Many of the world’s most important crops contain extraordinarily complex genomes, created through repeated rounds of whole-genome duplication and hybridization. These polyploid genomes contain multiple sets of chromosomes inherited from different ancestral species. However, determining exactly how these genomes are assembled can be very difficult, especially when the original ancestral species is extinct or unknown.
A new study offers a genome-wide approach to untangling these complex genetic histories. This method takes advantage of evolutionary signatures left by long retroviral vectors, a type of mobile DNA sequence. By comparing patterns of similarity between these elements across chromosomes, researchers can identify distinct subgenomes and estimate when major genome fusion events occur. When applied to cultivated octaploid strawberries, this technique revealed a step-by-step evolutionary history shaped by multiple rounds of polyploidy, providing new insight into how complex plant genomes form and diversify over millions of years.
Why are polyploid genomes so difficult to decipher?
Whole-genome duplication has played a major role in plant evolution, helping to drive innovation, adaptation, and the emergence of many crop species. In polyploid plants, chromosome sets originate from different ancestral genomes. These chromosome sets, known as subgenomes, continue to evolve and interact long after the original hybridization events.
Identifying those subgenomes is crucial to understanding how species evolve. Traditional approaches often rely on comparing polyploid genomes with known diploid ancestors. The problem is that many ancestral species are either extinct or not yet recognized.
Movable items provide another source of information. Long retrotransposons accumulate in distinct patterns within specific evolutionary lineages, preserving molecular evidence of past events. Although scientists have long recognized their potential value, reliable methods for converting these patterns into accurate subgenome mappings have remained limited. As a result, new tools are needed to reconstruct the evolution of polyploid genomes without relying on known ancestral species.
A new method reconstructs genome history
Researchers from the USDA and collaborating institutions describe such a tool in the journal Horticulture research. The team has developed a bioinformatics framework capable of reconstructing the evolutionary history of complex polyploid genomes.
To illustrate this method, they re-examined the cultivated octaploid strawberry (Fragaria × ananassa). Using a sequence similarity matrix built from long retroviral vectors, the researchers elucidated the structure of strawberry subgenomes and discovered several ancient genome fusion events that contributed to modern species. The findings help resolve long-standing questions about the evolutionary origins of strawberries.
This framework follows genome evolution through three broad stages: before ancestral species diverged, during their separate evolutionary histories, and after their genomes merged. Retrovectors that expanded during the divergence period retain unique signatures of specific subgenomes.
By calculating similarity matrices of these elements across chromosomes and examining how they cluster at different similarity thresholds, the researchers created what they call a “sequence similarity matrix.” This approach captures evolutionary signals that have accumulated over different time periods.
Testing the approach in crops
Before applying this technique to strawberries, the team tested it in well-studied polyploid crops, including teff and cotton. In both cases, the method was successful in distinguishing between known subgenomes and discrete events that occurred before and after polyploidy.
The researchers also evaluated the approach using artificial polyploid genomes. These tests confirmed that the method is sensitive to both divergence times and the abundance of transposable elements.
What the strawberry genome revealed
When this method was applied to diploid strawberries, it identified four distinct subgenomes and revealed evidence for three successive events of polyploidy that occurred approximately 3.1 to 4.2 million years ago, 1.9 to 3.1 million years ago, and 0.8 to 1.9 million years ago.
The results support close evolutionary relationships between the two strawberry subgenomes and the species Fragaria Visca and Fragaria enomai. At the same time, the results challenge previous models that suggested additional diploid ancestral species.
According to the analysis, some contributors to the strawberry genome may have become extinct or never been sampled, underscoring the complexity of polyploid genome evolution.
“This work demonstrates how transposable elements can serve as evolutionary time stamps embedded in plant genomes,” said one of the study’s senior authors. “By focusing on when and where these elements expanded, we can reconstruct genome history even when direct ancestral references are missing. This method provides a powerful new lens for studying polyploid crops and moves beyond reliance on incomplete ancestry data, providing a more objective and reproducible framework for evolutionary genomics.”
Implications for crop research and breeding
Potential applications extend beyond strawberries. Many economically important crops, including wheat, cotton, and sugarcane, are polyploid and have a similarly complex evolutionary history.
More precise identification of subgenomes can improve gene annotation, trait mapping and comparative genomic studies. These developments can, in turn, support precision breeding efforts and help accelerate crop improvement.
By making it possible to reconstruct the evolution of genomes without known ancestors, the sequence similarity matrix approach adds a valuable new tool for studying biodiversity, phylogeny, and adaptation. The framework may also be useful in the study of other complex polyploid organisms, helping to link evolutionary biology with practical agricultural research.
This work was supported by National Institute of Food and Agriculture (NIFA)-Specialty Crop Research Initiative (SCRI) Grant 2022-51181-38241 to Q.Y.
