LTR_retriever: A Highly Accurate and Sensitive Program for Identification of Long Terminal Repeat Retrotransposons

Abstract

Long terminal repeat retrotransposons (LTR-RTs) are prevalent in plant genomes. The identification of LTR-RTs is critical for achieving high-quality gene annotation. Based on the well-conserved structure, multiple programs were developed for the de novo identification of LTR-RTs; however, these programs are associated with low specificity and high false discovery rates. Here, we report LTR_retriever, a multithreading-empowered Perl program that identifies LTR-RTs and generates high-quality LTR libraries from genomic sequences. LTR_retriever demonstrated significant improvements by achieving high levels of sensitivity (91%), specificity (97%), accuracy (96%), and precision (90%) in rice (Oryza sativa). LTR_retriever is also compatible with long sequencing reads. With 40k self-corrected PacBio reads equivalent to 4.53 genome coverage in Arabidopsis (Arabidopsis thaliana), the constructed LTR library showed excellent sensitivity and specificity. In addition to canonical LTRRTs with 59-TG.CA-39 termini, LTR_retriever also identifies noncanonical LTR-RTs (non-TGCA), which have been largely ignored in genome-wide studies. We identified seven types of noncanonical LTRs from 42 out of 50 plant genomes. The majority of noncanonical LTRs are Copia elements, with which the LTR is four times shorter than that of other Copia elements, which may be a result of their target specificity. Strikingly, non-TGCA Copia elements are often located in genic regions and preferentially insert nearby or within genes, indicating their impact on the evolution of genes and their potential as mutagenesis tools.

The draft genome of Actinia tenebrosa reveals insights into toxin evolution

“…was performed using LTRharvest (GT 1.5.10;Ellinghaus, Kurtz, & Willhoeft, 2008) and LTR_FINDER v.1.06 (Xu & Wang, 2007), and these results were combined using LTR_retriever commit 9b1d08d (Ou & Jiang, 2018) to identify canonical and noncanonical (i.e., non-TGCA motif) LTR-RTs. MITE and LTR-RT libraries were concatenated, and the genome sequence was masked using RepeatMasker open-4.0.7 (Smit, Hubley, & Green, 2013) with settings "-e ncbi -nolow -no_is -norna."…”

TEsorter: lineage-level classification of transposable elements using conserved protein domains

“…Various tools have been developed for identification and classification of TEs or LTR-RTs, such as 25 RepeatModeler (http://www.repeatmasker.org/RepeatModeler/), REPET (Quesneville, et al, 2005) 26 and LTR_retriever (Ou and Jiang, 2017). To our knowledge, most of them can only classify TEs 27 into the superfamily level, leaving the gap for revealing phylogenetic relationships between TEs, 28 especially the LTR-RT Copia and Gyspy superfamilies.…”

“…Results and Discussion 64To benchmark the classification performance of TEsorter, we selected three non-redundant curated 65 TE libraries from rice(Ou and Jiang, 2017), maize(Schnable, et al, 2009) and fruit fly (from 66 Repbase v20.03,Bao, et al, 2015) and compared with four TE classifiers, including the 67 RepeatClassifier module of RepeatModeler (http://www.repeatmasker.org/RepeatModeler/), the 68 PASTEC module(Hoede, et al, 2014) of REPET, the annotate_TE module of LTR_retriever(Ou 69 and Jiang, 2017) and the online-only LTRclassifier(Monat, et al, 2016). TEsorter with REXdb 70 performed with the highest precision (0.94-1.0) in almost all the TE catalogs…”

LTR_FINDER_parallel: parallelization of LTR_FINDER enabling rapid identification of long terminal repeat retrotransposons

“…Transposable elements (TEs) are the most prevalent components in eukaryotic 21 genomes. Among different TE classes, long terminal repeat (LTR) retrotransposons, including 22 endogenous retroviruses (ERVs), is one of the most repetitive TEs due to their high copy 23 numbers and large element sizes (Ou and Jiang, 2018). LTR retrotransposons are found in 24 almost all eukaryotes including plants, fungi, and animals, but are most abundant in plant 25 genomes (Bennetzen and Wang, 2014).…”