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

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 an...

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Detalles Bibliográficos
Autores principales: Lexa, Matej, Jedlicka, Pavel, Vanat, Ivan, Cervenansky, Michal, Kejnovsky, Eduard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755421/
https://www.ncbi.nlm.nih.gov/pubmed/32663247
http://dx.doi.org/10.1093/bioinformatics/btaa632
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author Lexa, Matej
Jedlicka, Pavel
Vanat, Ivan
Cervenansky, Michal
Kejnovsky, Eduard
author_facet Lexa, Matej
Jedlicka, Pavel
Vanat, Ivan
Cervenansky, Michal
Kejnovsky, Eduard
author_sort Lexa, Matej
collection PubMed
description 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 considers 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.
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spelling pubmed-77554212020-12-29 TE-greedy-nester: structure-based detection of LTR retrotransposons and their nesting Lexa, Matej Jedlicka, Pavel Vanat, Ivan Cervenansky, Michal Kejnovsky, Eduard Bioinformatics Original Papers 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 considers 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. Oxford University Press 2020-07-14 /pmc/articles/PMC7755421/ /pubmed/32663247 http://dx.doi.org/10.1093/bioinformatics/btaa632 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Papers
Lexa, Matej
Jedlicka, Pavel
Vanat, Ivan
Cervenansky, Michal
Kejnovsky, Eduard
TE-greedy-nester: structure-based detection of LTR retrotransposons and their nesting
title TE-greedy-nester: structure-based detection of LTR retrotransposons and their nesting
title_full TE-greedy-nester: structure-based detection of LTR retrotransposons and their nesting
title_fullStr TE-greedy-nester: structure-based detection of LTR retrotransposons and their nesting
title_full_unstemmed TE-greedy-nester: structure-based detection of LTR retrotransposons and their nesting
title_short TE-greedy-nester: structure-based detection of LTR retrotransposons and their nesting
title_sort te-greedy-nester: structure-based detection of ltr retrotransposons and their nesting
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755421/
https://www.ncbi.nlm.nih.gov/pubmed/32663247
http://dx.doi.org/10.1093/bioinformatics/btaa632
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