Earl Grey ParTEA: scalable, consistent transposable element annotation from pangenomes to deep phylogenetic scopes

The human genome, and indeed the genome of almost any living thing, is not a static library of instructions but a dynamic landscape constantly reshaped by its own internal inhabitants. Among the most active of these inhabitants are transposable elements, often called "jumping genes." These are stretches of DNA that can copy themselves and insert into new locations within a genome, much like a book that can photocopy its own pages and paste them into different chapters. While many of these insertions are harmless or even beneficial, others can disrupt genes or alter how the genome functions. Because these elements move and multiply, they are a major source of genetic variation, driving evolution and sometimes causing disease. To understand how species adapt, how they diverge, or how their genomes are built, scientists must be able to map these jumping genes accurately. However, doing so has been a difficult task, especially when trying to compare many different genomes at once.

Traditionally, researchers have analyzed these genetic travelers one genome at a time. They would build a catalog of jumping genes for a single reference organism and use that list to find similar elements in other individuals. This approach has a critical flaw: if a jumping gene family is missing from the reference catalog, it will be missed entirely in the new samples. Conversely, if researchers build a separate catalog for every single genome they study, the results become messy. The same family of jumping genes might be given different names in different catalogs, making it impossible to tell if two organisms share a common genetic history or if they have evolved their own unique versions. This creates a blind spot in our understanding of how genetic diversity spreads across species and populations.

To solve this problem, Tobias Baril, Alice Feurtey, and Daniel Croll have developed a new automated tool called Earl Grey ParTEA. Think of it as a master librarian who does not just catalog books from a single library, but gathers every book from a thousand different libraries first, merges them into one giant, non-redundant collection, and then uses that single, complete collection to re-catalog every library again. This pipeline is designed to handle large groups of genomes simultaneously, whether they are ten different individuals of the same plant species, ten different species of fruit flies, or ten species of fungi from across the entire kingdom. By constructing a single, shared library of jumping genes from all the input genomes at once, the tool ensures that every genome is annotated with the same consistent set of names and definitions. This allows scientists to directly compare how many jumping genes each organism has, which ones they share, and which ones are unique to them.

The researchers tested this new system on three very different scales of life to see how well it worked. First, they looked at ten different accessions of the model plant Arabidopsis thaliana. Even within this single species, which is very closely related, the tool revealed that a single reference genome was not enough to capture the full picture. As they added more plant genomes to the analysis, the number of identified jumping gene families grew significantly, reaching a total of 1,357 distinct families. The analysis showed that while most of these families were shared across all the plants, a small number were unique to specific individuals. This suggests that even within a single species, the genetic landscape is more diverse and dynamic than previously thought, with some individuals carrying unique genetic baggage that others lack.

Next, the team applied the tool to ten different species of fruit flies, a group that is more distantly related than the plants. Here, the power of the new method became even more apparent. A standard, pre-existing library of fruit fly jumping genes contained only 343 families. However, by using ParTEA to build a new library from all ten species combined, the number of identified families exploded to 1,852. This massive increase revealed that a significant amount of genetic diversity was being missed by older methods. One striking discovery was a specific type of jumping gene, known as a rolling circle element, which was found in very low numbers in most of the fly species but had exploded into over 6,000 copies in one specific species, Drosophila miranda. Without the new tool's ability to look at all the genomes together, this massive expansion would have remained hidden, as it was not present in the standard reference libraries used for fruit flies.

Finally, the researchers pushed the tool to its limits by analyzing ten species of fungi from across the entire fungal kingdom, representing a vast evolutionary distance. In this deep comparison, the results were quite different. Because these species are so far apart in their evolutionary history, their jumping genes had diverged so much that almost none of them were shared. The tool identified nearly 2,800 families, but the vast majority were unique to a single genome, with only a tiny fraction shared across all ten species. This confirmed that over long periods of time, the genetic "families" of jumping genes turn over completely, with old ones dying out and new ones emerging. The tool also highlighted that the quality of the genome data matters; for some fungi with very small or fragmented genomes, the analysis was more difficult, but the pipeline still managed to organize the data and provide a clear picture of the differences in genetic content.

Beyond just counting and naming these elements, the tool provides a way to visualize the history of their activity. It can show whether a species is currently experiencing a burst of new jumping gene insertions or if its genome is dominated by older, inactive copies. In the fruit fly and fungal examples, the researchers could see that some species were actively accumulating new copies of specific genes, while others showed signs of ancient activity that had long since slowed down. This kind of detailed comparison helps scientists understand not just what genetic material is present, but how it has changed over time and how it might be influencing the evolution of the species.

The significance of this work lies in its ability to standardize how we look at genetic diversity. By moving away from single-genome snapshots and toward a unified, comparative approach, the tool reveals a much richer and more accurate picture of the living world. It shows that the genetic diversity within a species is often deeper than expected, and that the differences between species can be profound. The researchers have made this tool available to the scientific community, allowing others to apply the same rigorous, consistent methods to their own studies. This paves the way for a new era of genomic research where the complex, shifting landscape of jumping genes can be mapped with clarity, helping to unlock the secrets of how life evolves and adapts.