In conversation with Romy Petroll

Romy Petroll is a PhD student in the Borg group at the Max Planck Institute for Biology in Tübingen, Germany, where she studies genome evolution in red algae. Raised in Wiesbaden alongside her twin sister, she traces her early interest in biology to a high school teacher whose own background in plant research offered a first glimpse into academic science. Petroll later studied biology at the University of Mainz, followed by a master's degree in bioinformatics at the Universities of Gießen and Marburg, where she began working on transcription-associated protein (TAP) annotation and evolutionary genomics. 1. Can you tell us about yourself, your childhood, or anything that you're comfortable sharing? I am a PhD student in the Borg group in the Department of Algal Development and Evolution at the Max Planck Institute for Biology in Tübingen, Germany, where I study genome evolution in the fascinating red algal lineage. I grew up in Wiesbaden, Germany, and had a happy childhood alongside my twin sister. Outside the lab, I enjoy swimming and reading. 2. What is your educational background, and how did you become interested in plant biology? I first became interested in plant biology during high school, where my biology teacher played an important role in shaping my curiosity for science. She had completed a PhD in forest plant biology before becoming a teacher, and her perspective on academic research strongly influenced my decision to pursue a scientific career. I completed my bachelor's degree in biology at the University of Mainz. A course on the evolution of photosynthetic organisms introduced me to the remarkable diversity of algae and sparked my interest in algal evolution. During my bachelor's studies, I worked under the guidance of Dr. Martin Lohr on pigment evolution, focusing on phylogenetic analyses of a carotene isomerase across diverse algal lineages. I then completed a master's degree in bioinformatics at the Universities of Gießen and Marburg. During this time, I joined the lab of Prof. Dr. Stefan A. Rensing, where I worked on the annotation of TAPs using TAPscan and investigated the evolution of transcriptional regulation in red algae in relation to increasing morphological complexity, as well as in the green lineage in the context of plant terrestrialization. Now, under the supervision of Dr. Michael Borg, I am focusing on red algal genome evolution for my PhD. 3. What inspired you to pursue plant evolutionary genomics, and how did your academic path lead you to develop TAPscan v4? My interest in plant evolutionary genomics grew out of a fascination with algae, which have diverse and complex evolutionary histories. Streptophyte algae, in particular, are central to understanding land plant evolution. As the closest algal relatives of land plants, they offer an excellent system for studying the molecular innovations associated with the transition to life on land. During my master's studies, I became especially interested in combining evolutionary questions with computational approaches. This led me to develop TAPscan v4 as part of my master's project to study TAPs. I implemented a new version of the software and used it to analyze TAPs across streptophyte algae in order to better define the regulatory repertoire of the earliest land plants. 4. Can you share a defining moment or mentor that shaped your approach to computational biology? During my bachelor's project, I first experienced how computational observations can guide wet-lab work. My supervisor, Dr. Martin Lohr, introduced me to fundamental bioinformatic and phylogenetic methods, including BLAST searches, sequence alignment, and phylogenetic tree construction. At that time, my phylogenetic analyses revealed a conserved cluster of a specific isoform of a carotene isomerase in algae, suggesting a particular role in early carotenoid biosynthesis. This prediction was later confirmed experimentally in the lab. From then, my work has shifted toward genome-wide analyses. I now explore large genomic and transcriptomic datasets to study genome organization, using computational biology as a tool to investigate genome evolution. 5. What gaps in transcription factor annotation tools did TAPscan v4 address most critically? TAPscan v4 is a comprehensive tool for genome-wide TAP annotation based on domain profiles, with a particular focus on plants. One major challenge in TAP annotation is limited sensitivity and taxonomic bias. Many domain profiles are derived primarily from animal and seed plant model organisms and therefore perform poorly when applied to algae and non-seed plants. Earlier updates of TAPscan addressed this issue by expanding domain profiles to include sequences from brown, red, and streptophyte algae, allowing more sensitive and complete TAP annotation across these groups. TAPscan v4 further expands the framework by adding and updating several TAP families and improving subfamily resolution. In addition to the standalone tool, the updated web interface now provides access to genome-wide TAP annotations for 138 TAP families across 678 species. This significantly expands the taxonomic coverage previously available for TAP annotation resources. 6. How do you expect TAPscan v4 to influence comparative genomics research across non-model plants and algal relatives? Because TAPs perform diverse functions across species, TAPscan annotations support many types of downstream analyses. TAPscan v4 enables more specific and sensitive annotation of TAP complements in non-model plants and algae, making these datasets easier to explore in depth. These annotations can be integrated into comparative genomic studies that examine gene regulation, protein domain evolution, or the functional diversification of particular TAP families. By enabling TAP annotation across a wider range of organisms, TAPscan v4 broadens evolutionary analyses beyond well-studied land plant model systems to include the wider diversity of the green lineage as well as red and brown algae. 7. In what ways might improved TF family detection change our understanding of plant morphological evolution? Evidence from both the green lineage and animals suggests that the complexity of gene regulatory networks is linked to morphological complexity, often reflected in the number of distinct cell types an organism possesses. Improved detection of transcription factor families, combined with broader taxonomic sampling, allows researchers to trace when particular TF families emerged or expanded during evolution. Using TAPscan v4, we found that the TAP family complement of multicellular red algae correlates with the emergence of greater morphological complexity. In particular, the expansion of C2H2 zinc finger transcription factors may be associated with the evolution of more complex body plans in red algae. 8. Were there any surprising evolutionary patterns you uncovered with TAPscan v4 across streptophytes? Previous studies suggested a gradual increase in TAP family diversity across the green lineage. Using TAPscan v4, we confirmed that streptophyte algae generally contain more TAPs than other algal groups, with a further increase observed in embryophytes. Interestingly, more than one-third of all detected TAP family gains across the phylogeny occurred within streptophyte algae, before the transition from water to land. With the expanded TAP family definitions introduced in TAPscan v4, nine additional families could be traced back to the streptophyte ancestor or to early streptophyte algae. These observations indicate a diversified repertoire of TAPs that provided a rich substrate for evolutionary innovation and were likely important for enabling terrestrialization. 9. What future expansions or integrations do you envision for TAPscan? As new genome sequences continue to become available, we plan to expand the TAPscan dataset by incorporating newly sequenced species and updating annotations as improved genome assemblies are released. We also aim to refine TAP family and subfamily classifications as new standards and references emerge. For many TAP families, TAPscan already provides gene trees through the web interface. One goal is to extend this feature to all TAP families to facilitate evolutionary analysis. We also plan to strengthen connections with external resources by linking TAP family entries to other databases, including available three-dimensional protein models. Since the release of TAPscan v4, a standalone version of the tool has also been made available, allowing users to analyze their own datasets, including pangenome resources. With appropriate adjustments to the underlying domain profiles and classification rules, TAPscan may eventually be applied to protein classification tasks beyond TAPs. 10. How would you advise experimental biologists to integrate TAPscan v4 outputs into functional studies? I would recommend using TAPscan outputs as a starting point for identifying candidate TAPs for functional studies. The outputs provide family and subfamily classifications as well as domain structures, which help place proteins into a functional context. By combining these annotations with other types of data, such as gene expression profiles, experimental biologists can prioritize candidate genes that are most relevant to their species or experimental system. This approach can help guide targeted functional analyses.