R: Detection of replication-associated effects on base...

rearranged.oriloc {seqinr} | R Documentation

## Detection of replication-associated effects on base composition asymmetry in prokaryotic chromosomes.

### Description

Detection of replication-associated effects on base composition asymmetry in prokaryotic chromosomes.

### Usage

    rearranged.oriloc(seq.fasta = system.file("sequences/ct.fasta.gz", package = "seqinr"),
      g2.coord = system.file("sequences/ct.predict", package = "seqinr"))

### Arguments

`seq.fasta` | The path of the file containing a FASTA-format sequence. Default value: the FASTA sequence of the Chlamydia trachomatis chromosome.
`g2.coord` | The path of the file containing the coordinates of the protein coding genes found on this chromosome. This file can be obtained using the function `gbk2g2`. The format of the file is similar to the output of the Glimmer2 program. The first column contains the index or the name of the gene, the second one contains the start position and the third column contains the end position. For reverse transcribed genes, the start position is greater than the end position.

### Details

The purpose of this method is to decouple replication-related and coding sequence-related effects on base composition asymmetry. In order to do so, the analyzed chromosome is artificially rearranged to obtain a perfect gene orientation bias - all forward transcribed genes on the first half of the chromosome, and all reverse transcribed genes on the other half. This rearrangement conserves the relative order of genes within each of the two groups - both forward-encoded and reverse-encoded genes are placed on the rearranged chromosome in increasing order of their coordinates on the real chromosome. If the replication mechanism has a significant effect on base composition asymmetry, this should be seen as a change of slope in the nucleotide skews computed on the rearranged chromosome; the change of slope should take place at the origin or the terminus of replication. Use `extract.breakpoints` to detect the position of the changes in slope on the rearranged nucleotide skews.

### Value

A data.frame with six columns: `meancoord.rearr` contains the gene index on the rearranged chromosome; `gcskew.rearr` contains the normalized GC-skew ((G-C)/(G+C)) computed on the third codon positions of protein coding genes, still on the rearranged chromosome; `atskew.rearr` contains the normalized AT-skew ((A-T)/(A+T)) computed on the third codon positions of protein coding genes; `strand.rearr` contains the transcription strand of the gene (either "forward" or "reverse"); `order` contains the permutation that was used to obtain a perfect gene orientation bias; `meancoord.real` contains the mid-coordinate of the genes on the real chromosome (before the rearrangement).

### Author(s)

A. Necşulea

### References

Necşulea, A. and Lobry, J.R. (2007) A New Method for Assessing the Effect of Replication on DNA Base Composition Asymmetry. Molecular Biology and Evolution, 24:2169-2179.

### See Also

`oriloc`, `draw.rearranged.oriloc`, `extract.breakpoints`

### Examples

    ### Example for Chlamydia trachomatis ####

    ### Rearrange the chromosome and compute the nucleotide skews ###

    ## Not run: r.ori <- rearranged.oriloc(seq.fasta =
       system.file("sequences/ct.fasta.gz", package = "seqinr"),
        g2.coord =  system.file("sequences/ct.predict", package = "seqinr"))
    ## End(Not run)

    ### Extract the breakpoints for the rearranged nucleotide skews ###

    ## Not run: breaks <- extract.breakpoints(r.ori, type = c("gcfw", "gcrev"),
     nbreaks =c(2, 2), gridsize = 50, it.max = 100)
    ## End(Not run)

    ### Draw the rearranged nucleotide skews and place the position of the breakpoints ###
    ### on the graphics ###

    ## Not run: draw.rearranged.oriloc(r.ori, breaks.gcfw = breaks$gcfw$breaks,
     breaks.gcrev = breaks$gcrev$breaks)
    ## End(Not run)

[Package seqinr version 3.4-5 Index]