marrow (KM), is still lacking. We employed Oxford Nanopore Technologies (ONT) sequencing to profile DNA methylation in zebrafish KM by generating four KM datasets, with two groups based on the presence or absence of red blood cells. Our findings revealed that blood contamination in the KM samples reduced read quality and altered methylation patterns. Compared with whole-genome bisulfite sequencing (WGBS), the ONT-based methylation profiling can cover more CpG sites (92.4% vs 70%-80%), and exhibit less GC bias with more even genomic coverage. And the ONT methylation calling results showed a high correlation with WGBS results when using shared sites. This study establishes a comprehensive methylation profile for zebrafish KM, paving the way for further investigations into epigenetic regulation and the development of targeted therapies for hematopoietic disorders.

© The Author(s) 2023

Research Area(s)

  • Animals, CpG Islands, DNA Methylation, Epigenesis, Genetic, High-Throughput Nucleotide Sequencing/methods, Nanopore Sequencing, Sequence Analysis, DNA/methods, Zebrafish/genetics, Hematopoiesis/genetics

Bibliographic Note

© 2023. Springer Nature Limited.

Citation Format(s)

Unraveling the whole genome DNA methylation profile of zebrafish kidney marrow by Oxford Nanopore sequencing. / Liu, Xudong; Ni, Ying; Wang, Dandan et al.
In: Scientific data, Vol. 10, 2023, p. 532.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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