TEtrimmer: a tool to automate the manual curation of transposable elements

Transposable elements (TEs) are repetitive DNA sequences that move within genomes and play important roles in gene regulation and genome evolution. Accurate TE annotation in genomes is crucial for downstream analyses but challenging due to their sequence diversity and frequent fragmentation, including the occurrence of nested copies. We here present TEtrimmer, a tool that automates and replaces key steps of traditional manual curation of TEs. TEtrimmer combines phylogenetic tree analysis with the machine learning method DBSCAN to cluster TE sequences accurately and applies a sliding-window strategy to remove poorly conserved regions of TE-derived multiple sequence alignments. TEtrimmer also provides detailed report plots and features a graphical user interface (GUI) application. Tested on the genomes of six organisms belonging to various kingdoms of eukaryotic life and three simulated genomes, TEtrimmer consistently improved the identification of intact TEs compared to the established tools EDTA and RepeatModeler2.

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Publication Details

Journal
Nature Communications
Published
2025-09-25
DOI
https://doi.org/10.1038/s41467-025-63889-y
Citations
5
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
4.03

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article

TEtrimmer: a tool to automate the manual curation of transposable elements

Stefan Kusch, Ralph Panstruga, Mary C. Wildermuth, Tony Heitkam et al.
5 citations
Nature Communications
Genomics and Phylogenetic Studies
4.03
article

TEtrimmer: a tool to automate the manual curation of transposable elements

Stefan Kusch, Ralph Panstruga, Mary C. Wildermuth, Tony Heitkam, Lisa Fürtauer, Jessica M. Storer, Ludwig Mann, Shujun Ou, Hang Xue, Jiangzhao Qian
article en
5 citations

Abstract

Transposable elements (TEs) are repetitive DNA sequences that move within genomes and play important roles in gene regulation and genome evolution. Accurate TE annotation in genomes is crucial for downstream analyses but challenging due to their sequence diversity and frequent fragmentation, including the occurrence of nested copies. We here present TEtrimmer, a tool that automates and replaces key steps of traditional manual curation of TEs. TEtrimmer combines phylogenetic tree analysis with the machine learning method DBSCAN to cluster TE sequences accurately and applies a sliding-window strategy to remove poorly conserved regions of TE-derived multiple sequence alignments. TEtrimmer also provides detailed report plots and features a graphical user interface (GUI) application. Tested on the genomes of six organisms belonging to various kingdoms of eukaryotic life and three simulated genomes, TEtrimmer consistently improved the identification of intact TEs compared to the established tools EDTA and RepeatModeler2.

Nature CommunicationsVol. 16(1)
University of Connecticut (US), Forschungszentrum Jülich (DE), The Ohio State University (US), RWTH Aachen University (DE), University of California, Berkeley (US)
National Science Foundation, Ohio State University, Deutsche Forschungsgemeinschaft, RWTH Aachen University, Directorate for STEM Education
Openalex Percentile: Top 6%
Genomics and Phylogenetic Studies
4.03
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