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 of 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) # add code

What we get is a perfect diagonal line.

Visualizing repeats

A string with the entirety of LETTERS twice is made. When a dotplot is created, there is off-diagonals to show that the string appears twice.

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

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

A string with the entirety of LETTERS thrice is made. When a dotplot is created, there is off-diagonals to show that the string appears thrice

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

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

A string is created and the rep() funciton is used to copy it three times, so when the dotplot is made, you can see that it appears 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

When a string and its reverse (created by rev()) are made into a string, an inversion can be seen

“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)

Visualizing Translocations

When translocations occur, an element that was already there may be repeated, creating a bigger box in the dotplot.

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


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

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

Visualizing Random Sequences

When two random sequences are made into a dotplot, it will look scattered.

sample(x = LETTERS, size = 26, replace = T)
##  [1] "L" "N" "K" "J" "Y" "M" "R" "Z" "F" "W" "D" "W" "N" "C" "L" "W" "E" "Z" "Q"
## [20] "W" "C" "A" "M" "T" "T" "P"
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”

Each sequence is downloaded using rentrez::entrez_fetch and then cleaned and converted to a vector using compbio4all::fasta_cleaner

# 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 a dotplot for 2 FASTA files

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)

There is a lot of dots along the diagonal indicating similarity.

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.