Cargando…

TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches

Transposable Element MOnitoring with LOng-reads (TrEMOLO) is a new software that combines assembly- and mapping-based approaches to robustly detect genetic elements called transposable elements (TEs). Using high- or low-quality genome assemblies, TrEMOLO can detect most TE insertions and deletions a...

Descripción completa

Detalles Bibliográficos
Autores principales: Mohamed, Mourdas, Sabot, François, Varoqui, Marion, Mugat, Bruno, Audouin, Katell, Pélisson, Alain, Fiston-Lavier, Anna-Sophie, Chambeyron, Séverine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10069131/
https://www.ncbi.nlm.nih.gov/pubmed/37013657
http://dx.doi.org/10.1186/s13059-023-02911-2
_version_ 1785018798778089472
author Mohamed, Mourdas
Sabot, François
Varoqui, Marion
Mugat, Bruno
Audouin, Katell
Pélisson, Alain
Fiston-Lavier, Anna-Sophie
Chambeyron, Séverine
author_facet Mohamed, Mourdas
Sabot, François
Varoqui, Marion
Mugat, Bruno
Audouin, Katell
Pélisson, Alain
Fiston-Lavier, Anna-Sophie
Chambeyron, Séverine
author_sort Mohamed, Mourdas
collection PubMed
description Transposable Element MOnitoring with LOng-reads (TrEMOLO) is a new software that combines assembly- and mapping-based approaches to robustly detect genetic elements called transposable elements (TEs). Using high- or low-quality genome assemblies, TrEMOLO can detect most TE insertions and deletions and estimate their allele frequency in populations. Benchmarking with simulated data revealed that TrEMOLO outperforms other state-of-the-art computational tools. TE detection and frequency estimation by TrEMOLO were validated using simulated and experimental datasets. Therefore, TrEMOLO is a comprehensive and suitable tool to accurately study TE dynamics. TrEMOLO is available under GNU GPL3.0 at https://github.com/DrosophilaGenomeEvolution/TrEMOLO. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02911-2.
format Online
Article
Text
id pubmed-10069131
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-100691312023-04-04 TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches Mohamed, Mourdas Sabot, François Varoqui, Marion Mugat, Bruno Audouin, Katell Pélisson, Alain Fiston-Lavier, Anna-Sophie Chambeyron, Séverine Genome Biol Software Transposable Element MOnitoring with LOng-reads (TrEMOLO) is a new software that combines assembly- and mapping-based approaches to robustly detect genetic elements called transposable elements (TEs). Using high- or low-quality genome assemblies, TrEMOLO can detect most TE insertions and deletions and estimate their allele frequency in populations. Benchmarking with simulated data revealed that TrEMOLO outperforms other state-of-the-art computational tools. TE detection and frequency estimation by TrEMOLO were validated using simulated and experimental datasets. Therefore, TrEMOLO is a comprehensive and suitable tool to accurately study TE dynamics. TrEMOLO is available under GNU GPL3.0 at https://github.com/DrosophilaGenomeEvolution/TrEMOLO. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02911-2. BioMed Central 2023-04-03 /pmc/articles/PMC10069131/ /pubmed/37013657 http://dx.doi.org/10.1186/s13059-023-02911-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Mohamed, Mourdas
Sabot, François
Varoqui, Marion
Mugat, Bruno
Audouin, Katell
Pélisson, Alain
Fiston-Lavier, Anna-Sophie
Chambeyron, Séverine
TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
title TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
title_full TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
title_fullStr TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
title_full_unstemmed TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
title_short TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
title_sort tremolo: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10069131/
https://www.ncbi.nlm.nih.gov/pubmed/37013657
http://dx.doi.org/10.1186/s13059-023-02911-2
work_keys_str_mv AT mohamedmourdas tremoloaccuratetransposableelementallelefrequencyestimationusinglongreadsequencingdatacombiningassemblyandmappingbasedapproaches
AT sabotfrancois tremoloaccuratetransposableelementallelefrequencyestimationusinglongreadsequencingdatacombiningassemblyandmappingbasedapproaches
AT varoquimarion tremoloaccuratetransposableelementallelefrequencyestimationusinglongreadsequencingdatacombiningassemblyandmappingbasedapproaches
AT mugatbruno tremoloaccuratetransposableelementallelefrequencyestimationusinglongreadsequencingdatacombiningassemblyandmappingbasedapproaches
AT audouinkatell tremoloaccuratetransposableelementallelefrequencyestimationusinglongreadsequencingdatacombiningassemblyandmappingbasedapproaches
AT pelissonalain tremoloaccuratetransposableelementallelefrequencyestimationusinglongreadsequencingdatacombiningassemblyandmappingbasedapproaches
AT fistonlavierannasophie tremoloaccuratetransposableelementallelefrequencyestimationusinglongreadsequencingdatacombiningassemblyandmappingbasedapproaches
AT chambeyronseverine tremoloaccuratetransposableelementallelefrequencyestimationusinglongreadsequencingdatacombiningassemblyandmappingbasedapproaches