New Software Package Drives Deeper Understanding of Trait Evolution

NEW SOFTWARE — Rich Adams, assistant professor of agricultural statistics for the Arkansas Agricultural Experiment Station, developed a new software called TraitTrainR to simulate how organisms change over time. (U of A System Division of Agriculture photo)

MEDIA CONTACT

Maddie Johnson

U of A System Division of Agriculture
501-259-3247  |  mej048@uark.edu

​FAYETTEVILLE, Ark. — Evolution is complex and difficult to study, but a new software package developed by the Arkansas Agricultural Experiment Station offers researchers a better way to simulate how organisms change over time.

The new software, called TraitTrainR, builds on work in the field of comparative biology to provide an efficient and effective framework for replicating the evolutionary process many times over. An ultimate goal is to use this software to better understand the diversity of life forms on our planet.

Analyzing an organism’s traits, whether physical or molecular, and their changes, is at the heart of the study of biology, said Rich Adams, assistant professor of agricultural statistics for the Arkansas Agricultural Experiment Station. Understanding these changes is relevant to a number of disciplines, including biodiversity, environmental science, agriculture and biomedicine.

“The big picture is trying to understand how living organisms function and how they came to function in the way that they do,” Adams said.

“There’s a lot of invaluable models and software that comparative biologists have developed to mathematically describe what happens to organisms and their traits over time,” Adams said. “Previous work in the field has been instrumental in shaping modern evolutionary thought. So, we thought that we could improve our understanding of these models and processes by building an integrative software package that streamlines large-scale computer simulations under these models.”

Adams said TraitTrainR can perform a vast diversity of flexible evolutionary experiments through probabilistic simulations on a computer.

“Methods for trait simulation have been around a long time, and we thought to provide a new framework that unifies some of these approaches into a single platform,” he said.

Jenniffer Roa Lozano, a master’s student in the statistics and analytics program at the University of Arkansas, served as the lead author of the study introducing this software. Adams, who is part of the entomology and plant pathology department and the Center for Agricultural Data Analytics for the experiment station, the research arm of the University of Arkansas System Division of Agriculture, served as corresponding author and is Lozano’s adviser. Adams is also a teaching faculty member with the Dale Bumpers College of Agricultural, Food and Life Sciences.

Their study, “TraitTrainR: accelerating large-scale simulation under models of continuous trait evolution,” was published in Bioinformatics Advances in December 2024.

How it’s used

The software package could be used to address a host of compelling questions, Adams said, including the evolution of pathogen resistance, crop resistance and invasive species, to name just a few potential applications.

“If you think about it, there’s an almost limitless number and type of traits that you can study for a given system,” Adams said. “If you wanted to understand a certain trait, like the ability of insects to digest plant tissue, you can learn something new by comparing variation in this trait among related species.

“Through large-scale and well-organized simulation experiments, TraitTrainR allows us to generate many evolutionary scenarios for these species, which can then be used to compare with the observed trait,” he said. We can ask, ‘Given a set of parameters, what do we expect that trait to look like, and how different are our expectations from real data sampled from nature?’”

The package provides a bioinformatics pipeline for users and comes with a tutorial and implementations that can be used on standard computers. Lozano said the package is fast, with an organized code that is easy to understand. Inputs and outputs can be customized to fit a researcher’s desired focus.

“We envision a host of exciting applications in biology, agriculture, biomedicine, and beyond. The framework of TraitTrainR builds upon existing work, and is designed to open this door for fast, effective and efficient simulations for generating thousands-to-millions of evolutionary replicates,” Adams explained.

Replicates are multiple experimental simulations that use the same input settings. The ability to generate many replicates offers the opportunity to account for variability in the analyses.

“To understand a living being, we understand it by looking at its characteristics, which have been shaped over time, so this software helps us understand what we can expect to see given that information and maybe learn about why a living organism is living the way it is,” Lozano said.

The TrainTrainR software development team includes Mataya Duncan, left, Rokeya Akter, Rich Adams and Jenniffer Roa Lozano. (U of A System Division of Agriculture photo)

Co-authors of the study included Mataya Duncan, a graduate student in the cell and molecular biology program and with the Division of Agriculture’s Center for Agricultural Data Analytics; Duane D. McKenna with the University of Memphis; Todd A. Castoe with the University of Texas at Arlington; and Michael DeGiorgio with Florida Atlantic University.

The research was supported by the Arkansas Agricultural Experiment Station, the Arkansas High Performance Computing Center, the Arkansas Biosciences Institute and National Science Foundation grant no. IOS-2307044. Additional support came from National Institutes of Health grant no. R35GM128590 and National Science Foundation grant nos. DBI-2130666, DEB-2302258 and DEB-2110053.

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About the Division of Agriculture

The University of Arkansas System Division of Agriculture’s mission is to strengthen agriculture, communities, and families by connecting trusted research to the adoption of best practices. Through the Agricultural Experiment Station and the Cooperative Extension Service, the Division of Agriculture conducts research and extension work within the nation’s historic land grant education system.

The Division of Agriculture is one of 20 entities within the University of Arkansas System. It has offices in all 75 counties in Arkansas and faculty on three campuses.

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