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RNAdualPF: software to compute the dual partition function with sample applications in molecular evolution theory.

Juan Antonio Garcia-Martin1,2, Amir H Bayegan1, Ivan Dotu3

  • 1Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, 02467, MA, USA.

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|October 21, 2016
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RNA inverse folding software RNAdualPF samples sequences that fold into a target structure. This study suggests natural RNAs are under evolutionary pressure for marginal stability and that pre-miRNA is mutationally non-robust.

Keywords:
Boltzmann ensemblePartition functionRNA secondary structureRobustness

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Evolution

Background:

  • RNA inverse folding seeks sequences matching a target secondary structure (s₀).
  • This study examines RNA sequences with low free energy relative to a target structure.

Purpose of the Study:

  • Introduce RNAdualPF for computing the dual partition function (Z*).
  • Enable efficient sampling of RNA sequences folding into a target structure with constraints.
  • Investigate evolutionary pressures on RNA stability and microRNA robustness.

Main Methods:

  • Developed RNAdualPF to compute the dual partition function (Z*).
  • Sampled RNA sequences with specified GC-content and IUPAC constraints.
  • Calculated dual expected energy (〈E*〉) to assess thermodynamic stability.
  • Compared pre-miRNA robustness against sequences generated by RNAdualPF.

Main Results:

  • RNAdualPF efficiently samples sequences compatible with target structures, allowing constraints.
  • Natural RNAs exhibit higher minimum free energy than expected, suggesting marginal stability.
  • C. elegans pre-miRNA is significantly non-robust to mutations.
  • Confirmed plasticity in precursor microRNAs and bacterial small noncoding RNAs.

Conclusions:

  • RNAdualPF enables rapid computation and sequence sampling for RNA inverse folding.
  • Findings on pre-miRNA robustness contrast with previous studies, highlighting software dependency.
  • Computational insights into molecular evolution require careful consideration of the tools used.