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Open Access

Detection of Base Modifications Using Long-Read Sequencing: Methods, Applications, and Challenges

Xiangjiang Laboratory, Changsha 410205, China, and also with School of Computer Science and Engineering, Central South University, Changsha 410083, China
Xiangjiang Laboratory, Changsha 410205, China, and also with Hunan Provincial Key Lab on Bioinformatics and School of Computer Science and Engineering, Central South University, Changsha 410083, China
Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China, and also with Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong 999077, China
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Abstract

Base modifications are fundamental epigenetic marks widely present in both deoxyribonucleic acid (DNA) and ribonucleic acid (RNA), playing crucial roles in regulating gene expression, development, aging, and the pathogenesis of various diseases. Conventional detection methods often depend on harsh chemical treatments or amplification, which can introduce biases, damage biomolecules, and limit detection accuracy. The advent of third-generation long-read sequencing technologies, such as PacBio Single-Molecule Real-Time (SMRT) and Oxford Nanopore sequencing, has revolutionized the field by enabling direct, single-molecule resolution detection of base modifications without complex preprocessing. This review presents a comprehensive overview of the principles and advantages of these technologies, highlighting recent advances in the detection of DNA modifications (e.g., 5mC, 6mA, and 5hmC) and RNA modifications (e.g., m6A and Ψ). In contrast to prior reviews that typically focus on either DNA or RNA alone, our work provides an integrated perspective on modification detection across both molecular types, covering underlying mechanisms, computational tools, and technological innovations. We further provide a comparative analysis of representative detection methods, especially those that are compatible with the latest sequencing platforms and capable of supporting complex biological contexts. We also discuss emerging applications in epigenetics, disease research, and clinical diagnostics, alongside major challenges such as enhancing detection accuracy and enabling multi-omics integration. By unifying DNA and RNA modification analysis, this review offers a more holistic framework for advancing epigenetic research and its applications.

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Big Data Mining and Analytics
Pages 1276-1307

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Cite this article:
Sheng T, Wang S, Xiao Y, et al. Detection of Base Modifications Using Long-Read Sequencing: Methods, Applications, and Challenges. Big Data Mining and Analytics, 2026, 9(5): 1276-1307. https://doi.org/10.26599/BDMA.2025.9020101

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Received: 07 May 2025
Revised: 31 July 2025
Accepted: 25 August 2025
Published: 20 August 2026
© The author(s) 2026.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).