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Our research is dedicated to understanding the functional and evolutionary roles of transposable elements (TEs). To achieve a comprehensive understanding of these prevalent genetic contents, we are engaged in the following research topics:
1. Characterizing TE's Activities in Responded to Stresses
1. Characterizing TE's Activities in Responded to Stresses
When plants are stressed, TEs tend to be more active. We wonder what TEs are doing during these stressful times. Are they Jokers, exacerbating or exploiting the chaos, or Batmans, working to alleviate the stress? Utilizing model plant species like maize and rice, we combine long-read sequencing and experimental approaches to answer these questions. Currently, we study heat and cold stresses.
2. Understanding Local Adaptation and Speciation through TEs
2. Understanding Local Adaptation and Speciation through TEs
TEs are potent mutagens that constantly introduce kb-level mutations to the host genome, including within and nearby genes. We study TE's adaptative effects regarding their functional consequences using comparative genomic approaches and simulations. Over evolutionary time scales, TEs have left countless footprints on host genomes and faithfully recorded significant evolutionary events, such as divergence and speciation. Some of these footprints can be utilized to understand the evolutionary history of a species. In this line of research, we try to understand TEs' contribution to evolutionary processes and utilize TEs to reconstruct evolutionary events through the creation of theoretical frameworks and innovative algorithms.
3. Development of Algorithms and Tools for Accurate TE Annotation
3. Development of Algorithms and Tools for Accurate TE Annotation
TEs comprise a substantial portion of plant genomes and other eukaryotic genomes. Annotating TEs accurately is challenging because 1) TEs are highly divergent even between closely related species; 2) most TEs are highly degraded; 3) TEs are found between genes, around genes, and within genes, which is challenging to accurately distinguish from genes. Common practices of "masking" TEs (converting TE contents to Ns) often compromise the integrity of genomic research.
To address these challenges, we are at the forefront of designing cutting-edge computer algorithms and developing scalable software programs for precise TE annotation. We aim to enhance the applicability across diverse species and make meaningful contributions to the field of TE studies. For more details on this work, please check out our Software page or the GitHub repository.
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