Molloy Receives NSF CAREER Award to Advance Evolutionary Biology with Novel Computational Tools

A University of Maryland computer scientist has been awarded funding from the National Science Foundation (NSF) to develop innovative computational tools that advance the emerging field of retrophylogenomics, which uses “copy-and-paste” DNA sequences called retrotransposons to better understand how species are related and how they have evolved over time.

Erin Molloy, an assistant professor of computer science with an appointment in the University of Maryland Institute for Advanced Computer Studies, is principal investigator on the NSF Faculty Early Career Development Program (CAREER) award, totaling almost $600,000 over the next five years.

This highly competitive award—one of NSF’s most prestigious funding mechanisms for early-career faculty—recognizes researchers with the potential to serve as academic role models in both research and education and to lead transformative advances in their fields.

Molloy’s research aims to unravel the complexities of retrotransposons—mobile DNA elements that copy-paste themselves around the genome. Retrotransposons can significantly shape genome structure, and the specific ways they appear or seemingly disappear across species serve as powerful markers for tracing evolutionary history. Although these sequences are abundant in vertebrate genomes, their repetitive and dynamic nature has made them historically difficult to analyze at a genome-wide scale. 

To address this, Molloy is developing biologically accurate models for retrotransposon evolution, along with scalable open-source software tools that can automatically identify retrotransposon variants and infer evolutionary relationships.

“This project is about unlocking the potential of retrotransposons to study species and genome evolution,” says Molloy, who is also a member of the Center for Bioinformatics and Computational Biology. “This goal is within reach, thanks to major advancements in DNA sequencing technologies and genome assembly from just the last few years. By developing scalable computational tools grounded in realistic models, we aim to make these markers accessible to the broader scientific community and shed light on parts of evolutionary history that have remained unresolved despite significant efforts.”

Click HERE to read the full article