Mapping the evolutionary tree of life
By Wendy Sutton
Stephen Smith’s research on the evolutionary history of plants helps address some of today’s most urgent challenges, from understanding how species respond to climate change and informing conservation efforts to better understanding the evolution of infectious diseases and antibiotic resistance.
For Smith, associate chair of ecology and evolutionary biology, that work began with two childhood interests that seemed unrelated at the time. Hiking through the Appalachians with his father planted the seeds of a lifelong interest in plants and trees, while after-school experiments with an old computer and modem grew into a love of coding.
Eventually, the natural world and the computational one merged into a single career.
Today, Smith uses a computational approach to study the evolutionary history of plants and trees. The primary focus of his lab is to better understand how flowering plants have diversified over evolutionary time, specifically to explain why some lineages evolve quickly while others change very little over millions of years.
To achieve this, his team studies how processes like gene duplication, gene tree conflict and the rate of molecular evolution shape patterns across the tree of life. Gene tree conflict occurs when one gene from a plant or animal points to a close relationship with another species, while another gene from the same plant or animal points to a more distant relationship.
“One of the overarching questions for the lab is about the evolution of innovation, meaning how large changes in evolution occur,” Smith said. “One of the big unspoken secrets in biology is that we don’t actually understand how the big changes in evolution occur. Is it one big step at a single moment in time, or is it many small steps that accumulate?”
Read the full article in the Michigan Institute for Computational Discovery and Engineering Spring 2026 Magazine: https://micde.umich.edu/using-computational-modeling-to-construct-the-evolutionary-tree-of-life/
“It’s quite liberating that we do our own computational work in addition to our biological work, because we’re free to ask whatever question we would like. We are not limited by existing tools. Each set of results raises new biological questions, which drive us to develop new software to analyze new data. It’s an iterative approach, and that cycle is what fuels creativity in our lab.”
Smith’s work requires an intensive computational approach, given that there are approximately 350,000 species of flowering plants. To understand why some groups evolve more rapidly than others, his team requires a diverse data set, analyzing thousands of different species. The lab mines massive public databases while also generating its own large datasets. Because RNA cannot be sequenced from dead plants, Smith’s lab grows its own plants and then sequences them.
The impact of Smith’s work goes far beyond plants and trees. The methods developed in his lab are also applicable to the study of infectious diseases. His team applies these methods to analyze their molecular origins and evolution. Smith also collaborates with the University of Michigan Medical School to study the evolution of antibiotic resistance.
Smith’s work also helps inform conservation decisions. Understanding plant evolution and the relationships between species is critical to plant and tree management. By constructing large evolutionary “family trees” for plant species, conservationists can recognize which species are unique to a particular area. One of his current projects on North American plant life aims to determine how resilient various species are to changes in land use and shifting climate.
Because few researchers are investigating the questions Smith is asking at the same scale, he had to develop his own computational codes and programs. Essentially, the software and the science had to advance together.
Through computational modeling, Smith and his team determined that the longer a plant lineage’s lifespan, the slower its rates of molecular evolution tend to be. This may answer, at least in part, why some species evolve slowly and others more rapidly, suggesting that lifespan itself plays a key role in shaping evolutionary rates. Yet the research also unexpectedly demonstrated that the longer a species lives, the more gene conflict occurs.
His research also links rapid morphological change, meaning shifts in the physical appearance of plants, to gene tree conflict. For example, in branches of the phylogeny where major morphological innovations occurred, including the evolution of flowers or seeds, Smith observed both gene tree conflict and genome duplications.
Genome duplications occur when an organism inherits an extra copy of its entire genome. Over time, this duplicated genome can become fixed in the lineage. That extra genetic material serves as fuel for evolutionary innovation. It provides the raw material from which new traits can evolve. Researchers have found that these genome duplications often occur during periods of the greatest biological change in evolutionary history. Tracking those events is now helping Smith’s team identify precisely where to look to understand how major evolutionary leaps occurred.
Looking ahead, Smith’s lab is using AI to help gather data and is developing tools to identify and measure plant parts from museum and field images, extracting millions of measurements.
“It’s quite liberating that we do our own computational work in addition to our biological work, because we’re free to ask whatever question we would like,” Smith said. “We are not limited by existing tools. Each set of results raises new biological questions, which drive us to develop new software to analyze new data. It’s an iterative approach, and that cycle is what fuels creativity in our lab.”