TE-greedy-nester: structure-based detection of LTR retrotransposons and their nesting

Abstract

Motivation Transposable elements (TEs) in eukaryotes often get inserted into one another, forming sequences that become a complex mixture of full-length elements and their fragments. The reconstruction of full-length elements and the order in which they have been inserted is important for genome and transposon evolution studies. However, the accumulation of mutations and genome rearrangements over evolutionary time makes this process error-prone and decreases the efficiency of software aiming to recover all nested full-length TEs. Results We created software that uses a greedy recursive algorithm to mine increasingly fragmented copies of full-length LTR retrotransposons in assembled genomes and other sequence data. The software called TE-greedy-nester takes into account not only sequence similarity but also the structure of elements. This new tool was tested on a set of natural and synthetic sequences and its accuracy was compared to similar software. We found TE-greedy-nester to be superior in a number of parameters, namely computation time and full-length TE recovery in highly nested regions. Availability and implementation http://gitlab.fi.muni.cz/lexa/nested Supplementary information Supplementary data are available at Bioinformatics online.

Rapid Genome Evolution and Adaptation of Thlaspi arvense Mediated by Recurrent RNA-Based and Tandem Gene Duplications

“…Specifically, the Gypsy superfamily accounts for over half the size of the T. arvense genome assembly, and the athila and crm lineages made a great proportion to the proliferation of the Gypsy superfamily ( Figure 2A and Table 2 ). For further study of the evolution of LTR-RTs, nested LTR-RTs and relevant pipelines should be considered ( Jedlicka et al, 2019 ; Lexa et al, 2020 ). Overall, LTR-RT proliferation largely contributes to the enlargement of the T. arvense genome size, which is consistent with a recent report ( Geng et al, 2021 ).…”

The clove (Syzygium aromaticum) genome provides insights into the eugenol biosynthesis pathway

“…TEnester 76 and TEsorter 77 with REXdb 78 were used to predict and annotate transposable elements and their insertion age was calculated as previously reported 79 . In addition, repeats were predicted using Red 80 , MITEs using GRF 81 , helitron using EAHelitron 82 , and tandem repeats using tantan 83 .…”

Automatic curation of LTR retrotransposon libraries from plant genomes through machine learning

“…On the other hand, the complex dynamics of TEs have shown burst of insertions in specific sections of the genome [ 21 ], producing the presence of numerous insertions of transposable elements into other TEs, with the direct consequence of inactivating the activity of the first element. Such insertions are called nested insertions [ 22 – 24 ]. While multiple insertions of large transposable elements can have a profound impact on the structure of the inserted element, insertion of smaller and non-coding elements can go unnoticed by structural TE detection algorithms.…”

“…Within bioinformatics, there are different approaches for detecting nested elements, especially based on their structure such as TE-greedy-nester [ 24 ] and TEnest [ 25 ]. Nevertheless, these software require complex installation processes and have many dependencies such as BLAST [ 26 ], LTR_FINDER [ 27 ], GenomeTools [ 28 ] which results in long run times and possible failures linked to one of the dependencies.…”