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Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2
Long-read sequencing technologies have improved significantly since their emergence. Their read lengths, potentially spanning entire transcripts, is advantageous for reconstructing transcriptomes. Existing long-read transcriptome assembly methods are primarily reference-based and to date, there is l...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10202958/ https://www.ncbi.nlm.nih.gov/pubmed/37217540 http://dx.doi.org/10.1038/s41467-023-38553-y |
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author | Nip, Ka Ming Hafezqorani, Saber Gagalova, Kristina K. Chiu, Readman Yang, Chen Warren, René L. Birol, Inanc |
author_facet | Nip, Ka Ming Hafezqorani, Saber Gagalova, Kristina K. Chiu, Readman Yang, Chen Warren, René L. Birol, Inanc |
author_sort | Nip, Ka Ming |
collection | PubMed |
description | Long-read sequencing technologies have improved significantly since their emergence. Their read lengths, potentially spanning entire transcripts, is advantageous for reconstructing transcriptomes. Existing long-read transcriptome assembly methods are primarily reference-based and to date, there is little focus on reference-free transcriptome assembly. We introduce “RNA-Bloom2 [https://github.com/bcgsc/RNA-Bloom]”, a reference-free assembly method for long-read transcriptome sequencing data. Using simulated datasets and spike-in control data, we show that the transcriptome assembly quality of RNA-Bloom2 is competitive to those of reference-based methods. Furthermore, we find that RNA-Bloom2 requires 27.0 to 80.6% of the peak memory and 3.6 to 10.8% of the total wall-clock runtime of a competing reference-free method. Finally, we showcase RNA-Bloom2 in assembling a transcriptome sample of Picea sitchensis (Sitka spruce). Since our method does not rely on a reference, it further sets the groundwork for large-scale comparative transcriptomics where high-quality draft genome assemblies are not readily available. |
format | Online Article Text |
id | pubmed-10202958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102029582023-05-24 Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2 Nip, Ka Ming Hafezqorani, Saber Gagalova, Kristina K. Chiu, Readman Yang, Chen Warren, René L. Birol, Inanc Nat Commun Article Long-read sequencing technologies have improved significantly since their emergence. Their read lengths, potentially spanning entire transcripts, is advantageous for reconstructing transcriptomes. Existing long-read transcriptome assembly methods are primarily reference-based and to date, there is little focus on reference-free transcriptome assembly. We introduce “RNA-Bloom2 [https://github.com/bcgsc/RNA-Bloom]”, a reference-free assembly method for long-read transcriptome sequencing data. Using simulated datasets and spike-in control data, we show that the transcriptome assembly quality of RNA-Bloom2 is competitive to those of reference-based methods. Furthermore, we find that RNA-Bloom2 requires 27.0 to 80.6% of the peak memory and 3.6 to 10.8% of the total wall-clock runtime of a competing reference-free method. Finally, we showcase RNA-Bloom2 in assembling a transcriptome sample of Picea sitchensis (Sitka spruce). Since our method does not rely on a reference, it further sets the groundwork for large-scale comparative transcriptomics where high-quality draft genome assemblies are not readily available. Nature Publishing Group UK 2023-05-22 /pmc/articles/PMC10202958/ /pubmed/37217540 http://dx.doi.org/10.1038/s41467-023-38553-y 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Nip, Ka Ming Hafezqorani, Saber Gagalova, Kristina K. Chiu, Readman Yang, Chen Warren, René L. Birol, Inanc Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2 |
title | Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2 |
title_full | Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2 |
title_fullStr | Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2 |
title_full_unstemmed | Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2 |
title_short | Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2 |
title_sort | reference-free assembly of long-read transcriptome sequencing data with rna-bloom2 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10202958/ https://www.ncbi.nlm.nih.gov/pubmed/37217540 http://dx.doi.org/10.1038/s41467-023-38553-y |
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