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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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tRNAmodpred: A computational method for predicting posttranscriptional modifications in tRNAs.

Magdalena A Machnicka1, Stanislaw Dunin-Horkawicz1, Valérie de Crécy-Lagard2

  • 1Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland.

Methods (San Diego, Calif.)
|March 27, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces tRNAmodpred, a computational tool for predicting chemical modifications on transfer RNA (tRNA) sequences. It identifies potential tRNA modification pathways across different organisms and experimental conditions.

Keywords:
BioinformaticsHomologyMODOMICSRNA modificationSequence similaritytRNA

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Transfer RNA (tRNA) molecules undergo extensive post-transcriptional modifications by various enzymes.
  • These chemical modifications are crucial for tRNA function and vary significantly across species and cellular compartments.
  • Understanding tRNA modification patterns is essential for deciphering gene expression regulation and cellular processes.

Purpose of the Study:

  • To develop a computational method for predicting tRNA modifications.
  • To identify potential tRNA modification pathways within a given proteome.
  • To enable prediction of tRNA modifications in newly sequenced genomes and heterologous expression systems.

Main Methods:

  • Input: Unmodified tRNA sequences and proteome data.
  • Identification of homologous tRNA modification enzymes within the proteome.
  • Prediction of tRNA modification activities and mapping onto the MODOMICS database.
  • Proposal of theoretical modification pathways and resulting modified tRNAs.

Main Results:

  • The tRNAmodpred method successfully predicts theoretically possible tRNA modification pathways.
  • It allows for the prediction of modification patterns for novel genomes.
  • The tool can assess the potential modifications of tRNAs from one species expressed in another.

Conclusions:

  • tRNAmodpred provides a valuable computational resource for tRNA modification prediction.
  • It facilitates research into tRNA biology, particularly in comparative genomics and synthetic biology.
  • The web server offers a freely accessible platform for researchers worldwide.