Prediction of origin and terminus of replication in bacteria.
This program finds the putative origin and terminus of replication in procaryotic genomes. The program discriminates between codon positions.
oriloc(seq.fasta = system.file("sequences/ct.fasta.gz", package = "seqinr"),
g2.coord = system.file("sequences/ct.predict", package = "seqinr"),
glimmer.version = 3,
oldoriloc = FALSE, gbk = NULL, clean.tmp.files = TRUE, rot = 0)seq.fasta |
Character: the name of a file which contains the DNA sequence
of a bacterial chromosome in fasta format. The default value,
|
g2.coord |
Character: the name of file which contains the output of
glimmer program ( |
glimmer.version |
Numeric: glimmer version used, could be 2 or 3 |
oldoriloc |
Logical: to be set at TRUE to reproduce the (deprecated) outputs of previous (publication date: 2000) version of the oriloc program. |
gbk |
Character: the URL of a file in GenBank format. When provided
|
clean.tmp.files |
Logical: if TRUE temporary files generated when working with a GenBank file are removed. |
rot |
Integer, with zero default value, used to permute circurlarly the genome. |
The method builds on the fact that there are compositional asymmetries between the leading and the lagging strand for replication. The programs works only with third codon positions so as to increase the signal/noise ratio. To discriminate between codon positions, the program use as input either an annotated genbank file, either a fasta file and a glimmer2.0 (or glimmer3.0) output file.
A data.frame with seven columns: g2num for the CDS number in
the g2.coord file, start.kb for the start position of CDS
expressed in Kb (this is the position of the first occurence of a
nucleotide in a CDS regardless of its orientation), end.kb
for the last position of a CDS, CDS.excess for the DNA walk for
gene orientation (+1 for a CDS in the direct strand, -1 for a CDS in
the reverse strand) cummulated over genes, skew for the cummulated
composite skew in third codon positions, x for the cummulated
T - A skew in third codon position, y for the cummulated C - G
skew in third codon positions.
The method works only for genomes having a single origin of replication from which the replication is bidirectional. To detect the composition changes, a DNA-walk is performed. In a 2-dimensional DNA walk, a C in the sequence corresponds to the movement in the positive y-direction and G to a movement in the negative y-direction. T and A are mapped by analogous steps along the x-axis. When there is a strand asymmetry, this will form a trajectory that turns at the origin and terminus of replication. Each step is the sum of nucleotides in a gene in third codon positions. Then orthogonal regression is used to find a line through this trajectory. Each point in the trajectory will have a corresponding point on the line, and the coordinates of each are calculated. Thereafter, the distances from each of these points to the origin (of the plane), are calculated. These distances will represent a form of cumulative skew. This permets us to make a plot with the gene position (gene number, start or end position) on the x-axis and the cumulative skew (distance) at the y-axis. Depending on where the sequence starts, such a plot will display one or two peaks. Positive peak means origin, and negative means terminus. In the case of only one peak, the sequence starts at the origin or terminus site.
J.R. Lobry, A.C. Frank
More illustrated explanations to help understand oriloc outputs
are available there:
https://pbil.univ-lyon1.fr/software/Oriloc/howto.html.
Examples of oriloc outputs on real sequence data are there:
https://pbil.univ-lyon1.fr/software/Oriloc/index.html.
The original paper for oriloc:
Frank, A.C., Lobry, J.R. (2000) Oriloc: prediction of replication
boundaries in unannotated bacterial chromosomes. Bioinformatics,
16:566-567.
doi: 10.1093/bioinformatics/16.6.560
A simple informal introduction to DNA-walks:
Lobry, J.R. (1999) Genomic landscapes. Microbiology Today,
26:164-165.
https://seqinr.r-forge.r-project.org/MicrTod_1999_26_164.pdf
An early and somewhat historical application of DNA-walks:
Lobry, J.R. (1996) A simple vectorial representation of DNA sequences
for the detection of replication origins in bacteria. Biochimie,
78:323-326.
Glimmer, a very efficient open source software for the prediction of CDS from scratch
in prokaryotic genome, is decribed at http://ccb.jhu.edu/software/glimmer/index.shtml.
For a description of Glimmer 1.0 and 2.0 see:
Delcher, A.L., Harmon, D., Kasif, S., White, O., Salzberg, S.L. (1999)
Improved microbial gene identification with GLIMMER,
Nucleic Acids Research, 27:4636-4641.
Salzberg, S., Delcher, A., Kasif, S., White, O. (1998)
Microbial gene identification using interpolated Markov models,
Nucleic Acids Research, 26:544-548.
citation("seqinr")
## Not run:
#
# A little bit too long for routine checks because oriloc() is already
# called in draw.oriloc.Rd documentation file. Try example(draw.oriloc)
# instead, or copy/paste the following code:
#
out <- oriloc()
plot(out$st, out$sk, type = "l", xlab = "Map position in Kb",
ylab = "Cumulated composite skew",
main = expression(italic(Chlamydia~~trachomatis)~~complete~~genome))
#
# Example with a single GenBank file:
#
out2 <- oriloc(gbk="https://pbil.univ-lyon1.fr/datasets/seqinr/data/ct.gbk")
draw.oriloc(out2)
#
# (some warnings are generated because of join in features and a gene that
# wrap around the genome)
#
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.