panHiTE: A comprehensive and accurate pipeline for TE detection in large-scale population genomes

Transposable elements (TEs) are key drivers of genomic variation and species evolution. Although advances in high-throughput sequencing have enabled population-scale identification of TE insertions, accurate detection across large and complex genomes remains challenging. Existing tools often struggle to efficiently process large genomes, recover low-copy elements, or accurately reconstruct full-length TEs, limiting comprehensive TE analyses. Here, we present panHiTE, a population-scale TE detection framework that introduces several methodological innovations. First, panHiTE employs a dynamically updated global TE library to avoid redundant detection of previously identified elements, improving computational efficiency and enabling application to extremely large genomes, such as the 15-Gb wheat genome. Second, to recover low-copy TEs that are frequently missed in individual genomes, panHiTE realigns candidate elements across population-scale genomes, enabling accurate reconstruction of full-length TEs across accessions. Third, because long terminal repeat retrotransposons constitute a major fraction of plant genomes, panHiTE integrates a deep-learning-based detection algorithm developed in this study, achieving higher sensitivity and precision than the state-of-the-art tool panEDTA in population-scale analyses. In addition, a fault-tolerant redundancy-removal algorithm efficiently groups divergent family members, generating TE libraries with more than 50% fewer sequences while doubling the number of Perfect TEs across 26 maize genomes. These advances enable panHiTE to deliver high-resolution TE annotations and accurately resolve TE-gene positional relationships, thereby facilitating the systematic identification of TE-induced differential expression loci (TIDELs). In 32 Arabidopsis accessions, panHiTE identifies 85 TIDELs associated with diverse biological functions and metabolic pathways. Overall, panHiTE provides a robust and scalable solution for population-scale TE discovery and functional characterization in complex plant genomes.