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An improved approach for reconstructing consensus repeats from short sequence reads

BACKGROUND: Repeat elements are important components of most eukaryotic genomes. Most existing tools for repeat analysis rely either on high quality reference genomes or existing repeat libraries. Thus, it is still challenging to do repeat analysis for species with highly repetitive or complex genom...

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Autores principales: Chu, Chong, Pei, Jingwen, Wu, Yufeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101065/
https://www.ncbi.nlm.nih.gov/pubmed/30367582
http://dx.doi.org/10.1186/s12864-018-4920-6
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author Chu, Chong
Pei, Jingwen
Wu, Yufeng
author_facet Chu, Chong
Pei, Jingwen
Wu, Yufeng
author_sort Chu, Chong
collection PubMed
description BACKGROUND: Repeat elements are important components of most eukaryotic genomes. Most existing tools for repeat analysis rely either on high quality reference genomes or existing repeat libraries. Thus, it is still challenging to do repeat analysis for species with highly repetitive or complex genomes which often do not have good reference genomes or annotated repeat libraries. Recently we developed a computational method called REPdenovo that constructs consensus repeat sequences directly from short sequence reads, which outperforms an existing tool called RepARK. One major issue with REPdenovo is that it doesn’t perform well for repeats with relatively high divergence rates or low copy numbers. In this paper, we present an improved approach for constructing consensus repeats directly from short reads. Comparing with the original REPdenovo, the improved approach uses more repeat-related k-mers and improves repeat assembly quality using a consensus-based k-mer processing method. RESULTS: We compare the performance of the new method with REPdenovo and RepARK on Human, Arabidopsis thaliana and Drosophila melanogaster short sequencing data. And the new method fully constructs more repeats in Repbase than the original REPdenovo and RepARK, especially for repeats of higher divergence rates and lower copy number. We also apply our new method on Hummingbird data which doesn’t have a known repeat library, and it constructs many repeat elements that can be validated using PacBio long reads. CONCLUSION: We propose an improved method for reconstructing repeat elements directly from short sequence reads. The results show that our new method can assemble more complete repeats than REPdenovo (and also RepARK). Our new approach has been implemented as part of the REPdenovo software package, which is available for download at https://github.com/Reedwarbler/REPdenovo.
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spelling pubmed-61010652018-08-27 An improved approach for reconstructing consensus repeats from short sequence reads Chu, Chong Pei, Jingwen Wu, Yufeng BMC Genomics Research BACKGROUND: Repeat elements are important components of most eukaryotic genomes. Most existing tools for repeat analysis rely either on high quality reference genomes or existing repeat libraries. Thus, it is still challenging to do repeat analysis for species with highly repetitive or complex genomes which often do not have good reference genomes or annotated repeat libraries. Recently we developed a computational method called REPdenovo that constructs consensus repeat sequences directly from short sequence reads, which outperforms an existing tool called RepARK. One major issue with REPdenovo is that it doesn’t perform well for repeats with relatively high divergence rates or low copy numbers. In this paper, we present an improved approach for constructing consensus repeats directly from short reads. Comparing with the original REPdenovo, the improved approach uses more repeat-related k-mers and improves repeat assembly quality using a consensus-based k-mer processing method. RESULTS: We compare the performance of the new method with REPdenovo and RepARK on Human, Arabidopsis thaliana and Drosophila melanogaster short sequencing data. And the new method fully constructs more repeats in Repbase than the original REPdenovo and RepARK, especially for repeats of higher divergence rates and lower copy number. We also apply our new method on Hummingbird data which doesn’t have a known repeat library, and it constructs many repeat elements that can be validated using PacBio long reads. CONCLUSION: We propose an improved method for reconstructing repeat elements directly from short sequence reads. The results show that our new method can assemble more complete repeats than REPdenovo (and also RepARK). Our new approach has been implemented as part of the REPdenovo software package, which is available for download at https://github.com/Reedwarbler/REPdenovo. BioMed Central 2018-08-13 /pmc/articles/PMC6101065/ /pubmed/30367582 http://dx.doi.org/10.1186/s12864-018-4920-6 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Chu, Chong
Pei, Jingwen
Wu, Yufeng
An improved approach for reconstructing consensus repeats from short sequence reads
title An improved approach for reconstructing consensus repeats from short sequence reads
title_full An improved approach for reconstructing consensus repeats from short sequence reads
title_fullStr An improved approach for reconstructing consensus repeats from short sequence reads
title_full_unstemmed An improved approach for reconstructing consensus repeats from short sequence reads
title_short An improved approach for reconstructing consensus repeats from short sequence reads
title_sort improved approach for reconstructing consensus repeats from short sequence reads
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101065/
https://www.ncbi.nlm.nih.gov/pubmed/30367582
http://dx.doi.org/10.1186/s12864-018-4920-6
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