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DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery

Diversity-generating and mobile genetic elements are key to microbial and viral evolution and can result in evolutionary leaps. State-of-the-art algorithms to detect these elements have limitations. Here, we introduce DIVE, a new reference-free approach to overcome these limitations using informatio...

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Detalles Bibliográficos
Autores principales: Abante, Jordi, Wang, Peter L., Salzman, Julia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589994/
https://www.ncbi.nlm.nih.gov/pubmed/37864197
http://dx.doi.org/10.1186/s13059-023-03038-0
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author Abante, Jordi
Wang, Peter L.
Salzman, Julia
author_facet Abante, Jordi
Wang, Peter L.
Salzman, Julia
author_sort Abante, Jordi
collection PubMed
description Diversity-generating and mobile genetic elements are key to microbial and viral evolution and can result in evolutionary leaps. State-of-the-art algorithms to detect these elements have limitations. Here, we introduce DIVE, a new reference-free approach to overcome these limitations using information contained in sequencing reads alone. We show that DIVE has improved detection power compared to existing reference-based methods using simulations and real data. We use DIVE to rediscover and characterize the activity of known and novel elements and generate new biological hypotheses about the mobilome. Building on DIVE, we develop a reference-free framework capable of de novo discovery of mobile genetic elements. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03038-0.
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spelling pubmed-105899942023-10-22 DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery Abante, Jordi Wang, Peter L. Salzman, Julia Genome Biol Method Diversity-generating and mobile genetic elements are key to microbial and viral evolution and can result in evolutionary leaps. State-of-the-art algorithms to detect these elements have limitations. Here, we introduce DIVE, a new reference-free approach to overcome these limitations using information contained in sequencing reads alone. We show that DIVE has improved detection power compared to existing reference-based methods using simulations and real data. We use DIVE to rediscover and characterize the activity of known and novel elements and generate new biological hypotheses about the mobilome. Building on DIVE, we develop a reference-free framework capable of de novo discovery of mobile genetic elements. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03038-0. BioMed Central 2023-10-20 /pmc/articles/PMC10589994/ /pubmed/37864197 http://dx.doi.org/10.1186/s13059-023-03038-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Method
Abante, Jordi
Wang, Peter L.
Salzman, Julia
DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery
title DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery
title_full DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery
title_fullStr DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery
title_full_unstemmed DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery
title_short DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery
title_sort dive: a reference-free statistical approach to diversity-generating and mobile genetic element discovery
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589994/
https://www.ncbi.nlm.nih.gov/pubmed/37864197
http://dx.doi.org/10.1186/s13059-023-03038-0
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