Kim Woojin, Chon Mingweon, Koh Yoonhae, Choi Hansol, Choi Eunjin, Park Hyewon, Jung Yushin, Ryu Taehoon, Kwon Sunghoon, Choi Yeongjae
School of Materials Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea.
Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Nat Commun. 2025 Feb 12;16(1):1586. doi: 10.1038/s41467-025-56856-0.
Effective subset selection from complex oligonucleotide libraries is crucial for genomics, synthetic biology, and DNA data storage. The polymerase chain reaction, foundational for amplifying target subsets is limited by primer design and length for specificity, which constrains the scalability of oligo libraries and increases the synthesis burden for primers. We introduce an oligo subset selection methodology that utilizes sequence-specific cyclic nucleotide synthesis and blocking of the template oligos. This approach eliminates the need for primers for selective hybridization and enables the encoding and selection of hundreds of subsets with barcode lengths of fewer than five nucleotides. Moreover, cyclic selection enables a hierarchical data structure in the oligo library, enhancing the programmability. This advancement offers a scalable and cost-effective solution for handling complex oligo libraries.
从复杂的寡核苷酸文库中进行有效的子集选择对于基因组学、合成生物学和DNA数据存储至关重要。聚合酶链反应是扩增目标子集的基础,但受引物设计和特异性长度的限制,这限制了寡核苷酸文库的可扩展性,并增加了引物的合成负担。我们引入了一种寡核苷酸子集选择方法,该方法利用序列特异性环核苷酸合成和模板寡核苷酸的封闭。这种方法无需用于选择性杂交的引物,并能够对数百个子集进行编码和选择,条形码长度少于五个核苷酸。此外,循环选择能够在寡核苷酸文库中形成分层数据结构,增强了可编程性。这一进展为处理复杂的寡核苷酸文库提供了一种可扩展且经济高效 的解决方案。