Department of Applied Chemistry, Graduate School of Science and Engineering, Ehime University, Matsuyama, Ehime 790-8577, Japan.
Department of Applied Chemistry, Graduate School of Science and Engineering, Ehime University, Matsuyama, Ehime 790-8577, Japan
RNA. 2024 May 16;30(6):710-727. doi: 10.1261/rna.079923.123.
All kinds of RNA molecules can be produced by in vitro transcription using T7 RNA polymerase using DNA templates obtained by solid-phase chemical synthesis, primer extension, PCR, or DNA cloning. The oligonucleotide design, however, is a challenge to nonexperts as this relies on a set of rules that have been established empirically over time. Here, we describe a Python program to facilitate the rational design of oligonucleotides, calculated with kinetic parameters for enhanced in vitro transcription (ROCKET). The Python tool uses thermodynamic parameters, performs folding-energy calculations, and selects oligonucleotides suitable for the polymerase extension reaction. These oligonucleotides improve yields of template DNA. With the oligonucleotides selected by the program, the tRNA transcripts can be prepared by a one-pot reaction of the DNA polymerase extension reaction and the transcription reaction. Also, the ROCKET-selected oligonucleotides provide greater transcription yields than that from oligonucleotides selected by Primerize, a leading software for designing oligonucleotides for in vitro transcription, due to the enhancement of template DNA synthesis. Apart from over 50 tRNA genes tested, an in vitro transcribed self-cleaving ribozyme was found to have catalytic activity. In addition, the program can be applied to the synthesis of mRNA, demonstrating the wide applicability of the ROCKET software.
各种 RNA 分子都可以通过 T7 RNA 聚合酶在体外转录使用固相化学合成、引物延伸、PCR 或 DNA 克隆获得的 DNA 模板。然而，寡核苷酸的设计对于非专业人士来说是一个挑战，因为这需要一套经过时间验证的经验法则。在这里，我们描述了一个 Python 程序，以方便合理的设计寡核苷酸，计算与增强体外转录的动力学参数（火箭）。该 Python 工具使用热力学参数，进行折叠能计算，并选择适合聚合酶延伸反应的寡核苷酸。这些寡核苷酸提高了模板 DNA 的产量。使用该程序选择的寡核苷酸，tRNA 转录物可以通过 DNA 聚合酶延伸反应和转录反应的一锅反应来制备。此外，由于模板 DNA 合成的增强，ROCKET 选择的寡核苷酸比体外转录设计寡核苷酸的领先软件 Primerize 选择的寡核苷酸提供更高的转录产量。除了测试的 50 多个 tRNA 基因外，还发现体外转录的自我切割核酶具有催化活性。此外，该程序可应用于 mRNA 的合成，证明了 ROCKET 软件的广泛适用性。
