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Related Experiment Videos

A probabilistic model for the evolution of RNA structure.

Ian Holmes1

  • 1Department of Bioengineering, University of California, Berkeley 94720-1762, USA. ihh@berkeley.edu

BMC Bioinformatics
|October 28, 2004
PubMed
Summary

We developed a simplified evolutionary model for RNA sequences to align noncoding RNA (ncRNA) genes. This model effectively captures coordinated basepair substitutions and indels, forming a basis for multiple alignment tools.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Evolution

Background:

  • Aligning noncoding RNA (ncRNA) genes and cis-regulatory elements across multiple genomes requires systematic derivation of multi-sequence stochastic grammars.
  • Hypotheses about random mutation events and their rates are crucial for developing effective multiple alignment algorithms.

Purpose of the Study:

  • To implement and evaluate a simplified evolutionary model for RNA, the TKF91 Structure Tree, for pairwise alignment.
  • To test the model's ability to identify characteristic signatures of natural selection in functional ncRNA sequences.

Main Methods:

  • Developed and implemented the TKF91 Structure Tree model, based on Thorne, Kishino, and Felsenstein's 1991 model of sequence evolution with indels.
  • Applied the model to pairwise alignment of four functional ncRNA sequences: guanine riboswitch, nanos zipcode, U4 splicing factor, and RNase P ribozyme.
  • Visualized posterior probability matrices to identify signatures of natural selection.

Main Results:

  • The model successfully identified three signatures of natural selection in ncRNA: coordinated basepair substitutions, coordinated basepair indels, and whole-stem indels.
  • Coordinated basepair substitutions and indels were better modeled than whole-stem indels.
  • The model's performance on pairwise alignments suggests its potential for multiple alignment and genefinding tools.

Conclusions:

  • The TKF91 Structure Tree model, despite its simplifications, provides a promising foundation for developing advanced ncRNA alignment and genefinding tools.
  • The model's ability to capture key evolutionary events in ncRNA supports its utility in comparative genomics.

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