Research

1. Characterizing TE's Roles in Response to Stresses

When plants are stressed, TEs tend to be more active. This line of research inquires into TEs' roles during stress. Are they Jokers, exacerbating or exploiting the chaos, or Batmans, working to alleviate the stress? We hypothesize that TEs can contribute to gene regulation in response to stress, but how? Utilizing model plant species like maize and rice, we combine long-read sequencing and experimental approaches to answer these questions. We currently study cold stress, including chilling and freezing stresses.

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. Developing Scalable Algorithms for Accurate TE Annotations

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 (i.e., homology search works poorly); 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 genes' integrity; and 4) Sequence characters of TEs are not precisely defined, resulting in frequent false annotations.

To address these challenges, we are at the forefront of designing cutting-edge computer algorithms and developing scalable software 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 line of work, please visit our Software page or the GitHub repository.