80%, that’s how similar our protein-coding genes are to those of mice! Humans are larger, smarter,
and live longer than mice, not to mention the fact that humans don’t have fur or a tail!
The reason we have been able to calculate our similarity to mice is because of a massive
effort to sequence the genomes of humans, an undertaking called the Human Genome Project,
as well as from sequencing the genomes of mice and many other organisms.
Genome sequencing involves reading through the As, Ts, Gs, and Cs that make up our DNA,
and it has given us a lot of information about what our genes are, and how they are organized.
And, it has helped improve how we diagnose and even treat human disease. But genome sequencing
involves generating very large sets of data, so we need powerful tools to decipher all those ATGCs.
This is where the rapidly growing field of Bioinformatics comes in.
Extremely powerful computers are being used to store and manipulate all of this data. And the
people behind the computers are bioinformaticians, scientists who are often trained both in biology
as well as math or computer science. These multidisciplinary researchers develop methods
and software tools to program computers to dig through and make sense of all this data.
So, how did bioinformatics help us learn that humans and mice have 80% similarity in their
protein-coding genes? One way bioinformaticians approach this type of question is by looking for
small sequences in one genome that match the other genome: this is just like doing a word search on
your computer, but instead of searching for the word “Shakespeare” in your English term paper,
you scan for “ATTGCACGTCTA”. Once matching areas are found, researchers design algorithms that
can scan past the ends of both sequences to see just how far the matching regions extend.
So, in this case, do the letters after the “CTA” continue to match between the mouse and human
sequences? If they do not, and a difference is present, we can analyze the following sequence
and start to figure out which genes are involved many of the traits that make us humans different
from mice, like brain development and longevity. The flip side of this is that we can also find
sequences of the genome that are highly similar across different species – in addition to sharing
parts of our genome with mice, humans have genes in common with plants, flies,
and even microscopic bacteria. These regions are called “conserved genes,” and because they are
shared across many species, they likely code for proteins that are essential for life on Earth.
In addition to finding the similarities and differences between the genomes of two different
organisms, sequencing technology has also allowed us to pick up differences in DNA between different
people. This has been particularly important because it helps us better understand human
disease. Let’s say you knew a specific DNA base in a gene was different from person to person,
and you wanted to see if that difference was important for a disease like diabetes.
You could sequence that base in 50 people with diabetes and 50 healthy people—if 47
of 50 people with diabetes had an “A” while only 5 people out of 50 without diabetes did,
that would be strong evidence of association between that “A” variant and the disease (but,
importantly, it does not mean that variant causes disease!). Researchers have developed
technologies to look across hundreds of thousands of sites across the genome
for these kinds of single base differences and have looked for correlations between
certain bases and disease. These experiments are known as “Genome-wide Association Studies.”
Sequencing and bioinformatic analysis are also becoming increasingly important for the
diagnosis and treatment of cancer because cancer cells often have many mutations,
changes in the nucleotide code, compared to a patient’s normal cells.
As we learn more and more about the human genome and the cost of sequencing decreases, doctors can
order sequencing of parts of their patient’s genomes for a relatively low cost. By using
algorithms to compare a patient’s tumor cells to the normal genome, as well as to the tumors of
many other patients, doctors can quickly pinpoint the changes in the DNA that are causing the cancer
cells to grow uncontrollably. This helps them choose the best treatments for their patients.
As our ability to sequence genomes continues to increase, bioinformatics will need to
continue to develop faster and more advanced algorithms to handle these massive datasets.
An important part of this field has been the development of large, centralized databases
of genome sequences that can be accessed by anyone. The challenge for the future
will be to continue to grow these databases in a way that helps
scientists make important new discoveries, while preserving the privacy of patients.