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De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
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An extended genetic scale of reading frame coding.

Christian J Michel1

  • 1Theoretical bioinformatics, ICube, University of Strasbourg, CNRS, 300 Boulevard Sébastien Brant, 67400 Illkirch, France.

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|October 15, 2014
PubMed
Summary

This study reintroduces the reading frame coding (RFC) concept for trinucleotide codes. It reveals significant variations in RFC efficiency across different gene types, offering new insights into genetic code evolution.

Keywords:
Circular code usageCoding evolutionGenetic scaleReading frame codingTrinucleotide circular code

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Area of Science:

  • Genetics
  • Bioinformatics
  • Molecular Biology

Background:

  • The concept of reading frame coding (RFC) for trinucleotide sets has been under-explored for decades.
  • Statistical analysis of genetic code properties is crucial for understanding gene function and evolution.

Purpose of the Study:

  • To extend the definition of the statistical parameter PrRFC for analyzing trinucleotide code efficiency.
  • To analyze the RFC efficiency of usage for the C(3) self-complementary trinucleotide circular code (usage XU) in various genes.

Main Methods:

  • Extended definition of the statistical parameter PrRFC.
  • Application of PrRFC to analyze the RFC efficiency of usage XU.
  • Comparative analysis of RFC probabilities across different genetic entities (bacteria, archaea, viruses, eukaryotes, organelles).

Main Results:

  • RFC efficiency of usage XU varies significantly across different biological systems.
  • Highest RFC probabilities are found in bacterial plasmids and bacteria (~49.0%), followed by archaea (47.5%), viruses (45.4%), and nuclear eukaryotes (42.8%).
  • Mitochondria and chloroplasts exhibit the lowest RFC probabilities (~36.5%).

Conclusions:

  • Genes contain inherent information related to reading frame coding.
  • The identified genetic property of RFC may provide novel perspectives on the origin and evolution of the genetic code.
  • This research highlights the importance of previously overlooked genetic concepts.