School of Computer Science, Carleton University, Ottawa, Ontario K1S5B6, Canada.
RNA. 2010 Nov;16(11):2252-62. doi: 10.1261/rna.2102210. Epub 2010 Sep 24.
It is well known that using random RNA/DNA sequences for SELEX experiments will generally yield low-complexity structures. Early experimental results suggest that having a structurally diverse library, which, for instance, includes high-order junctions, may prove useful in finding new functional motifs. Here, we develop two computational methods to generate sequences that exhibit higher structural complexity and can be used to increase the overall structural diversity of initial pools for in vitro selection experiments. Random Filtering selectively increases the number of five-way junctions in RNA/DNA pools, and Genetic Filtering designs RNA/DNA pools to a specified structure distribution, whether uniform or otherwise. We show that using our computationally designed DNA pool greatly improves access to highly complex sequence structures for SELEX experiments (without losing our ability to select for common one-way and two-way junction sequences).
众所周知,在 SELEX 实验中使用随机 RNA/DNA 序列通常会产生低复杂度的结构。早期的实验结果表明,具有结构多样化的文库,例如包含高阶连接,可能有助于发现新的功能基序。在这里,我们开发了两种计算方法来生成表现出更高结构复杂性的序列,并可用于增加体外选择实验初始池的整体结构多样性。随机过滤选择性地增加了 RNA/DNA 池中的五向连接的数量,而遗传过滤则根据指定的结构分布(无论是均匀分布还是其他分布)设计 RNA/DNA 池。我们表明,使用我们计算设计的 DNA 池可大大提高 SELEX 实验中获得高度复杂序列结构的能力(而不会丧失选择常见单向和双向连接序列的能力)。