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High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing

RNA sequencing (RNA-seq) enables characterization and quantification of individual transcriptomes as well as detection of patterns of allelic expression and alternative splicing. Current RNA-seq protocols depend on high-throughput short-read sequencing of cDNA. However, as ongoing advances are rapid...

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Autores principales: Cho, Hyunghoon, Davis, Joe, Li, Xin, Smith, Kevin S., Battle, Alexis, Montgomery, Stephen B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4176000/
https://www.ncbi.nlm.nih.gov/pubmed/25251678
http://dx.doi.org/10.1371/journal.pone.0108095
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author Cho, Hyunghoon
Davis, Joe
Li, Xin
Smith, Kevin S.
Battle, Alexis
Montgomery, Stephen B.
author_facet Cho, Hyunghoon
Davis, Joe
Li, Xin
Smith, Kevin S.
Battle, Alexis
Montgomery, Stephen B.
author_sort Cho, Hyunghoon
collection PubMed
description RNA sequencing (RNA-seq) enables characterization and quantification of individual transcriptomes as well as detection of patterns of allelic expression and alternative splicing. Current RNA-seq protocols depend on high-throughput short-read sequencing of cDNA. However, as ongoing advances are rapidly yielding increasing read lengths, a technical hurdle remains in identifying the degree to which differences in read length influence various transcriptome analyses. In this study, we generated two paired-end RNA-seq datasets of differing read lengths (2×75 bp and 2×262 bp) for lymphoblastoid cell line GM12878 and compared the effect of read length on transcriptome analyses, including read-mapping performance, gene and transcript quantification, and detection of allele-specific expression (ASE) and allele-specific alternative splicing (ASAS) patterns. Our results indicate that, while the current long-read protocol is considerably more expensive than short-read sequencing, there are important benefits that can only be achieved with longer read length, including lower mapping bias and reduced ambiguity in assigning reads to genomic elements, such as mRNA transcript. We show that these benefits ultimately lead to improved detection of cis-acting regulatory and splicing variation effects within individuals.
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spelling pubmed-41760002014-10-02 High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing Cho, Hyunghoon Davis, Joe Li, Xin Smith, Kevin S. Battle, Alexis Montgomery, Stephen B. PLoS One Research Article RNA sequencing (RNA-seq) enables characterization and quantification of individual transcriptomes as well as detection of patterns of allelic expression and alternative splicing. Current RNA-seq protocols depend on high-throughput short-read sequencing of cDNA. However, as ongoing advances are rapidly yielding increasing read lengths, a technical hurdle remains in identifying the degree to which differences in read length influence various transcriptome analyses. In this study, we generated two paired-end RNA-seq datasets of differing read lengths (2×75 bp and 2×262 bp) for lymphoblastoid cell line GM12878 and compared the effect of read length on transcriptome analyses, including read-mapping performance, gene and transcript quantification, and detection of allele-specific expression (ASE) and allele-specific alternative splicing (ASAS) patterns. Our results indicate that, while the current long-read protocol is considerably more expensive than short-read sequencing, there are important benefits that can only be achieved with longer read length, including lower mapping bias and reduced ambiguity in assigning reads to genomic elements, such as mRNA transcript. We show that these benefits ultimately lead to improved detection of cis-acting regulatory and splicing variation effects within individuals. Public Library of Science 2014-09-24 /pmc/articles/PMC4176000/ /pubmed/25251678 http://dx.doi.org/10.1371/journal.pone.0108095 Text en © 2014 Cho et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Cho, Hyunghoon
Davis, Joe
Li, Xin
Smith, Kevin S.
Battle, Alexis
Montgomery, Stephen B.
High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing
title High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing
title_full High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing
title_fullStr High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing
title_full_unstemmed High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing
title_short High-Resolution Transcriptome Analysis with Long-Read RNA Sequencing
title_sort high-resolution transcriptome analysis with long-read rna sequencing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4176000/
https://www.ncbi.nlm.nih.gov/pubmed/25251678
http://dx.doi.org/10.1371/journal.pone.0108095
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