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Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads

BACKGROUND: Comprehensive annotation and quantification of transcriptomes are outstanding problems in functional genomics. While high throughput mRNA sequencing (RNA-Seq) has emerged as a powerful tool for addressing these problems, its success is dependent upon the availability and quality of refer...

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Autores principales: Martin, Jeffrey, Bruno, Vincent M, Fang, Zhide, Meng, Xiandong, Blow, Matthew, Zhang, Tao, Sherlock, Gavin, Snyder, Michael, Wang, Zhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3152782/
https://www.ncbi.nlm.nih.gov/pubmed/21106091
http://dx.doi.org/10.1186/1471-2164-11-663
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author Martin, Jeffrey
Bruno, Vincent M
Fang, Zhide
Meng, Xiandong
Blow, Matthew
Zhang, Tao
Sherlock, Gavin
Snyder, Michael
Wang, Zhong
author_facet Martin, Jeffrey
Bruno, Vincent M
Fang, Zhide
Meng, Xiandong
Blow, Matthew
Zhang, Tao
Sherlock, Gavin
Snyder, Michael
Wang, Zhong
author_sort Martin, Jeffrey
collection PubMed
description BACKGROUND: Comprehensive annotation and quantification of transcriptomes are outstanding problems in functional genomics. While high throughput mRNA sequencing (RNA-Seq) has emerged as a powerful tool for addressing these problems, its success is dependent upon the availability and quality of reference genome sequences, thus limiting the organisms to which it can be applied. RESULTS: Here, we describe Rnnotator, an automated software pipeline that generates transcript models by de novo assembly of RNA-Seq data without the need for a reference genome. We have applied the Rnnotator assembly pipeline to two yeast transcriptomes and compared the results to the reference gene catalogs of these organisms. The contigs produced by Rnnotator are highly accurate (95%) and reconstruct full-length genes for the majority of the existing gene models (54.3%). Furthermore, our analyses revealed many novel transcribed regions that are absent from well annotated genomes, suggesting Rnnotator serves as a complementary approach to analysis based on a reference genome for comprehensive transcriptomics. CONCLUSIONS: These results demonstrate that the Rnnotator pipeline is able to reconstruct full-length transcripts in the absence of a complete reference genome.
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spelling pubmed-31527822011-08-10 Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads Martin, Jeffrey Bruno, Vincent M Fang, Zhide Meng, Xiandong Blow, Matthew Zhang, Tao Sherlock, Gavin Snyder, Michael Wang, Zhong BMC Genomics Methodology Article BACKGROUND: Comprehensive annotation and quantification of transcriptomes are outstanding problems in functional genomics. While high throughput mRNA sequencing (RNA-Seq) has emerged as a powerful tool for addressing these problems, its success is dependent upon the availability and quality of reference genome sequences, thus limiting the organisms to which it can be applied. RESULTS: Here, we describe Rnnotator, an automated software pipeline that generates transcript models by de novo assembly of RNA-Seq data without the need for a reference genome. We have applied the Rnnotator assembly pipeline to two yeast transcriptomes and compared the results to the reference gene catalogs of these organisms. The contigs produced by Rnnotator are highly accurate (95%) and reconstruct full-length genes for the majority of the existing gene models (54.3%). Furthermore, our analyses revealed many novel transcribed regions that are absent from well annotated genomes, suggesting Rnnotator serves as a complementary approach to analysis based on a reference genome for comprehensive transcriptomics. CONCLUSIONS: These results demonstrate that the Rnnotator pipeline is able to reconstruct full-length transcripts in the absence of a complete reference genome. BioMed Central 2010-11-24 /pmc/articles/PMC3152782/ /pubmed/21106091 http://dx.doi.org/10.1186/1471-2164-11-663 Text en Copyright ©2010 Martin et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Martin, Jeffrey
Bruno, Vincent M
Fang, Zhide
Meng, Xiandong
Blow, Matthew
Zhang, Tao
Sherlock, Gavin
Snyder, Michael
Wang, Zhong
Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads
title Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads
title_full Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads
title_fullStr Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads
title_full_unstemmed Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads
title_short Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads
title_sort rnnotator: an automated de novo transcriptome assembly pipeline from stranded rna-seq reads
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3152782/
https://www.ncbi.nlm.nih.gov/pubmed/21106091
http://dx.doi.org/10.1186/1471-2164-11-663
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