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生物RNA分子的神经网络大小可以计算,且并非异常小。

Neutral network sizes of biological RNA molecules can be computed and are not atypically small.

作者信息

Jörg Thomas, Martin Olivier C, Wagner Andreas

机构信息

Inria Saclay, Ile-de-France, INRIA, Parc Orsay Université 4, Orsay Cedex, France.

出版信息

BMC Bioinformatics. 2008 Oct 30;9:464. doi: 10.1186/1471-2105-9-464.

Abstract

BACKGROUND

Neutral networks or sets consist of all genotypes with a given phenotype. The size and structure of these sets has a strong influence on a biological system's robustness to mutations, and on its evolvability, the ability to produce phenotypic variation; in the few studied cases of molecular phenotypes, the larger this set, the greater both robustness and evolvability of phenotypes. Unfortunately, any one neutral set contains generally only a tiny fraction of genotype space. Thus, current methods cannot measure neutral set sizes accurately, except in the smallest genotype spaces.

RESULTS

Here we introduce a generalized Monte Carlo approach that can measure neutral set sizes in larger spaces. We apply our method to the genotype-to-phenotype mapping of RNA molecules, and show that it can reliably measure neutral set sizes for molecules up to 100 bases. We also study neutral set sizes of RNA structures in a publicly available database of functional, noncoding RNAs up to a length of 50 bases. We find that these neutral sets are larger than the neutral sets in 99.99% of random phenotypes. Software to estimate neutral network sizes is available at (http://www.bioc.uzh.ch/wagner/publications-software.html).

CONCLUSION

The biological RNA structures we examined are more abundant than random structures. This indicates that their robustness and their ability to produce new phenotypic variants may also be high.

摘要

背景

中性网络或集合由具有给定表型的所有基因型组成。这些集合的大小和结构对生物系统对突变的稳健性及其进化能力(产生表型变异的能力)有很大影响;在少数已研究的分子表型案例中,这个集合越大,表型的稳健性和进化能力就越强。不幸的是,任何一个中性集合通常只包含基因型空间的极小一部分。因此,除了在最小的基因型空间中,当前方法无法准确测量中性集合的大小。

结果

在此,我们引入一种广义蒙特卡罗方法,该方法可以测量更大空间中的中性集合大小。我们将我们的方法应用于RNA分子的基因型到表型的映射,并表明它可以可靠地测量长度达100个碱基的分子的中性集合大小。我们还在一个公开可用的长度达50个碱基的功能性非编码RNA数据库中研究了RNA结构的中性集合大小。我们发现这些中性集合比99.99%的随机表型中的中性集合更大。用于估计中性网络大小的软件可在(http://www.bioc.uzh.ch/wagner/publications-software.html)获取。

结论

我们研究的生物RNA结构比随机结构更为丰富。这表明它们的稳健性以及产生新表型变体的能力可能也很高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd3/2639431/608257e1cd41/1471-2105-9-464-1.jpg

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