EDTA v2: enabling scalable TE annotation in animal genomes

bioRxiv (Cold Spring Harbor Laboratory) 2026 Preprint Open access

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Authors: Shujun Ou, Tim T. Lu, Hieu Nguyen, K. Gerhardt, Ning 'Faye' Fang, Usman Rashid, Joseph G. Guhlin, Jacques Dainat, Zhigui Bao, Philipp E. Bayer, Yeojung Na, Christopher W. Benson
DOI: 10.64898/2026.07.01.735963
Cited by: 1
References: 29

Abstract

Abstract The Extensive de-novo TE Annotator (EDTA) automates transposable element annotation in plant genomes but lacks direct LINE/SINE detection, limiting its applicability to animal genomes. We present EDTA v2, which integrates LINE and SINE detection, completely rewrites TIR-Learner for deployability and scalability, and accelerates structural detectors by up to two orders of magnitude. Tested in 30 animal genomes from the Vertebrate Genomes Project Phase I, EDTA v2 bridges the non-LTR detection gap that has prevented automated TE annotation in animals.

Fields of Study & Subjects

Chromosomal and Genetic Variations Genomics and Phylogenetic Studies Genomics and Chromatin Dynamics

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
6 July 2026
Document type
Preprint