North Dakota State University, Fargo, USA.
Georgia Institute of Technology, Atlanta, USA.
Bull Math Biol. 2020 Oct 7;82(10):133. doi: 10.1007/s11538-020-00804-0.
A growing number of RNA sequences are now known to exist in some distribution with two or more different stable structures. Recent algorithms attempt to reconstruct such mixtures using the list of nucleotides in a sequence in conjunction with auxiliary experimental footprinting data. In this paper, we demonstrate some challenges which remain in addressing this problem; in particular we consider the difficulty of reconstructing a mixture of two RNA structures across a spectrum of different relative abundances. Although progress has been made in identifying the stable structures present, it remains nontrivial to predict the relative abundance of each within the experimentally sampled mixture. Because the ratio of structures present can change depending on experimental conditions, it is the footprinting data-and not the sequence-which must encode information on changes in the relative abundance. Here, we use simulated experimental data to demonstrate that there exist RNA sequences and relative abundance combinations which cannot be recovered by current methods. We then prove that this is not a single exception, but rather part of the rule. In particular, we show, using a Nussinov-Jacobson model, that recovering the relative abundances is difficult for a large proportion of RNA structure pairs. Lastly, we use information theory to establish a framework for quantifying how useful auxiliary data is in predicting the relative abundance of a structure. Together, these results demonstrate that aspects of the problem of reconstructing a mixture of RNA structures from experimental data remain open.
越来越多的 RNA 序列现在已知存在于具有两个或更多不同稳定结构的某种分布中。最近的算法试图使用序列中的核苷酸列表以及辅助实验足迹数据来重建此类混合物。在本文中，我们展示了在解决此问题时仍然存在的一些挑战；特别是，我们考虑了在不同相对丰度范围内重建两种 RNA 结构混合物的困难。尽管在确定存在的稳定结构方面已经取得了进展，但预测实验采样混合物中每个结构的相对丰度仍然不是微不足道的。由于存在的结构的比例可以根据实验条件而变化，因此必须由足迹数据（而不是序列）来编码相对丰度变化的信息。在这里，我们使用模拟实验数据来证明存在 RNA 序列和相对丰度组合，这些组合不能通过当前的方法来恢复。然后，我们证明这不是一个例外，而是规则的一部分。具体来说，我们使用 Nussinov-Jacobson 模型证明，对于很大一部分 RNA 结构对，恢复相对丰度是困难的。最后，我们使用信息论来建立一个框架，用于量化辅助数据在预测结构的相对丰度方面的有用程度。总之，这些结果表明，从实验数据重建 RNA 结构混合物的问题的某些方面仍然存在。
