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Genotyping Single Nucleotide Polymorphisms in the Mitochondrial Genome by Pyrosequencing
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Bioinformatic tools for tRNA gene analyses in mitochondrial DNA sequence data.

Elena V Romanova1, Yurij S Bukin1,2, Dmitry Yu Sherbakov1,2

  • 1Laboratory of Molecular Systematics, Limnological Institute, Irkutsk, Russian Federation.

Data in Brief
|March 7, 2020
PubMed
Summary

Researchers developed an R script to accurately identify transfer RNA (tRNA) genes in mitochondrial genomes, addressing challenges like gene duplication and mutation. This tool aids in precise annotation for evolutionary studies.

Keywords:
Genetic distanceMitochondrial genomesR scriptSequence alignmenttRNA genes

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Accurate transfer RNA (tRNA) gene annotation in mitochondrial (mt) and nuclear genomes is challenging due to prediction program limitations.
  • False positive/negative predictions and difficulties with duplicated or remolded tRNA genes (altered anticodon sequences) complicate annotation.

Purpose of the Study:

  • To develop an automated R script for diagnosing ancestral tRNA gene coding specificity, irrespective of anticodon sequence.
  • To present predicted tRNA genes from amphipod mt genomes.
  • To create an R script for estimating optimal sequence alignment modes for tRNA genes and phylogenetic inferences.

Main Methods:

  • Development of an R script utilizing genetic distance comparison to identify ancestral tRNA gene coding specificity.
  • Application of a second R script for estimating the best sequence alignment modes.
  • Analysis of mitochondrial genomes from amphipods.

Main Results:

  • An automated R script successfully diagnoses ancestral tRNA gene coding specificity.
  • Predicted tRNA genes from amphipod mt genomes are presented.
  • An R script for optimal sequence alignment estimation was developed and applied.

Conclusions:

  • The developed R scripts automate and improve the accuracy of tRNA gene annotation in mitochondrial genomes.
  • These tools are valuable for analyzing genetic data, particularly in evolutionary studies involving amphipods.
  • The methods are applicable to testing nucleotide alignment sets for phylogenetic inferences.