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BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq

BACKGROUND: The time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high qu...

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Autores principales: Rapazote-Flores, Paulo, Bayer, Micha, Milne, Linda, Mayer, Claus-Dieter, Fuller, John, Guo, Wenbin, Hedley, Pete E., Morris, Jenny, Halpin, Claire, Kam, Jason, McKim, Sarah M., Zwirek, Monika, Casao, M. Cristina, Barakate, Abdellah, Schreiber, Miriam, Stephen, Gordon, Zhang, Runxuan, Brown, John W. S., Waugh, Robbie, Simpson, Craig G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6907147/
https://www.ncbi.nlm.nih.gov/pubmed/31829136
http://dx.doi.org/10.1186/s12864-019-6243-7
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author Rapazote-Flores, Paulo
Bayer, Micha
Milne, Linda
Mayer, Claus-Dieter
Fuller, John
Guo, Wenbin
Hedley, Pete E.
Morris, Jenny
Halpin, Claire
Kam, Jason
McKim, Sarah M.
Zwirek, Monika
Casao, M. Cristina
Barakate, Abdellah
Schreiber, Miriam
Stephen, Gordon
Zhang, Runxuan
Brown, John W. S.
Waugh, Robbie
Simpson, Craig G.
author_facet Rapazote-Flores, Paulo
Bayer, Micha
Milne, Linda
Mayer, Claus-Dieter
Fuller, John
Guo, Wenbin
Hedley, Pete E.
Morris, Jenny
Halpin, Claire
Kam, Jason
McKim, Sarah M.
Zwirek, Monika
Casao, M. Cristina
Barakate, Abdellah
Schreiber, Miriam
Stephen, Gordon
Zhang, Runxuan
Brown, John W. S.
Waugh, Robbie
Simpson, Craig G.
author_sort Rapazote-Flores, Paulo
collection PubMed
description BACKGROUND: The time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high quality, comprehensive reference transcripts dataset (RTD), which are rarely available in plants. RESULTS: A high-quality, non-redundant barley gene RTD and database (Barley Reference Transcripts – BaRTv1.0) has been generated. BaRTv1.0, was constructed from a range of tissues, cultivars and abiotic treatments and transcripts assembled and aligned to the barley cv. Morex reference genome (Mascher et al. Nature; 544: 427–433, 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al. Plant Physiol; 156: 20–28, 2011) determined transcript coverage, and high-resolution RT-PCR validated alternatively spliced (AS) transcripts of 86 genes in five different organs and tissue. These methods were used as benchmarks to select an optimal barley RTD. BaRTv1.0-Quantification of Alternatively Spliced Isoforms (QUASI) was also made to overcome inaccurate quantification due to variation in 5′ and 3′ UTR ends of transcripts. BaRTv1.0-QUASI was used for accurate transcript quantification of RNA-seq data of five barley organs/tissues. This analysis identified 20,972 significant differentially expressed genes, 2791 differentially alternatively spliced genes and 2768 transcripts with differential transcript usage. CONCLUSION: A high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS.
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spelling pubmed-69071472019-12-20 BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq Rapazote-Flores, Paulo Bayer, Micha Milne, Linda Mayer, Claus-Dieter Fuller, John Guo, Wenbin Hedley, Pete E. Morris, Jenny Halpin, Claire Kam, Jason McKim, Sarah M. Zwirek, Monika Casao, M. Cristina Barakate, Abdellah Schreiber, Miriam Stephen, Gordon Zhang, Runxuan Brown, John W. S. Waugh, Robbie Simpson, Craig G. BMC Genomics Research Article BACKGROUND: The time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high quality, comprehensive reference transcripts dataset (RTD), which are rarely available in plants. RESULTS: A high-quality, non-redundant barley gene RTD and database (Barley Reference Transcripts – BaRTv1.0) has been generated. BaRTv1.0, was constructed from a range of tissues, cultivars and abiotic treatments and transcripts assembled and aligned to the barley cv. Morex reference genome (Mascher et al. Nature; 544: 427–433, 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al. Plant Physiol; 156: 20–28, 2011) determined transcript coverage, and high-resolution RT-PCR validated alternatively spliced (AS) transcripts of 86 genes in five different organs and tissue. These methods were used as benchmarks to select an optimal barley RTD. BaRTv1.0-Quantification of Alternatively Spliced Isoforms (QUASI) was also made to overcome inaccurate quantification due to variation in 5′ and 3′ UTR ends of transcripts. BaRTv1.0-QUASI was used for accurate transcript quantification of RNA-seq data of five barley organs/tissues. This analysis identified 20,972 significant differentially expressed genes, 2791 differentially alternatively spliced genes and 2768 transcripts with differential transcript usage. CONCLUSION: A high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS. BioMed Central 2019-12-11 /pmc/articles/PMC6907147/ /pubmed/31829136 http://dx.doi.org/10.1186/s12864-019-6243-7 Text en © The Author(s). 2019 Open AccessThis 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 Article
Rapazote-Flores, Paulo
Bayer, Micha
Milne, Linda
Mayer, Claus-Dieter
Fuller, John
Guo, Wenbin
Hedley, Pete E.
Morris, Jenny
Halpin, Claire
Kam, Jason
McKim, Sarah M.
Zwirek, Monika
Casao, M. Cristina
Barakate, Abdellah
Schreiber, Miriam
Stephen, Gordon
Zhang, Runxuan
Brown, John W. S.
Waugh, Robbie
Simpson, Craig G.
BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq
title BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq
title_full BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq
title_fullStr BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq
title_full_unstemmed BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq
title_short BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq
title_sort bartv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using rna-seq
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6907147/
https://www.ncbi.nlm.nih.gov/pubmed/31829136
http://dx.doi.org/10.1186/s12864-019-6243-7
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