Higgs Paul G, Muller Ulrich F
Department of Physics and Astronomy, Faculty of Science, McMaster University, Hamilton, Ontario, Canada.
Department of Chemistry, University of California San Diego, La Jolla, CA, USA.
J R Soc Interface. 2025 Apr;22(225):20240878. doi: 10.1098/rsif.2024.0878. Epub 2025 Apr 16.
selection methods are used to identify catalytic RNAs from pools of random sequences. We discuss the central concepts using experimental data and computational models. Experiments proceed in multiple rounds, each with a reaction step and a step in which reacted sequences are recovered. Sequences are enriched each round by a factor depending on combined reaction and recovery probability. In the first round, there are few functional sequences, and it is necessary to minimize the probability of losing these. In later rounds, the loss probability is negligible, and the procedure can be optimized to maximize the enrichment factor. Clusters of related sequences emerge which descend from separate sequences in the initial pool. The fitness of an RNA depends on how well it matches a structure with specified sequence and base-pair constraints. Sequences that exactly match the constraints may be rare, but sequences a few mutations away are much more common; hence it is likely that clusters descend from suboptimal sequences. There is a high probability that beneficial mutations arise during the experiment. This explains the experimental observation that there is little correlation between cluster frequencies and fitnesses, whereas correlation between enrichment factors and fitnesses is strong.
选择方法用于从随机序列库中识别催化RNA。我们使用实验数据和计算模型来讨论核心概念。实验分多轮进行，每轮都有一个反应步骤和一个回收反应序列的步骤。每轮序列富集的倍数取决于反应和回收概率的综合情况。在第一轮中，功能序列很少，有必要将丢失这些序列的概率降至最低。在后续轮次中，丢失概率可以忽略不计，并且可以对该程序进行优化以最大化富集倍数。出现了相关序列的簇，这些簇源自初始库中的不同序列。RNA的适应性取决于它与具有特定序列和碱基对限制的结构的匹配程度。完全符合限制的序列可能很少见，但相差几个突变的序列则更为常见；因此，簇很可能源自次优序列。在实验过程中很有可能出现有益突变。这解释了实验观察结果，即簇频率与适应性之间几乎没有相关性，而富集倍数与适应性之间的相关性很强。
