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Updated: Jan 7, 2026

Strand-Specific Analysis of Proteins at Replicating DNA Strands by Enrichment and Sequencing of Protein-Associated Nascent DNA Method
Published on: May 2, 2025
Dynamic regulation of nucleic acid replication beyond the Watson-Crick base-pairing rule
Shuntaro Takahashi1,2, Lutan Liu1, Naoki Sugimoto1
1FIBER (Frontier Institute for Biomolecular Engineering Research), Konan University, 7-1-20 Minatojima-Minamimachi, Chuo-ku, Kobe 650-0047, Japan, shtakaha@konan-u.ac.jp.
None:
Nucleic acids form various helical structures through base-pair formation. The most fundamental base pairing is Watson-Crick, which establishes a complementary rule in nucleic acids. According to this rule, living systems can replicate their genes to propagate them correctly to their daughter organisms. The complementary rule can be interpreted in chemistry, as the Watson-Crick base pairing is the most stable. On the other hand, non-Watson-Crick base pairings, termed mismatch base pairings, are also frequently found. Mismatched base pairings formed during gene replication lead to mutations, which can cause evolution of life or diseases such as cancer. Such metastable non-Watson-Crick base pairings are considered to be randomly occurring events, and their underlying chemistry has been neglected. However, the stability of Watson-Crick base pairs can be modulated by the environments, and sometimes non-Watson-Crick base pairs indicate higher stability than Watson-Crick base pairs. Moreover, the formation of non-Watson-Crick base pairs in the template strand creates non-duplex structures that can cause replication errors. Therefore, a quantitative study of non-Watson-Crick base pairing by changing the environments of the solutions can provide novel insights into genetic mutations regulated by chemistry-validated "non-Watson-Crick rules". In this review, we summarise the basic and recent studies on the chemistry regulating replication by non-Watson-Crick base pairs and state how genetic mutations are chemically controllable. Furthermore, we discuss potential databases for predicting gene mutations under various solution conditions and their integration for future applications.
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