In the year 2000, the Human Genome Project released its draft human genome. 1 year later, it released its finalized version. The draft version was around 83% finalized, and finalizing (sequencing the “gaps” in the genome) seems not important. So how can we tell that finalizing the human genome is not just about adding the rest, but quality control?
Below is a dot-plot comparing the near-complete human genome’s chromosome 7 to its draft counterpart. This kind of graph is made by finding which gene sequences correspond to where on the other genome. In a dot plot comparing 2 perfectly identical genomes, a perfectly diagonal line should be shown to reflect that every consecutive nucleotide from the starting nucleotide 0 is perfectly identical. But as we can see below, a perfectly diagonal line is not shown. Lets analyze its issues.
The first odd thing you see is how there are several perpendicular lines to the overall line. Also, notice how these perpendicular lines seem to have an imaginary square box surrounding them that prevents the main diagonal line from touching its center. These perpendicular lines represent inversions in the DNA sequence. The draft sequence had several parts that were inverted compared to the near-finalized version. The diagonal lines that share the same slope as the main line, but are shifted, represent order disagreements between the draft and finalized versions.
What does this mean about the draft’s quality? It means that it is poor, and that for high-quality future research, finalizing the human genome was a good idea and yielded tangible improvements.
Dot plots against other animals
As we’ve seen earlier, dot plots can indicate a difference between two genomes. But what if we can use it to visualize changes caused by evolution between 2 species? Here is a dot plot I made comparing humans to chimpanzees. The image above shows how to identify changes.
Something interesting about chimpanzees is that they have 1 more chromosome than humans. Now, if the most recent common ancestor we have with chimpanzees also had 1 more chromosome than humans, where did the extra chromosome go? This dot plot actually has an answer. Notice the chimpanzee’s 12th and 13th chromosomes; it overlaps with the human’s 2nd chromosome. Our second chromosome contains homologous genetic material with a chimpanzee’s 12th and 13th chromosomes. That means that the 12th and 13th chromosomes fused into a 2nd human chromosome, explaining the presence of multiple chromosomal material within the second chromosome.
Looking at the overall graph, you can see some other transpositions and inversions (chr1), but the overall graph looks pretty linear, or similar. Let’s compare this graph to with other animals to get a qualitative estimate of humans’ relative similarity with other animals.
These 2 graphs I made with Chromeister (a very good, fast whole-genome dot-plot generation tool you should check out) are different from the first few graphs I’ve shown. The diagonal line comes from the top left and goes to the bottom right rather than how it was shown before. That is because the above are generated directly from Chromeister (looks uglier). The earlier graph shown before between chimpanzee and human was also generated from Chromeister, but I added necessary visualization postprocessing with matplotlib.
Anyway, you’ve seen earlier that the dot plot between humans and chimpanzees was basically entirely filled with lines. The more lines there are instead of gaps, the higher the number of genes conserved between the two species. Because inversions and transpositions (assumedly) do not change the gene’s contents, we can count all lines equally in representing the similarity of the species. Let’s quantify this qualitative comparison. The percent of the diagonal that can be covered with the sum of the length of all lines (diagonal, shifted, perpendicular…) I will call the qualitative percent similarity % (QPS%).
\frac{\text{length of diagonal line crossing the whole graph}}{\sum\text{length of all lines (diagonal, perpendicular, transposed)}}*100%=QPS%I won’t do any calculations involving QPS%, but I want you to have a feel for what I mean by more similar or less similar in comparing genomes with dot plots. The human versus chimpanzee dot plot probably has a QPS of >90%, the human versus mouse lemur probably has a QPS of <80%, and the human vs mouse probably has >40%. Mouse lemurs are related closely to humans and chimpanzees as hominids, so it is fair to make evolutionary comparisons between them. Chimpanzees > mouse lemurs in comparison of similarity to humans, visually it is obvious too.
There are flaws in this method, though, because it completely makes mice seem dissimilar to humans. Compared to mouse lemurs or chimpanzees, mice are equally, if not better, test subjects for medical trials on human drugs. Why? Mice are very dissimilar to humans according to these dot plots. Although chimpanzees and mouse lemurs share more DNA with humans, mice share quite a high amount of coding DNA (exons) that make it relevant for drug trials. Especially the exons that are relevant for genetic diseases and receptors. >90% of the exonic DNA is shared between humans and mice as orthologs (evolutionarily related genes) compared to a similar amount of around 99% or 98% for chimpanzees. However, mice have another benefit: they can reach maturing age significantly faster than chimpanzees or mouse lemurs. Although you can just find a mature hominid for a drug trial, if you want to study genetic diseases, it is important to cycle through generations in a matter of months.
Are humans more or less diverse than other hominids?
Who is more diverse? Humans or grey Mouse Lemurs? Visually, looking at the photos above, it is easy to assume that humans are more diverse than those grey Mouse lemurs.
I personally have never seen a distinct or unique hominid at all. As you probably know, the phenotype (exhibited traits) of a species is dependent on the genotype (gene content), so if a species has more unique-looking individuals, it is natural to assume that there is a great genotype diversity. Noticing how similar all monkeys look to each other, you will probably assume that monkeys are pretty homogeneous (non-diverse), especially compared to humans. Humans are probably psychologically perceived as one of the most heterogeneous, diverse species. In fact, in ancient times, other human races were perceived as different species.
But if you compare the dot-plot between 2 human individuals, and the dot-plot between 2 primate individuals of the same species. The humans look pretty homogeneous compared to other hominids. Here are some examples:
As you can see, 2 different humans compared to each other show a straight line. There is little to no diversity observed between these 2 individuals. But on the right figure, there is a comparison between 2 grey mouse lemurs. There is a shocking amount of diversity, and an abhorrent amount of inversions and transpositions. If this kind of diversity happened in humans, we would all have devastating genetic disorders. 2 monkeys that we may mistake as similar will surprisingly show more differences than 2 humans of different races. Dot plots statistically show that humans are less diverse than other primate species.
Concluding, we have seen many use-cases for dot-plots. We can use it to evaluate the improvements made on a genome, see changes in evolution, and as well as evaluate some obvious claims that may not turn out to be correct.
Dot-plots are an effective tool for comparing genomes, but there is now a shift towards making interactive, user-friendly graphical methods. If you go to NCBI to their Genomes page, you can quickly compare 2 genomes using a more intuitive interactive interface like this.
This image compares, on the top, the whole Lemur genome (separated lines signifying chromosomes); and on the bottom, the entirety of human chromosomes. Not only that, it shows inversions in the blue. Graphical representations of bioinformatic data have clearly improved from the first dot plots in the 2000s.