Assistant Professor of Biology
Jenn Brisson is an evolutionary biologist who studies the morphology of pea aphids. With more than 4,500 species of aphids in the world, many people think of them as pests. But Brisson looks at them differently—and data science helps inform her view of them.
For Brisson, aphids are a source through which she can try to answer some big evolutionary questions. They are ideal research subjects that have some remarkably human qualities. For instance, they have live births. Brisson looks at identical aphids, twins per se, that have the same exact genetic makeup yet one has wings and the other doesn’t. They key to their differences is the environment in which their mother was raised: mothers exposed to high aphid densities produce winged daughters and low density females produce wingless daughters. The big question she is trying to answer is, how does the genome integrate information from the environment to produce different outcomes?
Brisson is researching how the environment causes different gene expression profiles in the genome. These different gene expression profiles do or do not prompt the manifestation of wings. Today, much remains to be learned about how the environment influences the genome. Some evidence exists that in early development there are cues that can cause some DNA to change its structure from a closed state to an open one and stay that way for the rest of a lifetime. Brisson is asking questions to find out.
Her research involves raising hundreds to thousands of aphids in her lab. She creates control and test groups and then exposes them to different environmental cues. It takes data science approaches to help her find ideal candidates in the genome to examine, after which she conducts meticulous tasks to test hypotheses. “It’s immensely helpful to have established computational infrastructures in place,” Brisson says. “It saves me time and helps me sort through, analyze, and make sense of information.”
When she was a PhD student 10 years ago, there weren’t many data analysis options. Back then, evolutionary biologists had to have strong computer science skills just to handle the data. Today, data science helps solve some of her day-to-day questions. For instance, it helps her make the best choices for data integration, analysis, storage, and archiving. Without data science, it would be very difficult for her to profile the 35,000 genes in a pea aphid and determine the next steps.
“Data science is very important for hypothesis generation, after which we can go in and use more traditional biological tools to explore our questions,” she adds. “The University’s data science initiative will help advance the development of basic tools and will also create an umbrella under which areas can coalesce more efficiently. The opportunity for collaboration is a very exciting part of an initiative like this.”
“Although I can make this connection between what I study and human health, I really consider my work as basic research that is informed by advances in technology,” says Brisson. “There are whole fields of applied sciences, such as engineering, and then there are the other sciences, for example in biology, that don’t have an end goal in mind when it comes to an application. And that’s okay—this is what science is based on.”
“If you study, for instance, the biological underpinnings of a genetic question such as the one I look at, eventually something will be discovered that will make a huge difference in our understanding,” says Brisson.
Jenn Brisson is an evolutionary biologist who uses data science to generate and test hypotheses and to make the best choices for integrating, analyzing, storing, and archiving her research.