Measures of Compositional Strand Bias Related to Replication Machinery and its Applications

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

The compositional asymmetry of complementary bases in nucleotide sequences implies the existence of a mutational or selectional bias in the two strands of the DNA duplex, which is commonly shaped by strand-specific mechanisms in transcription or replication. Such strand bias in genomes, frequently visualized by GC skew graphs, is used for the computational prediction of transcription start sites and replication origins, as well as for comparative evolutionary genomics studies. The use of measures of compositional strand bias in order to quantify the degree of strand asymmetry is crucial, as it is the basis for determining the applicability of compositional analysis and comparing the strength of the mutational bias in different biological machineries in various species. Here, we review the measures of strand bias that have been proposed to date, including the ΔGC skew, the B 1 index, the predictability score of linear discriminant analysis for gene orientation, the signal-to-noise ratio of the oligonucleotide bias, and the GC skew index. These measures have been predominantly designed for and applied to the analysis of replication-related mutational processes in prokaryotes, but we also give research examples in eukaryotes.

Original languageEnglish
Pages (from-to)4-15
Number of pages12
JournalCurrent Genomics
Volume13
Issue number1
DOIs
Publication statusPublished - 2012 Mar

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Replication Origin
Transcription Initiation Site
Signal-To-Noise Ratio
Discriminant Analysis
Genomics
Eukaryota
Oligonucleotides
Genome
DNA
Research
Genes

Keywords

  • Bacterial replication
  • GC skew
  • Nucleotide composition bias
  • Replication-related mutations

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Measures of Compositional Strand Bias Related to Replication Machinery and its Applications. / Arakawa, Kazuharu; Tomita, Masaru.

In: Current Genomics, Vol. 13, No. 1, 03.2012, p. 4-15.

Research output: Contribution to journalArticle

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