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

We are assigning a name to a vector with this code. We assigned the name LETTERS.2.times to a vector that contains the object LETTERS twice. We then make a dotplot of it with itself and see three different diagonals (we see three because the middle diagonal represents the dientical object, and the two flanking the middle one represents the similar regions)

LETTERS.2.times  <- c(LETTERS, LETTERS)# add code

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

We are doing the same thing as above, but repeating the LETTERS object three times now and observing the dotplot.

LETTERS.3.times<- c(LETTERS, LETTERS, LETTERS)# add code

seqinr::dotPlot (LETTERS.3.times, LETTERS.3.times)# add code

This repeats the seq.repeat object three times, instead of making the vector of three repeating object how we did above.

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

seq1<- rep(seq.repeat, 3)
# add code

Make the dotplot:

seqinr::dotPlot(seq1, seq1)# add code

Dotplot with inversions of sequences

This shows us a dotplot with the LETTERS object and the LETTERS object inverted. the function rec(LETTERS) inverts LETTERS for us.

“invert” means “inversion”

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

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

Dotplot with translocated sequences

This shows us a dotplot with the LETTERS object and with some elements of the LETTERS object translocated.

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


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

seqinr::dotPlot(LETTERS.with.transloc, LETTERS.with.transloc)  # add code

Dotplot of random sequences

We are making a random sequence here and making a dotplot with two random sequences. Replace= T means that replacement is true, so can have repeats of the same letter but can still have 26 elements. For the dotplot, we do replace=F (for false).

sample(x = LETTERS, size = 26, replace = T)
##  [1] "H" "M" "S" "X" "R" "E" "Y" "D" "V" "H" "I" "F" "R" "L" "R" "J" "H" "E" "G"
## [20] "M" "X" "B" "P" "T" "Q" "V"
letters.rand1 <- sample(x = LETTERS, size = 26, replace = F)# add code
letters.rand2 <- sample(x = LETTERS, size = 26, replace = F)# add code


seqinr::dotPlot(letters.rand1, letters.rand2
                )# add code

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”

Here we are retrieving the FASTA file from entrez on NCBI wth entrez_fetch and cleaning them by getting rid of the new character lines with fasta_cleaner.

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

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

Dotplot of leprae and ulcerans

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)# add code

The plot shows a faint diagonal going from bottom left to top right, but the rest is sort of random.

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.