Sequence dotplots in R

By: Avril Coghlan.

Adapted, edited and expanded: Nathan Brouwer under the Creative Commons 3.0 Attribution License (CC BY 3.0).

NOTE: I’ve added some new material that is rather terse and lacks explication.

Good sources of more info: https://omicstutorials.com/interpreting-dot-plot-bioinformatics-with-an-example/

http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/650/Examples_interpretations_dot_plots.html

As a first step in comparing two protein, RNA or DNA sequences, it is a good idea to make a dotplot. A dotplot is a graphical method that allows the comparison of two protein or DNA sequences and identify regions of close similarity between them. A dotplot is essentially a two-dimensional matrix (like a grid), which has the sequences of the proteins being compared along the vertical and horizontal axes.

In order to make a simple dotplot to represent the similarity between two sequences, individual cells in the matrix can be shaded black if residues are identical, so that matching sequence segments appear as runs of diagonal lines across the matrix. Identical proteins will have a line exactly on the main diagonal of the dotplot, that spans across the whole matrix.

For proteins that are not identical, but share regions of similarity, the dotplot will have shorter lines that may be on the main diagonal, or off the main diagonal of the matrix. In essence, a dotplot will reveal if there are any regions that are clearly very similar in two protein (or DNA) sequences.

Preliminaries

library(compbio4all)
library(rentrez)

Visualzing two identical sequences

To help build our intuition about dotplots we’ll first look at some artificial examples. First, we’ll see what happens when we make a dotplot comparing the alphabet versus itself. The build-in LETTERS object in R contains the alphabet from A to Z. This is a sequence with no repeats.

#LETTERS
seqinr::dotPlot(LETTERS, LETTERS)

What we get is a perfect diagonal line.

Visualizing repeats

The variable LETTERS.2.times is the alphabet (the LETTERS object) twice. Plotting this against itself reveals more than one diagonal.

LETTERS.2.times  <- c(LETTERS, LETTERS)

seqinr::dotPlot(LETTERS.2.times, 
                LETTERS.2.times)

The center line is the main diagonal or the line of identity for the complete ‘sequence’. The top line is the idenity line for the first 1-27 letters, the bottom for the second half. A simple way to think about it is where the ‘A’ would start: if LETTERS.2.times is across the horizontal axis and down the vertical axis, they will match at multiple spots –> (1,1), (1, 27), (27, 1), (27, 27), (27, 54), (54, 54). This would occur for each letter, which gives rise to the multiple diagonals.

This can be done with multiple repeating factors.

LETTERS.3.times <- c(LETTERS, LETTERS, LETTERS)

seqinr::dotPlot(LETTERS.3.times, LETTERS.3.times)

The rep() function repeats the sequence given as an argument by the amount of times designated. Here, we are repeating the sequence saved as seq.repeat three times.

seq.repeat <- c("A","C","D","E","F","G","H","I")

seq1 <- rep(seq.repeat, 3)

Make the dotplot:

seqinr::dotPlot(seq1, seq1)

Visualizing Inversions

Inversions in sequences occur as the reverse of what the given pattern is. In a mRNA sequence, for example, could have a pattern GAAC, and an inversion of CAAG. The test sequence here is the alphabet, the alphabet in reverse (as done by the rev() function), and the alphabet again.

“invert” means “inversion”

LETTERS.3.times.with.invert <- c(LETTERS, rev(LETTERS), LETTERS)

seqinr::dotPlot(LETTERS.3.times.with.invert, LETTERS.3.times.with.invert)

With inversion, the dotplot will have diagonals in both directions.

Visualizing Translocation

Translocation occurs when segments of a gene switch places. Modeled below are three sequences (exons) where seq2 and seq3 change places.

seg1 <- LETTERS[1:8]
seg2 <-  LETTERS[9:18]
seg3 <-  LETTERS[18:26]


LETTERS.with.transloc <-  c(seg1, seg3, seg2)

seqinr::dotPlot(LETTERS.with.transloc, LETTERS.with.transloc)

Visualizing Unrelated Sequences

The sample() function creates a randomized sample of the data given to it as a parameter. For example, below we are randomly creating a vector of 26 characters with replacement (meaning duplicate letters can occur).

sample(x = LETTERS, size = 26, replace = T)
##  [1] "Z" "O" "P" "R" "R" "N" "V" "W" "M" "G" "A" "H" "E" "N" "W" "G" "C" "X" "B"
## [20] "E" "K" "E" "X" "R" "Z" "Q"
letters.rand1 <- sample(x = LETTERS, size = 26, replace = F)
letters.rand2 <- sample(x = LETTERS, size = 26, replace = F)


seqinr::dotPlot(letters.rand1, 
               letters.rand2)

Download sequences

Now we’ll make a real dotplot of the chorismate lyase proteins from two closely related species, Mycobacterium leprae and Mycobacterium ulcerans.

Note - these are protein sequences so db = “protein”

TODO: briefly summarize these steps

# sequence 1: Q9CD83
leprae_fasta <- rentrez::entrez_fetch(db = "protein",
                        id = "Q9CD83",
                         rettype = "fasta")
# sequence 2: OIN17619.1
ulcerans_fasta <- rentrez::entrez_fetch(db ="protein", 
                         id = "OIN17619.1",
                         rettype = "fasta")

# add code
leprae_vector   <- compbio4all::fasta_cleaner(leprae_fasta) 
ulcerans_vector <- compbio4all::fasta_cleaner(ulcerans_fasta)

Creating the DotPlot

We can create a dotplot for two sequences using the dotPlot() function in the seqinr package.

First, let’s look at a dotplot created using only a single sequence. This is frequently done to investigate a sequence for the presence of repeats.

(Note - and older version of this exercise stated this kind of anlysis wasn’t normally done; this was written last year before I knew of the use of dotplots for investigating sequence repeats.)

seqinr::dotPlot(leprae_vector, ulcerans_vector, main = "Leprae vs Ulcerans")

In the dotplot above, the M. leprae sequence is plotted along the x-axis (horizontal axis), and the M. ulcerans sequence is plotted along the y-axis (vertical axis). The dotplot displays a dot at points where there is an identical amino acid in the two sequences.

For example, if amino acid 53 in the M. leprae sequence is the same amino acid (eg. “W”) as amino acid 70 in the M. ulcerans sequence, then the dotplot will show a dot the position in the plot where x =50 and y =53.

In this case you can see a lot of dots along a diagonal line, which indicates that the two protein sequences contain many identical amino acids at the same (or very similar) positions along their lengths. This is what you would expect, because we know that these two proteins are homologs (related proteins) because they share a close evolutionary history.