Professor of Computer Science
Focused on Codes
A tomato looks very similar to a human being. Or it looks nothing like a human at all. It’s simply a matter of perspective.
At the visible level, of course, nobody is going to mistake a ripe, red tomato with anyone. But when everything is reduced to the genetic level, the situation changes dramatically. The same basic genetic principles apply. Understanding how genes interact with one another can help researchers whether they’re studying flies, mosquitoes, vegetables, or human beings.
Matthew Hahn, a professor of informatics and biology at IU, is among of group of researchers at Indiana who are studying the evolution of genomes. By identifying the genetic code of DNA through the letters A, C, T, and G, Hahn and his colleagues can investigate how different combinations of genes interact with one another and the impact the combinations have on an organism.
“At some level it’s just a string of A, C, G and T,” Hahn says. “It doesn’t seem that interesting, but understanding the genetic basis and the genetic changes that control the interesting genotypes you see – hair or no hair, wings or no wings – is much more tractable, so there’s some ease in getting into it. It’s a puzzle, and it’s much easier to feed all of that into a computer than to feed ‘this is what this organism looks like.’”
Hahn deals with vast amounts of data in his work, and he couldn’t confidently pursue his research without bioinformatics.
“We want to understand why the genomes of two individuals in a species, say two humans, differ,” Hahn says. “Why the genome of humans differs from the genomes of chimps. We apply all of these methods to new. It’s called Next Generation Sequencing, which will make the next generation of DNA sequencing super easy and super cheap, but it produces tons of data that you cannot analyze without a computer. It would be impossible to do.”
Multiple organisms are studied for various reasons. Mosquitoes and flies are easier to study because their lifespans are much shorter, allowing researchers to manipulate them in the lab.
Hahn says although the work with non-mammalian organisms might not be flashy, it’s a critical part of genomic research.
“What you quickly learn is that everyone is more interested in the human part, even though you might scientifically be able to make more headway with the others,” Hahn says. “At some level, you know what to lead with when you start those conversations.
There’s a lot of work to be done to fully understand genetics and how genes interact with one another. Through bioinformatics and solid bench-based biology done by collaborators, Hahn and his colleagues hope to help humans better understand the genetic basis of disease.
“One of the specific things we study is how genes are gained and lost,” Hahn says. “People don’t realize that any two humans actually have slightly different sets of genes. Some people have extra genes. Genes get copied, but some people lose genes. Sometimes it’s not harmful, but sometimes it results in a disease. All those differences get magnified when you start to compare different species. It’s not just individual bases that change but whole genes get multiplied or deleted between species.”
Hahn also uses computer models to study the evolution of genes, and thanks to the data that can be collected through physical studies, he can accurately predict how changes in DNA can impact an entire organism.
“I think the big goal is to understand the rules that relate changes in genes to changes in phenotypes,” Hahn says. “How things look and how they behave, you want some idea of… if I see lots of changes in the letters (on a computer), that relates to changes I see in nature. That’s the underlying goal. That’s a pretty broad goal, and there’s not a small set of rules. But that’s the large goal of the whole field.”